ARTHROPOD RECOVERY IN POST-MINE RECLAIMED SITES: THE EFFECTS OF
RECLAMATION AGE AND BIOSOLIDS AS A SOIL AMENDMENT ON ARTHROPODS

by

CHANTALLE GERVAN

Bachelor of Natural Resource Science (Honours), Thompson Rivers University, 2018

A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS
FOR THE DEGREE OF
MASTER OF SCIENCE IN ENVIRONMENTAL SCIENCES
Thesis examining committee:

Lauchlan Fraser (PhD), Thesis Supervisor & Professor,
Department of Natural Resource Science, Thompson Rivers University
Wendy Gardner (PhD), Committee Member & Associate Professor,
Department of Natural Resource Sciences, Thompson Rivers University
Jonanthan Van Hamme (PhD), Committee Member & Professor,
Department of Biological Sciences, Thompson Rivers University
Robert Higgins (PhD), Committee Member & Associate Professor,
Department of Biological Sciences, Thompson Rivers University
Karen Hodges (PhD), External Examiner & Professor,
Department of Biology, University of British Columbia Okanagan Campus

January 2023

Thompson Rivers University

© Chantalle Gervan, 2023

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Abstract
Mining is a significant disturbance on natural ecosystems and mining companies are
required to reclaim disturbed lands post mine-closure. This observational study addressed three
research questions based on the foundation of using DNA barcoding of arthropods as a new tool
for assessing reclamation. First, this study evaluated if differences in arthropod assemblage and
biodiversity are visible between sites representative of reclamation ages (‘new,’ ‘old’ and
‘reference’) and soil amendments (‘biosolids,’ ‘no biosolids’ and ‘reference’). Second, this study
assessed species richness in relation to reclamation age and soil amendment. Third, this study
assessed if any taxa can be used as indicators of reclamation age and soil amendments.
Arthropod samples were obtained in 2018 from Teck Resources Highland Valley and New Gold
Inc. New Afton. Arthropods from pitfall traps were processed by extracting DNA and identifying
taxa through DNA metabarcoding. Based on the results, the dissimilarity of arthropod
assemblage between the reclamation age and amendment sites implied another external factor is
a stronger driver. Second, despite treatment correlations with order-level taxa, there was not a
statistically significant relationship of the overall richness between the sites. Third, indicator
species analyses identified several taxa uniquely associated with age and amendment sites. It is
also interesting that there were no invasive taxa representative of the study sites. Using novel
methods (high-throughput DNA metabarcoding), this project contributes to the improvement of
planning and management practices, leading to more effective post-mining ecosystem-recovery
outcomes, as they relate to the sustainable health of ecosystems, which are vital to the continued
growth of BC’s communities and economy.

Keywords: biodiversity; ecosystem reclamation; arthropods; environmental DNA barcoding

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Table of Contents
Abstract ........................................................................................................................................... ii
Acknowledgements ........................................................................................................................ iv
Dedication ....................................................................................................................................... v
Table of Tables .............................................................................................................................. vi
Table of Figures ........................................................................................................................... viii
Chapter 1 Introduction .................................................................................................................... 1
1.1 Soil Amendments .................................................................................................................. 2
1.2 Ecological Succession and chronosequence ......................................................................... 3
1.3 Biodiversity ........................................................................................................................... 5
1.4 Arthropods............................................................................................................................. 5
1.5 DNA metabarcoding ............................................................................................................. 6
1.6 Significance ........................................................................................................................... 6
1.7 Research questions ................................................................................................................ 7
1.8 Literature Cited ..................................................................................................................... 8
Chapter 2 Investigating the Effects of Reclamation Age and Biosolids Amendment on arthropods
Using DNA Metabarcoding .......................................................................................................... 11
2.1 Introduction ......................................................................................................................... 11
2.2 Methods ............................................................................................................................... 16
2.3 Results ................................................................................................................................. 28
2.4 Discussion ........................................................................................................................... 48
2.5 References ........................................................................................................................... 60
Chapter 3 Research Conclusions .................................................................................................. 70
3.1 Research Synthesis .............................................................................................................. 70
3.2 Limitations .......................................................................................................................... 70
3.3 Management Implications ................................................................................................... 72
3.4 Future Research ................................................................................................................... 73
3.5 References ........................................................................................................................... 74
Appendix A OTUs used in statistical analyses ........................................................................... A.1
Appendix B GPS coordinates of sample sites .............................................................................. B.1
Appendix C Complete ‘Indicspecies’ analysis tables .................................................................. C.1

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Acknowledgements
First, I would like to thank my supervisor, Dr. Lauchlan Fraser for his support and
guidance over the years; Dr. Jon Van Hamme for his extraordinary direction and knowledge
through the DNA metabarcoding process; Dr. Wendy Gardner for her editorial support, as well
as mentor support through TA and workshop experiences; Dr. Rob Higgins for his arthropod
knowledge and going out of his way, by shipping textbooks to Prince Rupert, to ensure I had the
required materials.
Second, I would like to recognize the members of the Fraser Lab and TRUgen Lab who
helped and enriched my time as a graduate student. Specifically, I am so appreciative of the
large crew that contributed to fieldwork: Colton Stephens, Mathew Coghill, Jordann Foster,
Stephanie Jensen, Solenn Vogel, and Piotr Dzumek. In the lab, Eric Bottos, Jordann Foster,
Ashley Fischer, and Breanne McAmmond answered countless questions and helped me through
the DNA extractions and PCR processes, and always made sure the lab was a fun place to be. Dr.
Jay Prakash Singh provided unwavering advice through statistical analyses in RStudio.
Third, I would like to express my profound gratitude to my family and friends for
providing moral support and occasionally much-needed distractions. Specifically, I would like to
acknowledge my mom, Heather Gervan, for her unconditional support, as well as my fiancé,
Mike Neigel, for his continuous encouragement (and proofreading skills).
Fourth, thank you to Jaimie Dickson (Teck Resources Highland Valley Copper) and Luke
Holdstock (New Gold Inc. New Afton) for coordinating site visits to collect samples during the
field season.
Last, this research was possible through the funding provided by a Natural Sciences and
Engineering Research Council of Canada Industrial Research Chair to L Fraser, in partnership
with the Greater Vancouver Sewerage and Drainage District, New Afton Mine, Highland Valley
Copper Mine, Genome BC, Geoscience BC, Arrow Transport, Real Estate Foundation of BC,
BC Cattlemen’s Association and Trans Mountain Corp. Additionally several scholarships made
this study possible: Geoscience BC Scholarship, Dr. Sherman Jen Graduate Award, Trans
Mountain Environmental Scholarship, and the Jake McDonald Memorial Scholarship.

v

Dedication
In memory of my father, whose many weekends spent outdoors with me encouraged my love of
nature and inspired me to pursue my interest in environmental science.

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Table of Tables
Table 1.1 Upper limits of substances (µg/g dry weight) allowable in class biosolids growing
medium and class B biosolids (OMRR, 2019). .............................................................................. 3
Table 2.1 Teck Resources Highland Valley Copper and New Gold Inc. New Afton site
descriptions outlining material reclaimed, reclamation age category, biosolids application, and
subsequent year seeded, for 2018 sampled sites. .......................................................................... 19
Table 2.2 PCR primer name and sequence targeting the 402 base-pair region of the
mitochondrial cytochrome c oxidase subunit. .............................................................................. 26
Table 2.3 Permutational analysis of variance calculated using Jaccard distance (adonis)
addressing reclamation age and amendment, and reference site. Significant values are listed in
bold font. R2 values were considered significant if the p-values were below 0.05. No sites were
amended with Biosolids at New Afton (New Gold Inc.). ............................................................. 33
Table 2.4 Alpha diversity defined by the number of operational taxonomic units assigned to the
taxonomic group, between sites with different reclamation age sites (‘new,’ ‘old,’ and
‘reference’) at Highland Valley Copper (Teck Resources), and New Afton (New Gold Inc.).
Significance is based on Kruskal-Wallis test. Bold values represent significant p-values. .......... 38
Table 2.5 Dunn test comparing alpha diversity defined by the number of operational taxonomic
units assigned to the taxonomic group, between sites with different reclamation age sites (‘new,’
‘old,’ and ‘reference’) at Highland Valley Copper (Teck Resources), and New Afton (New Gold
Inc.). Bold values represent significant p-values. ......................................................................... 39
Table 2.6 Alpha diversity defined by the number of operational taxonomic units assigned to the
taxonomic group, between sites with different reclamation amendment treatments (‘biosolids,’
‘no biosolids,’ and ‘reference’) at Highland Valley Copper (Teck Resources), and New Afton
(New Gold Inc.). Significance is based on Kruskal-Wallis test. Bold values represent significant
p-values. No sites were amended with Biosolids at New Afton (New Gold Inc.). ...................... 41
Table 2.7 Dunn’s test comparing alpha diversity defined by the number of operational taxonomic
units assigned to the taxonomic group, between sites with different reclamation amendment
treatments (‘biosolids,’ ‘no biosolids,’ and ‘reference’) at Highland Valley Copper (Teck
Resources), and New Afton (New Gold Inc.). Bold values represent significant p-values. No sites
were amended with Biosolids at New Afton (New Gold Inc.). .................................................... 42
Table 2.8. Indicspecies analysis outlining the top operational units (OTU) associated with
different reclamation ages (‘new,’ ‘old,’ ‘reference’) of the 2018 sample sites at the Highland
Valley Copper (Teck Resources) and New Afton (New Gold Inc.) mines, where and ‘p’ is the
probability of finding the obtained results given that the null hypothesis is true, and ‘indicator
stat’ is an indicator value that ranges from 0 to1. ......................................................................... 44

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Table 2.9. Indicspecies analysis outlining the top operational units (OTU) associated with
different reclamation age (‘new,’ ‘old,’ ‘reference’) of the 2018 sample sites at the Highland
Valley Copper (Teck Resources) mine, where and ‘p’ is the probability of finding the obtained
results given that the null hypothesis is true, and ‘indicator stat’ is an indicator value that ranges
from 0 to1. ..................................................................................................................................... 45
Table 2.10. Indicspecies analysis outlining the top operational units (OTU) associated with
different reclamation age (‘new,’ ‘old,’ ‘reference’) of the 2018 sample sites at the New Afton
(New Gold Inc.) mine, where and ‘p’ is the probability of finding the obtained results given that
the null hypothesis is true, and ‘indicator stat’ is an indicator value that ranges from 0 to1........ 46
Table 2.11. Indicspecies analysis outlining the top operational units (OTU) associated with
different reclamation amendments (‘biosolids,’ ‘no biosolids,’ ‘reference) of the 2018 sample
sites at the Highland Valley Copper (Teck Resources) and New Afton (New Gold Inc.) mines,
where and ‘p’ is the probability of finding the obtained results given that the null hypothesis is
true, and ‘indicator stat’ is an indicator value that ranges from 0 to1. No sites were amended with
Biosolids at New Afton (New Gold Inc.) ..................................................................................... 46
Table 2.12. Indicspecies analysis outlining the top operational units (OTU) associated with
different reclamation amendment (‘biosolids,’ ‘no biosolids,’ ‘reference’) of the 2018 sample
sites at the Highland Valley Copper (Teck Resources) mine, where and ‘p’ is the probability of
finding the obtained results given that the null hypothesis is true, and ‘indicator stat’ is an
indicator value that ranges from 0 to1. ......................................................................................... 47

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Table of Figures
Figure 2.1. Location of mines sampled in July and August 2018 for arthropods in BC. Map
created in QGIS using Statistics Canada boundary file projected using NAD83/BC Albers
(Statistics Canada, 2021). ............................................................................................................. 17
Figure 2.2. Map of Teck Resources Highland Valley Copper sites sampled for arthropods
(Treatment Sites (TS) 1-12) in August 2018 created in QGIS using ESRI Satellite base map and
projected using NAD83/BC Albers) (ESRI, 2017)....................................................................... 20
Figure 2.3. Map of Teck Resources Highland Valley Copper sites sampled for arthropods in
August 2018 (Treatment site (TS) 13) created in QGIS using ESRI Satellite base map and
projected using NAD83/BC Albers (ESRI, 2017). ....................................................................... 20
Figure 2.4. Map of references sites near Teck Resources Highland Valley Copper sampled for
arthropods in August 2018 (Reference Sites (RS) 1-2) created in QGIS using ESRI Satellite base
map and projected using NAD83/BC Albers (ESRI, 2017). ........................................................ 21
Figure 2.5. Map of New Gold Inc. New Afton July 2018 sampled for arthropods in July 2018
(Treatment Sites (TS) 14-15)) created in QGIS using ESRI Satellite base map and projected
using NAD83/BC Albers (ESRI, 2017). ....................................................................................... 21
Figure 2.6 Map of reference sites near New Gold Inc. New Afton sampled for arthropods in July
2018 (Reference Sites (RS) 3-4) created in QGIS using ESRI Satellite base map and projected
using NAD83/BC Albers (ESRI, 2017). ....................................................................................... 22
Figure 2.7. Malaise trap set up to capture flying arthropods. Photo taken by Lauchlan Fraser. .. 22
Figure 2.8 2018 Pitfall trap layout that was used to collect epigeal arthropods at Highland Valley
Copper. Photo taken by Chantalle Gervan. ................................................................................... 23
Figure 2.9. Sampling of epigeal arthropods using a pitfall trap consisting of A) a 450 g container
placed flush with the ground , and B) a plastic plate over the top to reduce ethanol evaporation.
The pictured plastic plates were used instead of wooden boards in 2017. Photos taken by
Chantalle Gervan. ......................................................................................................................... 24
Figure 2.10 Collected arthropods being prepared for sequencing: A) Sorting specimens,
previously stored in ethanol, to be homogenized in liquid nitrogen B) Samples in a hot water
bath during DNA extraction process using Mag Bind® Blood and Tissue Kit (Omega Bio-tek,
Inc., Norcross, GA) according to manufacturer’s instructions. Photos taken by Chantalle Gervan.
....................................................................................................................................................... 25
Figure 2.11. PCoA diagram created using Jaccard distance, illustrating arthropod assemblages of
different reclamation ages (age, old) and reference collected in 2018 from sample sites at the
Highland Valley Copper (Teck Resources) and New Afton (New Gold Inc.) mines................... 30

ix
Figure 2.12 PCoA diagram created using Jaccard distance, illustrating arthropod assemblages in
sites amended with(out) biosolid collected at sample sites at the Highland Valley Copper (Teck
Resources) and New Afton (New Gold Inc.) mines in 2018. No sites were amended with
Biosolids at New Afton (New Gold Inc.). .................................................................................... 31
Figure 2.13. PCoA diagram created using Jaccard distance, illustrating arthropod assemblages in
sites with different reclaimed materials (waste rock, tailings) at 2018 sample sites at the
Highland Valley Copper (Teck Resources) and New Afton (New Gold Inc.) mines................... 32
Figure 2.14. Analysis of similarity, testing reclamation age, calculated using Jaccard distance.
Variation within groups is calculated by how much the samples differ from the group mean.
Comparatively, variation between groups is calculated by how much the samples differ from the
overall mean. In these figures, the horizontal line in the box illustrates the median, the top and
bottom of the box illustrate the 25th and 75th percentile, respectively, and the whiskers extend to
the furthest data points. The width of the boxes represents the sample size within that treatment.
....................................................................................................................................................... 34
Figure 2.15 Analysis of similarity, testing reclamation amendment, calculated using Jaccard
distance. Variation within groups is calculated by how much the samples differ from the group
mean. Comparatively, variation between groups is calculated by how much the samples differ
from the overall mean. In these figures, the horizontal line in the box illustrates the median, the
top and bottom of the box illustrate the 25th and 75th percentile, respectively, and the whiskers
extend to the furthest data points. The width of the boxes represents the sample size within that
treatment. No sites were amended with Biosolids at New Afton (New Gold Inc.). ..................... 35
Figure 2.16 PCoA diagram based on the number of taxa characterizing each order, using BrayCurtis percentage to calculate distance, illustrating arthropod assemblages in sites with different
reclamation ages (new, old) at 2018 sample sites from Highland Valley Copper (Teck Resources)
and New Afton (New Gold Inc.) mine.......................................................................................... 36
Figure 2.17 PCoA diagram based on the number of taxa characterizing each order, using BrayCurtis percentage to calculate distance, illustrating arthropod assemblages in sites amended
with(out) biosolids at 2018 sample sites from Highland Valley Copper (Teck Resources) and
New Afton (New Gold Inc.) mines. No sites were amended with Biosolids at New Afton (New
Gold Inc.). ..................................................................................................................................... 37
Figure 2.18 Bar plot with standard error illustrating the mean distribution of Diptera,
Entomobryomorpha, and Psocodea richness defined by the number of operational taxonomic
units assigned to the order, between sites with different reclamation ages (‘new,’ ‘old,’ and
‘reference’) at Highland Valley Copper (Teck Resources), and New Afton (New Gold Inc.). ... 40
Figure 2.19 Bar plots with standard error illustrating the distribution of mean
Entomobryomorpha, Formicidae, and Thysanoptera richness defined by the number of
operational taxonomic units assigned to the order, between sites amended with different soil

x
amendment (‘biosolids’, ‘no biosolids’, and ‘reference) at Highland Valley Copper (Teck
Resources), and New Afton (New Gold Inc.). No sites were amended with Biosolids at New
Afton (New Gold Inc.). ................................................................................................................. 43

1

Chapter 1 Introduction
Anthropogenically influenced ventures such as industry and urban development are in
place to satisfy societal and economic demands. However, these activities alter natural habitats
and ecosystems. Habitat alteration is the suspected leading cause of global extinction (Barnosky
et al., 2011; Cardoso et al., 2020). Increasing extinction rates contribute to losses in species
abundance and biomass, phylogenetic diversity, functional diversity, ecological networks, as
well as differences in space and time (e.g., phenology and distribution) (Cardoso et al., 2020).
Reclamation and restoration of altered habitats could reduce impacts of ecological consequences
from industry and urban development.
Mining, a natural resource industry, is the act of extracting mineral resources from the
planet. These extracted resources are used in the making of the technological items used in our
everyday lives and have significant economic benefits. For example, in 2017, mining in BC was
responsible for generating $11.7 billion in gross revenue and creating over 10,000 jobs for
British Columbians (Mining Association of BC, 2019). The mining industry employs more
Indigenous peoples proportionally than any other private sector in Canada (Mining Association
of Canada, 2019a), which demonstrates responsible industry practice involving stakeholders and
landowners. Mining activity significantly alters the landscape and native ecosystems through
processes such as heavy metal contamination, acid rock drainage, erosion, sedimentation,
hydrology modification, habitat loss, and rare species loss (Canadian Mining Innovation Council,
2013).
Mineral mining involves rock being removed from the ground and stored in stockpiles as
waste rock or milled to separate the desired mineral from rock as ore. Waste rock is can vary in
size from boulder size to gravel. Comparatively, tailings are typically similar to sand in size.
Both of these products are uneconomic waste (waste rock and tailings, respectively) that need to
undergo reclamation. To that end, the Canadian mining industry must adhere to federal,
provincial, and territorial acts and regulations regarding reclamation (Mining Association of
Canada, 2019b). Of note, it is mandatory that planning for mine closure takes place before
mining companies begin production (Mining Association of Canada, 2019c). Mine closure
includes ecosystem reclamation, returning the altered lands to a functioning, self-sustaining
ecosystem. Reclamation in BC addresses terrestrial areas, water bodies, and cultural resources
(Government of British Columbia, 2019). Natural ecological succession, the process of

2
ecosystem change over time, occurs without human intervention; however, in the context of
mine closure, the time scales may be too long to be acceptable for the public, industry, or
Indigenous groups; therefore, active reclamation practices are required.
Reclamation and restoration are commonly confused. Reclamation is the return of a
functioning and self-sustaining ecosystem. In contrast, restoration is to return the disturbed land
to its initial state (e.g., pre-mining). Post-mining restoration can be difficult, if not impossible, to
accomplish as a result of altered habitat, hydrology, and potential for metal contamination (Lima
et al., 2015). In British Columbia, planning towards post-mining end-land use objectives is
required. The identified end land use objectives can then inform reclamation planning and
practices. End Land Use Plans can enhance a community-based approach to reclamation.
Specifically, End Land Use Plans can incorporate input from local Indigenous peoples in terms
of reclamation goals, as well as establish possible post-closure land uses that are feasible and
important to local communities (Melaschenko et al., 2018).
1.1 Soil Amendments
During the mining process, topsoil is removed, reducing the amount of organic matter on
site (Larney and Angers, 2012). Organic matter loss negatively alters soil productivity via
physical, chemical, and biological processes, thus generating a need for soil amendments during
reclamation (Larney and Angers, 2012). Tailings pose reclamation challenges given their lack of
organic materials, their physical structure, the presence of toxic metals, and their tendency to be
nutrient poor (Hossner and Hons, 1992). Organic amendments, such as biosolids, woodchips,
compost, and manure, may address these limitations by adding organic matter vital to soil
productivity (Larney and Angers, 2012). Organic amendments may also provide nutrients and
structure that improve physical, chemical, and biological soil characteristics (Larney and Angers,
2012).
Biosolids (treated municipal wastewater solids) as a soil amendment have multiple
positive effects during mine reclamation because they are made up, largely, of organic matter (up
to 50%) and are high in nutrients (Lu et al., 2012). As a result, biosolids promote soil
stabilization, porosity, drainage, water and cation exchange, aeration, and support diverse
communities of microbes and soil fauna (Lu et al., 2012; Larney and Angers, 2012). The
ultimate effect of the amendment will depend on the individual site and amendment
characteristics (Larney and Angers, 2012).

3
British Columbia regulates biosolids under the Organic Matter Recycling Regulations
(OMRR). Specifically, biosolids are classified under either class A biosolids, biosolids growing
medium, and class B biosolids, as determined by the upper limit of elements within the biosolids
(Table 1.1). The upper limits of class A biosolids are not included in the below table, as they are
calculated under the Canadian Food Inspection Agency based on predicted accumulation over 45
years (Government of Canada, 2022).
Table 1.1 Upper limits of substances (µg/g dry weight) allowable in class biosolids growing
medium and class B biosolids (OMRR, 2019).
Substance
(µg/g dry weight)
Arsenic
Cadmium
Chromium
Cobalt
Copper
Lead
Mercury
Molybdenum
Nickel
Selenium
Zinc

Biosolids
growing medium
13
1.5
100
34
150
150
0.8
5
62
2
150

Class B biosolids/
Class B Compost
75
20
1 060
150
2 200
500
15
20
180
14
1 850

1.2 Ecological Succession and chronosequence
In the context of mine reclamation, ecological succession, as first modelled by Clements
(1916), is important to understand as post-mining disturbed sites move towards a functioning
ecosystem. Clements’ model described ecological succession as change in a community where
an inhabiting group of organisms modifies an area, leaving it more hospitable so that the group
of organisms is replaced by another group of organisms. More recently, Connell and Slatyer
(1977) developed the tolerance and inhibition succession models. The tolerance model is based
on success of later species, regardless of the presence of earlier species before them. In the
tolerance model, plants species are able to establish and mature at lower levels of nutrients. The
inhibition model is based on the theory that later species and earlier species do not co-exist, with
the later species replacing the early species following local disturbance.

4
No matter what the model, two types of succession can be broadly defined: primary and
secondary. Primary succession occurs in areas where vegetation has not occurred, such as
deglaciated areas (Wali, 1999). Secondary succession occurs in areas that have previously been
colonized by vegetation but have been disturbed by events such as forest fires, heavy grazing, or
logging (Wali, 1999).
As disturbed areas undergo vegetative succession wildlife habitats, plant-animal, and
plant-animal-microbe interactions will develop (Wali, 1999; McKelvey, 2015). An interesting
experiment assessing arthropod recovery in a given area is Simberloff and Wilson’s study (1969)
which monitored the recovery of arthropods on mangrove islands after defaunating the islands.
Simberloff and Wilson (1969) found that within a year, arthropod assemblages and diversity on
treated islands were comparable to arthropod assemblages and diversity on islands that were not
defaunated. It is also interesting to note that strong flying arthropods and non/weak flying
arthropods were initial immigrants on the islands and that ants were one of the last species to
recover on the defaunated islands (Simberloff and Wilson, 1969). Moreover, oscillations in the
number of arthropod species present on the islands indicated a dynamic equilibrium (Simberloff
and Wilson, 1969). Understanding of arthropod recovery overtime in disturbed areas can further
our knowledge of reclaiming post-mined ecosystems.
The long-term trajectory of reclaimed areas can be studied using a chronosequence. A
chronosequence is an approach to a study where multiple sites are sampled to assess the effects
of treatment over time, as opposed to sampling the same sites over time (which could take
decades). The duration of time since a site has been reclaimed affects soil development (Adeli et
al., 2013). Chronosequencing exemplifies varying degrees of ecological succession consisting of
varying ecological condition factors (Walker et al, 2010). Abiotic and biotic conditions can
impact animal habitats, including arthropods. For example, Li et al., (2018) studied arthropod
response in a reclaimed poplar (Populus deltoides) plantation over a chronosequence. They
found that soil arthropod assemblages varied along the chronosequence. In order to achieve a
functioning ecosystem, the ecosystem must be comprised of biotic and abiotic components that
interact as a system and operate as a whole through the transfer of energy and cycle of nutrients.
An important measure of the biotic component is biodiversity, particularly functional
biodiversity.

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1.3 Biodiversity
Biodiversity is often described in terms of genetic diversity and relationships in a given
area (Gaston and Spicer, 2004). Furthermore, ecological factors such as soil microbes,
vegetation, and animal diversity can influence each other (Bennett, 2010). These relationships
can have both top-down and bottom-up impacts to a reclaimed ecosystem (Bennett, 2010). It is
critical to understand what species are present and how they relate to specific ecosystem
functions (Prach and Tolvanen, 2016). For example, despite an area of high biodiversity being
perceived as positive for ecosystem functioning, it may be made up of specialist, generalist,
and/or invasive species (Prach and Tolvanen 2016). Therefore, measuring biodiversity indicators
can assist in manageable ecosystem factors (Prach and Tolvanen 2016). Alpha diversity is a
common measure of biodiversity; it is the number of unique taxa in a given area. Alpha diversity,
or species richness, is an accessible biodiversity measurement, informs of taxa in an area and can
be monitored over time or compared to another area.
1.4 Arthropods
Arthropods make up a significant portion of species biodiversity, are a key factor in
ecological succession, and provide important ecosystem services (McGeoch et al., 2011)
including soil formation in reclaimed areas, nutrient turnover, decomposition, litter breakup,
herbivory, pollination, acting as dispersal agents, and serving as food resources for wildlife
(Majer, 2002).
Alternatively, arthropods can be perceived to play negative ecological roles, such as
being vectors for disease or as being a nuisance for agriculture and forestry. Many arthropods are
herbivorous, and therefore, they may contribute to plant species composition by changing
competitive dynamics within the plant community (Yu et al., 2012; Barnett and Facey, 2016). On
the other hand, arthropod composition is affected by plant composition through a bottom-up
effect whereby vegetation structure and species impact arthropod habitat (Barnett and Facey,
2016). Generally, a high level of arthropod diversity is optimal so that a complete range of
ecosystem functions is achieved (Majer et al., 2002).
Arthropods are sensitive to environmental change (Buchori et al., 2018), and changes in
their geographic distribution, fecundity and diversity are good indicators of change (Samways et
al., 2010). As such, arthropod diversity metrics can be used to draw comparisons between
different landscapes to evaluate, for example, land reclamation efforts (Gerlach et al., 2013).

