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Global change is currently impacting ecosystems and their contributions to people (i.e. ecosystem services). These impacts have consequences for societies and human well-being, especially in Africa. Historically, efforts have focused on assessing global change from a social or biophysical perspective, treating them as separate entities. Yet, our understanding of impacts to social-ecological systems remains limited, particularly in the Global South, due to a lack of data, tools, and approaches accounting for social and ecological aspects of ecosystem services. This is especially relevant for cultural ecosystem services as they are less tangible. We use a simple indicator and important provider of a multitude of cultural ecosystem services, birding, to understand how climate, biodiversity, and land use change will impact cultural ecosystem services across Africa. We explore how emerging tools and data can overcome limitations in mapping and modeling cultural ecosystem services, particularly in analyzing human preferences and behavior at large spatiotemporal scales and in data-poor regions. Leveraging crowdsourced data from eBird and using machine learning techniques we map and model recreational birding to assess the underlying social-ecological relationships and the impact of future climate and environmental change. We show that bird species richness, protected areas, accessibility, and max temperature contribute most to birding suitability across the continent. Further, we show spatial shifts in the suitability of birding under three future climate scenarios (SSP126, 370, and 585). Models suggest climate and biodiversity change will increasingly constrain the flow of birding related cultural ecosystem services across Africa. This has implications for human-nature interactions, development of countries, management of protected areas, and overall human well-being in the future. More generally, we highlight opportunities for crowdsourced datasets and machine learning to integrate non-material ecosystem services in models and thus, enhance the understanding of future impacts to ecosystem services and human well-being.

Monitoring biodiversity can be critical for informing effective conservation strategies, but can also deplete the resources available for management actions if the time and money available for both activities are limited. Freely available participatory science data may help alleviate this issue, but only if data quality is sufficient to inform the best decisions. Our objective was to quantify the predicted outcomes of prioritizing conservation action based on regional participatory science compared to using targeted professional monitoring data. Using data from the BirdReturns program in the Central Valley of California as a case study, we prioritized properties for conservation action based on the predicted probability of detecting seven shorebird species, using a range of budgets as constraints. For prioritizations conducted using data from the professional surveys, the cost of monitoring was deducted from the total budget available for conservation action. Crowd‐sourced data performed better than professional data even before accounting for the cost of professional monitoring, and substantially better when monitoring costs were explicitly considered. The difference in performance was particularly stark at lower budgets, where the professional monitoring data consumed a substantial proportion of the budget. Synthesis and applications. Prioritizing conservation action based on high‐quality, freely available participatory science data could theoretically result in better biodiversity outcomes than paying for targeted professional monitoring, allowing managers to redistribute limited conservation resources from monitoring to action. [ABSTRACT FROM AUTHOR]

The rise of citizen science (also called community science) has led to vast quantities of species observation data collected by members of the public. Citizen science data tend to be unevenly distributed across space and time, but the treatment of sampling bias varies between studies, and interactions between different biases are often overlooked. We present a method for conceptualizing and estimating spatial and temporal sampling biases, and interactions between them. We use this method to estimate sampling biases in an example ornithological citizen science dataset from eBird in Brisbane City, Australia. We then explore the effects of these sampling biases on subsequent model inference of population trends, using both a simulation study and an application of the same trend models to the Brisbane eBird dataset. We find varying levels of sampling bias in the Brisbane eBird dataset across temporal and spatial scales, and evidence for interactions between biases. Several of the sampling biases we identified differ from those described in the literature for other datasets, with protected areas being undersampled in the city, and only limited seasonal sampling bias. We demonstrate variable performance of trend models under different sampling bias scenarios, with more complex biases being associated with typically poorer trend estimates. Sampling biases are important to consider when analysing ecological datasets, and analysts can use this method to ensure that any biologically relevant sampling biases are detected and given due consideration during analysis. With appropriate model specification, the effects of sampling biases can be reduced to yield reliable information about biodiversity. [ABSTRACT FROM AUTHOR]

Map‐based decision support tools (DSTs) that use species distributions are an important means of identifying priority areas for conservation. The Wisconsin Waterfowl Habitat Conservation Strategy (WWHCS) uses a DST to identify priority ecological landscapes and watersheds to guide waterfowl habitat projects. The WWHCS DST relies on waterfowl habitat suitability layers derived through expert opinion in lieu of species distributions, a common approach in DSTs. Given the subjectivity of expert opinion, model‐driven species distributions such as those available from community science projects could provide more reliable information and better identify areas for waterfowl conservation. Here, we explore the application of relative abundance products available through the eBird Status and Trends project as an alternative to expert‐derived habitat suitability layers in the WWHCS DST. Our objectives were to compare seasonal species distributions from habitat suitability models (expert‐derived) and species distribution models (eBird‐derived) and determine whether differences influenced DST prioritizations. Correlations between expert‐ and eBird‐derived distributions were generally low to moderate for breeding and fall layers (ρ: −0.03–0.76), and lowest for spring (ρ: −0.49–0.72). There was also minimal agreement among top‐ranked ecological landscapes (40%) and watersheds (28%) between the two versions of the DST. Finally, we compare tradeoffs and suggest a model‐driven approach for the WWHCS DST. However, additional work validating eBird relative abundance against professional surveys and empirical studies evaluating waterfowl habitat selection and vital rates are important future considerations for the DST and waterfowl habitat conservation in Wisconsin. [ABSTRACT FROM AUTHOR]

ABSTRACT Aim Location Methods Results Main Conclusions Historical bird atlases provide comprehensive datasets for investigating long‐term changes in species' distribution. In the context of accelerating biodiversity loss, these datasets can lend critical insights into the state of bird distributions across broad spatio‐temporal scales and provide much‐needed information for impactful conservation. In Africa, the potential of atlas data to understand changes in avian populations remains largely untapped.This study mapped changes in national distribution patterns of 1088 bird species found in Kenya.Tapping into one of the earliest atlas databases, this study compared Kenyan bird atlas data collected between 1970 and 1984 with recent citizen science data sourced from the Kenya Bird Map project and eBird to determine changes in ranges across 50 years. We produced maps displaying, for every 27 × 27 km square of the country, whether a species appeared, was present throughout both periods, or disappeared. We account for the change in data collection effort between the two periods by quantifying the confidence of the change for each square.The maps produced for each species are publicly accessible through an interactive website: https://kenyabirdtrends.co.ke/. We found that related species tended to experience similar changes in their distribution ranges. The ranges of Palearctic migrants and scavengers declined drastically, while introduced birds experienced a significant range increase over the past 50 years.This study demonstrates the potential of integrating recent citizen science data with historical atlas data to draw out the changes in range for all species at national level. The range contraction of Palearctic migrants and scavengers echoed corresponding drops in abundance at local, regional and global scales. These findings lend additional weight to the need for an increased conservation focus on migratory and scavenging birds in Kenya. [ABSTRACT FROM AUTHOR]

