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With many of the world's migratory bird populations in alarming decline, broad-scale assessments of responses to migratory hazards may prove crucial to successful conservation efforts. Most birds migrate at night through increasingly light-polluted skies. Bright light sources can attract airborne migrants and lead to collisions with structures, but might also influence selection of migratory stopover habitat and thereby acquisition of food resources. We demonstrate, using multi-year weather radar measurements of nocturnal migrants across the northeastern U.S., that autumnal migrant stopover density increased at regional scales with proximity to the brightest areas, but decreased within a few kilometers of brightly-lit sources. This finding implies broad-scale attraction to artificial light while airborne, impeding selection for extensive forest habitat. Given that high-quality stopover habitat is critical to successful migration, and hindrances during migration can decrease fitness, artificial lights present a potentially heightened conservation concern for migratory bird populations.

The size of animal home ranges often varies inversely with population density among populations of a species. This fact has implications for population monitoring using spatially explicit capture–recapture (SECR) models, in which both the scale of home-range movements σ and population density D usually appear as parameters, and both may vary among populations. It will often be appropriate to model a structural relationship between population-specific values of these parameters, rather than to assume independence. We suggest re-parameterizing the SECR model using kp = σp √Dp, where kp relates to the degree of overlap between home ranges and the subscript p distinguishes populations. We observe that kp is often nearly constant for populations spanning a range of densities. This justifies fitting a model in which the separate kp are replaced by the single parameter k and σp is a density-dependent derived parameter. Continuous density-dependent spatial variation in σ may also be modelled, using a scaled non-Euclidean distance between detectors and the locations of animals. We illustrate these methods with data from automatic photography of tigers Panthera tigris across India, in which the variation is among populations, from mist-netting of ovenbirds Seiurus aurocapilla in Maryland, USA, in which the variation is within a single population over time, and from live-trapping of brushtail possums Trichosurus vulpecula in New Zealand, modelling spatial variation within one population. Possible applications and limitations of the methods are discussed. A model in which kp is constant, while density varies, provides a parsimonious null model for SECR. The parameter k of the null model is a concise summary of the empirical relationship between home-range size and density that is useful in comparative studies. We expect deviations from this model, particularly the dependence of kp on covariates, to be biologically interesting.

Despite using the aerosphere for many facets of their life, most flying animals (i.e., birds, bats, some insects) are still bound to terrestrial habitats for resting, feeding, and reproduction. Comprehensive broad-scale observations by weather surveillance radars of animals as they leave terrestrial habitats for migration or feeding flights can be used to map their terrestrial distributions either as point locations (e.g., communal roosts) or as continuous surface layers (e.g., animal densities in habitats across a landscape). We discuss some of the technical challenges to reducing measurement biases related to how radars sample the aerosphere and the flight behavior of animals. We highlight a recently developed methodological approach that precisely and quantitatively links the horizontal spatial structure of birds aloft to their terrestrial distributions and provides novel insights into avian ecology and conservation across broad landscapes. Specifically, we present case studies that (1) elucidate how migrating birds contend with crossing ecological barriers and extreme weather events, (2) identify important stopover areas and habitat use patterns of birds along their migration routes, and (3) assess waterfowl response to wetland habitat management and restoration. These studies aid our understanding of how anthropogenic modification of the terrestrial landscape (e.g., urbanization, habitat management), natural geographic features, and weather (e.g., hurricanes) can affect the terrestrial distributions of flying animals.

The national network of weather surveillance radars (WSR-88D) detects flying birds and is a useful remote-sensing tool for ornithological study. We used data collected during fall 2008 and 2009 by 16 WSR-88D radars in the northeastern U.S. to quantify the spatial distribution of landbirds during migratory stopover. We geo-referenced estimates based on radar reflectivity, of the density of migrants aloft at their abrupt evening exodus from daytime stopover sites, to the approximate locations from which they emerged. We classified bird stopover use by the magnitude and variation of radar reflectivity across nights; areas were considered “important” stopover sites for conservation if bird density was consistently high. We developed statistical models that predict potentially important stopover sites across the region, based on land cover, ground elevation, and geographic location. Large areas of regionally important stopover sites were located along the coastlines of Long Island Sound, throughout th...