6
However, because of the complexities of identifying arthropods taxonomically, they have not
historically been used to monitor or assess reclamation strategies. Recent progress in DNA
metabarcoding, a molecular species identification technique, has helped overcome challenges in
the taxonomic identification of arthropod (Fernandes et al., 2018; Beng et al., 2016). In this
study, I will assess arthropod assemblage response to mine reclamation using DNA
metabarcoding.
1.5 DNA metabarcoding
High-throughput DNA metabarcoding is an identification tool that relies on amplification
and sequencing of DNA barcodes (short nucleotide sequences) from whole communities rather
than relying on identification of individual specimens from a community. Briefly, DNA is
extracted from a sample containing many homogenized arthropods collected in a trap prior to
using polymerase chain reaction (PCR) to amplify a barcode region that can be used for
taxonomic purposes, such as the mitochondrial cytochrome c oxidase subunit 1 gene (CO1) (Ji et
al., 2013). Next, clustering algorithms can be used to group sequences into Operational
Taxonomic Units (OTUs) prior to taxonomy assignment against public sequence data
collections, such as the Barcode of Life Database (BOLD) (Palmer et al., 2018;
https://www.boldsystems.org/). BOLD is a curated database that captures plant, fungal, bacterial,
and animal biodiversity and includes phylogenetically relevant barcode sequences alongside
traditional taxonomic information. In this study, arthropods captured in pitfall at 19 sites were
characterized using COI metabarcoding. Additionally, 16 individual samples were submitted for
curation and inclusion in the BOLD database in an effort to improve taxonomy assignment for
samples collected at Highland Valley Copper and New Afton. Specifically, this study will use
DNA metabarcoding as a foundation to assess arthropod response to reclamation age and
biosolids as a soil amendment in two mines in the interior of British Columbia.
1.6 Significance
The study outlined above will work towards reducing knowledge gaps regarding postmining reclamation outcomes by examining arthropod assemblage composition as an indicator of
reclamation trajectory. Additionally, this work will evaluate high throughput DNA
metabarcoding of arthropod communities as a tool for planning, managing, and improving post-

7
mining ecosystem reclamation, an activity that is vital to the sustainability of BC’s natural
ecosystems, communities, and economy.
Researchers have pointed out the lack of information addressing the outcomes of mine
reclamation (Buchori et al., 2018; Fernandes et al., 2019), especially regarding arthropod
recovery. More research is needed to fully understand mine reclamation success towards recreating a functioning ecosystem.
1.7 Research questions
This study will address three research questions, based on the foundation of using DNA
metabarcoding of arthropods as a new tool for assessing mine reclamation. Firstly, this study will
assess whether we can identify changes in arthropod assemblages from sites with different
reclamation ages (‘new,’ (10 years and newer) ‘old,’ (14 years and older) and reference) and soil
amendment (‘biosolids,’ ‘no biosolids,’ and ‘reference). Secondly, this study will assess the
effects of reclamation age and soil amendment on arthropod alpha diversity. Thirdly, this study
will examine if any arthropod taxa are indicators of reclamation age or soil amendment. This
thesis is made up of three chapters (including this chapter). Chapter two includes data analyses
that will answer the above research questions. Chapter three addresses management implications
and recommendations for mine reclamation, such as environmental monitoring, based on the
findings.

8
1.8 Literature Cited
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chronosequence effects on restoration quality of reclaimed coal mine soils in Mississippi
agroecosystems. Soil Science, 178(7)335-343.
Barnett, K., Facey, S. 2016. Grasslands, Invertebrates, and Precipitation: A review of the effects
of climate change. Frontiers in Plant Science. DOI.org/10.3389/fpls.2016.01196
Barnosky, A.D., Matzke, N., Tomiya, S., Wogan, G.O.U., Swartz, B., Quental, T.B., Marshall,
C., McGuire, J.L., Lindsey, E.L., Maguire, K.C., Mersey, B., Ferrer, E.A. 2011. Has the
Earth’s sixth mass extinction already arrived? Nature, 471, 51–57. DOI:
10.1038/nature09678.
Beng, K., Tomlinson, K., Shen, X., Surget-Groba, Y., Hughes, A., Corlett, R., Ferry, S. 2016.
The utility of DNA metabarcoding for studying the response of arthropod diversity and
composition to land-use change in the tropics. Scientific Reports, 6: 24965.
DOI:10.1038/srep24965.
Bennett, A. 2010. The role of soil community biodiversity in insect biodiversity. Insect
Conservation and Diversity, 3; 157–171. DOI: 10.1111/j.1752-4598.2010.00086.x
Buchori, D., Rizali, A., Rahayu, G., Mansur, I. 2018. Insect diversity in post-mining areas:
Investigating their potential role as bioindicator of reclamation success. Biodiversitas,
19:1696-1702. DOI: 10.0.13057/biodiv/d190515.
Canadian Mining Innovation Council. 2013. Environmental analysis of the mining industry in
Canada. Available from: http://www.cmic-ccim.org/wpontent/uploads/2013/07/HatchScopingReport.pdf
Cardoso, P., Bartonb, P., Birkhoferc, K., Chichorroa, F., Deacond, C., Fartmanne, T.,
Fukushimaa, C., Gaigherd, R., Habelf, J., Hallmanng, C., Hillh, M., Hochkirchi, A.,
Kwakk, M., Mammolaa, S., Noriegam, J., Orfingern, A., Pedrazap, F., Pryked, J.,
Roqueq, F., Setteles, J., Simaikav, J., Storkx, N., Suhlingy , F., Vorsterd, C., Samways,
M. Scientists' warning to humanity on insect extinctions. 2020. Biological Conservation,
242, 1-12. DOI: 10.1016/j.biocon.2020.108426.
Clements, F. 1916. Plant succession: analysis of the development of vegetation. Carnegie
Institution of Washington Publication Sciences, 242: 1-512.
Connell, J., Slatyer, R. 1977. Mechanisms of succession in natural communities and their role in
community stability and organization. The American Naturalist, 111(982):1119-1144.
Fernandes, K., Van der Heyde, M., Bunce, M., Dixon, K., Harris, R., Wardell-Johnson, G.,
Nevill, P. 2018. DNA metabarcoding—a new approach to fauna monitoring in mine site
restoration. Restoration Ecology, 26(6):1098-1107. DOI: 10.1111/rec.12868.
Fernandes, K., Van der Heyde, M., Coghlan, M., Wardell-Johnson, G., Bunce, M., Harris, R.,
Nevill, P. 2019. Invertebrate DNA metabarcoding reveals changes in communities across
mine site restoration chronosequences. Restoration Ecology, 27(5):1177-1186. DOI:
10.1111/rec.12976.

9
Gaston, K., Spicer, J. 2004. Biodiversity: an introduction, 2nd edn. Blackwell, Oxford.
Gerlach, J., Samways, M., Pryke, J. 2013. Terrestrial invertebrates as bioindicators: an overview
of available taxonomic groups. Insect Conservation, 17:831-850. DOI 10.1007/s10841013-9565-9.
Government of British Columbia. [Internet]. 2019. Reclamation and closure. [cited May 2019].
Available from: https://libguides.tru.ca/c.php?g=194007&p=1277162.
Government of Canada. [Internet]. 2022. T-4-93 – Safety standards for fertilizers and
supplements. [cited March 2022]. Available from: https://inspection.canada.ca/planthealth/fertilizers/trade-memoranda/t-4-93/eng/1305611387327/1305611547479.
Hossner, L., Hons, F. 1992. Reclamation of mine tailings. Soil Restoration. 17:311-350.
Ji, Y., Ashton, L., Pedley, S., Edwards, D., Tang, Y., Nakamura, A., Kitching, R., Dolman, P.,
Woodcock, P., Edwards, F., Larsen, T., Hsu, W., Bendick, S., Hamer, K., Wilcove, D.,
Bruce, C., Wang, X., Levi, T., Lott, M., Emerson, B., Yu, D. 2013. Reliable, verifiable
and efficient monitoring of biodiversity via metabarcoding. Ecology Letters, 16:12451257.
Larney, F., Angers, D. 2012. The role of organic amendments in soil reclamation: A review.
Canadian Journal of Soil Science, 92(1):19-38. DOI.org/10.4141/cjss2010-064.
Li, Y., Chen, H., Song, Q., Liao J., Xu, Z., Huang, S., Ruan H. 2018. Changes in Soil Arthropod
Abundance and Community Structure across a Poplar Plantation Chronosequence in
Reclaimed Coastal Saline Soil. Forests, 9: 644. DOI:10.3390/f9100644
Lima, A., Mitchella, K., O’Connell, D., Verhoeven, J., Van Cappellena, P. 2015. The legacy of
surface mining: Remediation, restoration, reclamation and rehabilitation. Environmental
Science and Policy, 66: 227-233.
Lu, Q., He, Z., Stoffella, P. 2012. Land application of biosolids in the USA: a review. Applied
and Environmental Soil Science. DOI:10.1155/2012/201462.
Majer, J., Brennan ,K., Bisevac, L. 2002. Terrestrial invertebrates. In: Handbook of ecological
restoration. Volume 1 Principles of Restoration (Ed. By Perrow, M. and Davy, J.).
Cambridge: Cambridge University Press, 279-294.
McGeoch, Sithole, H., Samways, M., Simaika, J., Pryke, J., Picker, M., Uys, C., Armstrong, A.,
Dippenaar-Schoeman, A., Engelbrecht, I., Braschler, B., Hamer, M. 2011. Conservation
and monitoring of invertebrates in terrestrial protected areas. Koedoe, 53:1–13.
McKelvey, K. 2015. The effects of disturbance and succession on wildlife habitat and animal
communities [Chapter 11]. In: Morrison, M. L.; Mathewson, H. A., editors. Wildlife
Habitat Conservation: Concepts, Challenges, and Solutions. Baltimore, MD: Johns
Hopkins University Press. p. 143-156.
Melaschenko, N., Dickson, J., Berg, K., Straker, J. 2018. A Community-Based Approach to end
land use planning at Highland Valley Copper. [cited 2020 Oct 8]. Available from:
https://open.library.ubc.ca/cIRcle/collections/59367/items/1.0374930.

10
Mining Association of BC. [Internet]. 2019. Mining in BC. [cited 2019 Feb 2]. Available from:
https://www.mining.bc.ca/economic-impact.
Mining Association of Canada [Internet]. 2019a. Aboriginal affairs. [cited 2019 Feb 2].
Available from: http://mining.ca/our-focus/aboriginal-affairs.
Mining Association of Canada [Internet]. 2019b. Regulatory effectiveness. [cited 2019 Feb 2].
Available from: http://mining.ca/our-focus/regulatory-effectiveness.
Mining Association of Canada [Internet]. 2019c. Reclamation. [cited 2019 Feb 2]. Available
from: http://mining.ca/reclamation.
Organic Matter Recycling Regulation. 2002. British Columbia, Canada. Available from:
https://www.bclaws.ca/civix/document/id/complete/statreg/18_2002.
Palmer, J.M., Jusino, M.A., Banik, M.T. and Lindner D.L. 2018. Non-biological synthetic spikein controls and the AMPtk software pipeline improve mycobiome data; PeerJ 6:e4925.
DOI 10.7717/peerj.4925.
Prach, K., Tolvanen, A. 2016. How can we restore biodiversity and ecosystem services in mining
and industrial sites? Environmental Science and Pollution Research, 23:13587–13590.
DOI10.1007/s11356-016-7113-3.
Samways, M., McGeoch, M., New, T. 2010. Insect conservation: a handbook of approaches and
methods. Oxford University Press, Oxford. P. 312-313.
Simberloff, D., Wilson, E. 1969. Experimental zoogeography of islands: the colonization of the
empty island. Ecology, 50(2):278-296.
Wali, M. 1999. Ecological succession and the rehabilitation of disturbed terrestrial ecosystems.
Plant and Soil, 213: 195-220.
Walker, L., Wardle, D., Bardgett, R., Clarkson, D. 2010. The use of chronosequences in studies
of ecological succession and soil development. Journal of Ecology, 98:725-736. DOI:
10.1111/j.1365-2745.2010.01664.x.
Yu, D., Ji, Y., Emerson, B., Wang, X., Ye, C., Yang, C., Ding, Z. 2012. Biodiversity soup:
metabarcoding of arthropods for rapid biodiversity assessment and biomonitoring.
Methods in Ecology and Evolution, 3:613-623.

11

Chapter 2 Investigating the Effects of Reclamation Age and
Biosolids Amendment on arthropods Using DNA Metabarcoding
2.1 Introduction
A global decrease in ecosystem function and biodiversity highlights a need for ecosystem
reclamation (Bullock et al., 2011). In particular, post-mining reclamation aims to return altered
lands to self-sustaining and functioning ecosystems, inclusive of waterbodies, terrestrial areas,
and cultural resources. As a result of resource extraction processes, post-mine reclamation is
faced with unique physical challenges, such as altered topography and hydrology (Shrestha and
Lal, 2006), and unique uneconomic by-products, including waste rock and tailings.
Tailings and waste rock can result in negative environmental impacts through the release
of trace heavy metals, and the introduction of substrate lacking organic material, structure, and
nutrients to healthy soils (Hossner and Hons, 1992). Additionally, tailings and waste rock dust
(particulate matter) can pose a risk to human respiratory health (EPA, 2020). Therefore, the
Canadian mining industry must adhere to federal, provincial, and territorial acts and regulations
regarding reclamation (Mining Association of Canada, 2019).
While natural succession occurs in post-mining areas without human intervention, it
requires decades to restore (Bradshaw, 1997). The timescales for post-mining areas to return to
functioning ecosystems are unacceptable for industry and the public. The duration of time since
an area was reclaimed (reclamation age) influences soil development (Adeli et al., 2013). Soil
biotic and abiotic conditions such as nutrient availability, texture, structure, and microbes will
develop over time (Walker et al., 2010). These below-ground changes are typically correlated
with above-ground changes as a result of ecological succession. These temporal changes can be
monitored using a chronosequence (Walker et al., 2010). In this case, a chronosequence is the
study of multiple sites that differ in time since they were reclaimed.

12
Currently, long-term post-mining reclamation outcomes and trajectories are not fully
understood and there are knowledge gaps regarding community recovery of arthropods. It is
currently understood that arthropod communities can be impacted by soil properties as well as
vegetation diversity and structure (Buchori et al., 2018; Joern and Laws, 2013). Due to feedback
loops between soil, plants, and arthropods, development in one of these three types of organisms
can prompt change in another (Bennett, 2010). A meta-analysis conducted by Bennett (2010)
outlines the various ways that plant-soil-arthropod dynamics can influence each other. For
example, plant diversity influences arthropod diversity through mechanisms such as resource
availability, limitation, and variation as well as through volatiles released by vegetation when
herbivores consume or attack it. Likewise, soil microbial diversity can influence above ground
arthropod diversity through indirect effects via plants, such as plant phenotypic variation and
plant quality. Soil microbial diversity and plant diversity can influence each other through
decomposition, mineralization, organic matter, moisture transportation, and allelopathy (Bennett,
2010; Walker and del Moral, 2003).
In addition to soil-plant-arthropod relationships, the stage of succession can influence
plant composition and structure (Clements, 1916; Davy, 2002), as well as soil microbial and
chemical composition (Allen et al., 2002; Ardeshir et al., 2013). For example, Pietrzykowski
(2008) identified a greater level of plant diversity in sites as they aged over 20 years since
reclamation. Soil nutrients, such as carbon, have also been found to increase since time of
reclamation (Ardeshir et al., 2013). Therefore, it stands to reason that as the succession of
reclaimed sites progresses (soil and vegetation), arthropod composition will also progress.
Furthermore, given that arthropods are mobile and have rapid generational times they can
quickly respond to environmental disturbance or recovery (Samways et al., 2010; Gerlach et al.,
2013).
Arthropod response to their surrounding environmental factors is nuanced because
different arthropod taxa have unique sensitivities to their surrounding environments (Sylvain et
al., 2019; Buchori et al., 2018). For example, arthropod habitat requirements can be unique for
different arthropods; herbivores require plants, and predators and parasites are dependant on prey
and hosts, respectively (Buchori et al., 2018). Some arthropods colonize early succession areas
and can be drivers of soil development. In particular, Formicidae and Coleoptera taxa have been
identified in studies as early colonizers in reclaimed areas (Varela and Garcia, 2017).

13
Furthermore, the presence of these taxa before the presence of additional taxa can be interpreted
as indicators of environmental conditions or reclamation stage (Buchori et al., 2018).
To return a post-mining reclaimed area to a functional ecosystem, both biotic and abiotic
factors must be considered. Biodiversity, the variety of biota in an area accounting for
phylogenetic diversity, trophic structure, and genetic diversity (Gaston and Spicer, 2004), can be
used as a measure of ecosystem (biotic) health (Hector and Bagchi, 2007). Historically, for mine
reclamation, focus has been given to vegetation cover and diversity (Fraser et al., 2015), with
less attention given to arthropods such as assemblage composition, diversity, and indicator taxa.
In terms of biotic factors, soil health is an important variable to address (Bradshaw,
1997), with exogenous organic amendments often being used to address soil health limitations by
providing nutrients and improving physical characteristics (Larney and Angers, 2012).
Compared to organic amendments such as biosolids, inorganic fertilisers do not provide longterm benefits to soil physical and chemical characteristics, and does not benefit vegetation
establishment (Gardner et al., 2010).
An example of an organic soil amendment are biosolids made from treated municipal
wastewater solids, with treatment and stabilization to reduce pathogens (Government of British
Columbia, 2019). Unless otherwise used, biosolids may be disposed of in landfills, or incinerated
(BC Ministry of Environment and Climate Change Strategy, 2020). Biosolids are often used as a
soil amendment, applied in reclaimed areas, such as mines, in countries including the United
States, Australia, New Zealand, the United Kingdom, member states of the European Union, and
Canada (Larney and Angers, 2012; Christodoulou and Stamatelatou, 2016).
Biosolids contribute to soil stabilization; improve porosity, drainage, aeration, water and
cation exchange; and improve microbial communities by being a source of food for soil microbes
(Lu et al., 2012). Furthermore, biosolids release nutrients into the ground more slowly and for a
longer duration than chemical fertilisers (Lu et al., 2012). The application of biosolids as a soil
amendment at post-mine reclaimed sites typically only requires a one-time application, opposed
to alternative amendments (such as fertiliser) requiring annual applications. However, hormones
and heavy metals can also be found in biosolids (Lu et al., 2012) and, for this reason, biosolids
are provincially regulated to limit the concentration of specific substances according to the
British Columbia OMRR policy. Despite government regulations, there can be public concern
regarding the movement of heavy metals within the nutrient cycle between trophic levels.

14
However, hypotheses such as the plateau hypothesis aim to answer these concerns (Lu et al.,
2012). The plateau hypothesis states that trace metals are not available for uptake by plants as a
result of being retained or ‘tightly held’ by the soil and biosolids (Lu et al., 2012).
Biosolids, have been shown to enhance vegetation biomass (Gardner et al., 2012). For
example, Gardner et al. (2012) found that, in a reclaimed mine environment, vegetation
establishment was substantially reduced on sites amended with fertilizer and sites with no added
soil amendment. This result was theorized to be caused by the addition of organic matter and
nutrients from biosolids.
Gaudreault et al. (2019) found that, in a grassland ecosystem, grasshoppers were more
abundant (higher in numbers) on sites amended with biosolids. This scenario illustrates a bottomup controlled ecosystem, as biosolids act as a source of nutrients where nutrients are limited
(Larney and Angers, 2012), and are associated with increased vegetation biomass (Gardner et al.,
2012), ultimately impacting arthropod habitat (Gaudreault et al., 2019). That being said, I found
research focused on understanding the relationships between fauna and biosolids, used as a soil
amendment, is relatively limited.
Globally, there are 1.5 million described arthropod species, representing up to 80% of
global animal biodiversity (Zhang, 2013). Furthermore, arthropods benefit their surrounding
environment by providing ecosystem services (McGeoch et al., 2011) such as nutrient cycling,
pollination, seed dispersal, soil aeration, organic matter decomposition, and as food for wildlife
(Majer et al., 2002). Arthropods are good environmental indicators due to their relatively short
generation times, high fecundity, mobility, and sensitivity to environmental change (Samways et
al., 2010).
To better understand post-mine reclamation trajectories, holistic monitoring of flora,
fauna and microbial communities is needed (Fraser et al., 2015). Previous post-mining
reclamation techniques focussed on vegetation (Holl, 2002; Cavender et al., 2014), while more
recent explorations using DNA metabarcoding technologies have targeted microbial (bacteria,
fungi, and protists) communities to monitor reclamation (Francioli et al., 2021; Rosenfeld et al.,
2018). Newer studies have approached reclamation by examining whole ecosystems, specifically
addressing biodiversity and functional services (Fraser et al., 2015). That being said, arthropods
have infrequently been used as a terrestrial biomonitoring tool because of the complexities of
identifying them.

15
Morphologically identifying arthropods is time consuming, costly, and requires specific
scientific expertise (Ji et al., 2013). Additionally, larval specimens may not be identifiable using
traditional morphological methods (Yu et al., 2012). Studies that do use arthropods as indicator
species often focus on a few indicator species, rather than capturing overall arthropod
community diversity (Hammond et al., 2018). The assessment of an indicator species does not
provide insight into arthropod assemblage composition and community dynamics (Siddig et al.,
2016; Fernandes et al. 2019). Recent progress in molecular identification techniques such as
deoxyribonucleic acid (DNA) metabarcoding has helped to overcome challenges in the
taxonomic identification of arthropods and other invertebrates when founded on morphologically
identified reference specimens (Hebert et al., 2003). DNA barcoding is conducted by extracting
DNA from a specimen prior to using the polymerase chain reaction (PCR) to amplify a
phylogenetically distinctive genetic marker by using specific primers. For individual specimens,
Sanger sequencing is used, while if DNA is extracted from homogenized mixtures of arthropods,
high throughput metabarcode sequencing is used (Ji et al., 2013).
Studies that have sequenced animals, including arthropod, barcodes often target the
cytochrome c oxidase subunit 1 (CO1) gene (Hebert et al., 2003; Ji et al., 2013; Beng et al.,
2016). The CO1 gene is a good target gene because it is present in all animals (Hebert et al.,
2003), has a relatively short sequence length making amplification through PCR easy, and
contains ample nucleotide variation to differentiate taxa (Hebert et al., 2004; Wang et al., 2018).
DNA barcoding and metabarcoding relies on databases such as the Barcode of Life
Database (BOLD) to assign taxonomies to the sequenced target genes. This approach can be
used to assign taxonomies to a wide range of biota, such as vegetation, fungi, bacteria, and
animals (Hebert et a., 2003). The international Barcode of Life Database is evolving based on
public submissions and has the potential to identify all multicellular species, creating a ‘library
of life,’ which can be used to establish ‘global biosurvalliance program’ (International Barcode
of Life, 2021).
For metabarcoding efforts, sequences are first clustered into operational taxonomic units
(OTUs) prior to taxonomy assignment. Reclamation trajectory can be monitored by comparing
OTU assemblages between reclaimed sites and undisturbed sites (Fernandes et al., 2019; Ji et al.,
2013). Furthermore, patterns in reclamation can be identified by categorizing and analyzing
arthropod taxonomies (e.g., family, order) to identify indicator taxa. For example, Biaggini et al.

16
(2007) found that higher taxa, such as order, can inform on primary agricultural land uses
(grazed, cultivated, undisturbed) based on diversity and assemblage composition. Specifically,
arthropod order assemblage characterized land use in sites even when the sites were located near
each other and were small (30 m x 10 m) (Biaggini et al., 2007).
The aim of research on post-mining ecosystem reclamation is to reduce knowledge gaps
and to further understanding of reclamation trajectories, thus leading to improved reclamation
practices. This study will address three research questions based on the foundation of using DNA
metabarcoding of arthropods as a tool for assessing reclamation. First, this study will assess
whether we can identify (dis)similarities in arthropod assemblage with different reclamation ages
(‘new,’ ‘old,’ and reference) and a soil amendment (‘biosolids,’ ‘no biosolids,’ and ‘reference).
Second, this study will assess arthropod alpha diversity between sites with different reclamation
ages and amendments. Thirdly, this study will examine if the presence of specific arthropod taxa
are indicators of reclamation approach and duration (i.e., soil amendments, reclamation age).
2.2 Methods
Data Collection
Arthropod samples were collected during July and August 2018 at Teck Resources
Highland Valley Copper and New Gold Inc. New Afton mine sites (Figure 2.1) when the average
temperature in Kamloops, BC was 22.1°C, 20.2°C and the total precipitation was 14.5 mm and
7.8 mm, respectively (Government of Canada, 2022).

17

Figure 2.1. Location of mines sampled in July and August 2018 for arthropods in BC. Map
created in QGIS using Statistics Canada boundary file projected using NAD83/BC Albers
(Statistics Canada, 2021).
At each mine, two treatment areas were sampled based on reclamation age and
amendment use (Table 2.1). The sample sites were categorized as ‘new’ (10 years and newer) or
‘old’ (14 years and older), as described in Table 2.1. Sites were also categorized into sites
amended with ‘biosolids’ and ‘no biosolids’. Two reference sites were sampled near both
Highland Valley Copper (forest sites) and New Afton (grassland sites). Maps were created in
QGIS to illustrate the sample locations. A total of 19 sites were sampled at Teck Resources
Highland Valley Copper (Figure 2.2, Figure 2.3, Figure 2.4) and New Gold Inc. New Afton
(Figure 2.5, Figure 2.6). The Highland Valley Copper mine and New Afton mine differ by
biogeoclimatic (BEC) zone. BEC zones are used to characterize unique ecosystems (climate and
vegetation) in British Columbia (Mackinnon et al., 1992). New Afton mine is located in both the
very dry warm Bunchgrass variant (BGx1) and the very dry hot ponderosa pine variant (PPxh2).
Comparatively, the sites sampled Highland Valley Copper mine are located in the very dry
Montane Spruce (MSxk2) variant. In general, the Bunchgrass zone occurs between 700 meters

18
and 1000 meters above sea level and is characterized by some of the hottest and driest conditions
in BC and the absence of trees (Alldritt-McDowell and Coupé, 1998). The Ponderosa Pine zone,
often found just above the bunchgrass zone, is the driest forested zone in BC (AlldrittMcDowell, 1998). The Montane spruce zone, typically occurring between 1250-1650 meters, is
typified by cold winters and short, dry summers (Alldritt-McDowell and Lloyd, 1999).