Background: Urban areas are a significant and rapidly expanding part of the global landscape. Urban expansion occurs alongside climate change, with both linked to declines in native species. However, urban environments can offer alternative resources during extreme climatic events such as droughts. Aims: We sought to identify bird species that had an increased presence in the major urban center of south-west Western Australia during a climate anomaly characterized by record low rainfall and high temperatures. Methods: Using eBird data, we analyzed changes in the reporting rates of all bird species in the period from January 2019 to August 2024. Generalized linear models were used to assess the influence of cumulative 6-month, 12-month, and 18-month rainfall on species reporting rates. Key results: Reporting rates increased dramatically (up to nine times higher than average) around the time of the drought, before reducing back to the average once the drought was broken for four species: (1) the black-shouldered kite; (2) the black-tailed native-hen; (3) the tawny-crowned honeyeater; and (4) the western spinebill. Cumulative 6-month rainfall was a strong predictor for the raptor and the two honeyeaters. Other similar species showed no significant change in reporting rate, suggesting the effect is highly species dependent. Conclusions: Multiple different types of birds may utilize urban areas during drought events. Further research is needed to identify what drives movement of wildlife in response to such events, and the type of urban resources the birds are using. Implications: Urban ecosystems should be integrated into broader conservation plans to support species through the interacting challenges posed by climate change and urbanization. Urban areas are expanding rapidly, leading to habitat and biodiversity loss. However, they may offer resources during environmental stressors like drought. Our study in south-west Western Australia found dramatic increases in reporting rates for four bird species during a climate anomaly, highlighting their adaptive behavioural responses and the potential of urban areas as refuges. Photograph by Harry Moore. [ABSTRACT FROM AUTHOR]

Background: Monitoring biodiversity is crucial in biogeography. Citizen science and biodiversity platforms have revolutionized data access across taxa, but they struggle to provide robust raw data essential for conservation decisions. Aims: This study addresses data gaps for under‐represented species and locations, observer expertise variability, and the lack of absence data and sampling effort information to improve data representation and suitability for statistical analyses. Materials & Methods: We collected, compared to IUCN‐recognized taxonomic groups, all worldwide living being (animal, plant and fungi) observations held by four major biodiversity platforms: eBird, GBIF, iNaturalist, and Observation.org. We also organized such observations by country of origin and based on their Human Development Index (HDI). Results: We found that, while GBIF, iNaturalist, and Observation.org cover all life forms, birds are the most observed (eBird is a bird‐specific platform), whereas fish, other marine organisms, arthropods, and invertebrates are dramatically underrepresented. Moreover, none of the above‐mentioned biodiversity platforms considered or directly analysed expertise variability among observers and, apart from eBird, the other three biodiversity platforms do not accommodate data on species absence and sampling effort. Discussion and Conclusion: Finally, we found that species observations on biodiversity platforms considered in this study are skewed towards high HDI countries, primarily North America and Europe. By enhancing the effectiveness of biodiversity platforms, this study has the potential to significantly advance the field of biogeography, paving the way for more informed and effective conservation strategies. Overall, our findings underscore the untapped potential of these platforms in contributing to our understanding of the spatial and temporal patterns of biodiversity. [ABSTRACT FROM AUTHOR]

Urban ecosystems are suitable for the introduction and spread of alien bird species, and early detection of their establishment and expansion is crucial to reduce potential negative impacts. In this context, the use of opportunistic citizen science data can have considerable advantages in relation to conventional scientific approaches. We gathered records of parakeets and parrots (Psittaciformes) and mynas and starlings (Sturnidae) for the urban area of Lisbon (Portugal) from the eBird database. We used this opportunistic citizen science data to document the establishment and expansion and to estimate distribution trends of alien bird species in urban ecosystems. In the last decade there has been a considerable increase in the amount of opportunistic citizen science data available in eBird for our study area. The probability of presence of the Senegal parrot, rose-ringed parakeet, blue-crowned parakeet, and crested myna was positively influenced by the number of lists. For the rose-ringed parakeet, blue-crowned parakeet, and crested myna, the year positively influenced the probability of presence, suggesting an increase in distribution range. We observed that spatio-temporal variations in effort associated to opportunistic citizen science data sources may generate bias in trend estimates, and therefore we recommend the effort should always be accounted for. Our approach agreed with the documented expansion of alien bird species in the study area, supporting the potential usefulness of opportunistic citizen science in providing early detection on biological invasions in urban ecosystems, particularly where this is the best or the only source of information available. [ABSTRACT FROM AUTHOR]

ABSTRACT Aim Location Time Period Major Taxa Studied Methods Results Main Conclusions As global change accelerates, accurate predictions of species distributions and biodiversity patterns are critical to limit biodiversity loss. Numerous studies have found that coarse‐grain species distribution models (SDMs) perform poorly relative to fine‐grain models because they mismatch environmental information with observations. However, it remains unclear how grain‐size biases vary in intensity across space and time, possibly generating inaccurate predictions for specific regions, seasons or species. For example, coarse‐grain biases may intensify in patchy, discontinuous landscapes. Such biases may accumulate to produce highly misleading estimates of continental and seasonal biodiversity patterns.United States and Canada.2004–2021.Birds (Aves).We fit presence‐absence SDMs characterising the summer and winter distributions of 572 bird species native to the US and Canada across five spatial grains from 1 to 50 km, using observations from the eBird citizen science initiative. We combined these predictions to generate seasonal biodiversity estimates across the US and Canada, which we validated using observations from 322 independent sites.We find that in both seasons, 1 km models more accurately predicted species presence, absence and richness at local sites. Coarse‐grain models (even at 3 km) consistently under‐predicted range area, potentially missing important habitat. This bias intensified during summer (83%–86% of species) when many birds have smaller ‘operational scales’ via localised home ranges while breeding. Biases were greatest in desert regions with patchier habitat and for range‐restricted and habitat‐specialist species. Predictions based on coarse‐grain models overpredicted avian diversity in the west and underpredicted it in the great plains, prairie pothole region and boreal zones.We demonstrate that coarse‐grain models can bias seasonal and continental estimates of biodiversity patterns across space and time and that grain‐related biases intensify during summer and in patchier landscapes, especially for range‐restricted and habitat specialist species at risk of population declines. [ABSTRACT FROM AUTHOR]

Avian population sizes fluctuate and change over vast spatial scales, but the mechanistic underpinnings remain poorly understood. A key question is whether spatial and annual variation in avian population dynamics is driven primarily by variation in breeding season recruitment or by variation in overwinter survival. We present a method using large‐scale volunteer‐collected data from project eBird to develop species‐specific indices of net population change as proxies for survival and recruitment, based on twice‐annual, rangewide snapshots of relative abundance in spring and fall. We demonstrate the use of these indices by examining spatially explicit annual variation in survival and recruitment in two well‐surveyed nonmigratory North American species, Carolina wren Thryothorus ludovicianus and northern cardinal Cardinalis cardinalis. We show that, while interannual variation in both survival and recruitment is slight for northern cardinal, eBird abundance data reveal strong and geographically coherent signals of interannual variation in the overwinter survival of Carolina wren. As predicted, variation in wintertime survival dominates overall interannual population fluctuations of wrens and is correlated with winter temperature and snowfall in the northeastern United States, but not the southern United States. This study demonstrates the potential of participatory science (also known as citizen science) datasets like eBird for inferring variation in demographic rates and introduces a new complementary approach towards illuminating the macrodemography of North American birds at comprehensive continental extents. [ABSTRACT FROM AUTHOR]

