DISTRIBUTION OF PLANT FUNCTIONAL GROUPS
ACROSS GRASSLAND-FOREST ECOTONES: TESTING THE
ASSUMPTIONS
by Mandy J. Ross
BSc., University of Guelph, 2007

A THESIS SUBMITTED IN THE PARTIAL FULFILLMENT OF THE
REQUIREMENTS FOR THE DEGREE OF
Masters of Science
in
Environmental Science

Thompson Rivers University
Kamloops, British Columbia, Canada
December 2016

Thesis examining committee:
Lyn Baldwin (PhD)
Department of Biological Sciences, Thompson Rivers University
Lauchlan Fraser (PhD)
Department of Natural Resource Sciences, Thompson Rivers University
Darryl Carlyle-Moses (PhD)
Department of Geography and Environmental Studies, Thompson Rivers
University
André Arsenault (PhD)
Natural Resources Canada, Canadian Forest Service
Rafael Otfinowski (PhD), External Examiner
Department of Biology, University of Winnipeg

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ACKNOWLEDGEMENTS
I would like to thank my supervisor Dr. Lyn Baldwin for her guidance and
patience on this project. Thanks to my committee members Dr. Lauchlan Fraser,
Dr. Darryl Carlyle-Moses and Dr. André Arsenault.
I would also like to thank Marc Jones for is help with statistics and editing.
Thanks to Andrew Corks for his never-ending help with fieldwork and support
throughout this project. And thanks to Sabina Donnelly, Ceryne Staples, Kathy
Dueck and Frank Pouw for their help in the field.
I would also like to thank the Nature Conservancy of Canada and BC
Parks for allowing this research to be carried out in Lac du Bois Grasslands
Protected Area.

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Thesis Supervisor: Dr. Lyn Baldwin

ABSTRACT
Ecotones, transition zones found at abrupt discontinuities in vegetation,
are a part of every landscape and have long been considered hotspots for
biodiversity and conservation of both plants and animals. However, many
assumptions about ecotone characteristics have not been rigorously tested.
The most prevalent claim in the literature is that ecotones support higher
species richness than adjacent habitats. Patterns of higher species richness in
ecotones has been hypothesized to arise from ecological processes ranging
from spatial mass effect, increased environmental heterogeneity, seed
predation or introduction by animals or insects, to increased dispersal ability
by exotic generalists. The purpose of this project is to document patterns of
plant functional group richness and abundance across grassland-aspen
ecotones in the Lac du Bois grasslands north of Kamloops, British Columbia.
Specifically, this research addresses the following questions: 1) Are ecotones
more species-rich than surrounding areas in both north-and south-facing
aspects? 2) What is the relationship between functional diversity and species
richness across the grassland-aspen ecotones? and 3) How does the method of
ecotone definition (statistical versus visual) and data analysis (blocking versus
gradient approach) impact the results?
Twenty ecotones (10 south-facing and 10 north-facing ecotones) were
intensively sampled along 35 m transects for richness and abundance of
herbaceous plant species, aspen saplings, soil pH and moisture and tree canopy
cover. To compare techniques, the location of each ecotone was defined both
statistically using moving window regression analysis and visually using the
treeline as an approximate centre. Ecotone locations varied greatly when the
statistical method was compared with the visual method. Overall, the results did
not support the assumption that ecotones are more species rich than adjacent
habitats. However there was variation between richness and abundance of other
functional groups (shade tolerance, dispersal method and drought tolerance, for
example) in ecotones compared to adjacent habitats. This research also found a
strong influence of aspect on the results, especially when grasslands and ecotones
were compared.

Keywords: ecotone, grassland, aspen, aspect, functional groups, treeline

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Table of Contents
List of Figures.................................................................................................................. VI
List of Tables ................................................................................................................... VI
Chapter 1 Distribution of herbaceous plants across grassland-forest ecotones:
Testing the assumptions ...................................................................................................... 1
Ecotones: Evolving definitions ...................................................................................... 1
Ecotone characteristics .................................................................................................... 2
Ecotones and climate change ......................................................................................... 3
Common assumptions regarding ecotones.................................................................. 4
Functional group approach ............................................................................................ 5
Identification of ecotones: By structure or rate of community change..................... 6
Analysis of grassland-aspen ecotones .......................................................................... 6
Study objectives ............................................................................................................... 8
Literature cited ............................................................................................................... 10
Chapter 2 Testing the assumptions: plant functional group richness and abundance
across grassland-aspen ecotones in Lac du Bois ............................................................ 17
Introduction .................................................................................................................... 17
Methods........................................................................................................................... 23
Study Area .................................................................................................................................. 23
Study Design ............................................................................................................................... 25

Data analysis................................................................................................................... 29
Results ............................................................................................................................. 31
Ecotone Definition ...................................................................................................................... 31

Soil Data and Non-Vascular Plant Species................................................................. 34
Functional Group Richness .......................................................................................... 34
Functional Groups Abundance ................................................................................... 35
Discussion ....................................................................................................................... 39
Ecotone attributes ...................................................................................................................... 39
Soils and Non-Vascular Plants ..................................................................................................... 40
Functional Group Characteristics ................................................................................................ 40

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Influence of Aspect ..................................................................................................................... 42
Conclusion .................................................................................................................................. 43

Literature cited ............................................................................................................... 44
Chapter 3 Testing the methods: Comparing structural and statistical approaches in
ecotone analysis .................................................................................................................. 51
Introduction .................................................................................................................... 51
Methods........................................................................................................................... 52
Blocked approach - Structurally-Defined Ecotones..................................................................... 53
Gradient approach - Statistical and Structural Definitions.......................................................... 53

Results ............................................................................................................................. 54
Blocked Approach, Structurally-Defined Ecotones ..................................................................... 54
Gradient Approach, Structurally-Defined Ecotones .................................................................... 59
Gradient Approach, Statistically-Defined Ecotones .................................................................... 66

Discussion ....................................................................................................................... 70
Structurally-defined Ecotones: Contrasting the blocked and gradient approach ....................... 70
Comparing the Gradient Approach with Previous Methods: Statistically-Defined Ecotone Results
.................................................................................................................................................... 73

Literature cited ............................................................................................................... 75
Chapter 4 Implications, future research and conclusions........................................... 78
Broad context .................................................................................................................. 78
Ecotones and climate change ....................................................................................... 80
Management ................................................................................................................... 81
Further studies ............................................................................................................... 82
Literature cited ............................................................................................................... 83
Appendix ............................................................................................................................. 85

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LIST OF FIGURES
Figure 2.1 Transects were composed of 35 contiguous 1x10 m belt transects, oriented
perpendicularly to the treeline. Within each 1x10 m belt transect, the abundance
of herbaceous species, soil pH and moisture was recorded in three 1x1 m plots
systematically located at 0, 4.5 and 9 m from the transect edge. .......................... 28
Figure 2.3 Graphical representation of the moving window analysis. ........................ 32
Figure 2.2 Illustration of ecotone boundaries as identified by the moving window
analysis. The dotted line shows the ordination score of the change in species
composition over the transect. The ecotone peak, or centre, is defined by the
first derivative of the ordination (Bray-Curtis dissimilarity) score measuring
species turnover along each transect. The boundaries are defined by the second
derivative of the ordination score.............................................................................. 32

LIST OF TABLES
Table 2.1 Processes (after Senft 2009), predictions and potential evidence that could
be used to test individual predictions correlating with potential species and
functional group richness patterns across the ecotones. Evidence gathered in
this study is bolded. ..................................................................................................... 22
Table 2.2 Transect locations and characteristics of measured transects. Azimuths
were measured from forest to grassland. ................................................................. 27
Table 2.3 Sampling terminology used in this study. ....................................................... 27
Table 2.4 Functional groups and specific categories used in this study, and related a
priori hypotheses that may explain results. .............................................................. 29
Table 2.5 Ecotone identification (centre, width, belt boundaries) based on moving
window results. Transects number 2,3,7,8 and 11 (marked with asterisks) did
not yield clear results. Belts are numbered from grassland into forest (0 to 35)
with the treeline falling between belt number 15 and 16. Lac du Bois Grasslands
Protected Area, Kamloops, BC, 2012. ........................................................................ 33
Table 2.6 Results from generalized linear models of acceptable transects comparing
canopy cover, soil moisture, soil pH and non-vascular plant species abundance
in statistically-defined ecotonal belts versus forested or grassland belts, with
transect as a blocking variable and belt type as a categorical variable in each
model (lm=variable~belt.type+transect).1 ................................................................. 34
Table 2.7 Results from generalized linear models of acceptable transects, comparing
richness of functional groups in statistically-defined ecotone belts versus
forested and grassland belts, with transect as a blocking variable and belt type
as a categorical variable in each model (lm=variable~belt.type+transect). 1......... 37

VII

Table 2.8 Results from generalized linear models comparing abundance of
functional groups in statistically-defined ecotone belts versus forested and
grassland belts, with transect as a blocking variable and belt type as a
categorical variable and belt type as a categorical variable in each model
(lm=variable~belt.type+transect).1 ............................................................................. 38
Table 3.1 Results from generalized linear models comparing canopy cover, soil
moisture and soil pH in structurally-defined ecotone belts versus forested or
grassland belts, with transect as a blocking variable and belt type as a
categorical variable in each model (lm=variable~belt.type+transect).1 ................ 55
Table 3.2 Results from linear models comparing functional group richness in
structurally-defined ecotone belts versus forested and grassland belts, with
transect as a blocking variable and belt type as a categorical variable in each
model (lm=Variable~Belt.type+Transect).1 ............................................................... 57
Table 3.3 Results from linear models comparing abundance of functional groups in
structurally-defined ecotone belts versus forested and grassland belts, with
transect as a blocking variable and belt type as a categorical variable in each
(lm=Variable~Belt.type+Transect).1 ........................................................................... 58
Table 3.4 Summaries of generalized linear models comparing canopy cover, soil
moisture and soil pH for both forested and grassland transects with increasing
proximity to the structurally-defined ecotone centre (treeline). Distance
included as a continuous variable. lm= variable~distance towards treeline. 1 .... 60
Table 3.5 Summaries of generalized linear models comparing plant functional group
richness for both forested and grassland transects with increasing distance from
the structurally-defined ecotone centre (treeline), with distance included as a
continuous variable. lm=variable~distance from treeline.1 .................................... 63
Table 3.6 Summaries of generalized linear models comparing abundance of plant
functional groups for both forested and grassland transects along a distance
gradient from the structural ecotone (treeline). lm=variable~distance from
treeline.1 ......................................................................................................................... 65
Table 3.7 Summaries of generalized linear models comparing plant functional group
richness for forested belts with increasing distance from the statistically-defined
ecotone centre, with distance included as a continuous variable.
lm=variable~distance from ecotone centre.1 ............................................................. 68
Table 3.8 Summaries of generalized linear models comparing plant functional group
abundance for forested belts with increasing distance from the statisticallydefined ecotone centre, with distance included as a continuous variable.
lm=variable~distance from statistically-defined ecotone centre.1 ......................... 69
Table A.1 Results from generalized linear models of all transects comparing canopy
cover, soil moisture, soil pH and non-vascular plant species abundance in
statistically-defined ecotonal belts versus forested or grassland belts, with

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transect as a blocking variable and belt type as a categorical variable in each
model (lm=variable~belt.type+transect).1 ................................................................. 85
Table A.2 Results from generalized linear models, of all transects, comparing
richness of functional groups in statistically defined ecotone belts versus
forested and grassland belts, with transect as a blocking variable and belt type
as a categorical variable in each model (lm=Variable~Belt.type+Transect).1....... 86
Table A.3 Results from generalized linear models, of all transects, comparing
abundance of functional groups in statistically defined ecotone belts versus
forested and grassland belts, with transect as a blocking variable and belt type
as a categorical variable and belt type as a categorical variable in each model
(lm=variable~belt.type+transect).1 ............................................................................. 87
Table A.4 Results from generalized linear models comparing canopy cover, soil
moisture and soil pH in structurally-defined ecotone belts versus forested or
grassland belts, with transect as a blocking variable and belt type as a
categorical variable in each model (lm=variable~belt.type+transect). 1 ............... 88
Table A.5 Results from linear models, from all transects, comparing functional group
richness in structurally-defined ecotone belts versus forested and grassland
belts, with transect as a blocking variable and belt type as a categorical variable
in each model (lm=Variable~Belt.type+Transect).1.................................................. 89
Table A.6 Results from linear models comparing abundance of functional groups in
structurally-defined ecotone belts versus forested and grassland belts, with
transect as a blocking variable and belt type as a categorical variable in each
(lm= variable~belt.type+transect).1 ............................................................................ 90
Table A.7 Summaries of generalized linear models comparing plant functional
group richness for forested belts with increasing distance from the statisticallydefined ecotone centre, with distance included as a continuous variable.
lm=variable~distance from statistically-defined ecotone centre.1 ......................... 91
Table A.8 Summaries of generalized linear models comparing plant functional
group abundance for forested belts with increasing distance from the
statistically-defined ecotone centre, with distance included as a continuous
variable. lm=variable~distance from statistically-defined ecotone centre.1......... 92
Table A.9 Summaries of generalized linear models comparing plant functional
group richness for both forested and grassland transects with increasing
distance from the structural ecotone (treeline), with distance included as a
continuous variable. lm=variable~distance from treeline.1 .................................... 93
Table A.10 Summaries of generalized linear models comparing abundance of plant
functional groups for both forested and grassland transects along a distance
gradient from the structurally-defined ecotone (treeline). lm=variable~distance
from treeline.1 ............................................................................................................... 95
Table A.11. Species identified in this study and functional groupings........................ 97

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CHAPTER 1 DISTRIBUTION OF HERBACEOUS PLANTS ACROSS
GRASSLAND-FOREST ECOTONES: TESTING THE ASSUMPTIONS
ECOTONES: EVOLVING DEFINITIONS
Ecology has long been concerned with both spatial and temporal patterns
of species richness (Pausas & Austin 2001; Starzomski et al. 2008), especially with
respect to the influence of biotic and abiotic factors (Iverson & Prasad 2001;
Midgley et al. 2002). Ecotones were first defined as a “stress line connecting
points of accumulated or abrupt change” on a landscape (Livingston 1903). With
the rise of conservation and global climate change biology ecotone research has
increased significantly in popularity beginning in the 1980s (Kark & Rensburg
2006). Since then, definitions of ecotones and methods used to delineate them
have evolved.
At the basic level, ecotones, from the Greek root oikos (home) and tonus
(tension), are the zones of transition where two distinct ecosystems such as forest
and grassland meet (Kark & Rensburg 2006). Most researchers follow the
definition first outlined by Clements in 1905 in which an ecotone is viewed as an
abrupt line between two systems. Curtis and McIntosh (1951) clarified that
ecotones are also zones of tension between biogeographic regions. This definition
was expanded further to define ecotones as broader landscape elements with
more dynamic, somewhat unstable characteristics (Van der Maarel 1990). Odum
(1971) added that the ecotone itself may have a large linear extent, but is
narrower than the adjacent communities. More specifically, some researchers
argue that there should be a distinction in the classification of edge environments
as either ecoclines (areas with typically higher species richness) or ecotones (areas
with similar or lesser species richness (Van der Maarel 1990)). This idea is based

2

on a previously held view of edge environments, but recent research seems to be
finding support for a return to this concept (Lloyd et al. 2000; Walker et al. 2003;
Senft 2009).

ECOTONE CHARACTERISTICS
Recently, ecotones have garnered considerable ecological attention for both
conservation and theoretical reasons. The potential of ecotones to contain high
species diversity coupled with their role in the flow of energy, nutrients, and genes
have led to the argument that ecotones are important landscape elements for
conservation of species and habitat (Risser 1995, Fagan et al. 2003, Kark 2013). Like
all ecological systems, ecotones can be observed from many spatial scales; from
continental i.e., latitudinal vegetation gradients (Gosz 1993), to the local landscape
level i.e., riparian zones of small water bodies (Risser 1995). Local scale ecotones can
be natural or anthropogenic in origin and range from very young and dynamic to
ancient and essentially static. An ecotone’s location, extent and sharpness can be
influenced by underlying environmental gradients such as soil type, bedrock, site
productivity, topography, local hydrology and snow cover (di Castri et al. 1988; Van
der Maarel 1990; Bestelmeyer et al. 2006; Gottfried et al. 2011). For example, in
reverse treelines, where lower elevations are grassy and trees occur at higher
elevations, Coop and Givnish (2007) found that treelines are strongly correlated to
shifts in the thermal regime, only weakly associated with soil nutrient and type and
not associated with soil moisture.
At the local scale, the study of ecotones has involved two major approaches;
the analysis of underlying environmental gradients or the response of populations,
species and communities to these gradients (Kark & Rensburg 2006). The plant
communities within these ecotonal zones are traditionally thought to be made up of

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a blending of the two adjacent systems, with some unique ecotonal species (di Castri
et al. 1988). Some studies have found that edge-effects (often equated with ecotones)
associated with disturbed or managed forests can extend to fifty metres or more into
adjacent ecosystems (Matlack 1994). As a result, an ecotone associated with a
treeline, for example, can be very wide, reaching beyond the physical treeline on
both sides. Ecotones and plant communities are also strongly influenced by aspect
(McLean 1970; Vyse & Clarke 2000; Hylander 2005) since differences in solar
exposure, prevailing winds and precipitation patterns impact plant abundance and
richness. As a result, it is important to measure plant richness and abundance
patterns on both north- and south-facing aspects (Holland & Steyn 1975; Orczewska
& Glista 2005).

ECOTONES AND CLIMATE CHANGE
As changing climates impact the location and extent of ecosystems, ecotones
will likely migrate or change size (Loehle 2000). This is often noted when treeline
ecotones are discussed. Treelines often shift north or upwards in elevation as climate
changes locally (Taylor & Taylor 1997; Díaz-varela et al. 2010). Due to this movement
and sensitivity to climate, treeline ecotones are often seen as early indicators of
future changes and have been identified as potentially useful for evaluating the
stability of forest stands under the increasing stresses of climate change (Walker et
al. 2003; Senft 2009; Díaz-varela et al. 2010).
The ecological response of ecotone species to disturbances such as climate
change may be related, in part, to the distribution of individual species across
environmental gradients (Shipley et al. 2011). Ecotones dominated by a large
number of species with narrow distributions are likely to experience more
compositional shifts than ecotones dominated by species with wide distributions
across the ecotone (Hylander 2005). In dynamic ecotones, the age of the ecotone

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may also impact patterns of species richness (Halpern et al. 2010).

COMMON ASSUMPTIONS REGARDING ECOTONES
Definitions of ecotones often include several untested assumptions that are
important to evaluate empirically. First and foremost, there has been a
longstanding assumption that ecotones are areas of high species diversity due to
an increased rate of species change across environmental gradients (Camarero et
al. 2006). However, several researchers (Lloyd et al. 2000; Walker et al. 2003; Senft
2009) have found evidence that not all ecotones are more species-rich than their
surrounding communities. Similarly, a meta-analysis of 21 studies found that
riparian ecotones contributed to increased regional species richness through the
occurrence of different, rather than more, plant species (Sabo et al. 2005). Other
common assumptions regarding ecotone concepts are that ecotones are defined
by sharp rather than gradual vegetation transitions, that they encompass changes
in physiognomy when compared to adjacent plant communities, that they contain
unique ecotonal species (di Castri et al. 1988), or contain more exotic species than
in adjacent plant communities (Allen & Knight 1984; Vavra et al. 2007).
Senft (2009) reviewed hypotheses presented to explain the potential
richness of ecotones. In general, Senft found that increased ecotonal richness was
predicted to result from: 1) increased environmental heterogeneity allowing
increased species packing (Auerbach & Shmida 1987) and a higher species
richness overall; 2) an increase in animal-dispersed seeds into ecotones (Russo et
al. 2006; Vazquez et al. 2009) or animal grazing (Willson & Traveset 2000); 3) an
increase of propagules from adjacent areas (spatial mass effect (Shmida & Wilson
1985)); or 4) an increase in exotic species found in the ecotone.

