Abundance Of Bird Populations Research Articles

Evaluating community-wide temporal sampling in passive acoustic monitoring: A comprehensive study of avian vocal patterns in subtropical montane forests.

From passive acoustic monitoring (PAM) recordings, the vocal activity rate (VAR), vocalizations per unit of time, can be calculated and is essential for assessing bird population abundance. However, VAR is subject to influences from a range of factors, including species and environmental conditions. Identifying the optimal sampling design to obtain representative acoustic data for VAR estimation is crucial for research objectives. PAM commonly uses temporal sampling strategies to decrease the volume of recordings and the resources needed for audio data management. Yet, the comprehensive impact of this sampling approach on VAR estimation remains insufficiently explored. In this study, we used vocalizations extracted from recordings of 12 bird species, taken at 14 PAM stations situated in subtropical montane forests over a four-month period, to assess the impact of temporal sampling on VAR across three distinct scales: short-term periodic, diel, and hourly. For short-term periodic sampling analysis, we employed hierarchical clustering analysis (HCA) and the coefficient of variation (CV). Generalized additive models (GAMs) were utilized for diel sampling analysis, and we determined the average difference in VAR values per minute for the hourly sampling analysis. We identified significant day and species-specific VAR fluctuations. The survey season was divided into five segments; the earliest two showed high variability and are best avoided for surveys. Data from days with heavy rain and strong winds showed reduced VAR values and should be excluded from analysis. Continuous recordings spanning at least seven days, extending to 14 days is optimal for minimizing sampling variance. Morning chorus recordings effectively capture the majority of bird vocalizations, and hourly sampling with frequent, shorter intervals aligns closely with continuous recording outcomes. While our findings are context-specific, they highlight the significance of strategic sampling in avian monitoring, optimizing resource utilization and enhancing the breadth of monitoring efforts.

Census of breeding birds in the Pyrenees in the early 1980s: A publicly available dataset for ecological research.

The Pyrenees is a mountain range in south-western Europe that supports a rich diversity of bird species. In 1981, point count surveys of breeding birds (passerines and picidae) were carried out in the Vanera valley, a valley in the eastern Pyrenees, resulting in a data set of 228 counts. These data provide valuable information on the distribution and abundance of bird populations on 5350 ha of heterogeneous land (including cropland, grasslands, heaths and river banks, and pine forest) at altitudes ranging from 1100 to 2600 meters. Additional point count surveys were carried out in the pine forest from 1982 to 1985, resulting in a data set of 144 counts. Habitat descriptors (percentage of herbaceous and ligneous plant cover at different heights - 0-1m, 1-4m and more than 8m; vegetation type) and altitude were assessed around each point count. This dataset provides a complete picture of the breeding bird community in a typical valley of eastern Pyrenees in the early 1980s, which could be compared with future censuses to contribute to a variety of research questions, such as quantifying changes in birds between the early 1980s and now in mountain areas, understanding the effects of climate change on bird populations, examining the effects of habitat fragmentation and land-use change, and identifying priority areas for conservation and management. These data could inspire new research and contribute to our collective understanding of bird ecology in the Pyrenees.

Spatial modeling of the relative abundance of wading birds in peninsular Florida using citizen science data

AbstractRecent literature has shown citizen science data that include reported counts, such as observations from the eBird database, can be used to model the relative abundance of selected species. The objective of our study was to extend on both the methodology and the range of species considered by previous research on relative abundance modeling; we selected the Floridian peninsula as our geographical area of interest. We confirmed that, much like for other bird species and geographical areas, modeling such data with a classic Poisson generalized linear model was not appropriate due to overdispersion. Moreover, assuming linearity for the effects of all environmental and observer effort covariates on relative abundance was shown to be overly simplistic. These concerns led us to consider a variety of potentially suitable modeling techniques; the quasi‐Poisson generalized additive model displayed the best combination of flexibility, strong predictive performance, and ease of interpretation. Expanding on previous research for eBird data, we chose to explicitly incorporate spatial dependence into the modeling task by performing hierarchical generalized additive modeling with a spatial conditional autoregressive structure for random effects. This practice allows us to account for spatial factors not represented by model covariates, such as species dispersal patterns or colonial breeding habits. After conducting appropriate testing procedures and fitting spatially explicit models, we found that our data contain moderate spatial dependence and that spatially explicit models have overall superior predictive performance to models that do not account for spatial dependence. Upon closer inspection, spatially explicit models perform especially well compared with their nonspatial counterparts in identifying situations with low abundance, with a negligible trade‐off in prediction accuracy for situations with high abundance. We conclude that quasi‐Poisson hierarchical generalized additive models with spatial random effects provide the best representation of the relative abundance of bird populations. Moreover, our spatially explicit models are more realistic based on domain knowledge when regarding the impact of environmental covariates, which is important when considering conservation implications and future projections.

