Comparison of Avian Diversity Between Man-Made Wetland and Meadow In Lacey,
Washington
Blayse Chun
Bio 402
Final Draft
May 07, 2007
1
Table of Contents
Abstract
Introduction
1
1
Methods
Results
Discussion
Acknowledgments
11
15
17
23
Literature Cited
24
2
Abstract
This study was undertaken to determine if there was a change in the avian
diversity whose meadow habitat had been artificially altered into a man-made wetland.
Two sites were observed in Lacey, Washington. A Before-After-Control-Impact (BACI)
model was incorporated when observing both habitats in order to see how a species
would react to a major disturbance within its habitat. Anas platyrhynochos, Anas crecca,
Branta canadenis, Turdus migratorius, Actitis macularia, Corvus corax, and other
unidentifiable bird species were observed during a 6-week period in order to compare
population trends between the avian communities in both habitats. Other biodiversity
trends were taken into account such as the introduction of various species into the
wetland habitat, as well as any other short or long term trends. The data that were
observed suggested that there was not a change in avian population (p>0.05). However,
further research is needed to fully support this outcome.
3
Introduction
Wetlands are a source of many valuable ecological resources, providing a number
of ecosystem services such as water supply and quality, functioning traps for raw
materials and nutrients, increased landscape biodiversity, food, flood control, and
recreation (Hansson et al., 2005). Wetland ecosystems historically were not conserved
because they were considered less desirable than industrialization, modern agriculture,
and more dry land for development (Hansson et al., 2005). Yet, wetlands often undergo
important human-induced changes that tend to alter or modify their ecological function
(Schmid et al., 2004). However, this “development” has often led to the destruction or
reduction of wetlands which yields both positive and negative results. Thus, humans have
taken an interest in restoring and even constructing wetlands in agricultural areas due to
their multiple functions (Hansson et al., 2005).
There have been many studies examining the functionality of wetlands
(Andrewartha and Birch, 1954; Mitsch et al., 1998; Ratti et al., 2001; Snell-Rood and
Cristol, 2003; Stapanian et al., 2004; Hansson et al., 2005; Koellner and Schmitz, 2006).
Many of these studies compare multiple wetlands and take into account the differences
and similarities in biodiversity. For example, Houlahan and Findlay (2004) conducted a
study on invasive plant species affecting the diversity of native plants across 58 wetlands
in Ontario, Canada. They concluded that in order to maintain wetland biodiversity
between invasive and noninvasive plants was to discourage the spread of community
dominants. Other studies even compare newly constructed wetlands to natural wetlands
and restored wetlands to natural wetlands, but they have seldom considered studying
newly constructed wetlands in comparison to the previous, non-wetland, land use or
4
using previously gathered research of a specific habitat in comparison with an unaltered
habitat (Ratti et al., 2001; Snell-Rood and Cristol, 2003). In doing so, wetland
biodiversity could be viewed in a “before and after” comparison. The before and after
comparison would be beneficial because it allows one to see any prominent differences or
similarities in regards to differing habitats such as wetlands to meadows.
Wetlands are areas that are saturated by ground or surface water and can sustain
organisms that flourish under these conditions (Harding Lawson Associates, 1998). Many
organisms such as Caster Canadensis, or goldfish, (Cunningham et al., 2006) and
amphibians (Blaustein and Bancroft, 2007) occupy and are specialized to these
ecosystems. A wetland must have one or more of the following attributes: land that
predominantly supports plants that grow in water (hydrophytes), a substrate with
predominantly undrained soil that contains hydrogen in it and can adapt to the moist
environment (hydric soil), and a substrate (College Ditch sedimentation ponds) that is
saturated or covered with water during the growing season of the year (City of Lacey,
1992 as cited by Harding Lawson Associates, 1998). Feest (2006) suggests that since
diversity can occur within species, between species, or ecosystems, the diversity in
wetland communities can vary, particularly with respect to wetland bird species.