19
Table 2.1 Teck Resources Highland Valley Copper and New Gold Inc. New Afton site descriptions outlining the material reclaimed,
reclamation age category, biosolids application, and subsequent seeding, for 2018 sampled sites.
Mine

Site

Reclaimed materials

Teck Resources
Highland Valley
Copper

Treatment site 1
Treatment site 2
Treatment site 3
Treatment site 4
Treatment site 5
Treatment site 6
Treatment site 7
Treatment site 8
Treatment site 9
Treatment site 10
Treatment site 11
Treatment site 12
Treatment site 13
Reference site 1
Reference site 2
Treatment site 14
Treatment site 15
Reference site 3
Reference site 4

Tailings, overburden
Tailings, overburden
Tailings
Tailings, overburden
Tailings, overburden
Waste rock, overburden
Waste rock, overburden
Waste rock, overburden
Waste rock, overburden
Waste rock, overburden
Waste rock, overburden
Waste rock, overburden
Waste rock, overburden
n/a
n/a
Tailings
Tailings
n/a
n/a

New Gold Inc.
New Afton

Reclamation age
category
old
new
new
old
new
old
old
new
new
old
old
old
old
n/a
n/a
old
new
n/a
n/a

Year seeded

Biosolids application

2004
2013
2012
2004
2008
1999
1999
2015
2015
1999
1992
1994
1998
n/a
n/a
2001
n/a
n/a
n/a

No biosolids
Biosolids (2013)
Biosolids (2011)
Biosolids (1998)
Biosolids (2000, 2007)
Biosolids (1999)
Biosolids (1999)
Biosolids (2014)
Biosolids (2014)
No biosolids
No biosolids
No biosolids
No biosolids
n/a
n/a
No biosolids
No biosolids
n/a
n/a

20

Figure 2.2. Map of Teck Resources Highland Valley Copper sites sampled for arthropods (Treatment Sites (TS)
1-12) in August 2018 created in QGIS using ESRI Satellite base map and projected using NAD83/BC Albers)
(ESRI, 2017).

Figure 2.3. Map of Teck Resources Highland Valley Copper sites sampled for arthropods in August 2018
(Treatment site (TS) 13) created in QGIS using ESRI Satellite base map and projected using NAD83/BC Albers
(ESRI, 2017).

21

Figure 2.4. Map of references sites near Teck Resources Highland Valley Copper sampled for arthropods in
August 2018 (Reference Sites (RS) 1-2) created in QGIS using ESRI Satellite base map and projected using
NAD83/BC Albers (ESRI, 2017).

Figure 2.5. Map of New Gold Inc. New Afton July 2018 sampled for arthropods in July 2018 (Treatment Sites
(TS) 14-15)) created in QGIS using ESRI Satellite base map and projected using NAD83/BC Albers (ESRI,
2017).

22

Figure 2.6 Map of reference sites near New Gold Inc. New Afton sampled for arthropods in July 2018
(Reference Sites (RS) 3-4) created in QGIS using ESRI Satellite base map and projected using NAD83/BC
Albers (ESRI, 2017).
At each site, traps were set up to collect both flying and ground-dwelling arthropods. To
collect flying arthropods, tent-like structures called Malaise traps (Figure 2.7) were used
(Thomas, 2016; Lynggaard et al., 2020). One Malaise trap was constructed at each site.

Figure 2.7. Malaise trap set up to capture flying arthropods. Photo taken by Lauchlan Fraser.
Epigeal arthropod samples were collected in a 40 m x 40 m grid layout (

23
Figure 2.8). Nine pitfall trap samples were collected in three rows of three within the 40 m x 40
m grid .At each of the nine sample areas, a pitfall trap was set up. Pitfall traps were used to
collect ground-dwelling arthropods (Bassett and Fraser, 2015) (Figure 2.9). Pitfall traps were
assembled by inserting a 450-g container (Solo® cup) in the soil, flush to the ground. The cups
were filled with an 87% denatured ethanol solution. A wooden board was placed approximately
5 cm above the ground, held by nails, to reduce ethanol evaporation as well as reduce the
potential for any wildlife from falling into the pitfall trap, or removing sample specimens from
the pitfall trap.

Figure 2.8 2018 Pitfall trap layout that was used to collect epigeal arthropods at Highland
Valley Copper. Photo taken by Chantalle Gervan.

24

Figure 2.9. Sampling of epigeal arthropods using a pitfall trap consisting of A) a 450 g container
placed flush with the ground , and B) a plastic plate over the top to reduce ethanol evaporation.
The pictured plastic plates were used instead of wooden boards in 2017. Photos taken by
Chantalle Gervan.
Malaise traps and pitfall traps remained in the ground for five days in the summer
(Lynggaard et al., 2020; Foster et al., 2020). After five days, the trap contents (ethanol and
arthropods) were collected and stored in a freezer -20°C until laboratory processing. Due to
access constraints at Highland Valley Copper, arthropod traps at some sites were collected after
six days (TDA12A1, BMJ11A, BM98B, BM98A) or seven days (BND95e, BN92A, BN99A1,
BN99B).
Two pitfall traps were removed from each site with the intention of sending them to the
Centre for Biodiversity Genomics at Guelph University to be Sanger-sequenced and added to the
Barcode of Life Database (BOLD). Sanger-sequenced specimen are individually
morphologically identified by an expert then individually sequenced to determine a portion of
that individual specimen’s nucleotide sequence of their genome. Separating the samples to
submit to the Centre for Biodiversity Genomics was done to ensure that arthropods collected in
this region were available in the barcode of Life database for identification. However, due to
complications caused by COVID-19, the samples were not sent.
In 2017 four mines were sampled (Teck Resources Highland Valley Copper, New Gold
Inc. New Afton, Avino Silver and Gold Mine Ltd. at Bralorne, and Imperial Metals Corporation
Mount Polley) but are not included in this study due to differences in sampling methodologies.

25
The contents of twelve pitfall traps and four malaise traps from the 2017 samples were sent to
the Centre for Biodiversity Genomics at Guelph University to be Sanger sequenced and added to
the Barcode of Life database. This was to ensure that arthropods collected in this region were
available in the Barcode of Life database for identification.
DNA extraction, PCR amplification, and sequencing
Identification of the collected arthropods was conducted using high-throughput DNA
metabarcoding targeting a 402 base-pair region of the mitochondrial cytochrome c oxidase
subunit one gene (CO1 gene). The CO1 gene has approximately 650 base-pairs.
Individual arthropod specimens that measured >5 mm were subsampled by removing the
body below the head and retaining the head for DNA extractions (Foster et al., 2020; modified
from Beng et al., 2016), while for those that were <5 mm, whole specimens were used. The
tissues were homogenized in liquid nitrogen with a sterilized mortar and pestle (Beng et al.,
2016). DNA was extracted from the homogenized tissue using a Mag Bind® Blood and Tissue
Kit (Omega Bio-tek, Inc., Norcross, GA), according to the manufacturer’s instructions (Figure

2.10).
Figure 2.10 Collected arthropods being prepared for sequencing: A) Sorting specimens,
previously stored in ethanol, to be homogenized in liquid nitrogen B) Samples in a hot water
bath during DNA extraction process using Mag Bind® Blood and Tissue Kit (Omega Bio-tek,
Inc., Norcross, GA) according to manufacturer’s instructions. Photos taken by Chantalle
Gervan.
A 402 base-pair region of the mitochondrial cytochrome c oxidase subunit one gene
(CO1 gene) was amplified via polymerase chain reaction (PCR) using the universal PCR primer
pair MHemF and DgHCO-2198 (Table 2.2) (Park et al., 2011; Meyer, 2003). Each 25 μL PCR

26
solution included 12.5 µL 2X GoTaq DNA polymerase (Promega Corporation, Madison,
Wisconsin, USA), 1.0 μL of forward primer, 1.0 μL reverse primer, 10 ng DNA extract, and
nuclease-free water.
Table 2.2 PCR primer name and sequence targeting the 402 base-pair region of the
mitochondrial cytochrome c oxidase subunit.
Primer name

Sequence (5'-3')

MhemF

GCA TTY CCA CGA ATA AAT AAY ATA AG

DgHCO-2198

TAA ACT TCA GGG TGA CCA AAR AAY CA

PCR cycling was conducted in a SimpliAmpTM Thermal Cycler (Applied Biosystems,
Thermo Fisher Scientific, Waltham, Massachusetts, USA) using the following temperature
program: 94 °C for one minute, seven cycles of 94 °C for 30 seconds, 43 °C for 30 seconds, 72
°C for 40 seconds, then 30 cycles of 94 °C for 30 seconds, 55 °C for 30 seconds, 72 °C for 40
seconds and 72 °C for five minutes (Foster et al., 2020; modified from Beng et al., 2016).
PCR products (amplicons) were purified to remove DNA shorter than 100 base pairs
using AgenCourt AMPure (Beckman Coulter Inc., Brea, California) beads according to the
manufacture’s protocol. Amplicons were visualized following separation on a 1.5% agarose gel
(70 V for 35 minutes in TAE buffer), and their sizes estimated by comparing to a molecular
weight standard. Purified DNA was quantified using a Quant-iT dsDNA HS Assay Kit (Thermo
Fisher Scientific, Waltham, USA) and Qubit 2.0.
A second round of PCR was used to add IonXpress barcodes and P1 adapters for
subsequent sequencing on an IonS5 system. For example, in the below sample primer sequence
the underlined text represents the A adaptor sequence and red text represents the IonXpress
barcode in the forward primer; the bold text represents P1 adaptor sequence in the reverse
primer.
CCATCTCATCCCTGCGTGTCTCCGACTCAGTAGGTGGTTCGATGCATTYCCACGAAT
AAATAAYATAAG
CCACTACGCCTCCGCTTTCCTCTCTATGGGCAGTCGGTGATTAAACTTCAGGGT
GACCAAARAAYCA
After the second-round PCR, barcoded amplicons were purified and quantified as
described above, and then pooled into sub-pools in equimolar amounts to remove non-target
DNA, pooled amplicons were separated via gel electrophoresis, and target amplicons were

27
excised from the gel and purified using a MicroElute® Gel Extraction Kit (Omega Bio-tek,
Georgia, USA).
Sequencing adapted amplicons in the sub-pools were quantified using an Ion Library
Quantitation Kit via quantitative real-time PCR (qPCR). These were then pooled again prior to
sequencing on an Ion S5 XL™ sequencing platform (Thermo Fisher Scientific, Waltham, MA)
using an Ion 530™ Chip Kit.
Data processing
The bioinformatic pipeline AMPtk (version 1.5.1) was used to cluster sequences into
operational taxonomic units (OTUs) at an identity threshold of 97% (Palmer et al., 2018.
Taxonomies were assigned using the (Yu et al., 2012) BOLD database
(http://v4.boldsystems.org) downloaded on November 9th, 2020. The original dataset (2017 and
2018) contained 1787 OTUs. OTUs with fewer than 5000 reads were pruned and rarefied using
Phyloseq v1.32.0 (McMurdie and Holmes, 2013). Data were rarefied to an even depth
(McKnight et al., 2019; Beng et al., 2016). OTUs that were not classified to the domain level
were removed. The subsequent data set produced for statistical analysis included a total of 524
OTUs. OTU data were converted to presence-absence to adjust for bias in PCR amplification
(Beng et al., 2016; Yu et al., 2021; Lynggaard et al., 2020).
Statistical analysis
Five statistical analysis methods were used to analyze the Teck Resource Highland
Valley and New Gold Inc. New Afton data. The analyses included principal coordinate analysis
(PCoA), permutational multivariate analysis of variance using distance matrices (adonis),
analysis of similarities (ANOSIM), indicator species analysis, and the Kruskal-Wallis test.
All of the statistical analyses were conducted in R (R Core Team, 2019) using RStudio
4.0.0, “Arbor Day “(RStudio Team, 2019). All images were created using ‘ggplot2’ (Wickham,
2016) and ‘wesanderson’ (Ram et al., 2018). The ‘tidyverse’ package (Wickham, 2017) was used
for data manipulation and visualization.
PCoA plots were calculated based on the Jaccard distance using the ape package (Paradis
and Schliep, 2018). PCoA plots were used to visualize arthropod assemblage data based on
treatments. The adonis test partitions sums of squares using dissimilarities and was used to assess
whether arthropod assemblages among groups were similar. The ANOSIM analyses were used to

28
test for a difference between groups of OTU assemblages. Specifically, ANOSIM tests if the
similarity between the OTU groups is greater than or equal to the similarity within the OTU
groups. Both adonis and ANOSIM analyses were calculated based on Jaccard dissimilarity, using
the ‘vegan’ function (Oksanen, 2018). The Kruskal-Wallis test was used to compare OTU
richness between treatments. OTU richness is defined by the number of operational taxonomic
units between each of the study sites. Pairwise comparisons using the Dunn’s test were
conducted to identify the significance between sample sites. Indicator species analyses were
calculated using the ‘indicspecies’ package (De Caceras and Legendre, 2009), with 999
permutations. The functions ‘multipatt’ and ‘indVal.g’ were used. Multipatt identifies taxa that
are associated with sites and a combination of sites (De Caceras and Legendre, 2009). The
indicator value ranges from 0-1, 1 being maximum association. The indicator value is based on
two factors: positive predictive value and fidelity (De Caceras and Legendre, 2009).
The data were also separated by taxonomic order to better understand the assemblage
structure. Presence-absence OTUs were characterized and summed into taxonomic order. OTUs
were sorted into 17 taxonomic orders, including Diptera, Coleoptera, Entomobryomorpha,
Orthoptera, Hemiptera, Hymenoptera, Archaeognatha, Lepidoptera, Opiliones, Araneae,
Psocodea, Thysanoptera, Neuroptera, Poduromorpha, Mesostigmata, Sarcoptiformes,
Trombidiformes, and family Formicidae. Although order-level organization was primarily used
to categorize the OTUs, Hymenoptera was additionally separated into two groups (family
Formicidae and not family Formicidae). Formicidae were separated to family as they have been
previously identified as an indicator family (Buchori et al., 2018). Because the order data is not
presence-absence, PCoA was calculated using Bray-Curtis dissimilarity and was percent
transformed (relative abundance).
2.3 Results
To explore the arthropod assemblage recovery on reclaimed mine sites, all arthropod
metabarcoding data from 2018, along with associated metadata, including reclamation age
(‘new’, ‘old’), soil amendment (‘biosolids’, ‘not biosolids’), and reference were analyzed using
the following groupings: full dataset, separated by mine (Highland Valley Copper and New
Afton), separated by taxonomic order. The results implied that the dissimilarity of arthropod
assemblage is primarily driven by an external factor, opposed to reclamation age and
amendment. The results also found patterns between several order level taxa and reclamation age

29
and amendment. Indicator species analyses identified several taxa uniquely associated with age
and amendment sites.
Arthropod assemblage (dis)similarity characterising reclamation sites
In order to examine the effects of reclamation age, amendment, material, and mine
location on arthropod assemblages, PCoA was carried out using the full 2018 dataset. Neither
reclamation age (Figure 2.11) nor biosolids treatment (Figure 2.12) appeared to influence
arthropod assemblages. Indeed, for both of these comparisons, arthropod assemblages on
reclaimed sites did not appear to be different than natural reference sites. In contrast, when
examining arthropod assemblages in the context of mine location and type of material reclaimed
(waste rock and tailings), it is clear that sites located closer to each other in ordination space are
more similar to each other (Figure 2.13). Specifically, waste rock sites located at Highland
Valley Copper are near the top left of the plot, and tailings sites located at New Afton are near
the bottom center of the plot. This separation between sites with waste rock at Highland Valley
Copper and tailings at New Afton implies that arthropod assemblages at waste rock sites at
Highland Valley Copper are more similar to each other, and arthropod assemblages at tailings
sites at New Afton are more similar to each other.

30

Figure 2.11. PCoA diagram created using Jaccard distance, illustrating arthropod assemblages
of different reclamation ages (age, old) and reference collected in 2018 from sample sites at the
Highland Valley Copper (Teck Resources) and New Afton (New Gold Inc.) mines.

31

Figure 2.12 PCoA diagram created using Jaccard distance, illustrating arthropod assemblages
in sites amended with(out) biosolid collected at sample sites at the Highland Valley Copper
(Teck Resources) and New Afton (New Gold Inc.) mines in 2018. No sites were amended with
Biosolids at New Afton (New Gold Inc.).

32

Figure 2.13. PCoA diagram created using Jaccard distance, illustrating arthropod assemblages
in sites with different reclaimed materials (waste rock, tailings) at 2018 sample sites at the
Highland Valley Copper (Teck Resources) and New Afton (New Gold Inc.) mines.
To explore the sources of arthropod assemblage differences between sites amended with
and with(out) biosolids and sites with different reclamation ages, permutational analysis of
variance using the Jaccard distance (Adonis) was carried out. Table 2.3, where the R2 value
represents the correlation between the treatments and arthropod assemblages. Here, the
reclamation ‘age’ explains 3.0% (p=0.001) of the observed variation, the soil ‘amendment’
explains 1.4% (p=0.005) of the variation, and reclamation age combined with soil amendment
(‘Age: Amendment’) explained 1.5% (p=0.003).

33

Table 2.3 Permutational analysis of variance calculated using Jaccard distance (adonis)
addressing reclamation age and amendment, and reference site. Significant values are listed in
bold font. R2 values were considered significant if the p-values were below 0.05. No sites were
amended with Biosolids at New Afton (New Gold Inc.).
Factor
Age
Amendment
Age:
Amendment
Residuals

Df
2
1
1

Sum sq
1.703
0.795
0.862

Mean sq
0.851
0.795
0.862

121

53.261

0.440

F model
1.934
1.805
1.957

R2
0.030
0.014
0.015

P-value
0.001
0.005
0.003

0.941

Two ANOSIM tests were conducted to assess whether the similarity between the groups
(reclamation ‘age’ and biosolids as a soil ‘amendment’) is greater than or equal to the similarity
within the groups. An examination of the effect of reclamation age (new, old) as compared to
natural reference sites, suggests an even ranking of assemblage (dis)similarity given the R-value
(R = 0.086; p=0.001) (Figure 2.14). Similarly, an examination of the effect of biosolids as a soil
amendment (biosolids, no biosolids) as compared to natural reference sites, suggests an even
ranking of assemblage (dis)similarity given the R-value (R = 0.062; p=0.002) (Figure 2.15).

34

Figure 2.14. Analysis of similarity, testing reclamation age, calculated using Jaccard distance.
Variation within groups is calculated by how much the samples differ from the group mean.
Comparatively, variation between groups is calculated by how much the samples differ from the
overall mean. In these figures, the horizontal line in the box illustrates the median, the top and
bottom of the box illustrate the 25th and 75th percentile, respectively, and the whiskers extend to
the furthest data points. The width of the boxes represents the sample size within that treatment.

35

Figure 2.15 Analysis of similarity, testing reclamation amendment, calculated using Jaccard
distance. Variation within groups is calculated by how much the samples differ from the group
mean. Comparatively, variation between groups is calculated by how much the samples differ
from the overall mean. In these figures, the horizontal line in the box illustrates the median, the
top and bottom of the box illustrate the 25th and 75th percentile, respectively, and the whiskers
extend to the furthest data points. The width of the boxes represents the sample size within that
treatment. No sites were amended with Biosolids at New Afton (New Gold Inc.).
The PCoA, exploring the impact of reclamation and reclamation strategy, based on taxa
separated by order, did not reveal a pattern distinguishing reclamation age (Figure 2.16) and soil
amendment variables (Figure 2.17).

36

Figure 2.16 PCoA diagram based on the number of taxa characterizing each order, using BrayCurtis percentage to calculate distance, illustrating arthropod assemblages in sites with different
reclamation ages (new, old) at 2018 sample sites from Highland Valley Copper (Teck Resources)
and New Afton (New Gold Inc.) mine

37

Figure 2.17 PCoA diagram based on the number of taxa characterizing each order, using BrayCurtis percentage to calculate distance, illustrating arthropod assemblages in sites amended
with(out) biosolids at 2018 sample sites from Highland Valley Copper (Teck Resources) and
New Afton (New Gold Inc.) mines. No sites were amended with Biosolids at New Afton (New
Gold Inc.).
Alpha diversity characterising reclamation sites
From the pitfall traps collected at Highland Valley Copper and New Afton, the average
pitfall trap identified 17 unique taxa. The results of Kruskal-Wallis tests comparing species
richness between ‘new,’ ‘old,’ and ‘reference’ sites revealed that there was no significant
difference in taxa richness between reclamation age sites at New Afton and Highland Valley
Copper (p = 0.783; Table 2.4).
Data organized by taxonomic order were also analyzed for richness between treatments.
The results of Kruskal-Wallis tests comparing the number of unique arthropod taxa in 18
arthropod taxonomic groups between sites revealed that there were significant differences in the

38
richness of Diptera (p=0.021), Entomobryomorpha (p=0.006), Psocodea (p=0.025), and
Hemiptera (p=0.042) taxa between reclamation age sites (Table 2.4).
Table 2.4 Alpha diversity defined by the number of operational taxonomic units assigned to the
taxonomic group, between sites with different reclamation age sites (‘new,’ ‘old,’ and
‘reference’) at Highland Valley Copper (Teck Resources), and New Afton (New Gold Inc.).
Significance is based on Kruskal-Wallis test. Bold values represent significant p-values.
Taxonomic group
All taxa
Diptera
Entomobryomorpha
Psocodea
Hemiptera
Poduromorpha
Mesostigmata
Sarcoptiformes
Trombidiformes
Neuroptera
Thysanoptera
Araneae
Coleoptera
Orthoptera
Opiliones
Lepidoptera
Archaeognatha
Hymenoptera (Non -Formiciade)
Formicidae

X2
0.490
7.691
10.302
7.359
6.325
4.998
3.5
3.5
1.419
1.955
5.356
2.81
0.424
0.807
3.516
1.486
3.185
1.972
3.270

P
0.783
0.021
0.006
0.025
0.042
0.082
0.174
0.174
0.492
0.376
0.069
0.245
0.809
0.786
0.172
0.476
0.204
0.373
0.195

A post hoc analysis was done to identify the significance between the age sites (Table
2.5). The Dunn’s test found that Diptera OTU richness was significantly greater on ‘new’ sites
compared to ‘old’ sites (p=0.017). The ‘old’ site has significantly less Entomobryomorpha OTU
richness than the ‘new’ (p=0.041) site and the ‘reference’ site (p=0.015). Psocodea OTU richness
was greater at the ‘old’ sites compared to the ‘reference’ sites (p=0.039). Despite the KruskalWallis displaying significance for the order Hemiptera, there was not a significant difference
between age sites and Hemiptera richness (p>0.05). Comparisons between order (Diptera,
Entomobryomorpha, and Psocodea) richness and reclamation age sites are illustrated in Figure
2.18.

39
Table 2.5 Dunn test comparing alpha diversity defined by the number of operational taxonomic
units assigned to the taxonomic group, between sites with different reclamation age sites (‘new,’
‘old,’ and ‘reference’) at Highland Valley Copper (Teck Resources), and New Afton (New Gold
Inc.). Bold values represent significant p-values.
Taxonomic group
Diptera

Entomobryomorpha

Psocodea

Hemiptera

Pairwise comparisons
New vs. Old
New vs. Reference
Old vs. Reference
New vs. Old
New vs. Reference
Old vs. Reference
New vs. Old
New vs. Reference
Old vs. Reference
New vs. Old
New vs. Reference
Old vs. Reference

Z
-2.77
-1.36
1.02
-2.46
0.58
2.81
1.91
-0.73
-2.49
0.18
2.27
2.27

P
0.017
0.525
0.916
0.041
1
0.015
0.167
1
0.039
1
0.069
0.070

40

Figure 2.18 Bar plot with standard error illustrating the mean distribution of Diptera,
Entomobryomorpha, and Psocodea richness defined by the number of operational taxonomic
units assigned to the order, between sites with different reclamation ages (‘new,’ ‘old,’ and
‘reference’) at Highland Valley Copper (Teck Resources), and New Afton (New Gold Inc.).