Many parts of the world lack the large and coordinated volunteer networks required for systematic monitoring of bird populations. In these regions, citizen science (CS) programs offer an alternative with their semi-structured data, but the utility of these data are contingent on how, where, and how comparably birdwatchers watch birds, year on year. Trends inferred from the data can be confounded during years when birdwatchers may behave differently, such as during the COVID-19 pandemic. We wanted to ascertain how the data uploaded from India to one such CS platform, eBird, were impacted by this deadly global pandemic. To understand whether eBird data from the pandemic years in India are comparable to data from adjacent years, we explored several characteristics of the data, such as how often people watched birds in groups or at public locations, at multiple spatial and temporal scales. We found that the volume of data generated increased during the pandemic years 2020–2021 compared to 2019. Data characteristics changed largely only during the peak pandemic months (April–May 2020 and April–May 2021) associated with high fatality rates and strict lockdowns. These changes in data characteristics (e.g. greater site fidelity and less group birding) were possibly due to the decreased human mobility and social interaction in these periods. The data from the remainder of these restrictive years remained similar to those of the adjacent years, thereby reducing the impact of the aberrant peak months on any annual inference. Our findings show that birdwatchers in India as contributors to CS rapidly returned to their pre-pandemic behavior, and that the effects of the pandemic on birdwatching effort and birdwatcher behavior are scale- and context-dependent. In summary, eBird data from the pandemic years in India remain useful for abundance trend estimation and similar large-scale applications, but will benefit from preliminary data quality checks when utilized at a fine scale. [ABSTRACT FROM AUTHOR]

Describing how hybrid zones respond to anthropogenic influence can illuminate how the environment regulates both species distributions and reproductive isolation between species. In this study, we analyzed specimens collected from the Passerina cyanea × P. amoena hybrid zone between 2004 and 2007 and between 2019 and 2021 to explore changes in genetic structure over time. This comparison follows a previous study that identified a significant westward shift of the Passerina hybrid zone during the latter half of the twentieth century. A second temporal comparison of hybrid zone genetic structure presents unique potential to describe finer-scale dynamics and to identify potential mechanisms of observed changes more accurately. After concluding that the westward movement of the Passerina hybrid zone has accelerated in recent decades, we investigated potential drivers of this trend by modeling the influence of bioclimatic and landcover variables on genetic structure. We also incorporated eBird data to determine how the distributions of P. cyanea and P. amoena have responded to recent climate and landcover changes. We found that the distribution of P. cyanea in the northern Great Plains has shifted west to track a moving climatic niche, supporting anthropogenic climate change as a key mediator of introgression in this system. [ABSTRACT FROM AUTHOR]

Aim: In continuous environments, niche limits of species often determine their distribution limits. However, when these limits spatially coincide with a perceived dispersal barrier, the determinants of species' ranges may be confounded. We investigate the distribution pattern of the Brown Hornbill (Aves: Bucerotidae), which spans significant riverine barriers, but stops south of the Brahmaputra River. Considering its preference for low‐elevation evergreen forests, we posit that the lack of sufficient habitats north of the Brahmaputra prevents dispersal of the Brown Hornbill, and not the river itself. Location: The Brahmaputra valley and the Indo‐Burma hotspot. Taxa: Anorrhinus austeni, Aceros nipalensis. Methods: We analysed citizen‐science occurrence data on hornbill presence against a suite of climatic, canopy‐specific and topographical predictors to model the environmental niche of the Brown Hornbill. We used presence‐only maximum entropy modelling in an information theoretic framework, in conjunction with constructing binary logistic regression models using presence and pseudoabsence data. We compared niche models of the Brown Hornbill and the Rufous‐necked hornbill, a close relative with a similar distribution, but which has spanned the Brahmaputra River. Results: Despite the presence of suitable wet‐evergreen forests north of the Brahmaputra River, the hilly terrains in the region act as a biogeographic barrier for the Brown Hornbill, which prefers lowland evergreen forests. Further, highly suitable regions for the Brown and the Rufous‐necked Hornbills precisely delineate low and high‐elevation evergreen forests respectively, indicating that these birds are separated along an elevational axis. Main Conclusions: The Brahmaputra River lies at the cusp of two subtly different environmental regimes. It may therefore serve as the niche limit for certain organisms and not as a physical obstacle to their dispersal. Our study implicitly predicts how widespread deforestation prevalent in the lowland evergreen forests of this region adversely impacts the distributions of organisms that depend on them, such as the Brown Hornbill. Further, our study proffers an approach to ascertain determinants of species distributions in a hypothesis testing framework. [ABSTRACT FROM AUTHOR]

Alternative ecological theories make divergent predictions about the relationship between predators and their prey. If predators exert top‐down ecosystem control, increases in predation should diminish prey abundance and could either diminish or enhance community diversity of prey species. However, if bottom‐up ecosystem controls predominate, predator populations should track underlying variation in prey diversity and abundance, which ultimately should reflect available energy. Past research, both across islands and comparing islands with the mainland, has frequently invoked the importance of predation in regulating lizard abundance and diversity, suggesting an important role of top‐down control when predators are present. However, others have posited a stronger role of food limitation, via competition or bottom‐up forces. If top‐down control predominates, then negative correlations between prey abundance and predator occurrence should emerge within and among islands. Using data from eBird, we inferred landscape‐level presence data for bird species on the islands of Jamaica and Hispaniola. By summing occurrence probabilities of all known anole‐predator birds, we estimated total avian predation pressure and combined these estimates with anole community data from a mark‐recapture study that spanned spatial and climatic gradients on both islands. Avian predators and anole lizards were both affected by climate, with total predator occurrence, anole abundance and anole species richness increasing with mean annual temperature. Anole abundance and predator occurrence showed a curvilinear relationship, where abundance and predator occurrence increased together until predator occurrence became sufficiently high that anole abundance was negatively impacted. This indicates that bottom‐up ecosystem controls drive richness of both anoles and their predators, mitigating the negative effects predators might have on their prey, at least until predator occurrence reaches a threshold. We did not detect consistent evidence of predator occurrence reducing anole community richness. These findings support past research showing that islands with more predators tend to have lower prey abundances, but it does not seem that these top‐down forces are strongly limiting species coexistence. Instead, bottom‐up forces linked with climate may be more important drivers of diversity in both lizards and their avian predators on these islands. [ABSTRACT FROM AUTHOR]

Abstract Identifying the drivers of population declines in migratory species requires an understanding of how individuals are distributed between periods of the annual cycle. We built post- (fall) and pre-breeding (spring) migratory networks for the blackpoll warbler (Setophaga striata), a Neotropical-Nearctic songbird, using tracking data from 47 light-level geolocators deployed at 11 sites across its breeding range. During pre-breeding migration, two stopover nodes (regions) on the U.S. eastern seaboard received high scores in our network metrics (betweenness centrality and time-adjusted node weight), likely acting as key refuelling areas for most of the global blackpoll warbler population before their multi-day flights over the Atlantic Ocean. During post-breeding migration, highly ranked stopover nodes in the southeastern U.S. acted as a geographical bottleneck before birds dispersed to their boreal breeding destinations. Nodes located in northern Colombia and Venezuela were also ranked highly during both migrations and were likely used to prepare for (pre-breeding) and recover from (post-breeding) Atlantic flights. Blackpoll warblers showed a crosswise migration pattern, whereby individuals from western breeding populations tended to spend the nonbreeding season in the eastern part of the nonbreeding range and vice-versa. Despite this, the strength of migratory connectivity between the breeding and nonbreeding grounds ranged from moderate to low, largely because many individuals used more than one node during the ‘stationary’ nonbreeding period. Our results suggest that the number of breeding populations affected by a threat in the blackpoll warbler’s range will strongly depend on where and when this threat occurs. Consequently, our migratory network should be key to inform future conservation planning and population monitoring efforts.