Often, avian communities and small mammals are studied when dealing with
wetland ecosystems (Ratti et al., 2001; Snell-Rood and Cristol, 2003; Stapanian et al.,
2004). Nally et al. (2004) explain that birds have been widely regarded as key elements
in monitoring biodiversity. Given their responses to changes in agricultural landscapes,
their mobility, and their ability to occupy 3-D space, birds are regionally more species-
5
rich than most vertebrates. Thus, they are extensively monitored in relation to the
biodiversity of different habitats (Nally et al., 2004).
Koellner and Schmitz (2006) define biodiversity as the number of species
contained in a system and also as the magnitude of disturbance that can be absorbed or
accommodated by an ecosystem before its structure is fundamentally changed to a
different state. Hence, “development” has often led to the destruction or reduction of
wetlands. Andrewartha and Birch (1954) suggest that the introduction of new elements;
whether biotic or abiotic, into an ecosystem, tend to have a disruptive effect. They
suggest this because if a new element(s) is introduced, it could potentially dominant or
overthrow a less dominant species. Based on this assumption, biodiversity can be a
predominant factor in the success or failure of an ecosystem. However, if the ecosystem
itself was altered, one could assume that the success or failure of a species biodiversity
also relied on the stability of its ecosystem.
Hansson et al. (2005) studied and addressed the demands of 32 recently
constructed wetland ecosystems in southern Sweden. Their main objective was to identify
the features that define a “suitable” wetland. In doing so, Hansson et al. provided useable
data for future wetland construction projects. They measured the chemical and biological
features of each wetland using the “helicopter perspective” which screens general
patterns in a large set of variables. This can potentially be an important determinant for
the wetland’s ecosystem because the data collected could be used to benefit future
wetland restoration projects (Hansson et al., 2005). Their results suggest that certain
features like shallow depth, large surface area, and high shoreline complexity are likely to
provide high levels of biodiversity. They suggest that there are features such as depth,
6
surface area, and shoreline complexities that may direct the ecosystem function of a
wetland in the desired direction (Hansson et al, 2005). The desired direction being a rich
and diverse wetland. Hansson et al. further indicate that if certain aspects (depth, surface
area, shoreline complexity, etc.) of a wetland are monitored, wetland functions (i.e.
nutrient retention) could possibly be governed in a more controllable/monitored
environment. This possibility could provide additional information for future wetland
construction projects. This study also suggests that the amount of biodiversity is
dependent on the amount of physical and chemical functions in a wetland. This study
relates to my proposed research by introducing me to the possible variables that could
affect my study and hypothesis.
Stapanian et al. (2004) evaluated the usefulness of the Ohio Rapid Assessment
Method (ORAM) for Wetlands Version 5.0 when dealing with ecological integrity that is
beyond its purpose (not avian biodiversity). Wetlands Version 5.0 is a wetland
monitoring system that distinguishes wetland quality by comparing quantitative data.
ORAM was developed to categorize natural wetlands for regulatory purposes and to
contribute to the development of indicators of biotic integrity in wetlands across Ohio.
However, the total scores of ORAM also served as an adequate predictor of avian
diversity. Avian diversity was monitored by data programs that used three different levels
of assessment. Level one used any source of remote information available, level two
required onsite surveying of specific predetermined characteristics, and finally level three,
which required gathering detailed biological data. The study was conducted at 14 wetland
sites using certain criteria to factor in habitat heterogeneity affecting species richness
(Stapanian et al., 2004). The criteria that had to be met consisted of each site being a
7
small natural wetland, with shallow-water and shrub-scrub vegetation, open water, and
partial or complete forest border.
Stapanian et al. (2004) then evaluated whether the avian species richness in
wetlands could be reliably predicted from each of the following variables: total ORAM
score, total score minus the score of one metric (size of wetland in km2) which did not
apply to all wetlands because not all of the wetlands fell into studies suitable wetland
criteria, and the sum of four ORAM component scores. The four components used were
aquatic vegetation communities, microtopography, modifications to natural hydrolic
regime, and any sources of water. They found that all three variables (total ORAM score,
total score minus metric, and sum of ORAM component scores) were significant
predictors of both total species richness and mean species richness of birds of
conservation concern. Variable three (sum of ORAM scores) was a significant predictor
of mean species richness of wetland-dependent birds whereas variable two (total score
minus one metric) was a weak predictor of species richness for all birds. Based on these
results, Stapanian et al. (2004) suggested that ORAM is a reliable indicator of ecological
integrity of wetlands and can unexpectedly serve as an adequate predictor of avian
diversity. This study showed that different variables in a wetland can affect the diversity
of avian communities. However, since different variables were measured at the same time
and avian species were not specified, it is difficult to have a clear picture if the
biodiversity will be similar or different in adjacent wetlands. This study is related to my
study because it emphasizes that if avian species is not specified, comparing biodiversity
will be difficult.