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FUNCTIONAL GROUP APPROACH
Plant richness and abundance within ecotones have traditionally been
examined using only taxonomic-based, rather than a functional trait-based,
response variables (see Bossuyt et al. 1999; Mast et al. 1997; Kark and Rensburg
2006; Sabo et al. 2005). However, the ecological processes believed to account for
the high species richness expected in ecotones would likely influence functional
groups of species differently (Kyle & Leishman 2009).
Functional group analyses allow researchers to draw general conclusions on
a broader scale (Herault & Honnay 2007), and may help to distinguish between
competing hypotheses for an observed pattern (Roscher et al. 2012). As the use of
functional traits and groups became more popular in research, there has been as
increase in confusion of definitions of the terms (Shipley et al. 2016), much like the
disagreement over ecotone definition. In an attempt to clarify the issue, functional
traits have been defined as “any trait which impacts fitness indirectly via its effects
on growth, reproduction and survival” (Violle et al. 2007). Functional groups,
discussed in this study, are collections of plants based on these traits and
morphological, behavioural or environmental responses (Steffen 1996). Using
functional groups can help to delinate the underlying mechanisms driving an
ecosystem and allow predictions in different systems (Sandel et al. 2010). These
influences can be made visible through functional traits expressed by the
overlying plant community (Kyle & Leishman 2009; Schellberg & Pontes 2012).
The functional group approach is useful for large scale studies where it is
important to group species based on their response to environmental variables
(Lavorel et al. 2007). This approach could be helpful for meta-analysis, allowing for
comparisons across studies regardless of ecosystem or scale (Violle et al. 2007).
Additionally, a functional group approach may allow for the comparison of ecotone

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effects on both flora and fauna, and help to observe underlying interactions
between them (Kark & Rensburg 2006).

IDENTIFICATION OF ECOTONES: BY STRUCTURE OR RATE OF COMMUNITY
CHANGE

Conflicting results regarding ecotones and their characteristics may have
arisen due to differences in the way ecotones are defined by researchers. Defining
the location of an ecotone can be problematic and factors such as temporal
dynamics, size, shape and sharpness need to be considered (Kark & Rensburg
2006). In the field, ecotones are often identified by the structural edge created by
an obvious shift in vegetation physiognomy i.e., the boles of mature trees (Murcia
1995). However, this approach focuses on a subjective, visually obvious aspect of
the plant community rather than a definition based on changes in the community
as a whole. In order to objectively define the boundaries of the ecotones, ecotones
have been defined as areas with the highest rate of change in species richness or
composition (Cornelius & Reynolds 1991; Fortin et al. 2000). Species composition
is then plotted graphically through an ordination technique. Delcourt and
Delcourt (1992) suggest using moving window analysis to statistically identify the
area with the greatest rate of change in species composition which defines the
boundaries of ecotones. This analysis helps to define the ecotone and then allow
for objective comparison between the ecotone and the surrounding communities.
Additionally, richness and/or composition can be compared between objectively
identified ecotonal habitats, of any type, found around the globe.

ANALYSIS OF GRASSLAND-ASPEN ECOTONES
In the upper grasslands of Lac du Bois Provincial Park and nearby
properties, trembling aspen (Populus tremuloides (Michx.)) occur as isolated stands

7

within a larger matrix of grassland and Douglas-fir (Pseudotsuga menziesii (Mirb.))
forest. Aspen stands are important sites of native plant and animal diversity and
are sometimes considered “keystone ecosystems” (Stohlgren et al. 1997). Aspen
stands provide important habitats for vascular plants, insects, birds, and
mammals (Campbell & Bartos 2001; Stohlgren et al. 1997). Vyse & Clarke (2000)
found that aspen edges are important winter habitat for sharped-tailed grouse in
this area. As a broadleaf, deciduous tree, aspen represent a unique canopy type
within the study region which is dominated by grassland and large Douglas-fir
stands. In the dry grasslands of Lac du Bois, aspen tend to be associated with
depressions or gullies where moisture is likely to accumulate (Giesbrecht 2011).
Aspen forest patches most often expand though clonal reproduction, using
lateral shoots that emerge from the soil as suckers. An entire patch can be
composed of one organism, known as a clone, connected through the root system
(Swanson et al. 2010). Within arid grassland-conifer dominated landscapes such as
the interior British Columbia, aspen patches are important for small mammal
diversity, ungulate browsing and vascular plant species richness (Oaten & Larsen
2008; Jules et al. 2010; Kuhn et al. 2011). Much of the recent attention devoted to
aspen has arisen due to the concern that many aspen populations are in decline
around North America (Wooley et al. 2008; Michaelian et al. 2010; Worrall et al.
2010). However, air photo analysis indicates that the aspen patches in the Lac du
Bois area have apparently expanded over the last thirty years (Alan Vyse,
personal correspondence 2013).
While aspen habitats have elicited much consideration over the last fifteen
years (Kuhn et al. 2011), little attention has been paid to diversity patterns found
within the ecotones between aspen patches and the surrounding habitat.
Relatively few studies have documented patterns of herbaceous species

8

distribution across low-elevation ecotones, such as the aspen treeline ecotones in
Lac du Bois. Hylander (2005) suggests that anthropogenic forest edges, sometimes
compared with naturally occurring ecotones, may be optimum habitats for some
organisms when there is a trade-off between moisture and sunlight, for example,
due to intermediate conditions offered by the edge environment. The ecotones
between the aspen patches and the grassland may offer a similar intermediate
habitat.
In forest edges, the herbaceous community often represents the largest
component of plant diversity (Matlack 1994; Bossuyt et al. 1999). The spread of
herbaceous plants across forest ecotone boundaries is influenced by individual
species’ ecological tolerances (specifically soil pH, moisture, and canopy closure
conditions), competitive hierarchies, storage within seed banks, dispersal method
(Foster & Tilman 2003) and local climatic variations (i.e., snow cover and wind
patterns (Camarero et al. 2006)).
Within the interior of British Columbia, aspect has a strong influence and
is visually obvious on a broader scale where vegetation cover differs greatly
between northern and southern exposures. Here north-facing slopes are generally
heavily forested, whereas south-facing slopes are often open grasslands with only
sparse trees.

STUDY OBJECTIVES
The potential for ecotones to maintain high species diversity, their role in
energy, gene and nutrient flows across a landscape, and their potential early
sensitivity to climate change impacts increase their importance for the
conservation of both plants and animals. The presence of an aspen-grassland
mosaic within the upper reaches of Lac du Bois Grasslands Protected Area
provides an opportunity to not only document species richness patterns across a

9

little examined ecotone (i.e., aspen-grassland), but also provides a natural
laboratory in which to critically examine the effects of ecotone definition
(statistical versus subjective), and experimental design approach (block versus
gradient) on observed species richness patterns. Finally, the presence of aspengrassland ecotones on both north- and south-facing slopes provides a unique
opportunity to examine the universality of observed species richness patterns on
ecotones differing in aspect within one system. This study will add to our
understanding of ecotones in general and will specifically evaluate the following
questions:
1) Are ecotones more species-rich than surrounding areas in both north-and southfacing aspects?
2) What is the relationship between functional diversity and species richness across
the grassland-aspen ecotones?
This thesis is divided into four chapters, the introduction, two data chapters
and one conclusion chapter. Chapter Two evaluates the evidence for the four
competing hypotheses that could lead to increased species richness in ecotones
with a functional plant approach. This chapter also defines ecotone centre location,
boundaries and width using a statistical analysis based on the evaluation rate of
change of species composition. Once the ecotones were identified, plant functional
group richness and abundance were compared across grassland, ecotonal and
forested habitats, separated by aspect.
Chapter Three compares how two methods used in ecotone research
impact the results. In this chapter, ecotones and their attributes (plant functional
group richness and abundance) that were defined using the statistical method
used in Chapter Two were compared to ecotones defined by a structural,
subjective approach. This subjective approach involves using a visually-defined

10

location (the treeline created by the boles of mature aspen) to identify the ecotone
centres. This chapter also compares a blocked data treatment (used in Chapter
Two) to a gradient treatment. Chapter Four discusses conclusions, future research
suggestions and management implications related to ecotones.

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richness. Trends in Ecology and Evolution. 2:238–242.
Bestelmeyer BT, Ward JP, Havstad KM. 2006. Soil-geomorphic heterogeneity
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17

CHAPTER 2 TESTING THE ASSUMPTIONS: PLANT FUNCTIONAL
GROUP RICHNESS AND ABUNDANCE ACROSS GRASSLAND-ASPEN
ECOTONES IN LAC DU BOIS
INTRODUCTION
Within ecology, evolving definitions are not uncommon. Ecotones were
first defined by Livingston (1903) as a “stress line connecting points of
accumulated or abrupt change.” However, at the turn of the 21st century variable
and non-exclusive use of the term “ecotone” led to a call for a consensus on
ecotone definition in order to facilitate interpretation and comparison of different
studies (Hufkens et al. 2009). Part of the ambiguity surrounding the use of the
term ecotone undoubtedly arises from the multiple causes and origins of these
ecological boundaries; ecotones can arise from either anthropogenic or nonanthropogenic causes, occur in diverse landscapes and can be found at widely
varying spatial and temporal scales (Risser 1995). Ecotone characteristics such as
width and species richness can also vary in response to aspect, solar radiation,
wind patterns, precipitation and grazing (Harper & MacDonald 2001; Harper et al.
2005; Hylander 2005; Orczewska & Glista 2005).
Variously referred to as edges, borders, or interfaces (Danz et al. 2012),
ecotones have been delineated using a variety of approaches (Lloyd et al. 2000;
Harper & MacDonald 2001; Walker et al. 2003; Hufkens et al. 2009; Senft 2009), yet
characterization of ecotones remains contentious. Attempts to characterize
ecotones have included both boundary delineation as well as ecotonal community
descriptions. As ecotones can rarely be delineated by a fine line, identifying the
boundary of ecotones is complex (Fortin et al. 2000; Erdôs et al. 2011; Kark 2013).
While numerous ecotone studies have used subjective or poorly documented

18

means to identify boundaries, such as changes in vegetation height, there has been
an increasing reliance on the use of statistical methods to objectively identify the
ecotonal community boundaries (Chen et al. 1996; Fortin et al. 2000; Walker et al.
2003; Hennenberg et al. 2005). Of the multiple methods used (see Hufkens et al.
2008 for a review), one objective approach uses the moving window regression
(Cornelius & Reynolds 1991; Fortin et al. 2000; Walker et al. 2003; Hennenberg et
al. 2005; Kent et al. 2006).
Moving window regression allows for the objective identification of
ecotone centres and boundaries from which analysis of species and functional
group richness can be completed (Walker et al. 2003). This analysis identifies the
midpoint of an ecotone by regressing the ordination scores of species composition
measured along transects. The peak in the first axis ordination scores identifies
the midpoint of the ecotone and the inflection points along the second ordination
scores delineate the boundaries of the ecotone. In this way ecotones are defined
based on a statistical change in species composition rather than being defined by a
visual change such as a treeline. Proponents of this statistical approach argue that
this helps to standardize ecotone research and allow for comparisons between
very different systems in an effort to articulate general ecotone characteristics
(Fortin et al. 2000; Walker et al. 2003). The moving window approach allows for
repeatable and comparable ecotone definition, but requires intensive sampling
methods. As a result, ecotone studies using this approach are often based on
relatively small sample sizes which could lead to potentially misleading results
and conclusions about the general characteristics of ecotones (Luczaj & Sadowska
1997; Lloyd et al. 2000; Walker et al. 2003; Orczewska & Glista 2005).
Although there is little consensus regarding which specific method is best
to define, delineate or characterize ecotones, few doubt the importance of

19

ecotones as landscape elements (Murcia 1995; Kark 2013). The potential of
ecotones to contain high species diversity coupled with their role in the flow of
energy, nutrients, and genes have led to the argument that ecotones are
important for conservation of species and habitat (Risser 1995; Erdôs et al. 2011).
For instance, Hylander (2005) suggests that even anthropogenic ecotones – such
as agricultural edges – are optimal habitat for species with a preference for
intermediate conditions. Although ecotones have garnered considerable
attention for both conservation and theoretical reasons, there has been little
research completed to address assumptions about specific characteristics such as
richness, diversity or uniqueness (di Castri et al. 1988; Walker et al. 2003; Kark &
Rensburg 2006).
In one of the few studies to explicitly evaluate the high species richness of
ecotones, Senft (2009) identified four separate hypotheses that had been proposed
to explain increased species richness in ecotones:
I.

Increased environmental heterogeneity leading to increased species packing

II. Spatial mass effect leading to increased richness/diversity within ecotones
III. Animal seed predation and dispersal impacts plant richness
IV. Easily dispersed generalists and exotics lead to increased richness
Although Senft (2009) found little evidence for increased richness in
anthropogenic ecotones between deciduous forest and a mowed meadow,
she analyzed only composite community-level response variables such as
species richness and diversity. When patterns in ecotone species richness are
examined using only taxonomic-based response variables (Mast et al. 1997;
Bossuyt et al. 1999; Sabo et al. 2005; Kark & Rensburg 2006), the differential
response of different plant functional groups may be swamped by opposing

20

responses of species within the same taxonomic group. Certainly, as a
community-level response variable, species richness will provide little
information about what ecological factors could be driving shifts (or lack
thereof) in species richness across ecotones.
However, a plant functional group approach that allows for the
examination of a large number of organisms and their interaction with
environment factors (Garnier & Navas 2012) could help to distinguish between the
competing hypotheses identified by Senft (2009), as potential drivers of species
richness within ecotones (Table 2.1). For instance, spatial mass effect is defined as
the addition of propagules from adjacent systems into an area where the
adult plants generally do not survive to reproduce (Shmida & Wilson 1985). The
influence of spatial mass effect on patterns within the ecotone could be evaluated
using a priori defined functional groups composed of indicator species from
adjacent habitats. The impact of animal seed predation and/or dispersal can be
measured by the analysis of the richness of seed type functional groups across an
ecotone. Likewise, comparing the number of exotic versus native functional
groups in ecotones and adjacent habitats would provide evidence for the
importance of easily-dispersed species in ecotone communities. The final
ecological process hypothesized to lead to higher richness in ecotones is increased
environmental heterogeneity. Evidence for this process could be detected by
examining species or functional group turnover within the ecotone boundary. In
addition, evidence for this hypothesis could be collected if high rates of species
composition change are used as a proxy for increased species packing. Then high
species richness would be predicted to occur in the same locations where high
species composition change occurred. In general, functional group analyses may
allow generalization of observed findings rising above the taxonomic specifics of a

21

single locality (Herault & Honnay 2007).
Although many studies have investigated conifer or riparian ecotones
(Maher et al. 2005; Mason et al. 2005; Sabo et al. 2005; Danby & Hik 2007; Bai et al.
2011; Griesbauer et al. 2011), few studies have examined species richness over
aspen-grassland ecotones. The importance of grassland and aspen patches as
separate reservoirs of diversity and critical habitat is well recognized for both
plants and animals (Oaten & Larsen 2008; Kuhn et al. 2011). In British Columbia
(BC), grasslands form a unique and important habitat for many species and are
home to 42% of the province’s 2854 vascular plants species including many red
and blue listed species, even though they only cover about 1% of the province
(Wikeem & Wikeem 2004; Lee 2011). Likewise, aspen stands in western North
America have been described as “keystone ecosystems” for native plant and
animal diversity (Stohlgren et al. 1997; Campbell & Bartos 2001; Swanson et al.
2010; Kuhn et al. 2011).
Aspen-grassland mosaics in the southern interior of BC provide an
opportunity to document species richness patterns across a little examined
ecotone. Furthermore, the presence of north- and south-facing aspen-grassland
ecotones allow for the evaluation of the universality of the observed results across
ecotones differing in a fundamental characteristic within one system. Using the
moving-window regression approach to statistically identify ecotones, this
chapter evaluates the following questions: 1) How does species richness and
abundance of functional groups (taxonomic, shade tolerance, growth form, dispersal
method, status, drought tolerance and habitat indicator species) vary over grassland-aspen
ecotones? 2) How do the observed patterns vary across north- and south-facing ecotones in
the same system?

22

Table 2.1 Processes (after Senft 2009), predictions and potential evidence that could
be used to test individual predictions correlating with potential species and
functional group richness patterns across the ecotones. Evidence gathered in this
study is bolded.
Processes
1. Increased environmental
heterogeneity leads to increased
species packing
(Auerbach & Shmida 1987)

Testable predictions
1a. Ecotonal area will have
increased species turnover
compared to adjacent habitats

1b. Competitive effects will be
reduced under ecotonal
conditions compared to adjacent
habitats
1c. Germination rates will be
higher under ecotonal conditions

Evidence gathered
1a. Use rates of high species
composition change as a
proxy for species packing.
Analyze if species richness
highest in these areas of
high species turnover.
1b. Analyze how dominance
varies between belt types
1c. Compare soil seed banks
in ecotones and adjacent
habitats.

2. Spatial mass effect: the
addition of propagules from
adjacent systems into an area
where the adult plants
generally do not survive to
reproduce
(Shmida & Wilson 1985)

2a. Ecotone habitat will have
increased richness and/or
abundance of grasslandassociated species than forest
habitats, and increased
abundance of forest-associated
species than adjacent grassland
areas.
2b. Ecotonal areas will have
higher richness of forest seeds
than grasslands; and higher
richness of grassland seeds than
forested areas.

2a. Richness and abundance
of grassland or aspen
indicator species compared
across ecotones and adjacent
habitats.

3. Animal seed
distribution/predation will
impact species richness in
ecotones.
(Willson & Traveset 2000; Russo
et al. 2006; Vazquez et al. 2009)

3a. Ecotonal areas will have a
greater richness and/or
abundance of animal-dispersed
species than adjacent habitats.
3b. Ecotonal areas will have
higher richness and/or
abundance of animals and
invertebrates than adjacent areas.

3a. Richness and abundance
of seed dispersal functional
groups compared across
ecotones and adjacent
habitats.
3b. Animal sign/trapping
across ecotones and adjacent
habitats

4. Generalist and exotics which
are easily dispersed lead to
increased richness (Vavra et al.
2007)

4a. Ecotones contain a greater
richness and/or abundance of
exotics and generalists than
adjacent areas.

4a. Richness and abundance
of exotic and functional
group generalist species
compared over ecotones and
adjacent habitat types.

2b. Seed bank study across
ecotones.

