Bird Survey Data Research Articles

Slower but deeper community change: Intrinsic dynamics regulate anthropogenic impacts on species temporal turnover.

Understanding the mechanisms behind biodiversity dynamics is central to assessing and forecasting anthropogenic impacts on ecological communities. However, the manner in which external environmental drivers act in concert with intrinsic ecological processes to influence local temporal turnover is currently largely unexplored. Here, we determine how human impacts affect multiple metrics of bird community turnover to establish the ecological mechanisms behind compositional change. We used US Breeding Bird Survey data to calculate transect-level rates of three measures of temporal species turnover: (1) "short-term" (initial rate of decline of Sørensen similarity), (2) "long-term" (asymptotic Sørensen similarity), and (3) "throughput" (overall species accumulation rate from species-time relationship exponents) over 2692 transects across 27 regional habitat types. We then hierarchically fit linear models to estimate the effect of anthropogenic impact on these turnover metrics, using the Human Modification Index proxy, while accounting for observed species richness, the size of the species pool, and annual environmental variability. We found broadly consistent impacts of increased anthropogenic pressures across diverse habitat types. The Human Modification Index was associated with greater turnover at long timescales, but marginally slower short-term turnover. The species "throughput" (accumulation rate) was not notably influenced. Examining anthropogenic impacts on different aspects of species turnover in combination allows greater ecological insight. Observed human impacts on short-term turnover were the opposite of existing expectations and suggest humans are disrupting the background turnover of these systems, rather than simply driving rapid directed turnover. The increased long-term turnover without concurrent increases in species accumulation implies human impacts lead to shifts in species occurrence frequency rather than simply greater arrival of "new" species. These results highlight the role of intrinsic dynamics and caution against simple interpretations of increased species turnover as reflections of environmental change.

Birds as sacred ‘children of god’, beholders of spirit and symbols of twinhood: Human–bird interaction among the Nuer in western Ethiopia

Abstract The deep connection between Indigenous communities and nature plays a pivotal role in biodiversity conservation. Ethiopia, one of Africa's priority countries for bird conservation, harbours 821 bird species and 83 ethnic groups of Indigenous people. However, cultural and spiritual ties between Indigenous peoples and bird species remain largely unexplored. This is particularly true for remote Indigenous communities such as the Nuer. Relying on preexisting bird survey data, we conducted focussed group discussions and semi‐structured interviews with Indigenous Nuer in western Ethiopia to explore human–bird interactions and documented associated traditional ecological knowledge and considered their conservation implications. We found that Nuers have strong ties with birds. In Nuer community, birds are collectively known by three interchangeable terms: ‘gaatkuoth’ to mean sacred children of god, ‘kuoth’ meaning bearers of spirit and ‘diit’ symbols of human twins (since birds nurture multiple offspring, they associate the incidence of twins in human with birds). We identified 71 culturally important bird species that were used in seven different use categories. Among these species, 10 were used as bushmeat, five for traditional medicine, eight as fish indicators, seven as omens (believed to indicate upcoming misfortunes), three as amulets (believed to protect against danger when bird's body parts are used as necklaces and bracelets), three as season indicators and 45 for their scenic beauty. An informant consensus factor for species in all use categories was >90%, except for the scenic value, indicating a high homogeneity of knowledge about species uses. Bird species with multiple uses have significant cultural values among locals, emphasizing the need to understand these values in conservation efforts. Nuer traditional systems regulate the direct use of birds including for bushmeat. Hunting is permitted only by impoverished households during severe food shortages and is prohibited for those with a history of twins in their ancestry. The Nuer people exhibit a profound cultural connection to birds, viewing them as sacred and spiritually valuable beings. This deep‐seated reverence and traditional knowledge highlight the importance of integrating Indigenous perspectives into bird conservation strategies to enhance their effectiveness and respect cultural values. Read the free Plain Language Summary for this article on the Journal blog.