8
Ratti et al. (2001) compared avian use of 39 restored and 39 natural wetlands in
North and South Dakota during spring and summer of 1997 and 1998. Their study
defined natural wetlands as existing wetlands with no prior physical manipulations to the
basin or water levels whereas restored wetlands resemble natural wetlands in form and
function. Every ten days they conducted paired comparisons between restored and natural
wetlands for wetland bird density, waterfowl-breeding pairs, and wetland-avian
abundance, species richness, and diversity. They did this by physically counting the
number of birds present at specific vantage points from sunrise to 10 o’clock at night and
excluded birds flying away or into the specific wetland. They calculated density by using
an ordered-pair distance method which estimated the overall population of each bird
species.
Ratti et al. (2001) also compared abundance, species richness, and diversity of
birds on upland areas adjacent to wetlands. They observed that Canada goose, mallard,
redhead, and ruddy duck had higher densities on restored wetlands. They failed to detect
differences in overall avian abundance, species richness, or diversity between restored
and natural wetlands. They concluded that restored wetlands in the Prairie Pothole
Region supported similar avian communities with equal or higher abundances than those
of natural wetlands. Their results suggest that there is no real difference in bird
populations when comparing a natural wetland to a restored wetland. This study is
essential to my study and hypothesis because it supports my hypothesis and proposed
goals.
Snell-Rood and Cristol (2003) compared the avian communities of constructed
forested wetlands to those on natural forested wetlands regenerating from logging. In the
9
summer of 2000, they tested whether forested wetlands that were created eight years
earlier had developed avian communities similar to natural wetlands of the same age in
southeastern Virginia. They compared six created wetlands to five natural wetlands that
had undergone ecological succession after clear-cutting. Snell-Rood and Cristol (2003)
tested this by creating a trajectory of expected avian community development by
comparing 20 previously referenced wetlands, which were logged 1-25 years prior, to
mature forested wetlands that had not been logged for 50 years or more. They observed
that the created wetlands had significantly lower avian richness and diversity, and a
different community composition compared to the referenced wetlands. They suggested
that these differences were due to the fact that created wetlands supported low numbers
of the expected passerine or bird species. This study related to my study by introducing
the fact that certain constructed wetlands may only attract certain avian species.
In addition, Snell-Rood and Cristol (2003) suggested that the natural wetlands
supported species of higher conservation concern, migratory status, trophic level, habitat
specificity, and wetland dependency. Their trajectory of avian community development
indicated that the created wetlands were developmentally behind referenced wetlands or
were following a different developmental trajectory altogether. Snell-Rood and Cristol
(2003) hypothesized that the differences between created and reference forested wetlands
were due to unnatural patterns of hydrology or retarded vegetation development on
created wetlands. This study suggests that natural wetlands will have a larger avian
population then a created wetland which contradicts the study done by Ratti et al. (2001).
This contradiction only further supports that ecosystems are complex and that certain
variables can contradict others.
10
Forcey et al. (2007) suggest that bird populations are influenced by a variety of
factors that consist of both small and large scales ranging from suitable nesting habitats,
predators, food supplies, climate conditions, and land-use patterns. They evaluated the
influences of regional climate and land-use variables on Canadian wetland breeding birds
in the Prairie Potholes region. Forcey et al. used bird abundance data from the North
American Breeding Bird Survey, land-use data from the Prairie Farm Rehabilitation
Administration, weather data from the National Climatic Data, and the Information
Archive to model specific effects of regional/environmental variables that can affect bird
abundance. The models that were constructed consisted of a priori which used
information from published habitat associations in the literature, and the fitting was
performed with WinBUGS using Markov chain Monte Carlo techniques which are
specific types of statistical tests that allows one to draw simulations from a wide range of
distributions that can arrive in statistical work (Forcey et al., 2007).