23

METHODS
STUDY AREA
The study area is located on the traditional territory of the Tk’emlúps te
Secwepemc in the BC Southern Interior Plateau, near the city of Kamloops. This
plateau is in the rain shadow of the coast mountains and experiences hot, dry
summers with an average annual temperature of 6.4°C (Vyse & Clarke 2000;
Wikeem & Wikeem 2004). The southern interior of BC is characterized by rolling
grasslands dotted with sagebrush (Artemesia tridentata (Nutt.)) and ponderosa
pine (Pinus ponderosa (C. Lawson)) at lower elevations, and Douglas-fir
(Pseudotsuga menziesii (Mirb.)) and lodgepole pine (Pinus contorta (Douglas ex
Louden)) forests at higher elevations. Topography has a strong influence within
this region. Moisture increases with elevation creating distinct vegetation bands
and lower treelines. Aspect also influences the elevation of treelines where trees
grow at lower elevations on northern slopes than on southern slopes. Within the
interior plateau, grasslands are divided into three elevational bands where the
upper grassland (850-975 m) is the wettest and coolest (Tisdale 1947; Wikeem &
Wikeem 2004).
The study site is located in the Lac du Bois Grasslands Protected Area and
adjacent Nature Conservancy of Canada property about 30 km north of
Kamloops, BC. This upper grassland matrix receives approximately 190 mm
rainfall during the growing season, and the average temperature during this
period is 11.5°C (Vyse & Clarke 2000). This grassland matrix is bordered at the
upper edge by the Douglas-fir treeline. The study site includes the lower edge of
the IDFxh2 and the top edge of the BGxw1 biogeoclimatic zones (Vyse & Clarke
2000) and the soils in this zone are classified as sandy loam to loamy sand (Lee

24

2011).
Aspen patches within Lac du Bois Grasslands Protected Area are primarily
found in the upper grasslands matrix where they tend to be associated with moist
depressions or gullies, and north facing slopes (Ryswyk et al. 1966; Vyse & Clarke
2000; Giesbrecht 2011). Small aspen patches, ranging from approximately 2500 m2
to 38000 m2, are found throughout this upper grassland, creating ecotones where
these two systems meet. These aspen stands range in age from approximately 24
to 148 years old (Jones et al. 2015). Common species within the aspen stands
include common snowberry (Symphoricarpos albus (L.)), prickly rose (Rosa acicularis
(Lindl.)), saskatoon (Amelanchier alnifolia (Nutt.)), wild strawberry (Fragaria
virginiana (Duchesne)) and common harebell (Campanula rotundifolia (L.)). The
upper grassland matrix in this area is characterized by Kentucky bluegrass (Poa
pratensis (L.)), bluebunch wheatgrass (Pseudoroegneria spicata (Pursh)), rough fescue
(Festuca campestris (Rydb.)), yellow salsify (Tragopogon dubius (Scop.)), timber milk
vetch (Vicia americana (Muhl. ex Willd.)) and arrowleaf balsamroot (Balsamorhiza
sagittata (Pursh)) (Vyse & Clarke 2000; Jones et al. 2015).
Historically, this area was intensively grazed by sheep and cattle, and was
home to approximately 200 people in the early 1900s, but it is now parkland with
no human inhabitants, limited human use and minimal cattle grazing (Vyse &
Clarke 2000; Lee 2011). Air photo analysis indicates that the aspen patches in the
Lac du Bois area have expanded over the last thirty years, likely as a result of
decreased human use (Alan Vyse, personal communication 2013).
Site Selection
Satellite imagery was used to identify aspen stands within the Lac du Bois
grasslands (Google Earth, 2012). Aspen stands were chosen randomly and visited
to assess suitability; rejection criteria included stand size and proximity to roads

25

and fences. Only those forest patches that were large enough to accommodate 30
meter transects placed perpendicular to the edge were included in the study; none
of the transects crossed the patch centres at suitable sites. The length of the transect
was chosen based on previous studies and constrained by the average aspen stand
size available (Kunin 1998; Walker et al. 2003; Orczewska & Glista 2005; Senft 2009).
Each transect extended 15 m into the grassland and in order to ensure that transects
were longer than the average tree height (16m), each transect extended 20 m into
the forest. Pure aspen stands were selected to minimize the impact that other tree
species might have on the understory, although the presence of some non-target
species seedlings was unavoidable. Forest patches which were smaller than 0.25 ha
were rejected, to minimize the influence of nearby edges. Sample site locations and
characteristics are summarized in Table 2.2.

STUDY DESIGN
Vegetation Sampling
Within each study site 10x35 m sampling grids were established
perpendicular to the structural edge of the forest, between June and September
2012. Each transect extended 20 m into the aspen patch and 15 m into the
grassland (Figure 2.1). In order to record the pattern of understory vascular plant
species occurrence across each ecotone, species presence and abundance was
measured in three 1x1 m plots within each 1x10 m belt transects, located at the
centre and at each edge. Abundance was measured using percent cover within
the plots. Mean values for all data collected in each 1x10 m belt was used in the
analysis. Each plot was examined for percent cover of non-vascular plants;
however these were not identified to species but were recorded as a group. Tree
seedlings and saplings were recorded within the plots and along each belt, and
tree canopy in each belt was recorded. Plant identification was confirmed using

26

the Illustrated Flora of British Columbia (Douglas et al. 1998-2000). See Table 2.3
for terminology used in this study.
Soil moisture and pH
To relate understory species occurrence across ecotones to environmental
attributes, moisture and pH data were measured within each plot. Soil moisture
along each transect (measured using a 12 cm probe, Field Scout TDR 300 Soil
Moisture Meter, Spectrum Technologies, Illinois) was evaluated as each transect
was surveyed. This data was collected within a half hour period to minimize
temporal variations in evaporation or drainage. As biotic processes and forest
canopy can alter soil chemistry (Finzi et al. 1998), the pH of mineral soil exposed
in each 1x1 m plot was determined using a Hellige-Truog Soil pH Test Kit. Soil
samples were collected in the same 1x1 m plots in which the herbaceous species
data was gathered.
Functional groupings
Vascular plant species were categorized into functional groupings based
on shade tolerance, growth form, dispersal mode, origin status, drought tolerance
and indicator status (Table 2.4). Functional group information for each plant
species was gathered from USDA Plants, E-Flora BC and Kew Gardens
(Klinkenberg 2013; Royal Botanic Gardens Kew 2015; USDA, NRCS 2015).
Abundance data for plant functional groups was calculated by summing the
percent cover (rounded to 1%) of all species within each functional group,
sampled in the 1x1 m quadrat (Krebs 1999).

27

Table 2.2 Transect locations and characteristics of measured transects. Azimuths
were measured from forest to grassland.
Aspect

Transect Azimuth

North

Mean±SD
South

Coordinates (UTM)
10U

Elevation
(m)
912
915
946
964
954
964
975
1000
981
993
960.4±29.7
909
927
958
948
965
980
969
972
974
947
954.9±22.6

2
4
6
8
9
11
12
17
18
19

335
18
24
36
46
20
27
20
10
44

10U 680059E 5629572N
10U 679694E 5631522N
10U 680538E 5630655N
10U 680470E 5632016N
10U 680312E 5631975N
10U 680259E 5632202N
10U 680343E 5632290N
10U 680750E 5631993N
10U 680637E 5631962N
10U 680678E 5632210N

1
3
5
7
10
13
14
15
16
20

172
217
230
226
220
256
220
198
222
218

10U 680077E 5629491N
10U 680089E 5630246N
10U 680641E 5630579N
10U 680405E 5631835N
10U 680249E 5632239N
10U 680588E 5632094N
10U 680554E 5631860N
10U 680603E 5631778N
10U 680633E 5631743N
10U 680223E 5631923N

Mean±SD

Aspen stand
dimensions (m)
Maximum
Maximum
Length
width
102
51
123
62
328
54
184
55
205
83
299
92
299
92
259
160
259
160
202
74
226±76.0
88.3±40.7
102
51
138
53
328
54
196
71
299
92
192
65
276
244
276
244
276
244
205
83
228.8±73.6 120.1±86.5

Table 2.3 Sampling terminology used in this study.
Term
Transect
Belt
Plot

Description
Sampling zone laid out perpendicular to aspen treeline. Each
transect is 10x35 m and is made up of 35 1x10 m belts. 20
transects were sampled.
Contiguous 1x10 m sections of the transects, each running
parallel to the treeline.
1x1 m plot were located systematically at 1, 4.5 and 9 m
across each belt. 2100 plots were sampled.

28

Figure 2.1 Transects were composed of 35 contiguous 1x10 m belt
transects, oriented perpendicularly to the treeline. Within each 1x10 m belt
transect, the abundance of herbaceous species, soil pH and moisture was
recorded in three 1x1 m plots systematically located at 0, 4.5 and 9 m from
the transect edge.

29

Table 2.4 Functional groups and specific categories used in this study, and related a
priori hypotheses that may explain results.
Functional group
Shade Tolerant Groups
Growth Form Groups
Drought Tolerant
Groups
Indicator Species Groups

Categories
Tolerant/Intermediate/
Intolerant
Forb/Graminoid/Shrub/Tree
sapling
Tolerant/Intermediate/
Intolerant
Aspen stand/Grassland

Dispersal Method
Groups

None/Wind/Animal/Generalist

Status Groups

Native/Exotic

Related a priori hypothesis
Increased species packing
Increased species packing
Increased species packing
Spatial mass effect
Animal dispersal impact
richness
More exotics lead to increased
richness

DATA ANALYSIS
Ecotones were defined statistically using the moving window regression
method to identify areas of rapid change in species composition as measured by
mean abundance in 1x1 m plots sampled within each belt (Walker et al. 2003).
Ecotone boundaries were defined using the first and second derivatives of
ordination scores (first axis) based on species abundance data (Kark & Rensburg
2006). Non-metric multidimensional scaling (NMDS) was used to characterize
variation in species composition along each transect with the Bray-Curtis
dissimilarity. Species that occurred less than twice along each transect in question
were omitted from this analysis to reduce the impact of rare species on the
ordination and to improve interpretability of ordination results. All data were
checked for homogeneity of variance and normality, and transformed as needed
for analysis. To evaluate the relationship between belt type and functional group
richness and abundance, normal linear regression was used with functional group
richness and abundance logarithmically transformed (where necessary) and belt

30

type (grassland, ecotone, forest) entered as a categorical variable in the model.
In order to statistically define the center of each ecotone, ordination scores
of each belt were regressed against the distance along the transect. Ecotone centers
were identified as the location of maximum rate of change in species composition
which can be observed as “peaks” in the regression slopes. To determine the
width of each ecotone, a second moving window regression was performed on
the rates of change (slopes) of the first regression analysis. In this second analysis,
the inflection points of the second regression identifies the boundaries of the
ecotone within each transect (Figure 2.2, Walker et al. 2003). As window widths
used in the analysis can influence the outcomes, regressions with window widths
ranging from five to eight belts wide were used to find the clearest peaks and
valleys in the regressions, before adopting a standard moving window size of 5 m.
The moving window analysis is represented graphically in Figure 2.3.
Associations of environmental and plant functional group variables with
ecotone and adjacent habitats were evaluated using generalized linear models.
Models incorporated transect as a blocking variable and belt type (grassland,
ecotonal, forested) as a categorical variable, using specific planned comparisons
(ecotone: grassland and ecotone: forest) rather than all pairwise comparisons. In
order to simplify interpretation, analyses were completed separately for all northand south-facing transects, regardless of ecotone definition. When completing the
moving window analyses five of the transects did not have a single clearly defined
ecotone, as a result all analyses were completed using the data from all twenty
transects (all transects) and then again using only the fifteen with clearly defined
ecotone centres (acceptable transects).
Two different measures of alpha diversity are reported: 1) mean plot
richness averaged from all plots within a belt and 2) total species richness derived

31

from plots and visual surveys of belts. Comparison of species richness and
abundance among belt types were made using the functional groupings. Linear
models compared abundance and richness of functional groups in statistically
defined ecotone belts versus forested and grassland belts, with transect as a
blocking variable and belt type as a categorical variable in each model with north
and south aspects analyzed separately.

RESULTS
ECOTONE DEFINITION
A standard moving window size (5 m) was used throughout the study to
ensure comparisons were equal. Although most transects showed a secondary
peak in the first ordination plot, the majority of those were minor and were not
considered separate ecotones. Table 2.5 outlines the results of the moving window
analysis used to define ecotone centres and boundaries. Ecotone widths ranged
from 5 to 10 m; where the mean width at north-facing aspects was 6.1 m and 6.6 m
at south-facing aspects. Eleven of the twenty ecotone centres sampled were
located in the grassland; eight were located inside the aspen canopy and only one
ecotone directly straddled the structural treeline (Table 2.5). The majority of
ecotone centres were not equidistant from ecotone boundaries; often the centres
were skewed towards one boundary or the other.
Transects marked with asterisks (numbered 2,3,7,8 and 11) did not display
a single clear peak using the moving window analysis (Table 2.5). As the results
did not differ substantially between the full data set and the “acceptable”
transects, I discuss only the results from ecotones with clearly identifiable centres
and boundaries. However, results from the analysis of all sampled transects can
be found in Appendix A (Tables A.1, A.2 and A.3).

32

Ecotone
peak

Ecotone
boundary
Ecotone
boundary

Figure 2.3 Illustration of ecotone boundaries as identified by the moving window
analysis. The dotted line shows the ordination score of the change in species
composition over the transect. The ecotone peak, or centre, is defined by the first
derivative of the ordination (Bray-Curtis dissimilarity) score measuring species
turnover along each transect. The boundaries are defined by the second derivative
of the ordination score.

Figure 2.2 Graphical representation of the moving window analysis.

Table 2.5 Ecotone identification (centre, width, belt boundaries) based on moving window results. Transects number
2,3,7,8 and 11 (marked with asterisks) did not yield clear results. Belts are numbered from grassland into forest (0 to 35)
with the treeline falling between belt number 15 and 16. Lac du Bois Grasslands Protected Area, Kamloops, BC, 2012.
Aspect

Transect
ID

Clear primary
peak(s) in
ordination scores

Ecotone centre
location (belt
number) 1)

Ecotone centre
under forest
canopy

Ecotone width
(metres) 2)

Ecotone belt
boundaries
(metres)

Belt number
of secondary peak(s)
(metres)

North

2*

no

19

Yes

7

18-24

many

4

yes

22

Yes

7

20-26

31

6

yes

6

No

5

5-9

19

South

8*

no

8

No

6

5-10

29

9

yes

11

No

5

10-14

29

11*

no

30

Yes

5

25-31

13, 23

12

yes

17

Yes

9

16-24

8

17

yes

14

Marginal3

6

13-18

23

18

yes

11

No

5

9-13

6

19

yes

8

No

6

6-11

23

1

yes

11

No

6

9-14

24

3*

no

11

No

10

9-18

30

5

yes

7

No

10

6-15

20

7*

no

24

Yes

10

20-29

9, 17

10

yes

10

No

7

8-14

25

13

yes

23

Yes

5

21-25

8

14

yes

28

Yes

7

24-30

7

15

yes

8

No

5

6-10

29

16

yes

11

No

5

9-13

27, 30

20

yes

27

Yes

8

23-30

9, 15

1) As defined by regressing the first ordination scores with distance using the moving window analysis (NMDS)
2) As defined by regressing the second ordination scores with distance using the moving window analysis
3) Ecotone center located at structural edge

33

34

SOIL DATA AND NON-VASCULAR PLANT SPECIES
Based on linear models (lm = soil moisture~belt.type+transect) soil
moisture did not vary significantly between ecotones and grasslands, or ecotones
and forests for either north or south aspects (Table 2.6). Soil pH generally
increased, in all cases, away from the ecotone, however none of these results
were significant (Table 2.6). Although there is a general trend of increasing
abundance (as measured by percent cover) of non-vascular plants (terrestrial
mosses and lichens) in grassland and forest belts as compared to ecotonal belts,
none of the results were significant (Table 2.6).
Table 2.6 Results from generalized linear models of acceptable transects comparing canopy
cover, soil moisture, soil pH and non-vascular plant species abundance in statisticallydefined ecotonal belts versus forested or grassland belts, with transect as a blocking
variable and belt type as a categorical variable in each model
(lm=variable~belt.type+transect).1

Variable
Canopy cover
Tree
Intermediate
Shrub
Soil moisture
Soil pH
Non-vascular
plants

North-Facing Ecotones
Forest-Ecotone
Grassland-Ecotone
∆ in
∆ in
p
p value
intercept
value
intercept

South-Facing Ecotones
Forest-Ecotone
Grassland-Ecotone
∆ in
∆ in
p value
p value
intercept
intercept

neg
neg
pos
pos
neg

0.128
0.406
0.517
0.938
0.113

pos
pos
pos
neg
neg

0.012
0.596
0.396
0.107
0.225

neg
neg
neg
neg
neg

<0.000
0.059
0.315
0.341
0.341

pos
neg
neg
pos
pos

0.125
0.757
0.587
0.593
0.593

neg

0.620

neg

0.499

pos

0.207

neg

0.174

Change in intercept indicates the direction of change in the variable from ecotonal to adjacent
belts (i.e., at north-facing transects there is significant more tree canopy cover in ecotone belts than
grassland belts). North and south transects are analyzed separately and p values in bold are
statistically significant (p<0.05).
1

FUNCTIONAL GROUP RICHNESS
Overall, the results of the general linear models did not support the
assumption that ecotones are more species rich than adjacent habitats (Table 2.7).

35
However, the richness of individual functional groups did vary significantly when
ecotonal belts were compared to adjacent belts. When compared to adjacent
forests, south-facing ecotones had greater species richness of those functional
groups expected to be associated with grasslands (i.e., shade intolerants,
graminoids, wind and generalist dispersers, intermediate drought tolerants and
grassland indicators). South-facing ecotones, when compared to adjacent forests,
also exhibited a decline in the species richness of forest-associated groups such as
shrubs and drought intolerants (Table 2.7). However, when south-facing ecotones
were compared to adjacent grasslands, all significant comparisons identified a
lower species richness of as rarely occuring species, forbs, and drought intolerants
in the ecotone belts.
Within north-facing ecotones, many functional groups expected to be
associated with grasslands (i.e., shade intolerants, graminoids, wind dispersed
species and drought tolerants) displayed greater richness in ecotonal habitats than
in adjacent forested habitats. Also within north-facing ecotones, there was
significantly higher species richness of drought intolerants, trees, and generalist
dispersers as compared to adjacent forests. When north-facing ecotones were
compared to adjacent grasslands, the richness of forbs and shrubs were higher in
the ecotone than in the adjacent grassland.

FUNCTIONAL GROUPS ABUNDANCE
Functional group abundance analysis yielded far fewer significant
comparisons than the richness analysis (Table 2.8). In contrast to the richness
data, the majority of significant comparisons showed decreased abundance
within ecotone belts compared to both grassland and forest belts.
Within north-facing ecotones, there was significantly lower abundance of
shrubs within ecotone belts as compared to forest belts, but a higher abundance of

36
drought intolerants. When north-facing ecotones were compared to adjacent
grasslands, shade intolerants and generalist dispersers exhibited a lower
abundance and intermediate-shade tolerants exhibited a higher abundance.
When south-facing ecotones were compared to adjacent forests, there was
lower abundance of aspen-associated groups (shade tolerants, shrubs and aspen
indicators) as well as animal dispersers within ecotone belts compared to forest
belts. There was a greater abundance of grassland indicators within south-facing
ecotone belts as compared to forest belts. When the same south-facing ecotones
were compared to adjacent forests, only the abundance of rare species was higher
in the ecotone.