Bayesian integrated species distribution models for hierarchical resource selection by a soaring bird

Migratory birds exhibit seasonal geographic range (hereafter, range) dynamics during the annual cycle. Few studies have examined how migratory birds select their habitats for range occupancy at the species level and space use at the individual level simultaneously. We hypothesized that environmental variables directly related to fitness components would affect the range occupancy probabilities of migrants, whereas environment variables related to movements and flights would affect the space use intensities of migrants. We built Bayesian integrated species distribution models (ISDMs) to evaluate the effects of climate conditions, wind conditions, and landcover compositions on the seasonal range dynamics of American white pelicans Pelecanus erythrorhynchos (hereafter, pelican) during summer and winter. The ISDMs estimated the summer range occupancy probabilities of pelicans with Breeding Bird Survey data, winter range occupancy probabilities with Christmas Bird Count data, and summer and winter space-use intensity rates with eBird data jointly. We evaluated the predictive performance of ISDMs using independent datasets of pelican GPS locations. Integrated species distribution models outperformed the occupancy-only models in the predictive performance of occupancy probabilities. Climate conditions had opposite effects on the range occupancy probabilities between the breeding and non-breeding grounds, whereas landcovers had relatively consistent effects on range occupancy probabilities between the seasons.

Integrating counts from rigorous surveys and participatory science to better understand spatiotemporal variation in population processes

Abstract Knowledge of variation in population processes (e.g. population growth) across broad spatiotemporal scales is fundamental to population ecology and critical for conservation decision‐making. Count data from rigorous surveys (e.g. surveys with probabilistic sampling design and distance sampling information) can inform population processes but are often limited in space and time. Participatory science data cover broader spatiotemporal extents but are prone to bias due to limited to no sampling design and lack of distance sampling information, hindering their capability of informing population processes. Here, we developed an integrated dynamic N‐mixture model that jointly analyses rigorous survey and participatory science data to inform population growth at broad spatiotemporal extents. The model contains a flexible scaling parameter that allows fixed and random effects to account for biases and errors in participatory science data. We conducted simulations to evaluate the inference performance of this model across a broad range of spatial and temporal overlap between rigorous survey and participatory science data. We also conducted a case study of Baird's Sparrow (Centronyx bairdii), a species of conservation concern, to illustrate the application of the integrated model with rigorous survey data from the Integrated Monitoring in Bird Conservation Regions programme and participatory science North American Breeding Bird Survey and eBird data. Simulations showed that the integrated model improved precision without biasing parameter estimates, in comparison with a model informed by rigorous survey data alone. The case study further demonstrated the utility of the integrated model for quantifying range‐wide, long‐term population processes and environmental drivers despite limited spatiotemporal extent of rigorous survey data. In particular, we found that population growth rate peaked under medium temperature, which were only apparent in the integrated model. The integrated model developed in this study is useful for understanding wildlife population processes at broad spatiotemporal scales with count data. The flexible structure of this model, in particular the scaling parameter, makes it highly adaptable to a broad range of ecological systems and survey procedures. These properties make this modelling approach highly relevant for both population ecology and conservation practice.

The benefits of protected areas for bird population trends may depend on their condition

The Post-2020 Global Biodiversity Framework calls for at least 30% of land and sea to be protected by 2030. Whilst there is growing evidence that protected areas can benefit biodiversity, to achieve the greatest possible gains from their expansion, we must understand how protected area quality impacts upon biodiversity metrics. We used UK BTO/JNCC/RSPB Breeding Bird Survey data and protected areas condition data from national Common Standards Monitoring, to test whether improving site condition (for which there are UK policy targets) would contribute to stated policy targets to increase species' abundance. After controlling for differences in climate, land cover, and elevation, we found a positive association between the proportion of favourable habitat and bird abundance trends in the UK, while in Wales, Scotland and Northern Ireland combined, the positive effect was also significantly greater than in unfavourable habitat. Conversely, we also found a negative effect of proportion of favourable habitat on bird abundance. There was no evidence that these relationships varied between conservation status or many of the traits considered, although there was some evidence that favourable condition was beneficial for habitat specialists, cold-adapted species, and varied by habitat. Our findings suggest that improving the condition of protected areas currently in unfavourable condition, will contribute to nature recovery as measured by species' abundance trends in some circumstances. This also suggests that achieving the “30 by 30” target without ensuring those protected areas are of sufficient quality, may not be sufficient to restore biodiversity.

