Bachelor of Natural Resource Sciences

UNDERGRADUATE RESEARCH EXPERIENCE AWARD PROGRAM
in the
Department of Natural Resource Sciences

Assessing the Atmospheric Deposition of Heavy Metals
Using Biomonitoring of Moss Near a Mine in Southcentral British Columbia
BY
KELLIE E. SYCH
NOVEMBER 30TH, 2020

Assessing the Atmospheric Deposition of Heavy Metals Using Biomonitoring of Moss Near a Mine in
South-central British Columbia
By: Kellie E. Sych
A Final Report Submitted In Fulfillment Of The Requirements For The Undergraduate Research
Experience Award Program
In the Department of Natural Resource Sciences
At
Thompson Rivers University

Supporting Faculty
John Karakatsoulis, (Ph.D), Supervisor
Associate Teaching Professor, Department of Natural Resource Sciences
Christine Petersen, (MSc.), Co-supervisor
Associate Teaching Professor, Department of Biology
Kinsley Donkor, (Ph.D), Chemistry Analysis Supervisor
Professor, Department of Chemistry
Supporting Thompson Rivers University Student(s)
Abu Harera Nadeem, Chemistry Analyst and Student Research Assistant
Chemical Biology Undergraduate Student, Department of Chemistry
Zhi Chao Guo (Michelle), Chemistry Analyst
Masters Student in Environmental Chemistry, Department of Chemistry
I

ABSTRACT
Supervisor: Dr. John Karakatsoulis
Co-supervisor: Christine Petersen
Mines are known to cause severe environmental problems. Heavy metals appear in the
environment (i.e., during combustion, extraction, and processing), surface water (i.e., through
runoff and releases from storage and transport), and in the soil. Air pollution is noted to be the
primary concern of the public, in regard to mines. The presence of heavy metals in the air are
known to have a drastic effect on human health and cause ecological implications. Moss have
become a popular plant in monitoring studies as they have the ability to receive and accumulate
heavy metals through absorption from the atmosphere and from their rooting substrate. These
plants are very simple morphologically and anatomically and as a result, they are often chosen as
an ideal organism for biomonitoring. I collected a total of 90 moss samples from 3 primary radii
(North, East, and West) at distances of 1km, 2km, and 5km from the mine boundary for chemical
analysis in order to meet two primary objectives: 1) determine whether moss outside the limits of
the mine contain heavy metals: Lead (Pb), Zinc (Zn), Copper (Cu), and Nickel (Ni); and 2)
analyze the potential use and effectiveness of biomonitoring to assess ecosystem response. Due
to COVID restrictions, only samples from East 5km and West 2km were analyzed. Using flame
atomic adsorption spectrometry (FAAS), concentrations of Zn and Cu were found to be higher at
the East 5km site than at the West 2km site due to elevation, wind trends, and leaching.
Concentrations of Pb and Ni were undetectable by the FAAS. Moving forward, biomonitoring is
a relatively inexpensive, passive way to assess ecosystem response. Air pollution levels change
rapidly over time and moss as biomonitors are capable of monitoring and detecting external
conditions averaged over periods of time. The environmental impacts of mines outside their
boundaries is poorly studied and future research would be beneficial. A standardized protocol is
lacking for sampling, sample preparation, and elemental analysis.

Keywords: biomonitoring, bioindicator, biodiversity, moss, mining, heavy metals, pollution

II

TABLE OF CONTENTS
ABSTRACT ............................................................................................................................... II
LIST OF TABLES ..................................................................................................................... IV
LIST OF FIGURES .................................................................................................................... V
INTRODUCTION ....................................................................................................................... 1
STUDY SITES ........................................................................................................................... 5
METHODS ............................................................................................................................... 8
FIELD DATA COLLECTION ...............................................................................................................8
CHEMICAL ANALYSIS ......................................................................................................................8
STATISTICAL ANALYSIS ...................................................................................................................9

RESULTS ................................................................................................................................. 9
DISCUSSION ...........................................................................................................................11
SITE CLASSIFICATION AND VEGETATION DATA ............................................................................ 11
FACTORS AFFECTING HEAVY METALS CONCENTRATIONS ........................................................... 11

CONCLUSIONS AND PROPOSED FUTURE STUDIES .....................................................................12
LITERATURE CITED ................................................................................................................15
APPENDIX A. ..........................................................................................................................19
APPENDIX B. ..........................................................................................................................20
APPENDIX C. ..........................................................................................................................21