41
The results of Kruskal-Wallis tests comparing species richness between ‘biosolids,’ ‘no
biosolids,’ and ‘reference’ sites revealed that there was no significant difference in species
richness between reclamation soil amendment sites at New Afton and Highland Valley Copper
(p = 0.318; Table 2.6).
Data organized by taxonomic order were also analyzed for richness between treatments.
The results of Kruskal-Wallis tests comparing the number of unique arthropod taxa in 18
arthropod taxonomic groups between sites revealed that there were significant differences in the
richness of Entomobryomorpha (p=0.013), Formicidae (p=0.003), Thysanoptera (p=0.005),
Araneae (p=0.049), and Hemiptera (p=0.042) and taxa between sites with and without biosolids
(Table 2.6).
Table 2.6 Alpha diversity defined by the number of operational taxonomic units assigned to the
taxonomic group, between sites with different reclamation amendment treatments (‘biosolids,’
‘no biosolids,’ and ‘reference’) at Highland Valley Copper (Teck Resources), and New Afton
(New Gold Inc.). Significance is based on Kruskal-Wallis test. Bold values represent significant
p-values. No sites were amended with Biosolids at New Afton (New Gold Inc.).
Taxonomic group
All taxa
Entomobryomorpha
Formicidae
Thysanoptera
Araneae
Hemiptera
Poduromorpha
Mesostigmata
Sarcoptiformes
Trombidiformes
Neuroptera
Psocodea
Coleoptera
Orthoptera
Diptera
Opiliones
Lepidoptera
Archaeognatha
Hymenoptera (Non -Formicidae)

X2
2.293
8.641
11.488
10.702
6.026
6.320
5.569
3.5
3.5
0.236
1.622
3.966
0.1352
0.289
1.378
5.413
1.177
3.373
3.325

P
0.318
0.013
0.003
0.005
0.049
0.042
0.062
0.174
0.174
0.889
0.444
0.158
0.935
0.865
0.502
0.067
0.555
0.185
0.190

A post hoc analysis was done to identify the significance between the age sites (Table
2.7). The Dunn’s test found that Entomobryomorpha demonstrated a significant difference in

42
richness between the ‘reference’ sites and the ‘biosolids’ sites (p=0.020). The family Formicidae
had greater richness on sites with no biosolids compared to sites amended with biosolids
(p=0.002). There was greater Thysanoptera richness on sites without biosolids compared to sites
amended with biosolids (p=0.003). Despite the orders Aranea and Hemiptera being statistically
significant in the Kruskal-Wallis test, the Dunn’s test did not uncover a significant relationship
between the sites (p>0.05). Comparisons between Thysanoptera, Entomobryomorpha, and
Formicidae and soil amendment sites are illustrated in Figure 2.19.
Table 2.7 Dunn’s test comparing alpha diversity defined by the number of operational taxonomic
units assigned to the taxonomic group, between sites with different reclamation amendment
treatments (‘biosolids,’ ‘no biosolids,’ and ‘reference’) at Highland Valley Copper (Teck
Resources), and New Afton (New Gold Inc.). Bold values represent significant p-values. No sites
were amended with Biosolids at New Afton (New Gold Inc.).
Taxonomic group
Entomobryomorpha

Formicidae

Thysanoptera

Araneae

Hemiptera

Pairwise comparisons
Biosolids vs. No biosolids
Biosolids vs. Reference
No biosolids vs. Reference
Biosolids vs. No biosolids
Biosolids vs. Reference
No biosolids vs. Reference
Biosolids vs. No biosolids
Biosolids vs. Reference
No biosolids vs. Reference
Biosolids vs. No biosolids
Biosolids vs. Reference
No biosolids vs. Reference
Biosolids vs. No biosolids
Biosolids vs. Reference
No biosolids vs. Reference

Z
2.10
2.72
0.85
3.37
1.64
-1.25
3.26
0.98
-1.79
-1.81
-2.24
-0.63
-0.17
2.24
2.30

P
0.108
0.020
1
0.002
0.300
0.636
0.003
0.984
0.219
0.211
0.08
1
1
0.074
0.064

43

Figure 2.19 Bar plots with standard error illustrating the distribution of mean
Entomobryomorpha, Formicidae, and Thysanoptera richness defined by the number of
operational taxonomic units assigned to the order, between sites amended with different soil
amendment (‘biosolids’, ‘no biosolids’, and ‘reference) at Highland Valley Copper (Teck
Resources), and New Afton (New Gold Inc.). No sites were amended with Biosolids at New Afton
(New Gold Inc.).

44
Indicator taxa characterising reclamation sites
To assess if specific taxa were associated with reclamation age and amendment
treatments, indicator species analyses were used. The association between the OTU and the
reclamation variable increases with the measure of the statistic, from 0-1. The below tables
describe the taxa with the strongest affinity for different site types. It should be noted that these
tables are condensed for efficiency, and that the complete indicator tables are available in
Appendix C.
Arthropod taxa were more associated with different reclamation ages (‘new’, ‘old’, and
‘reference’) and a combination of sites at Highland Valley Copper mine and New Afton mine
(Table 2.8). The taxon that was most correlated with the reference site was Latalus misseullus.
The taxon that was most associated with the ‘new’ sites was Leia spp. In this analysis, there was
not a taxon that was strongly tied to the ‘old’ site. However, Formica lasioides (potential genetic
variations of ant species) were most associated with a combination of the ‘old’ and ‘new’ sites.
Finally, Haplothrips tenuipennis was the taxon most identified with the ‘old’ and ‘reference’
sites.
Table 2.8. Indicspecies analysis outlining the top operational units (OTU) associated with
different reclamation ages (‘new,’ ‘old,’ ‘reference’) of the 2018 sample sites at the Highland
Valley Copper (Teck Resources) and New Afton (New Gold Inc.) mines, where and ‘p’ is the
probability of finding the obtained results given that the null hypothesis is true, and ‘indicator
stat’ is an indicator value that ranges from 0 to1.
OTU

Taxon

Indicator stat

p-value

0.463
0.438
0.404

0.001
0.001
0.003

0.392
0.373
0.316

0.036
0.031
0.012

0.440
0.404

0.021
0.050

0.469

0.025

Reference
0181
0124
0050

Latalus missellus
Formica neorufibarbis
Sciaridae

0930
0030
0206

Leia spp
Fannia canicularis
Delia extensa

New

New and Old
1367
1552

Formica lasioides
Formica lasioides

0205

Haplothrips tenuipennis

Reference and Old

45
Data were divided into unique mines (Highland Valley Copper and New Afton) to further
understand and identify patterns within the data set. To assess if specific taxa were associated
with reclamation age and amendment treatment, indicator species analyses were used.
Arthropod taxa were more associated with different reclamation ages (‘new’, ‘old’, and
‘reference’) and a combination of sites at Highland Valley Copper mine (Table 2.9). The
‘reference’ site was most associated with Formica neorufibarbis, Latalus missellus taxon, and
Tachinus spp. The ‘new’ site was correlated with the taxa Fannia canicularis, Staphylinidae
taxon, and Machilidae taxon. Two potential genetic variations of the same taxa were associated
with the ‘old’ site; Otiorhynchus ovatus. The combination of the ‘reference’ and ‘old’ sites were
correlated with Phloeostiba lapponica, and Haplothrips tenuipennis. Only one taxon, Formica
lasioides, was tied to the ‘new’ and ‘old’ site combination.
Table 2.9. Indicspecies analysis outlining the top operational units (OTU) associated with
different reclamation age (‘new,’ ‘old,’ ‘reference’) of the 2018 sample sites at the Highland
Valley Copper (Teck Resources) mine, where and ‘p’ is the probability of finding the obtained
results given that the null hypothesis is true, and ‘indicator stat’ is an indicator value that ranges
from 0 to1.
OTU
0124
0181
0011
0030
0040
0111
0012
0344
0035
0205
0002

Taxon
Reference
Formica neorufibarbis
Latalus missellus
Tachinus spp
New
Fannia canicularis
Staphylinidae
Machilidae
Old
Otiorhynchus ovatus
Otiorhynchus ovatus
Reference and Old
Phloeostiba lapponica
Haplothrips tenuipennis
New and old
Formica lasioides

Indicator stat

p-value

0.659
0.620
0.566

0.001
0.001
0.002

0.450
0.442
0.343

0.024
0.028
0.044

0.484
0.412

0.019
0.025

0.623
0.477

0.015
0.040

0.614

0.038

Arthropod taxa were more associated with different reclamation ages (‘new’, ‘old’, and
‘reference’) and a combination of sites at New Afton mine (Table 2.10). The ‘new’ site was
strongly associated with a Heleomyzidae taxon as well as Tapinoma sessile. The ‘old’ site was

46
correlated with Meinertellidae taxon, Myrmica fracticornis, and Archaeognatha taxon. Both the
‘new’ and ‘old’ age sites were most affiliated with Entomobrya unostrigata.
Table 2.10. Indicspecies analysis outlining the top operational units (OTU) associated with
different reclamation age (‘new,’ ‘old,’ ‘reference’) of the 2018 sample sites at the New Afton
(New Gold Inc.) mine, where and ‘p’ is the probability of finding the obtained results given that
the null hypothesis is true, and ‘indicator stat’ is an indicator value that ranges from 0 to1.
OTU

Taxon

0771
1504

Heleomyzidae
Tapinoma sessile

Indicator stat

p-value

0.82
0.707

0.005
0.016

0.685
0.632
0.632

0.018
0.034
0.032

0.798

0.018

New

Old
0017
0267
0300

Meinertellidae
Myrmica fracticornis
Archaeognatha

1499

Entomobrya unostrigata

New and Old
Arthropod taxa were more associated with different amendment treatments (‘biosolids,’
‘no biosolids,’ and ‘reference’) and a combination of sites at Highland Valley Copper mine and
New Afton mine (Table 2.11). Staphylinidae taxon, Amara fortis, and Lepidoptera taxon were
the taxa most associated with the ‘biosolids’ variable. Latalus missellus was the taxon most
strongly correlated with the ‘reference’ site. The reference site was most strongly tied to Latalus
missellus, Formica neorufibarbis, and Sciaridae taxon. ‘No biosolids’ shared the strongest
relationship with Leptothorax spp, Heleomyzidae taxon, and Camnula pellucida.
Table 2.11. Indicspecies analysis outlining the top operational units (OTU) associated with
different reclamation amendments (‘biosolids,’ ‘no biosolids,’ ‘reference) of the 2018 sample
sites at the Highland Valley Copper (Teck Resources) and New Afton (New Gold Inc.) mines,
where and ‘p’ is the probability of finding the obtained results given that the null hypothesis is
true, and ‘indicator stat’ is an indicator value that ranges from 0 to1. No sites were amended
with Biosolids at New Afton (New Gold Inc.)
OTU

Taxon

Indicator stat

p-value

0.416
0.332
0.304

0.024
0.025
0.028

0.463
0.444
0.398

0.001
0.001
0.004

Biosolids
0040
0076
0948

Staphylinidae
Amara fortis
Lepidoptera
Reference

0181
0124
0050

Latalus missellus
Formica neorufibarbis
Sciaridae

47
No biosolids
0064
0771
0590
0015
0570
0205
1367
1552

Leptothorax sp.
Heleomyzidae
Camnula pellucida
No biosolids and reference
Formica subaenescens
Entomobrya spp
Haplothrips tenuipennis
No biosolids and biosolids
Formica lasioides
Formica lasioides

0.403
0.327
0.313

0.012
0.043
0.042

0.557
0.545
0.523

0.025
0.001
0.002

0.440
0.404

0.025
0.039

Arthropod OTUs were more associated with different amendment treatments (‘biosolids,’
‘no biosolids,’ and ‘reference’) and a combination of sites at Highland Valley Copper mine
(Table 2.12). Formica neorufibarbis, Latalus missellus, and Tachinus spp were most associated
with the reference site. Sites without biosolids were linked to Haplothrips tenuipennis,
Otiorhynchus ovatus, and Leptothorax spp. The ‘biosolids’ and ‘no biosolids’ were most
associated with Formica lasioides. Both the ‘reference’ and ‘no biosolids’ sites were correlated
with Formica subaenescens (formerly Formica fusca var complex).
Table 2.12. Indicspecies analysis outlining the top operational units (OTU) associated with
different reclamation amendment (‘biosolids,’ ‘no biosolids,’ ‘reference’) of the 2018 sample
sites at the Highland Valley Copper (Teck Resources) mine, where and ‘p’ is the probability of
finding the obtained results given that the null hypothesis is true, and ‘indicator stat’ is an
indicator value that ranges from 0 to1.
OTU

Taxon

Indicator stat

p-value

0.666
0.620
0.572

0.001
0.001
0.001

0.526
0.500
0.459

0.006
0.018
0.032

0.617

0.026

0.677

0.001

Reference
0124
0181
0011
0205
0012
0064
0002
0015

Formica neorufibarbis
Latalus missellus
Tachinus spp
No biosolids
Haplothrips tenuipennis
Otiorhynchus ovatus
Leptothorax spp
Biosolids and No biosolids
Formica lasioides
Reference and No biosolids
Formica subaenescens

48
2.4 Discussion
The effects of postmining reclamation on recovering arthropod assemblages were
examined at two mines in BC. DNA metabarcoding techniques were used, and few differences in
arthropod assemblages between mine sites and different reclamation treatments groups were
detected. In this section, arthropod assemblage similarity, arthropod alpha diversity, and
arthropod indicator species are used to interpret patterns in reclamation against soil amendments
and reclamation age. Analyses discussed in this section used OTUs categorized to order-level, as
well as to the lowest identified taxonomic rank i.e., species.
Arthropod assemblage (dis)similarity distinguishing reclamation sites
Over time, arthropod communities recover in reclaimed areas following disturbance
(Steed et al. 2018; Watts and Mason, 2015; Fernandes et al. 2019). In this study, arthropod
assemblage similarity was assessed between different age plots at Highland Valley Copper and
New Afton mines to better understand post mine reclamation trajectory. Arthropod assemblages
did not show a strong relationship with reclamation age, as shown in Figure 2.11 and Table 2.3.
Figure 2.14 illustrates that the ‘old’ and ‘reference’ sites are slightly more similar than ‘new’,
indicating that over time the arthropod assemblage becomes more similar to the reference sites.
Despite this pattern being significant, it only explains a small percentage (8.6%) of the variation
within the dataset. Order-level arthropod assemblage similarity of different age plots (‘new,’
‘old,’ and ‘reference) at Highland Valley Copper and New Afton mines were also analyzed.
Arthropod assemblage composition did not show a strong relationship with reclamation age, as
shown in Figure 2.11. This indicates that no trajectory of order-level arthropod assemblages that
becomes more similar to the corresponding reference site with age was detected with the
methods used here. Fernandes et al. (2019) carried out a similar experiment, examining terrestrial
arthropod community response to mine reclamation age, using DNA metabarcoding. Their study
identified that ‘older’ sites were more analogous to ‘reference’ sites than recently reclaimed sites.
The arthropod assemblage similarity of sites without biosolids and with biosolids at
Highland Valley Copper and New Afton mines were also compared in an effort to understand the
long-term ecological response to a soil amendment known to impact nutrient content and soil
properties (Gardner et al., 2010). In this study, soil amendments (‘biosolids,’ ‘no biosolids’) did
not explain the variation in arthropod assemblages (Figure 2.12). Likewise, Figure 2.15 shows
that sites with ‘no biosolids’ are slightly more similar to the ‘reference’ sites; however, the

49
pattern only accounts for 6.2% of the variation. Order-level arthropod assemblage similarity of
soil amendment (‘biosolids,’ ‘no biosolids’) at Highland Valley Copper and New Afton mines
were also assessed (Figure 2.12) and, once again, no pattern was detected. A similar study in
New Zealand compared arthropod assemblage to sites before and after biosolids application
(Denholm, 2003), and no additional taxa (family-level taxa and individual species taxa) were
detected post biosolids treatment.
Understanding the reclamation trajectory of arthropod assemblage post-mining
reclamation is an important objective on the road to achieving successful end land use. Below
sections in this discussion address the patterns between reclamation age and amendment to order
level taxa and indicator taxa. Analysing arthropod assemblages did not detect a successional
trajectory between reclamation and soil amendment. Other factors than reclamation age and
biosolids application may be responsible for the separation seen in Figure 2.11 and Figure 2.12,
such as elevation, soil chemistry and biology, moisture, vegetation, solar radiation and climate of
the sampled sites; and they should be included in future analyses. For example, Buchori et al.
(2018) conducted a study looking at arthropod diversity in post-mine reclaimed areas. The most
notable variables associated with insect diversity recovery were vegetation diversity and total
nitrogen content in the soil.
To further understand potential patterns within the data set, data were analyzed using
‘mine’ location and ‘reclaimed material’ as factors (Figure 2.13). The clear separation in Figure
2.13 suggests that the arthropod assemblages are correlated with the ‘mine’ and ‘reclaimed
material’ factors. The Highland Valley Copper sites are located on a combination of waste rock
and tailings, whereas the ‘reference’ sites are located on a naturally forested site. New Afton
sites occur on a historical tailings facility, and the reference sites are located in a natural
grassland.
The two mines (Highland Valley Copper and New Afton) have a variety of differences
between each other. For example, the elevation between the two sampled mines differs by 3001050 meters above sea level (New Afton 700 meters, Highland Valley Copper 1000-1750
meters). The distribution and range of plant and arthropod species are affected along elevation
gradients (Parmesan and Hanley, 2015; Gonzalez-Reyes et al., 2017). Change in insect taxa
along elevational gradients can be a direct or indirect response to other biota, including insect
host flora, as well as a response to predation, competition, and parasitoids (Hodkinson, 2005).

50
Altitude can affect morphology, phenology, nutrient concentrations, and reproduction in insect
host vegetation (Hodkinson, 2005) and these variations in vegetation can result in differences in
insect nutrient intake, growth rate, survival, and fecundity (Hodkinson, 2005).
Corresponding with the elevation change, the Highland Valley Copper mine and New
Afton mine also differ by their aforementioned BEC zone. Specifically, Highland Valley Copper
is located in the Montane Spruce zone, whereas New Afton is located in the Bunchgrass and
Ponderosa Pine zone. Using BEC zones to classify ecosystems allows for the uncovering of
community relationships within and between ecosystems, which can be applied to research and
management (MacKinnon et al., 1992). In this study, understanding the biotic and abiotic
environmental characteristics of the BEC zones associated with the two mines could aid in
explaining the difference in arthropod assemblage community.
The data point separation, seen in Figure 2.13, between sites that were reclaimed on
mining material by-products, tailings and waste rock, implies that the materials the sites were
built on affect arthropod assemblage composition. Waste rock is bedrock removed prior to the
mining process due to a lack of marketable materials (minerals, metal, bitumen). Comparatively,
tailings are the fine residuals after the marketable materials have been isolated from the ore.
These two mining by-products differ in moisture-retaining potential. In particular, tailings fine
size has slow draining, compared to waste rocks large porosity, resulting in tailing having a
greater potential for retaining moisture (Blowes, 2003). Though the by-product material that is
amended through the reclamation process is not a practice or material that is able to be changed,
it is interesting to note other environmental variables that can impact arthropod assemblage
compositions, post-mine reclamation.
Alpha diversity distinguishing reclamation sites
As a measure of species richness, alpha diversity (to the point of functional redundancy)
is associated with ecological stability and resilience (Naeem and Li, 1997), and can be influenced
by environmental and biological factors, including immigration, competitive exclusion,
predation, pathogens, herbivory, facilitation, resource availability, temporal variation, and habitat
disturbance (Brown et al., 2007). For example, increased immigration, impacted by population
size and distance between areas, can positively affect species richness (Brown et al., 2007).
Additionally, variance in population can be influenced by whether an arthropod is a strong and
weak disperser. Specifically, active dispersers (e.g., winged arthropods), compared to passive

51
dispersers (e.g., transported via wind or other animals), can colonize new areas more effectively
(Vannette and Fukami, 2017). It could then be anticipated that a greater amount of active
dispersing arthropods taxa would be identified in the new site than arthropods that are passive
dispersers.
The intermediate disturbance hypothesis, proposed by Connell (1978), could also be
relevant to the analyses in this study examining arthropod alpha diversity. The intermediate
disturbance hypothesis predicts that areas with both ‘high’ and ‘low’ levels of disturbance
determined by intensity, frequency, scale, and duration, will have less species richness than areas
with intermediate levels of disturbance. The rationale for the theory is that in areas with ‘low’
disturbance levels, species are excluded as a result of competition. In areas with ‘high’
disturbance levels, failure to survive of disturbance reduces species richness. Based on this
hypothesis, we would expect to see higher alpha diversity in reclaimed areas with intermediate
disturbance. However, in this study, the Kruskal-Wallis test (Table 2.4; Table 2.6) demonstrated
no significant differences in species richness between the sampled sites (reclamation age and soil
amendment, and reference); this is potentially a result of large variation between the replicates,
which could be addressed in future studies by increasing the number of samples collected
representing each treatment.
To further understand arthropod species richness response to reclamation, arthropods
were categorized to taxonomic order prior to analysis. At this taxonomic level, the order Diptera
OTUs (true flies) had greater diversity in ‘new’ sites compared to ‘old’ sites. Currently, having
160,000 species globally, the order Diptera is diverse both phylogenetically and functionally
(Courtney et al., 2017). Dipteran taxa can occupy a range of functional feeding guilds including
herbivores, predators, omnivores, detritivores, and parasites (Sarwar, 2020). Diptera can also
provide various ecosystem services, depending on species, such as, pollination, decomposition,
prey for other species, mobilizing nutrients, and regulating populations of prey species (Adler
and Courtney, 2019).
Diptera are commonly used as indicators of environmental characteristics, however, they
are typically identified to lower taxonomic levels (e.g., species, genus, family) opposed to order
level (De Souza et al., 2014; Lynggaard et al., 2020). For example, Lynggaard et al. (2020)
conducted a study examining the arthropod response to reclamation succession in post-mining
sites. They found evidence that different Diptera families were more associated with initial

52
stages (Family Micropeziidae), intermediate stages (Family Muscidae), and advanced stages
(Family Chironomidae) of succession (Lynggaard et al., 2020). This finding could illustrate that
different families of Diptera have varying environmental sensitivities, making it difficult to infer
the environmental relationships based on Diptera diversity and highlighting the need for
analyzing lower-level taxa, such as conducted in the indicator section of this study.
Similar to the order Diptera, Entomobryomorpha OTUs, springtails, were more diverse in
‘new’ sites than in ‘old’ sites. Likewise, the ‘reference’ sites had a greater richness of
Entomobryomorpha than the ‘old’ sites (Table 2.5; Figure 2.18). Fernandes et al. (2019) also
found that post-reclamation mine sites that were more recently reclaimed were typified by
Entomobryomorpha presence. Site factors including, pH, organic matter and nutrient availability
can affect Collembola diversity (Cassagne et al., 2003), and vegetation species richness has been
correlated with increased Collembolan diversity (Sabais et al., 2011). The reference sites in this
study could also be expected to have greater vegetation richness than reclaimed sites as
supported by a study assessing vegetation species-based diversity Highland Valley Copper
(Smyth et al., 2016). Additionally, a study conducted by Ji et al (2022) measured microbial
diversity in reclaimed mine sites over five unique reclamation ages and a reference site. They
found that more recently reclaimed sites had lower fungal diversity than the ‘reference’ site (Ji et
al., 2022). Studies have linked Collembola and soil fungal communities (biomass and diversity)
through grazing, dissemination of spores, soil mixing, and modifying available nutrients
(Klironomos and Kendrick, 1995; Coulibaly et al., 2019).
Moreover, Collembolans positively affect plant production by mobilising nutrients
through their consumption of fungi (Harris and Boerner, 1990). Similar to other decomposer
species, interspecific interactions between Collembola taxa may play a role in environmental
function (Eisenhauer et al., 2011). The presence of Collembola taxa in early phases of
reclamation help advance the return of soil function and play a meaningful part in soil restoration
(Rusek, 1998; Langmaack et al., 2001). Collembola taxa colonize specific soil depths (between 0
cm and 15 cm) and affect soil processes at these depths uniquely (Ponge, 2000); Eisenhauer et al.
(2011) theorized that the taxonomic diversity of Collembola affects litter decomposition and
vegetation success. Because samples were retrieved at the ground surface level, Collembola taxa
that colonize deeper soil depths were not analyzed in this study.

53
Contrary to the orders Diptera and Entomobryomorpha, the order Psocodea had greater
OTU richness on ‘old’ sites compared to ‘reference’ sites (Table 2.5). Psocodea, formerly
Psocoptera, are bark lice often found on trees or shrubs (Hollier, 2008). Simberloff and Wilson
(1969) examined the recovery of arthropods on sites that had been defaunated. They collected
arthropod recovery data over time and compared it to pre-defaunation arthropod communities.
They found that Psocodea taxa were one of first arthropod taxa to return to sites and produce
large populations (Simberloff and Wilson, 1969). Moreover, Psocodea were found in greater
abundance on the re-faunating site than generally found on undisturbed sites, potentially a result
of a lack of Psocodea predators on the re-faunating islands (Simberloff and Wilson, 1969).
Increased predation could contribute to reduced diversity in the ‘reference’ sites compared to the
‘old’ reclaimed sites, seen in the results of this thesis. However, if predation was the primary the
cause of decreased Psocodea diversity in the reference sites compared to the ‘old’ sites, it would
stand to reason that the ‘new’ sites would also be statistically more diverse than the reference
sites. Moreover, Gerlach et al. (2013) conducted a review of terrestrial arthropods as
bioindicators and noted that Psocodea most likely had little potential for inference, as they are
often generalists. It would be interesting for future studies to assess trophic interactions on postmining reclaimed sites compared to reference sites.
In addition to reclamation age, the effects of soil amendments (‘biosolids’, ‘no biosolids’,
‘reference’) on arthropod alpha diversity were examined. No significant difference in species
richness was detected between the sampled soil amendment sites (Table 2.6). Denholm (2003)
conducted a study examining biosolids affect on arthropods and also found that biosolid
applications did not significantly affect arthropod species diversity. However, this study did
identify patterns between biosolids as a soil amendment and Entobryomorpha, Formicidae, and
Thysanoptera. Similar to the pattern seen typifying reclamation age, differences in
Entomobryomorpha richness were statistically significant between ‘biosolids’ sites and
‘reference’ sites (Table 2.7; Figure 2.19).
In addition to a significant difference in Entomobryomorpha richness between sites,
Formicidae (ant) richness varied between sites with ‘biosolids’ and ‘no biosolids.’ Sites with ‘no
biosolids’ had significantly more Formicidae taxa richness (Table 2.7; Figure 2.19). Formicidae
taxa are expected, given that they are the most dominant insect in terrestrial ecosystems globally
(Wilson, 1990) and are paramount to environmental functioning (Higgins and Lindgren, 2009).