Contributory science—including citizen and community science—allows scientists to leverage participant-generated data while providing an opportunity for engaging with local community members. Data yielded by participant-generated biodiversity platforms allow professional scientists to answer ecological and evolutionary questions across both geographic and temporal scales, which is incredibly valuable for conservation efforts. The data reported to contributory biodiversity platforms, such as eBird and iNaturalist, can be driven by social and ecological variables, leading to biased data. Though empirical work has highlighted the biases in contributory data, little work has articulated how biases arise in contributory data and the societal consequences of these biases. We present a conceptual framework illustrating how social and ecological variables create bias in contributory science data. In this framework, we present four filters—participation, detectability, sampling and preference—that ultimately shape the type and location of contributory biodiversity data. We leverage this framework to examine data from the largest contributory science platforms—eBird and iNaturalist—in St. Louis, Missouri, the United States, and discuss the potential consequences of biased data. Lastly, we conclude by providing several recommendations for researchers and institutions to move towards a more inclusive field. With these recommendations, we provide opportunities to ameliorate biases in contributory data and an opportunity to practice equitable biodiversity conservation. Read the free Plain Language Summary for this article on the Journal blog.

Assemblages in seasonal ecosystems undergo striking changes in species composition and diversity across the annual cycle. Despite a long‐standing recognition that seasonality structures biogeographic gradients in taxonomic diversity (e.g., species richness), our understanding of how seasonality structures other aspects of biodiversity (e.g., functional diversity) has lagged. Integrating seasonal species distributions with comprehensive data on key morphological traits for bird assemblages across North America, we find that seasonal turnover in functional diversity increases with the magnitude and predictability of seasonality. Furthermore, seasonal increases in bird species richness led to a denser packing of functional trait space, but functional expansion was important, especially in regions with higher seasonality. Our results suggest that the magnitude and predictability of seasonality and total productivity can explain the geography of changes in functional diversity with broader implications for understanding species redistribution, community assembly and ecosystem functioning. [ABSTRACT FROM AUTHOR]

High pathogenicity avian influenza virus (HPAIV) is a rapidly evolving virus causing significant economic and environmental harm. Wild birds are a key viral reservoir and an important source of viral incursions into animal populations, including poultry. However, we lack a thorough understanding of which species drive incursions and whether this changes over time. We explored associations between the abundances of 152 avian species and outbreaks of highly pathogenic avian influenza (HPAI) in poultry premises across Great Britain between October 2021 and January 2023. Spatial generalized additive models were used, with species abundance distributions sourced from eBird. Associations were investigated at the species-specific level and across species aggregations. During autumn/winter, associations were generally strongest with waterbirds such as ducks and geese; however, we also found significant associations in groups such as non-native gamebirds and rapid change in species-specific associations over time. Our results demonstrate the value of citizen science to rapidly explore wild species as potential facilitators of disease incursions into well-monitored populations, especially in regions where viral surveillance in wild species is limited. This can be a critical step towards prioritizing targeted surveillance that could inform species-specific biosecurity measures; particularly for HPAIV, which has undergone sudden shifts in host range and continues to rapidly evolve. [ABSTRACT FROM AUTHOR]

Research Highlight: Bourbour et al., 2024. Feeding en route: Prey availability and traits influence prey selection by an avian predator on migration. Journal of Animal Ecology. Diet selection plays a key role in the eco‐evolutionary dynamics of animals, exhibiting substantial variability across species, environments and seasons. The complex interplay between movement capability, hunting strategies, habitat use, prey traits and availability shapes the foraging patterns of avian predators. However, detailed information on how these birds exploit their extensive territories remains limited. In this study, Bourbour et al. utilised a novel integration of eDNA metabarcoding and citizen science to explore predator–prey interactions between migrating sharp‐shinned hawks (Accipiter striatus) and an ephemeral avian prey community along North America's Pacific flyway. The research identified 1396 detections from the diet (65 species) of 588 migrating sharp‐shinned hawks. Hawks' diet composition correlated with prey abundance indices sourced from the eBird database throughout the migration season, highlighting the significant impact of prey availability—shaped by migration tendency, flocking behaviour, and habitat—on raptor‐songbird interactions. Notably, the study also found significant differences in prey size between male and female hawks, indicating that sexual dimorphism has led to diverse foraging strategies during migration. These findings underscore the potential of combining eDNA metabarcoding with citizen science to deepen our understanding of the foraging ecology of highly mobile and wide‐ranging birds, as well as to monitor complex and vast ecosystems. [ABSTRACT FROM AUTHOR]

During animal migration, ephemeral communities of taxa at all trophic levels co‐occur over space and time. The interactions between predators and prey along migration corridors are ecologically and evolutionarily significant. However, these interactions remain understudied in terrestrial systems and warrant further investigations using novel approaches.We investigated the predator–prey interactions between a migrating avivorous predator and ephemeral avian prey community in the fall migration season. We tested for associations between avian traits and prey selection and hypothesized that prey traits (i.e. relative size, flocking behaviour, habitat, migration tendency and availability) would influence prey selection by a sexually dimorphic raptor on migration.To document prey consumption, we sampled trace prey DNA from beaks and talons of migrating sharp‐shinned hawks Accipiter striatus (n = 588). We determined prey availability in the ephemeral avian community by extracting weekly abundance indices from eBird Status and Trends data. We used discrete choice models to assess prey selection and visualized the frequency of prey in diet and availability on the landscape over the fall migration season.Using eDNA metabarcoding, we detected prey species on 94.1% of the hawks sampled (n = 525/588) comprising 1396 prey species detections from 65 prey species. Prey frequency in diet and eBird relative abundance of prey species were correlated over the migration season for top‐selected prey species, suggesting prey availability is an important component of raptor‐songbird interactions during fall. Prey size, flocking behaviour and non‐breeding habitat association were prey traits that significantly influenced predator choice. We found differences between female and male hawk prey selection, suggesting that sexual size dimorphism has led to distinct foraging strategies on migration.This research integrated field data collected by a volunteer‐powered raptor migration monitoring station and public‐generated data from eBird to reveal elusive predator–prey dynamics occurring in an ephemeral raptor‐songbird community during fall migration. Understanding dynamic raptor‐songbird interactions along migration routes remains a relatively unexplored frontier in animal ecology and is necessary for the conservation and management efforts of migratory and resident communities. [ABSTRACT FROM AUTHOR]

Understanding what drives the evolution of nectar‐robbing strategies is key for gaining insight into the functioning of pollination networks. However, nectar robbing is often an anecdotal behaviour, difficult to quantify and record through field observations, especially in hummingbirds, limiting our understanding of how ecological networks change across communities. Here, we report new records of nectar robbing by Peru's endemic Black Metaltail (Metallura phoebe) in a high‐elevation forest at ca. 4000 m a.s.l. and how this species uses either legitimate pollination feeding or nectar robbing in relation to corolla lengths. Furthermore, by analysing 452 citizen science records of photographic observations, we found that 36% of the photographs depicting a foraging event in this species were actually nectar‐robbing events. After identifying the plant species in all photographs involving foraging events, we describe how nectar robbing conducted by this hummingbird species is strongly associated with flowers that have longer corollas. We propose that the hummingbird‐flower interactions in harsh high‐altitude environments, where resources and competition vary markedly across seasons, can offer insight into the ecological drivers of nectar‐robbing behaviour in hummingbirds. [ABSTRACT FROM AUTHOR]