37
Table 2.7 Results from generalized linear models of acceptable transects, comparing
richness of functional groups in statistically-defined ecotone belts versus forested
and grassland belts, with transect as a blocking variable and belt type as a
categorical variable in each model (lm=variable~belt.type+transect).1

Variable

North-facing Ecotones
Forest-Ecotone
Grassland-Ecotone
∆ in
∆ in
p value
p value
intercept
intercept

Mean species
richness
neg
Total species
richness
pos
Rare species
pos
Shade Tolerant Groups
Tolerant
pos
Intermediate
pos
Intolerant
pos
Growth Form Groups
Forb
pos
Graminoid
pos
Shrub
neg
Tree sapling
pos
Dispersal Method Groups
None
neg
Wind
pos
Animal
pos
Generalist
pos
Status
Groups
Native
pos
Exotic
pos
Drought Tolerant Groups
Tolerant
pos
Intermediate
pos
Intolerant
pos
Indicator Species Groups
Aspen
neg
Grassland
neg

South-facing Ecotones
Forest-Ecotone
Grassland-Ecotone
∆ in
∆ in
p value
p value
intercept
intercept

0.407

pos

0.373

pos

0.326

pos

0.060

0.826
0.387

pos
pos

0.212
0.967

pos
pos

0.061
0.718

neg
neg

0.958
0.026

0.840
0.671
0.001

pos
pos
neg

0.635
0.484
0.549

neg
neg
pos

0.415
0.415
0.001

neg
pos
neg

0.789
0.687
0.053

0.117
0.045
0.126
0.023

pos
neg
pos
pos

0.035
0.708
0.050
0.706

pos
pos
neg
pos

0.142
0.009
0.034
0.065

neg
neg
pos
neg

0.042
0.591
0.072
0.823

0.968
0.020
0.880
0.049

pos
pos
pos
neg

0.566
0.506
0.336
0.249

pos
pos
neg
pos

0.332
0.030
0.201
0.009

neg
neg
neg
neg

0.530
0.111
0.974
0.683

0.186
0.007

pos
pos

0.457
0.716

pos
pos

0.050
0.448

neg
neg

0.570
0.096

0.013
0.263
0.022

pos
neg
pos

0.325
0.957
0.992

neg
pos
neg

0.122
0.032
0.016

neg
neg
neg

0.220
0.297
0.043

0.174
0.098

pos
neg

0.516
0.357

neg
pos

0.004
0.002

pos
neg

0.398
0.305

Change in intercept indicates the direction of change in the variable in ecotonal belts compared to
either the forested or grassland belts (i.e., at south-facing aspects, there is significantly lower richness
of rare species in ecotone belts than grassland belts). North and south are analyzed separately and p
values in bold are statistically significant (p<0.05).
1

38
Table 2.8 Results from generalized linear models comparing abundance of
functional groups in statistically-defined ecotone belts versus forested and grassland
belts, with transect as a blocking variable and belt type as a categorical variable and
belt type as a categorical variable in each model (lm=variable~belt.type+transect).1
North-facing Ecotones
Forest-Ecotone
Grassland-Ecotone
∆ in
∆in
Variable
p value
p value
intercept
intercept
Rare species
neg
0.579
pos
0.395
Shade Tolerant Groups
Tolerant
neg
0.482
pos
0.078
0.071
Intermediate
pos
0.526
pos
Intolerant
neg
0.829
neg
<0.000
Growth Form Groups
Forb
pos
0.180
pos
0.283
Graminoid
pos
0.186
neg
0.127
Shrub
neg
0.018
pos
0.532
Tree sapling
pos
0.152
neg
0.334
Dispersal Method Groups
None
neg
0.193
neg
0.615
Wind
pos
0.100
pos
0.130
Animal
neg
0.237
pos
0.645
Generalist
pos
0.255
neg
0.033
Status Groups
Native
neg
0.363
neg
0.112
Exotic
pos
0.217
pos
0.974
Drought Tolerant Groups
Tolerant
neg
0.644
neg
0.079
Intermediate
neg
0.468
neg
0.081
Intolerant
pos
0.044
pos
0.313
Indicator Species Groups
Aspen
neg
0.174
pos
0.516
Grassland
pos
0.098
neg
0.357

South-facing Ecotones
Forest-Ecotone
Grassland-Ecotone
∆ in
∆ in
p value
p value
intercept
intercept
pos
0.062
pos
0.017
neg
neg
neg

0.030
0.350
0.623

neg
pos
neg

0.529
0.660
0.487

pos
pos
neg
pos

0.354
0.090
0.010
0.192

pos
neg
pos
neg

0.427
0.099
0.267
0.179

neg
neg
neg
pos

0.193
0.993
0.006
0.100

neg
neg
neg
neg

0.615
0.389
0.883
0.325

neg
neg

0.894
0.580

pos
neg

0.702
0.680

pos
pos
pos

0.601
0.528
0.316

pos
neg
pos

0.695
0.074
0.812

neg
pos

0.004
0.002

pos
neg

0.398
0.305

Change in intercept indicates the direction of change in the variable in ecotonal belts compared to
either the forested or grassland belts (i.e., at south-facing aspects, there is a significantly greater
abundance of rare species in ecotone belts compared to grassland belts). North and south are analyzed
separately and p values in bold are statistically significant (p<0.05).
1

39

DISCUSSION
ECOTONE ATTRIBUTES
In general, ecotonal attributes were more variable than expected; the width
and centre location of the ecotones varied broadly with no obvious pattern. Using
the moving window method to identify multiple ecotones along a single long
transect covering ground from a mangrove through a woodland to a pasture,
Walker et al. (2003) identified two peaks in the rate of change of species
composition relatively close to one another within the woodland-marsh interface.
They considered these two peaks to signify a single ecotone due to their close
proximity. Similarly, during the identification of the ecotones boundaries within
this study there was often a second lesser peak in the rate of change of species
composition found within the forested portion of the transect. This second peak
indicates that there is a second sharp change in species composition that might
suggest another ecotone within the forest, in addition to the more significant ones
generally found closer to the edge.
Orczewska and Glista (2005), in a comparison of one north- and one southfacing ecotone, found that the south-facing forest ecotone was wider. Although the
widest ecotones in this study were in fact south-facing, a t-test showed no
significant difference in the overall widths between aspects (p=0.146). The mean
width for south-facing ecotones was 7.3 m and 6.1 m for north-facing ecotones.
The aforementioned study only compared two transects one north and one south,
so it is hard to draw any strong conclusions. It seems that many ecotone studies
involve relatively low sample sizes, likely due to sampling intensity needed to
detect patterns (Murcia 1995). In this study the sample size was relatively large
and so the results tended to encompass a large range of possible ecotone patterns,

40
leading to the conclusion that ecotone locations and width patterns are highly
variable, and supporting the understanding that ecotones are not discrete lines on
the landscape but rather a zone of rapid species turnover.

SOILS AND NON-VASCULAR PLANTS
Based on previous forest soil research (Rhoades 1997; Binkley & Giardina
1998), a difference in pH between forest soils and grassland soils was expected,
largely due to influence of leaf litter and rainfall stemflow near tree trunks
(Rhoades 1997). Tree species, litterfall quality and rainfall stemflow all influence
surface soil pH (Binkley & Giardina 1998, Finzi, Canham & Breemen 1998). Soil
pH showed no significant differences between habitat types. It is possible that the
pH kit used was not sensitive enough, or that surface soil pH does not vary
widely in this region. Surface soil pH might not be a good indicator of deeper soil
biotic processes, since this layer of soil is susceptible to desiccation in summer and
freezing in winter. Surface soil pH and deeper mineral soil pH may not be
strongly correlated (Finzi et al. 1998). It is also possible that the influence of the
forest cover on pH may extend much further than expected into the grassland.

FUNCTIONAL GROUP CHARACTERISTICS
The ecotones sampled in this study were not more species rich than the
adjacent grasslands and aspen stands, regardless of aspect. These results add
support to a growing number of ecotonal studies that question the assumption
that all ecotones are species-rich (Van der Maarel 1990; Harper & MacDonald
2001; Walker et al. 2003; Senft 2009). Walker et al. (2003) also found little
significant difference in species richness in ecotones and within their study only
one of the five identified ecotones displayed greater species richness than the
adjacent habitats. They also found this relationship to be scale-dependent; that is,

41
at a 1 m2 scale the results were non-significant but at a 0.5 m2 scale they were
significant.
Four a priori hypotheses were identified to explain expected differences in
functional group richness and abundance (Chapter 2, Table 2.1). The first
hypothesis proposed that environmental heterogeneity could lead to increased
species packing within ecotonal belts. In this study, high rates of species change
were used as a proxy for species packing; increased species richness, therefore,
was predicted to co-occur with the center of identified ecotones. Overall there was
no significant difference in mean or total species richness at the ecotonal belts
indicating that the location of the greatest species turnover does not coincide with
increased species richness. This means that that even though the ecotone regions
are zones of rapid species turnover, they are not necessary zones of increased
richness (Table 2.7).
The second a priori hypothesis identified by Senft (2009) suggests that
spatial mass effects would lead to increased richness. Spatial mass effects results
when species dominating one habitat (e.g. aspen indicator species) would have
higher richness in ecotones than in the habitat found on the opposite side of the
ecotone (e.g., in the grassland). In this study, however, only one of the four
relevant comparisons (i.e., grassland indicators compared in south-facing
ecotones as compared to forests) showed increased richness and abundance (Table
2.7 and 2.8). This suggests that the influence of spatial mass effect in the ecotones
sampled in this study is minimal.
The third a priori hypothesis suggests that animal seed dispersal or
predation could explain differences in functional group richness and abundance
within ecotones. Animal-dispersed seeds differed significantly in only one case: at
south-facing ecotones where the abundance was lower than in adjacent forests

42
(Table 2.8). Some studies have cited higher diversity of bird-dispersed species
(Kollmann 2000) and greater abundance of animal seed dispersers (Burgess et al.
2006) at forest edges. Animal-dispersed seeds can move great distances both
inside and outside forest patches (Bossuyt et al. 1999), which might explain why
there was very little difference found in richness of this functional group.
However, wind dispersed species may be influenced by the structure of a forest
canopy and edge (Devlaeminck et al. 2005; Kumar et al. 2006) and this is
supported by the data; at both north and south transects there was a significant
decrease in the richness of wind dispersed species in adjacent forest habitats
(Table 2.7). Likewise, Baldwin and Bradfield (2005) noted that disturbanceassociated bryophytes which have a high wind-dispersal capacity have higher
richness in forest edges.
The final a priori hypothesis suggests the increased richness and abundance
of exotic species within ecotones may explain expected patterns. In this study, this
was supported only at north-facing transects where there was an increased
richness of exotic species within ecotonal belts when compared with forested belts
(Table 2.7). If a link between aspect, moisture and productivity is assumed this
result correlates with the findings of Stohlgren et al. (1998) who found that
riparian zones (a type of ecotone) contained an increase in exotic species
compared to adjacent habitats. The authors of this study suggested that because
riparian zones are highly productive, they are easily invaded by opportunistic
exotics. However, the abundance of exotic species did not contribute to significant
differences in species composition within these ecotones when compared to
adjacent belt types; this agrees with the findings of both Senft (2009) and Walker
et al. (2003).

INFLUENCE OF ASPECT

43
Based on the results of this study, the influence of aspect varied with the
habitat type with which ecotones were compared. When ecotones were compared
to adjacent forest, the majority of significant comparisons (15 out of 18 across both
north- and south-facing aspects) indicated that ecotones contained a higher species
richness of each functional group. Aspect was more important in the ecotonegrassland comparisons where significant comparisons indicated ecotones had
higher species richness within functional groups on north-facing ecotones and
lower species richness within functional groups on south-facing ecotones. A lack
of aspect influence on the ecotone forest comparisons may be explained by the
moderating effect of the forest canopy on solar radiation, drought and
temperature (Rhoades 1997). But, in contrast, Hylander (2005) observed a strong
influence of aspect on bryophyte community characteristics at forest edges. Some
studies have found that edge zones between forest and meadow are wider on
edges with higher solar exposure i.e., south aspects (Fraver 1994; Murcia 1995;
Orczewska & Glista 2005).

CONCLUSION
Overall, the ecotones in this study were not more species rich than the
adjacent grasslands and aspen stands, when considered using the moving
window method to define boundaries. There were very few significant differences
in species richness and functional group richness or abundance. In general,
differences in functional group richness between ecotones and adjacent habitats
did not support the four a priori hypotheses, with one exception; dispersal mode
played a role in the difference in species richness between ecotones and forests. It
would seem, that at least in this aspen-grassland matrix, assumptions about
increased richness and abundance within ecotones are not supported.

44

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51

CHAPTER 3 TESTING THE METHODS: COMPARING STRUCTURAL
AND STATISTICAL APPROACHES IN ECOTONE ANALYSIS

INTRODUCTION
It is increasingly clear that, in science, how we ask and answer questions
influences the nature of our conclusions. Bogen (2014) argued that all aspects of
research – experimental design, methods and data production – are strongly
influenced by background assumptions about the subject under investigation. In
ecology, differing assumptions have led to contradictory definitions even of such
fundamental terms as “competition” and “interference”; these definitions took
years of extensive debate to achieve consensus (Connolly et al. 2001). Beyond
definitions, aspects of experimental design such as the choice of predictor and
response variables, scale, and methods of ecosystem simplification can lead to
conflicting conclusions from studies testing similar hypotheses even within the
same communities (Gosz 1993; Murcia 1995; Pausas & Austin 2001; Erdôs et al.
2011). Finally, competing statistical approaches can also lead to variable results.
An additional issue related to ecotones, specifically, is that they have been
analyzed both as discrete blocks and as gradients between the surrounding
habitats (Gosz 1993; Fortin et al. 2000). This difference in approach is not unlike
the historic controversy between Gleason and Clements regarding plant
communities (Clements 1916; Gleason 1926; Callaway 1997). Within ecotones,
some species may respond to an ecotone as a discrete boundary (or a block),
whereas some may respond as if it is a gradient (Harper & MacDonald 2001).
With this in mind, it is important to examine the data from a gradient as well as a
blocked approach.

52
In science we often strive to clearly categorize and simplify systems, but
natural systems often do not fit within such discrete definitions (Erdôs et al.
2011). With this in mind, this chapter will compare the analysis of Chapter Two
(a blocked approach) with a gradient approach. This chapter will also compare
the results when ecotones are defined subjectively to the results when ecotones
are defined statistically as in Chapter Two. Although repeated analysis of the
same dataset will increase the likelihood of finding significant results, in this case
it was necessary to compare methods of ecotone definition.
The objective of this chapter is to address how ecotone definition and
experimental approach affect observed patterns by asking these questions:
1) How does species richness and abundance of functional groups (taxonomic,
shade tolerance, growth form, dispersal method, status, drought tolerance and habitat
indicator species) vary over grassland-aspen ecotones? 2) How do the observed patterns
vary across north- and south-facing ecotones in the same system?

METHODS
Methods follow Chapter Two for site selection, vegetation sampling,
functional group classification and statistical identification of ecotones. The same
dataset that was used in Chapter 2 is used here. This chapter compares alternative
methods of ecotone definition and analysis, where ecotones have been defined either
statistically as the location of the greatest species turnover, or structurally as the
location of aspen patch treeline, and were analyzed either with a blocked approach
similar to that used in Chapter 2 or with a gradient approach. When the data was
analyzed as a gradient distance from treeline into forest or grassland was included
as a continuous variable in the generalized linear models and the belts were not
blocked together. Data was compared from the treeline outwards into the forested

53
belts or grassland belts for this approach.

BLOCKED APPROACH - STRUCTURALLY-DEFINED ECOTONES
The centres of structurally-defined ecotones were located at the treeline
edge of aspen stands as defined by the presence of mature aspen boles. To allow
for comparison of structurally-defined ecotones with the statistically defined
ecotones in Chapter Two, I used the mean ecotone width identified by the
moving window analysis (7 m) centred on the treeline. All belts falling within the
ecotone boundaries were categorized as ecotone belts, while those on the forest
side and grassland sides of the ecotone were categorized respectively as forest and
grassland belts. To evaluate the relationship between belt type and functional
group richness and abundance, I used normal linear regression with functional
group richness and abundance logarithmically transformed (where necessary)
and belt type entered as a categorical variable in the model. As the overall intent
of this chapter is to compare the results that are found when ecotones are defined
statistically or structurally, I limited the analysis of transects to those fifteen
“acceptable” transects with clearly defined ecotone centers and boundaries
(Chapter 2, page 34). However, results from the analysis of all sampled transects
can be found in Appendix A (Tables A.4, A.5, A.6, A.7, A.8, A.9 and A.10).

GRADIENT APPROACH - STATISTICAL AND STRUCTURAL DEFINITIONS
The data was also analyzed from a gradient approach, in order to compare
the effect of increasing distance from the centre of the ecotone. Each variable was
compared using linear regression from the centre outwards. This analysis was
repeated using both the statistically- and structurally-defined ecotone centres. In
the case of the statistically-defined ecotone, the belt identified as the peak in
species turnover was used as the ecotone centre and data was analyzed outward

54
into either the forest or the grassland. For the structurally-defined ecotone, the
treeline created by the mature boles of the aspen trees was used to identify the
centre. Again, all data was analyzed outwards into the forest or grassland. To
evaluate the relationship between distance from ecotone centre and functional
group richness and abundance, I used normal linear regression with functional
group richness and abundance logarithmically transformed where necessary.

RESULTS
BLOCKED APPROACH, STRUCTURALLY-DEFINED ECOTONES
Canopy cover and Soil Data
As might be expected, canopy cover was significantly higher in structurallydefined ecotone belts when compared to grassland belts on both north- and southfacing aspect (Table 3.1). In comparison soil moisture and soil pH in ecotones did
not differ significantly from that found in either forest or grassland belts.
Functional Group Richness and Abundance: Blocked Approach, Structurally-Defined
Ecotones
As in Chapter Two, the results from this analysis did not find general
support for the assumption that ecotones are more species rich than adjacent
habitats (Table 3.2); however, statistically significant differences in total species
richness were found in the comparison of south-facing structurally-defined
ecotonal and grassland belts.
Overall, comparison of individual plant functional group richness between
ecotone and grassland belts varied with aspect (Table 3.2). This pattern is consistent
with that observed in Chapter Two (p. 34). On south-facing transects, ecotone belts
had lower total richness than adjacent grassland belts as well as lower richness in
functional groups expected to be associated with grasslands: shade intolerants,

55

Table 3.1 Results from generalized linear models comparing canopy cover, soil
moisture and soil pH in structurally-defined ecotone belts versus forested or
grassland belts, with transect as a blocking variable and belt type as a categorical
variable in each model (lm=variable~belt.type+transect). 1

Variable

North-facing Ecotone
Forest-Ecotone
Grassland-Ecotone
∆ in
∆ in
p
p
intercept
intercept
value
value

South-facing Ecotone
Forest-Ecotone
Grassland-Ecotone
∆ in
∆ in
p
p
intercept
intercept
value
value

Canopy
cover
Tree
Intermediate
Shrub
Soil
moisture
Soil pH

pos
neg
pos

0.360
0.265
0.682

pos
pos
pos

<0.000
0.495
0.564

neg
pos
pos

0.008
0.555
0.653

pos
pos
pos

<0.000
0.008
0.307

pos
neg

0.902
0.104

neg
neg

0.075
0.298

neg
pos

0.307
0.898

pos
pos

0.171
0.627

Change in intercept indicates the direction of change in the variable between belt types (i.e., at
north-facing aspects there is significant more tree canopy cover in ecotone belts compared to
grassland belts). North and south transects are analyzed separately and p values in bold are
statistically significant (p<0.05).
1

wind dispersers and grassland indicator species. Ecotonal belts in this comparison
also had significantly fewer rare species and forbs. Only one functional group,
shrubs, showed higher richness at south-facing structurally-defined ecotone belts
when compared to grassland belts. In comparison, on north-facing transects,
structurally-defined ecotonal belts, as compared to grassland belts, had significant
increases in the richness of four functional groups (shrubs, animal-dispersed
species, species with no clear dispersal method and aspen indicators, Table 3.2).
When ecotone belts were compared with adjacent forest belts, aspect
influenced the results far less. For both north- and south-facing ecotones, nearly
all statistically significant comparisons of plant functional groups found higher
species richness in the ecotone as compared to the adjacent forest (with the
exception of aspen-indicator species in south-facing ecotones, Table 3.2).
Specifically, on south-facing aspects, ecotones had significantly higher richness of
shade intolerants, graminoids, wind dispersers, generalists, intermediate drought

56
tolerants, grassland indicators, and aspen indicator species. The only functional
group to show decreased richness in the ecotone as compared to the forest was
the aspen-indicator group. Likewise comparison of north-facing structurallydefined ecotones with adjacent forest indicated ecotones had significantly higher
richness of grassland-associated groups (shade intolerants, graminoids, wind
dispersers, high and intermediate drought tolerant species and grassland
indicators) as well as non-grassland associated groups (forbs, generalist
dispersers, native and exotic species).
Overall, analysis of functional group abundance yielded fewer significant
results than the richness analysis (Table 3.3). Unlike the analysis of functional
group richness, significant differences in functional group abundance across the
ecotone did not vary with aspect in an obvious pattern. At south facing sites there
was an increase in rarely occurring species in structurally-defined ecotone belts
compared to both grassland and forest belts. South-facing ecotone belts, when
compared to adjacent grassland belts, had a decrease in the abundance of
grassland indicator species. Compared to adjacent forest belts, south-facing
structurally-defined ecotone belts showed a significant decrease in the abundance
of shrubs and animal-dispersed species and an increase in the abundance of
aspen indicator species, generalist dispersers and grassland indicators.
North-facing structurally-defined ecotone belts exhibited a significant
decrease in native species abundance when compared to both forest belts and
grassland belts (Table 3.3). North-facing ecotonal belts compared to grassland
belts exhibited a significant increase in the abundance of aspen indicator species
and a decrease in shade intolerant abundance. There was a decrease in shrub and
an increase in exotic species abundance within north-facing structurally-defined
ecotonal belts compared to forested belt.