Landscape-wide pulse events predict trait-based responses among wetland birds in perennial channels of a dryland wetland.

Wetlands in arid or semiarid zones are vital for maintaining biodiversity but face growing threats. Flooding regime variability is a key driver of ecological dynamism in these systems, dictating primary productivity on a large spatial scale. The functional composition or diversity of wetland-dependent bird species has been found to be sensitive to fluctuations in hydrological regimes and can thus be indicative of cascading ecosystem responses associated with climate change. In this paper, we investigate whether large-scale changes in inundation and fire-a significant additional biodiversity determinant in (semi-)arid landscapes-are reliable predictors of functional group responses of wetland-dependent birds along a perennial channel of the Okavango Delta, Botswana. We fit generalized additive models (GAMs) to 6 years of bird survey data collected along ~190-km-long annual transects and use remotely sensed landscape-level inundation estimates, as well as spatiotemporal distance to fire, to predict the responsiveness of seven trait-based functional group abundances. During the surveys, a total of 89 different wetland-dependent bird species were recorded, including 76 residents, across all years, with below-surface feeding waders consistently the most abundant functional group. Including estimated spatiotemporal variability in flooding and fire, as well as their interactions, improved model fit for all seven functional groups, explaining between 46.8% and 68.3% of variability in functional group abundances. Covariates representing longer-term variability in inundation generally performed better than shorter-term ones. For example, variability in inundation over the 5 months preceding a survey best predicted the responses of all functional groups, which also all exhibited responsiveness to the interaction between flooding and fire. We were able to interpret the responses of individual functional groups, based on the resource exploitation assumption. Overall, our results suggest that perennial waters in dryland wetlands offer functional refugia to wetland-dependent birds and highlight the indicative power of large-scale trait-based bird monitoring. Our findings demonstrate the potential utility of such a monitoring regime for dryland wetland ecosystems vulnerable to industrial-scale anthropogenic pressure and associated climate change.

Trending against the grain: Bird population responses to expanding energy portfolios in the US Northern Great Plains.

Future global energy demand may be met through increased extraction of fossil fuels and production of renewable energy such as biofuels. Renewable energy from biofuels is often proposed as an environmentally friendly alternative to fossil fuels; however, impacts of renewable energy sources on wildlife populations have rarely been evaluated in working landscapes. We used North American Breeding Bird Survey data (1998 to 2021) to assess whether the joint effects of oil and gas and biofuel crop production explained grassland bird population declines. We modeled location-specific effects of land use on grassland bird habitat use for four grassland bird species (bobolink [Dolichonyx oryzivorus], grasshopper sparrow [Ammodramus savannarum], Savannah sparrow [Passerculus sandwichensis], and western meadowlark [Sturnella neglecta]) in North Dakota, a state experiencing rapid growth in both energy sectors. Our analysis showed that grassland birds responded more negatively to biofuel feedstocks (i.e., corn and soybeans) on the landscape compared with oil and gas development. Furthermore, we found that the effect of feedstocks was not generalizable to other forms of agricultural land use. When combined, these land use changes resulted in distributional shifts of grassland birds, with use by birds being lower in regions dominated by biofuel production, which appears partially responsible for observed abundance trends at the state level. Our results indicate that expansion of oil and gas development has negatively affected habitat use by some grassland birds, but this impact was more localized when compared to biofuel crops. Conservation practitioners may need to adapt their conservation strategies to account for widespread and rapid land use change driven by United States energy policies.

