- The study compared bird diversity between an area that will be inundated for a reservoir project (Inundated Area) and a proposed compensation area (Compensation Area) in Costa Rica. - While total bird abundance and number of species did not differ significantly between areas, species richness was significantly higher in the Inundated Area based on rarefaction analysis. - Due to the higher species richness found in the more mature forest of the Inundated Area, the authors recommend expanding the Compensation Area to better account for differences in biodiversity and habitat quality between the two areas.

1. 1
Biological reserve compensation project: dry forest bird species diversity and habitat
quality
Tropical Ecology Directed Research Paper, Spring 2016
Stefanie Farrington, stefanie.farrington@gmail.com (author)
J. Edgardo Arevalo (Resource Person)
Key Words
Biodiversity, Costa Rica, national park, mitigation, species richness, species abundance, species
density, unique species, habitat preference
Abstract
The National Service of Subterranean Water, Irrigation, and Agreements (SENARA) has
plans to implement a reservoir project that will conflict with a biological reserve in the
Guanacaste area of Costa Rica. In order to minimize the environmental impacts of this project,
another area will be protected as compensation. This study compares the species abundance,
species density, and species richness of birds within these two areas in order to assess the
suitability of the compensation area. We predict that the Inundated Area will have greater species
abundance, density, and richness than the Compensation Area based on the forest maturity-
quality hypothesis. Birds were counted through point counts, bioacoustic recording, and mist-
netting for six days, alternating between sites. Differences in species abundance and density were
analyzed using Chi-square and Wilcoxon tests, and differences in species richness were analyzed
using rarefaction and the Shannon Index of diversity. We found no significant difference
between locations for species abundance or density, but species richness was significantly higher
in the Inundated Area. Based on these findings, we recommend that the Compensation Area be
expanded in order to account for this discrepancy in biodiversity and habitat quality between the
two areas.
Introduction
Biodiversity is a crucial component of ecosystem services and conservation. Habitat loss
due to development projects is one of the major causes of biodiversity loss (Quetier & Lavorel
2011). Regulatory actions are often required to minimize habitat destruction and other
environmental impacts of development. Offsets for wetland mitigation, such as preservation of
compensation areas to replace affected areas, are used globally to mitigate loss of biodiversity
due to development. In mitigation projects, there is a goal of no net loss of diversity, although
this goal is often not met (Burgin 2008). While the success of an ecosystem mitigation project is
largely dependent upon robust initiation and enforcement of laws and regulations (Robertson

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2004), these projects cannot be successful without sufficient understanding of the habitat and
biodiversity of the original and compensation areas.
The National Service of Subterranean Water, Irrigation, and Agreements (SENARA) has
begun implementation of the Río Piedras Reservoir Project (RPRP), the creation of an artificial
reservoir that will connect the Arenal and Tempisque catchment areas. The uses of the reservoir
will include agriculture, hydroelectric power, and touristic activities, and the project is expected
to generate millions of dollars through direct and indirect impacts (SENARA 2012). SENARA
has identified a zone in the RPRP that conflicts with an area in the Lomas de Barbudal
Biological Reserve.
For the RPRP to continue, the establishment of a compensation area is required in order
to minimize the environmental impacts of development, especially on biodiversity. The
compensation area should be ecologically equivalent, in terms of biodiversity, to the Lomas
reserve (OET 2016, Quetier & Lavorel 2011). The proposed compensated area is in the
ASETREK farm, property of Tres Azul S.A. The Organization for Tropical Studies (OET) is
currently working to evaluate multiple components of the biodiversity of the Lomas reserve and
the ASETREK farm in order to assess the mitigation actions required to ensure the lowest
environmental impact possible.
This study is in line with goal 6 of the OET project: to identify the richness and
abundance of existing species, including bird species, in the two areas (OET 2016). The
objectives of our study are: 1) to compare species abundance and uniqueness at the two sites; 2)
to compare bird density at the two sites, and; 3) to compare species richness and diversity at the
two sites in order to 4) assess the quality of the compensated area compared to the inundated
area. We expect that because the Lomas reserve is an older forest than the ASETREK farm and