III

LIST OF TABLES
Table 1. Summary of two-sample t-test results. T-test compared average µg Zn/g of moss
samples from each site (East 5km and West 2km). . ....................................................................... 9
Table 2. Summary of two-sample t-test results. T-test compared average µg Cu/g of moss
sampled from each site (East 5km and West 2km). ...................................................................... 10
Table 3. Site classification information collected for the East 5km site, and the West 2km site. . 20
Table 4. Vegetation data collected for the East 5km site and the West 2km site. Data provided in
percent cover. ................................................................................................................................ 20
Table 5. Summary of moss samples identified to Genus and percent coverage along a 10m
transect within a 5km radius East of the mine. Data collected on July 10th, 2020. ...................... 21
Table 6. Summary of moss samples identified to Genus and percent coverage along a 10m
transect within a 2km radius West of the mine. Data collected on July 10th, 2020. ...................... 21

IV

LIST OF FIGURES
Figure 1. Photo taken on July 10th, 2020 at the starting point of the East 5km transect line. ......... 6
Figure 2. Photo taken on July 10th, 2020 at the starting point of the West 2km transect line. ........ 7
Figure 3. Average concentrations of Zn and Cu per gram of moss in samples collected from the
East 5km and West 2km sites. Concentrations between the two sites were significantly different
(Cu: p=0.023; Zn: p=0.000). Error bars represent 1 SE. ............................................................... 10
Figure 4. Map outlining the boundary of Highland Valley Copper Mine with 1km, 2km, and 5km
radii overlaid. Potential access also outlined. The map was created and provided by Nikki Knuit,
a GIS Technician with BC Timber Sales. Blue dots were added to display site locations. .......... 19

V

INTRODUCTION
Ecosystems are fundamentally comprised of various biotic and abiotic factors that work
together to perform ecosystem functions. Without all of these factors, an ecosystem would be
unable to function properly. Fauna act as key players ecologically requiring food, thus playing a
role in energy transfer. Meanwhile, flora and fauna provide food to various different organisms.
Relationships between all biota in an ecosystem can be described in the form of an ecological
pyramid or trophic levels. Ecological pyramids refer to the community structure in an ecosystem,
whereas trophic levels refer to how energy is moved throughout the system. Understanding how
community structures occur in ecosystems is a fundamental goal in ecology. Community
structure and function are formed based on interactions amongst organisms and the nature of
these interactions is governed by the organisms involved (Trebilco et al. 2013). Simply put,
trophic pyramids are composed of primary producers on the bottom level, herbivores in the
middle, and carnivores on the top (Fath and Killian 2007). The sun is the primary source of
energy for almost every ecosystem on Earth. Primary producers, typically referring to plants in
terrestrial ecosystems, utilize energy from the sun to produce their own food. When primary
producers are consumed by herbivores, energy flows up the pyramid one level at a time. There
are several roles to be filled within ecological pyramids to ensure energy flows throughout the
system; none of this can be achieved without adequate biodiversity.
Biodiversity is a broad unifying concept encompassing all forms, levels and combinations
of natural variation, at all levels of biological organization. Put simply, biodiversity is the variety
of life (Gaston and Spicer 2004, Gardner 2010). It can be measured on a variety of scales and is
shaped by natural processes and increasingly by the influence of humans. The value of diversity
can be classified into direct and indirect values. Direct values include consumptive use (i.e.,
global food supply) and productive use (i.e., commercial pesticides, pharmaceutical products).
Whereas, the indirect values include: ethical, aesthetic, option, and environment service
(Meerabai and Pullaiah 2016). For the purpose of this study, I would like to highlight the
importance of biodiversity in plant communities.
Plants are a valuable resource for humanity; however, plant usage and importance are not
limited to humanity. Plant life balances ecosystems, mitigates erosion, protects watersheds,
moderates climate, and provides shelter for many animal species (Clark et al. 2018). Biodiversity
is threatened by increasing human population, pollution, deforestation, and species extinction

1

(Pennsylvania State University 2020). Several species found on this Earth are indicator species
give a signal by their presence, lack of abundance, or chemical composition about the distinctive
aspects of the character or quality of an environment. A perfect example of an indicator species
are moss species, sometimes referred to as bioindicators (Aboal et al. 2010, Angelovska et al.
2016, Berg and Steinnes 1997). The condition and health of moss can be used as an indication of
ecosystem health.
Mosses are small green land plants found in a variety of habitats across the globe.
Morphologically and anatomically, these plants are very simple (Godvindapyari et al. 2010,
Schofield 1927). They lack a true root system allowing them to absorb heavy metals over their
entire surface (Berg and Steinnes 1997, Degola et al. 2014, Stanković et al. 2018). Due to the
lack of a cuticle layer, and a large surface-to-weight ratio, the cell walls of moss, with
pronounced ion-exchange properties, are easily accessible to metal ions (Stanković et al. 2018).
As a result of their simplicity, they react and reflect changes in heavy metal concentrations faster
than most vascular plants making them an ideal organism for air pollution studies (Zvereva and
Kozlov 2011). Moss species reproduce at a rapid rate, are totipotent, and have a high heavy
metal accumulation capacity (Godvindapyari et al. 2010). Mosses have the capacity to absorb
heavy metals from the atmosphere, their rooting substrate, or a combination of the two; as such,
moss have recently become the most popular plant for biomonitoring studies (Aboal et al. 2010,
Angelovska et al. 2016, Berg and Steinnes 1997). Moss lack specialized conducting tissue
(Onianwa 2001) and have a slow growth rate (Chakrabortty and Paratkar 2006). Their growth
segments can provide information about the exposure to heavy metals over longer periods of
time, which can be very useful information in areas like mines where introduced heavy metals
change rapidly (Stanković et al. 2018). The state of the moss species (whether it is living or
dead) will affect the level of heavy metal contamination on the moss (Aboal et al. 2010, Berg
and Steinnes 1997). Heavy metals have been classified as one of the most dangerous groups of
anthropogenic pollutants due to their toxicity and persistence in the environment (Koz et al.
2012). Industrial processing and mining are two of the main sources of heavy metal
contamination in the environment (Angelovska et al. 2016, Koz et al. 2012). Air pollution can
result in a decrease in biodiversity and productivity in forests. In order to maintain a sustainable
environment and minimize human expose to these strong pollutants, environmental policy must
reflect desired outcomes.