Bayesian geostatistical modeling for discrete‐valued processes

AbstractWe introduce a flexible and scalable class of Bayesian geostatistical models for discrete data, based on nearest‐neighbor mixture processes (NNMP), referred to as discrete NNMP. To define the joint probability mass function (pmf) over a set of spatial locations, we build from local mixtures of conditional pmfs using a directed graphical model, with a directed acyclic graph that summarizes the nearest neighbor structure. The approach supports direct, flexible modeling for multivariate dependence through specification of general bivariate discrete distributions that define the conditional pmfs. In particular, we develop a modeling and inferential framework for copula‐based NNMPs that can attain flexible dependence structures, motivating the use of bivariate copula families for spatial processes. Moreover, the framework allows for construction of models given a pre‐specified family of marginal distributions that can vary in space, facilitating covariate inclusion. Compared to the traditional class of spatial generalized linear mixed models, where spatial dependence is introduced through a transformation of response means, our process‐based modeling approach provides both computational and inferential advantages. We illustrate the methodology with synthetic data examples and an analysis of North American Breeding Bird Survey data.

Regional Context for Balancing Sagebrush- and Woodland-Dependent Songbird Needs with Targeted Pinyon-Juniper Management

In the western United States, pinyon-juniper woodlands have expanded by as much as sixfold among sagebrush landscapes since the late 19th century, with demonstrated negative impacts to the behavior, demography, and population dynamics of species that rely on intact sagebrush rangelands. Notably, greater sage-grouse (Centrocercus urophasianus) are unable to tolerate even low conifer cover, which can result in population declines and local extirpation, whereas removing expanding conifer cover has been demonstrated to increase sage grouse population growth rates and sagebrush obligate songbird abundance. Yet conifer management among sagebrush landscapes has been met with concerns about unintended impacts to species that rely on conifer woodlands, notably the pinyon jay (Gymnorhinus cyanocephalus), whose population declines are distinctive among birds breeding in pinyon-juniper woodlands. Spatial models of bird abundance can help management prioritize future actions in light of multiple species requirements, while also providing a framework to retroactively test the impact of past treatments. We used Breeding Bird Survey data to model indices to abundance in relation to multiscale habitat features including landcover, fire, topography, and climate variables for nine songbird species reliant on sagebrush and pinyon-juniper woodlands for breeding. Predictive maps allowed us to also examine the overlap of conifer management conducted by the Sage Grouse Initiative (SGI), which targets management of early successional conifers among priority sage-grouse habitats, with predicted indices to abundance of songbirds. Our findings demonstrate that targeted sage grouse habitat restoration under SGI was not at odds with protection of pinyon jay populations. Rather, conifer management has largely occurred among northern sagebrush landscapes where models suggest that past cuts likely benefit Brewer's sparrow and sage thrasher while avoiding pinyon jay habitats.

Land cover differentially affects abundance of common and rare birds.

While rare species are vulnerable to global change, large declines in common species (i.e., those with large population sizes, large geographic distributions, and/or that are habitat generalists) also are of conservation concern. Understanding if and how commonness mediates species' responses to global change, including land cover change, can help guide conservation strategies. We explored avian population responses to land cover change along a gradient from common to rare species using avian data from the North American Breeding Bird Survey and land cover data from the National Land Cover Database for the conterminous United States. Specifically, we used generalized linear mixed effects models to ask if species' commonness affected the relationship between land cover and counts, using the initial amount of and change in land cover surrounding each North American Breeding Bird Survey route from 2001 to 2016. We quantified species' commonness as a continuous metric at the national scale using the logarithm (base 10) of each species' total count across all routes in the conterminous United States in 2001. For our focal 15-year period, we found that higher proportions of initial natural land cover favored (i.e., was correlated with higher) counts of rare but not common species. We also found that commonness mediated how change in human land cover, but not natural land cover, was associated with species' counts at the end of the study period. Increases in developed lands did not favor populations of any species. Increases in agriculture and declines in pasture favored populations of common but not rare species. Our findings show a signal of commonness in how species respond to a major dimension of global change. Evaluating how and why commonness mediates species' responses to land cover change can help managers design conservation portfolios that sustain the spectrum of common to rare species.