Biodiversity metrics have become a ubiquitous component of conservation assessments across scales. However, whilst indices have become increasingly widely used, their ability to perform in the face of different biases has remained largely untested under realistic conditions. Citizen science data are increasingly available, but present new challenges and biases, thus understanding how to use them effectively is essential. Here, we built a virtual world incorporating BirdLife data and accounting for their biases, then explored how well commonly‐used diversity metrics could estimate known values across a suite of representative scenarios. We used predictive modelling to model bird diversity globally and overcome biases using the approaches found most accurate in prior assessments. Performance was highly variable across the different types of biases, but in many instances Simpson's index performed best, followed by Hill numbers, whereas Pielou's index was almost universally worst. From standardised tests, we then applied these metrics to eBird data using 611 520 112 samples of 10 359 species of bird (around 88% of known species), to reconstruct global diversity patterns at five and ten km resolutions. However, when we mapped out diversity using Maxent based on these indices, Simpson's index generally over‐predicted diversity, whereas Hill numbers were more conservative. Based on an average of the better projected indices, one can map out diversity across resolutions and overcome biases accurately predicting diversity patterns even for data‐poor areas, but if a single metric is used, Hill numbers are most robust to bias. Going forward, this workflow will enable standardized best practices for diversity mapping based on a clear understanding of the performance of different metrics. [ABSTRACT FROM AUTHOR]

Every night during spring and autumn, the mass movement of migratory birds redistributes bird abundances found on the ground during the day. However, the connection between the magnitude of nocturnal migration and the resulting change in diurnal abundance remains poorly quantified. If departures and landings at the same location are balanced throughout the night, we expect high bird turnover but little change in diurnal abundance (stream‐like migration). Alternatively, migrants may move simultaneously in spatial pulses, with well‐separated areas of departure and landing that cause significant changes in the abundance of birds on the ground during the day (wave‐like migration). Here, we apply a flow model to data from weather surveillance radars (WSR) to quantify the daily fluxes of nocturnally migrating birds landing and departing from the ground, characterizing the movement and stopover of birds in a comprehensive synoptic scale framework. We corroborate our results with independent observations of the diurnal abundances of birds on the ground from eBird. Furthermore, we estimate the abundance turnover, defined as the proportion of birds replaced overnight. We find that seasonal bird migration chiefly resembles a stream where bird populations on the ground are continuously replaced by new individuals. Large areas show similar magnitudes of take‐off and landing, coupled with relatively small distances flown by birds each night, resulting in little change in bird densities on the ground. We further show that WSR‐inferred landing and take‐off fluxes predict changes in eBird‐derived abundance turnover rate and turnover in species composition. We find that the daily turnover rate of birds is 13% on average but can reach up to 50% on peak migration nights. Our results highlight that WSR networks can provide real‐time information on rapidly changing bird distributions on the ground. The flow model applied to WSR data can be a valuable tool for real‐time conservation and public engagement focused on migratory birds' daytime stopovers. [ABSTRACT FROM AUTHOR]

Using data from the mid-1990s to the present, we assessed correlations of Ruffed Grouse (Bonasa umbellus) hunter cooperator reports from seven states to Breeding Bird Survey, Christmas Bird Count, and eBird data to determine which program's trends best reflected patterns seen in hunter-sourced data that has historically been used for monitoring purposes. Christmas Bird Count data most closely reflected state-wide long-term trends in cooperator flush rates. Using an analytical approach that accounts for sources of bias and examines abundance at a finer spatial scale, we observed a pattern of decline across our study area. In recent decades, Ruffed Grouse populations in the eastern United States are thought to have suffered persistent declines due to a combination of young forest habitat loss and West Nile virus mortality. Declining hunter participation in much of the species' range has highlighted the need to identify harvest-independent indices of grouse abundance to enable continued monitoring of regional long-term trends. Recent analytical methods can better capture complex trends in population dynamics, account for biases inherent to community-sourced data, and potentially inform designs of future survey efforts aimed at fulfilling priority monitoring and research needs. Comparable results across varying statistical methodologies suggest that our inferences are robust, demonstrating that Christmas Bird Count data can be used to inform regional monitoring efforts for grouse and other cryptic game bird populations, but require careful consideration of program designs and protocols to identify and implement data appropriately. [ABSTRACT FROM AUTHOR]

Ecologists often leverage contributory science, also referred to as citizen science, to answer large-scale spatial and temporal biodiversity questions. Contributory science platforms, such as eBird and iNaturalist, provide researchers with incredibly fine-scale data to track biodiversity. However, data generated by these platforms are spatially biased. Research has shown that factors like income, race, and historical redlining can influence spatial patterns of reported eBird and iNaturalist data. However, the role of contemporary residential segregation remains unclear. Additionally, we do not understand how these variables potentially relate to certain Census tracts having more or less biodiversity data than you would expect based on size or population density. To further understand the social factors that may contribute to spatial biases in eBird and iNaturalist data, we focused on three cities within the USA (Oakland, California; St. Louis, Missouri; and Baltimore, Maryland). We specifically investigated how income, race, segregation, and redlining via Home Owners' Loan Corporation grades (grades A = best, B, C, and D = hazardous and "redlined") are associated with the difference between reported and expected observations based on area and human population density. We find that census tracts with higher income and more White people generally have more observations than expected. We only find segregation to influence differences in reported and expected observations in Baltimore, with more segregated Census tracts having more observations than expected. Lastly, we find that grades C and D consistently have fewer data than expected compared with grades A and B for both platforms in each city. Our results show that although each city has distinct societal and ecological features, societal inequity permeates each city to shape the uptake of data for two of the largest sources of biodiversity data. [ABSTRACT FROM AUTHOR]

Simple Summary: Early detection of the introduction and establishment of exotic species is crucial to prevent further spread and minimize negative impacts on native species, ecosystems, and agrosystems. Using citizen science and field surveys, this study documents the establishment and expansion of the Bare-eyed Pigeon, Patagioenas corensis, native to South America, on the island of Saint-Martin, the West Indies. Following its introduction about 10 years ago, the species is now expanding fast on the island, where it could compete with native bird species. First observed in coastal areas, the Bare-eyed Pigeon has progressively diversified its habitat use to exploit anthropized areas. Evidence for steady increases in both numbers and reproductive activity on the island calls for rapid management before it is too late. To that end, we strongly recommend adding the exotic Bare-eyed Pigeon to the official list of game species on Saint-Martin. Early reporting of the introduction and establishment of exotic species is of paramount importance for successful management. Here, we report the introduction and rapid spread of the Bare-eyed Pigeon, Patagioenas corensis, on the binational island of Saint-Martin, the West Indies. This range-restricted species naturally occurs in arid coastal areas of Columbia and Venezuela and nearby islands. Its introduction on Saint-Martin represents an expansion of about 1000 km beyond its established native range. Using observations recorded in eBird and results from a recent field survey, we show that since its introduction, most probably between late 2012 and early 2013, the species has expanded fast in Saint-Martin and has recently broadened its habitat to include anthropized, built areas. The expansion of Bare-eyed Pigeon on Saint-Martin and the neighboring Leeward Islands, possibly facilitated by climate change in the future, could be a threat to both native columbid species and other bird species through competition for resources. We therefore recommend that local authorities and stakeholders rapidly eradicate the species or at least prevent its further spread on Saint-Martin, possibly though listing it as a game species, while it is still possible to do so. [ABSTRACT FROM AUTHOR]