3. 3
has been protected from deforestation, the habitat will be more complex and of higher quality
(Sánchez-Azofeifa et. al. 2003). Mature forests are considered to be high quality habitat due to
greater complexity and abundance of resources than new-growth forests (Parkes et. al. 2003,
Powers et. al. 2008.). Indeed, tree growth has been positively associated with bird species
richness, and bird population density may be used as an indicator of habitat preference and
quality (Chalfoun & Martin 2007, Feeley & Terborgh 2006, Johnson 2007). We therefore
predict that bird species abundance, density, and richness will be greater in the Lomas reserve
than in the compensation area because the habitat is of greater quality in the more mature forest.
Methods
Data Collection
Our study was performed in a seasonal dry forest and wetland in the Guanacaste area of
Costa Rica. We collected data in two areas: the protected Lomas reserve, in which approximately
130 hectares will be inundated by the irrigation project (henceforth Inundated Area, 10.45069º, -
85.299637º) and the unprotected ASETREK farm area that will compensate for the inundated
area (henceforth Compensation Area, 10.450233º, -85.419727º). Data was collected from April
24 to April 29, 2016, during the transitional period from the dry season to the wet season.
Three methods were used in order to count birds: point counts, bioacoustic recordings,
and mist-netting. The combination of these three methods was chosen in order to achieve the
most robust estimation of species abundance, density, and richness possible during the limited
data collection period. Point counts are the most common method for estimating bird species
abundance, but bioacoustic recordings are also common and just as successful or slightly more
so (Celis-Murillo et. al. 2009). Mist-netting, although less successful than the other methods, can

4. 4
be useful in capturing birds, including migrant species, that could not otherwise be identified
(Blake & Loiselle 2001).
Point counts were performed every other day at each site starting at 6:00am, for a total of
three counts at each site. Each point lasted for ten minutes during which time all species seen or
heard vocalizing in the area were recorded. Points were located 200m apart, and each point count
consisted of five points. Two Songmeter Wildlife Acoustics SM2+ recorders were used to collect
bioacoustic data. The Songmeters were placed at each site at ear-level and bioacoustics
recordings were collected every day for five days. Two-minute recordings were taken with three
minute intervals from 5:00am to 7:00 am. The Songmeters were moved each day, so that they
were placed at each point along the point count in their respective study sites over the five-day
period. Birds were captured using mist nests every other day at each site for a total of three days
at each site. Five nets were placed at each site, and were open for three hours each day starting at
6:00am, making a daily net effort of 15 hours/nets.
Data Analysis
All bird species data was compiled using Microsoft Excel. The data collected using the
three methods was combined to create an overall species list for both the Inundated Area (IN)
and Compensated Area (CP). Wilcoxon and chi-square (χ2
) analyses were performed using JMP
Pro 10. Rarefaction and biodiversity analyses were performed using PAST 3. Species richness
was assessed using the Shannon Index, as this is one of the most commonly used diversity
indices and tends to have low levels of variance (Chao & Tsung-Jen 2003, Nagendra 2002, Peet
1975, Spellerberg & Fedor 2003, Tóthmérész 1995). Bioacoustic data was processed using the
Cornell Lab of Ornithology’s software, RavenPro 1.4, as this program is useful in the analysis
and organization of bioacoustic recordings (Frommolt & Tauchert 2014). Sonograms of each

5. 5
two-minute recording were examined by experts (including the resource person for this paper)
for species identification.
Results
During the six-day research period, 1612 birds were counted, including 62 different
species (for a full list of species, see Appendix Table A). More birds were counted in IN overall,
and there were more species represented in IN than in CP (Table 1). However, there was no
significant difference between the total number of birds counted at the two sites (χ2
=1.5509,
DF=1, p=0.2130) or the between the number of species at each site (χ2
=0.1569, DF=1,
p=0.6921). The number of unique species (species only found in one of the two study sites, for a
full list see Appendix Table B) was higher in IN than in CP (Table 1), but this difference was not
significant (χ2
=0.7273, DF=1, p=0.3938).
Table 1. Total number of individuals, total number of species, daily average of individuals, and
unique species counted at each study site. Values in parentheses are ±1 standard deviation. Data
was collected April 24 to April 29, 2016, at the Lomas de Barbudal Biological Reserve and the
ASETREK farm.
Location Total individuals Total species Daily average individuals Unique species
CP 781 49 130 (72) 9
IN 831 53 139 (77) 13
The highest number of birds counted in one day were located at IN, and the number of
birds counted at each site varied greatly day by day (for daily bird counts, see Appendix Figure
A). The number of birds counted on average per day was higher in IN than in CP (Table 1), but
this difference was not significant (Wilcoxon, S=40, Z=0.08006, p=0.9362).
Corrected for the same number of individuals counted, species richness was higher in IN
than CP (Figure 1). For a given number of individuals counted, the number of species was 3.92
higher on average in IN than in CP. The Shannon Index of diversity indicated that IN had greater
diversity than CP (Table 2), and we found that the difference in species richness at the two sites