57
Table 3.2 Results from linear models comparing functional group richness in
structurally-defined ecotone belts versus forested and grassland belts, with transect
as a blocking variable and belt type as a categorical variable in each model
(lm=Variable~Belt.type+Transect).1
North-facing Ecotone
Forest-Ecotone

South-facing Ecotone

Grassland-Ecotone

Forest-Ecotone

Grassland-Ecotone

∆ in
intercept

p
value

∆ in
intercept

p
value

∆ in
intercept

p
value

∆ in
intercept

p
value

Mean species
richness

pos

0.055

pos

0.758

pos

0.767

neg

0.097

Total species
richness

neg

0.406

neg

0.303

neg

0.062

neg

0.021

Rare species

pos

0.093

neg

0.836

pos

0.227

neg

0.029

Variable

Shade Tolerant Groups
Tolerant

pos

0.214

pos

0.348

neg

0.469

neg

0.831

Intermediate

pos

0.090

pos

0.203

neg

0.444

pos

0.871

Intolerant

pos

0.005

neg

0.053

pos

0.011

neg

0.007

Forb

pos

0.007

pos

0.456

pos

0.392

neg

0.038

Graminoid

pos

0.004

neg

0.870

pos

0.022

neg

0.338

Shrub

neg

0.188

pos

0.054

neg

0.066

pos

0.041

Tree sapling

pos

0.190

neg

0.809

pos

0.446

neg

0.102

Growth Form Groups

Dispersal Method Groups
None

pos

0.127

pos

0.034

neg

0.719

neg

0.106

Wind

pos

0.047

neg

0.693

pos

0.040

neg

0.010

Animal

pos

0.157

pos

0.039

neg

0.207

neg

0.623

Generalist

pos

0.028

neg

0.197

pos

0.005

neg

0.528

Native

pos

0.021

pos

0.521

pos

0.256

neg

0.145

Exotic

pos

0.003

pos

0.438

pos

0.337

neg

0.167

Status Groups

Drought Tolerant Groups
Tolerant

pos

0.049

pos

0.489

neg

0.224

neg

0.103

Intermediate

pos

0.009

pos

0.554

pos

0.023

neg

0.374

Intolerant

pos

0.103

pos

0.986

neg

0.136

neg

0.072

pos

0.403

pos

0.003

neg

0.004

pos

0.279

pos

0.019

pos

0.011

neg

0.010

Indicator Species Groups
Aspen stands
Grassland

neg

0.170

Change in intercept indicates the direction of change in the variable in structurally-defined ecotonal
belts compared to either the forested or grassland belts (i.e., at south-facing aspects total species
richness is significantly lower in ecotonal belts than in grassland belts). North and south are analyzed
separately and p values in bold are statistically significant (p<0.05).
1

58
Table 3.3 Results from linear models comparing abundance of functional groups in
structurally-defined ecotone belts versus forested and grassland belts, with transect
as a blocking variable and belt type as a categorical variable in each
(lm=Variable~Belt.type+Transect).1
North-facing Ecotone
Forest-Ecotone
Grassland-Ecotone
∆ in
∆ in
p
p
Variable
intercept
intercept
value
value
Rare species
neg
0.889
pos
0.072
Shade Tolerant Groups
Tolerant
neg
0.178
pos
0.594
Intermediate
pos
0.386
pos
0.127
Intolerant
neg
0.290
neg
<0.000
Growth Form Groups
Forb
pos
0.354
pos
0.437
Graminoid
pos
0.090
neg
0.099
Shrub
neg
0.010
pos
0.267
Tree sapling
pos
0.192
neg
0.179
Dispersal Method Groups
None
neg
0.808
pos
0.225
Wind
pos
0.151
pos
0.942
Animal
neg
0.172
pos
0.921
Generalist
pos
0.129
neg
0.276
Status Groups
Native
neg
0.026
neg
0.015
Exotic
pos
0.032
pos
0.295
Drought Tolerant Groups
Tolerant
pos
0.226
neg
0.652
Intermediate
neg
0.467
neg
0.151
Intolerant
pos
0.336
pos
0.772
Indicator species Groups
Aspen stands
pos
0.507
pos
0.003
Grassland
pos
0.079
neg
0.229

South-facing Ecotone
Forest-Ecotone
Grassland-Ecotone
∆ in
∆ in
p
p
intercept
intercept
value
value
pos
0.054
pos
0.005
neg
neg
pos

0.605
0.090
0.888

pos
neg
pos

0.304
0.760
0.690

neg
pos
neg
pos

0.894
0.087
0.002
0.396

neg
pos
neg
neg

0.594
0.514
0.984
0.070

neg
pos
neg
pos

0.053
0.892
0.009
0.030

neg
neg
pos
pos

0.409
0.485
0.751
0.623

neg
pos

0.316
0.820

neg
pos

0.689
0.550

pos
pos
pos

0.731
0.534
0.551

pos
neg
neg

0.138
0.084
0.653

pos
pos

0.003
0.011

pos
neg

0.609
0.008

Change in intercept indicates the direction of change in the variable in structurally-defined ecotonal
belts compared to either the forested or grassland belts (i.e., at south-facing aspects there is
significantly greater abundance of rare species ecotonal belts than in grassland belts). North and
south are analyzed separately and p values in bold are statistically significant (p<0.05).
1

59

GRADIENT APPROACH, STRUCTURALLY-DEFINED ECOTONES
Canopy Cover and Soil Data
Both north- and south-facing grassland belts exhibited a significant
increase in canopy cover with increasing proximity to the structurally-defined
ecotone (Table 3.4). In addition, north-facing forest belts also displayed a
significant increase in tree canopy cover with proximity to the structurally-defined
ecotone centre. This agrees with personal observations of diminished forest
canopy in the patch center where it appeared old trees were dying (M. Ross,
personal observation). On north-facing grassland belts, soil moisture was
positively associated with increased proximity to the structurally-defined ecotone.
Soil pH increased with proximity to the structural edge on north-facing grassland
belts and decreased with proximity on south-facing belts. With one exception
(south-facing grassland belts) non-vascular plant abundance decreased with
proximity to the structural ecotone across both north- and south-facing aspects
(Table 3.4).
Species Richness and Abundance: Gradient Approach
In this study, the gradient approach analysis of ecotones produced more
significant differences in species richness (Table 3.5) than when the same ecotones
were analyzed with a blocked approach (Tables 3.2). However, like the blocked
approach, results varied with the ecotone aspect. At north-facing structurallydefined ecotones, both grassland and forest belts exhibited a positive association
between mean species richness and proximity to the structurally-defined ecotone
(Table 3.5). In contrast, within south-facing ecotones, mean richness in grasslandbelts significantly decreased with proximity to structurally-defined ecotone and
forested belts showed no significant association with mean species richness and

60
proximity to the structurally-defined ecotone (Table 3.5).

Table 3.4 Summaries of generalized linear models comparing canopy cover, soil
moisture and soil pH for both forested and grassland transects with increasing
proximity to the structurally-defined ecotone centre (treeline). Distance included as
a continuous variable. lm= variable~distance towards treeline.1
Variable

North-facing Ecotones

South-facing Ecotones

p value

slope

p value

slope

Canopy cover
Grassland
Tree

0.000

pos

0.000

pos

Tree sapling
Shrub
Forested
Tree
Tree sapling
Shrub
Soil Moisture

0.005
0.428

pos
neg

0.000
0.157

pos
pos

0.000
0.002
0.119

pos
neg
pos

0.316
0.301
0.157

pos
neg
pos

Grassland
Forested

<0.000
0.434

pos
neg

0.481
0.062

neg
pos

Grassland
Forested
Non-vascular Plants
Grassland

0.020
0.156

pos
pos

0.002
0.598

neg
neg

0.042

neg

0.003

neg

Forested

0.002

neg

0.003

pos

Soil pH

North and south transects are analyzed separately and p value in bold are statistically
significant (p<0.05). Slope indicates the change in variable values with increasing
proximity to the ecotone, defined here as the structural treeline (i.e. for north-facing
aspects, there is a significant increase in tree canopy cover with increasing proximity to
the structural ecotone).
1

The significant association between mean species richness and ecotone
proximity found in north-facing grassland and forest belts was driven by the
large number of significantly positive associations between individual functional
groups and proximity to the structural edge. In grassland-belts, the richness of
groups expected to be associated with aspen habitats (high- and medium-shade

61
tolerants, shrubs, drought-intolerants, medium drought-tolerants and aspen
indicators) as well as nitrogen and non-nitrogen-fixers, animal-dispersed species
and species with no obvious dispersal method all increased significantly with
proximity to the structural ecotone (Table 3.5). Likewise forest belts on northfacing ecotones were characterized by significantly positive associations between
the proximity from the structural ecotone and the richness of groups associated
with grasslands (shade- intolerant species and graminoids) as well as the richness
of exotic species, forbs, medium- and drought-intolerants, non nitrogen-fixers,
wind-, animal-, and generalist-dispersers. On north-facing ecotones, those
functional groups that exhibited a negative association between richness and
proximity to the structural edge differed between grassland and forest belts. On
forested belts, the richness of shrubs and aspen-indicators showed negative
association with proximity to the structural edge, whereas on grassland-belts, the
richness of shade intolerants, drought-tolerants, grassland indicators (all groups
expected to increase in grasslands) as well as generalist dispersers displayed
significant negative associations with proximity (Table 3.5).
On south-facing grassland-belts, the negative association between mean
species richness and proximity to the structural ecotone was likely driven by the
large number of functional groups that displayed a significant negative association
between richness and proximity to the structural edge (i.e., shade intolerants,
forbs, graminoids, drought tolerant and drought intolerants, non-nitrogen fixers,
nitrogen fixers, grassland-indicators, wind and species with no dispersal
mechanism (Table 3.5)). The only functional groups to show a significant positive
association with proximity to the structural edge in south-facing grassland-belts
were shrubs and aspen indicators. In south-facing forest belts, groups associated
with grasslands such low shade-tolerants, graminoids, as well as medium

62
drought-tolerants, non-nitrogen fixers, exotics, and generalist dispersers all
displayed significant negative associations with increasing proximity to the
structurally-defined ecotone. In comparison, shrubs, low drought-tolerants, aspen
indicators and animal-dispersed species) exhibited positive associations with
proximity (Table 3.5). In most cases in forested belts, grassland-associated
functional group richness showed positive associations with proximity to the
structural ecotone and negative association with proximity in grassland-belts.
Aspen-associated groups, in general, exhibited the opposite trend.
When functional group abundance was analyzed, fewer functional groups
showed significant associations with proximity to the structurally-defined
ecotone (Table 3.6). Within north-facing grassland-belts, the abundance of some
forest-associated species (shade tolerants, forbs, shrubs and aspen indicators) was
positively associated with proximity to the structurally-defined ecotone, whereas
the abundance of grassland-associated groups (shade intolerants, graminoids,
drought tolerants and grassland indicators) were negatively associated with
proximity to the structural ecotone. South-facing grassland-belts exhibited the
same general trend although the fewer functional groups had significant
associations between abundance and proximity (Table 3.6). In these belts, the
abundance of one forest-associated group (aspen indicator species) was
positively associated with proximity to the structural ecotone and one grasslandassociated group (drought tolerants) was negatively associated with proximity to
the structural edge.
Within north-facing forested belts, the abundance of aspen-associated
groups (forbs, shrubs and aspen indicators) was positively associated with
proximity to the structural edge. On south-facing forest belts, the abundance of
grassland-associated groups (graminoids, drought tolerants and grassland

63
indicators) was positively associated with proximity to the structurally-defined
ecotone (Table 3.6).
Table 3.5 Summaries of generalized linear models comparing plant functional
group richness for both forested and grassland transects with increasing distance
from the structurally-defined ecotone centre (treeline), with distance included as a
continuous variable. lm=variable~distance from treeline. 1
North-facing Ecotone

South-facing Ecotone

p value

slope

p value

slope

Grassland

0.002

pos

0.008

neg

Forested

<0.000

pos

0.973

pos

Grassland

0.327

neg

0.454

neg

Forested

0.030

pos

0.001

pos

Tolerant

0.001

pos

0.588

pos

Intermediate

<0.000

pos

0.459

neg

Intolerant

0.003

neg

<0.000

neg

Tolerant

0.534

pos

0.003

neg

Intermediate

0.056

pos

0.323

neg

Intolerant

<0.000

pos

<0.000

pos

Variable
Mean Species Richness

Exotic Species

Shade Tolerant Groups
Grassland

Forested

Growth Form Groups
Grassland
Forb

0.002

pos

0.002

neg

Graminoid

0.731

neg

0.026

neg

Shrub

<0.000

pos

0.002

pos

Tree sapling

0.895

pos

0.100

neg

Forb

0.001

pos

0.169

neg

Graminoid

0.002

pos

<0.000

pos

Shrub

0.007

neg

0.005

neg

Tree sapling

0.033

pos

0.332

pos

Tolerant

0.125

neg

0.023

neg

Intermediate

0.001

pos

0.261

neg

Intolerant

<0.000

pos

0.005

neg

Forested

Drought Tolerance
Grassland

Forested

64
Tolerant

0.775

pos

0.064

pos

Intermediate

<0.000

pos

<0.000

pos

Intolerant

0.001

pos

0.004

neg

Fixation

0.004

pos

0.002

neg

None

0.015

pos

0.004

neg

Fixation

0.068

pos

<0.000

neg

None

0.001

pos

0.001

pos

Aspen

<0.000

pos

0.001

pos

Grassland

<0.000

neg

<0.000

neg

Aspen

<0.000

neg

<0.000

neg

Grassland

0.367

pos

0.027

pos

None

0.022

pos

0.001

neg

Wind

0.542

pos

0.007

neg

Animal

<0.000

pos

0.450

neg

Generalist

0.002

neg

0.585

neg

None

0.061

pos

0.365

neg

Wind

<0.000

pos

0.090

pos

Animal

0.036

pos

0.006

neg

Generalist

0.003

pos

<0.000

pos

Nitrogen fixation
Grassland

Forested

Indicator Groups
Grassland

Forested

Dispersal method
Grassland

Forested

North- and south-facing are analyzed separately and p values in bold are
statistically significant (p<0.05). Slope indicates the change in the variable
over the distance gradient (i.e., on north-facing grassland belts there is a
significant increase in mean species richness with increasing proximity to the
ecotone).
1

65
Table 3.6 Summaries of generalized linear models comparing abundance of plant
functional groups for both forested and grassland transects along a distance
gradient from the structural ecotone (treeline). lm=variable~distance from treeline. 1
North-facing Ecotones

South-facing Ecotones

p value

slope

p value

slope

Grassland

0.212

pos

0.040

pos

Forest

0.404

pos

0.024

pos

Tolerant

<0.000

pos

0.091

pos

Intermediate

<0.000

pos

0.131

pos

Intolerant

<0.000

neg

0.225

neg

Variable
Exotic Species

Shade Tolerance
Grassland

Forested

Tolerant

0.171

neg

0.697

neg

Intermediate

0.874

neg

<0.000

neg

Intolerant

0.062

neg

0.279

pos

Growth Form
Grassland

Forested

Forb

0.021

pos

0.791

neg

Graminoid

<0.000

neg

0.666

neg

Shrub

0.001

pos

0.005

pos

Tree sapling

0.948

pos

0.182

neg

Forb

0.888

pos

<0.000

neg

Graminoid

0.001

pos

<0.000

pos

Shrub

<0.000

neg

<0.000

neg

Tree sapling

0.117

pos

0.294

pos

Tolerant

0.007

neg

<0.000

neg

Intermediate

0.007

neg

<0.000

pos

Intolerant

0.056

neg

<0.000

neg

Tolerant

0.055

pos

<0.000

pos

Intermediate

0.409

neg

0.064

pos

0.091

pos

0.015

pos

Fixation

0.038

pos

0.676

pos

None

<0.000

neg

0.594

neg
neg

Drought Tolerance
Grassland

Forested

Intolerant
Nitrogen Fixation
Grassland
Forested

Fixation

0.624

pos

<0.000

None

0.002

neg

0.194

neg

Aspen

<0.000

pos

0.001

pos

Grassland

0.001

neg

<0.000

neg

Aspen

<0.000

neg

<0.000

neg

Grassland

0.208

pos

0.027

pos

Indicator Species
Grassland
Forested
Dispersal Method

66
Grassland

Forested

None

0.006

pos

0.600

neg

Wind

0.273

pos

0.831

pos

Animal

0.315

pos

0.681

neg

Generalist

<0.000

neg

0.936

neg
neg

None

0.357

pos

0.001

Wind

0.888

neg

0.010

neg

Animal

<0.000

neg

<0.000

neg

Generalist

0.005

pos

<0.000

pos

North- and south-facing aspects are analyzed separately and p values in bold are statistically
significant (p<0.05). Slope indicates the change in the variable over the distance gradient (i.e., for
south-facing grasslands there is a significant increase in abundance of exotic species with
increasing proximity to the ecotone).
1

GRADIENT APPROACH, STATISTICALLY-DEFINED ECOTONES
Gradient analysis was also completed using distance from the statistically
defined ecotone centre rather than the structurally-defined ecotone centre
(treeline). Due to the fact that statistically defined ecotone centres were located
primarily within the grassland-belts of each section, it was only feasible to
analyze the data from the ecotone center toward the forest. Thus, all the
following results are only one-sided: examining the richness and abundance from
the ecotone center towards the forest belts.
With this approach, mean species richness within south-facing ecotones
was positively associated with increasing proximity to the statistically-defined
ecotone centres (Table 3.7). This increase in mean richness on these south-facing
transects was likely driven by the positive association of both grasslandassociated groups (graminoids, drought tolerant species and wind dispersers)
and aspen-associated groups (forbs, juvenile trees) in addition to animal and
generalist dispersers.
Within north-facing ecotones, the richness of grassland-associated groups
(shade intolerants, graminoids, drought-tolerants and grassland indicators) and

67
two aspen-associated groups (forbs and understory trees), as well as exotics,
nitrogen fixers, and animal and generalist dispersers all showed a significant
positive association with increasing proximity to the ecotone center. On northfacing ecotones the only plant functional groups with significant negative
associations with proximity to the statistical ecotone were non-nitrogen fixers and
two aspen-associated groups (shrubs and aspen indicator species).
When plant abundance is considered the results are quite similar with a
few exceptions (Table 3.8). At both north- and south-facing transects, the
abundance of animal-dispersed species was negatively associated with increasing
proximity to the ecotone center, even though the richness of this functional group
showed the opposite trend. Furthermore, on south-facing ecotones, the abundance
of two grassland-associated groups (shade intolerants and grassland indicators)
was negatively associated with increasing proximity and the abundance of
drought intolerants was positively associated with increasing proximity. In
general, the gradient approach, using the statistically-defined ecotone centre,
showed even more significant associations between plant functional group
richness and abundance with increasing distance from the ecotone center than
was found using a gradient approach from the structural ecotone.