54
Buchari et al. (2018) explored the role of insects as bioindicators for reclamation success. In that
study, Formicidae were the most notable insect group in terms of species richness and
abundance. Indeed, it was concluded that the successes of post-reclaimed areas was best
evaluated by using ants as bioindicators (Buchari et al. 2018).
In some instances, Formicidae species richness has been more strongly associated with
soil properties than plant communities (Boulton et al., 2005). In particular, soil chemical
properties (Mg and Cu concentration), were negatively correlated with Formicidae richness
(Boulton et al., 2005). Interestingly, a study conducted by Gardner et al. (2012) found that sites
located at Highland Valley Copper mine had a positively correlated relationship between
biosolids and Mg (supported by Griebel et al.,1979; Hinesly et al., 1982). This relationship
between biosolids and increased Mg could potentially contribute to the decrease of Formicidae
richness on sites amended with biosolids, however, other factors are likely affecting the
relationship between sites with and without biosolids.
In addition to abiotic soil characteristics, Formicidae can be correlated with soil biota.
Anderson and Sparling (1997) found that Formicidae richness was positively correlated with
microbial biomass in sites subject to disturbance. Their findings point to the complementary
relationship between decomposition within the soil and biotic activity on the surface.
Furthermore, their study illustrates that Formicidae can indicate the status of environmental
functions, such as nutrient cycling (Anderson and Sparling, 1997), which highlights the potential
for Formicidae to act as bioindicators of reclamation. Despite not being included in this study,
soil microbial data were collected at the same time as arthropod samples at Highland Valley
Copper mine and New Afton mine. It would be interesting to analyze the relationships between
Formicidae richness and soil microbial community composition and biomass in the future.
Thysanoptera (thrip) was the final order to have a statistically significant correlation
between soil amendment sites and alpha diversity. A greater diversity of Thysanoptera OTUs
occurred on sites with ‘no biosolids’ compared to sites with ‘biosolids’. This result is
complemented by the indicator species analysis results that associate Haplothrips tenuipennis (a
Thysanoptera species) with sites amended without biosolids at Highland Valley Copper.
Thysanoptera taxa are known to be associated with vegetation, and many species breed
specifically in flowers (Mound et al., 2018). For example, Haplothrips spp. can be linked to
Asteraceae plants (Mound et al., 2018). That being said, Thysanoptera’s close association to

55
vegetation and flowers has resulted in them being considered a pest species. Thysanoptera, as an
order, appear to be understudied outside the context of pest management, making it difficult to
identify patterns between Thysanoptera diversity and sites with and without biosolids. Future
studies linking amendments, vegetation composition, and Thysanoptera biodiversity could
potentially uncover further links in bottom-up trophic interactions in a reclamation setting.
Overall, my results did not show a difference in alpha diversity between sites, when
analysed using the full data set. There was, however, a significant difference in the richness of
the orders Diptera, Entomobryomorpha, Psocodea, Thysanoptera, and the family Formicidae.
Researchers have noted that differences in alpha diversity may be difficult to detect or be
negligible due to the substitution of taxa (Dornelas et al., 2014). Furthermore, categorizing the
OTUs into higher taxonomic classifications (order/family) was helpful for making inferences
about the study sites for Entomobryomorpha and Formicidae. However, lesser studied orders
including Psocodea and Thysanoptera, as well as diverse orders such as Diptera provided less
insight into patterns between the study sites. Therefore, biodiversity composition between sites
could be a more informative measure of post-reclamation arthropod return than species richness
(Lynggaard et al., 2020).
Indicator arthropod taxa distinguishing reclamation sites
Understanding arthropod assemblage (dis)similarities and richness can illustrate an
overall picture of tested variables, in this case ‘reclamation age’ and ‘soil amendment’. However,
policy decisions and land management have previously been motived by indicator species (Ji et
al., 2013). Therefore, identifying (arthropod) indicator species for reclamation age and soil
amendments is also constructive. The presence of indicator taxa was measured using the
‘Indicspecies’ analyses, which is based on the indicator value index and identifies the association
of taxa with grouping variables.
Indicator analysis showed that despite statistically significant associations between
several taxa and site age, they did not demonstrate strong sensitivity and specificity values (near
1), indicating that they were not ideal indicator taxa (Table 2.8). To better understand indicator
taxa between sites, data were separated by mine. Because the mine locations were separated
using ordination (Figure 2.13), implying that there are differences in taxa composition, additional
analyses addressed the arthropod assemblage at each mine individually. This section will only
discuss indicator values greater than 0.65 for efficiency (Hammond et al., 2018).

56
The ‘new’ site at New Afton mine had the strongest arthropod indicator species
associations. In particular, OTU 0771 (family Heleomyzidae taxon) and OTU 1504 (Tapinoma
sessile) showed a strong affiliation with the ‘new’ sites (Table 2.10). Heleomyzidae (a true fly
taxon) was the taxon with the highest association with a treatment. The Heleomyzidae OTU was
associated with ‘new’ sites at the New Afton mine. Studies have noted the members of the
Heleomyzidae family can be found in various adverse locations, including caves (KocotZalewska and Woźnica, 2021), high elevation areas (Lee et al., 2015), and in arctic conditions
(Danks, 2004). Heleomyzidae’s presence in adverse environments indicates that the taxa has the
ability to survive in harsh environmental conditions, which may explain our observation that they
were primarily associated with the ‘new’, most recently disturbed, sites in this study.
The second taxon strongly associated with the ‘new’ sites at the New Afton mine was
Tapinoma sessile, an ant species. Tapinoma sessile is a small, potentially aggressive ant that is
common in North America (Higgins and Lindgren, 2009). Their nests are typically correlated
with wood but are also often located in moss or soil. Often undetected due to their small size
(Higgins and Lindgren, 2009), Salyer et al. (2014) found that Tapinoma sessile adapts quickly in
urban (disturbed) environments by taking advantage of unfamiliar resources. They also identified
the reduced ant species richness and consequent, interspecific competition, allowed Tapinoma
sessile to capitalize on the available resources (Salyer et al., 2014). Specifically, Tapinoma does
not compete effectively, and instead are more likely to be a colonizer taxon (Buczkowski and
Bennett, 2008). Given their adaptability to harsh environments, it is understandable that they
were the dominant taxa in the ‘new’ sites in this study.
Entomobrya unostrigata (cotton springtail) was strongly associated with the ‘new’ and
‘old’ reclaimed sites. A review of Entomobrya unostrigata noted that this Collembolan species
was an early colonizer in reclaimed mine sites (Greenslade, 1995). More specifically,
Entomobrya unostrigata was primarily detected in disturbed sites and was not commonly found
in areas with native vegetation (Greenslade, 1995). Greensade’s (1995) findings is aligned with
my results, that Entomobrya unostrigata was associated with both the ‘new’ and ‘old’ sites, but
not the ‘reference’ sites.
It is also interesting that ‘reference’ sites were significantly affiliated with substantially
more indicator taxa (36) than the ‘new’ sites (7), while the ‘old’ sites were not associated with
any indicator species. When data were separated by mine, the indicator species analysis for the

57
Highland Valley Copper ‘reference’ was associated with 36 taxa, but the New Afton ‘reference’
was not represented by any indicator taxa.
Similar to what was seen with reclamation age, the results of the complete soil
amendment dataset produced a variety of statistically significant indicator taxa without high
indicator values meaning that the arthropods did not demonstrate strong sensitivity and
specificity values, indicating that they were not ideal indicator taxa. Data were separated by
mines to identify patterns between indicator taxa and biosolids as a soil amendment; however,
biosolids were only applied at Highland Valley Copper mine. As seen in Table 2.12, two
Formicidae taxa are significantly associated with the ‘reference’ sites and a combination of the
‘reference’ sites and ‘no biosolids’ sites. This result is complemented by the results found in the
alpha diversity statistics from this study, where a greater Formicidae richness was associated
with the ‘no biosolids’ sites than the ‘biosolids’ sites.
Both strong indicator species associated with soil amendments belong to the genus
Formica. Ant species that belong to this genus have nests housing tens of thousands of worker
ants. Moreover, worker ants in the genus Formica are often observed collecting food (prey) for
their colony (Higgins and Lindgren, 2009). It stands to reason that the taxa belonging to the
genus Formica can make a notable impression of the functioning on a site, specifically through
predation on local prey species (Higgins and Lindgren, 2009).
Indeed, the ant species Formica neorufibarbis was predominantly associated with the
Highland Valley Copper mine ‘reference’ sites that were visually rich in woody materials.
Indeed, Formica neorufibarbis is frequently located in woody materials within clear-cuts
(Higgins and Lindgren, 2009). Concerning my findings, it could make sense that the species was
correlated to these sites because the ‘reference’ sites were visually rich in woody materials.
Formica subaenescens was associated with a combination of the soil amendment
variables ‘reference’ and ‘no biosolids’. Formica subaenescens are often found at disturbed sites,
nesting in the soil (Higgins and Lindgren, 2009). Similar to Formica neorufibarbis, Formica
subaenescens has an affinity for woody materials, more specifically for structurally intact wood
(Higgins and Lindgren, 2009). The strong association of this taxon with the combination of sites
could potentially be explained in part by the disturbance in the ‘no biosolids’ site and the visually
observed woody materials at the ‘reference’ sites. Like the relationship between indicator taxa
and reclamation age, there was a noticeable difference in the number of indicator taxa associated

58
with the treatment sites and the reference sites at Highland Valley Copper mine. Again, the
‘reference’ sites were associated with a greater number of indicator taxa (34) than with the
‘biosolids’ treatment (1) and the ‘no biosolids’ treatment (4).
Ultimately, the goal of indicator species analyses is to identify a relatively short list of
species that can be used as reclamation bioindicators (Denholm, 2003). For example, in this
study Formica neorufibarbis is a strong indicator species of the ‘reference’ variable at Highland
Valley Copper mine, for both reclamation age and soil amendment. The presence of this species
on treatment sites could suggest a trajectory towards natural forested sites free of previous
mining activity. Other environmental and situational factors, such as vegetation mix seeded, can
affect the trajectory of succession, relating to the available habitat and recovery of arthropod
taxa (Swab et al., 2017).
It is notable that no known invasive species, as listed by Invasive species of BC (n.d.) and
Government of BC (n.d.), were detected at any of the sites sampled in this study. In general,
invasive species success can be attributed to adverse conditions, such as disturbance regime,
anthropogenic influences, altered weather patterns (Dix et al., 2010). That is, invasive insect
species have better success adapting to altered environmental conditions than native species (Dix
et al., 2010). Invasive species may alter ecosystem structure and function by changing
environmental processes and food chains (Dix et al., 2010). These ecosystem alterations can
cause both environmental and economic challenges. Continued monitoring will best inform on
invasive species presence and management.
DNA metabarcoding as a research technique
Historically, arthropod monitoring methods primarily relied on morphological methods to
identify taxa. However, using morphological methods to identify arthropod taxa requires
significant time, labour, and expertise (Fernandes et al., 2018). Additionally, morphological
identification is particularly challenging for taxa with variable phenotypes over life stages. DNA
metabarcoding provides potential solutions for some of these concerns but does come with
important limitations.
PCR amplification bias can skew sequence abundance for specific taxa and may result in
missing some taxa altogether (Elbrecht and Leese, 2015). Additionally, the number of
sequencing reads can be affected by total biomass for an individual group, as well as the physical
size of individual arthropods (Elbrecht and Leese, 2015). For these reasons, neither absolute nor

59
relative abundance were used in this study. Instead, presence-absence was used to measure
arthropod biodiversity and assemblage.
Species level taxonomic assignment of OTUs in can be negatively impacted by
information gaps in biological databases, such as BOLD. Biological refence databases are
relatively new, and therefore are still acquiring taxonomic data (Beng et al., 2016; Yu et al.,
2012). Additionally, taxonomic resolution can face challenges due to short sequences, which can
complicate capture overall genetic diversity (Porter and Hajibabaei, 2018). These factors could
contribute to some (39) OTUs only being identified to order level, or higher, taxonomies.
DNA metabarcoding can fail to detect certain taxa; for example, Fernandes et al. (2019)
experienced difficulties detecting Hymenoptera in their study that used DNA metabarcoding to
identify terrestrial invertebrates that were collected on reclaimed mine sites. However, regardless
of current limitations, DNA metabarcoding identifies a greater diversity of taxa than alternative
identification methodologies. Specifically, Elbrecht et al. (2017) compared molecular OTU
identification methods, using a range of primer combinations, against morphological
identification methods and found that DNA metabarcoding ultimately detected a greater diversity
of macroinvertebrates than morphological methods. The overall benefits of DNA metabarcoding
held true despite the fact that morphological identification methods found taxa that were not
detected through DNA metabarcoding.
Overall, DNA metabarcoding offers an efficient, accessible, and accurate method for
environmental monitoring. Using the current reference databases, this study found differences
related to environmental variables and detected indicator taxa. Taxonomic identification and
precision continue to improve as more samples are identified and added to reference databases.

60
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69
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70

Chapter 3 Research Conclusions
3.1 Research Synthesis
The results of this study aid in reducing the knowledge gap for postmining reclamation
outcomes. Using novel methods (high-throughput DNA metabarcoding), this project contributes
to the improvement of planning and management practices, leading to more effective postmining ecosystem-recovery outcomes. In turn, the outcomes and methodologies of this project
can assist in the development of further advancements in mine reclamation as it relates to the
sustainable health of ecosystems, which are vital to the continued growth of BC’s communities
and economy.
In particular, this study investigated the effects different reclamation ages and soil
amendments have on arthropod assemblages, indicator taxa, and alpha diversity. In this study,
differences in arthropods between sampled areas were detected. First, the (dis)similarity of
arthropod assemblages between the reclamation age and amendment sites implied that neither
factor is the primary driver of arthropod composition; rather an external environmental factor is a
stronger driver of arthropod composition. Second, despite treatment correlations with higherlevel taxa, there was not a statistically significant relationship of overall species richness between
sites. Thirdly, indicator taxa analyses detected several taxa associated with study sites.
Examining these unique research questions, and comparing their outputs with each other, helped
navigate the story of reclamation trajectory. Individually, each analysis is limited in the scope of
the information that it can provide about the sites. For example, alpha diversity alone can
determine how many OTUs are present on study sites, however, it can not determine what
species are present on the sites. By examining both alpha diversity and indicator species, we see
that there is greater Formicidae richness in sites amended without biosolids, and we can also see
that none of the Formicidae species were the invasive European fire ant, Myrmica rubra, which
could negatively impact the ecosystem by displacing native arthropods.
3.2 Limitations
The purpose of this study was to shed light on arthropod recovery in a post-mine
environment. In general, field studies, compared to laboratory studies, are less able to control
additional environmental variables. Moreover, this study was descriptive in nature, as it was
based on observation and did not involve a manipulative study. For example, species-specific

71
relationships with soil amendments in a manipulative trial setting would expand the current
knowledge base.
Arthropod data used in this research were collected once per site during the summer of
2018. This study thus represented a ‘snapshot’ of arthropod assemblage and biodiversity. A onetime sampling methodology is associated with several limitations. Specifically, the idiosyncratic
behaviour of species (seasonality and life span) can impact the likelihood of capturing them at a
single collection time (Danks, 1996). Furthermore, passively detecting arthropods can also be
affected by their abundance in the given area, which could lead to reduced recognition of rare
taxa. Other studies have recommended collecting arthropod samples over different seasons to
capture a more complete view of species composition (Lynggaard et al., 2020; Danks, 1996).
Data were gathered from mines at a time that satisfied industry partner schedules. As a
result, the two mines were sampled four weeks apart from each other. Foster et al. (2020) found
that there were seasonal differences (early and late summer) in arthropod assemblages in the
Kamloops’ Lac du Bois grasslands. Their findings suggest that seasonal influences, such as
temperature and precipitation, impact arthropod assemblage composition (Foster et al., 2020; Liu
et al., 2013). Seasonality can also have indirect effects on arthropods communities through
availability of vegetation, litter, and soil moisture (Liu et al., 2013). For example, Denholm
(2003) highlighted the importance of understanding arthropod life cycles and behaviour to
explain biodiversity. In their experiment, they found craneflies (Tipulidae) were a negative
indicator of biosolids application; however, if sampling occurred before or after their
approximate 14-day temporal window of emergence, the relationship would go undetected
(Denholm, 2003).
In this study, sites reclaimed in different years were sampled to provide insight to how
arthropod assemblages change over time. Continual sampling at the same sites would deepen
insight to unique site-specific characteristics and development of arthropod assemblages. Two
‘reference’ sites were sampled near both mines for the purpose of comparing arthropod
assemblage and diversity at reclaimed mine sites to undisturbed sites. Ideally, arthropod
assemblages and biodiversity could be compared to pre-disturbance conditions, as each site may
have unique microsite conditions. However, opportunities to collect baseline data predisturbance can be limited; but are possible in some situations, as exemplified by Kega (2021).

72
3.3 Management Implications
This study intended to identify patterns between mine reclamation and arthropod
assemblage composition, ultimately aiming to better understand reclamation practices to reach
end land-use goals. As previously mentioned, reclamation efforts are commonly focused on
achieving end land use objectives, opposed to restoring the disturbed area to its original state
(Lima et al., 2015). End Land Use Plans, such as the ones developed by Highland Valley Copper
With engagement and consultation from Nlaka’pamux communities, and the ones developed by
New Afton with engagement and consultation from Stk’emlupsemc te Secwepemc Nation and
Tk’emlúps te Secwépemc can enhance a community-based approach to reclamation.
Specifically, end land use at both Highland Valley Copper and New Afton focuses on returning
post-mined areas to natural ecosystems, with potential uses including hunting and trapping
(Melaschenko et al., 2018; New Gold Inc., 2017). Studies such as this one aim to reduce the
knowledge gap and provide management recommendations, which ultimately strive to achieve a
functional ecosystem for end land uses. In particular, future explorations could conduct an
ecological assessment or multi-year monitoring, determining arthropod assemblage and
biodiversity, prior to mining an area. This would provide baseline data about the pre-disturbance
natural ecosystem which could be used as a comparison and/or target for reclaimed ecosystems.
Additionally, continued monitoring arthropod assemblage and biodiversity can inform on
potential ecological concerns, such as the presence of invasive species.
Historically, reclamation has been focused on vegetation health, but recently the focus
has shifted to include additional environmental characteristics such as overall biodiversity,
structure, and ecosystem function (Fraser et al., 2015). However, methods to measure whole
ecosystem reclamation trajectories are poorly understood and can be difficult for monitors to
select, as they are unfamiliar. This study aimed to reduce the knowledge gap of arthropod
recovery trajectories in a post-mining reclaimed area and demonstrate efficient DNA
methodologies for arthropod monitoring.
The use of DNA metabarcoding technology to characterize arthropod assemblages
reduces reliance on indicator taxa (Lindenmayer and Likens, 2011). Despite the practical benefits
of indicator taxa, outlined in chapter 2, using indicator taxa exclusively to monitor biodiversity
has unique limitations and challenges. Specifically, indicator taxa may be incorrectly used as a

73
surrogate of environmental conditions, causing confusion for policymakers (Lindenmayer and
Likens, 2011).
3.4 Future Research
Moving forward, research should work to inform what treatments or environmental
factors are correlated with arthropod recovery in mine sites through a whole ecosystem approach.
This research can be used by policymakers and land managers to aid post-mining reclamation by
creating optimal recovery conditions (Fernandes et al., 2018). Additionally, as climate change
progresses and temperatures increase, arthropods will have varied reactions, such as increasing
or decreasing ranges across altitudes (Hodkinson, 2005) and latitudes (Wilson and Fox, 2020). A
deeper understanding of insect response to climate conditions, such as temperature, will prepare
reclamation scientists with optimal practices to face upcoming challenges. Ultimately, this study
provides a benchmark for future research to build on, to understand optimal environmental
conditions to aid post-mining ecosystem recovery. Moreover, this study was descriptive in
nature, and identified multiple small patterns between arthropods and the conditions of the study
environments in an effort to interpret the results and provide recommendations. Based on these
results, future studies could look at correlations between vegetation (community and structure),
soil conditions (microbial and chemical), water availability, elevation, and arthropod biodiversity
and assemblages. For example, different plant communities and structures can affect predatory
success; despite greater food availability, some taxa favor sparce plant cover (Gaudreault et al.,
2019). Additionally, this study assessed the effects of biosolids as a soil amendment on arthropod
assemblages in a binary sense (biosolids and no biosolids). It would be interesting to conduct a
study comparing the effects of compost, biosolids, and manure on arthropods.

.

74
3.5 References
Danks, H. 1996. How to assess insect biodiversity without wasting your time. Biological Survey
of Canada (Terrestrial Arthropods). Canadian Museum of Nature. [cited December
2021]. Available from: http: //www.biology.ualberta.ca/bsc/briefs/brassess.htm
Denholm, P. 2003. Biodiversity, Biosolids and bioindicators in Pinus radiata D. Don planted
forests. University of Caterbury.
Fernandes, K., Van der Heyde, M., Bunce, M., Dixon, K., Harris, R., Wardell-Johnson, G.,
Nevill, P. 2018. DNA metabarcoding—a new approach to fauna monitoring in mine site
restoration. Restoration Ecology, 26(6):1098-1107. DOI: 10.1111/rec.12868
Fraser L, Harrower W, Garris H, Davidson S, Hebert, P, Howie R, Moody A, Polster D, Schmitz
O, Sinclair A, Starzomski B, Sullivan T, Turkington R, Wilson D. 2015. A call for
applying trophic structure in ecological restoration. The Journal of the Society for
Ecological Restoration, 23(5): 503-507. DOI 10.1111/rec.12225
Foster, J., Ploughe, L, Akin-Fajiye, M., Singh, J., Bottos, E., Van Hamme, J., Fraser, L. 2020.
Exploring trophic effects of spotted knapweed (Centaurea stoebe L.) on arthropod
diversity using DNA metabarcoding. Food Webs, 24:2352-2496. DOI:
10.1016/j.fooweb.2020.e00157.
Gaudreault, E., Lalonde, R., Lawson, K., Doyle, F., Hodges K. 2019. Biosolids application
increases grasshopper abundance in the short term in a northern Canadian grassland. The
Rangeland Journal. DOI: 10.1071/RJ18075
Hodkinson, I. 2005. Terrestrial insects along elevation gradients: species and community
responses to altitude. Biological Reviews, 80: 489-513. DOI:
10.1017/S1464793105006767
Kega, S. 2021. Evaluating the potential for increased forage productivity and soil carbon
sequestration in strip thinned silvopastures. Thompson Rivers University. [cited
December 2021]. Available from:
https://www.tru.ca/__shared/assets/Steven_Kega_MSc_ENVS_Thesis53099.pdf
Lima, A., Mitchella, K., O’Connell, D., Verhoeven, J., Van Cappellena, P. 2015. The legacy of
surface mining: Remediation, restoration, reclamation and rehabilitation. Environmental
Science and Policy, 66: 227-233.
Liu, R., Zhu, F., Song, N., Yang, X., Chai, Y. 2013. Seasonal distribution and diversity of
ground arthropods in microhabitats following a shrub plantation age sequence in
desertified steppe. PLoS ONE 8(10): e77962. DOI:10.1371/journal.pone.0077962.
Lynggaard, C., Yu, D., Oliveria, G., Caldeira, C., Ramos, S., Ellegaard, M., Gilbert, T.,
Gastauer, M., Bohmann, K. 2020. DNA-based arthropod diversity assessment in
Amazonian iron mine lands show ecological succession towards undisturbed reference
sites. Frontiers in Ecology and Evolution, 8:59097. DOI:0.3389/fevo.2020.590976

75
Lindenmayer, D., Likens, G. 2011. Direct measurement versus surrogate indicator species for
evaluating environmental change and biodiversity loss. Ecosystems 14:47-59. DOI:
10.1007/s10021-010-9394-6.
Melaschenko, N., Dickson, J., Berg, K., Straker, J. 2018. A Community-Based Approach to End
Land Use Planning at Highland Valley Copper. [cited 2020 Oct 8]. Available from:
https://open.library.ubc.ca/cIRcle/collections/59367/items/1.0374930
New Gold Inc. 2017. New Afton: 2017 Annual Reclamation Report. Kamloops, BC.
Wilson, R., Fox, R. 2020. Insect responses to global change offer signposts for biodiversity and
conservation. Entomological Ecology, 46(4):699-717. DOI:10.1111/een.12970.

A.1

Appendix A OTUs used in statistical analyses
Table A.1. Operation taxonomic units of arthropods, collected from Highland Valley Copper and New Gold Inc. New Afton used in data analyses
OTU
0001
0010
0100
1004
1006
0101
1010
0102
1027
1039
0104
1040
1042
1048
1055
0106
1060
1068

Taxonomy
GS|99.3|BOLD:AAL2821_KR5
04455
GS|96.3|BOLD:AAG8962_KR
042869
GS|90.7|BOLD:AAC6116_KR0
39436
GS|91.0|BOLD:AAA8764_JN2
94644
GS|86.7|BOLD:ACA5986_NA
GS|97.7|BOLD:AAN6555_MF
606846
GS|92.0|BOLD:ADC9253_NA
GS|91.0|BOLD:ACK5012_KM
909774
GS|94.7|BOLD:AAG2875_MF
932157
GS|99.3|BOLD:AAH0413_NA
GS|100.0|BOLD:AAL2821_MF
889772
GS|95.7|BOLD:AAA8764_JN2
94644
GS|100.0|BOLD:AAP7809_K
M843868
GS|97.9|BOLD:AAF2735_NA
GS|85.7|BOLD:ACZ1106_KU9
16435
GS|90.3|BOLD:AAP8157_KM
952442
GS|98.0|BOLD:AAA2674_KR
971587
GS|90.5|BOLD:AAM7579_NA

Kingdom
Animalia

Phylum
Arthropoda

Class
Insecta

Order
Diptera

Family
Muscidae

Genus
Phaonia

Species

Animalia

Arthropoda

Insecta

Hemiptera

Nabidae

Nabicula

Nabicula nigrovittata

Animalia

Arthropoda

Insecta

Hemiptera

Scutelleridae

Homaemus

Homaemus bijugis

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia
Animalia

Arthropoda
Arthropoda

Lepidocyrtus

Lepidocyrtus cyaneus

Arthropoda
Arthropoda

Coleoptera
Entomobryomo
rpha
Hemiptera
Diptera

Entomobryidae

Animalia
Animalia

Insecta
Collembo
la
Insecta
Insecta

Cicadellidae
Sciaridae

Ceratagallia

Animalia

Arthropoda

Insecta

Hemiptera

Cicadellidae

Ceratagallia

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Coleoptera
Diptera

Muscidae

Phaonia

Phaonia apicalis

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia

Arthropoda

Insecta

Coleoptera

Staphylinidae

Atheta

Atheta capsularis

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Coleoptera
Coleoptera

Scarabaeidae

Aphodius

Aphodius zenkeri

Animalia

Arthropoda

Insecta

Diptera

Mycetophilidae

Katatopygia

Animalia

Arthropoda

Insecta

Diptera

Drosophilidae

Drosophila

Animalia

Arthropoda

Insecta

Coleoptera

Dermestidae

Dermestes

Phaonia apicalis

Drosophila

subquinaria
Dermestes

marmoratus

A.2
1069

Animalia

Arthropoda

Animalia

1104

GS|90.7|BOLD:AAN6562_JN2
90616
GS|96.3|BOLD:AAE0406_KR8
96490
GS|78.7|BOLD:ACO5516_NA
GS|81.4|BOLD:AEB3573_NA
GS|88.4|BOLD:AAP7095_KM
844723
GS|100.0|BOLD:AAL5087_MF
635391
GS|92.3|BOLD:AAU6111_NA

Entomobryomo
rpha
Hymenoptera

Entomobryidae

Arthropoda

Collembo
la
Insecta

Formicidae

Formica

Animalia
Animalia
Animalia

Arthropoda
Arthropoda
Arthropoda

Insecta
Insecta
Insecta

Diptera
Archaeognatha
Coleoptera

Dolichopodidae

Thinophilus

Staphylinidae

Tachinus

Animalia

Arthropoda

Insecta

Coleoptera

Staphylinidae

Philonthus

Philonthus cognatus

Animalia

Arthropoda

Insecta

Orthoptera

Ceuthophilu
s

Ceuthophilus agassizii

GS|75.3|BOLD:ADA7549_NA

Animalia

Arthropoda

Insecta

Archaeognatha

Rhaphidophorid
ae
Machilidae

0111
1112

GSL|94.3|BOLD:AAB3450_N
A
GS|96.7|BOLD:AAU6111_NA

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Animalia

Arthropoda

Insecta

Orthoptera

Animalia

Arthropoda

Insecta

Orthoptera

Ceuthophilu
s
Camnula

Ceuthophilus agassizii

GS|92.8|BOLD:AAA8764_JN2
94644
GS|100.0|BOLD:ACE3663_NA
GS|93.3|BOLD:AAA8764_JN2
94644
GS|100.0|BOLD:AAD6543_K
R934988
GS|82.7|BOLD:AAP7796_JF88
8053
GS|98.4|BOLD:AAV1530_JN3
09491
GS|99.6|BOLD:AAF7755_MG
477257
GS|97.0|BOLD:AAU6111_NA