2

There is a lack of environmental regulation, leading to a large input of toxic pollutants to
the atmosphere, particularly from mining (Govindapyari et al. 2010). Biomonitoring is an
excellent, cost-efficient method of monitoring air quality and could be used to test the impact
mines are having on the environment surrounding their boundaries. Moss, as a bioindicator, is
able to depict the quality of the environment on the basis of changes observed in the plant itself
(Saxena and Harinder 2004). Air pollution problems can often arise in urban valleys due to high
emissions of pollutants and limited ventilation resulting from inversions (Rendón et al. 2015). In
complex terrain, such as in the Kamloops British Columbia region, topography limits the
ventilation of pollution out of the valley and traps heat. With heavy metals being carried via air,
this can result in the deposition of the particles in highly populated areas of the city, which will
in turn have negative effects on human health and the vitality of plants species. Several elements
pose a potential threat to human health in high levels including lead (Pb), cadmium (Cd), and
arsenic (As). Copper (Cu) and Zinc (Zn) are essential to the human body for proper cellular
function, regulation of the immune system, wound healing, and the synthesis of
neutrotransmitters. Often elevated levels of Cu depress the absorption of Zn levels in the human
body and vice versa (Hoffman et al. 1988). Zinc deficiencies can cause various symptoms such
as, hair loss, weight loss, and problems with wound healing. Deficiencies of copper can lead to
problems with connective tissue, muscle weakness, and neurological problems, however too
much copper and zinc can be toxic (Uni. Of Roch. Med. Center 2020). Airborne emissions of
these metals are of particular concern in terms of human health, because of the widespread
dispersal capability and the inability of humans to avoid polluted air. Air quality in these areas
also depends on the intensity of emissions, as well as atmospheric dispersion, chemical
transformation conditions, and topographic location (Baumbach and Vogt 2003).
With environmental degradation becoming a prominent issue in today’s society, there is
growing concern for the environmental effects of mines. Studies have found high concentrations
of heavy metals in the surrounding area of abandoned mines (Angelovska et al. 2016;
Godvindapyari et al. 2010). Using atomic emission spectrometry with inductively coupled
plasma, over 20 different elements were found in moss samples around a lead-zinc mine near
Krivia Palanks town in Eastern Macedonia (Angelovska et al. 2016). Although heavy metals are
naturally occurring, an excess amount can result in ultrastructural changes in chloroplasts and
cell membranes as well as changes in the physiological processes and characteristics of moss
(Choudhury and Panda 2005). Once heavy metals are introduced to the environment, they are

3

often hard to remove and tend to accumulate in the tissues of plants and other organisms
throughout the food chain (Lee and Von Lehmden, 1973, Maevskaya et al. 2001, Stanković et al.
2018.). Continuous monitoring is needed to ensure the heavy metals concentrations in the
environment do not begin to negatively affect and influence ecosystems.
Highland Valley Copper Operations (HVC) is a copper and molybdenum operation
located approximately 17km west of Logan Lake and about 50km southwest of Kamloops in
British Columbia. Annual copper production is between 155,000 and 165,000 tonnes per year.
This mine is one of the largest open pit copper mining and concentrating operations in the world
(Teck Resources Limited 2019). Mining operations at Highland Valley began in 1962. HVC was
created by the combination of three historic mining operations in 1986: Bethlehem, Lornex, and
Highmont. The Bethlehem Copper operation was operating until 1982, meanwhile development
began for the Lornex pit. Highmont Operating Corporation ran from 1979 until 1984 (BC Mine
… n.d.). Over time, the mine increased in size and now occupies roughly 10,000 hectares (iMap
BC 2020). Under the current mine plan, Highland Valley Copper Operations will be operating
until 2027 (Teck Resources Limited 2019).
Prior to beginning their operations, HVC had to obtain a Project Approval Certificate at
the mine. In order to do this, potential impacts on watersheds, fish and aquatic resources, wildlife
resources, and land use was assessed through the use of models that facilitated projections of the
effects under various management scenarios as required by the Environmental Code of Practice
for Metal Mines. The code of practice was created with the objective of identifying and
promoting the recommended best practices to encourage continual improvement in the
environmental performance of mining through the mine life cycle (Gov. Canada 2013). A
comprehensive mitigation and several monitoring plans were developed based on the results of
the projections (Associated Environmental n.d.). My study took place outside the boundary of
HVC to determine whether the environment outside of the mine boundary was being
contaminated.
My study performed a chemical analysis on moss samples to determine heavy metal
quantities in species located outside the boundaries of the Highland Valley Copper Mine. My
overarching objective with this study was to collect new data and observations on the potential
use of moss species as biomonitors within the low-elevation Douglas-fir forests in south-central
British Columbia. More specifically, I sought to