68

Table 3.7 Summaries of generalized linear models comparing plant functional group
richness for forested belts with increasing distance from the statistically-defined
ecotone centre, with distance included as a continuous variable.
lm=variable~distance from ecotone centre.1
North-facing Ecotone

South-facing Ecotone

p value

slope

p value

slope

Mean Species Richness

0.859

pos

0.004

pos

Exotic Species

<0.000

pos

0.425

neg

Tolerant

0.064

pos

0.515

pos

Intermediate

0.001

pos

0.692

pos

Intolerant

<0.000

pos

<0.000

pos

Forb

<0.000

pos

<0.000

pos

Graminoid

<0.000

pos

<0.000

pos

Acceptable Ecotones

Shade Tolerant Groups

Growth Form Groups

Shrub

<0.000

neg

<0.000

neg

Tree sapling

0.016

pos

0.002

pos

Tolerant

<0.000

pos

0.003

pos

Intermediate

<0.000

pos

<0.000

pos

Intolerant

0.001

pos

<0.000

neg

Fixation

<0.000

pos

0.459

pos

None

0.001

neg

<0.000

neg

Aspen

<0.000

neg

<0.000

neg

Grassland

<0.000

pos

<0.000

pos

None

0.573

pos

0.716

pos

Wind

0.233

pos

0.026

pos

Animal

<0.000

pos

<0.000

pos

Generalist

<0.000

pos

<0.000

pos

Drought Tolerance

Nitrogen Fixation

Indicator Species

Dispersal Method

North and south are analyzed separately and p values in bold are statistically
significant (<0.05). Slope indicates the change in the variable over the distance
gradient (i.e., for south-facing aspects there is a significant increase in mean species
richness with increasing proximity to the ecotone centre).
1

69

Table 3.8 Summaries of generalized linear models comparing plant functional group
abundance for forested belts with increasing distance from the statistically-defined
ecotone centre, with distance included as a continuous variable.
lm=variable~distance from statistically-defined ecotone centre.1
North-facing Ecotone

South-facing Ecotones

p value

slope

p value

slope

<0.000

pos

0.004

neg

Tolerant

0.048

neg

0.009

neg

Intermediate

<0.000

pos

0.001

neg

Intolerant

0.001

neg

0.001

neg

Forb

<0.000

pos

0.673

neg

Graminoid

<0.000

pos

0.606

pos

Shrub

<0.000

neg

<0.000

neg

Tree sapling

0.023

pos

<0.000

pos

Tolerant

0.001

pos

0.004

neg

Intermediate

0.827

neg

0.001

pos

Intolerant

<0.000

pos

<0.000

pos

Fixation

<0.000

pos

0.327

pos

None

<0.000

neg

<0.000

neg

Aspen

<0.000

neg

0.459

pos

Grassland

<0.000

pos

<0.000

neg

pos

0.268

neg

Acceptable Ecotones
Exotic species
Shade Tolerant Groups

Form

Drought Tolerance

Nitrogen fixation

Indicator Species

Dispersal method
None

0.007

Wind

<0.000

pos

0.473

neg

Animal

<0.000

neg

<0.000

neg

Generalist

<0.000

pos

0.330

pos

North and south are analyzed separately and p values in bold are statistically
significant (p<0.05). Slope indicates the change in the variable over the distance
gradient (i.e., for north-facing aspects there is a significant increase in abundance
of exotic species with increasing proximity the ecotone centre).
1

70

DISCUSSION
STRUCTURALLY-DEFINED ECOTONES: CONTRASTING THE BLOCKED AND
GRADIENT APPROACH

Treelines, such as those forming the center of the structurally-defined
ecotones analyzed in this chapter, are conspicuous features of the landscape and
are often assumed to indicate the location of abrupt changes in species
composition and/or diversity (Grytnes et al. 2006). Whereas the results of Chapter
Two clearly indicated that structurally-defined ecotones were not the location of
the most rapid compositional change in understory plants, the results of this
chapter indicate that our understanding of structurally-defined ecotones as sites
of increased plant richness depends upon whether the ecotone was analyzed as a
block or as a gradient. Regardless of aspect, the blocked approach found little
evidence for increased richness, as compared to adjacent belt types, in ecotonal
belts. The gradient approach, in comparison, demonstrated the species richness
declined with increasing distance from the structurally-defined ecotone for both
grassland and forest belts, but only for north-facing transects. This result concurs
with that of Gelhausen et al. (2000) who found a similar decrease in species
diversity with increasing distance from treeline in their aspen stand surveys.
Fundamentally, the decision to adopt a blocked or gradient approach to
analyzing ecotones depends upon whether the entire ecotone is viewed as distinct
from adjacent communities or as an assemblage of individual species distributed
across an ecotonal gradient—a difference of opinion that dates back to the debate
between Gleason and Clements in the first half of the twentieth century (Clements
1916; Gleason 1926). While numerous studies (Walker et al. 2003; Senft 2009;
Hennenberg et al. 2005; Harper & MacDonald 2001; Jules et al. 2010; Kark 2013)
have taken a blocked approach to describing patterns of species richness at edges

71
and ecotones, however some functional groups may respond to environmental
variation as a gradient rather than an abrupt change (Harper & MacDonald,
2001). This “lumping” of belts found at different distances from the structurallydefined ecotones may mask difference between the blocks and may explain why,
in this study, blocked analysis of the ecotones found fewer significant differences
and the gradient approach found more.
The first of the four a priori hypothesis considered in Chapter Two
suggested that increased environmental heterogeneity found in ecotones could
lead to increased species packing, which in turn would be associated with
increased species richness. In Chapter Two, high rates of species composition
change were used as a proxy for increased species packing and found no
correlation with increased species richness. In this chapter, the presence of an
abrupt treeline, would, nearly by definition, imply increased environmental
heterogeneity at the structurally-defined ecotone (Camarero et al. 2006; Peltzer &
Wilson 2006). However, the results of this study, as stated above, indicate support
for this specific hypothesis only when the north-facing ecotones are analyzed with
a gradient approach. In contrast, Camarero et al. (2006) found some evidence in
favour of the impact of environmental heterogeneity on increased species
diversity at a small scale. A study on old growth forest edges found that increased
environmental heterogeneity lead to increased species richness as compared to
forest interiors (Brothers & Spingarn 1992). Kumar et al. (2006) found
environmental heterogeneity influenced native and nonnative species differently
and also varied between spatial scales.
The second hypothesis suggests that ecotones will be species-rich due to
the influx of propagules (spatial mass effect) from adjacent habitats. In this
chapter, both the blocked and gradient approach provided support for this
hypothesis as, in general, the richness and abundance of aspen indicators were

72
higher in ecotones than in grasslands. Likewise, as would be expected with spatial
mass effects, the richness and abundance of grassland indicators were higher in
ecotone belts when compared to forest belts. In a study of altitudinal gradients
Grytnes et al. (2008) found support for mass effects at a finer scale (0.5x0.5 m2
plots), but no evidence when they examined the gradient at a coarser scale (5x5 m2
plots). However, Walker et al. (2003) found little evidence for the impact of spatial
mass effect on ecotone species composition. A study of a large number of transects
found mixed evidence for the influence of mass effects on species composition at
edges (Kunin 1998).
The third hypothesis predicts animal seed dispersal and/or predation as
potential drivers of richness within ecotones. In this chapter, I found evidence
supporting this hypothesis (i.e., higher richness of animal-dispersed species in
ecotones compared to adjacent habitats) only in the north-facing structurallydefined ecotone-grassland comparison. Previously, Jones et al. (2015) working in
the same area of Lac du Bois found that no animal-dispersed species occurred
within the grassland matrix. As many of the animal-dispersed species in this study
are bird-dispersed, the increased richness found at the ecotones could have arisen
as birds used edge trees as perches. North-facing slopes are moister than southfacing ecotones and moisture levels have been shown to affect the occurrence of
animal-dispersed seeds (Herault & Honnay 2007). Likewise, a Belgian study found
the occurrence of animal-dispersed seeds in the seed bank increased as they
moved from the clearings into forest interiors (Devlaeminck et al. 2005).
Interestingly, one study found that the structure of forest edges can influence seed
dispersal through the structure of the stand edge; that is, if the forest edge is
densely vegetated wind dispersed seed interception will be high, however, if the
forest edge is relatively open wind dispersed seed can reach deeper into the forest
(Cadenasso et al. 2003). This could be a factor influencing observed seed dispersal

73
patterns across these aspen-grassland ecotones, where the vegetation density at the
treeline was variable when compared between forest patches (M. Ross, personal
observation). Additionally, although Baker et al. (2011) found no evidence for
ecotone-specific birds in their study, they did find significantly more bird species
within the forest than in an adjacent heathland. This increased bird activity within
the forest could also explain way and increase in animal dispersers was found only
within forest belts.
The final a priori hypothesis suggests that increased ecotone richness might
arise through an influx of exotic species. In this chapter, I did find both increased
richness and abundance of exotic species in north-facing structurally-defined
ecotones as compared to north-facing forested belts. Likewise, Chapter Two
found an increase in richness of exotic species in north-facing, statistically-defined
ecotones, when compared to adjacent forest belts. These results support Risser's
(1995) contention that ecotones allow exotic species invasion, in contrast to the
other studies such as Walker et al. 2003 which failed to find any such evidence.
Lloyd et al. (2000) found no clear pattern of higher exotic species richness within
ecotones and suggested that an increased richness of exotics is not an intrinsic
characteristics of ecotones. In comparison, Stohlgren et al. (1998) argued that
riparian ecotones were particularly susceptible to invasion by exotic species,
furthering the argument that ecotone characteristics differ based on ecological
conditions and generalization about ecotones as a whole are problematic.

COMPARING THE GRADIENT APPROACH WITH PREVIOUS METHODS:
STATISTICALLY-DEFINED ECOTONE RESULTS
Of the different definitional and analytic approaches used in this study,
the results of the gradient analysis of species richness patterns from the center of
the statistically-defined ecotone towards the aspen stands was, perhaps

74
unsurprisingly, most similar to the results found with the structurally-defined
ecotone, gradient approach. It is important, however, to emphasize that these two
approaches are not analyzing the exact data as the structurally-defined and
statistically-defined ecotones rarely overlapped on any given transects. Perhaps
the most surprising result of this study is that overall, a blocked approach
showed more significant differences in the richness of plant functional groups on
south-facing ecotones, whereas the gradient approach showed more significant
differences within north-facing ecotones.
Overall, it is clear that both the method of defining ecotones and the
analytical approach have a significant impact on the nature of the results when
patterns of species richness in ecotones are assessed. Walker et al. (2003) and Senft
(2009) also came to a similar conclusion. Not only does overall significant
difference in species richness alter, but which plant functional group changes in
either richness or abundance also varies with ecotone definition and analytical
approach. Based on this study, there appears to be few universal attributes of
ecotones related to species richness, although the richness and/or abundance of
functional groups such as seed-dispersal methods, shade and drought tolerance
and as well as indicator status were repeatedly found to vary within multiple
analyses. This research went a step further than Walker et al. (2003) and Senft
(2009) in that it explicitly considered the influence of aspect on the patterns of
species richness. This is particularly important as patterns of change in species
richness were often reversed on north- versus south-facing ecotones.
This study makes apparent that using a standardized method is important
to allow comparison across different systems and scales. Furthermore, this study
highlights the importance of not relying on composite response variables such as
species richness but evaluating the response of individual plant functional groups.

75
Future studies in this system could also develop a functional group analysis which
could allow for comparisons of ecotone functional characteristics between flora
and fauna (Garnier & Navas 2012). This comparison may help create a more
holistic understanding of natural systems and their underlying processes.

LITERATURE CITED
Baker J, French K, Whelan RJ. 2011. The edge effect and ecotonal species:
bird communities across a natural edge in Southeastern Australia.
Ecology. 83:3048–3059.
Bogen, J, "Theory and observation in science", The Stanford Encyclopedia of
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<http://plato.stanford.edu/archives/spr2013/entries/science-theoryobservation/>.
Brothers TS, Spingarn A. 1992. Forest fragmentation and alien plant invasion of
Central Indiana old-growth forests. Conservation Biology. 6:91–100.
Cadenasso ML, Pickett STA, Weathers KC, Jones CG. 2003. A framework for a
theory of ecological boundaries. BioScience. 53:750–758.
Callaway R. 1997. Positive interactions in plant communities and the
individualistic- continuum concept. Oecologia. 112:143–149.
Camarero JJ, Gutiérrez E, Fortin MJ. 2006. Spatial patterns of plant richness
across treeline ecotones in the Pyrenees reveal different locations for
richness and tree cover boundaries. Global Ecology and Biogeography.
15:182–191.
Clements F. 1916. Plant succession: an analysis of the development of vegetation.
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Devlaeminck R, Bossuyt B, Hermy M. 2005. Inflow of seeds through the forest
edge: evidence from seed bank and vegetation patterns. Plant Ecology.
176:1–17.
Erdôs L, Zalatnai M, Morschhauser T, Bátori Z, Körmöczi L. 2011. On the terms
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Fortin M, Olson R, Ferson S, Iverson L. 2000. Issues related to the detection of
boundaries. Landscape Ecology. 15:453–466.
Garnier E, Navas M-L. 2012. A trait-based approach to comparative functional
plant ecology: concepts, methods and applications for agroecology. A
review. Agronomy for Sustainable Development. 32:365–399.
Gleason HA. 1926. The individualistic concept of the plant association. Bulletin of
the Torrey Botanical Club. 53:7–26.
Gosz J. 1993. Ecotone hierarchies. Ecological Applications. 3:369–376.
Grytnes J, Heegaard E, Romdal TS. 2008. Can the mass effect explain the midaltitudinal peak in vascular plant species richness? Basic and Applied
Ecology. 9:373–382.
Grytnes JA, Heegaard E, Ihlen PG. 2006. Species richness of vascular plants,
bryophytes, and lichens along an altitudinal gradient in western Norway.
Acta Oecologica. 29:241–246.
Harper K, MacDonald S. 2001. Structure and composition of riparian boreal forest:
new methods for analyzing edge influence. Ecology. 82:649–659.
Hennenberg KJ, Goetze D, Kouamé L, Orthmann B, Klaus JI. 2005. Border and
ecotone detection by vegetation composition along forest-savanna transects
in Ivory Coast. Journal of Vegetation Science. 16:301–310.
Herault B, Honnay O. 2007. Using life-history traits to achieve a functional
classification of habitats. Applied Vegetation Science. 10:73–80.
Jules ES, Carroll AL, Kauffman MJ. 2010. Relationship of climate and growth
of quaking aspen (Populus tremuloides) in Yellowstone National Park.
Aspen Bibliography. Paper 7056:1–26.
Kark S. 2013. Chapter 9: Ecotones and ecological gradients. R. Leemans, editor.
New York: Springer Science and Business Media.
Kumar S, Stohlgren TJ, Chong GW. 2006. Spatial heterogeneity influences native
and nonnative plant species richness. Ecology. 87:3186–3199.
Kunin WE. 1998. Biodiversity at the edge: A test of the importance of spatial “mass
effects” in the Rothamsted Park grass experiments. Proceedings of The
National Academy of Science. 95:207–212.
Lloyd KM, McQueen AAM, Lee BJ, Wilson RCB, Wilson JB, Kelvin M, Amelia
AM, Beatrice J, Robert CB, Bastow J. 2000. Evidence on ecotone concepts
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Vegetation Science. 11:903–910.
Murcia. 1995. Edge effects in fragmented forests implications for conservation.
Trends in Ecology & Evolution. 10:58–62.
Pausas JG, Austin MP. 2001. Patterns of plant species richness in relation to
different environments: An appraisal. Journal of vegetation. 12:153–166.
Peltzer DA, Wilson SD. 2006. Hailstorm damage promotes aspen invasion into
grassland. Canadian Journal of Botany. 84:1142–1147.
Risser PG. 1995. The status of science examining ecotones. BioScience. 45:318–325.
Senft A. 2009. Species diversity patterns at ecotones. Masters Thesis. University of
North Carolina, Chapel Hill, North Carolina.
Stohlgren TJ, Bull KA, Otsuki Y, Villa CA, Lee M. 1998. Riparian zones as havens
for exotic plant species in the central grasslands. Plant Ecology. 138:113–
125.
Walker S, Wilson J, Steel JB, Rapson G, Smith B, King WM, Cottam YH. 2003.
Properties of ecotones: evidence from five ecotones objectively determined
from a coastal vegetation gradient. Journal of Vegetation Science. 14:579–
590.

78

CHAPTER 4 IMPLICATIONS, FUTURE RESEARCH AND
CONCLUSIONS

BROAD CONTEXT
This study contributes to a further understanding of functional group
richness and abundance patterns, as well as the influence of aspect on ecotones in
general and at aspen-grassland ecotones specifically. By using a standardized
approach, the moving window method, this study is directly relatable to other
studies, regardless of the specific system examined. The observed patterns can be
compared to other types of ecotones like riparian edges, mangroves or even animal
boundaries for example. As with any study, choices need to be made regarding site
location, methods and analysis. As this is an observational study, it comes with both
limitations and strengths (Dunne et al. 2004). Short term manipulative studies can
yield poor predictions of long term responses, so it is important to use both
manipulative and natural experiments (Saleska et al. 2002). In the Lac du Bois area
the grassland-aspen ecotones are naturally occurring and are not perfect replicates.
However, this type of observational study does provide baseline data upon which
future manipulative studies could be based.
Using the moving window analysis, one peak in the first ordination score was
used to define the ecotone centres. Many of the transects, however, have multiple
minor peaks. Those transects with multiple similar sized peaks were not used in the
analysis of acceptable transects, however many of the acceptable transects also had
minor, secondary peaks. Further investigation into these secondary peaks may yield
some interesting results. In most cases the secondary peak was within the aspen
stand and there were also in some cases more than one secondary peak. Based on
my understanding of the moving window method, I chose the highest peak to

79
identify the main ecotone (Walker et al. 2003). It is possible, however, that I should
have chosen the one closest to the structural edge (physiognomic change) in order to
better compare like variables. This study looked at ecotone locations relative to
grassland-aspen treeline. I found a few ecotones located within or near the treeline;
but more often they were not associated with the treeline at all, occurring within the
grassland or forested belts. This study contradicts any assumption that peaks in
species richness or species turnover will occur at a visually obvious boundary such
as a treeline. Given ecologists long reliance on visually obvious breaks in vegetation,
the results of this study suggest that managing for biodiversity along ecosystem
gradients may be more complicated than initially assumed.
Choice of analysis within this research followed a standardized approach to
ecotone definition (Walker et al. 2003). Using a standardized approach allows for the
comparison between studies where ecotone types may vary. Non-metric
multidimensional scaling ordination was used with a Bray-Curtis dissimilarity
measure. Many possible measures of dissimilarity can be used, but Bray-Curtis is a
widely used dissimilarity for ecological abundance data (Warton et al. 2001). BrayCurtis can be sensitive to outliers (McCune et al. 2002), and this was addressed in
this research by first removing species with very low abundance (less than 1%)
before running the ordinations. However, by using the raw (as opposed to
relativized abundance data), the Bray-Curtis dissimilarity index also weights
abundant species more heavily than less common species. In the future, it would be
interesting to compare the ordinations obtained with a dissimilarity index that
relativized abundance across all species.
A further factor that needs to be considered is the local topography of the
study site. Although the grasslands in this area are have a rolling topography, they
also have an overall south-facing exposure. Due to this specific geographic feature,
north-facing ecotones tended to occur on the upslope side of the aspen patches. This

80
could have implication for plant functional richness and abundance patterns across
the ecotones, as slope locations may impact soil moisture regimes.
A final consideration for this study involves language used in the definition
of ecotones in general. The lack of increased species richness in this paper found in
statistically defined ecotones contributes to the definition of ecotones as areas of
tension rather than areas of mixing. Van der Maarel (1990) argued that there should
be a distinction in the classification of edge environments as either ecoclines (areas
with typically higher species richness) or ecotones (areas with similar or lesser
species richness). I am inclined to agree with this at least in the broad sense; there is
no simple way to generalize characteristics of ecotones universally. As demonstrated
in this study, the greatest change in species composition was not correlated with the
greatest change in structure. This suggests that boundaries are more subtle than we
might first approximate.

ECOTONES AND CLIMATE CHANGE
Given that the impacts of environmental shifts are expected to show at
ecosystem margins first, ecotones are generally viewed as being at the frontline of
climate change, and (Hampe & Petit 2005). Hebda (2007) specifically predicts that
treeline ecotones will move northward or to higher elevations as climate change
increases environmental pressures. It has been suggested that species in ecotones
may already be adapted to frequent change, which would help to mitigate climate
change impacts (Gayton 2008).
However, one study found that alpine treeline ecotones are slow to
respond to change and are often broken up, rather than advancing as a front
(Noble 1993). Such a treeline ecotone would not be ideal for climate change
monitory as one needs high resiliency and stability within an ecotone in order to
detect potential climate change impacts (Noble 1993). Van der Maarel (1990)

81
cautions that although it might be convenient to think of ecotones as good
predictors of climate change impacts, it is important to understand which features
to measure, which features are being influenced and which are influencing others.
Changing climate also has a strong impact on aspen stands specifically;
many aspen populations are in decline around North America, much of this
attributed to climate change and land use practices (Wooley et al. 2008; Michaelian
et al. 2010; Worrall et al. 2010). This is concerning to researchers because aspen
stands are cited as the second most biodiverse ecosystem in western North
America (Wooley et al. 2008).