They found that while both land-use and climate variables contributed to
predicting bird abundance in Prairie Pothole region, climate predictors contributed the
most to improving model fit. Forcey et al. also looked at the examination of regional
effects of climate and land use on wetland birds. This revealed relationships with
environmental covariates that are often overlooked by small-scale habitat studies. Based
on their results, they suggested these studies can be used to improve conservation and
management planning for regional populations of avifauna. This study also presents data
pertaining to specific variables that can affect avian populations and the methods used to
study them under certain conditions. This study relates to my study by setting a specific
guideline pertaining to studying birds.
11
The methods that I have utilized in this study have been used in similar studies.
One of the most commonly used techniques of monitoring bird diversity and abundance
is known as point counting. Thompson (2002) describes point counting as counting birds
that are seen, heard, or captured in order to assess avian-habitat relationships with
response to disturbances and population trends. The point counting method involves one
or more observers that record all birds detected within a fixed or unlimited distance from
a point during a specified time period (Thompson, 2002). Many researchers have
collected their data through bird surveying because this method proved much more
practical due to financial and time constraints (Ratti et al., 2001).
Ratti et al. (2001) physically completed a count of all birds directly on the
wetland which included all inundated zones with open water or signs of vegetation. They
set up specific vantage points while walking around the wetland. At each vantage point,
Ratti et al. (2001) physically counted each bird that was observed and counted. They also
visited each wetland 4 times from mid-May through July from sunrise to 1000 hours.
They did not do counts during inclement weather and at certain wind speeds in order to
reduce random errors. Each observer rotated observing times in order to limit biased data.
Ratti et al. (2001) also used variable circular plot (VCP) methods to estimate densities of
breeding birds within a specific area. Variable circular plot or variable area surveys
methods are widely used to estimate the size and trend of forest bird populations when
vegetation and terrain around study deem impractical or impossible to use other methods
(Fancy, 1997). To do this they established a 75-meter radius circle and measured the
number of birds observed within the radius.
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Stapanian et al. (2004) used similar methods of surveying bird populations. The
only difference between methods was that they input the data that were collected into a
wetland monitoring program (i.e. Wetlands Version 5.0) which utilized three levels of
assessment that inadvertently monitored the biodiversity of birds. These assessments
require in-depth data collection and onsite surveying. Nally et al. (2004) on the other
hand, offers an array of monitoring programs in order to estimate the ecological effects of
known, well-specified impacts pertaining to bird populations. Thompson (2002) also
overviewed general sampling framework methods for conducting population studies.
The models that I am mimicking in the present study are the Before-After
Control-Impact (BACI) design which utilizes comparisons between a point of reference
or control and the actual study in order to assess an impact (i.e. change or disturbance)
that could have affected the study (Underwood, 1993 as cited by Nally et al., 2004), point
count procedures (Thompson, 2002; Alldredge et al., 2006; Thogmartin et al., 2007), and
VCP techniques (Fancy, 1997; Ratti et al., 2001). The methods and results from these
previous studies have been taken into account because each model is seen as an
appropriate representation for the present study.
I surveyed the bird population in the newly developed storm water treatment
facility on 6th avenue in Lacey, Washington. This man-made ecosystem was an open
meadow before wetland construction began. The City of Lacey is advancing this College
Ditch Project with hopes of improving water quality functions (i.e. water purity) which in
turn should augment the existing habitat that is present at the site (Harding et al., 1998).
This means that since the existing habitat was formerly a meadow, the habitat will be
altered to a certain extent because it is now a constructed wetland. College Ditch is a
13
series of water purifying sedimentation ponds that drains water from Woodland Creek.
