DOI: 10.5061/dryad.00000003d
title: Data from: Species diversity and habitat use of birds in Menagesha Suba State Forest, central highlands of Ethiopia

description: This study was carried out to investigate the species diversity and
 habitat use of birds in the Menagesha Suba State forest and surrounding
 farmland. The study was conducted from July 2018 to January 2019 during
 the wet and dry seasons. The study area was stratified based on the
 dominant habitat types. A standardized survey technique was employed using
 systematically established point counts for all habitat types. EstimateS
 software (version 9.1) and Chi-square test were applied to analyze the
 data. A total of 122 bird species belonging to 14 orders and 49 families
 were identified in the study area during the two-season surveys. There was
 a statistically significant difference in the relative abundance of
 species among habitat types (χ2=81.928, df = 2, p&lt;0.05). During
 both seasons, the highest bird diversity was observed in farmland
 (H’=3.65), followed by plantation forest (H’=3.52). The lowest and highest
 distributions were observed in natural forests (J=0.77) and plantation
 forests (J=0.89), respectively. Variations in the number of bird species
 were observed among the three habitats. Species similarity was highest
 between natural forests and plantation forests during both the dry and wet
 seasons. There was a statistically significant difference in habitat use
 of bird species among the three habitat types either when seasons were
 considered separately (dry season: χ2 = 22.825, df = 6, P&lt;0.05; wet
 season: χ2 = 22.186, df = 6, P&lt;0.05) or when combined (χ2 = 26.658,
 df = 6, P&lt;0.05). The Menagesha Suba State forest is rich in endemic
 bird species to Ethiopia and shared with Eritrea, and more than 15% of
 bird species distributions are locally rare. There is a need for a
 detailed study of long duration on the diversity and other ecological
 aspects of forest bird species should be conducted to get exhaustive
 information.
description: 1. Sampling Design A stratified random sampling
 design was used to study bird species composition, abundance, habitat use,
 and relative distribution. The study site was stratified into three
 dominant habitat types: dry evergreen afro-montane forest, plantation
 forest, and farmland. A total of 80 sampling plots were systematically
 generated by a geographic information system (ESRI, 2012) using QGIS
 V2.18. The study area covers 9557 hectares, and the area is stratified
 into three dominant habitat types (Natural forest, Plantation forest, and
 Farmland). To avoid edge effects, sample plots were established 300 m away
 from the edge of each habitat type (natural forest, farmland, and
 plantation forest). Sampling plots were established proportional to each
 habitat type; as a result, in the dry evergreen Afro-montane forest 34
 sampling plots, in the plantation forest 10 sampling plots, and farmland
 36 sampling plots were established. The radius of each point count was
 fixed at 50m at the center of the sampling plots. To avoid double-counting
 of the birds, sampling plots were reasonably spaced out at 500 m in
 natural forest and plantation forest and 1000 meter in farmland (Bibby
 <i>et al</i>., 1998; Sutherland, 2006). Following Yosef Mamo
 <i>et al.</i> (2016), the Chao 1 richness estimator was
 computed in EstimateS to determine sampling adequacy. This estimator
 computes the total number of species (observed plus not observed during
 the survey though present in the area) expected to be present in a
 particular area (Colwell <i>et al</i>., 2012). Thus, the ratio
 of observed richness to Chao 1 estimated richness gives the proportional
 number of species recorded during the survey relative to the expected
 total number of species (Colwell, 2013). 2. Data
 Collection Data collection was carried out
 in two seasons; the wet season (July and August 2018) and the dry season
 (November 2018 and January 2019). In each season (dry and wet) two terms
 comprised a total of four data collection sessions. In each session each
 sampling plot in each habitat type was visited three times, making up a
 total of 6 visits of each sampling plot per season, and each sampling plot
 was visited 12 times. The observers start for all dominant habitats
 uniform from the southern point to the northern point because of the slope
 of the area that easily walks one point to other points without
 challenges. Observers stand in the center of one point and count over nine
 minutes per point count before walking through the area (Bibby<i> et
 al</i>., 1998). Data were collected
 early in the morning from 6:00 to 10:00 am and late in the afternoon from
 3:00 to 6.30 pm when birds are more active (Bibi and Ali, 2013). There
 were no censuses during rainy and cloudy days because such climatic
 conditions significantly affect the activities of birds and make the
 identification of bird species difficult (Bibby <i>et al</i>.,
 1998). While the observer stands in one location the bird species
 observed, the number of individuals, time of observation of vegetation
 (habitat) characteristics (species, height, cover type) of perching trees,
 and perching distance and activity of birds were carefully recorded. In