Rhaphidophorid
ae
Acrididae

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Coleoptera
Orthoptera

Carabidae
Acrididae

Amara
Camnula

Amara farcta
Camnula pellucida

Animalia

Arthropoda

Insecta

Hymenoptera

Formicidae

Aphaenogaster

Animalia

Arthropoda

Insecta

Coleoptera

Curculionidae

Aphaenogast
er
Cossonus

Animalia

Arthropoda

Insecta

Archaeognatha

Machilidae

Animalia

Arthropoda

Insecta

Coleoptera

Carabidae

Cymindis

Cymindis cribricollis

Animalia

Arthropoda

Insecta

Orthoptera

Rhaphidophorid
ae

Ceuthophilu
s

Ceuthophilus agassizii

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Archaeognatha
Orthoptera

Acrididae

Camnula

Camnula pellucida

1163

GS|81.3|BOLD:AEB3573_NA
GS|94.7|BOLD:AAA8764_JN2
94644
GS|95.3|BOLD:AAU6111_NA

Animalia

Arthropoda

Insecta

Orthoptera

Rhaphidophorid
ae

Ceuthophilu
s

Ceuthophilus agassizii

1165

GS|82.3|BOLD:AEB3573_NA

Animalia

Arthropoda

Insecta

Archaeognatha

1072
1076
0109
0011
0110

1125
1127
0113
1132
0114
1141
1144
0115
1152
0116
1162

Formica lasioides

Camnula pellucida

occidentalis
Cossonus piniphilus

A.3
1166

Animalia

Arthropoda

Insecta

Hemiptera

1167

GS|77.6|BOLD:AAG2875_KR
569482
GS|96.0|BOLD:ACJ0553_NA

Animalia

Arthropoda

Opiliones

1174

GS|96.7|BOLD:AAB3450_NA

Animalia

Arthropoda

Arachnid
a
Insecta

0119

GS|98.0|BOLD:ACF5385_KJ9
64115
GS|100.0|BOLD:AAG5198_K
M843557
GS|93.4|BOLD:AAA8764_KM
533615
GS|73.3|BOLD:AAW9344_NA

Animalia

Arthropoda

Animalia

GS|95.3|BOLD:AAA8764_JN2
94649
GS|100.0|BOLD:AAA8914_K
M824705
GS|87.4|BOLD:ACP5629_NA
GS|100.0|BOLD:ACC6491_K
M848552
GS|100.0|BOLD:AAD0461_KP
653242
GS|93.0|BOLD:AAY6676_KM
838130
GS|88.7|BOLD:ACP5629_NA
GS|96.3|BOLD:AAN6561_JN2
90615
GS|100.0|BOLD:ACF2871_KR
923535
GS|100.0|BOLD:ACM2411_K
R683544
GS|99.7|BOLD:AAL7523_HM
860450
GSL|91.0|BOLD:AAB3450_N
A
GSL|89.3|BOLD:ACF3208_NA
GS|99.7|BOLD:ACF3749_KR6
88854
GS|98.5|BOLD:AAG8804_NA

0012
1205
1207
1219
0122
1223
1224
0123
1230
1235
1236
0124
1247
0127
1270
1274
0128
1280

Cicadellidae

Ceratagallia

Orthoptera

Acrididae

Circotettix

Circotettix

Insecta

Coleoptera

Carabidae

Amara

carlinianus
Amara alpina

Arthropoda

Insecta

Coleoptera

Curculionidae

Otiorhynchus ovatus

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Otiorhynchu
s
Camnula

Animalia

Arthropoda

Insecta

Diptera

Asilidae

Ospriocerus

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Ospriocerus aeacus
Camnula pellucida

Animalia

Arthropoda

Araneae

Gnaphosidae

Zelotes

Zelotes fratris

Animalia
Animalia

Arthropoda
Arthropoda

Arachnid
a
Insecta
Insecta

Diptera
Coleoptera

Staphylinidae

Earota

Earota dentata

Animalia

Arthropoda

Araneae

Gnaphosidae

Animalia

Arthropoda

Opiliones

Sclerosomatidae

Haplodrassu
s
Togwoteeus

Togwoteeus biceps

Animalia
Animalia

Arthropoda
Arthropoda
Arthropoda

Diptera
Entomobryomo
rpha
Hymenoptera

Entomobryidae

Animalia

Arachnid
a
Arachnid
a
Insecta
Collembo
la
Insecta

Formica

Formica

Animalia

Arthropoda

Insecta

Diptera

Cecidomyiidae

Animalia

Arthropoda

Insecta

Diptera

Anthomyiidae

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Orthoptera
Diptera

Acrididae
Phoridae

Animalia

Arthropoda

Insecta

Hemiptera

Cicadellidae

Formicidae

Camnula pellucida

neorufibarbis
Eutrichota

Eutrichota tarsata

Megaselia
Psammotetti
x

Psammotettix confinis

A.4
1287
0129
1293
0013
1300
1303
1310
1314
0132
1339
0134
1343
1344
1346
0135
1350
0136
1363
1367
1370
1380
0014

GS|76.3|BOLD:ACG9299_NA
GS|90.6|BOLD:AAP9950_KR9
87592
GS|100.0|BOLD:ACI8307_MF
936428
GS|100.0|BOLD:AAV1530_JN
309491
GS|93.3|BOLD:ACJ0553_NA

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Diptera
Diptera

Mycetophilidae

Animalia

Arthropoda

Insecta

Hymenoptera

Braconidae

Animalia

Arthropoda

Insecta

Archaeognatha

Machilidae

Animalia

Arthropoda

Opiliones

GS|89.2|BOLD:AAC8406_MF
937863
GS|79.0|BOLD:ACA5986_NA
GS|99.7|BOLD:AAC6116_KR0
32723
GS|100.0|BOLD:ABA5839_M
G403656
GS|87.3|BOLD:ACP5629_NA
GS|100.0|BOLD:ABY7010_N
A
GS|87.3|BOLD:AAP8157_KM
952442
GSL|90.3|BOLD:ACF3208_NA

Animalia

Arthropoda

Arachnid
a
Insecta

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Animalia

Arthropoda

Animalia
Animalia

GS|100.0|BOLD:ABZ3849_MF
831862
GS|96.3|BOLD:ACJ8525_KM8
41491
GS|89.7|BOLD:ABX4044_NA
GS|83.3|BOLD:ACM2566_KR
147632
GS|89.1|BOLD:ACP5629_NA
GS|97.6|BOLD:AAE0406_KR8
79680
GS|100.0|BOLD:AAA9476_M
F813717
GS|89.3|BOLD:ACG3239_KM
955768
GS|99.3|BOLD:ACI5842_KM6
42700

Hemiptera

Cordyla

Rhyparochromid
ae

Sphragisticu
s

Sphragisticus

Coleoptera
Hemiptera

Scutelleridae

Homaemus

Homaemus bijugis

Insecta

Hemiptera

Cicadellidae

Euscelis

Arthropoda
Arthropoda

Insecta
Insecta

Diptera
Diptera

Fanniidae

Fannia

Animalia

Arthropoda

Insecta

Diptera

Mycetophilidae

Katatopygia

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Animalia

Arthropoda

Insecta

Hemiptera

Cicadellidae

Animalia

Arthropoda

Insecta

Coleoptera

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Animalia
Animalia

Arthropoda
Arthropoda

Animalia

Arthropoda

Animalia
Animalia

nebulosus

Diplocolenus evansi

Staphylinidae

Diplocolenu
s
Quedius

Coleoptera
Archaeognatha

Nitidulidae
Meinertellidae

Urophorus
Machilinus

Urophorus humeralis

Insecta
Insecta

Diptera
Hymenoptera

Formicidae

Formica

Formica lasioides

Araneae

Linyphiidae

Grammonota

Grammonota gentilis

Arthropoda

Arachnid
a
Insecta

Diptera

Sciaridae

Claustropyg
a

Arthropoda

Insecta

Diptera

Hybotidae

A.5
0140
1400
1401
1418
0142
1423
1424
1430
1431
1455
1457
0146
1464
0147
1477
1479
1481
1486
1488
0149
1490
1492

GS|100.0|BOLD:ACC5897_K
M841972
GS|98.0|BOLD:AAG2472_KR
689987
GS|100.0|BOLD:AAV1530_JN
309491
GS|96.0|BOLD:AAU6111_NA

Animalia

Arthropoda

Insecta

Coleoptera

Staphylinidae

Animalia

Arthropoda

Insecta

Diptera

Anthomyiidae

Animalia

Arthropoda

Insecta

Archaeognatha

Machilidae

Animalia

Arthropoda

Insecta

Orthoptera

Animalia

Arthropoda

Insecta

Diptera

Ceuthophilu
s
Paradidyma

Ceuthophilus agassizii

GS|100.0|BOLD:AAG2341_K
R693011
GS|90.3|BOLD:ACF3208_NA
GS|87.7|BOLD:ACP5629_NA
GS|98.0|BOLD:AAA8764_JN2
94532
GS|97.3|BOLD:ACX6073_MG
035016
GS|90.9|BOLD:AAG2875_MF
938947
GS|90.7|BOLD:AAH4207_HM
412662
GS|97.0|BOLD:AAP9080_KM
945424
GS|99.7|BOLD:AAH4153_KM
631260
GS|100.0|BOLD:ACU2723_M
F760195
GS|96.7|BOLD:AAA8764_JN2
94649
GS|92.5|BOLD:AAG2875_MG
509309
GS|83.5|BOLD:ACP5629_NA
GS|100.0|BOLD:ACM2385_M
F891107
GS|83.2|BOLD:AAA8764_JN2
94644
GS|82.0|BOLD:AEB3573_NA
GS|98.3|BOLD:ACG1460_NA
GS|88.3|BOLD:ADR1193_NA

Rhaphidophorid
ae
Tachinidae

Animalia
Animalia
Animalia

Arthropoda
Arthropoda
Arthropoda

Insecta
Insecta
Insecta

Orthoptera
Diptera
Orthoptera

Acrididae

Conozoa

Conozoa sulcifrons

Acrididae

Camnula

Camnula pellucida

Animalia

Arthropoda
Arthropoda

Entomobryomo
rpha
Hemiptera

Entomobryidae

Animalia

Collembo
la
Insecta

Cicadellidae

Ceratagallia

Animalia

Arthropoda

Insecta

Diptera

Chloropidae

Meromyza

Animalia

Arthropoda

Insecta

Diptera

Mycetophilidae

Leia

Animalia

Arthropoda

Insecta

Diptera

Chloropidae

Animalia

Arthropoda

Insecta

Diptera

Anthomyiidae

Delia

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Animalia

Arthropoda

Insecta

Hemiptera

Cicadellidae

Ceratagallia

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Diptera
Diptera

Muscidae

Coenosia

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia
Animalia
Animalia

Arthropoda
Arthropoda
Arthropoda

Insecta
Insecta
Insecta

Archaeognatha
Coleoptera
Coleoptera

Carabidae

Amara

Amara fortis

Delia

Camnula pellucida

A.6
1495
1499
0015

1500
1502
1504
0152
1522
1528
0153
0154
1542
1545
1548
1550
1551
1552
1554
1560
1561

GS|92|BOLD:AAA3898_KF60
5178
GS|97.0|BOLD:AAH6630_KJ4
45452
GS|100.0|BOLD:AAA1468_K
R801242

Animalia

Arthropoda

Insecta

Hymenoptera

Formicidae

Tapinoma

Tapinoma sessile

Animalia

Arthropoda

Entomobrya

Entomobrya

Arthropoda

Entomobryomo
rpha
Hymenoptera

Entomobryidae

Animalia

Collembo
la
Insecta

Formicidae

Formica

GS|83.9|BOLD:AAA8764_JN2
94649
GSL|84.4|BOLD:AAI9028_NA
GS|99.0|BOLD:AAA3898_KR
791510
GS|99.3|BOLD:ACE2096_KM
844015
GS|90.3|BOLD:AAG2875_KR
037999
GS|98.3|BOLD:ACF6995_KR5
77795
GS|81.7|BOLD:AEB3573_NA
GS|100.0|BOLD:AAA7374_JN
285899
GS|94.3|BOLD:AAY3979_KR
457459
GS|94.3|BOLD:ACC5897_KM
849278
GS|96.3|BOLD:ACK7799_KM
846655
GS|88.6|BOLD:AAA8764_JN2
94644
GS|93.7|BOLD:ACJ0553_NA

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

fusca var. complex)
Camnula pellucida

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Orthoptera
Hymenoptera

Acrididae
Formicidae

Tapinoma

Tapinoma sessile

Animalia

Arthropoda

Insecta

Coleoptera

Staphylinidae

Atheta

Animalia

Arthropoda

Insecta

Hemiptera

Cicadellidae

Ceratagallia

Animalia

Arthropoda

Insecta

Hemiptera

Cicadellidae

Ceratagallia

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Archaeognatha
Diptera

Syrphidae

Animalia

Arthropoda

Insecta

Diptera

Tachinidae

Animalia

Arthropoda

Insecta

Coleoptera

Staphylinidae

Animalia

Arthropoda

Insecta

Coleoptera

Animalia

Arthropoda

Insecta

Orthoptera

Animalia

Arthropoda

Opiliones

GS|96.7|BOLD:AAE0406_KR8
97079
GS|96.7|BOLD:AAZ1683_MG
170293
GS|99.1|BOLD:AAP7044_KM
848665
GS|75.7|BOLD:AAC9088_KM
570098

Animalia

Arthropoda

Arachnid
a
Insecta

Animalia

Arthropoda

Animalia
Animalia

unostrigata
Formica subaenescens
(formerly Formica

Ceratagallia

sanguinolenta
Ceratagallia

sanguinolenta
Sphaerophor
ia
Freraea

Sphaerophoria

Leiodidae

Neoeocatops

Neoeocatops

Acrididae

Camnula

decipiens
Camnula pellucida

Hymenoptera

Formicidae

Formica

Formica lasioides

Insecta

Hemiptera

Miridae

Psallovius

Psallovius piceicola

Arthropoda

Insecta

Coleoptera

Staphylinidae

Phloeostiba

Phloeostiba lapponica

Arthropoda

Insecta

Diptera

Tipulidae

Tipula

Tipula angulata

philanthus
Freraea gagatea

A.7
1568
1574
1576
1579
1580
1585
1586
0159
0016
0160
1601
1623
0163
1645
0166
1673
1678
1679
1697
0017
0170
1700

GS|99.7|BOLD:AAI5560_KR0
44828
GS|95.7|BOLD:AAA8764_MG
468655
GSL|94.0|BOLD:ACF3208_NA
GS|96.0|BOLD:AAG5198_KJ9
63586
GS|100.0|BOLD:AAA4977_K
R934170
GS|98.9|BOLD:ABA5839_KR5
83463
GS|99.3|BOLD:AAG2877_MF
832746
GS|97.0|BOLD:ACF9170_KR7
22833
GS|92.0|BOLD:ABA2351_NA

Animalia

Arthropoda

Insecta

Hemiptera

Scutelleridae

Eurygaster

Eurygaster amerinda

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Orthoptera
Coleoptera

Acrididae
Curculionidae

Otiorhynchus ovatus

Animalia

Arthropoda

Insecta

Hymenoptera

Formicidae

Otiorhynchu
s
Formica

Animalia

Arthropoda

Insecta

Hemiptera

Cicadellidae

Euscelis

Animalia

Arthropoda

Insecta

Hemiptera

Cicadellidae

Cuerna

Cuerna cuesta

Animalia

Arthropoda

Insecta

Diptera

Sphaeroceridae

Pullimosina

Pullimosina moesta

Animalia

Arthropoda

Insecta

Diptera

Fanniidae

Fannia

GS|99.7|BOLD:AAD5009_KP6
51027
GS|97.5|BOLD:AAP7044_KR4
81778
GS|83.0|BOLD:AAI9028_NA
GS|100.0|BOLD:ACA9180_KR
482485
GS|99.3|BOLD:AAG8681_KR
918070
GS|97.0|BOLD:ACJ0553_NA

Animalia

Arthropoda

Araneae

Gnaphosidae

Gnaphosa

Gnaphosa muscorum

Animalia

Arthropoda

Arachnid
a
Insecta

Coleoptera

Staphylinidae

Phloeostiba

Phloeostiba lapponica

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Orthoptera
Coleoptera

Acrididae
Melyridae

Cratypedes
Hypebaeus

Cratypedes neglectus

Animalia

Arthropoda

Insecta

Hemiptera

Cicadellidae

Psammotetti
x

Psammotettix

Animalia

Arthropoda

Opiliones

GS|92.3|BOLD:AAA8764_JN2
94644
GS|92.7|BOLD:AAM7579_NA

Animalia

Arthropoda

Arachnid
a
Insecta

Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia

Arthropoda

Insecta

Coleoptera

Dermestidae

Dermestes

Dermestes

GS|99.7|BOLD:AAE1002_NA
GS|83.4|BOLD:ABW2776_NA
GS|81.3|BOLD:AAG6186_HM
416864
GS|100.0|BOLD:AAW1617_K
R486565
GS|88.8|BOLD:AAG2442_KM
864353

Animalia
Animalia
Animalia

Arthropoda
Arthropoda
Arthropoda

Insecta
Insecta
Insecta

Hymenoptera
Orthoptera
Archaeognatha

Formicidae
Acrididae
Meinertellidae

Formica

marmoratus
Formica subpolita

Animalia

Arthropoda

Insecta

Coleoptera

Staphylinidae

Aleochara

Aleochara rubricalis

Animalia

Arthropoda

Insecta

Diptera

Anthomyiidae

Zaphne

Zaphne implicata

Formica

neorufibarbis

Hypebaeus bicolor

lividellus

A.8
0171
1717

GS|96.0|BOLD:ABX3986_NA
GS|99.7|BOLD:ACD0897_MF
762743
GS|100.0|BOLD:ABZ3849_MF
831862
GS|93.3|BOLD:ACW8722_KR
805644
GS|95.0|BOLD:ACF3208_NA
GS|79.3|BOLD:AAZ7477_NA

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Coleoptera
Diptera

Anthicidae
Anthomyiidae

Anthicus

Anthicus punctulatus

Animalia

Arthropoda

Insecta

Hemiptera

Cicadellidae

Diplocolenus evansi

Animalia

Arthropoda

Insecta

Hymenoptera

Formicidae

Diplocolenu
s
Myrmica

Animalia
Animalia

Arthropoda
Arthropoda

Orthoptera
Opiliones

Acrididae

Conozoa

Conozoa sulcifrons

Animalia

Arthropoda

Diptera

Mycetophilidae

Phronia

Animalia

Arthropoda

Insecta

Lepidoptera

Gelechiidae

Chionodes

Animalia

Arthropoda

Insecta

Diptera

Phoridae

Megaselia

Animalia

Arthropoda

Lepidocyrtus

Lepidocyrtus cyaneus

Arthropoda

Entomobryomo
rpha
Diptera

Entomobryidae

Animalia

Collembo
la
Insecta

Animalia
Animalia

Arthropoda
Arthropoda

Chorthippus

Chorthippus montanus

Arthropoda

Orthoptera
Entomobryomo
rpha
Coleoptera

Acrididae
Entomobryidae

Animalia

Insecta
Collembo
la
Insecta

Staphylinidae

Phloeostiba

Phloeostiba lapponica

1776

GS|99.3|BOLD:AAP6497_MG
091533
GS|96.3|BOLD:AAH4273_KM
545000
GS|98.0|BOLD:ACF3950_KM
633224
GS|100.0|BOLD:AAN4465_K
M623929
GS|100.0|BOLD:ACX5751_KT
104856
GS|96.6|BOLD:AAG5331_NA
GS|96.3|BOLD:AAN6561_JN2
90615
GS|95.2|BOLD:AAP7044_KR4
87949
GS|89.1|BOLD:AAE2480_NA

Insecta
Arachnid
a
Insecta

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Spharagemon

1778

GS|94.1|BOLD:AAU6111_NA

Animalia

Arthropoda

Insecta

Orthoptera

0179

GS|86.0|BOLD:ABY0171_NA

Animalia

Arthropoda

Insecta

Hemiptera

0018

GS|99.7|BOLD:AAG8804_NA

Animalia

Arthropoda

Insecta

Hemiptera

Rhaphidophorid
ae
Rhyparochromid
ae
Cicadellidae

Spharagemo
n
Ceuthophilu
s

Psammotetti
x

Psammotettix confinis

0180

GS|79.0|BOLD:ACI5842_KM6
42700
GS|98.7|BOLD:ACE4532_KR0
44858
GS|88.7|BOLD:AAN6145_KR
489904
GS|100.0|BOLD:AAF2735_NA

Animalia

Arthropoda

Insecta

Diptera

Hybotidae

Animalia

Arthropoda

Insecta

Hemiptera

Cicadellidae

Latalus

Latalus missellus

Animalia

Arthropoda

Insecta

Coleoptera

Staphylinidae

Philonthus

Philonthus varians

Animalia

Arthropoda

Insecta

Coleoptera

0172
1720
1728
0173
1733
1742
1749
0175
1751
1758
1769
1775

0181
0182
0183

Sciaridae

campestris
Ceuthophilus agassizii

A.9
0184
0185
0189
0019
0191
0194
0197
0198
0199
0002
0200
0202
0204
0205
0206
0207
0208
0021
0210
0211
0213

GS|85.7|BOLD:ACB8951_MF7
47714
GS|99.3|BOLD:ACG1315_KF5
49892
GS|100.0|BOLD:ACZ4231_K
M532906
GS|100.0|BOLD:ACB0775_KR
694678
GS|100.0|BOLD:ACL6983_K
M645139
GS|100.0|BOLD:ACG1894_K
M844736
GS|83.3|BOLD:AEB3573_NA
GS|92.4|BOLD:AAA8764_JN2
94644
GS|100.0|BOLD:ABA1213_KR
633872
GS|100.0|BOLD:AAE0406_KR
897079
GS|100.0|BOLD:ABZ2976_KR
970957
GS|100.0|BOLD:AAG7279_JN
301730
GS|100.0|BOLD:AAG1503_KP
046668
GS|89.7|BOLD:AAN4488_KP8
45857
GS|100.0|BOLD:AAA6915_K
M840627
GS|90.1|BOLD:ACI5842_KM6
25260
GS|98.3|BOLD:AAN6561_JN2
90615
GS|100.0|BOLD:AAI2023_NA
GS|98.3|BOLD:ACS0312_KR4
59682
GS|100.0|BOLD:AAE2976_GQ
373468
GS|91.0|BOLD:AAW9040_KR
579838

Animalia

Arthropoda

Insecta

Psocodea

Lachesillidae

Lachesilla

Animalia

Arthropoda

Insecta

Coleoptera

Elateridae

Selatosomus

Animalia

Arthropoda

Insecta

Thysanoptera

Thripidae

Frankliniella

Animalia

Arthropoda

Insecta

Diptera

Hybotidae

Animalia

Arthropoda

Insecta

Diptera

Chloropidae

Olcella

Animalia

Arthropoda

Insecta

Coleoptera

Staphylinidae

Phloeostiba

Phloeostiba lapponica

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Archaeognatha
Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia

Arthropoda

Insecta

Diptera

Phoridae

Megaselia

Animalia

Arthropoda

Insecta

Hymenoptera

Formicidae

Formica

Formica lasioides

Animalia

Arthropoda

Insecta

Diptera

Drosophilidae

Drosophila

Drosophila munda

Animalia

Arthropoda

Insecta

Diptera

Sphaeroceridae

Eulimosina

Eulimosina ochripes

Animalia

Arthropoda

Insecta

Diptera

Chloropidae

Tricimba

Tricimba

Animalia

Arthropoda

Insecta

Thysanoptera

Phlaeothripidae

Haplothrips

Haplothrips

Animalia

Arthropoda

Araneae

Linyphiidae

Islandiana

tenuipennis
Islandiana holmi

Animalia

Arthropoda

Arachnid
a
Insecta

Diptera

Hybotidae

Animalia

Arthropoda
Arthropoda
Arthropoda

Entomobryomo
rpha
Coleoptera
Diptera

Entomobryidae

Animalia
Animalia

Collembo
la
Insecta
Insecta

Carabidae
Anthomyiidae

Harpalus
Delia

Harpalus fraternus
Delia extensa

Animalia

Arthropoda
Arthropoda

Entomobryomo
rpha
Hemiptera

Entomobryidae

Animalia

Collembo
la
Insecta

Entomobryid
ae
Orius

Orius tristicolor

Selatosomus

aeripennis
Frankliniella

occidentalis

melancholica

Anthocoridae

A.10
0214
0215
0219
0022
0220
0222
0223
0224
0227
0228
0023
0230
0231
0232
0233
0234
0237
0242
0244
0245
0246

GS|99.7|BOLD:AAD0484_KR
588113
GS|94.7|BOLD:ADA3514_NA

Animalia

Arthropoda

Insecta

Diptera

Chironomidae

Animalia

Arthropoda

Insecta

Diptera

Heleomyzidae

GSL|79.3|BOLD:ADA7549_N
A
GS|99.0|BOLD:ACR9309_KM
943654
GS|100.0|BOLD:AAD2901_K
R571882
GS|98.7|BOLD:ACB0946_KM
990445
GS|91.7|BOLD:ACM2566_KR
147632
GS|97.3|BOLD:AAA4555_NA
GS|85.6|BOLD:ACP5629_NA
GS|100.0|BOLD:AAP8834_MF
636045
GS|100.0|BOLD:AAU6111_N
A
GS|100.0|BOLD:AAC9614_KR
944318
GS|73.0|BOLD:ACB0901_KX8
44319
GS|88.0|BOLD:AAU3560_JN2
99334
GS|100.0|BOLD:ACX4703_KR
694949
GS|89.9|BOLD:AAN5901_MF
634185
GS|85.0|BOLD:ABA1267_NA

