road impact area - capstone thesis
TRANSCRIPT
Running Head: Road Impact Area 1
Road Impact Area:
Ecological Effects of Road Proximity
Graham Pritchard
9/21/2014
LIB 495 Capstone Project
Mentor: Brenda Moore
Thomas Edison State College
Running Head: Road Impact Area 2
Table of Contents
Chapter 1: Introduction p#4
Chapter 2: Literature Review p#8
Chapter 3: Methodology p#11
Chapter 4: Results p#14
Chapter 5: Summary and Discussion p#19
References p#27
List of tables and figures
Table 1: Species populations for experimental site p#15
Table 2: Species populations for control site P#16
Figure 1:Figure 1:Dominant species and total populations experimental p#17
Figure 2:Figure 1:Dominant species and total populations control p#18
Figure 3:Simpson's Index for experimental site p#18
Figure 4:Simpson's index for control site p#19
Figure 5:Number of Species by distance from control line p#23
Figure 6:Number of Species by distance from road p#23
Figure 7: Dominance vs. Total number of trees p#25
Figure 8:Tree density and dominance between sites p#26
Abstract
Running Head: Road Impact Area 3
While roads as a whole tend to be a major encroachment on ecosystems, changes as found
by some researchers can be easily missed amid the effects of succession, and resource
availability. Distribution of tree species near a roadway were investigate using transects
parallel and perpendicular to a roadway. Peak specie diversity was highest closest to the
road, but quickly dropped off, and did not surpass the initial figure despite a slight upward
trend out to 50m. This trend however was not strong enough to reject a null hypothesis that
diversity would remain average at each distance. Fewer trees were found when data was
collected on transects perpendicular to the the road. However, the highest recorded total was
at 50m parallel to the road at the experimental site and there was no clear decrease along the
gradient. Although the average number of species per transect only changed slightly except
between 10-20m, several species were only found in a smaller range of distances. Dominant
species seem less susceptible to the stresses of road proximity.
Chapter 1: Introduction
This is an ecological study of a temperate forest ecosystem encroached upon by
roadways designed for motor vehicle traffic. Field surveys were conducted to examine the
relationship between distance from roadways and the population of key endemic a invasive
Running Head: Road Impact Area 4
species. This data can be used in conjunction with other collected data to form a more
complete understanding of how human use and development of land effects temperate forest
ecosystems, and by extension other ecosystems. The background, purpose, professional
significance, and methodology of this study are further discussed in this chapter.
Background
Roadways are known stressors to wildlife. Some mechanisms by which roadways
affect ecosystems include as barriers to movement, and places of avoidance. (Forman &
Alexander 1998). Major effects of roadways include: roadkill, barrier effects, chemical
pollution and fragmentation of ecosystems (Forman & Alexander 1998) (Coffin, 2007).
Proximity to a road or trail has also been correlated with changes in distribution of plant
species, and it is expected that these are in part due to changes in animal distribution
(ARÉVALO, DELGADO, & FERNÁNDEZ-PALACIOS 2008). Another explanation comes from
pollutants, such as de-icing agents in runoff water that can have a detrimental effect on many
plant species (Forman & Alexander 1998). This is a further factor that may influence the
distribution of of plant species near roadways, and change with increasing distance from the
roadway.
Changes in reproductive rates in of birds, have been found by Dietz, Murdock,
Romero, Ozgul, & Foufopoulos (2013). However, this was not a simple inverse relationship
with more successful nests being further away from roads, rather, there was an optimum
distance from the road (Dietz et al. 2013). This establishes that roads can have more complex
interactions with an ecosystem than simply encouraging, or discouraging the success of a
species in the roads immediate area. A further bolstering of this is the finding by Montgomery,
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Roloff, & Millspaugh (2012) of the varied have varied responses of elk to the distance and
visibility of roads depending on sex, and frequency of motor vehicle traffic, and the
importance of both euclidean distance and visibility as metrics in road effect research.