Urban Bird Community Assembly Mechanisms and Driving Factors in University Campuses in Nanjing, China.

University campuses are important components of cities, harboring the majority of urban biodiversity. In this study, based on monthly bird survey data covering 12 university campuses located either downtown or in the newly developed areas in Nanjing, China, in 2019, we studied the assembly processes of each campus's bird population and their main drivers by modeling a set of ecological and landscape determinants. Our results showed that (1) bird abundance and species diversity in the newly developed areas were significantly higher than in those downtown; (2) the phylogeny of bird communities in all universities followed a pattern of aggregation, indicating that environmental filtering played a major role in community assembly; (3) specifically, grass, water, and buildings were the main factors affecting each campus's bird community's functional and phylogenetic diversity, with the areas of grass and water habitats having a significant positive correlation with phylogenetic diversity, while the size of building areas was negatively correlated. Our results emphasize that habitat features play a decisive role in determining urban bird population diversity and community assembly processes. We suggest that increasing landscape diversity, e.g., by reasonably arranging the location and area of water bodies and grasslands and improving the landscape connectivity, could be a powerful way to maintain and promote urban bird diversity.

Change in altitudinal distribution of Newfoundland Gray-cheeked Thrush ( Catharus minimus minimus ) revealed through historical stop-level breeding bird survey data

Breeding bird survey (BBS) data are typically analyzed at the route level in which the average or combined total number of individuals across the 50 stops is treated as a single observation. However, analysis at the stop level may provide information on finer-scale habitat affiliations of species within the broader landscape, as well as changes in species distribution over time. Though once abundant, the Newfoundland Gray-cheeked Thrush (<em>Catharus minimus minimus</em>) underwent a dramatic population collapse across most of the island during the 1980s and 1990s and today is most common in montane forests. The reason for this collapse is not well understood but introduced North American red squirrels (<em>Tamiasciurus hudsonicus</em>), which colonized most forested areas on the island below ~400 m from the late 1970s through the mid-1990s, have been identified as a possible cause. To improve our understanding of changes in the elevational distribution of Gray-cheeked Thrushes, we compared stop-level BBS data from two periods. Our historic period from 1974-1984 corresponds with the initial expansion phase of introduced red squirrels, whereas that from 2000-2015 reflects a period during which the colonization of suitable habitat by squirrels was complete. We used 17 routes (850 stops) where the thrushes had been observed and there were at least 3 surveys completed during each period. Surveys during the 1970s and 1980s indicated that Gray-cheeked Thrushes were abundant at all elevations sampled by the BBS (0-450 m), with higher incidence below 100 m and above 300 m; in contrast, recent surveys indicate that the species is now essentially absent below 350 m. This finding highlights the value of historical stop-level BBS data for reconstructing changes in species distributions and is consistent with the hypothesis that red squirrels have adversely affected Newfoundland Gray-cheeked Thrushes.

Using Breeding Bird Survey and eBird data to improve marsh bird monitoring abundance indices and trends