Animalia

Arthropoda

Insecta

Animalia

Arthropoda

Insecta

Diptera

Drosophilidae

Drosophila

Animalia

Arthropoda

Insecta

Hemiptera

Emblethis

Animalia

Arthropoda

Insecta

Diptera

Rhyparochromid
ae
Chironomidae

Animalia

Arthropoda

Insecta

Archaeognatha

Meinertellidae

Machilinus

Animalia
Animalia
Animalia

Arthropoda
Arthropoda
Arthropoda

Insecta
Insecta
Insecta

Orthoptera
Diptera
Diptera

Anthomyiidae

Delia

Delia albula

Animalia

Arthropoda

Insecta

Orthoptera

Arthropoda

Insecta

Diptera

Animalia

Arthropoda

Insecta

Diptera

Tachinidae

Animalia

Arthropoda

Insecta

Neuroptera

Hemerobiidae

Ceuthophilu
s
Protophormi
a
Cylindromyi
a
Hemerobius

Ceuthophilus agassizii

Animalia

Rhaphidophorid
ae
Calliphoridae

Animalia

Arthropoda

Insecta

Diptera

Ceratopogonidae

Animalia

Arthropoda

Insecta

Coleoptera

Chrysomelidae

Phyllotreta

Phyllotreta pusilla

Animalia

Arthropoda

Poduromorpha

GS|100.0|BOLD:AAG3286_M
G104438
GSL|76.6|BOLD:ADL1711_N
A
GS|76.3|BOLD:ACK3624_NA

Animalia

Arthropoda

Collembo
la
Insecta

Phoridae

Megaselia

Megaselia

Animalia

Arthropoda

Insecta

Diptera

Animalia

Arthropoda

Insecta

Diptera

Chironomidae

GS|99.7|BOLD:ACF4680_KR8
90066

Animalia

Arthropoda

Insecta

Hymenoptera

Formicidae

Diptera

Psectrocladi
us

Psectrocladius

barbimanus

Emblethis vicarius

Smittia

Protophormia

terraenovae
Cylindromyia

rufifrons
Hemerobius lutescens

lombardorum
Heterotrisso
cladius
Formica

Heterotrissocladius

subpilosus
Formica planipilis

A.11
0249
0025
0250
0251
0253
0256
0258
0259
026
0260
0263
0264
0266
0267
027
0271
0272
0273
0274
0275
0276
0277

GS|95.7|BOLD:AAA8764_JN2
94644
GS|99.7|BOLD:AAG2472_JF8
76932
GS|90.3|BOLD:ACA5986_NA
GS|98.4|BOLD:AAV1530_JN3
09491
GS|86.7|BOLD:AAZ4548_NA
GS|100.0|BOLD:ABX3926_KR
039655
GS|79.7|BOLD:ACO5516_NA
GS|99.7|BOLD:ACE1079_MG
088886
GS|99.7|BOLD:AAP9080_KM
945424
GS|98.4|BOLD:AAV1530_JN3
09491
GS|100.0|BOLD:ACY7534_N
A
GS|94.0|BOLD:AAF7101_NA
GS|97.3|BOLD:ACJ0553_NA

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Animalia

Arthropoda

Insecta

Diptera

Anthomyiidae

Delia

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Coleoptera
Archaeognatha

Machilidae

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Diptera
Hemiptera

Cicadellidae

Auridius

Auridius auratus

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Diptera
Diptera

Dolichopodidae
Muscidae

Thinophilus
Spilogona

Spilogona pacifica

Animalia

Arthropoda

Insecta

Diptera

Mycetophilidae

Leia

Animalia

Arthropoda

Insecta

Archaeognatha

Machilidae

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Melanoplus

Melanoplus rugglesi

Animalia
Animalia

Arthropoda
Arthropoda

Diptera
Opiliones

Fanniidae

Fannia

Fannia canicularis

GS|93.3|BOLD:ACJ7984_KR9
30486
GS|99.0|BOLD:AAF6788_NA
GS|100.0|BOLD:ACE8833_MF
892636
GS|97.7|BOLD:ABY5198_MG
170315
GS|98.7|BOLD:AAQ0769_JF8
85347
GS|99.3|BOLD:ACD1662_KM
638892
GS|78.3|BOLD:ABY3348_NA

Animalia

Arthropoda

Insecta
Arachnid
a
Insecta

Hymenoptera

Formicidae

Myrmica

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Hymenoptera
Diptera

Formicidae
Muscidae

Formica
Helina

Formica neogagates

Animalia

Arthropoda

Insecta

Diptera

Syrphidae

Melangyna

Melangyna

Animalia

Arthropoda

Araneae

Linyphiidae

Scotinotylus

Animalia

Arthropoda

Arachnid
a
Insecta

Diptera

Cecidomyiidae

Animalia

Arthropoda

Insecta

Coleoptera

Cerambycidae

Placosternus

GS|99.7|BOLD:AAA3453_KM
634911
GS|95.7|BOLD:AAU6111_NA

Animalia

Arthropoda

Insecta

Diptera

Anthomyiidae

Delia

Animalia

Arthropoda

Insecta

Orthoptera

Rhaphidophorid
ae

Ceuthophilu
s

Camnula pellucida

umbellatarum
Scotinotylus

exsectoides
Placosternus guttatus
Delia platura
Ceuthophilus agassizii

A.12
0280
0281
0282
0284
0285
0291
0292
0294
0295
0297
0298
0003
0030
0300
0304
0307
0308
0031
0311
0313
0316
0319
0032

GS|100.0|BOLD:ACX5072_KR
679990
GS|80.7|BOLD:AEB3573_NA
GS|83.3|BOLD:ACM2566_KR
147632
GS|76.7|BOLD:ACU6811_NA
GS|97.3|BOLD:AAA8764_JN2
94644
GS|79.3|BOLD:AAU6693_NA
GS|100.0|BOLD:AAG4872_K
R983531
GS|100.0|BOLD:AAL8938_K
M826455
GS|79.7|BOLD:ACO5516_NA
GS|95.3|BOLD:ACL0992_MG
118623
GS|99.7|BOLD:AAG8838_KF9
19844
GS|100.0|BOLD:AAA8764_M
G468655
GS|99.7|BOLD:AAF7101_NA
GS|80.3|BOLD:AEB3573_NA
GS|77.6|BOLD:ACO5516_NA
GSL|86.7|BOLD:AAH3537_H
M417301
GS|84.0|BOLD:ACF9803_NA
GS|86.0|BOLD:ADP0308_NA

Animalia

Arthropoda

Insecta

Diptera

Hybotidae

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Archaeognatha
Archaeognatha

Meinertellidae

Machilinus

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Diptera
Orthoptera

Micropezidae
Acrididae

Camnula

Camnula pellucida

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Diptera
Diptera

Asilidae
Mycetophilidae

Mycetophila

Mycetophila

Animalia

Arthropoda

Araneae

Linyphiidae

Collinsia

perpallida
Collinsia ksenia

Animalia
Animalia

Arthropoda
Arthropoda

Arachnid
a
Insecta
Insecta

Diptera
Diptera

Dolichopodidae
Anthomyiidae

Thinophilus

Animalia

Arthropoda

Insecta

Hemiptera

Cicadellidae

Helochara

Helochara communis

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia
Animalia
Animalia
Animalia

Arthropoda
Arthropoda
Arthropoda
Arthropoda

Insecta
Insecta
Insecta
Insecta

Diptera
Archaeognatha
Diptera
Diptera

Fanniidae

Fannia

Fannia canicularis

Dolichopodidae

Thinophilus

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Hemiptera
Hemiptera

Cicadellidae
Cicadellidae

Neoaliturus

Neoaliturus

GS|94.0|BOLD:AAA8764_JN2
94644
GS|97.3|BOLD:AEC6585_KP6
57062
GS|96.7|BOLD:AAA8764_KM
533615
GS|100.0|BOLD:ABZ3849_MF
831862
GS|100.0|BOLD:ACL0992_M
G118623

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

fenestratus
Camnula pellucida

Animalia

Arthropoda

Araneae

Linyphiidae

Islandiana

Islandiana holmi

Animalia

Arthropoda

Arachnid
a
Insecta

Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia

Arthropoda

Insecta

Hemiptera

Cicadellidae

Diplocolenu
s

Diplocolenus evansi

Animalia

Arthropoda

Insecta

Diptera

Anthomyiidae

A.13
0321
0322
0326
0330
0331
0332
0333
0334
0337
0338
0034
0340
0344
0347
0035
0351
0356

GS|100.0|BOLD:AAY7951_K
Y269962
GS|89.0|BOLD:AAC6413_NA

Animalia

Arthropoda

Araneae

Linyphiidae

Silometopus

Arthropoda

Arachnid
a
Insecta

Animalia

GS|100.0|BOLD:AAE6488_KU
875052
GS|100.0|BOLD:AAF9976_NA
GS|94.7|BOLD:AAA8764_JN2
94644
GS|99.7|BOLD:AAG2875_KR
038524
GS|99.7|BOLD:AAP8985_JF87
5965
GS|100.0|BOLD:AAC2393_M
F829622
GS|99.3|BOLD:ACL3102_KR3
46406
GS|90.7|BOLD:AAC6413_NA
GSL|99.7|BOLD:AAB3450_N
A
GS|100.0|BOLD:AAE4456_K
M628530
GS|97.0|BOLD:AAG5198_KJ9
63586
GS|90.7|BOLD:ADC9253_NA
GS|100.0|BOLD:AAG4317_K
M842658
GS|94.7|BOLD:AAA8764_JN2
94644
GS|93.4|BOLD:AAM7579_NA

Silometopus

Coleoptera

Carabidae

Amara

Animalia

Arthropoda

Insecta

Hemiptera

Miridae

Europiella

Animalia

Arthropoda

Insecta

Lepidoptera

Gelechiidae

Aroga

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Aroga websteri
Camnula pellucida

Animalia

Arthropoda

Insecta

Hemiptera

Cicadellidae

Ceratagallia

Ceratagallia siccifolia

Animalia

Arthropoda

Insecta

Diptera

Milichiidae

Leptometopa

Animalia

Arthropoda

Insecta

Hemiptera

Berytidae

Neoneides

Neoneides muticus

Animalia

Arthropoda

Insecta

Hemiptera

Cicadellidae

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Coleoptera
Orthoptera

Carabidae
Acrididae

Diplocolenu
s
Amara

Amara obesa

Animalia

Arthropoda

Insecta

Diptera

Syrphidae

Platycheirus

Platycheirus pictipes

Animalia

Arthropoda

Insecta

Coleoptera

Curculionidae

Otiorhynchus ovatus

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Hemiptera
Coleoptera

Cicadellidae
Staphylinidae

Otiorhynchu
s
Ceratagallia
Phloeostiba

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia

Arthropoda

Insecta

Coleoptera

Dermestidae

Dermestes

Dermestes

reussi
Amara obesa
Europiella decolor

Phloeostiba lapponica

marmoratus
0358
0036
0360
0361
0368

GS|80.7|BOLD:ACM2566_KR
147632
GS|95.3|BOLD:AAG3766_NA
GS|70.6|BOLD:ADK0436_KX
072071
GS|90.6|BOLD:AAN6555_MF
602326
GS|90.7|BOLD:ADB1949_NA

Animalia

Arthropoda

Insecta

Archaeognatha

Meinertellidae

Machilinus

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Diptera
Lepidoptera

Geometridae

Elophos

Elophos caelibaria

Animalia

Arthropoda

Lepidocyrtus

Lepidocyrtus cyaneus

Arthropoda

Entomobryomo
rpha
Coleoptera

Entomobryidae

Animalia

Collembo
la
Insecta

Cleridae

A.14
0369
0037
0373
0375
0380
0381
0382
0384
0385
0386
0388
0389
0392
0393
0395
0397
0004
0040
0400
0407
0408
0411

GS|99.7|BOLD:ABA6488_KM
967845
GS|100.0|BOLD:AAA1831_K
R654855
GSL|90.1|BOLD:ACF3208_NA
GS|96.4|BOLD:AAA8764_KM
533615
GS|96.3|BOLD:AAA8764_JN2
94644
GS|95.0|BOLD:AAA8764_KM
536285
GSL|92.3|BOLD:ACF3208_NA
GS|98.7|BOLD:AAG2454_KR
514726
GS|99.7|BOLD:ACT5834_KR9
50814
GS|97.3|BOLD:ABX3928_KR0
36427
GS|100.0|BOLD:ACJ8319_KM
630123
GS|100.0|BOLD:ACY9729_N
A
GS|98.0|BOLD:ACI3068_KR5
76576
GS|95.7|BOLD:AAA8764_JN2
94644
GS|84.0|BOLD:ACF9803_NA
GS|100.0|BOLD:AAG6953_K
M938527
GS|100.0|BOLD:AAP7044_K
M850147
GS|87.7|BOLD:ADF5560_NA
GSL|79.0|BOLD:AAI1266_GU
689776
GS|97.0|BOLD:AAG5198_KJ9
63586
GS|76.0|BOLD:AAV4709_NA
GS|96.0|BOLD:AAE0406_NA

Animalia

Arthropoda

Insecta

Diptera

Sciaridae

Bradysia

Bradysia trivittata

Animalia

Arthropoda

Insecta

Diptera

Drosophilidae

Drosophila

Drosophila barbarae

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Orthoptera
Orthoptera

Acrididae
Acrididae

Camnula

Camnula pellucida

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Orthoptera
Diptera

Acrididae
Anthomyiidae

Animalia

Arthropoda

Insecta

Diptera

Cecidomyiidae

Animalia

Arthropoda

Insecta

Hemiptera

Cicadellidae

Athysanella

Athysanella obesa

Animalia

Arthropoda

Insecta

Diptera

Chloropidae

Meromyza

Animalia

Arthropoda

Insecta

Coleoptera

Tenebrionidae

Eleodes

Eleodes vandykei

Animalia

Arthropoda

Insecta

Hemiptera

Cicadellidae

Ceratagallia

Ceratagallia siccifolia

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Hemiptera
Diptera

Cicadellidae
Hybotidae

Animalia

Arthropoda

Insecta

Coleoptera

Staphylinidae

Phloeostiba

Phloeostiba lapponica

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Coleoptera
Diptera

Staphylinidae

Animalia

Arthropoda

Insecta

Coleoptera

Curculionidae

Otiorhynchu
s

Otiorhynchus ovatus

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Diptera
Hymenoptera

Asilidae
Formicidae

Formica

Formica lasioides

A.15
0412
0413
0414
0415
0416
0417

GS|94.0|BOLD:AAA8764_JN2
94644
GS|100.0|BOLD:AAL7755_KR
691547
GS|90.0|BOLD:ACP5629_NA
GS|89.0|BOLD:AAZ4548_NA
GS|82.9|BOLD:ACB8951_NA
GS|84.0|BOLD:ADP0308_NA

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia

Arthropoda

Insecta

Diptera

Sphaeroceridae

Spelobia

Spelobia tufta

Animalia
Animalia
Animalia
Animalia

Arthropoda
Arthropoda
Arthropoda
Arthropoda

Insecta
Insecta
Insecta
Insecta

Diptera
Diptera
Psocodea
Hemiptera

Lachesillidae
Cicadellidae

Lachesilla
Neoaliturus

Neoaliturus

GS|89.9|BOLD:ABX9412_KR8
04190
GS|99.3|BOLD:AAA5308_JF8
76496
GS|71.8|BOLD:AAA8764_MG
468655
GS|100.0|BOLD:ACF0670_K
M955493
GS|97.5|BOLD:AAG4317_KM
848028
GS|100.0|BOLD:AAP6259_M
G048117
GS|98.7|BOLD:AAB1385_KR8
99940
GS|100.0|BOLD:ACE1891_MF
911832
GS|96.7|BOLD:AAM7650_KU
914062
GS|89.9|BOLD:AAA8764_JN2
94644
GS|99.3|BOLD:ACI4294_KM6
28173
GS|86.4|BOLD:ABU8876_NA
GS|100.0|BOLD:AAB0377_K
M627814
GSL|92.7|BOLD:ACA5984_N
A
GS|98.7|BOLD:AAP7807_JF88
8079
GS|94.6|BOLD:AAC7186_KT0
85784

Animalia

Arthropoda

Insecta

Hymenoptera

Formicidae

Leptothorax

Animalia

Arthropoda

Insecta

Diptera

Chironomidae

Cricotopus

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia

Arthropoda

Insecta

Diptera

Cecidomyiidae

Animalia

Arthropoda

Insecta

Coleoptera

Staphylinidae

Phloeostiba

Phloeostiba lapponica

Animalia

Arthropoda

Araneae

Linyphiidae

Agyneta

Agyneta ordinaria

Animalia

Arthropoda

Arachnid
a
Insecta

Hymenoptera

Formicidae

Leptothorax

Animalia

Arthropoda

Mesostigmata

Parasitidae

Animalia

Arthropoda

Arachnid
a
Insecta

Coleoptera

Chrysomelidae

Animalia

Arthropoda

Insecta

Orthoptera

Animalia

Arthropoda

Insecta

Animalia
Animalia

Arthropoda
Arthropoda

Animalia

fenestratus
0418
0419
0042
0420
0426
0043
0432
0436
0437
0439
0044
0447
0045
0452
0454
0046

Chaetocnema

Acrididae

Chaetocnem
a
Camnula

Diptera

Anthomyzidae

Stiphrosoma

Stiphrosoma hirtum

Insecta
Insecta

Lepidoptera
Diptera

Chironomidae

Smittia

Arthropoda

Insecta

Orthoptera

Acrididae

Animalia

Arthropoda

Insecta

Coleoptera

Staphylinidae

Phloeostiba

Phloeostibala pponica

Animalia

Arthropoda

Insecta

Diptera

Muscidae

Helina

Helina flavisquama

hortensis
Camnula pellucida

A.16
0460

Animalia

Arthropoda

Insecta

Hymenoptera

Formicidae

Myrmica

Animalia

Arthropoda

Insecta

Archaeognatha

Meinertellidae

Machilinus

Animalia

Arthropoda

Insecta

Diptera

Anthomyiidae

Zaphne

Zaphne implicata

0472

GS|100.0|BOLD:AAA1834_K
R879274
GS|83.7|BOLD:ACM2566_KR
147632
GS|92.0|BOLD:AAG2442_KJ4
44803
GS|96.3|BOLD:AAU6111_NA

Animalia

Arthropoda

Insecta

Orthoptera

GS|93.7|BOLD:ACA5984_NA

Animalia

Arthropoda

Insecta

Orthoptera

0475

GS|99.7|BOLD:ACC3017_NA

Animalia

Arthropoda

Insecta

Coleoptera

Staphylinidae

0476

GS|100.0|BOLD:ACF9614_M
G150830
GS|100.0|BOLD:ACR5480_KR
696819
GS|96.2|BOLD:AAG5198_KU
911307
GS|100.0|BOLD:ACG4478_KT
113373
GS|100.0|BOLD:AAG2474_K
M638129
GS|84.0|BOLD:ACF9803_NA
GSL|90.1|BOLD:AAE2480_N
A
GS|97.0|BOLD:ACL3102_KR3
45756
GS|99.7|BOLD:ABX3899_KR0
35906
GS|99.7|BOLD:ABY5760_KU
875076
GS|92.0|BOLD:AAA8764_JN2
94644
GS|100.0|BOLD:ADO7114_K
M645444
GS|97.3|BOLD:AAA8764_JN2
94644
GS|100.0|BOLD:AAG8681_K
R577666

Animalia

Arthropoda

Insecta

Diptera

Sciaridae

Ceuthophilu
s
Trimerotropi
s
Phloeonomu
s
Bradysia

Ceuthophilus agassizii

0473

Rhaphidophorid
ae
Acrididae

Animalia

Arthropoda

Insecta

Diptera

Carnidae

Meoneura

Animalia

Arthropoda

Insecta

Coleoptera

Curculionidae

Animalia

Arthropoda

Insecta

Diptera

Anthomyiidae

Otiorhynchu
s
Delia

Animalia

Arthropoda

Insecta

Diptera

Anthomyiidae

Delia

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Hemiptera
Orthoptera

Cicadellidae
Acrididae

Animalia

Arthropoda

Insecta

Hemiptera

Cicadellidae

Animalia

Arthropoda

Insecta

Hemiptera

Animalia

Arthropoda

Insecta

Animalia

Arthropoda

Animalia

0463
0047

0478
0479
0048
0484
0485
0487
0489
049
0490
0491
0496
0497
0005

Myrmica detritinodis

Trimerotropis fontana

Bradysia strenua

Otiorhynchus ovatus

Cicadellidae

Diplocolenu
s
Athysanella

Athysanella

Hymenoptera

Formicidae

Formica

acuticauda
Formica aserva

Insecta

Orthoptera

Acrididae

Camnula

Camnula pellucida

Arthropoda

Insecta

Diptera

Sphaeroceridae

Leptocera

Leptocera erythrocera

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia

Arthropoda

Insecta

Hemiptera

Cicadellidae

Psammotetti
x

Psammotettix

lividellus

A.17
0050
0502
0508
0051
0513
0514
0517
0519
0052
0521
0526
0053
0531
0532
0535
0536
0537
0054
0540
0541
0542
0543

GS|94.0|BOLD:AAM9235_JF8
66971
GS|92.0|BOLD:ACM2566_KR
147632
GS|94.7|BOLD:AAA8764_JN2
94644
GS|83.0|BOLD:AAP7796_JF88
8053
GS|97.3|BOLD:AAA8764_JN2
94644
GSL|98.0|BOLD:AAB3450_N
A
GS|95.0|BOLD:AAH1663_MG
504469
GS|93.3|BOLD:AAA8764_JN2
94644
GS|99.3|BOLD:AAF6787_NA
GS|99.7|BOLD:AAG3311_MG
105542
GS|99.7|BOLD:ACG2756_KR4
81284
GS|91.7|BOLD:ACV8058_MF
712440
GS|99.7|BOLD:AAC5850_NA
GS|95.0|BOLD:AAG6437_KR
498973
GS|97.7|BOLD:ACE4532_KR0
36390
GS|97.3|BOLD:ACG1315_KF5
49892
GS|79.7|BOLD:ACP2164_NA
GS|100.0|BOLD:ACX5303_M
F873972
GS|92.7|BOLD:ACG1460_KF5
49893
GS|78.7|BOLD:ABW2464_NA
GS|85.3|BOLD:ACM2566_KR
147632
GS|100.0|BOLD:AAM9013_M
G094039

Animalia

Arthropoda

Insecta

Diptera

Sciaridae

Animalia

Arthropoda

Insecta

Archaeognatha

Meinertellidae

Machilinus

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia

Arthropoda

Insecta

Coleoptera

Curculionidae

Cossonus

Cossonus piniphilus

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Animalia

Arthropoda

Insecta

Hymenoptera

Ichneumonidae

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Hymenoptera
Diptera

Formicidae
Phoridae

Formica
Megaselia

Megaselia tecticauda

Animalia

Arthropoda

Insecta

Coleoptera

Monotomidae

Monotoma

Monotoma longicollis

Animalia

Arthropoda

Insecta

Diptera

Cecidomyiidae

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Lepidoptera
Diptera

Gelechiidae
Ceratopogonidae

Bryotropha
Dasyhelea

Animalia

Arthropoda

Insecta

Hemiptera

Cicadellidae

Latalus

Latalus curtus

Animalia

Arthropoda

Insecta

Coleoptera

Elateridae

Selatosomus

Selatosomus

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Diptera
Diptera

Dolichopodidae
Heleomyzidae

Suillia

Suillia nemorum

Animalia

Arthropoda

Insecta

Coleoptera

Elateridae

Selatosomus

Selatosomus

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Diptera
Archaeognatha

Asilidae
Meinertellidae

Machilinus

Animalia

Arthropoda

Insecta

Diptera

Keroplatidae

Macrocera

aeripennis

aeripennis

Macrocera pusilla

A.18
0544
0545
0546
0547
0549
0055
0552
0557
0559
0056
0560
0569
0057
0570
0572
0576
0577
0579
0585
0588
0590
0593
0594

GS|88.7|BOLD:ACP5629_NA
GS|96.7|BOLD:AAL2821_MF8
89772
GS|100.0|BOLD:ACE1420_K
M843710
GS|83.7|BOLD:AAE1524_KF5
49248
GS|99.2|BOLD:AAB8583_KF9
20426
GS|99.3|BOLD:AAV0264_KR
044992
GS|90.7|BOLD:AAA8764_JN2
94644
GS|91.3|BOLD:AAN6561_JN2
90615
GS|80.3|BOLD:ACO5516_NA
GS|100.0|BOLD:AAI1608_NA
GS|100.0|BOLD:AAP6246_K
M646447
GS|99.7|BOLD:AAH3941_KM
629859
GS|100.0|BOLD:AAG8842_K
R576758
GS|99.7|BOLD:AAH6630_NA

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Diptera
Diptera

Muscidae

Phaonia

Phaonia apicalis

Animalia

Arthropoda

Insecta

Coleoptera

Staphylinidae

Oxypoda

Oxypoda irrasa

Animalia

Arthropoda

Insecta

Diptera

Tachinidae

Houghia

Houghia romeroae

Animalia

Arthropoda

Insecta

Hemiptera

Aphrophoridae

Philaenarcys

Philaenarcys spartina

Animalia

Arthropoda

Insecta

Hemiptera

Cicadellidae

Latalus

Latalus mundus

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia

Arthropoda
Arthropoda
Arthropoda
Arthropoda

Entomobryomo
rpha
Diptera
Hymenoptera
Diptera

Entomobryidae

Animalia
Animalia
Animalia

Collembo
la
Insecta
Insecta
Insecta

Animalia

Arthropoda

Insecta

Animalia

Arthropoda

Animalia

Arthropoda

GS|77.4|BOLD:ACO5516_NA
GS|100.0|BOLD:ACE5391_KR
678446
GS|86.3|BOLD:ACP5629_NA
GS|98.0|BOLD:AAB3450_NA

Animalia
Animalia

GS|89.7|BOLD:ACP5629_NA
GS|94.7|BOLD:AAA8764_JN2
94644
GS|92.0|BOLD:AAA8764_JN2
94644
GS|78.4|BOLD:AEB3573_NA
GS|91.0|BOLD:AAA8764_JN2
94644

Dolichopodidae

Thinophilus

Piophilidae

Mycetaulus

Diptera

Sciaridae

Lycoriella

Insecta

Hemiptera

Cicadellidae

Entomobryomo
rpha
Diptera
Diptera

Entomobryidae

Arthropoda
Arthropoda

Collembo
la
Insecta
Insecta

Scaphytopiu
s
Entomobrya

Dolichopodidae
Tephritidae

Thinophilus
Chaetorellia

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Diptera
Orthoptera

Acrididae

Trimerotropi
s

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Diptera
Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Archaeognatha
Orthoptera