Problem Statement
More data needs to be gathered on the overall effects that a road has on an
ecosystem. What effects does proximity to a road have on a temperate forest ecosystem?
These changes could include fluctuations in the populations of, or even a turnover of the
dominant plant species. What are the dominant tree species near and away from roads, and
do they change with distance from the road? Do the number of species found in the area
increase or decrease with distance from the roadway? Can changes in key species
populations be linked to each other via ecological relationships?
Professional Significance
The understanding of anthropogenic effects upon ecosystems is ever expanding, and
constantly being revised. Although there exist significant works which surpass this project in
scope, complexity and analytical methodology, some of which are referenced, ecosystems
change. To monitor these changes, and to test understanding, new information must
constantly be gathered, and verified. The site where this study was conducted likely has
never been examined quite the same way, and if it was, was certainly in a different state than
during the completion of this study. Uniqueness of data aside, this study serves to test the
observations of changes in distribution of plant and animal species made by Arévalo,
Running Head: Road Impact Area 6
Delgado, & Fernández-Palacios (2008) in a different ecosystem.
Overview of Methodology
Population data was gathered using a series of line surveys parallel to the roadway,
and mapping plant species distribution in small plots at various distances. The number of
unique plant and animal species seen at each distance interval from the roadway was
counted. The total number of species was found by numbering each species as it was
encountered. Population interactions between dominant species were examined, and a
populations compared for each relationship at each surveyed distance from the roadway to
determine to what extent the change in population was linked directly to the roadway or to a
change in population of an interacting species. A nearby site on the same road was surveyed
with transects running away from the road as a control.
Delimitations
Field studies were conducted at two sites 100m x 50m on a logging road extension of
Robinson road in Bennington, Indiana. Data is limited to tree species visible during the period
of August 17-20th 2014. Population fragmentation, and habitat fragmentation effects are
outside the scope of this study, as are changes in population over time. This study did not use
visibility of the roadway as a metric, although visibility may may help explain some of it's
findings. Statistical analysis of the data was limited to chi-square analysis.
Definition of Terms
Running Head: Road Impact Area 7
Road distance: The shortest distance from any point on an observers designated path, to the
edge of the road where foliage is not growing.
Control line: The line between two markers used as a stand in for road distance
measurements at the control site.
Dominant Species: A species which takes up much of a resource, limiting the population of
other species, and governing the function of the ecosystem.
Summary
This is a study of the ecological effects of roads, a known stressor to wildlife. By
verifying and expanding on currently known principals of ecology, this study has examined the
of proximity to roadways. Using transects at varying distances from the road, population and
distribution information about key species near a logging road were collected and analyzed to
verify the expected results from similar studies, and to gain a better understanding of the role
of the roadway in the studied ecosystem.
Chapter II: Background
Road effects extend further than the edge of the road due to animal road interactions,
avoidance, road edge effects, and pollution. Roads can play a major part in shaping
ecosystems, sometimes in counter intuitive ways due to the interplay between anthropogenic
effects and intraspecies interactions. Changes in an ecosystem can be seen, and attributed
to road proximity.
Measures of ecosystem health
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Various methods are used to estimate ecological impact. These include the use of "indicator
species", and "landscape-based indicators" (Banks-Leite, Ewers, Kapos, Martensen, & Metzger, 2011).
One such landscape-based indicator would be fragmentation, which was found to be more reliable than
species based indicators when used on larger scales (Banks-Leite et al., 2011). Road density can be
used to estimate the severity of fragmentation and ecological damage caused by roads, but can have
errors introduced from mapping sources, because smaller roads are often not included (Hawbaker &
Radeloff, 2004). The use of indicator species as a measure of ecosystem health has the disadvantage of
being highly sensitive to species selection, habitat, and study area (Banks-Leite et al., 2011). Both
changes in plant and animal species composition, and population have been used as measures of
ecosystem health (LaPaix, Freedman, & Patriquin, 2009).