Summer bird populations of burnt bog-forest land of the Kerzhensky Nature Reserve ten years after wildfires (Central Volga region, Russia)

The bird population was monitored during ten years in the Kerzhensky Nature Reserve damaged by severe wildfires in 2010. In the burned territory 126 bird species (120 species in the breeding season) were noted, for which weighted averages of bird abundance were calculated. It was noted that the number of species was increasing gradually in the breeding season. The birds of forest edges and of dry valleys appeared already during the second post-fire year, but their abundance increased only in the third-fourth year. The bird population abundance has increased almost 2 times in the breeding season over ten years, while it has not increased significantly in the post-breeding season. The total biomass and the transformed energy, on the contrary, decreased especially in the post-breeding season. During the first six years Fringilla coelebs Linnaeus, 1758 was the absolute leader at the abundance, and its co-dominant was Anthus trivialis (Linnaeus, 1758), and in last two years Phylloscopus trochilus (Linnaeus, 1758) was the leader. The share of the leaders in the breeding season gradually decreased, and the species diversity and the alignment grew. The birds fed in the breeding season mostly on the soil surface. The share of shrubby species increased by two times a couple of years after the wildfires, and the share of crowns birds increased after another four years. The similarity of the ornithocomplex of the burnt territory in the first and last two years of the research amounted to only 0.63 units (the Sorensen-Chekanovsky index).

Meta-analysis shows that overabundant deer (Cervidae) populations consistently decrease average population abundance and species richness of forest birds

AbstractLocal-scale studies have shown that an overabundance of Cervidae species (deer, elk, moose) impacts forest bird communities. Through meta-analysis, we provide a generalized estimate of the overall direction and magnitude of the indirect effects overabundant cervids have on avian species. We conducted 2 distinct meta-analyses that synthesized data on 130 bird species collected from 17 publications. These analyses compared bird species’ population abundance and/or species richness at sites with overabundant cervids to sites with lower cervid abundance or without cervids. We evaluated whether the impacts of overabundant cervids are generally in the same direction (positive, negative) across avian species and locations and if effects vary in magnitude according to avian nesting location and foraging habitat. We found that where cervids were overabundant, there was a significant decrease in mean bird population abundance and species richness. Species that nest in trees, shrubs, and on the ground showed the largest decreases in abundance, as did species whose primary habitat is forest and open woodland and species that are primarily insectivores or omnivores. We did not find significant decreases in abundance for avian species that nest in cavities, whose primary habitat is grassland or scrub, nor for species that mainly eat seeds. Our results indicate that overabundant cervids, likely through their direct effects on vegetation and indirect effects on insects and forest birds, negatively impact individual bird populations and decrease overall avian species richness.

Pushing back the baseline: a novel approach to detect long-term changes in terrestrial faunal abundance using historical qualitative descriptions

AbstractStudies that examine changes in the populations of flora and fauna often do so against a baseline of relatively recent distribution data. It is much rarer to see evaluations of population change over the longer–term in order to extend the baseline back in time. Here, we use two methods (regression analysis and line of equality) to identify long-term differences in abundance derived from qualitative descriptions, and we test the efficacy of this approach by comparison with contemporary data. We take descriptions of bird population abundance in Cambridgeshire, UK, from the first half of the 19th century and compare these with more recent estimates by converting qualitative descriptions to an ordinal scale. We show, first, that the ordinal scale of abundance corresponds well to quantitative estimates of density and range size based on current data, and, second, that the two methods of comparison revealed both increases and declines in species, some of which were consistent using both approaches but others showed differing responses. We also show that the regional rates of extinction (extirpation) for birds are twice as high as equivalent rates for plants. These data extend analyses of avifaunal change back to a baseline 160-190 years before present, thus bringing a novel perspective on long-term change in populations and categories of conservation concern (e.g., Amber- or Red-lists) based on recent data. Changes in status are discussed in relation to various factors, although perhaps the most pervasive were of anthropogenic origin.