Acrididae

Camnula

Camnula pellucida

Mycetaulus

bipunctatus

A.19
0596
0006
0060
0600
0601
0603
0606
0607
0609
0610
0616
0618
0619
0062
0621
0623
0630
0632
0633
0637
0064

GS|79.3|BOLD:ACA8144_KR3
85033
GS|87.7|BOLD:ACD9132_MG
398954
GS|97.3|BOLD:AAH3943_KM
639609
GS|77.0|BOLD:ADA7549_NA

Animalia

Arthropoda

Insecta

Diptera

Dolichopodidae

Animalia

Arthropoda

Insecta

Hemiptera

Animalia

Arthropoda

Insecta

Diptera

Rhyparochromid
ae
Sciaridae

Animalia

Arthropoda

Insecta

Archaeognatha

Machilidae

GS|94.3|BOLD:AAA8764_JN2
94644
GS|96.7|BOLD:AAA8764_KM
533615
GS|99.7|BOLD:ACK7799_KM
846655
GS|91.0|BOLD:AAA8764_JN2
94644
GSL|90.3|BOLD:ACF3208_NA

Animalia

Arthropoda

Insecta

Orthoptera

Animalia

Arthropoda

Insecta

Animalia

Arthropoda

Animalia

Perigenes

Perigenes constrictus

Acrididae

Camnula

Camnula pellucida

Orthoptera

Acrididae

Camnula

Camnula pellucida

Insecta

Coleoptera

Leiodidae

Neoeocatops

Neoeocatops

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

decipiens
Camnula pellucida

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

GS|96.6|BOLD:AAV0237_MF
830974
GS|95.0|BOLD:AAA8764_JN2
94644
GSL|87.3|BOLD:AAH3915_M
G151438
GS|94.7|BOLD:ACB0775_KR6
94678
GS|77.3|BOLD:ACV4172_KY
831905
GS|90.3|BOLD:AAF9959_KR0
42773
GS|100.0|BOLD:AAZ1768_KR
033451
GS|88.5|BOLD:AAU6111_NA

Animalia

Arthropoda

Insecta

Hemiptera

Cicadellidae

Latalus

Latalus personatus

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia

Arthropoda

Insecta

Diptera

Sciaridae

Animalia

Arthropoda

Insecta

Diptera

Hybotidae

Animalia

Arthropoda

Insecta

Diptera

Tachinidae

Animalia

Arthropoda

Insecta

Hemiptera

Miridae

Lygidea

Lygidea annexa

Animalia

Arthropoda

Insecta

Hemiptera

Miridae

Litomiris

Animalia

Arthropoda

Insecta

Orthoptera

GS|95.3|BOLD:AAA8764_JN2
94644
GS|91.7|BOLD:ACM2566_KR
147632
GS|93.4|BOLD:AAA8764_JN2
94644
GS|98.3|BOLD:AAB7203_KR8
90199

Animalia

Arthropoda

Insecta

Orthoptera

Rhaphidophorid
ae
Acrididae

Ceuthophilu
s
Camnula

Animalia

Arthropoda

Insecta

Archaeognatha

Meinertellidae

Machilinus

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Animalia

Arthropoda

Insecta

Hymenoptera

Formicidae

Leptothorax

Ceuthophilus agassizii
Camnula pellucida

Camnula pellucida

A.20
0643
0645
0065
0653
0066
0660
0663
0664
0067
0674
0675
0677
0068
0681
0682
0683
0685
0687
0691
0693
0696
0698

GS|92.4|BOLD:AAA8764_JN2
94644
GS|100.0|BOLD:ACG3736_K
M628503
GS|100.0|BOLD:AAC2498_H
M860486
GS|99.7|BOLD:AAA2372_KR
785178
GS|84.4|BOLD:AAV6192_NA
GS|91.3|BOLD:AAA8764_KM
533615
GS|84.0|BOLD:ACM2566_KR
147632
GS|86.0|BOLD:ADL7370_NA

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Animalia

Arthropoda

Insecta

Diptera

Mycetophilidae

Exechiopsis

Animalia

Arthropoda

Insecta

Diptera

Muscidae

Helina

Helina evecta

Animalia

Arthropoda

Insecta

Hymenoptera

Formicidae

Camponotus

Camponotus

GS|100.0|BOLD:ACI3968_KM
624882
GSL|95.3|BOLD:AAB3450_N
A
GS|94.7|BOLD:AAA8764_JN2
94644
GS|70.2|BOLD:AAM6781_JF8
71903
GS|99.3|BOLD:AAU6757_KM
631883
GS|94.4|BOLD:ACI3068_KR5
76576
GSL|97.7|BOLD:AAB3450_N
A
GS|92.3|BOLD:AAA8764_JN2
94644
GS|75.7|BOLD:ACU6811_NA
GS|92.0|BOLD:AAA8764_JN2
94644
GS|87.4|BOLD:ACP5629_NA
GS|91.2|BOLD:AAA3075_GU
694503
GS|88.0|BOLD:AAI2112_NA
GS|82.7|BOLD:AEB3573_NA

Camnula pellucida

herculeanus
Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Hemiptera
Orthoptera

Cicadellidae
Acrididae

Camnula

Animalia

Arthropoda

Insecta

Archaeognatha

Meinertellidae

Machilinus

Animalia

Arthropoda

Sarcoptiformes

Animalia

Arthropoda

Arachnid
a
Insecta

Diptera

Gymnodamaeida
e
Anthomyiidae

Hylemya

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia

Arthropoda

Insecta

Diptera

Dolichopodidae

Neurigona

Neurigona tenuis

Animalia

Arthropoda

Insecta

Diptera

Cecidomyiidae

Animalia

Arthropoda

Insecta

Hemiptera

Cicadellidae

Ceratagallia

Ceratagallia siccifolia

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Diptera
Orthoptera

Micropezidae
Acrididae

Camnula

Camnula pellucida

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Diptera
Lepidoptera

Geometridae

Pasiphila

Pasiphila

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Diptera
Archaeognatha

Pipunculidae

Jassidophaga

Camnula pellucida

rectangulata
Jassidophaga villosa

A.21
0007
0070
0700
0702
0706
0709
0071
0714
0715
0721
0731
0734

GS|90.3|BOLD:ACM2566_KR
147632
GS|99.0|BOLD:AAN6462_KR
691637
GS|99.0|BOLD:ACA5986_NA
GS|100.0|BOLD:AAP7048_KU
875710
GS|91.4|BOLD:AAU6111_NA

Animalia

Arthropoda

Insecta

Archaeognatha

Meinertellidae

Machilinus

Animalia

Arthropoda

Insecta

Diptera

Tachinidae

Linnaemya

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Coleoptera
Coleoptera

Staphylinidae

Oxypoda

Oxypoda irrasa

Animalia

Arthropoda

Insecta

Orthoptera

Animalia

Arthropoda

Insecta

Diptera

Ceuthophilu
s
Smittia

Ceuthophilus agassizii

GS|100.0|BOLD:ACW5117_M
F734954
GS|82.0|BOLD:ADF4779_NA
GS|100.0|BOLD:ACA2681_KR
950089
GS|85.0|BOLD:ACA6706_NA

Rhaphidophorid
ae
Chironomidae

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Psocodea
Diptera

Psocidae
Cecidomyiidae

Animalia

Arthropoda

Insecta

Orthoptera

Animalia

Arthropoda

Insecta

Lepidoptera

Ceuthophilu
s
Coleotechnit
es

Ceuthophilus agassizii

GS|100.0|BOLD:AAA5953_N
A
GSL|97.7|BOLD:AAB3450_N
A
GS|94.3|BOLD:AAE2480_NA

Rhaphidophorid
ae
Gelechiidae

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Spharagemon

Coleotechnites

piceaella

0738

GS|80.3|BOLD:ACS7235_NA

Animalia

Arthropoda

Insecta

Diptera

Tabanidae

Spharagemo
n
Chrysops

0074

GS|100.0|BOLD:AAG2186_K
M636151
GS|97.7|BOLD:AAG7279_KR
662822
GS|99.0|BOLD:ABA6352_NA
GS|97.0|BOLD:AAU6111_NA

Animalia

Arthropoda

Insecta

Diptera

Tachinidae

Peleteria

madagascarensis
Peleteria iterans

Animalia

Arthropoda

Insecta

Diptera

Sphaeroceridae

Eulimosina

Eulimosina ochripes

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Coleoptera
Orthoptera

Mycetophagidae
Rhaphidophorid
ae

Typhaea
Ceuthophilu
s

Typhaea stercorea
Ceuthophilus agassizii

GS|78.7|BOLD:ACY5086_NA
GS|100.0|BOLD:AAG1725_K
M634700
GS|70.7|BOLD:AAI9028_NA
GS|90.7|BOLD:ADR1193_NA
GS|91.0|BOLD:AAA8764_JN2
94649

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Diptera
Diptera

Muscidae

Coenosia

Animalia
Animalia
Animalia

Arthropoda
Arthropoda
Arthropoda

Insecta
Insecta
Insecta

Orthoptera
Coleoptera
Orthoptera

Acrididae
Carabidae
Acrididae

Cratypedes
Amara
Camnula

0740
0745
0746
0749
0075
0754
0076
0762

campestris
Chrysops

Cratypedes neglectus
Amara fortis
Camnula pellucida

A.22
0763

GS|75.7|BOLD:AAC4201_NA

Animalia

Arthropoda

Insecta

Diptera

Chironomidae

0771

GS|94.3|BOLD:ADA3514_NA

Animalia

Arthropoda

Insecta

Diptera

Heleomyzidae

0774
0776

GS|83.4|BOLD:ABW2776_NA
GS|93.3|BOLD:AAY6676_KM
838130
GS|84.3|BOLD:AAV6192_NA
GS|98.3|BOLD:ACI2871_KR5
69600
GS|100.0|BOLD:ABX3085_N
A
GS|84.0|BOLD:AAA8764_JN2
94649
GS|99.3|BOLD:ABX3968_KR0
36090
GS|100.0|BOLD:AAG8821_M
F829417
GS|90.3|BOLD:AAA8764_JN2
94644
GS|96.0|BOLD:ACI5842_KM6
42700
GS|92.7|BOLD:AAM7579_NA

Animalia
Animalia

Arthropoda
Arthropoda

Orthoptera
Opiliones

Acrididae
Sclerosomatidae

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Arachnid
a
Insecta
Insecta

Hemiptera
Hemiptera

Cicadellidae
Cicadellidae

Animalia

Arthropoda

Insecta

Diptera

Phoridae

Megaselia

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia

Arthropoda

Insecta

Hemiptera

Cicadellidae

Psammotettix

Animalia

Arthropoda

Insecta

Hemiptera

Cicadellidae

Psammotetti
x
Doratura

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia

Arthropoda

Insecta

Diptera

Hybotidae

Animalia

Arthropoda

Insecta

Coleoptera

Dermestidae

Dermestes

Dermestes

GS|100.0|BOLD:AAA1858_JN
292000
GS|94.7|BOLD:ACI4795_KR7
90290
GS|93.0|BOLD:AAL7874_NA
GS|95.0|BOLD:AAF6546_NA

Animalia

Arthropoda

Insecta

Hymenoptera

Formicidae

Myrmica

marmoratus
Myrmica incompleta

Animalia

Arthropoda

Insecta

Hymenoptera

Ichneumonidae

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Diptera
Orthoptera

Sciaridae
Acrididae

GS|91.3|BOLD:AAN6561_JN2
90615
GSL|91.0|BOLD:ACF3208_NA

Animalia

Arthropoda
Arthropoda

Entomobryomo
rpha
Orthoptera

Entomobryidae

Animalia

Collembo
la
Insecta

GS|100.0|BOLD:AAP7560_K
M625819
GS|90.0|BOLD:ACM2566_KR
147632
GS|100.0|BOLD:AAA4555_N
A

Animalia

Arthropoda

Insecta

Diptera

Chloropidae

Meromyza

Animalia

Arthropoda

Insecta

Archaeognatha

Meinertellidae

Machilinus

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Melanoplus

0777
0778
0078
0781
0787
0079
0790
0798
0008
0080
0800
0081
0810
0812
0822
0828
0832
0084

Paraphaenoc
ladius

Paraphaenocladius

Togwoteeus

Togwoteeus biceps

Lycoriella
Trimerotropi
s

Acrididae

impensus

lividellus
Doratura stylata

Trimerotropis

saxatilits

A.23
0846
0847
0849
0085
0854
0855
0086
0860
0865
0869
0871
0875
0877
0088
0885
0888
0889
0089
0890
0090
0901

GS|97.7|BOLD:AAI4346_KY2
68967
GS|87.1|BOLD:AAA8764_JN2
94649
GSL|91.3|BOLD:ACF3208_NA
GS|100.0|BOLD:AAH6662_KP
040076
GS|93.7|BOLD:AAA8764_JN2
94644
GS|99.7|BOLD:ACH2123_KR5
78876
GS|99.7|BOLD:AAG6835_KR
686798
GS|99.3|BOLD:AAF4462_HQ1
05942
GSL|79.0|BOLD:ACW9757_N
A
GS|96.3|BOLD:AAA8764_JN2
94535
GS|92.7|BOLD:AAY6676_KM
838130
GS|96.3|BOLD:ABX3968_KR5
66017
GS|99.0|BOLD:AAM7650_HQ
551565
GS|99.7|BOLD:ACB0918_KM
641668
GS|97.3|BOLD:AAA8764_JN2
94532
GS|92.7|BOLD:ABX3926_KR0
39655
GS|88.0|BOLD:ACU8123_MF
937387
GS|100.0|BOLD:AAD0642_H
Q962013
GS|100.0|BOLD:AAB0973_N
A
GS|100.0|BOLD:AAA4659_KT
148359
GS|99.7|BOLD:AEF1036_NA

Animalia

Arthropoda

Opiliones

Phalangiidae

Phalangium

Phalangium opilio

Arthropoda

Arachnid
a
Insecta

Animalia

Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Orthoptera
Diptera

Acrididae
Tachinidae

Tachina

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia

Arthropoda

Insecta

Hemiptera

Cicadellidae

Animalia

Arthropoda

Insecta

Diptera

Therevidae

Animalia

Arthropoda

Insecta

Hemiptera

Rhyparochromid
ae

Megalonotus

Megalonotus

Animalia

Arthropoda

Insecta

Diptera

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia

Arthropoda

Opiliones

Sclerosomatidae

Togwoteeus

Togwoteeus biceps

Animalia

Arthropoda

Arachnid
a
Insecta

Hemiptera

Cicadellidae

Animalia

Arthropoda

Insecta

Coleoptera

Chrysomelidae

Chaetocnema

sabulicola

Animalia

Arthropoda

Insecta

Diptera

Sphaeroceridae

Psammotetti
x
Chaetocnem
a
Spelobia

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia

Arthropoda

Insecta

Hemiptera

Cicadellidae

Auridius

Auridius auratus

Animalia

Arthropoda

Insecta

Hymenoptera

Braconidae

Elasmosoma

Animalia

Arthropoda

Insecta

Diptera

Muscidae

Helina

Animalia

Arthropoda

Insecta

Hymenoptera

Halictidae

Animalia

Arthropoda

Insecta

Lepidoptera

Gelechiidae

Agapostemo
n
Chionodes

Animalia

Arthropoda

Insecta

Diptera

Acroceridae

Ogcodes

hortensis

Helina reversio

A.24
0903
0905
0907
0908
0091
0910
0913
0917
0926
0930
0934
0094
0943
0944
0948
0950
0955
0970
0973
0975
0098
0984

GSL|96.1|BOLD:AAB3450_N
A
GS|99.7|BOLD:AAN6196_KM
846085
GS|93.0|BOLD:AAA8764_JN2
94644
GS|100.0|BOLD:AAG7284_K
R398833
GS|100.0|BOLD:AAC4680_KT
127902
GS|93.3|BOLD:AAA8764_JN2
94644
GS|88.7|BOLD:ACM2566_KR
147632
GS|97.0|BOLD:AAU6111_NA

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Animalia

Arthropoda

Insecta

Coleoptera

Eucinetidae

Eucinetus

Eucinetus terminalis

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia

Arthropoda

Insecta

Diptera

Sphaeroceridae

Pullimosina

Pullimosina pullula

Animalia

Arthropoda

Insecta

Lepidoptera

Nymphalidae

Cercyonis

Cercyonis sthenele

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Camnula

Camnula pellucida

Animalia

Arthropoda

Insecta

Archaeognatha

Meinertellidae

Machilinus

Animalia

Arthropoda

Insecta

Orthoptera

Ceuthophilu
s

GS|99.7|BOLD:ACN9284_NA
GS|98.7|BOLD:AAP9080_KM
945424
GSL|92.7|BOLD:AAD3251_K
R142810
GS|99.3|BOLD:AAP6481_KR6
88517
GS|87.4|BOLD:ACP5629_NA
GS|81.2|BOLD:AAI9028_NA
GS|83.2|BOLD:ABU8876_NA

Animalia
Animalia

Arthropoda
Arthropoda

Insecta
Insecta

Hemiptera
Diptera

Rhaphidophorid
ae
Miridae
Mycetophilidae

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

Animalia

Arthropoda

Insecta

Diptera

Muscidae

Coenosia

Animalia
Animalia
Animalia

Arthropoda
Arthropoda
Arthropoda

Insecta
Insecta
Insecta

Diptera
Orthoptera
Lepidoptera

Acrididae

Cratypedes

Cratypedes neglectus

GS|92.0|BOLD:AAG2875_KR
041070
GS|98.7|BOLD:AAA1468_KR
876306
GS|92.1|BOLD:ABA5839_KR0
34424
GS|95.3|BOLD:AAH0190_KM
850258
GS|83.4|BOLD:ABW2776_NA

Animalia

Arthropoda

Insecta

Hemiptera

Cicadellidae

Ceratagallia

Ceratagallia cinerea

Animalia

Arthropoda

Insecta

Hymenoptera

Formicidae

Formica

Formica glacialis

Animalia

Arthropoda

Insecta

Hemiptera

Cicadellidae

Euscelis

Euscelis confinis

Animalia

Arthropoda

Insecta

Coleoptera

Melyridae

Hoppingiana

Hoppingiana

Animalia

Arthropoda

Insecta

Orthoptera

Acrididae

GSL|93.4|BOLD:AAA3920_KJ
207446
GS|100.0|BOLD:AAE3210_NA

Animalia

Arthropoda

Insecta

Lepidoptera

Crambidae

Animalia

Arthropoda

Insecta

Diptera

Culicidae

Ceuthophilus agassizii

Leia

hudsonica

Culiseta

Culiseta morsitans

A.25
0989

GS|90.1|BOLD:AAM7579_NA

Animalia

Arthropoda

Insecta

Coleoptera

Dermestidae

Dermestes

Dermestes

0099

GS|88.7|BOLD:ACG4154_KM
443320
GS|100.0|BOLD:AAP6790_KR
692867
GS|95.7|BOLD:AAA2674_MF
873013
GS|99.3|BOLD:AAM7983_KM
825699
GS|99.7|BOLD:ACX2014_KT1
06334

Animalia

Arthropoda

Insecta

Coleoptera

Staphylinidae

Atheta

marmoratus
Atheta cribrata

Animalia

Arthropoda

Insecta

Diptera

Chloropidae

Incertella

Incertella incerta

Animalia

Arthropoda

Insecta

Diptera

Drosophilidae

Drosophila

Drosophila

Animalia

Arthropoda

Trombidiformes

Erythraeidae

Animalia

Arthropoda

Arachnid
a
Insecta

Diptera

Chironomidae

0992
0996
0997
0998

subquinaria
Tanytarsus

Tanytarsus mendax

B.1

Appendix B GPS coordinates of sample sites
Table B.1 GPS coordinates (decimal degrees) of 2018 sample sites at Teck Resources Highland Valley Copper
mine and New Gold Inc. New Afton mine based on NAD 83/ BC Albers projection.
Site
Treatment site 1
Treatment site 2
Treatment site 3
Treatment site 4
Treatment site 5
Treatment site 6
Treatment site 7
Treatment site 8
Treatment site 9
Treatment site 10
Treatment site 11
Treatment site 12
Treatment site 13
Reference site 1
Reference site 2
Treatment site 14
Treatment site 15
Reference site 3
Reference site 4

GPS Coordinates
50.511519, -121.002735
50.510847, -120.999348
50.506219, -120.985045
50.506376, -120.992450
50.505604, -120.994691
50.504845, -120.978449
50.504424, -120.983555
50.496785, -121.007454
50.501484, -121.007532
50.504564, -120.981955
50.505577, -120.977773
50.500136, -120.981978
50.491549, -121.066168
50.518789, -121.026010
50.536450, -121.006242
50.655090, -120.534504
50.653393, -120.535907
50.681645, -120.531749
50.690958, -120.539467

C.1

Appendix C Complete ‘Indicspecies’ analysis tables
Table C.1 complete age
OTU
Indicator statistic
Reference (number of taxa=36)
0181
0.463
0124
0.438
0050
0.404
0011
0.360
0136
0.357
0045
0.349
0114
0.348
0055
0.339
0219
0.327
0244
0.327
0251
0.327
0258
0.327
0291
0.327
0358
0.327
0460
0.327
0502
0.327
0832
0.327
0063
0.310
0013
0.304
0140
0.304
1076
0.267
1144
0.267
1401
0.267
0214
0.267
0260
0.267
0275
0.267
0295
0.267
0304
0.267
0385
0.267
0400
0.267
0053
0.267
0546
0.267
0572
0.267
0606
0.267
0610
0.267
0865
0.267
New (number of taxa=7)
0930
0.392
0030
0.979

p-value
0.001
0.001
0.003
0.017
0.006
0.011
0.036
0.014
0.011
0.011
0.011
0.011
0.011
0.007
0.014
0.007
0.007
0.048
0.035
0.031
0.046
0.046
0.046
0.046
0.046
0.046
0.046
0.046
0.041
0.046
0.037
0.050
0.046
0.048
0.046
0.046
0.036
0.031

C.2
0206
0.316
1504
0.274
0234
0.274
0245
0.274
0067
0.274
Reference and Old (number of taxa=1)
0205
0.469
New and Old (number of taxa=2)
1367
0.440
1552
0.404

0.012
0.035
0.040
0.037
0.043
0.025
0.021
0.050

C.3
Table C.4 HVC Age
OTU
Indicator statistic
Reference (number of taxa=37)
0124
0.659
0181
0.620
0011
0.566
0045
0.555
1601
0.553
0050
0.538
0219
0.480
0244
0.480
0251
0.480
0258
0.480
0291
0.480
0460
0.480
1560
0.468
0013
0.462
0140
0.462
0063
0.417
0700
0.417
0426
0.410
1076
0.392
1144
0.392
1401
0.392
1586
0.392
0260
0.392
0275
0.392
0295
0.392
0304
0.392
0385
0.392
0400
0.392
0546
0.392
0572
0.392
0606
0.392
0610
0.392
0865
0.392
0088
0.388
0128
0.370
0454
0.359
0055
0.351
New (number of taxa=4)
0030
0.450
0040
0.442
0111
0.343
0081
0.343

p-value
0.001
0.001
0.002
0.003
0.017
0.002
0.003
0.003
0.003
0.003
0.003
0.005
0.007
0.006
0.004
0.011
0.011
0.02
0.021
0.021
0.021
0.021
0.021
0.021
0.021
0.021
0.009
0.021
0.017
0.021
0.014
0.017
0.021
0.046
0.030
0.041
0.041
0.024
0.028
0.044
0.043

C.4
Old (number of taxa=2)
0012
0.484
0344
0.412
Reference and Old (number of taxa=2)
0035
0.623
0205
0.477
New and Old (number of taxa=1)
0002
0.614

0.019
0.025
0.015
0.040
0.038

C.5
Table C.5 New Afton age
OTU
Indicator statistic
New (number of taxa=2)
0771
0.820
1504
0.707
Old (number of taxa=3)
0017
0.685
0267
0.632
0300
0.632
New and Old (number of taxa=1)
1499
0.798

p-value
0.005
0.016
0.018
0.034
0.032
0.018

C.6

Table C.2 all data amendment
OTU
Indicator statistic
Biosolids (number of taxa=3)
0040
0.416
0076
0.332
0948
0.304
Reference (number of taxa=33)
0181
0.463
0124
0.444
0050
0.398
0011
0.366
0114
0.352
0136
0.351
0045
0.351
0055
0.329
0219
0.327
0244
0.327
0251
0.327
0258
0.327
0291
0.327
0358
0.327
0460
0.327
0502
0.327
0832
0.327
1076
0.267
1144
0.267
1401
0.267
1586
0.267
0214
0.267
0260
0.267
0275
0.267
0295
0.267
0304
0.267
0385
0.267
0400
0.267
0053
0.267
0572
0.267
0606
0.267
0610
0.267
00865
0.267
No biosolids (number of taxa=7)
0064
0.403
0771
0.327
0590
0.313

p-value
0.024
0.025
0.028
0.001
0.001
0.004
0.009
0.032
0.008
0.008
0.028
0.011
0.011
0.011
0.011
0.011
0.009
0.010
0.009
0.009
0.049
0.049
0.049
0.049
0.037
0.049
0.049
0.049
0.049
0.049
0.049
0.044
0.049
0.043
0.041
0.049
0.012
0.043
0.042

C.7
0526
0.302
0116
0.261
0215
0.261
0389
0.261
Biosolids and no biosolids (number of taxa=2)
1367
0.440
1552
0.404
Reference and no biosolids (number of taxa=7)
0015
0.557
0570
0.545
0205
0.523
0027
0.505
1499
0.391
0007
0.342
0063
0.333

0.038
0.049
0.042
0.047
0.025
0.039
0.025
0.001
0.002
0.002
0.008
0.021
0.034

C.1
Table C.3 HVC amendments
OTU
Indicator statistic
Biosolids (number of taxa= 1)
0040
0.462
Reference (number of taxa= 34)
0124
0.666
0181
0.620
0011
0.572
0045
0.555
1601
0.546
0050
0.529
0219
0.480
0244
0.480
0251
0.480
0258
0.480
0291
0.480
0460
0.480
1560
0.463
0013
0.452
0140
0.452
0426
0.418
0700
0.396
1076
0.392
1144
0.392
1401
0.392
1586
0.392
0260
0.392
0275
0.392
0295
0.392
0304
0.392
0385
0.392
0400
0.392
0546
0.392
0572
0.392
0606
0.392
0610
0.392
0865
0.392
0454
0.371
0152
0.352
No Biosolids (number of taxa=4)
0205
0.526
012
0.500
064
0.459
0590
0.367

p-value
0.034
0.001
0.001
0.001
0.001
0.049
0.002
0.003
0.003
0.003
0.003
0.003
0.003
0.010
0.008
0.006
0.10
0.043
0.014
0.014
0.014
0.029
0.014
0.014
0.014
0.014
0.023
0.014
0.018
0.014
0.018
0.021
0.014
0.023
0.025
0.006
0.018
0.032
0.042

C.2
Biosolids and No Biosolids (number of taxa=1)
0002
0.617
Reference and No Biosolids (number of taxa =1)
0015
0.677

0.026
0.001