Road effects on animals
While roadkill is a highly visible reminder that human activities affect local ecosystems, the
danger of ecological upset, or population depressions from roadkill are small (Forman & Alexander,
1998). Rather, it is how animals respond to the dangers presented by roads that more strongly affect an
ecosystem (Forman & Alexander,1998). These behaviors can Include traveling along road edges rather
than crossing, or avoiding roads altogether (Forman & Alexander, 1998). In the former case, this can
result in extending the range of a species along a roadway. The latter case, will dampen or completely
prevent dispersion across the roadway (Forman & Alexander, 1998). A road which bars passage of a
migratory species can disrupt migration and bar access to resources, depressing the population (Holdo,
Fryxell, Sinclair, Dobson & Holt, 2011). A particular animal does not need to be struck by a motor
vehicle in order for the ecosystem to be affected by a roadway (Forman & Alexander, 1998).
Running Head: Road Impact Area 9
Proximity to roadways can be a source of stress for animals, as indicated by changes in
behavior, as well as an increase in blood cortisone (DIETZ, MURDOCK, ROMERO, OZGUL &
FOUFOPOULOS, 2013). Visibility of roadways may also be used to predict animal movement in
conjunction with distance from road (Montgomery, Roloff & Millspaugh, 2012). Predator prey
relationships can also shape animal distribution, causing peak prey populations to be found closer to
roadways than expected due predator avoidance of roads (DIETZ et al., 2013).
Road effects on Plants
The sum of animal responses, as well as effects on plant life contribute to ecological damage.
The accumulation of barrier effects, and the change in landscape caused by roadways is called habitat
fragmentation. This alteration of the landscape affects not only animal life, but also plant life
(ARÉVALO, DELGADO & FERNÁNDEZ-PALACIOS, 2008). A road edge can often also be a forest
edge, harboring plant species that typically grow in such places (Forman & Alexander, 1998). This is
true especially when the break in tree cover is sufficient to increase the amount of sunlight penetrating
to the understory (Forman & Alexander, 1998). Increases in tree growth have also been found at the
edge of logging roads (Bowering, LeMay & Marshall, 2006). Other effects of roads on plant life extend
further into a forest ecosystem, some of which can be explained by changes in animal distribution and
behavior (ARÉVALO et al., 2008). Changes in tree size and composition, as well as diversity of lichen
species can be seen along a gradient from a forest edge (Belinchón, Martínez, Escudero, Aragón &
Valladares, 2007).
Conclusion
Running Head: Road Impact Area 10
Proximity to roads can be linked with ecosystem health. Evidence for this includes
increase in fragmentation effects with increasing road density, changes in animal behavior
and stress response near roadways, and changes in plant species composition both on the
edge of roads linked with road distance. Changes in plant plant and animal life can have
secondary effects on each other, further extending the ecological effects of roads from the
road edge.
Chapter 3: Methodology
What effects does proximity to a road have on a temperate forest ecosystem?
To answer this question, field studies of plant life composition were conducted in two areas on
privately owned, unmanaged land. The first area was road adjacent, extending 50m from the
road edge into the forest, and up to 100m along the roadway. The second area , which
served as a control, had the same dimensions, but turned 90 degrees to the roadway so that
the long end extends into the forest up to 100m, with the 50m edge along the road. These are
referred to as the experimental area, and the control area respectively. The dependent
variables were species number, and population levels of each species.
A transect is a line upon which a researcher walks while collecting research data. In
each area, a transect will be walked parallel to the area's long edge at 10m intervals, noting
each type of wooded plant (a tree or shrub) falling within 1m of the transect and
photographing it for identification. Number of species, and populations for each species along
each transect were recorded in this fashion. Seedlings were not counted, nor was any plant
less than 1m in height. This limit served to keep reproductive strategies from skewing the data
with highly variable numbers of seedlings, and allowed for the data collection to be completed
Running Head: Road Impact Area 11
in a reasonable amount of time. Species were identified using the National Audubon Society
Field Guide to North American Trees (Little, 1980). The research perspective is quasi-
experimental, with the independent variable being distance from a roadway, or from a
designated line in the case of the control. The independent variable will be species number.