Aim: Answering many fundamental and applied scientific questions relies on accurate geographic range maps for species, such as those compiled by experts working with the International Union for Conservation of Nature (IUCN). However, these maps are resource demanding to produce and only available for a limited number of organisms. Here, we test to what extent standardized, data‐driven methods based on publicly available occurrences can reproduce expert‐based IUCN range maps and the macroecological conclusions drawn from them. Location: Global. Time Period: Present. Taxa: Birds. Materials and Methods: We estimated the geographic ranges for 7385 non‐marine bird species which either were non‐migratory or had spatially connected breeding and wintering ranges from publicly available, georeferenced point occurrences. We then quantified the spatial overlap between these range estimates and the IUCN expert‐derived range estimates. Finally, we compared global species richness patterns and the environmental correlates that emerge from both approaches. Results: We find that range estimates based on point occurrence records overlap on average 52% with expert range estimates for the same species. The global species richness patterns estimated under both approaches are overall similar but show local and regional differences, for example, in the tropical Andes of northern South America and the Central Arc region of Africa. The estimated global drivers of richness are similar. Main Conclusions: Expert‐derived estimates of species distributions are not reproducible by data‐driven approaches relying on currently available public records, even for well‐documented taxa such as birds. However, these discrepancies do not substantially change our macroecological understanding of global drivers of bird diversity. [ABSTRACT FROM AUTHOR]

Aim: Understanding and addressing the global biodiversity crisis requires ecological information compiled continuously from across the globe. Data from citizen science initiatives are useful for quantifying species' ecological niches and geographical distributions but can be difficult to apply towards biodiversity monitoring. The presence of fixed geographical locations reduces the opportunistic nature of citizen science data, allowing for more reliable and nuanced trend estimation. The eBird citizen‐science program contains predefined locations whose bird assemblages are sampled across years ('hotspots'). For hotspots to function as a biodiversity monitoring resource, issues related to data coverage, biases, and trends need to be addressed. Location: Global. Methods: We estimated the survey completeness of species richness at 300,500 eBird hotspots during 2002–2022. We documented sampling biases at eBird hotspot and non‐hotspot locations during 2022 based on protection status, temperature, precipitation, and landcover. Results: A total of 10,410 bird species (ca. 96.9% of total) were recorded at hotspots. The number of hotspots, checklists, and participants and the quality of species richness estimates increased worldwide with the Nearctic containing the strongest and most consistent trends. Compared to non‐hotspots, hotspots oversampled areas with higher protection status. Hotspots and non‐hotspots oversampled warmer and wetter locations in the Antarctic, Nearctic, and Palearctic, and cooler locations in the Afrotropics, Australasia, and the Neotropics. Hotspots and especially non‐hotspots oversampled urban areas. Hotspots and non‐hotspots undersampled shrublands in Australasia. Hotspots and especially non‐hotspots undersampled forests in the Afrotropics, Indomalaya, Neotropics, and Oceania. Main Conclusions: Hotspots have captured a large component of the world's avian diversity but have done so inconsistently across space and time. Data quantity and quality are increasing in many regions, but the presence of regionally specific sampling biases and spatial uncertainty in hotspot locations should be addressed when applying the data. [ABSTRACT FROM AUTHOR]

Tufted Titmice (Baeolophus bicolor) (TUTI) and Black-crested Titmice (Baeolophus atricristatus) (BCTI) are sister species that hybridize within a narrow east–west contact zone that extends from central Texas into southwest Oklahoma. The zone corresponds with an ecotone that transitions from closed-canopy deciduous forests in the east, occupied by TUTI, to arid and open woodlands in the west occupied by BCTI. Furthermore, the ecotone encompasses areas impacted by urban and suburban development. We tested whether landscape-level landcover characteristics found within the TUTI × BCTI hybrid zone influence the abundances of the two parent species and their hybrids. We predicted that the parent species would differ in their habitat associations and hybrids would associate with habitats intermediate between that of TUTI and BCTI and with human disturbed habitats. In ArcGIS Pro, we used a grid-based sampling design to extract estimates of six land cover variables (derived from National Landcover Database data) and TUTI, BCTI, and hybrid abundances (derived from eBird data). Partial redundancy analysis (RDA) was used to examine the habitat associations of the three titmice types. The results revealed that TUTI associated most strongly with the percentage of mixed forest cover, and BCTI with the percentage of evergreen forest cover and impervious surface cover. No single landcover variable could be identified as a definitive association for hybrids, however, hybrid individuals do appear to be more abundant in a habitat type that is intermediate between that of the two parent species. Future studies should incorporate genotypic data from titmice in the hybrid zone and analyze habitat associations at finer spatial scales to gain a more conclusive understanding of the patterns detected in this broad scale study. [ABSTRACT FROM AUTHOR]

Abstract Alternative ecological theories make divergent predictions about the relationship between predators and their prey. If predators exert top‐down ecosystem control, increases in predation should diminish prey abundance and could either diminish or enhance community diversity of prey species. However, if bottom‐up ecosystem controls predominate, predator populations should track underlying variation in prey diversity and abundance, which ultimately should reflect available energy. Past research, both across islands and comparing islands with the mainland, has frequently invoked the importance of predation in regulating lizard abundance and diversity, suggesting an important role of top‐down control when predators are present. However, others have posited a stronger role of food limitation, via competition or bottom‐up forces. If top‐down control predominates, then negative correlations between prey abundance and predator occurrence should emerge within and among islands. Using data from eBird, we inferred landscape‐level presence data for bird species on the islands of Jamaica and Hispaniola. By summing occurrence probabilities of all known anole‐predator birds, we estimated total avian predation pressure and combined these estimates with anole community data from a mark‐recapture study that spanned spatial and climatic gradients on both islands. Avian predators and anole lizards were both affected by climate, with total predator occurrence, anole abundance and anole species richness increasing with mean annual temperature. Anole abundance and predator occurrence showed a curvilinear relationship, where abundance and predator occurrence increased together until predator occurrence became sufficiently high that anole abundance was negatively impacted. This indicates that bottom‐up ecosystem controls drive richness of both anoles and their predators, mitigating the negative effects predators might have on their prey, at least until predator occurrence reaches a threshold. We did not detect consistent evidence of predator occurrence reducing anole community richness. These findings support past research showing that islands with more predators tend to have lower prey abundances, but it does not seem that these top‐down forces are strongly limiting species coexistence. Instead, bottom‐up forces linked with climate may be more important drivers of diversity in both lizards and their avian predators on these islands.

Abstract Hierarchical models are common for ecological analysis, but determining appropriate model selection methods remains an ongoing challenge. To confront this challenge, a suitable method is needed to evaluate and compare available candidate models. We compared performance of conditional WAIC, a joint-likelihood approach to WAIC (WAICj), and posterior-predictive loss for selecting between candidate N-mixture models. We tested these model selection criteria on simulated single-season N-mixture models, simulated multi-season N-mixture models with temporal auto-correlation, and three case studies of single-season N-mixture models based on eBird data. WAICj proved more accurate than the standard conditional formulation or posterior-predictive loss, even when models were temporally correlated, suggesting WAICj is a robust alternative to model selection for N-mixture models.