The recommended design will have a sedimentation pond and two storage ponds that can
hold a maximum storage handling capacity of 42 acre-feet on Saint Martin’s University
campus (Harding et al., 1998). In doing so, the proposed construction should alter the
biodiversity of the organisms surrounding the site. Generally, the construction of
wetlands should increase biological richness through the increase of habitat complexity;
however, this may not prove to be the case (Feest, 2006). This may be due to the fact, that
a more dominant species may be introduced into a habitat. Although, this introduction
adds to the complexity of the habitat it may reduce the populations of less dominant
species. Therefore, I hypothesized that the population of birds will remain the same even
though their habitat has been changed. I also surveyed the bird population on the meadow
adjacent from the storm drains which will act as my control in order to test my hypothesis.
Materials and Methods
Two sites were chosen within Lacey, Washington to conduct a 6-week study of
avian population trends. These two sites were located adjacent to 6th Avenue, across from
Saint Martin’s University. The first site, College Ditch, was recently developed into a
storm water treatment facility which consists of one sedimentation pond and two storage
ponds that drain and purify water from Woodland Creek (Harding Lawson Association,
1998). The second site was the adjacent meadow that is located northeast of the storm
water treatment facility. I surveyed the avian population (number of birds seen)
surrounding both sites in order to compare population trends. Bird counts were conducted
in late winter and spring (January-March) in 2008 at both sites, 3-4 times a week from
7AM-10AM, 12PM-2PM, and 4PM-sunset. I visited the sites during these times because
14
other studies (Ratti et al., 2001) had conducted their studies at these time intervals. I also
noticed after the first few visits that these times had the most bird activity. Each visit
represented a sampling event that has been replicated continuously (at least 3 or more
times a week) during a 6-week period. I survey both the wetland and its adjacent meadow
individually or both sites during each sampling event.
College Ditch acted as the main habitat and the adjacent meadow acted as my
control. College Ditch remained unaltered during my entire study in order to aid in the
comparisons between avian population and diversity trends and also establish a BeforeAfter-Control-Impact (BACI) model. Each vantage point was measured with a
rangefinder which allowed me to also establish specific controls and variables that will
aid in analyzing my data statistically in order to test if my hypothesis was supported or
rejected. For each habitat I mimicked the point counting and Variable Circular Plot
methods in order to estimate population densities in each quadrant. I did this by first
measuring a radius of 75-100 meter at habitat which was chosen because this radius was
used in previous studies (Ratti et al., 2001).
After I established each radius at each site, I split each circle into 4 quadrants and
measured 25 meters from the outer boundaries of the circle to the center of the circle. I
proceeded to mark these 25 meter spots as my vantage points, which I used as a 360
degree spatial area to reduce any bias data and to identify any bird(s) flying in the air. In
each quadrant, I made observations by watching, using binoculars (Bushnell PermaFocus
17-3507 7X35), and listening, for 8 minute intervals. Each quadrant enabled me to keep
on moving so I would not be observing birds in just one area. After 8 minutes I would
proceed to the next quadrant in a clockwise motion. I chose to observe for 8 minute
15
intervals because previous studies used a 5-8 minute range (Alldredge et al., 2006). I
observed birds flying over the study area, landing in the study area, and already in study
the area (Table 1). The table that I used incorporated listing the following: bird name,
scientific name, which site the bird was identified in, the total number of times I saw each
bird, the time that it was identified, the direction it was flying if applicable, and any other
information that could be used in my results section (i.e. eating, perched, following
another bird, etc.). For each bird that I saw or heard, I recorded the number and, if
possible, the species and the direction that it flew in order to reduce double counting. I
used a compass to keep track of what direction the bird was flying. If I could, I took a
snapshot of the bird that I saw. I tried to listen to any auditory bird calls and mark it as an
indication that a bird was present. If I could not see any birds, but could hear them, I
counted the approximate number of birds that were heard and list those in my table
(Table 1).
Table 1. Sample bird count and observations gathered during sampling event.