4

1) Determine whether moss outside the limits of the mine contain heavy metals:
Lead (Pb), Zinc (Zn), Copper (Cu), and Nickel (Ni)
2) Analyze the potential use and effectiveness of biomonitoring to assess ecosystem
response
With these findings, further preventative measures can be put in place to ensure that mine
companies are mitigating their impact on environmental pollution as much as possible.

STUDY SITES
Site determination was done using maps and forestry road exploration to determine
access (Appendix A). My study sites were located approximately 20km west on the outskirts of
Logan Lake, British Columbia adjacent to the boundary of the Highland Valley Copper Mine.
Study sites were located within 1km, 2km, and 5km radii in the East, West, and North cardinal
directions from the mine boundary (Appendix A). Due to laboratory restrictions as a result of
COVID-19, the only samples that were analyzed for the purpose of this preliminary report
include those collected at East 5km and West 2km.
All study sites were located within the Interior Douglas-fir (IDF) Biogeoclimatic (BEC)
zone, dk1 (dry, cool) variant (Meidinger and Pojar 1991a and b). The West 2km site was located
in a transition zone between the IDKdk1 zone and the MSxk (Montane Spruce, (very dry, cool)
variant) zone. The IDFdk1 zone occurs in the lee of the Coast and Cascade mountains. It
occupies lower to middle elevations of the southern Interior Plateau. Continental climate is
characterized by warm, dry summers, a relatively long growing season, and cool winters. A
rainshadow is the main factor controlling climate in this zone created in the lee of the Coast,
Cascade, and Columbia mountains. Growing season moisture deficits are common as roughly
20-50% of all precipitation received falls as snow. The soils in this zone often have medium to
rich nutrient status (Meidinger and Pojar 1991a). The Montane Spruce zone is found
elevationally above the Interior Douglas-fir zone. The growing season is relatively warm and dry
and moisture deficits can occur. This zone lacks many species that are characteristics of the IDF
zone (Meidinger and Pojar 1991b).
The East 5km site (50.4740 -120.8943) was located at approximately 1200m in elevation
(Figure 1). Forest cover consisted of mixed Interior Lodgepole pine (Pinus contorta var.
latifolia) and Interior Douglas-fir (Pseudotsuga menziesii var. glauca) stand. Understory

5

vegetation composition was limited to pinegrass (Calamagrostis rubscens), red-stem feathermoss
(Pleurozium schreberi), and twinflower (Linnea borealis) (Table 4).

Figure 1. Photo taken on July 10th, 2020 at the starting point of the East 5km transect line.

6

Figure 2. Photo taken on July 10th, 2020 at the starting point of the West 2km transect line.

7

The West 2km site (50.5790 -121.200) was located in an area where forest harvesting
commonly occurs (Figure 2). Vegetation on the site consisted mostly of young and mature
Interior Douglas-fir (Pseudotsuga menziesii var. glauca) with minimal Interior Lodgepole pine
the understory was comprised primarily of herbs and grasses. The understory of the East and
West sites was very similar; however, percent cover of moss was higher at the West 2km site
than the East 5km site (Table 4).

METHODS
FIELD DATA COLLECTION
Field data collection occurred on July 10th, 2020 during the peak of the growing season.
Upon arrival to the sites, site classification information was collected along with vegetation
information (Appendix B, Tables 1 and 2). A 10m transect line was laid in pre-determined study
site locations deemed representative of the plant community. Along the transect line, a 30cm by
30cm grab sample of moss was taken every meter using a frame constructed out of white PVC
piping. Species were identified to genus using a field identification guide written by Ryan, MW
(n.d.) and a percentage estimate was taken for their coverage (Appendix C, Tables 3 and 4). In
areas along the transect line where no moss was detected, the frame was moved up to 1.5m off
the transect line in either direction creating a 1.5m buffer for moss detection.