The elusive nature of many marsh-breeding birds presents a challenge for effective population monitoring. The Great Lakes Marsh Monitoring Program (GLMMP), delivered by Birds Canada, addressed these challenges by concentrating survey efforts in marsh bird habitats and by using survey protocols aimed at maximizing marsh bird detections. GLMMP data suggest that numerous marsh bird species are declining. Here we consider the value of other avian monitoring programs to support our understanding of marsh bird population trends. Our goal was to compare the GLMMP, North American Breeding Bird Survey (BBS), and eBird with each other and with a combined survey, by evaluating frequency of detection, annual indices of abundance, and trend estimates. Using 23 years (1997–2019) of GLMMP, BBS, and eBird data, we calculated annual indices of abundance and trends for each survey for 18 marsh-breeding species across southern Ontario, Canada. We found that the GLMMP had more frequent detections, greater counts, and/or more precise trends for 8 species that breed almost exclusively in marshes, whereas 10 species with more variable habitat preferences had more frequent detections, greater counts, and/or more precise trends based on eBird and/or BBS. We found that combining counts from the GLMMP, BBS, and eBird increased the precision around trend estimates for 11/18 (61%) species; however, trend estimates for combined data tended to be positively biased relative to GLMMP trends for species that also frequent non-marsh habitats. We, therefore, provide evidence that combining citizen science data from multiple sources could increase the power to detect changes in marsh-dependent bird populations. Integrated datasets thus provide a promising avenue for future marsh bird conservation and management.

Changes in habitat suitability for wintering dabbling ducks during dry conditions in the Central Valley of California

AbstractIn arid and Mediterranean regions, landscape‐scale wetland conservation requires understanding how wildlife responds to dynamic freshwater availability and conservation actions to enhance wetland habitat. Taking advantage of Landsat satellite data and structured and community science bird survey data, we built species distribution models to describe how three duck species, the Northern Pintail (Anas acuta), Green‐winged Teal (Anas crecca), and Northern Shoveler (Anas clypeata), respond to freshwater supply and food resources on different flooded land cover types in the Central Valley of California. Specifically, our models compared duck habitat suitability between the wettest and driest conditions in each month from September through April. Using abundance‐weighted boosted regression trees, we created three sets of species occurrence models based on different covariates: (1) near real‐time (hereafter “real‐time”) covariates in which duck observations were matched to the water availability within the 16‐day window of a Landsat observation, (2) a combination of real‐time covariates and waterfowl food resource covariates describing annual corn and rice biomass and managed wetland moist soil seed yield estimates derived from Landsat data, and (3) long‐term average covariates—the most common approach to species distribution modeling—in which long‐term average surface water availability was used. We modeled the monthly occurrence of three duck species as a function of surface water availability, land cover type, road density, temperature, and bird data source. We found that dry conditions result in reduced habitat suitability, with the biggest reductions in November through January and in agricultural fields; in contrast, suitability of flooded wetland habitat was relatively robust to surface water availability. When models of habitat suitability based on long‐term average climate conditions were compared to models based on real‐time conditions, the highest long‐term suitability values occurred in areas where suitability was high regardless of whether it was a wet or a dry year. While all models performed well, the inclusion of crop and wetland plant yield covariates resulted in slightly higher model performance. Overall, species distribution models created using data on the environmental conditions present at the time of bird observations can aid conservation efforts under extreme conditions over large spatial scales.

Big changes in backyard birds: An analysis of long-term changes in bird communities in Australia's most populous urban regions

Urban environments are increasingly acknowledged as a priority for biodiversity conservation. Birds in particular are capable of persisting, and sometimes thriving, in cities and towns globally. However, the process of urbanization results in the loss of many bird species due to the resulting changes in habitat conditions. Urban expansion and densification present a threat to both urban bird biodiversity and bird conservation more broadly. Australian urban areas, including suburban and peri-urban areas, currently support moderate bird species richness, but the rapidly changing urban landscape threatens these communities. Unfortunately, many bird species' population trends are not actively studied, resulting in a poor understanding of species persistence in urban environments. Here, we used bird survey data from long-running citizen science databases in a Bayesian List Length Analysis to determine changes in bird species prevalence (the probability of observing a species in a given survey event) over time in Australia's four most populous urban regions. We found that introduced species, historically prominent in Australian urban bird communities, are decreasing in prevalence in all four regions, while a small group of native urban exploiters are becoming more prevalent. Our results also show that many species perceived to be “iconic” or “common” are experiencing declines in prevalence in urban areas, highlighting the importance of monitoring and conservation action in urban areas.