Bird
Scientific
Site
Number
Time
Direction
Other
Mallard
Anas
Wetland
10
6-10AM
Fly in
Eating
from
and
north.
bathing.
platyrhynchos
Once my two vantage points and radii were established, I factored in
environmental variables such as seasons, climate, observer errors, detection errors, and
any disturbances present at the sampling event in order to set positive and negative
controls. I was able to control some of these variables by researching what types of birds
16
were prevalent during specific climates and seasons and doing a mock trial run to see
what part of the day or week when bird sightings were most prevalent. The one control
that I could not possibly control was disturbances like weather and people. Previous
studies discourage going out in inclement weather due to the increased amount of
variables that can arise (Alldredge et al., 2006).The positive controls in this study were
the buffer zones which separate wetland from meadow, the types of birds to be expected,
and previously researched data. Since my study took place during the seasonal transition
of winter to early spring, I had assumed that certain avian species could be counted
because of seasonal and migration changes. This notion aided me in identifying certain
species (mallard, Anas platyrhynchos) that would usually not inhabit my study sites
during winter.
Factoring in these variables allowed me to take into account anything that could
produce errors in my data/observations. The potential types of errors that occurred during
my study were: counting the same bird more than once, too many disturbances, being
biased when bird counting (remaining in one area for too long, etc.), and not observing
enough birds to compare. I addressed this issue by focusing on other potential methods
that factor in this variable, such as listening for bird calls as well as watching them. My
null hypothesis was that the avian population will remain the same, even though their
habitat has been changed. I compared the number of birds observed between College
Ditch and its adjacent to see if my hypothesis was supported using Analysis of Variance
(ANOVA) testing. Tukey tests were conducted if appropriate after the ANOVA testing to
analyze my data. I set my level of significance to 95% and compared theoretical data to
observed data. These tests told whether or not there were any significant differences
17
between bird populations inhabiting a wetland and its previous non-wetland meadow. If I
observed no difference in bird population, my data supported my null hypothesis. If I saw
a significant difference (i.e. greater or lesser populations between wetland and adjacent
meadow) at the p<0.05 level, I rejected my null hypothesis, and assumed that there was a
change in the avian population inhabiting College Ditch.
Results
The intention of this study was to observe the avian population trends between a
wetland and its previous non-wetland meadow. Two habitats were surveyed in the data
collection process. Each sampling event displayed the number of birds detected and
spotted in each habitat. As a result of using spot counts and VCP methods, the maximum
number of birds counted in the wetland at one sampling event was 39, whereas the
meadow was 24. The minimum was 0 for the wetland and 4 for the meadow. The entire
bird count observed during the 6-week study was 378 (Figure 1). The first statistical test
conducted was the Analysis of Variance (ANOVA) between the bird population trends
between College Ditch and its adjacent meadow. The ANOVA showed no significant
difference between the bird populations (F=1.02; d.f. =1; p-value=0.319). Since p>0.05,
the null hypothesis can be supported which suggested that there was no difference in bird
population trends between habitats.
The mallard, Anas platyrhynochos, inhabited the wetland while the spotted
sandpiper, Actitis macularia, inhabited the meadow. These two species were primarily
spotted during field observations. The listed birds that do not have a scientific name are
marked as n/a because they could not be specifically identified (Table 2).
Table 2. List of birds that were identified during 6-week field study.
18
Wetland
Both Areas
Meadow
Mallard, Anas
Spotted Sandpiper, Actitis
platyrhynochos
macularia
Green-winged Teal, Anas
American Robin, Turdus
Common Raven, Corvus
crecca
migratorius
corax
Swallow, n/a
Sparrow, n/a
Canada Goose, Branta
Gull, n/a
canadenis
Table 2 depicts the birds that were identified during the 6-week study. There were other
birds that were present at the both sites but they are not listed in Table 2 because I could
not identify what type of bird was counted.
The values in Figure 1 were gathered from the 6-week field observation of the
bird populations between the College Ditch wetland and its neighboring meadow. These
values do not accurately represent the true bird population of both habitats because not all
birds were accounted for. During each sampling event, only birds that could be visually
accounted for were counted. This did not include birds that were not visually present.
When my field study first began (Jan 13-Jan26), there were sampling events that had zero
bird counts due to poor visibility and disturbances such as inclement weather. However,
there were often audio cues that suggested birds were in the area. If no birds were seen,
this did not mean that there were no birds present.