CHEMICAL ANALYSIS
Chemical analysis was conducted by chemical biology undergraduate student, Abu
Harera Nadeem and Zhi Chao Guo, a masters student in environmental chemistry, under the
supervisor of Dr.Kinsley Donkor. Chemical analysis was conducted using methods developed by
Rinne and Barclay (1980), to determine concentrations of Pb, Zn, Cu, and Ni measured in a
microgram of the metal per gram of moss. Few modifications were made to the methods due to
differing equipment available in the laboratory. Rather than boiling samples, a microwave
digester was used and a pre-made program was created. The pre-made program began at 40°C
then increased at 10mm/ss until it reached a temperature of 100°C. At this time, the digester held
for 2 minutes and then proceeded to increase in temperature up to 185°C, once it cooled the
samples were digested. Once digested, samples were filtered through a 0.45 micrometer nylon
filter. Sample vials were rinsed twice with 18 MOhm water and diluted to 50mL in a volumetric
flask using 18 MOhm water. For 48-72 hours the samples were stored in a fridge until the flame
atomic absorption spectrometry (FAAS) analysis was conducted.

8

STATISTICAL ANALYSIS
Results were compiled using Microsoft Excel. Each sample was run through the FAAS
three times; therefore, the results were averaged for each sample. A Two-Sample T-Test was
conducted using MiniTab (Vers. 19) to compare whether the mean concentrations of Zn and Cu
were equal at the East 5km site versus at the West 2km site.

RESULTS
Site classification and vegetation information data were collected at a total of nine
different study sites. A total of 90, 30cm by 30cm, grab samples of moss were collected. Results
displayed are preliminary, based solely on the East 5km and West 2km locations. Due to
COVID-19 restrictions throughout the university, the entire lab sample analysis will not be
completed until December 2020. Majority of the samples collected at the East 5km site were
identified as Pleurozium spp. (Appendix C, Table 5). The West 2km site showed more variation
in the species found on site. The site was dominated by Pleurozium spp., but Dicranum spp.,
Pohlia spp., and Brachythecium spp. were also found and sampled (Appendix C, Table 6).
Chemical analysis was conducted to determine the concentrations of four main metals in
the samples for the East 5km and West 2km sites. Both sites contained the same number of
samples. The concentrations found for Pb and Ni thus far were not within the detectable limit of
the FAAS, and therefore will not be discussed. When comparing the average concentration of
Zinc measured in micrograms per gram of moss for the East 5km and West 2km sites using a
two-sample t-test, it can be observed that the mean of the average concentrations is much higher
at the East 5km site. The standard deviation and standard error mean are both greater values as
well. The results determined the means to be significantly different with a p-value of 0.023 and a
t-value of 2.49 (Table 1).
Table 1. Summary of two-sample t-test results. T-test compared average µg Zn/g of moss samples from each site
(East 5km and West 2km). .

Sample

Sample Size

Mean

Standard

Standard

Deviation

Error Mean

East 5km

10

56.5

21.2

6.7

West 2km

10

34.2

18.8

5.9

9

T-Value

P-Value

2.49

0.023

When comparing the average concentration of Copper in each one-gram sample, the
mean for the East 5km site was again found to be greater than that of the West 2km site. The tvalue was calculated to be 5.11 and the p-value was 0.000, respectively (Table 2).
Table 2. Summary of two-sample t-test results. T-test compared average µg Cu/g of moss sampled from each site
(East 5km and West 2km).

Sample

Sample Size

Mean

Standard

Standard

Deviation

Error Mean

East 5km

10

133.0

54.9

17.0

West 2km

10

41.0

15.0

4.8

T-Value

P-Value

5.11

0.000

Overall, mean concentrations of both Copper and Zinc were very high in the East 5km
samples (133.0 µg Cu/g of moss and 56.47 µg Zn/g of moss) in comparison to the West 2km
samples (40.97 µg Cu/g of moss and 31.17 µg Zn/g of moss) (Figure 3).
160
140

- East

Mean concentrations
(µg/g Moss)

120

- West

100
80
60
40
20
0

Zinc (Zn)

Copper (Cu)

Figure 3. Average concentrations of Zn and Cu per gram of moss in samples collected from the East 5km and West
2km sites. Concentrations between the two sites were significantly different (Cu: p=0.023; Zn: p=0.000). Error bars
represent 1 SE.

10

DISCUSSION
SITE CLASSIFICATION AND VEGETATION DATA
The West 2km site was more difficult to classify into a specific Biogeoclimatic zone
based on the vegetation data and the site classification information collected. The site had plants
from both the IDF zone and the MS zone. Vaccinium scoparium is a species more commonly
found in the MS zone, whereas Calamagrostis rubescens is often found in the IDF zone. The MS
zone generally occurs at higher elevations that the IDF zone, however upper elevations of the
IDF zone are at 900 to 1450m. The MS zone ranges from 1100 to 1500m in elevation in wetter
parts of the zone, and from 1250 to 1700m in drier areas. The West 2km site had an elevation of
1425m and showed visible signs of seepage and a water table close to the surface.