Do the number of species found in the area increase or decrease with distance from
the roadway?
Once data was collected along the transects, the data was tabulated in a spreadsheet
program to create graphs of species number vs. distance from edge of the area, and graphs
of specific species populations with respect to the edge of the study area. The data for each
area was then be subjected to a chi-squared analysis against a null hypothesis of no change
with distance from study area edge. No change means that the average value of all transects
was used as expected value for each term. The formula used for chi-square analysis was
χ2=Ʃ(o-e)2/e with each transect having it's own term.
If there was a significant change in number of species with distance to the road, the
null hypothesis should fail for the experimental area, while the control area will pass. The chi
squared test is supposed to measure the probability that the observed results were produced
by the hypothesis, so even though it is not a pass fail test, it can give guidance on the
likelihood of a hypothesis being true. The spreadsheet program's best fit line function was
then used to formulate new hypotheses for species number, and populations.
What are the dominant species near and away from roads, and do they change with
distance from the road?
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The dominant species will be the most populous. A change in dominant species at any
of the transects will be noted. Additionally Simpson's index, a measure of biodiversity and,
inversely, dominance will be computed for each transect. Simpsons index is the sum of each
species population divided by the total population, with each fraction squared. D=Ʃ(n/N)2 This
will produce a number close to 1 when there is high dominance and low diversity, and closer
to 0 when there is higher diversity and lower dominance. This data will be plotted on tables
concurrent with populations of species of varying dominance.
Can changes in key species populations be linked to each other via ecological
relationships?
Most plant species will be interacting with each other in competition for sunlight, and
space, so an increase in one species will usually mean a decrease in others. Simpson's index
is again helpful here, but will not be able to establish a species-species link. The data will
have to be examined to find correlations between changes in populations, and the ecological
link verified by consulting outside sources.
Conclusion
This methodology provided data for species number, and population of each species
along five lines parallel to a roadway, at varying distances. A combination of qualitative, and
quantitative analysis were used to answer the research questions. These included, the chi-
squared test, Simpson's index, and visualization of the data in the form of scatter plots and
graphs.
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Chapter 4: Results
Below are the results of the field survey sorted by sited and transect. Data collected or
computed for each transect is sorted by its distance from the road, or distance from a control
line perpendicular to the road. Chi square analysis did not reject any of the null hypotheses
for change in species number, or dominance. However, changes in species number, and
dominance can be seen in visualizations of the data. There is some indication of a
relationship interplay between dominance and tree population density.
Do the number of species found in the area increase or decrease with distance from
the roadway?
According to this data, species diversity was highest near the road, but increased with
distance after an initial drop. A null hypotheses of no change in species diversity with
increasing distance from road was not rejected using chi-square analysis for either the
experimental or the control site.
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Table 1: Species and populations for experimental site
Table 2: Species and populations for control site
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What are the dominant species near and away from roads, and do they change with
distance from the road?
Between the experimental and control sites, 13 different tree species were found. The
dominant species was by far Sugar Maple, Acer Saccharum followed by the White Ash,
Fraxinus americana,and the Eastern Redcedar. The dominant species remained the sugar
maple on every transect of the experimental site, except the 40m transect where the
dominant species was Prunus Serotina. The simpson index tended upwards with distance
from the road as the dominant species made up a greater number of the total trees. Chi
square analysis of Simpson's index at each transect did not reject a null hypothesis of no
change in Simpson's index with distance from road for either the control, or experimental
sites.
Can changes in key species populations be linked to each other via ecological
relationships?
While the total populations of the top three tree species tended to move up and down
together, less populus species were more prominent along transects with fewer trees, and
fewer of the more dominant species.