Avian brood parasites, species assemblage, and bird diversity: A case study using a grid-based survey in South Korea

Identifying proper surrogate species or groups is a challenging but critical step in the application of surrogate species approaches in biodiversity conservation because their effectiveness can vary according to biological communities. Recently, the brood parasitic common cuckoo, Cuculus canorus, has been suggested as a surrogate for describing biodiversity, primarily based on its strong parasitic relationship with other host species. However, the efficiency of cuckoo surrogates has been challenged because of the potential limitations of the methodological approaches. Furthermore, its generality rarely has been explicitly tested in other parasitic species with local biodiversity data collected through conventional schemes such as grid-based sampling. Using bird survey data obtained from a grid-based sampling scheme in South Korea, we evaluated the surrogate efficiency of five cuckoo species for bird diversity (species richness and phylogenetic diversity) and generated surrogate species groups. We found that among the five parasitic cuckoo species breeding in South Korea, the common cuckoo and the Indian cuckoo C. micropterus were effective surrogate species. Among these, only the common cuckoo belonged to the best surrogate species group together with its major host species; the Indian cuckoo showed less effective surrogate efficiency than the common cuckoo. In conclusion, our study shows that the common cuckoo, as a single species and a member of a species assemblage, is an effective indicator species for bird diversity in grid-based survey data. However, the result that not all parasitic cuckoo species performed a surrogate role effectively implies that multiple functions may be associated with the surrogate efficiency of brood parasitic cuckoos, along with the importance of host-parasite relationships.

Mapping breeding bird species richness at management‐relevant resolutions across the United States

Human activities alter ecosystems everywhere, causing rapid biodiversity loss and biotic homogenization. These losses necessitate coordinated conservation actions guided by biodiversity and species distribution spatial data that cover large areas yet have fine-enough resolution to be management-relevant (i.e., ≤5km). However, most biodiversity products are too coarse for management or are only available for small areas. Furthermore, many maps generated for biodiversity assessment and conservation do not explicitly quantify the inherent tradeoff between resolution and accuracy when predicting biodiversity patterns. Our goals were to generate predictive models of overall breeding bird species richness and species richness of different guilds based on nine functional or life-history-based traits across the conterminous United States at three resolutions (0.5, 2.5, and 5km) and quantify the tradeoff between resolution and accuracy and, hence, relevance for management of the resulting biodiversity maps. We summarized 18 years of North American Breeding Bird Survey data (1992-2019) and modeled species richness using random forests, including 66 predictor variables (describing climate, vegetation, geomorphology, and anthropogenic conditions), 20 of which we newly derived. Among the three spatial resolutions, the percentage variance explained ranged from 27% to 60% (median=54%; mean=57%) for overall species richness and 12% to 87% (median=61%; mean=58%) for our different guilds. Overall species richness and guild-specific species richness were best explained at 5-km resolution using ~24 predictor variables based on percentage variance explained, symmetric mean absolute percentage error, and root mean square error values. However, our 2.5-km-resolution maps were almost as accurate and provided more spatially detailed information, which is why we recommend them for most management applications. Our results represent the first consistent, occurrence-based, and nationwide maps of breeding bird richness with a thorough accuracy assessment that are also spatially detailed enough to inform local management decisions. More broadly, our findings highlight the importance of explicitly considering tradeoffs between resolution and accuracy to create management-relevant biodiversity products for large areas.