Hierarchical models are common for ecological analysis, but determining appropriate model selection methods remains an ongoing challenge. To confront this challenge, a suitable method is needed to evaluate and compare available candidate models. We compared performance of conditional WAIC, a joint-likelihood approach to WAIC (WAICj), and posterior-predictive loss for selecting between candidate N-mixture models. We tested these model selection criteria on simulated single-season N-mixture models, simulated multi-season N-mixture models with temporal auto-correlation, and three case studies of single-season N-mixture models based on eBird data. WAICj proved more accurate than the standard conditional formulation or posterior-predictive loss, even when models were temporally correlated, suggesting WAICj is a robust alternative to model selection for N-mixture models. [ABSTRACT FROM AUTHOR]

Citizen science platforms such as eBird provide essential spatiotemporal information and big data for the study of birds. The analysis of an extensive 20-year dataset of the distribution of the Eurasian Magpie Pica pica showed that the species is steadily expanding within urbanised areas in the south of the Iberian Peninsula. The occurrence of the species in the eBird checklists in the study area has an average exponential growth rate greater than 20%. The area occupied by the species has multiplied by 40 in the last 20 years, going from 25 to almost 1000 km2. In order to test potential negative impacts of this demographic expansion on potential Magpie prey species, such as other birds, a seasonal study of the Magpie's diet through pellet analysis showed that its stable diet consists of insects, snails and seeds, while other birds or food from anthropogenic sources does not constitute a significant part of its diet. The combined use of new open-science big data technologies together with classical monitoring and laboratory study offers indispensable tools for the assessment of species distribution and potential spatial management. [ABSTRACT FROM AUTHOR]

Aim: Ongoing climate change is presently influencing the distribution ranges of numerous species, with both range expansions and latitudinal shifts being observed. In southern Europe, a biogeographical border that separates African and European biota, while at the same time acting as a migration bridge for many species, these changes are of particular relevance. This study aimed to analyse the responses of nine typically African birds to climate change to provide information on the ongoing and future occupation of Europe by these species. Location: Western Palearctic and surrounding areas. Methods: To this end, the distributions of the species in their native ranges were modelled, both in the present and in future climate scenarios, using their current breeding ranges and a set of topographic and climatic variables. The climatic favourability for the nine species was then combined using fuzzy logic. Results: The results showed that southern Europe is highly favourable for our set of African birds, except for Rüppell's Vulture, and future forecasts indicated that this favourability would increase further north, again excluding the African Vulture. Main conclusions: If the climate continues to warm, further arrivals of individuals are to be expected, increasing the possibility that self‐sustaining populations may become established in southern Europe. Furthermore, new African species may start to occupy this area, with the likelihood of an Africanisation of the European fauna. Considering the role played by southern Europe as a potential focal point for the colonisation of this continent by African species, it is important to track their northward expansion and future spread. [ABSTRACT FROM AUTHOR]

Copyright of Avian Conservation & Ecology is the property of Resilience Alliance and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Citizen science is a popular approach to biodiversity surveying, whereby data that are collected by volunteer naturalists may help analysts to understand the distribution and abundance of wild organisms. In Australia, birdwatchers have contributed to two major citizen science programs, eBird (run by the Cornell Lab of Ornithology) and Birdata (run by Birdlife Australia), which collectively hold more than 42 million records of wild birds from across the country. However, these records are not evenly distributed across space, time, or taxonomy, with particularly significant variation in the number of records of each species in these datasets. In this paper, we explore this variation and seek to determine which Australian bird species are least known as determined by rates of citizen science survey detections. We achieve this by comparing the rates of survey effort and species detection across each Australian bird species' range, assigning all 581 species to one of the four groups depending on their rates of survey effort and species observation. We classify 56 species into a group considered the most poorly recorded despite extensive survey effort, with Coxen's Fig Parrot Cyclopsitta coxeni, Letter-winged Kite Elanus scriptus, Night Parrot Pezoporus occidentalis, Buff-breasted Buttonquail Turnix olivii and Red-chested Buttonquail Turnix pyrrhothorax having the very lowest numbers of records. Our analyses provide a framework to identify species that are poorly represented in citizen science datasets. We explore the reasons behind why they may be poorly represented and suggest ways in which targeted approaches may be able to help fill in the gaps. [ABSTRACT FROM AUTHOR]

Bird migration in the Neotropics is complex and highly diverse. Indeed, for many taxa, basic questions such as where they go are still relevant. Satellite-tracking studies of Turkey Vulture (Cathartes aura) migration have revealed extensive variability in their movement strategies, contributing to their widespread distribution. However, South American migratory populations are still among the least explored. By integrating five years of satellite-tracking data, citizen science databases and classical raptor monitoring techniques, we present a case study reporting a hitherto unknown nonbreeding area for the Turkey Vulture subspecies ruficollis. Specifically, we document that a minor proportion of the population that breeds in northwestern Argentine Patagonia migrates northwards to central Chile at the beginning of the austral autumn. Our findings improve our basic knowledge of the Turkey Vulture migration within the Neotropics and establish a baseline to study the movement strategies of the migratory ruficollis populations breeding in high latitudes of South America. [ABSTRACT FROM AUTHOR]

Aim: Climate change and habitat loss or degradation are some of the greatest threats that species face today, often resulting in range shifts. Species traits have been discussed as important predictors of range shifts, with the identification of general trends being of great interest to conservation efforts. However, studies reviewing relationships between traits and range shifts have questioned the existence of such generalized trends, due to mixed results and weak correlations, as well as analytical shortcomings. The aim of this study was to test this relationship empirically, using analytical approaches that account for common sources of bias when assessing range trends. Location: Tanzania, East Africa. Time period: 1980–1999 and 2000–2020. Major taxa studied: 57 savannah specialist birds found in Tanzania, belonging to 26 families and 11 orders. Methods: We applied recently developed integrated spatio‐temporal species distribution models in R‐INLA, combining citizen science and bird Atlas data to estimate ranges of species, quantify range shifts, and test the predictive power of traditional trait groups, as well as exposure‐related and sensitivity traits. We based our study on 40 years of bird observations in East African savannahs, a biome that has experienced increasing climatic and non‐climatic pressures over recent decades. We correlated patterns of change with species traits using linear regression models. Results: We find indications of relationships identified by previous research, but low average explanatory power of traits from an ecological perspective, confirming the lack of meaningful general associations. However, our analysis finds compelling species‐specific results. Main conclusions: We highlight the importance of individual assessments while demonstrating the usefulness of our analytical approach for analyses of range shifts. [ABSTRACT FROM AUTHOR]

Aim: Some species thrive in human‐dominated environments, while others are highly sensitive to all human pressures. However, standardized estimates of species' tolerances to human pressures are lacking at large spatial extents and taxonomic breadth. Here, we quantify the world's bird species' tolerances to human pressures. The associated precision values can be applied to scientific research and conservation. Location: Global. Time Period: 2013–2021. Major Taxa Studied: 6090 bird species. Methods: We used binary observation data from eBird and modelled species' occurrences as a function of the Human Footprint Index (HFI). With these models, we predicted how likely each species was to occur under different levels of human pressures. Then, we calculated each species' Human Tolerance Index (HTI) as the level of the HFI where predicted occurrence probability was reduced to 50% of the maximum species' occurrence probability. We used resampling to obtain estimates of uncertainty of the Human Tolerance Indices. We also compared tolerances across species with increasing, stable, and decreasing population trends. Results: We found that 22% of the bird species tolerated the most modified human‐dominated environments, whereas 0.001% of species only occurred in the intact environments. We also found that HTI varied according to species' population trend categories, whereby species with decreasing population trends had a lower tolerance than species with increasing or stable population trends. Main Conclusions: The estimated HTI indicates the potential of species to exist in a landscape of intensifying human pressures. It can identify species unable to tolerate these environments and inform subsequent conservation efforts. We found evidence that species' sensitivity to human‐dominated environments may be driving birds' use of space. Bird species' tolerances are also linked to their population trends, making the tolerances a relevant addition to conservation planning. [ABSTRACT FROM AUTHOR]