FACTORS AFFECTING HEAVY METALS CONCENTRATIONS
Results from the two-sample t-test comparing the two sites showed that mean
concentrations were significantly different. Both t-values calculated (2.49 and 5.11) for the
concentrations of Zn and Cu act as evidence that there is a significant difference between
concentrations found at the East 5km site versus the West 2km site. The p-values are both very
low (0.023 and 0.000) suggesting there is great difference in the concentrations collected. Mean
concentrations of Zinc and Copper detected in the East 5km samples were much higher than
those found in the West 2km samples. My original hypothesis was that samples collected further
away from the mine boundary (i.e. 5km) would contain lower concentrations of heavy metals
than those collected within one and two kilometers from the boundary.
All moss samples analyzed contained heavy metals, however none of the samples
analyzed thus far contain Pb or Ni. Metals such as Zinc and Copper are essential to moss plants,
therefore there may always be a background level of the element in the moss (Berg and Steinnes
1997). My study did not account for the base concentrations of metal elements that moss require.
Copper and Zinc toxicity is relatively well studied in vascular plants (Elvira et al. 2020,
Choudhury and Panda 2005), however much less is known about copper tolerance and resistance
in bryophytes (Elvira et al. 2020). Various species of bryophytes such as the genera Scopelophila
and Mielichhoferia are metallophilous, which means they require high metal levels to develop
and therefore they uptake and concentrate metals in their tissues. Moss species that are native
from contaminated soils often display higher tolerances to heavy metal contamination (Elvira et
al. 2020). I struggled to find data in the literature describing acceptable tolerance levels of Zinc
and Copper in moss species.
11

A large proportion of the pollutant load accumulates in mosses through wet deposition
(Chakrabortty and Paratkar 2006). Copper is known to be an element that has a high uptake
efficiency from wet deposition (Ross 1990). Accumulation and leaching are affected by the
duration, intensity, and the amount of precipitation (Berg and Steinnes 1997). The East 5km site
was characterized by a more arid climate, therefore the contribution of dry deposition would
increase (Couto et al. 2004). Concentrations of heavy metals in the moss samples can be affected
by various factors: stand throughfall, the nutrient status of the site, altitude, age of the moss,
sampling technique, etc. (Chakrabortty and Paratkar 2006). Moss samples were collected using
bare hands and samples were collected under the canopy and near other plants, which contradicts
many sampling techniques found in the literature (Fernández et al. 2015).
I speculate that the moss samples collected at the East 5km site contain a greater
concentration of heavy metals due to numerous factors. When looking at historical wind trends,
it can be observed that prior to field data collection prevailing winds blew towards the East
(Enviro. Canada 2020). Wind-blown dust may carry pollutants from the mine for several
kilometers eventually resulting in deposition (Angelovska et al. 2016). Research conducted by
Kim et al. (2012) concludes westerly winds were associated with enhanced concentrations of
trace-elements in precipitation It is important to note that my study did not account for any soil
dust that may have been deposited on the moss samples, therefore the results may be slightly
skewed.
Natural sources may also contribute to the observed results: natural and cyclic processes, root
uptake in higher plants and transfer to the moss, mineral particles releases to the air (i.e., from
wind erosion to local soil), and uptake from the ground when the surface is saturated with water.
The East 5km site is lower in elevation than the West 2km site, conceivably watershed processes
could be impacting the deposition of metals as leaching occurs down the elevational gradient
(Jarsjö et al. 2017). Perhaps there is an ideal distance that heavy metals can be suspended in the
air for. After travelling 5km the particles may begin to deposit. There was no evidence found to
support this claim, however it may be valuable to consider and study further.

CONCLUSIONS AND PROPOSED FUTURE STUDIES
Biomonitoring is a great way to assess ecosystem response moving forward. It is passive
and provides a measure of integrated exposure over a period of time. This method is relatively
inexpensive, and no long-term use of expensive sampling equipment is required. Heavy metal