6. 6
was statistically significant (t=-3.5687, DF=1607.2, p=0.00036931).
Figure 1. Rarefaction analysis of number of individual birds counted compared to number of
species represented at the two locations. Rarefaction analysis was performed using PAST3. Data
was collected April 24 to April 29, 2016, at the Lomas de Barbudal Biological Reserve and the
ASETREK farm.
Table 2. Shannon Index of diversity H values for the two locations. Higher H value indicates
higher diversity. Data was collected April 24 to April 29, 2016, at the Lomas de Barbudal
Biological Reserve and the ASETREK farm.
Location H Variance
CP 2.9897 0.0015371
IN 3.1853 0.0014668
Discussion
Our prediction was correct that more birds and more species of birds would be counted in
IN than in CP. This was also true for the number of individuals counted on average per day and
the number of unique species counted per day. Although these differences were not significant as
0
10
20
30
40
50
60
1 101 201 301 401 501 601 701 801
Numberofspecies
Number of individuals
CP
IN

7. 7
raw data, when corrected for the same number of individuals using rarefaction species were
shown to accumulate faster in IN.
Given the raw data for species abundance, density, and uniqueness, it is possible that the
difference in forest maturity at the two sites was not a limiting factor on bird habitat preference.
Authors Smith et. al. (2011) found that habitat amount is a more important indicator of quality
than habitat fragmentation or matrix quality, so it is possible that the differences in forest age did
not significantly influence bird habitat selection. Other studies have found that birds may choose
habitats with tradeoffs in quality, such as areas higher predation risk in exchange for greater
availability of food (Johnson 2007). It is also possible that younger forests actually provide more
suitable habitat for some species than older forests (Powers et. al. 2008), and this may increase
rather than decrease diversity in these areas (Blake & Loiselle 2001). Alternatively, the close
proximity of the two locations may have masked any differences in habitat quality.
However, the higher species richness in IN, as shown by the rarefaction, supports our
hypothesis that IN would have higher diversity than CP because of the differences in forest age
at these locations. The Shannon Index of diversity also found that species richness was
significantly higher in IN, and the variance was low, which adds weight to these findings. This
diversity information is more useful than the comparisons of number of individuals counted,
species abundance, species density, and unique species because it also takes species evenness
into account (Hill 1973). Rarefaction also corrects for the number of individuals counted, making
the comparison between locations more accurate (Crist & Veech 2006, Evans & Gates 1997,
Hurlbert 2004). Authors James and Rathbun (1981) recommend that rarefaction be used in
junction with the Shannon Index of diversity in order to achieve the most accurate representation
of the sample populations. Therefore, although the differences in the overall number of