Species richness response to human pressure hides important assemblage transformations

Human activities’ negative impact on biodiversity is undisputed, but debate remains vivid on their effect on species richness, a key index in ecology and conservation. While some studies suggest that species richness declines with human pressure, others show that it can be insensitive or even respond positively to some human pressure, because some species (“losers”) are replaced by others (“winners”). However, many winners are favored by intermediate pressure but decline when pressure becomes too high, and we can thus expect species richness to decline above a certain human pressure. Analyzing eBird data in tropical forests, I find that, under a certain threshold, increasing human footprint causes important composition changes, with losers (habitat specialist, endemic, sensitive, and threatened species) being replaced by winners (habitat non-specialist, large-range, human-tolerant, anthropophilic, and non-native species), resulting in a slight increase in species richness. Above this threshold though, richness in winners stops increasing (except for anthropophilic and non-native species), leading to a steep decline in overall species richness. I find that the shape of species richness response to human footprint varies between regions (comparing results from the North America Breeding Bird Survey, PREDICTS database, and eBird data across eight biodiversity hotspots) and identify five different trajectories in species richness response to human pressure. I suggest that they can be classified depending on their slope and monotony in the “replace then remove framework,” unifying contradictory effects of human pressure on species richness.

The Role of Rare Avian Species for Spatial Resilience of Shifting Biomes in the Great Plains of North America

Human activity causes biome shifts that alter biodiversity and spatial resilience patterns. Rare species, often considered vulnerable to change and endangered, can be a critical element of resilience by providing adaptive capacity in response to disturbances. However, little is known about changes in rarity patterns of communities once a biome transitions into a novel spatial regime. We used time series modeling to identify rare avian species in an expanding terrestrial (southern) spatial regime in the North American Great Plains and another (northern) regime that will become encroached by the southern regime in the near future. In this time-explicit approach, presumably rare species show stochastic dynamics in relative abundance – this is because they occur only rarely throughout the study period, may largely be absent but show occasional abundance peaks or show a combination of these patterns. We specifically assessed how stochastic/rare species of the northern spatial regime influence aspects of ecological resilience once it has been encroached by the southern regime. Using 47 years (1968–2014) of breeding bird survey data and a space-for-time substitution, we found that the overall contribution of stochastic/rare species to the avian community of the southern regime was low. Also, none of these species were of conservation concern, suggesting limited need for revised species conservation action in the novel spatial regime. From a systemic perspective, our results preliminarily suggest that stochastic/rare species only marginally contribute to resilience in a new spatial regime after fundamental ecological changes have occurred.

Evaluating compositional changes in the avian communities of eastern North America using temperature and precipitation indices

AbstractAimSpecies distributions are altered by climate change, resulting in changes in community composition. How communities are changing with climate is important for understanding the dynamics of changing diversity patterns. In this study, we employ two community weighted means (CWMs) of temperature (CTI) and precipitation (CPI) to evaluate patterns in climate‐driven community changes.LocationEastern North America between −100° and −60° longitude and 25°–50°N latitude.TaxonNorth American birdsMethodsWe used North American Breeding Bird Survey (BBS) data from 1990 to 2018 to test the spatiotemporal trends of these indices at a sub‐continental (across all BBS routes) and at a regional scale (sub‐continental scale partitioned by 5° latitude bands). We employ a jackknife analysis to highlight individual species contributions to CTI and CPI trends and further identify group characteristics of species based on relative abundance trends and range expansion and contraction trends.ResultsAcross all BBS routes, temperature marginally increased and precipitation significantly increased. At the sub‐continental scale, we found no correlation between CTI and temperature, but a positive correlation between CPI and precipitation. CTI and CPI both increased, driven by increased abundances of “warm” and “wet” dwelling species expanding in range. Regional scale CTI and CPI patterns deviated from sub‐continental patterns. CTI was driven by “warm” dwelling species increasing in abundance and expanding in range, whereas decreases in “dry” dwelling species contracting in range drove CPI trends at the highest latitudes.Main conclusionsThe concurrent use of CTI and CPI highlights that community dynamics are more complicated than using temperature metrics alone. Employing more than one community index demonstrates how simultaneous increases in two separate evaluative indices can have disproportionate effects on the number of species that contribute to a trend and highlight disparate mechanisms that contribute to these underlying differences.