12

concentrations within the moss samples are higher than within the ecosystem as whole therefore,
accuracy of measurements is improved. It is apparent that air pollution levels change rapidly
over time. The use of moss as biomonitors has the capability to monitor and detect external
conditions averaged over certain periods of time. Moss is a renowned and respected species to
use a biomonitor as it is common to various areas across British Columbia, it is available for
sampling during the field season, and it is relatively tolerant to pollutants (Berg and Steinnes
1997).
My primary objective was to provide insight into the environmental pollution caused by
mines outside of their boundaries; I sought to compare data collected in two different sites, at
two different distances from the mine boundary. The analysis of my results and the depth of my
study was limited by time, my ability to access potential study sites, a small sample size, and
ultimately restrictions imposed by the ongoing global pandemic, but overall, my data provides a
foundation for a more detailed study on the environmental impacts of mines outside their
boundaries. I feel biomonitoring studies lack a standardized protocol for sampling, sample
preparation, and elemental analysis. Without a standardized method it is difficult to obtain
comparable results. It would be interesting to conduct more studies combining the use of dustfall
monitoring and biomonitoring. Soils often contain quantities of heavy metals as well and surely
through soil dusting, soils may deposit on moss. In order to account for heavy metal deposition
via soil dusting, biomonitoring in combination with soil analysis could be performed. It would
be beneficial to further understand what mean levels of heavy metals moss samples contain to
maintain themselves. As aforementioned, moss species require certain quantities of metal
elements for growth, development, and reproduction (Berg and Steinnes 1997, DalCorso et al.
2014). With the knowledge of those quantities, calculations could account for them and subtract
them from total concentration values.
Currently, the environmental impact of mines outside of their boundaries is poorly
studied. The majority of the literature focuses on how moss can be used as biomonitors but does
not delve deep into the importance of biomonitoring in Natural Resource Management. This
research will contribute to bridging the knowledge gap of the air pollution effects outside mine
boundaries, with emphasis on determining whether there are any heavy metals present in moss
samples in those areas. It is known that bioindicators are a useful tool when assessing air quality;
biomonitoring could be an effective and economical alternative to investigating trace-element
atmospheric pollution. The findings of this project provide important information about the

13

impact mines have on the environment surrounding their boundaries and will hopefully increase
the frequency in which natural resource managers use moss as bioindicators. It is my hope that
moving forward management strategies and policies will reflect the goal of decreasing air
pollution caused by heavy metal mines.

14

LITERATURE CITED
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/10.1007/s00244-015-0251-7.pdf doi: https://doi.org/10.1007/s00244-015-0251-7
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15

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Fernández, JA. Boquete, A., Carballeira, Aboal, JR. 2015. A critical review of protocols for
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Gardner, T. 2010. Monitoring Forest Biodiversity: Improving Conservation Through
Ecologically Responsible Management. Routledge.
[Gov. Canada] Government of Canada [Internet]. 2013. Environmental Code of Practice for
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Govindapyari H, Leleeka M, Nivedita M, Uniyal PL. 2010. Bryophytes: indicators and
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/1901/byrophytes%20article.pdf

16

iMap BC. 2020. B.C. Conservation Data Centre: CDC iMap [web application]. [cited 2020 Nov
23]. Victoria, British Columbia, Canada. Available from: http://maps.gov.bc.ca/
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Koz, B., Cevik, U., Akbulut, S. 2012. Heavy Metal analysis around Murgul (Artvin) copper
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17

Saxena DK, Harinder. 2004. Uses of Bryophytes. Resonance [Internet]. [cited 2020 Oct 4]. 9:
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18

APPENDIX A.
121°4'0"W

121°2'0"W

121°0'0"W

120°58'0"W

Leighton120°52'0"W
L

120°56'0"W

120°54'0"W

n

5 km Buffer

a

n

Main Road or Highway

d

Gravel or Unimproved Road

e

e

50°28'0"N

!

k

S p a i s t
n
M o u n t a i

C r

Dot

Mamit
Lake

Lake

SOAP LAKE
ECOLOGICAL
RESERVE

121°18'0"W

k

o

G n a w e d
n
M o u n t a i
r

121°16'0"W

121°14'0"W

121°12'0"W

121°10'0"W

!

!

!

!

!

Flooded Land - Inundated Indefinite
Marsh

Î!

Island
Protected Areas & Prov Parks
Study Sites
West 2km (top-left), East
5km (bottom-right)

50°24'0"N

M

C

121°20'0"W

o

s

L
121°22'0"W

Lake - Indefinite/Intermittent/Marshy
!

50°26'0"N

u

P

S

n

River/Stream/Lake

Gump
Lake

u h o s t

50°24'0"N

50°26'0"N

50°28'0"N

Soap

e s

Rail Line

!

T

Airstrip

a

O

H

Bridge

!

nnie
Ra oad
R
Pit

h
oad
Nort tage R
Fron
B
8N
Rte

t c h

s
Witche
k Road
Broo

Tunnel

!

i m

y

B r

Wi

O

e k

P

ka R
na te
ga

e

O

N

50°30'0"N

l

Snow Shed (Railway)

È

r e

Ok
Lake

r

l

r

Trail

!

C

C

Quiltanton
Lake

a

- to
B ec
W nn
97 C o
n

Rte
EB
97D

a k w i l
S k w i l k w
i n
a
t
n
u
121°8'0"W M 121°6'0"W
121°4'0"W
121°2'0"W
o

.