19
133; 35.85%
Wetland
Meadow
238; 64.15%
Figure 1. This is a summary of the number of birds counted in both habitats during a 6-week field study.
Figure 1 represents both identified and unidentified birds that were visually accounted for using point
counting and VCP methods. There were 238 birds counted in the wetland habitat and 133 birds in the
meadow habitat. However, these values do not include the birds that were not visually present during each
sampling event. The percentiles do not represent the actual percentages of birds in each habitat but the
percentage each value represents in the pie graph in Figure 1.
Discussion
This study failed to support the hypothesis that the avian population between a
wetland and its previous non-wetland meadow would not result in any change in
population trends even though their habitat has been altered. The hypothesis was tested
because the functionality of wetlands has produced both positive and negative results
(broaden diversity but at the same time could lessen diversity) in correlation to
biodiversity because Andrewartha and Birch (1954) suggested that the introduction of a
new element whether biotic or abiotic could have a disruptive affect. Based on this
assumption, a major disturbance such as a modification to a habitat could change the
functionality of that habitat. Moreover, wetlands often undergo important human-induced
changes that tend to alter or modify their ecological function (Schmid et al., 2004).
20
However, this development has often led to the destruction or reduction of wetlands.
Thus, humans have taken an interest in restoring and even constructing wetlands in
agricultural areas due to their multiple functions (Hansson et al., 2005).
It was my intention to set up a before and after comparison in avian population
trends between a wetland and its previous non-wetland habitat. In doing so, I hoped to
observe how a major disturbance (i.e. construction of manmade habitat) could potentially
alter animal populations. I also wanted to take into account any other short or long term
trends such as changes in populations, introduction or reduction of a specific species, and
so forth that could have been witnessed during a 6-week period. I collected field data
using point counting, one of the most commonly used techniques of monitoring bird
diversity and abundance (Thompson, 2002).
The resulting analysis of variance (ANOVA) testing of my field data suggested
that there was no significant difference (p-value>0.05). Based on my p-value, I can
assume that there was a change in the avian population. Alternatively, this does not mean
that there was not a difference in population or that my null hypothesis was incorrect.
There could be an inadequate amount of data (i.e. sample size, time, etc.) which may
have skewed my results. However, based on the resulting ANOVA testing, my data
suggests (p-value >0.05) that my alternative hypothesis of there being a change in avian
population can be supported and whether this change indicates an increase or decrease in
population depends on further and future testing. I speculate that there may be an increase
of marine-type bird species due to the data that I observed over a 6-week period because
certain organisms often flourish in habitat specific ecosystems. This assumption is based
on the study conducted by Kushlan (1986) which implied that wetlands of all sorts are a
21
valuable commodity and act as a crucial factor for the stability and maintenance of
regional aquatic bird populations. Yet, I feel that the overall bird population may have
decreased because Snell-Rood and Cristol (2003) found that created wetlands had
significantly lower bird populations because created wetlands supported lower numbers
of bird species.
Quantitative
The hypothesis could not be supported in a quantitative perspective because
results from the ANOVA suggested no significant difference between avian population
trends in each habitat (p-value=0.319). Although my hypothesis states that the avian
population will remain the same; results from ANOVA testing (p>0.05) suggest that this
can not be supported at this time and that further studies need to be conducted in order to
see what type of population change occurred. My p-value suggests that the alternative
hypothesis can be supported, but does not necessarily mean that it can be completely
supported. The variability of sample sizes and sampling events may have influenced my
results in such a way that when trying to plug in my data, the data was either too
inconsistent or too small to show any significant differences. I speculate that this is due to
a small sample size and short period of time which did not allow me to observe an
accurate population trend. I also feel that the first few sampling events that resulted in a
zero bird count could have drastically thrown off my results.
Qualitative
Other observations suggest that certain birds inhabit specific habitats
(Table 2). Many of the birds observed flew into the sedimentation ponds to bathe and
22
feed on a daily basis while other birds were observed singing or perched in trees.