MANAGEMENT
Management of ecotones is problematic – due, at least in part, to the lack of
consensus around the definition of ecotone boundaries, study designs, low sample
size and analysis methods (objectively or subjectively defined). “Ecotone” is a very
broad term and is therefore not a useful management unit unless the specific
ecotone type is noted. For example, riparian ecotones are often very dynamic
(Naiman & Décamps 1990) whereas alpine treeline ecotones tend to be more static
and slow to change (Noble 1993). Broad references and generalizations about
ecotones in general should be avoided as no intrinsic properties of ecotones have
been identified (Lloyd et al. 2000; Walker et al. 2003). Adding to this difficulty, most
management decisions do not consider boundaries, but focus solely on the uniform
habitats in isolation (Naiman & Décamps 1990). Overall, within this study, ecotones
were not more species rich than adjacent habitat types. However, aspen forests were
more species rich than grasslands in many cases and the ecotones were generally
found to contain similar species richness as the forest patches. This helps highlight
the importance of aspen stands for increased species richness within the grassland
matrix. Management of grazing may consider the impact on aspen stands rather

82
than just the impact on the grassland. Carlson et al. (2014) found a reduction in
grassland habitat due to changes in land use practices and due to a management
focus on the preservation of forested land. The pattern of species richness differs
somewhat when the gradient approach was considered (species richness decreases
away from edge/ecotone centre) in this study. This serves to support the point that
definition of the ecotone (using a blocked or gradient approach) matters for
management decisions. When monitoring changes for future management decisions,
it is important to consider the approach taken.

FURTHER STUDIES
In future ecotone studies, it would be interesting to examine site specific
functional traits to study how characteristics such as leaf area, plant height and
seed size differ over the ecotones. Functional characteristics used in this paper
were relatively general and gleaned from the literature, and it would be
informative to observe if ecotonal habitats have any effect on the functional traits
of individual species. These site specific traits could tell us more about the impact
of the ecotone on resource acquisition, dispersal and fecundity, for example
(Lavorel et al. 2007).
This research focused on vascular plant species in the grasslands and
forest understory. Non-vascular plant richness and abundance data was not
specifically examined; this would be an interesting project for future work in this
area as these organisms may respond to environmental gradients differently.
Underlying soils and other substrates are invisible factors that impact plant
survival and site preference (McLean 1970; Ryswyk & McLean 1989; Kunin 1998).
Future ecotone research in the Lac Du Bois area should consider the underlying
soil type or even aspen stand age, to observe if these have an impact on the
position, boundaries and characteristics of ecotones. Additionally, it would be

83
informative to investigate grassland-aspen ecotone importance for other species –
insects, rodents or ungulates, for example.

LITERATURE CITED
Carlson BZ, Renaud J, Biron PE, Choler P. 2014. Long-term modeling of the forestgrassland ecotone in the French Alps: Implications for land management
and conservation. Ecological Applications. 24:1213–1225.
Dunne JA, Saleska SR, Fischer ML, Harte J. 2004. Integrating experimental and
gradient methods in ecological climate change research. Concepts and
synthesis. 85:904–916.
Gayton D. 2008. Impacts of climate change on British Columbia’s biodiversity.
Forum for Research and Extension in Natural Resources. 23:1–24.
Hampe A, Petit RJ. 2005. Conserving biodiversity under climate change: the rear
edge matters. Ecology Letters. 8:461–467.
Hebda R. 2007. Ancient and future grasslands. BC Grasslands. Spring:14–16.
Kunin WE. 1998. Biodiversity at the edge: A test of the importance of spatial “mass
effects” in the Rothamsted Park grass experiments. Proceedings of The
National Academy of Science. 95:207–212.
Lavorel S, Díaz S, Cornelissen JHC, Garnier E, Harrison SP, Mcintyre S, Pausas
JG, Catherine NP, Carlos R. 2007. Plant Functional Types: Are We
Getting Any Closer to the Holy Grail? In: Canadell J, Pataki D, Pitelka L,
editors.Terrestrial Ecosystems in a Changing World. Berlin: SpringerVerlag; p. 149– 160.
Lloyd KM, McQueen AAM, Lee BJ, Wilson RCB, Wilson JB, Kelvin M, Amelia
AM, Beatrice J, Robert CB, Bastow J. 2000. Evidence on ecotone concepts
from switch, environmental and anthropogenic ecotones. Journal of
Vegetation Science. 11:903–910.
McCune B, Grace JB, Urban DL. 2002. Analysis of Ecological Communities. MjM
Software Design, Gleneden Beach, Oregon. 300 p.
McLean A. 1970. Plant communities of the Similkameen Valley, British Columbia,
and their relationships to soils. Ecological Monographs. 40:403–424.
Naiman RJ, Décamps H. 1990. Management of aquatic-terrestrial ecotones. Man
and the Biosphere. 4:141 – 169.

84
Noble IANR. 1993. A model of the responses of ecotones to climate change.
Ecological Applications. 3:396–403.
Ryswyk AL Van, McLean A. 1989. Geology and soils of grassland range,
Kamloops, British Columbia. Rangelands. 11:65–67.
Saleska SR, Shaw MR, Fischer ML, Dunne JA, Still CJ, Holman ML, Harte J. 2002.
Plant community composition mediates both large transient decline and
predicted long-term recovery of soil carbon under climate warming. Global
Biogeochemical Cycles. 16:1–14.
Walker S, Wilson J, Steel JB, Rapson G, Smith B, King WM, Cottam YH. 2003.
Properties of ecotones: evidence from five ecotones objectively determined from a
coastal vegetation gradient. Journal of Vegetation Science. 14:579–590.
Warton DI, Wright ST, Wang Y. 2012. Distance-based multivariate analyses
confound location and dispersion effects. Methods in Ecology and Evolution.
3: 89–101.
Van der Maarel E. 1990. Ecotones and ecoclines are different. Journal of Vegetation
Science. 1:135–138.

85

APPENDIX
Table A.1 Results from generalized linear models of all transects comparing canopy
cover, soil moisture, soil pH and non-vascular plant species abundance in
statistically-defined ecotonal belts versus forested or grassland belts, with transect as
a blocking variable and belt type as a categorical variable in each model
(lm=variable~belt.type+transect).1

Variable

North-facing Ecotone
Forest-Ecotone
Grassland-Ecotone
∆ in
p
∆ in
p value
intercept
intercept
value

South-facing Ecotone
Forest-Ecotone
Grassland-Ecotone
∆ in
∆ in
p value
p value
intercept
intercept

Canopy
cover
Tree
Intermediate
Shrub
Soil
moisture
Soil pH
Nonvascular
plants

neg
neg
pos

0.020
0.326
0.196

pos
pos
pos

0.027
0.148
0.226

neg
neg
neg

0.002
0.096
0.279

pos
pos
pos

0.089
0.737
0.856

pos
neg

0.897
0.142

neg
neg

0.064
0.533

pos
neg

0.897
0.654

neg
neg

0.064
0.856

neg

0.299

neg

0.133

pos

0.319

neg

0.169

Change in intercept indicates the direction of change in the variable from ecotonal to adjacent belts
(i.e., at north-facing aspects there is significant less tree canopy cover in ecotone belts than forest
belts). North- and south-facing ecotones are analyzed separately and p values in bold are statistically
significant (p<0.05).
1

86
Table A.2 Results from generalized linear models, of all transects, comparing richness
of functional groups in statistically defined ecotone belts versus forested and grassland
belts, with transect as a blocking variable and belt type as a categorical variable in each
model (lm=Variable~Belt.type+Transect).1

Variable
Mean species
richness
Total species
richness
Rare species
Shade tolerance
Group
Tolerant
Intermediate
Intolerant
Form
Forb
Graminoid
Shrub
Tree sapling
Dispersal
None
Wind
Animal
Generalist
Status
Native
Exotic
Drought
tolerance
Tolerant
Intermediate
Intolerant
Indicator species
Aspen stands
Grassland

North-facing Ecotones
Forest-Ecotone
Grassland-Ecotone
∆ in
∆ in
p value
p value
intercept
intercept

South-facing Ecotones
Forest-Ecotone
Grassland-Ecotone
∆ in
∆ in
p value
p value
intercept
intercept

neg

0.700

pos

0.155

pos

0.291

pos

0.021

neg
pos

0.742
0.412

pos
neg

0.338
0.308

pos
pos

0.133
0.346

neg
neg

0.962
0.061

neg
pos
pos

0.970
0.828
<0.000

pos
pos
pos

0.536
0.595
0.063

neg
pos
pos

0.407
0.224
<0.000

neg
pos
neg

0.956
0.590
0.028

pos
pos
pos
pos

0.092
0.023
0.070
0.031

pos
pos
pos
pos

0.832
0.189
0.013
0.577

pos
pos
pos
pos

0.074
0.002
0.013
0.089

neg
neg
pos
neg

0.089
0.238
0.018
0.686

neg
pos
neg
pos

0.643
0.010
0.584
0.006

pos
neg
pos
neg

0.585
0.741
0.302
0.049

pos
pos
neg
pos

0.250
0.007
0.084
0.005

neg
neg
pos
neg

0.848
0.062
0.731
0.255

pos
pos

0.195
0.004

pos
neg

0.863
0.987

pos
pos

0.019
0.521

neg
neg

0.654
0.049

pos
pos
pos

0.301
0.197
0.047

pos
neg
neg

0.305
0.178
0.814

pos
pos
neg

0.360
0.029
0.025

pos
neg
neg

0.606
0.454
0.063

neg
pos

0.073
0.018

pos
neg

0.362
0.074

neg
pos

0.001
<0.000

pos
neg

0.334
0.244

Change in intercept indicates the direction of change in the variable in ecotonal belts compared to
either the forested or grassland belts (i.e., at south-facing aspects, there is a significantly greater mean
species richness in ecotone belts than grassland belts). North and south transects are analyzed
separately and p values in bold are statistically significant (p<0.05).
1

87
Table A.3 Results from generalized linear models, of all transects, comparing
abundance of functional groups in statistically defined ecotone belts versus forested
and grassland belts, with transect as a blocking variable and belt type as a categorical
variable and belt type as a categorical variable in each model
(lm=variable~belt.type+transect).1

Variable
Rare species
Shade
tolerance
Tolerant
Intermediate
Intolerant
Form
Forb
Graminoid
Shrub
Tree sapling
Dispersal
None
Wind
Animal
Generalist
Status
Native
Exotic
Drought
tolerance
Tolerant
Intermediate
Intolerant
Indicator
species
Aspen
stands
Grassland

North-facing Ecotones
Forest-Ecotone
Grassland-Ecotone
∆ in
∆ in
p value
p value
intercept
intercept
pos
0.528
pos
0.744

South-facing Ecotones
Forest-Ecotone
Grassland-Ecotone
∆ in
∆ in
p value
p value
intercept
intercept
pos
0.050
pos
0.004

neg
pos
pos

0.276
0.585
0.110

pos
pos
neg

0.152
0.053
0.006

neg
neg
pos

0.067
0.514
0.826

neg
pos
neg

0.970
0.241
0.396

pos
pos
neg
pos

0.641
0.100
0.015
0.107

pos
neg
pos
neg

0.286
0.048
0.274
0.132

pos
pos
neg
pos

0.842
0.024
0.001
0.287

pos
neg
pos
neg

0.684
0.112
0.218
0.067

neg
pos
neg
pos

0.671
0.100
0.140
0.161

pos
pos
pos
neg

0.102
0.099
0.681
0.026

neg
pos
neg
pos

0.815
0.532
0.002
0.035

pos
neg
pos
neg

0.270
0.466
0.923
0.269

neg
pos

0.495
0.219

neg
pos

0.066
0.393

neg
neg

0.613
0.890

pos
neg

0.810
0.800

neg
neg
pos

0.812
0.233
0.073

neg
neg
neg

0.507
0.009
0.728

neg
pos
pos

0.864
0.737
0.233

pos
neg
pos

0.459
0.379
0.881

neg

0.073

pos

0.362

neg

0.001

pos

0.334

pos

0.018

neg

0.074

pos

<0.000

neg

0.244

Change in intercept indicates the direction of change in the variable in ecotonal belts compared to
either the forested or grassland belts (i.e., at north-facing aspects, there is a significantly less
abundance of intermediately shade tolerant species in grassland belts than in ecotonal belts). North
and are analyzed separately and p values in bold are statistically significant.
1

88
Table A.4 Results from generalized linear models comparing canopy cover, soil moisture
and soil pH in structurally-defined ecotone belts versus forested or grassland belts, with
transect as a blocking variable and belt type as a categorical variable in each model
(lm=variable~belt.type+transect). 1

Variable
Canopy cover
Tree
Intermediate
Shrub
Soil moisture
Soil pH

North-facing Ecotones
Forest-Ecotone
Grassland-Ecotone
∆ in
∆ in
p value
p value
intercept
intercept
pos
neg
pos
pos
neg

0.194
0.043
0.880
0.896
0.056

pos
pos
neg
neg
neg

<0.000
0.897
0.661
0.050
0.555

South-facing Ecotones
Forest-Ecotone
Grassland-Ecotone
∆ in
∆ in
p value
p value
intercept
intercept
neg
pos
neg
pos
pos

0.069
0.653
0.820
0.898
0.831

pos
pos
pos
pos
pos

<0.000
0.004
0.422
0.627
0.266

Change in intercept indicates the direction of change in the variable between belt types (i.e., at northfacing aspects there is significant greater tree canopy cover in ecotonal belts than grassland belts). North
and south transects are analyzed separately and p values in bold are statistically significant (p<0.05).
1

89
Table A.5 Results from linear models, from all transects, comparing functional group
richness in structurally-defined ecotone belts versus forested and grassland belts, with
transect as a blocking variable and belt type as a categorical variable in each model
(lm=Variable~Belt.type+Transect).1

Variable

North-facing Ecotones
Forest-Ecotone
Grassland-Ecotone
∆ in
∆ in
p value
p value
intercept
intercept

Mean species
Richness
pos
Total species
Richness
neg
Rare species
pos
Shade Tolerant Groups
Tolerant
pos
Intermediate
pos
Intolerant
pos
Growth Form Group
Forb
pos
Graminoid
pos
Shrub
neg
Tree sapling
pos
Dispersal Method Group
None
pos
Wind
pos
Animal
pos
Generalist
pos
Status Groups
Native
pos
Exotic
pos
Drought Tolerant Groups
Tolerant
pos
Intermediate
pos
Intolerant
pos
Indicator Groups
Aspen stands
pos
Grassland
pos

South-facing Ecotones
Forest-Ecotone
Grassland-Ecotone
∆ in
p
∆ in
p
intercept
intercept
value
value

0.062

neg

0.756

pos

0.526

neg

0.157

0.145
0.079

neg
neg

0.103
0.326

neg
pos

0.033
0.194

neg
neg

0.087
0.076

0.564
0.162
<0.000

pos
pos
neg

0.221
0.701
<0.000

neg
neg
pos

0.280
0.217
0.001

neg
pos
neg

0.900
0.930
0.001

0.011
<0.000
0.023
0.018

neg
neg
pos
neg

0.868
0.383
0.210
0.282

pos
pos
neg
pos

0.488
0.020
0.017
0.505

neg
neg
pos
neg

0.020
0.061
0.011
0.059

0.182
0.011
0.319
0.002

pos
neg
pos
neg

0.043
0.022
<0.000
<0.000

neg
pos
neg
pos

0.447
0.007
0.064
0.007

neg
neg
pos
neg

0.007
0.003
0.934
0.024

0.011
0.001

neg
pos

0.736
0.584

pos
pos

0.265
0.478

neg
neg

0.062
0.137

0.134
0.003
0.114

pos
neg
neg

0.860
0.834
0.891

neg
pos
neg

0.395
0.054
0.068

neg
neg
neg

0.314
0.301
0.234

0.799
0.021

pos
neg

0.004
0.010

neg
pos

0.008
0.005

pos
neg

0.346
0.006

North and are analyzed separately and p values in bold are statistically significant (p<0.05). Change
in intercept indicates the direction of change in the variable in ecotonal belts compared to either the
forested or grassland belts (i.e., at south-facing aspects total species richness is significantly lower in
ecotonal belts than in forest belts).
1

90
Table A.6 Results from linear models comparing abundance of functional groups in
structurally-defined ecotone belts versus forested and grassland belts, with transect as a
blocking variable and belt type as a categorical variable in each (lm=
variable~belt.type+transect).1
North-facing Ecotones
Forest-Ecotone
Grassland-Ecotone
∆ in
∆ in
Variable
p value
p value
intercept
intercept
Rare species
pos
0.740
neg
0.017
Shade Tolerant Groups
0.052
Tolerant
neg
pos
0.863
Intermediate
pos
0.602
pos
0.039
0.005
Intolerant
pos
0.576
neg
Growth Form Groups
Forb
pos
0.842
pos
0.684
Graminoid
pos
0.024
neg
0.112
0.001
Shrub
neg
pos
0.218
Tree sapling
pos
0.287
pos
0.067
Dispersal Method Groups
None
neg
0.788
pos
0.001
0.050
Wind
pos
0.177
pos
Animal
neg
0.070
pos
0.201
Generalist
pos
0.037
neg
<0.000
Status Groups
Native
neg
0.047
neg
0.011
Exotic
pos
0.054
pos
0.117
Drought Tolerant Groups
Tolerant
pos
0.251
pos
0.924
0.017
Intermediate
neg
0.710
neg
Intolerant
pos
0.221
pos
0.130
Indicator Groups
Aspen stands
Grassland

pos
pos

0.893
0.009

pos
neg

0.005
0.046

South-facing Ecotones
Forest-Ecotone
Grassland-Ecotone
∆ in
p
∆ in
p
intercept
intercept
value
value
pos
0.062
pos
0.002
neg
neg
pos

0.313
0.048
0.704

pos
pos
neg

0.327
0.959
0.615

neg
pos
neg
pos

0.379
0.022
0.005
0.636

neg
neg
pos
neg

0.399
0.926
0.421
0.037

neg
pos
neg
pos

0.010
0.531
0.006
0.015

pos
pos
pos
pos

0.965
0.072
0.442
0.984

neg
pos

0.218
0.780

neg
pos

0.522
0.580

pos
pos
pos

0.736
0.734
0.269

pos
neg
neg

0.121
0.285
0.849

neg
pos

<0.000

pos
neg

0.464
0.010

0.001

North and south are analyzed separately and p values in bold are statistically significant (p<0.05).
Change in intercept indicates the direction of change in the variable in ecotonal belts compared to
either the forested or grassland belts (i.e., at north-facing aspects rare species abundance is
significantly lower in ecotone belts than in grassland belts).
1

91
Table A.7 Summaries of generalized linear models comparing plant functional group
richness for forested belts with increasing distance from the statistically-defined
ecotone centre, with distance included as a continuous variable. lm=variable~distance
from statistically-defined ecotone centre.1
North-facing Ecotone

South-facing Ecotones

Variable

p value

slope

p value

slope

Mean Species Richness

0.468

pos

0.001

pos

Exotic Species
Shade Tolerant Groups

<0.000

pos

0.439

neg

Tolerant

0.016

pos

0.430

neg

Intermediate

0.002

pos

0.167

neg

Intolerant

<0.000

pos

<0.000

pos

Forb
Graminoid
Shrub
Tree sapling
Drought Tolerant Groups

<0.000

pos

<0.000

pos

<0.000
0.001
0.020

pos
neg
pos

<0.000
0.002
<0.000

pos
neg
pos

Tolerant

<0.000

pos

<0.000

pos

Intermediate

<0.000
0.001

pos
pos

<0.000
<0.000

pos
neg

0.051

pos

0. 892

pos

0.136

neg

<0.000

neg

Aspen
Grassland
Dispersal Method Groups

<0.000

neg

<0.000

neg

<0.000

pos

<0.000

pos

None
Wind
Animal
Generalist

0.227

pos

0.101

neg

0.246
<0.000
<0.000

pos
pos
pos

0.050
<0.000
<0.000

pos
pos
pos

Growth Form Groups

Intolerant

Nitrogen Fixation Groups
Fixation
None
Indicator Species Groups

North and south are analyzed separately and p values in bold are statistically
significant (p<0.05). Slope indicates the change in the variable over the distance
gradient (i.e., at south-facing aspects there is a significant increase in mean
species richness with increasing proximity to the ecotone centre).
1

92
Table A.8 Summaries of generalized linear models comparing plant functional group
abundance for forested belts with increasing distance from the statistically-defined
ecotone centre, with distance included as a continuous variable. lm=variable~distance
from statistically-defined ecotone centre.1
North-facing Ecotone

South-facing Ecotones

p value
0.114

slope
pos

p value
0.734

slope
neg

0.592

neg

0.014

neg

0.001
0.015

pos
neg

0.003
0.096

neg
neg

Forb
Graminoid
Shrub
Tree sapling
Drought Tolerant Groups
Tolerant
Intermediate

0.323

neg

0.312

pos

0.263
0.060
0.247

neg
neg
pos

0.499
0.972
0.058

pos
pos
neg

0.001

pos

0.004

neg

0.692

pos

0.034

pos

Intolerant
Nitrogen Fixation Groups
Fixation
None
Indicator Species Groups
Aspen
Grassland

<0.000

pos

0.001

pos

0.446

pos

0.812

pos

0.198

neg

<0.000

neg

<0.000

neg

<0.000

neg

<0.000

pos

<0.000

pos

Variable
Exotic Species
Shade Tolerant Groups
Tolerant
Intermediate
Intolerant
Growth Form Groups

Dispersal Method Groups
None
0.005
pos
0.002
neg
Wind
<0.000
pos
0.014
pos
Animal
<0.000
neg
<0.000
neg
Generalist
<0.000
pos
0.027
pos
1North and south are analyzed separately and p values in bold are statistically
significant (p<0.05). Slope indicates the change in the variable over the distance
gradient (i.e., at north-facing aspects there is a significant increase in abundance
of intermediate shade tolerant species with increasing proximity to the ecotone
centre).