50°22'0"N

50°34'0"N

i et
ar
ab ad
o

50°32'0"N

l

V

Big

2 km Buffer

!

h

l

Martel

1 km Buffer

C

Logan Lake
I n k i k u h

121°24'0"W

Highland Valley Copper Mine
50°32'0"N

g

Highland Valley Copper Mine

50°30'0"N

i

Legend

wa
Tunk
Old ad
Ro

da
na

North
Road

a
sC

Tunkwa
Lake Road

n
Tra

H

M
i nn
R

Spences
Bridge

Highland Valley Copper Mine
with Buffers of 1, 2 and 5 km

50°34'0"N

Rte 97C WB Highlan
d Valley

B-

F o r g e
M o u n t a i

Spatsum

s
ble d
na o a
Ve ley R
l
Va

Lake

120°48'0"W

TUNKWA PARK

Tunkwa
Lake

EPSOM
PARK

Venables

120°50'0"W

!

121°6'0"W

50°36'0"N

121°8'0"W

G l o s s y
n
M o u n t a i

Î

50°38'0"N

121°10'0"W

d

1E

50°36'0"N

121°12'0"W

!

121°14'0"W

f Roa
Relie

Rte

e k

Drinkwater
Road
UE
BAS Q T
W ES

e

121°16'0"W

!

121°18'0"W

!

121°20'0"W

!

121°22'0"W

G y p s u m
n
M o u n t a i

0

1,250

120°58'0"W

120°56'0"W

120°54'0"W

120°52'0"W

120°50'0"W

3,750

5,000

6,250
Meters

1:125,000
Date

2020-06-24

Template Name
121°0'0"W

2,500

User

NKNUIT

Kellie_HVC_11x17L

Coordinate System

NAD 1983 BC Environment Albers

Figure 4. Map outlining the boundary of Highland Valley Copper Mine with 1km, 2km, and 5km radii overlaid. Potential access also outlined. The map was created and provided by Nikki Knuit, a
GIS Technician with BC Timber Sales. Blue dots were added to display site locations.

19

APPENDIX B.
Table 3. Site classification information collected for the East 5km site, and the West 2km site.

General Features
BEC zone/subzone/variant
Elevation (m)
Slope Gradient (%)
Aspect
Slope Position
Slope Shape
Soil Features
Soil Texture
Seepage or Ground Water Table
Gleyed Horizon
Flooding
Soil Colour
A Horizon/Thickness (cm)
Humus Form/Thickness (cm)
Soil Order

East 5 km
IDFdk1
1200
0
Flat
Straight

West 2 km
IDFdk1/MSxk
1425
0
Flat
Straight

Loamy
No
No
No
Medium
Ah/1cm
Mor-Moder/5cm
Brunisol

Silty
Yes
Unknown
No
Medium
Ah/2cm
Moder/3cm
Brunisol (Gleysol)

Table 4. Vegetation data collected for the East 5km site and the West 2km site. Data provided in percent cover.

Trees (% Cover)
Pinus contorta var. latifolia
Pseudotsuga menziesii var. glauca
Shrubs (% Cover)
Arctostaphylos uva-ursi
Populus tremuloides
Rosa acicularis
Shepherdia canadensis
Vaccinium scoparium
Spiraea betulifolia
Juniperus communis
Herbs/Grasses (% Cover)
Calamagrostis rubescens
Arinca cordifolia
Fragaria virginiana
Aster consicuus
Epilobium angistifolium
Linnaea borealis
Lathyrus nuttalli
Mosses/Lichens (% Cover)
Pleurozium shreberi

East 5 km
25
2

West 2 km
5
30
4

<1
3
3

45
2

1
7
1
1
<1
30
1
1
3
1

5
1
7

20

15

APPENDIX C.
Table 5. Summary of moss samples identified to Genus and percent coverage along a 10m transect within a 5km radius East of
the mine. Data collected on July 10th, 2020.

Sample Name
E-5km-1m
E-5km-2m
E-5km-3m
E-5km-4m
E-5km-5m
E-5km-6m
E-5km-7m
E-5km-8m
E-5km-9m
E-5km-10m

Genus
Pleurozium spp.
Brachythecium spp.
Pleurozium spp.
Pleurozium spp.
Pleurozium spp.
Pleurozium spp.
Pleurozium spp.
Pleurozium spp.
Pleurozium spp.
Pleurozium spp.

Percent Cover (%)
80
12
80
20
30
50
80
80
80
70

Table 6. Summary of moss samples identified to Genus and percent coverage along a 10m transect within a 2km radius West of
the mine. Data collected on July 10th, 2020.

Sample Name
W-2km-1m
W-2km -2m
W-2km -3m
W-2km -4m
W-2km -5m
W-2km -6m
W-2km -7m
W-2km -8m
W-2km -9m
W-2km -10m

Genus
Pohlia spp. and Dicranum
spp.
Brachythecium spp.
Pleurozium spp.
Pleurozium spp.
Pleurozium spp. and
Dicranum spp.
Pleurozium spp. and
Dicranum spp.
Brachythecium spp.
Pleurozium spp.
Pleurozium spp.
Pleurozium spp. and
Dicranum spp.

21

Percent Cover (%)
80
12
80
20
30
50
80
80
80
70