Precipitation and winter temperature predict long-term range-scale abundance changes in Western North American birds.

Predicting biodiversity responses to climate change remains a difficult challenge, especially in climatically complex regions where precipitation is a limiting factor. Though statistical climatic envelope models are frequently used to project future scenarios for species distributions under climate change, these models are rarely tested using empirical data. We used long-term data on bird distributions and abundance covering five states in the western US and in the Canadian province of British Columbia to test the capacity of statistical models to predict temporal changes in bird populations over a 32-year period. Using boosted regression trees, we built presence-absence and abundance models that related the presence and abundance of 132 bird species to spatial variation in climatic conditions. Presence/absence models built using 1970-1974 data forecast the distributions of the majority of species in the later time period, 1998-2002 (mean AUC=0.79±0.01). Hindcast models performed equivalently (mean AUC=0.82±0.01). Correlations between observed and predicted abundances were also statistically significant for most species (forecast mean Spearman's ρ=0.34±0.02, hindcast=0.39±0.02). The most stringent test is to test predicted changes in geographic patterns through time. Observed changes in abundance patterns were significantly positively correlated with those predicted for 59% of species (mean Spearman's ρ=0.28±0.02, across all species). Three precipitation variables (for the wettest month, breeding season, and driest month) and minimum temperature of the coldest month were the most important predictors of bird distributions and abundances in this region, and hence of abundance changes through time. Our results suggest that models describing associations between climatic variables and abundance patterns can predict changes through time for some species, and that changes in precipitation and winter temperature appear to have already driven shifts in the geographic patterns of abundance of bird populations in western North America.

Successful restoration of water level and surface area restored migrant bird populations in a Hungarian wetland

Water level and water surface area fluctuations are important factors determining abundance of bird populations and bird assemblages structure in a wetland habitat. The water level and water surface area of the Marsh Tomord (West Hungary) changed drastically between 1998 and 2008, and the marsh dried out because of scarce rainfall in 2000 and 2001. A habitat restoration in winter 2001 repaired the waterholding capacity of the marsh. We analyzed changes in parameters of bird assemblages in investigated wetland area in relation of environmental factors. We used full redundancy analysis (RDA) on number of caugth migratory birds per year, species richness, diversity and evenness of bird assemblages to examine correlations among water level, water surface area and vegetation core. Species like water rail, common snipe, river warbler, Savi’s warbler, great reed warbler, reed warbler, marsh warbler, sedge warbler, reed bunting showed high and positive linear correlations with the water level and water surface area in the postbreeding period. Some wetland species, sedge warbler, Savi’s warbler and reed bunting as well as total number of caugth birds per year and total numbers of caugth species per year were clearly associated with thick marsh vegetation. According to our results the bird species composition of the wetland might have returned to the prerestoration levels and surface areas.

Associations between multiscale landscape characteristics and breeding bird abundance and diversity across urban-rural gradients in Northeastern Georgia, USA

Urbanization is rapidly changing the southeastern US landscape, particularly in Georgia within and around the Atlanta metropolitan area, the fastest-growing Southeastern population center. Landscape characteristics related to human disturbance, landscape composition, and landscape configuration vary across the urban-rural gradient and are easily and inexpensively evaluated using geographic information systems (GIS). Previous studies have suggested that avian communities and populations respond in scale-dependent ways to urbanization-related landscape changes through changes in abundance and diversity. We conducted a 2-year study (2007–2008) of the response of breeding bird population abundance, community abundance, species richness, and relative diversity in young and mature single-family residential areas to 15 landscape characteristics measured at multiple spatial scales across urban-rural development intensity gradients near Athens, Georgia. We grouped birds by species, entire site assemblage, and by functional guild affiliation. Our models suggest strong relationships between the landscape and both community and population abundance of birds, as well as a somewhat weaker relationship with species richness. We detected only a weak relationship between breeding season relative diversity and landscape characteristics; we hypothesize a possible seasonal component to that relationship based on an earlier study. Our results suggest that widely available geospatial metrics of human disturbance and landscape pattern can be used to model breeding bird abundance and diversity across urban-rural gradients. This study sets the framework for a landscape scale understanding of the effects of housing developments and development intensity on breeding birds in northeastern Georgia and such a landscape-based approach to modeling species numbers represents a valuable tool in natural resources management.