93
Table A.9 Summaries of generalized linear models comparing plant functional group
richness for both forested and grassland transects with increasing distance from the
structural ecotone (treeline), with distance included as a continuous variable.
lm=variable~distance from treeline.1
North-facing Ecotone

South-facing Ecotones

p value

slope

p value

slope

Grassland

0.053

pos

0.026

neg

Forested
Exotic species

<0.000

pos

0.246

pos

Grassland

0.817

pos

0.035

neg

Forested
Shade Tolerant Groups
Grassland
Tolerant
Intermediate
Intolerant

<0.000

pos

0.001

pos

0.248

pos

0.221

pos

0.003
0.001

pos
pos

0.701
<0.000

pos
neg

Tolerant

0.044

neg

0.002

neg

Intermediate
Intolerant
Growth Form Groups

0.182
<0.000

pos
pos

0.027
<0.000

neg
pos

Forb
Graminoid
Shrub

0.184
0.032
<0.000

pos
neg
pos

0.002
0.255
0.002

neg
neg
pos

Tree sapling

0.416

neg

0.100

neg

<0.000
<0.000
<0.000
0.029

pos
pos
neg
pos

0.169
<0.000
0.005
0.332

neg
pos
neg
pos

0.008
0.060
<0.000

neg
neg
pos

0.001
0.648
0.059

neg
neg
neg

Variable
Mean Species richness

Forested

Grassland

Forested
Forb
Graminoid
Shrub
Tree sapling
Drought Tolerant Groups
Grassland
Tolerant
Intermediate
Intolerant
Forested

94
Tolerant

<0.000

pos

0.169

pos

Intermediate
Intolerant
Nitrogen Fixation Groups

<0.000
0.251

pos
neg

0.000
0.243

pos
neg

Fixation
None

0.003
0.991

pos
neg

0.062
0.003

neg
neg

Fixation

<0.000

pos

<0.000

neg

None

0.002

pos

0.003

pos

Aspen

<0.000

pos

0.277

pos

Grassland

<0.000

neg

0.013

neg

Aspen

0.723

pos

<0.000

neg

Grassland

<0.000

pos

<0.000

pos

None

0.043

neg

0.007

pos

Wind

0.022

pos

0.003

pos

Animal

<0.000

neg

0.933

neg

Generalist

<0.000

pos

0.024

pos

None

0.013

neg

0.318

pos

Wind

<0.000

neg

0.023

neg

Animal

0.253

pos

<0.000

pos

Generalist

<0.000

neg

<0.000

neg

Grassland

Forested

Indicator Species Groups
Grassland

Forested

Dispersal Method Groups
Grassland

Forested

North and south are analyzed separately and p values in bold are statistically
significant (<0.05). Slope indicates the change in the variable over the distance
gradient (i.e., at north-facing grasslands there is a significant increase in mean species
richness with increasing proximity to the ecotone centre).
1

95
Table A.10 Summaries of generalized linear models comparing abundance of plant
functional groups for both forested and grassland transects along a distance gradient
from the structurally-defined ecotone (treeline). lm=variable~distance from treeline. 1
North-facing Ecotone

South-facing Ecotones

p value

slope

p value

slope

0.001
0.073

pos
pos

0.927
0.002

neg
pos

Tolerant

0.010

pos

0.011

pos

Intermediate
Intolerant

<0.000
<0.000

pos
neg

0.026
0.091

neg
neg

<0.000
0.058
0.802

neg
pos
neg

0.586
<0.000
0.622

pos
neg
pos

Forb
Graminoid
Shrub
Tree sapling

0.002
<0.000
0.002
0.521

pos
neg
pos
neg

0.867
0.808
0.017
0.191

neg
pos
pos
neg

Forb

0.296

neg

<0.000

neg

Graminoid
Shrub
Tree sapling
Drought Tolerant Groups

0.163
0.050
0.176

pos
neg
pos

<0.000
<0.000
0.668

pos
neg
pos

Tolerant
Intermediate

0.151
0.003

pos
neg

<0.000
<0.000

pos
neg

Intolerant

0.410

pos

0.052

pos

Tolerant
Intermediate
Intolerant
Nitrogen Fixation Groups

<0.000
0.298
0.086

pos
neg
pos

<0.000
0.898
0.052

pos
neg
pos

Fixation

0.114

pos

0.390

pos

None

<0.000

neg

0.716

pos

Variable
Exotic species
Grassland
Forest
Shade Tolerant Groups
Grassland

Forested
Tolerant
Intermediate
Intolerant
Growth Form Groups
Grassland

Forested

Grassland

Forested

Grassland

Forested

96
Fixation
None

0.034
0.012

Aspen

<0.000

pos

0.001

pos

Grassland

<0.000

neg

<0.000

neg

Aspen

<0.000

neg

<0.000

neg

Grassland

<0.000

pos

0.060

pos

None

0.001

neg

0.965

neg

Wind

0.050

neg

0.072

neg

Animal

0.201

neg

0.442

pos

Generalist

<0.000

pos

0.984

pos

None

0.930

pos

0.930

neg

Wind

0.281

neg

0.281

pos

Animal

<0.000

pos

<0.000

neg

pos
neg

<0.000
0.228

neg
neg

Indicator Species Groups
Grassland

Forested

Dispersal method Groups
Grassland

Forested

Generalist

<0.000
neg
<0.000
pos
North and south are analyzed separately and p values in bold are statistically
significant (p<0.05). Slope indicates the change in the variable over the distance gradient
(i.e., at north-facing aspects there is a significant increase in abundance of exotic species
with increasing proximity to the ecotone centre into the grassland).
1

97
Table A.11. Species identified in this study and functional groupings.
Scientific names

Status

Growth
form

Shade
tolerance

Seed
distribution

Nitrogen
fixation

Drought
tolerance

Indicator

Acer glabrum
Achillea
millefolium
Achnatherum
occidentale
Achnatherum
richardsonii

native

shrub

intermediate

wind

none

intermediate

unkn

native

forb

tolerant

wind

none

intermediate

grassland

native

graminoid

intermediate

wind/animal

none

tolerant

grassland

native

graminoid

intermediate

wind/animal

none

unkn

grassland

Agoseris glauca
Agoseris
grandiflora

native

forb

intolerant

wind

none

intermediate

none

native

forb

intolerant

wind

none

intermediate

none

Agrostis scabra

native

graminoid

intolerant

none

none

intolerant

unkn

Allium cernuum
Allium geyeri var.
Tenerum
Alnus incana
subsp. tenuifolia
Alyssum
alyssoides
Amelanchier
alnifolia
Anemone
multifida var.
multifida
Antennaria
microphylla

native

forb

intermediate

none

none

intermediate

none

native

forb

unkn

none

none

unkn

none

native

forb

intermediate

animal

intermediate

intolerant

unkn

exotic

forb

unkn

none

none

unkn

unkn

native

forb

intermediate

animal

none

intolerant

aspen

native

forb

intermediate

wind

none

intermediate

none

native

forb

intolerant

wind

none

intermediate

grassland

Arabis holboellii

native

forb

intermediate

wind

none

intermediate

none

Arctium minus
Arenaria
serpyllifolia

exotic

forb

unkn

animal

none

unkn

unkn

exotic

forb

unkn

none

none

unkn

none

Arnica fulgens
Artemisia
dracunculus
Astragalus
collinus

native

forb

tolerant

wind

none

intolerant

none

native

forb

intermediate

wind

none

tolerant

unkn

native

forb

intolerant

animal

none

unkn

none

Astragalus miser
Balsamorhiza
sagittata

native

forb

intolerant

animal

none

unkn

unkn

native

forb

intermediate

wind

none

tolerant

none

Bromus ciliatus

native

graminoid

tolerant

wind

none

intolerant

unkn

Bromus inermis
Bromus
pumpellianus

exotic

graminoid

intolerant

wind/animal

none

intermediate

none

native

graminoid

unkn

none

none

unkn

unkn

exotic

graminoid

intolerant

wind/animal

none

tolerant

none

native

graminoid

tolerant

wind

none

intolerant

none

native

forb

intolerant

none

none

tolerant

grassland

Bromus tectorum
Calamagrostis
rubescens
Calochortus
macrocarpus

98
Camelina
microcarpa
Campanula
rotundifolia

exotic

forb

unkn

none

none

unkn

none

native

forb

intolerant

wind

none

tolerant

none

Carex aurea

native

forb

intermediate

none

none

intolerant

none

Carex disperma

native

forb

intermediate

wind

none

intolerant

none

Carex petasata
Castilleja
thompsonii

native

graminoid

unkn

none

none

unkn

none

native

forb

intolerant

none

none

intermediate

none

Centaurea stoebe

exotic

forb

intolerant

wind

none

tolerant

unkn

Cerastium arvense
Chenopodium
album
Chimaphila
umbellata

native

forb

intermediate

animal

none

tolerant

grassland

exotic

forb

intolerant

none

none

intermediate

none

native

forb

tolerant

none

none

intermediate

unkn

Cichorium intybus
Collinsia
parviflora

exotic

forb

intolerant

animal

none

intermediate

none

native

forb

tolerant

none

none

intolerant

none

Collomia linearis
Comandra
umbellata
Conyza
canadensis
Crataegus
monogyna

native

forb

intolerant

animal

none

tolerant

grassland

native

forb

intolerant

animal

none

tolerant

grassland

exotic

forb

intolerant

wind

none

intolerant

unkn

exotic

tree

intolerant

animal

none

tolerant

unkn

Crepis atribarba

native

forb

intermediate

wind

none

intermediate

none

Crepis tectorum
Cynoglossum
officinale
Dactylis
glomerata
Danthonia
intermedia
Delphinium
nutallianum
Descurainia
sophia

exotic

forb

intolerant

wind

none

intermediate

unkn

exotic

forb

intolerant

animal

none

unkn

none

exotic

graminoid

tolerant

animal

none

intermediate

none

native

graminoid

intermediate

wind/animal

none

intermediate

unkn

native

forb

tolerant

none

none

tolerant

none

exotic

forb

intolerant

animal

none

intermediate

none

Elymus glaucus

native

graminoid

tolerant

none

none

tolerant

aspen

Elymus repens
Epilobium
angustifolium
Eremogone
capillaris var.
americana
Erigeron
corymbosus
Erigeron filifolius
var. filifolius
Erigeron
flagellaris

exotic

graminoid

intolerant

none

none

intolerant

none

native

forb

tolerant

wind

none

intermediate

unkn

native

forb

tolerant

none

none

tolerant

unkn

native

forb

tolerant

wind

none

intermediate

none

native

forb

intolerant

wind

none

tolerant

none

native

forb

unkn

wind

none

unkn

none

99
Erigeron linearis
Erigeron pumilus
var. Intermedius
Eriogonum
heracleoides

native

forb

intolerant

wind

none

tolerant

unkn

native

forb

unkn

wind

none

unkn

unkn

native

forb

intolerant

wind

none

unkn

grassland

Eurybia conspicua

native

forb

unkn

wind

none

unkn

none

Festuca campestris
Fragaria
virginiana

native

graminoid

intolerant

wind/animal

none

intermediate

grassland

native

forb

tolerant

animal

none

intolerant

aspen

Fritillaria affinis

native

forb

intermediate

wind

none

unkn

unkn

Fritillaria pudica
Gaillardia
aristata

native

forb

intermediate

wind

none

intermediate

grassland

native

forb

intolerant

wind

none

intermediate

none

Galium boreale
Gentianella
amarella
Geranium
viscosissimum

native

forb

intermediate

animal

none

intermediate

aspen

native

forb

intermediate

wind

none

unkn

none

native

forb

tolerant

none

none

intolerant

none

Geum triflorum
Hesperostipa
comata
Heuchera
cylindrica

native

forb

intermediate

wind

none

tolerant

none

native

graminoid

intolerant

wind/animal

none

tolerant

none

native

forb

intermediate

none

none

tolerant

none

Juncus balticus
Juniperus
communis
Juniperus
scopulorum
Koeleria
macrantha
Lathyrus
nevadensis
Lathyrus
ochroleucus
Lilium
columbianum

native

graminoid

tolerant

wind/animal

none

intermediate

grassland

native

shrub

intolerant

animal

none

tolerant

none

native

shrub

intolerant

animal

none

tolerant

none

native

graminoid

tolerant

none

none

tolerant

unkn

native

forb

intermediate

none

none

unkn

unkn

native

forb

intermediate

none

none

unkn

aspen

native

forb

intermediate

wind

none

unkn

none

Linnaea borealis
Lithospermum
ruderale
Lomatium
dissectum
Lomatium
macrocarpum
Lomatium
triternatum

native

forb

tolerant

none

none

unkn

none

native

forb

intolerant

none

none

intermediate

grassland

native

forb

intermediate

wind

none

tolerant

none

native

forb

intolerant

wind

none

tolerant

none

native

forb

intermediate

wind

none

intolerant

unkn

Lotus denticulatus
Mahonia
aquifolium
Maianthemum
racemosum

native

forb

intolerant

none

none

unkn

grassland

native

shrub

tolerant

animal

none

tolerant

aspen

native

forb

tolerant

animal

none

unkn

none

Maianthemum

native

forb

tolerant

animal

none

unkn

aspen

100
stellatum

Medicago lupulina

exotic

forb

intolerant

animal

intermediate

intolerant

none

Medicago sativa

exotic

forb

intolerant

animal

tolerant

tolerant

none

Melilotus alba
Moehringia
lateriflora
Muhlenbergia
richardsonis

exotic

forb

intolerant

wind/animal

intermediate

tolerant

none

native

forb

tolerant

animal

none

unkn

aspen

native

graminoid

intolerant

none

none

intolerant

none

exotic

forb

intolerant

animal

none

unkn

grassland

native

forb

intolerant

none

none

tolerant

none

native

forb

intermediate

animal

none

unkn

aspen

native

forb

intolerant

none

none

unkn

grassland

native

forb

intolerant

wind/animal

none

intolerant

unkn

Phacelia linearis

native

forb

intermediate

none

none

unkn

unkn

Phleum pratense
Piperia
unalascensis

native

graminoid

intermediate

wind/animal

none

intolerant

none

native

forb

tolerant

wind

none

unkn

unkn

Poa compressa

exotic

graminoid

tolerant

wind/animal

none

intermediate

unkn

Poa pratensis

exotic

graminoid

intolerant

wind/animal

none

unkn

none

Poa secunda
Polygonum
douglasii
Populus
tremuloides
Potentilla
glandulosa

native

graminoid

intermediate

wind/animal

none

tolerant

grassland

native

forb

intolerant

wind

none

unkn

grassland

native

tree

intolerant

wind

none

intolerant

aspen

native

forb

unkn

none

none

unkn

none

Potentilla gracilis
Prosartes
trachycarpa

native

forb

intolerant

none

none

intermediate

none

native

forb

tolerant

animal

none

unkn

none

Prunus virginiana
Pseudoroegneria
spicata
Pseudotsuga
menziesii

native

shrub

intolerant

animal

none

intermediate

none

native

graminoid

intolerant

wind/animal

none

tolerant

grassland

native

tree

intermediate

wind

none

intolerant

none

Rhinanthus minor

native

forb

intolerant

wind

none

unkn

grassland

Ribes lacustre

native

shrub

tolerant

animal

none

intolerant

none

Rosa acicularis

native

shrub

tolerant

animal

none

intolerant

none

Silene menziesii
Sisyrinchium
idahoense

native

forb

intermediate

wind

none

unkn

aspen

native

forb

tolerant

none

none

intolerant

none

Solidago simplex

native

forb

tolerant

wind

none

unkn

none

Myosotis stricta
Orthocarpus
luteus
Osmorhiza
berteroi
Penstemon
procerus
Perideridia
gairdneri

101
Sonchus arvensis

exotic

forb

intolerant

wind

none

unkn

none

Spartina gracilis

native

graminoid

intolerant

wind

none

intermediate

none

Spiraea betulifolia
Spiranthes
romanzoffiana
Sporobolus
cryptandrus
Streptopus
lanceolatus
Symphoricarpos
albus
Symphyotrichum
ericoides var.
pansum
Symphyotrichum
foliaceum
Symphyotrichum
subspicatum
Taraxacum
officinale
Thalictrum
occidentale
Tragopogon
dubius

native

shrub

tolerant

wind/animal

none

intolerant

unkn

native

forb

intermediate

wind

none

intolerant

unkn

native

graminoid

intolerant

wind

none

tolerant

unkn

native

forb

tolerant

animal

none

unkn

unkn

native

shrub

intolerant

animal

none

tolerant

aspen

native

forb

intermediate

wind

none

unkn

unkn

native

forb

intermediate

wind

none

unkn

unkn

native

forb

intermediate

wind

none

intolerant

unkn

exotic

forb

intermediate

wind

none

intermediate

aspen

native

forb

intermediate

wind

none

unkn

unkn

exotic

forb

intolerant

wind

none

tolerant

grassland

Trifolium pratense

exotic

forb

intermediate

animal

intermediate

unkn

none

Trifolium repens
Verbascum
thapsus

exotic

forb

intermediate

animal

tolerant

unkn

unkn

exotic

forb

intermediate

none

none

unkn

none

Vicia americana

native

forb

intermediate

none

intolerant

tolerant

aspen

Viola adunca

native

forb

intolerant

animal

none

intolerant

none

Viola canadensis

native

forb

tolerant

animal

none

intolerant

none

Vulpia octoflora
Zigadenus
venenosus

native

graminoid

intolerant

wind

none

unkn

unkn

native

forb

intolerant

none

none

unkn

grassland