We examined the effects of habitat change on Cerulean Warbler (Dendroica cerulea) populations at stops along Breeding Bird Survey (BBS) routes in the central Appalachians. We used aerial photographs to compare early (1967/1971), middle (1982/1985), and late (2000/2003) periods and compared 1992 and 2001 National Land Cover Data (NLCD). Mean Cerulean Warbler detections per stop decreased at 68 BBS stops between the early (0.05) and middle (0.01) time periods and their distribution became more restricted (15 vs. 3% of stops), but the amount of deciduous/mixed forest increased. Mean detections at 240 stops decreased from the middle (0.09) to the late (0.06) time periods, but the deciduous/mixed forest land cover and fragmentation metrics did not change. The amounts of deciduous/mixed forest, core forest area, and edge density in the NLCD analysis decreased from 1992 to 2001, whereas the amount of non-forest land cover increased. The number of Cerulean Warbler detections did not change (1992 = 0.08...

Conservation and management actions often have direct and indirect effects on a wide range of species. As such, it is important to evaluate the impacts that such actions may have on both target and non-target species within a region. Understanding how species richness and composition differ as a result of management treatments can help determine potential ecological consequences. Yet it is difficult to estimate richness because traditional sampling approaches detect species at variable rates and some species are never observed. We present a framework for assessing management actions on biodiversity using a multi-species hierarchical model that estimates individual species occurrences, while accounting for imperfect detection of species. Our model incorporates species-specific responses to management treatments and local vegetation characteristics and a hierarchical component that links species at a community-level. This allows for comprehensive inferences on the whole community or on assemblages of interest. Compared to traditional species models, occurrence estimates are improved for all species, even for those that are rarely observed, resulting in more precise estimates of species richness (including species that were unobserved during sampling). We demonstrate the utility of this approach for conservation through an analysis comparing bird communities in two geographically similar study areas: one in which white-tailed deer (Odocoileus virginianus) densities have been regulated through hunting and one in which deer densities have gone unregulated. Although our results indicate that species and assemblage richness were similar in the two study areas, point-level richness was significantly influenced by local vegetation characteristics, a result that would have been underestimated had we not accounted for variability in species detection.

— Point counts are used widely to index bird populations. Variation in the proportion of birds counted is a known source of error, and for robust inference it has been advocated that counts be converted to estimates of absolute population size. We used simulation to assess nine methods for the conduct and analysis of point counts when the data included distance-related heterogeneity of individual detection probability. Distance from the observer is a ubiquitous source of heterogeneity, because nearby birds are more easily detected than distant ones. Several recent methods (dependent double-observer, time of first detection, time of detection, independent multiple-observer, and repeated counts) do not account for distance-related heterogeneity, at least in their simpler forms. We assessed bias in estimates of population size by simulating counts with fixed radius w over four time intervals (occasions). Detection probability per occasion was modeled as a half-normal function of distance with scale ...

Distance-sampling methods are commonly used in studies of animal populations to estimate population density. A common objective of such studies is to evaluate the relationship between abundance or density and covariates that describe animal habitat or other environmental influences. However, little attention has been focused on methods of modeling abundance covariate effects in conventional distance-sampling models. In this paper we propose a distance-sampling model that accommodates covariate effects on abundance. The model is based on specification of the distance-sampling likelihood at the level of the sample unit in terms of local abundance (for each sampling unit). This model is augmented with a Poisson regression model for local abundance that is parameterized in terms of available covariates. Maximum-likelihood estimation of detection and density parameters is based on the integrated likelihood, wherein local abundance is removed from the likelihood by integration. We provide an example using avian point-transect data of Ovenbirds (Seiurus aurocapillus) collected using a distance-sampling protocol and two measures of habitat structure (understory cover and basal area of overstory trees). The model yields a sensible description (positive effect of understory cover, negative effect on basal area) of the relationship between habitat and Ovenbird density that can be used to evaluate the effects of habitat management on Ovenbird populations.

Models predicting the occurrence of area-sensitive bird species in forests were developed from bird survey data from 499 forests in Prince George's County, Maryland. The predicted probabilities of occurrence for species were integrated with forest cover data for the County in a Geographic Information System (GIS). This information was used in combination with local zoning and forest conservation requirements to develop a preliminary forest conservation plan for the watershed of the Western Branch of the Patuxent River. We identify forests patches most likely to support breeding populations of area-sensitive birds, and use the GIS to devise ways to consolidate and link them. Forests that do not contribute significantly to the integrity of these priority forests are designated as sites in which development could occur. The resulting conservation plan will maintain and enhance breeding habitat for area-sensitive forest birds, while still allowing for additional development as human populations increase.