8. 8
individuals and number of species were not significant, the findings of the rarefaction and
diversity index indicate that IN should be considered more biologically diverse than CP. Because
bird species richness can be used as a proxy for habitat quality, it can thus be inferred that IN and
CP are not ecologically equivalent areas. These findings have important implications for the
RPRP, as the current plan assumes that CP is not less diverse than IN (OET 2016).
Conclusions
IN was shown to be significantly more diverse than CP in terms of bird species, and was
shown to accumulate species at a higher rate per individual than CP. While we have used the
forest maturity-quality hypothesis to infer that IN is a higher quality habitat than CP due to
differences in forest maturity, future studies should also examine other measures of the habitat
quality in order to better understand bird habitat preferences.
Given the finding that IN and CP are not ecologically equivalent due to significant
differences in bird species richness and diversity, we suggest that the Compensation Area be
expanded in order to account for the loss of biodiversity that will follow the construction of the
RPRP. We believe that protecting more land will be the most effective way of minimizing the
environmental impacts of the development project. We recommend that studies be performed in
order to determine the appropriate amount of land to be used as compensation given the
discrepancies in bird species diversity at the Inundated and Compensation Areas.
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Appendix
Table A. Species counted at both locations using all three methods (mist-netting, point counts,
and bioacoustic recordings). Data was collected April 24 to April 29, 2016, at the Lomas de
Barbudal Biological Reserve and the ASETREK farm.
Species (Common name) CP IN Total
Acadian Flycatcher 1 1 2
Amazilia sp 0 13 13
Banded Wren 42 12 54
Barred Antshrike 0 5 5
Black-headed Trogon 2 4 6
Blue-crowned Motmot 0 1 1
Boat-billed Flycatcher 3 2 5
Bright-rumped Attila 0 1 1
Brown-crested Flycatcher 48 34 82
Canivet's Emerald 0 1 1
Cinnamon Hummingbird 1 6 7
Common Pauraque 1 2 3
Dusky-capped Flycatcher 0 4 4
Elegant Trogon 21 24 45
Ferruginous Pygmy-Owl 46 27 73
Gartered Trogon 5 10 15
Great Kiskadee 22 13 35
Green-breasted Mango 0 1 1
Groove-billed Ani 3 0 3
Hoffmann's Woodpecker 85 36 121
Inca Dove 23 20 43
Ivory-billed Woodcreeper 0 1 1
Laughing Falcon 1 0 1
Lesser Greenlet 10 20 30
Lesser Ground-Cuckoo 0 2 2
Long-billed Gnatwren 0 4 4
Long-tailed Manakin 0 34 34
Mangrove Cuckoo 5 1 6
Masked Tityra 2 4 6
Northern-barred Woodcreeper 2 1 3
Olive Sparrow 3 20 23
Orange-chinned Parakeet 9 5 14
Orange-fronted Parakeet 3 3 6
Pale-billed Woodpecker 4 4 8
Plain-capped Starthroat 0 1 1

12. 12
Roadside Hawk 7 8 15
Rose-throated Becard 0 2 2
Rufous-and-white Wren 1 0 1
Rufous-capped Warbler 5 17 22
Rufous-naped Wren 76 82 158
Rufous-tailed Hummingbird 1 0 1
Scrub Euphonia 10 16 26
Social Flycatcher 9 5 14
Squirrel Cuckoo 6 23 29
Steely-vented Hummingbird 1 1 2
Streak-backed Oriole 17 1 18
Streaked Flycatcher 5 6 11
Stripe-headed Sparrow 1 0 1
Thicket Tinamou 82 112 194
Tropical Gnatcather 5 7 12
Tropical Kingbird 1 3 4
Turquoise-browed Motmot 83 75 158
White-fronted Parrot 17 26 43
White-lored Gnatcatcher 2 4 6
White-necked Puffbird 1 0 1
White-throated Magpie-Jay 9 1 10
White-tipped Dove 91 99 190
White-winged Dove 1 0 1
Yellow Warbler 1 0 1
Yellow-naped Parrot 1 11 12
Yellow-olive Flycatcher 5 15 20
Zone-tailed Hawk 1 0 1
Total 781 831 1612

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Table B. Unique species by location. Species were considered unique if they were counted in
only one of the two study sites. Data was collected April 24 to April 29, 2016, at the Lomas de
Barbudal Biological Reserve and the ASETREK farm.
Species (Common name) Location
Groove-billed Ani CP
Laughing Falcon CP
Rufous-and-white Wren CP
Rufous-tailed Hummingbird CP
Stripe-headed Sparrow CP
White-necked Puffbird CP
White-winged Dove CP
Yellow Warbler CP
Zone-tailed Hawk CP
Amazilia sp IN
Barred Antshrike IN
Blue-crowned Motmot IN
Bright-rumped Attila IN
Canivet's Emerald IN
Dusky-capped Flycatcher IN
Green-breasted Mango IN
Ivory-billed Woodcreeper IN
Lesser Ground-Cuckoo IN
Long-billed Gnatwren IN
Long-tailed Manakin IN
Plain-capped Starthroat IN
Rose-throated Becard IN

14. 14
Figure A. Number of individual birds counted per day at the two locations. Counts are for data
from all three data collection methods (point counts, bioacoustic recordings, and mist-netting).
No effort was made at IN on April 24, and only mist-netting (no bioacoustic recording) was
performed at CP on April 29. Data was collected April 24 to April 29, 2016, at the Lomas de
Barbudal Biological Reserve and the ASETREK farm.
0
50
100
150
200
250
Numberofindividuals
Date
CP
IN