Effect of remote spatial connections on the population dynamics of passerine birds

45 Assessment of global environmental changes caused by both economic activity and factors other than anthropogenic ones is an urgent ecological problem [1]. Habitat deterioration, both direct and indirect, via destruction of spatial connections, results in animal population decline throughout the world [2]. Monitoring of these changes is necessary for comparing the situations in large regions. Birds may serve as special indicator organisms, because changes in their abundance are informative with respect to the state of vast geographical regions. Like other vertebrates, birds produce an integrated response to the environment rather than to individual factors; however, birds are much less restricted in movements. Avian communities are diverse, abundant, and relatively easy to observe. Because of this, studying the abundance of bird populations for many years is assumed to be a promising field of biological monitoring. The most interesting results were obtained when this indicator was used to assess the influence of pesticides and

FIELD TESTS OF THE ROSENBERG-BLANCHER METHOD FOR CONVERTING POINT COUNTS TO ABUNDANCE ESTIMATES

Abstract The North American Breeding Bird Survey (BBS) provides a widely used source of information on changes in bird population abundance based on data obtained for >50 years by 3-min point counts (Sauer et al. 2005). Rosenberg and Blancher (2005) provided a method that purports to convert BBS data into estimates of absolute abundance. To test this method, we compiled detection efficiencies using BBS protocol at five stations in southern New York where territories of most breeding birds were known. Following the Rosenberg-Blancher method, we assigned species to distance categories, within which it is assumed that the equivalent of 100% of a species will be detected. Field results show that individual detection efficiencies varied from 3% to 49% among 29 species. These values are similar to results from other field studies. Most males did not sing within a 3-min count during June, and the detection distances assumed by the method are much too high. We recommend that conservation priorities of the Landbir...

Evaluation of Two Methods to Estimate and Monitor Bird Populations

BackgroundEffective management depends upon accurately estimating trends in abundance of bird populations over time, and in some cases estimating abundance. Two population estimation methods, double observer (DO) and double sampling (DS), have been advocated for avian population studies and the relative merits and short-comings of these methods remain an area of debate.Methodology/Principal FindingsWe used simulations to evaluate the performances of these two population estimation methods under a range of realistic scenarios. For three hypothetical populations with different levels of clustering, we generated DO and DS population size estimates for a range of detection probabilities and survey proportions. Population estimates for both methods were centered on the true population size for all levels of population clustering and survey proportions when detection probabilities were greater than 20%. The DO method underestimated the population at detection probabilities less than 30% whereas the DS method remained essentially unbiased. The coverage probability of 95% confidence intervals for population estimates was slightly less than the nominal level for the DS method but was substantially below the nominal level for the DO method at high detection probabilities. Differences in observer detection probabilities did not affect the accuracy and precision of population estimates of the DO method. Population estimates for the DS method remained unbiased as the proportion of units intensively surveyed changed, but the variance of the estimates decreased with increasing proportion intensively surveyed.Conclusions/SignificanceThe DO and DS methods can be applied in many different settings and our evaluations provide important information on the performance of these two methods that can assist researchers in selecting the method most appropriate for their particular needs.