Figure 1:
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Figure 2
0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.50
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Dominant Species Control
Sugar MapleTotals:White AshRed Cedar
Distance from start/10m
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Dominant Species Experimental
Sugar MapleTotals:White AshRed Cedar
Distance From Road/10m
Num
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Figure 3
Figure 4
Chapter 5: Summary and Discussion
0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.50
0.05
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0.15
0.2
0.25
0.3
0.35
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0.45
f(x) = 0.214464732541203 x^0.168464766014099R² = 0.127999592376933
Simpson's Index for Experimental site
Distance From road/10m
Sim
pson
's In
dex
0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.50
2
4
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8
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f(x) = 5.01791955321469 x^0.329409593221023R² = 0.392147936277337
Simpson's Index for control
Higer index indicates lower diversity
Distance from start/10m
Sim
pson
's In
dex
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This is a study of tree species and distribution with respect to the edge of a logging road.
A road edge can often also be a forest edge, harboring plant species that typically grow in
such places (Forman & Alexander, 1998). This is true especially when the break in tree cover
is sufficient to increase the amount of sunlight penetrating to the understory (Forman &
Alexander, 1998). Increases in tree growth have also been found at the edge of logging roads
(Bowering, LeMay & Marshall, 2006). These and other studies support the existence of a road
distance gradient. Arévalo et al. specifically found evidence for changes in plant composition
linked to distance from logging roads (2008).
Problem statement
More data needs to be gathered on the overall effects that a road has on an ecosystem.
Major Question: What effects does proximity to a road have on a temperate forest
ecosystem? These changes could include fluctuations in the populations of, or even a
turnover of the dominant plant species. What are the dominant species near and away from
roads, and do they change with distance from the road? Do the number of species found in
the area increase or decrease with distance from the roadway? Can changes in key species
populations be linked to each other via ecological relationships?
Methodology
Two sites along a logging road were surveyed by walking transects at 10m intervals,
and recording the number and species of trees of along it. The experimental set of five
transects began 10m from the road, with further transects beginning further away running
Running Head: Road Impact Area 19
parallel to the road. The control set of transects began at the road edge, and extended away
from the road, with subsequent transects beginning further along the road.
Summary of results
What are the dominant species near and away from roads, and do they change
with distance from the road. The dominant species throughout the study area was the
Sugar Maple. There were changes in species composition along the road distance gradient,
and transient changes in species dominance, however overall the sugar maple remained
dominant at all distances.
Do the number of species found in the area increase or decrease with distance
from the roadway. The data did not refute the null hypothesis of no change in biodiversity, or
dominance when chi square test was applied. It was expected that the control site would have
a roughly random distribution with respect to distance from the starting point. However, chi
square analysis provided similar results for the experimental site as well, with the null
hypothesis having about a significance level of just over 20% for both sites for species
number. The number of species increased slightly with distance from the road, after an initial
drop between the 10m and 20m transects.
Can changes in key species populations be linked to each other via ecological
relationships. The main point of interaction between species was total population density of
the trees. Less prevalent species were better represented on transects with lower numbers of
trees, and lower numbers of Sugar Maples.
Relationship of Research to the Field
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While changes in species composition were seen, evidence for changes in biodiversity
could not be conclusively linked to the road distance gradient. Changes in species
composition were found between transects at different differences supporting the findings of
(ARÉVALO et al., 2008). Furthermore the collecting of data along transects parallel to to the
roadway at varying distances does not seem to be a widely used technique in road effect
research. Most of the reviewed studies were focused on species level effects, rather than the
net change in biological makeup proximate to roads. This project could serve as the basis for
more extensive research using similar techniques.