Davidson and Evans (1986) emphasized the importance of wetlands in correlation to the
winter survival of shorebirds who found refuge and food in man-made wetlands during
severe winter weather. Peterson and Low (1977) found that the waterfowls, mallard
(Anas platyrhynochos), green-winged teal (Anas crecca), pintail (Anas acuta), and ringnecked duck (Aythya collaris) were most abundant in wetlands during migratory seasons
and lowest during breeding seasons. They concluded that wetlands of lower elevations
yielded better aquatic plants which acted as a source of food for the waterfowls. I also
noticed that in the mornings (6AM-10AM), there was the greatest presence and activity
of birds. I speculate that this is the time of least disturbances (i.e. people, traffic noises,
etc.) or could possibly be an instinctual time to come out of hiding.
This speculation correlates with Oswald et al. (2008) study of seabirds and their
reactions towards heat and food supply. One of the major problems encountered during
field observations was hearing and not necessarily seeing birds in the surrounding habitat.
This made identifying and counting more difficult. Although, the Washington Audubon
Society suggests that directional hearing or carefully listening for the direction of birds is
beneficial to bird watching; it did not prove useful in my study because trying to
distinguish the number of birds making noises could misrepresent the number of birds
actually present and skew data. Overall, the initial intent of avian identification was to
gain some understanding of which bird species were present at each habitat and to set up
a foundation for future studies. The qualitative data collected did not fully support the
hypothesis because there was simply not enough data collected to suggest any significant
differences in population.
23
Conclusion
Although the results did not support my hypothesis, it is understandable how
other variables such as disturbances, inclement weather, sample sizes, and audio versus
visual detection of birds may have influenced the outcome of my study. Also a wide array
of wildlife can occupy and utilize wetlands depending on the seasonal and annual water
level fluctuations which mean that a single wetland may have a drastically different
wildlife composition from year to year (Kirby et al., 2002). Identifying which birds
inhabiting each habitat was not conclusive with the utilization of just point counting and
field observations alone because the methodology of identifying birds had many flaws in
it. However, speculation of birds that were not seen but present can be inferred.
If this study were modified and retested, conditions and the methodology of the
experiment would be drastically changed. First and foremost, the idea of comparing an
organism inhabiting a before and after habitat change would remain the same. The
problems with sample size variability would need to be solved for future studies. I feel
that this problem could be solved by starting the study at the beginning of the first
semester versus after winter break. Although this study’s primary methodology involved
field observations and each observation acted as a sampling event, I would suggest
deciding on an adequate sample size or sampling event quota. I felt that counting at least
50 birds or more would be adequate enough for data comparisons. Since two habitats
were being compared, having more than one observer conducting field observations
would make life a little easier.
Although, only one person is needed for point counting, having another person
would aid in the precision of not missing a bird count. The addition of another person
24
would also allow for comparing two habitats simultaneously at similar time periods
versus having one person going back and forth between habitats or just observing one
habitat in any single sampling event. This may reduce the variability of sample sizes and
any bias data because on some days I would only go and conduct a sampling event at one
habitat at a certain time which made data comparisons very difficult. Also this allows the
observers to have more time to try to identify each bird. A problem that occurred while
bird watching was trying to successfully focus the binoculars while trying to look at the
bird, bird picture, and description all at the same time. This is why a lot of prior research
such as reading books and deciding on identification schemes (patterns and
pigmentations) is needed to successfully identify birds because the birds that I observed
were very skittish. Another suggestion that will benefit future studies is to be flexible and
patient because field observations tend to have uncontrollable disturbances (i.e. inclement
weather) that can skew data.
Logical arguments or modifications to this study would be related to the study and
generalization of a “before and after” habitat comparison. Could a single disturbance
affect or influence the biodiversity of a habitat to the point of great change? Can one
organism sufficiently illustrate this change over time? Or would each organism adapt to
the change and no difference would be seen?
Acknowledgements
I would like to thank the 2007-2008 senior seminar class for their constant input
with peer reviews, presentations, and group meetings. I would also like to extend my
gratitude to Dr. Margaret Olney, Dr. Aaron Coby, and Dr. Mary Jo Hartman for their
25
nonstop support and helpful insight with my project. Finally, I would like to thank Amber
Noval and my family for their moral support throughout the year.
26
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