Estimating Detection Probabilities From Multiple-Observer Point Counts

Abstract Point counts are commonly used to obtain indices of bird population abundance. We present an independent-observer point-count method, a generalization of the dependent-observer approach, based on closed-population capture- recapture methods. The approach can incorporate individual covariates, such as detection distance, to account for individual differences in detection probabilities associated with measurable sources of variation. We demonstrate a negative bias in two-observer estimates by comparing abundance estimates from two- and four- observer point counts. Models incorporating data from four independent observers were capable of accounting for this bias. Modeling individual bird differences in detection probabilities produced abundance estimates 15–21% higher than models that did not account for individual differences, in four out of five data sets analyzed. Although independent-observer methods are expensive and impractical for large- scale applications, we believe they can provide important insights into the sources and degree of perception bias (i.e., probability of detecting an individual, given that it is available for detection) in avian point-count estimates. Therefore, they may be useful in a two-stage sampling framework to calibrate larger surveys based on single-observer estimates. Estimación de Probabilidades de Detección a Partir de Conteos en Puntos Hechos por Varios Observadores

ESTIMATING DETECTION PROBABILITIES FROM MULTIPLE-OBSERVER POINT COUNTS

Abstract Point counts are commonly used to obtain indices of bird population abundance. We present an independent-observer point-count method, a generalization of the dependent-observer approach, based on closed-population capture- recapture methods. The approach can incorporate individual covariates, such as detection distance, to account for individual differences in detection probabilities associated with measurable sources of variation. We demonstrate a negative bias in two-observer estimates by comparing abundance estimates from two- and four- observer point counts. Models incorporating data from four independent observers were capable of accounting for this bias. Modeling individual bird differences in detection probabilities produced abundance estimates 15–21% higher than models that did not account for individual differences, in four out of five data sets analyzed. Although independent-observer methods are expensive and impractical for large- scale applications, we believe they can provide importa...

Monitoring the Abundance of Bird Populations

Monitoring the Abundance of Bird Populations

Long-Term Trends in Bird Populations on an Electric Transmission Right-of-Way

We conducted a 2-year study of bird populations on the Green Lane Research and Demonstration Project, which is located along a 500-kV transmission line right-of-way (ROW) of the Philadelphia Electric Company, in the Piedmont Province, Montgomery County, Pennsylvania, U.S., in spring and summer 2001 and 2002. The objectives of our study were to (1) determine the diversity and relative abundance of bird populations in spring versus summer on the ROW, (2) compare bird use among five representative treatment units of the ROW, and (3) compare use of wire zones versus border zones on the ROW. In addition, bird populations in this study were compared to those observed on the ROW in 1987 and 1988. Forty-four species (including one hybrid) were observed on the ROW during 2001 and 2002. In 1987 and 1988 combined, 42 species were noted on the ROW; thus, despite continued mechanical and herbicidal maintenance of the right-of-way, the bird community has changed very little over the past 15 years. More species were observed on the ROW in spring than in summer. Common bird species on the ROW in one or both seasons were those adapted to early successional or edge habitats. Total abundance of all species combined, however, was higher in summer than in spring, in part because of the presence of many family groups (parents and fledgling young). Most species were found in the mowing plus herbicide unit and the fewest were noted in the foliage-spray unit. Considerably more birds were observed in border zones than in wire zones of the ROW. Thus, border zones are very important habitat for birds along a ROW, with its combination of shrub­forb­grass cover type.

ANALYSIS OF POPULATION TRENDS FOR FARMLAND BIRDS USING GENERALIZED ADDITIVE MODELS

Knowledge of the direction, magnitude, and timing of changes in bird population abundance is essential to enable species of priority conservation concern to be identified, and reasons for the population changes to be understood. We give a brief review of previous techniques for the analysis of large-scale survey data and present a new approach based on generalized additive models (GAMs). GAMs are used to model trend as a smooth, nonlinear function of time, and they provide a framework for testing the statistical significance of changes in abundance. In addition, the second derivatives of the modeled trend curve may be used to identify key years in which the direction of the population trajectory was seen to change significantly. The inclusion of covariates into models for population abundance is also discussed and illustrated, and tests for the significance of covariate terms are given. We apply the methods to data from the Common Birds Census of the British Trust for Ornithology for 13 species of farmland birds. Seven of the species are shown to have experienced statistically significant declines since the mid-1960s. Two species exhibited a significant increase. The population trajectories of all but three species turned downward in the 1970s, although in most cases the 1980s brought either some recovery or a decrease in the rate of decline. The majority of populations have remained relatively stable in the 1990s. The results are comparable with those from other analysis techniques, although the new approach is shown to have advantages in generality and precision. We suggest extensions of the methods and make recommendations for the design of future surveys.