 addition, auxiliary data such as latitude and longitude, elevation, slope,
 and aspect were recorded using clinometers and GPS (Garmin 60). Birds were
 detected with the naked eye and with the help of a pair of binocular
 (Nikon 10*50). For identification of species present in the study area,
 plumage pattern, size, shape, color, songs, and calls were important
 parameters (Bibby <i>et al</i>., 1998; Sutherland, 2006;
 Shimelis Aynalem and Afework Bekele, 2008). Identifications of species are
 confirmed by using the Field guide book (Redman <i>et al.</i>,
 2009), and photographs and videos are taken to justify the species type
 which difficult to identify. Finally, the identified bird species are
 properly grouped into their
 taxonomic category. 3. Data
 Analysis Species diversity was
 computed in three approaches: species richness (number of species present
 in a particular area), evenness (relative abundance distribution of
 species), and Shannon diversity index (a heterogeneity measure that
 includes both species richness and evenness) (Colwell, 2013). Species
 richness was computed in EstimateS version 9.1 software (Colwell, 2013),
 using an individual-based sampling procedure. This was computed for each
 of the three habitat types separately for each season (i.e., dry and wet
 seasons) and pooled season, as well as for each season based on pooled
 habitat. As the treatments (habitat types or seasons) differed in sample
 size (i.e., number of individual birds recorded in each treatment
 category), both rarefaction of the observed number of species and
 extrapolation methods were used to calculate species richness and compare
 between respective treatments. Extrapolations were made up to twice the
 smallest (or smaller) sized sample size (i.e., twice the number of
 individuals recorded in the site with the smallest number of individual
 birds were recorded) (Addisu Asefa <i>et al</i>., 2017). In
 both rarefaction and extrapolation methods, mean richness was computed
 along with 95% confidence intervals based on 100 times sample
 randomization and used for comparisons between treatments. Following
 Addisu Asefa <i>et al.</i> (2017), two treatments were
 considered to be significantly different if they had non-overlapping 95%
 confidence intervals of species richness. Similarly, Chao 1 richness
 estimator was computed in EstimateS to determine sampling adequacy. This
 estimator computes the total number of species (observed plus not observed
 during the survey though present in the area) expected to be present in a
 particular area (Colwell <i>et al</i>., 2012). Thus, the ratio
 of observed richness to Chao 1 estimated richness gives the proportional
 number of species recorded during the survey relative to the expected
 total number of species (Colwell, 2013). <b>Shannon
 index of diversity:</b> It was being calculated using the formula
 below: <i>H</i><sup><i>I</i></sup><i>=-</i><i>PilnPi</i> Where P<i>i</i>: The proportion of the <i>i</i><sup>th</sup> species to total abundance value P<i>i</i>= n<i>i</i>/N<i>i</i>. Ln P<i>i</i>: the natural logarithm of P<i>i</i>. <b>Evenness (Shannon-Wiener's Equitability) index (J): </b>It was calculated using the formula below: <b><i>J=</i></b><b><i>H</i></b><sup><b><i>I</i></b></sup><b><i>H</i></b><sup><b><i>max</i></b></sup> Where; H<sup>max</sup>= lnS Where, H<sup>I</sup> is Shannon-Wiener's diversity index, H<sup>max </sup>is the maximum value of H<sup>I</sup> and S is Species richness. <b>Simpson’s Diversity Index ‘D’</b> was calculated using the formula below: <b><i>D=1-</i></b><b><i><sup>Pi</sup></i></b><sup><b><i><sup>2</sup></i></b></sup> Where P<i>i</i>: The proportion of the <i>i</i><sup>th</sup> species to total abundance value P<i>i</i>= n<i>i</i>/N<i>i</i>. <b>Bird Species Similarity</b> Sorensen’s similarity index was calculated using the following equation: <b><i>Cs=</i></b><b><i>2ab</i></b><b><i>a+b</i></b> Where <i>a </i>is the number of species found in site A; <i>b </i>is the number of species in site B and <i>ab </i>is the number of species shared by the two sites (Bibi and Ali, 2013). <b>Relative Abundance</b> The relative abundance of each species in each habitat type was calculated using a simple formula: <i>RAi=</i><i>ni</i><i>Tni</i>   Where, RAi = relative abundance of species i; ni = number of individual birds (abundance) of species i recorded in a particular habitat; and Tni = the total number of individual birds recorded in that habitat. Based on these RA values, each species was classified into four relative abundance categories: Abundant (the top abundant species whose sum of RA values equals 0.25), Common (the second top abundant species whose sum of RA values equals 0.25), Uncommon (the third top abundant species whose sum of RA values equals to 0.25), and Rare (the least abundant species whose sum of RA values equals to 0.25) (Addisu Asefa, 2014). Then, the number of species classified in each relative abundance category was computed and the difference in the number of species classified in each relative abundance category was tested using the chi-square test in SPSS version 20 software. This was conducted separately for each season and season combined.
description: The data sets analyzed during the current study are available
 from the corresponding author (H.T) upon request.