Discussion
Species Number. Change in species number from the road was found to be consistent
with a null hypothesis of no change. The null hypothesis holds even if the 10m transect is
disregarded, however the probability threshold used to reject based on a chi square test less
than twenty percent. This does not mean that the road had no effect on the tree community, it
means that the variations seen could be random. The level of significance on the control site
was similar, which adds weight to the null hypothesis. Although possibly not a statistically
significant change, there was a general upward trend after the initial drop. Further studies
using similar methodologies would be needed to see if this trend holds. A best fit line omitting
the 10m transects produced upward trends for both the experimental and the control site. Of
the options available, the trend lines for the experimental group had a better fit, as can be
seen in the R2 values of figure 5 and figure 6.
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Figure 5
Figure 6
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Number of Species by distance from Road
Distance from Road in meters
Num
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15 20 25 30 35 40 45 50 550
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Number Of species by distance from Control line
Distance from start point in meters
Num
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Changes in Dominance and Ecological Relationships. Dominance as measured by
Simpson's index, trended upwards with distance from the road when all transects were
included, but trended down when omitting the most road proximate transect. Yet again, chi
square analysis did not reject the null hypothesis of no change for either the control or the
experimental site, indicating that the correlation may be coincidental.
The dominant tree species at both the experimental and control sites was the sugar
maple, although it was not the dominant species on every transect. The only change in
dominant species at the experimental site was to cherry at the 40m transect. At the control
site, the dominant species was ash on one transect, and Red Cedar at another. These
changeovers in dominance coincided with lower numbers of maples in the respective
transects. The cherry dominant transect also had the fewest trees of any transect at the
experimental site. As the change in dominance to cherry happened at the 40m transect in the
experimental site, and the average distance from the road was greater at the control site, this
could indicate that significant clusters of non-dominant tree species are more likely to occur
further from a roadway.
The average distance of the control transects from the road may have also had another
affect. The average number of trees for the control site was much lower than at the
experimental site. Combined with the number of changes in dominance at the control site, it
begins to look as if overall density of tree cover might have an effect on biodiversity and
dominance. This can be seen when Simpson's index is compared to the number of trees in a
transect. As the number of trees increases, so does dominance.
Figure 7
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When the control and experimental sites are looked at separately, there are two distinct
trends. For the experimental site, there is an inverse relationship between Simpson's index
and number of trees, while the relationship is direct for the control site. This may indicate that
there is a peak in dominance from the effect of tree density and road distance overlapping.
This cannot be seen directly in the data, because the distance from the road for each tree
was not recorded, and the correlation between total tree density and distance from the road is
only seen by comparing the orientations of the two sites with respect to the road. A correlation
between tree number and distance from the road is in agreement with some of the findings of
Bowering, LeMay & Marshall (2006). A peak in dominance of sugar maples at an intermediate
distance would parallel in the plant kingdom the effects of interacting stressors creating an
optimum distance from a road for reproductive success in birds as found by DIETZ, et al.
(2013).
Figure 8
20 25 30 35 40 45 50 550
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45f(x) = 0.138573544369717 x^0.169280867784973R² = 0.0164688100644462
Dominance vs. Total number of trees
Trees in transect
Sim
pson
's In
dex
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Conclusion
A decrease in dominance, and increase in species biodiversity among trees were correlated
with distance from the road, but other causes were not eliminated via chi-squared analysis.
The relationships between the Sugar maple, and other prevalent species were such that
areas of dominance by Cherry, Eastern Redcedar, and White Ash, appeared only along
transects with lower numbers of Sugar Maples. Past 50m the decrease in overall tree density
may benefit non-dominant species. Within 50m of the road, tree density is correlated with
areas of higher dominance. Further study into the relationship between tree density,
dominance, and road distance may be warranted.
20 25 30 35 40 45 50 550
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
f(x) = 0.0193459363896883 x − 0.290681742825547R² = 0.670113687389476
f(x) = − 0.00412279816735156 x + 0.423948792964092R² = 0.0981697182752017
Tree density and dominance between sites
Experimental siteLinear (Experimental site)Control siteLinear (Control site)
Simpson's Index
Num
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