We used capture-recapture methods to estimate bird species richness from mist-net and point-count data from a study area in Campeche, Mexico. We estimated species richness separately for each survey technique for two habitats, forest and pasture, in six sampling periods. We then estimated richness based on species' detections by either technique, and estimated the proportion of species detected by each technique that are not part of the population sampled by the other technique. No consistent differences existed between richness estimates from count data and from capture data in the two habitats. In some sampling periods, over 50% of the richness estimate from one survey technique may be species that are not sampled by the other technique, suggesting that one technique may not be adequate to estimate total species richness and that comparing estimates from areas sampled by different techniques may not be valid.

Nine marsh sites were selected in Maryland, Delaware, and New Jersey to assess the importance of ponds created by Open Marsh Water Management (OMWM) to migratory birds. Ateight of the nine sites, OMWM ponds were paired with areas of similar-sized natural ponds. Eleven aerial surveys were conducted, mostly in fall and winter of 1987 and 1988 to compare relative use of ponds and sites by black ducks (Anas rubripes), other waterfowl, shorebirds, wading birds, gulls, and other species of birds. We noted a high degree of variation in bird use. Seasonal effects were significant, but treatment (OMWM vs. natural ponds) effect was not. Water/marsh (W/M) area ratio was positively correlated with waterfowl and black ducks, but pond number was not. Larger ponds (>0.25 ha) tended to be used more than smaller ponds by most bird species.

s of Workshop Research Presentations This section provides extended abstracts of the research presentations given on the first day and a half of the workshop. (Presenting Author’s name is in bold; full contact information for presenting authors is found in the “Contact Information” section; see “References Cited” section for full reference citations). Disclaimer – All presentations at the workshop were for informational purposes only. Neither the USGS nor the USFWS endorses any products promoted during the workshop. Primer on Radar Biology and Applications to Conservation Issues Ron Larkin, Illinois Natural History Survey, Champaign, Ill. This lecture is based primarily on two book chapters (Larkin, 2005; Diehl and Larkin, 2005). The brief summary here does not do justice to those more thorough treatments of the subject. Because bats make up an unknown and possibly appreciable part of the radar-echo-producing flying animals in many situations, and because arthropods are also often prominent, it is best to speak of radar biology rather than radar ornithology and "flying vertebrates" rather than "birds."

The probability that a site has at least one individual of a species (‘occupancy') has come to be widely used as a state variable for animal population monitoring. The available statistical theory for estimation when detection is imperfect applies particularly to habitat patches or islands, although it is also used for arbitrary plots in continuous habitat. The probability that such a plot is occupied depends on plot size and home-range characteristics (size, shape and dispersion) as well as population density. Plot size is critical to the definition of occupancy as a state variable, but clear advice on plot size is missing from the literature on the design of occupancy studies. We describe models for the effects of varying plot size and home-range size on expected occupancy. Temporal, spatial, and species variation in average home-range size is to be expected, but information on home ranges is difficult to retrieve from species presence/absence data collected in occupancy studies. The effect of variable ...

We measured the diameter at breast height of all trees and shrubs 25 meters in height, including standing dead trees, on 68 0.04-hectare study plots in a montane, subtropical rain forest on Mauna Loa, Hawai'i. The canopy species consisted of 88 percent Metrosideros polymorpha (ohia) and 12 percent Acacia koa (koa). Negative associations were found between the densities of koa and ohia, the density of koa and the total basal area of ohia, and the total basal areas of koa and ohia. The two-species lottery competition model, a stochastic model in which the coexistence of two species in a space-limited community results from temporal variation in recruitment and death rates, predicts a quadratic-beta distribution for the proportion of space occupied by each species. A discrete version of the quadraticbeta distribution, the quadratic-beta binomial distribution, was fit to the live koa and ohia densities and assessed with goodness-of-fit tests. Likelihood ratio tests provided evidence that the mean adult death rates of the two species were equal but that the relative competitive abilities of the two species favored ohia. These tests were corroborated by a contingency table analysis of death rates based on standing dead trees and growth rate studies which report that koa grows much faster than ohia. The lottery model predicts a positive covariance between death rates and ohia recruitment when mean death rates are equal and koa has a higher growth rate than ohia. We argue that the competitive advantage of ohia is due to its superior dispersal ability into large gaps, which would yield the positive covariance described above, and it is this positive covariance term that skews the occupation of space in favor of ohia.