Abstract Contributory science—including citizen and community science—allows scientists to leverage participant‐generated data while providing an opportunity for engaging with local community members. Data yielded by participant‐generated biodiversity platforms allow professional scientists to answer ecological and evolutionary questions across both geographic and temporal scales, which is incredibly valuable for conservation efforts. The data reported to contributory biodiversity platforms, such as eBird and iNaturalist, can be driven by social and ecological variables, leading to biased data. Though empirical work has highlighted the biases in contributory data, little work has articulated how biases arise in contributory data and the societal consequences of these biases. We present a conceptual framework illustrating how social and ecological variables create bias in contributory science data. In this framework, we present four filters—participation, detectability, sampling and preference—that ultimately shape the type and location of contributory biodiversity data. We leverage this framework to examine data from the largest contributory science platforms—eBird and iNaturalist—in St. Louis, Missouri, the United States, and discuss the potential consequences of biased data. Lastly, we conclude by providing several recommendations for researchers and institutions to move towards a more inclusive field. With these recommendations, we provide opportunities to ameliorate biases in contributory data and an opportunity to practice equitable biodiversity conservation. Read the free Plain Language Summary for this article on the Journal blog.

Copyright of Bulletin of the L.N. Gumilyov Eurasian National University. Bioscience Series is the property of L.N. Gumilyov Eurasian National University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Contributory science—including citizen and community science—allows scientists to leverage participant‐generated data while providing an opportunity for engaging with local community members. Data yielded by participant‐generated biodiversity platforms allow professional scientists to answer ecological and evolutionary questions across both geographic and temporal scales, which is incredibly valuable for conservation efforts.The data reported to contributory biodiversity platforms, such as eBird and iNaturalist, can be driven by social and ecological variables, leading to biased data. Though empirical work has highlighted the biases in contributory data, little work has articulated how biases arise in contributory data and the societal consequences of these biases.We present a conceptual framework illustrating how social and ecological variables create bias in contributory science data. In this framework, we present four filters—participation, detectability, sampling and preference—that ultimately shape the type and location of contributory biodiversity data. We leverage this framework to examine data from the largest contributory science platforms—eBird and iNaturalist—in St. Louis, Missouri, the United States, and discuss the potential consequences of biased data.Lastly, we conclude by providing several recommendations for researchers and institutions to move towards a more inclusive field. With these recommendations, we provide opportunities to ameliorate biases in contributory data and an opportunity to practice equitable biodiversity conservation. Read the free Plain Language Summary for this article on the Journal blog. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

Context: Species distribution models are widely used in ecology. The selection of environmental variables is a critical step in SDMs, nowadays compounded by the increasing availability of environmental data. Objectives: To evaluate the interaction between the grain size and the binary (presence or absence of water) or proportional (proportion of water within the cell) representation of the water cover variable when modeling water bird species distribution. Methods: eBird occurrence data with an average number of records of 880,270 per species across the North American continent were used for analysis. Models (via Random Forest) were fitted for 57 water bird species, for two seasons (breeding vs. non-breeding), at four grains (1 km2 to 2500 km2) and using water cover as a proportional or binary variable. Results: The models’ performances were not affected by the type of the adopted water cover variable (proportional or binary) but a significant decrease was observed in the importance of the water cover variable when used in a binary form. This was especially pronounced at coarser grains and during the breeding season. Binary representation of water cover is useful at finer grain sizes (i.e., 1 km2). Conclusions: At more detailed grains (i.e., 1 km2), the simple presence or absence of a certain land-cover type can be a realistic descriptor of species occurrence. This is particularly advantageous when collecting habitat data in the field as simply recording the presence of a habitat is significantly less time-consuming than recording its total area. For models using coarser grains, we recommend using proportional land-cover variables. [ABSTRACT FROM AUTHOR]

Tracking the state of biodiversity over time is critical to successful conservation, but conventional monitoring schemes tend to be insufficient to adequately quantify how species' abundances and distributions are changing. One solution to this issue is to leverage data generated by citizen scientists, who collect vast quantities of data at temporal and spatial scales that cannot be matched by most traditional monitoring methods. However, the quality of citizen science data can vary greatly. In this paper, we develop three metrics (inventory completeness, range completeness, spatial bias) to assess the adequacy of spatial observation data. We explore the adequacy of citizen science data at the species level for Australia's terrestrial native birds and then model these metrics against a suite of seven species traits (threat status, taxonomic uniqueness, body mass, average count, range size, species density, and human population density) to identify predictors of data adequacy. We find that citizen science data adequacy for Australian birds is increasing across two of our metrics (inventory completeness and range completeness), but not spatial bias, which has worsened over time. Relationships between the three metrics and seven traits we modelled were variable, with only two traits having consistently significant relationships across the three metrics. Our results suggest that although citizen science data adequacy has generally increased over time, there are still gaps in the spatial adequacy of citizen science for monitoring many Australian birds. Despite these gaps, citizen science can play an important role in biodiversity monitoring by providing valuable baseline data that may be supplemented by information collected through other methods. We believe the metrics presented here constitute an easily applied approach to assessing the utility of citizen science datasets for biodiversity analyses, allowing researchers to identify and prioritise regions or species with lower data adequacy that will benefit most from targeted monitoring efforts. Citizen science data are increasingly being used to monitor biodiversity, but datasets produced by citizen scientists come with a number of well‐recognised challenges. In this paper, we develop several metrics to assess the adequacy of spatial observation data from citizen science projects and explore these metrics at the species level for Australia's terrestrial birds. We find that data adequacy for most Australian birds is increasing, but several gaps still remain in the spatial coverage of citizen science data across the Australian continent. [ABSTRACT FROM AUTHOR]

Monitoring is vital to conservation, enabling conservation scientists to detect population declines, identify threats and measure the effectiveness of interventions. However, not all threatened taxa are monitored, monitoring quality is variable, and the various components of monitoring are likely to differ in their rates of improvement over time. We assessed the presence of monitoring and monitoring quality, using a range of metrics, for all Australia's threatened bird taxa from 1990 to 2020 (four assessments spanning 30 years). We used our assessments to understand decadal trends in the number of taxa monitored; monitoring quality; and the groups that conduct monitoring. The monitoring of Australia's threatened birds has increased substantially since 1990, from 19% of taxa to 75% in 2020. Monitoring quality has also improved, with 24.1% of taxa assessed overall as 'Good' or 'Very Good' in 2020 (up from 4.8% in 1990). However, by 2020, most monitoring programmes still scored poorly for Data availability/reporting, Management linkage, Demographic data and Training/succession planning. In 2020, private individuals and governments accounted for 59% of monitoring contributions, with the greatest number of taxa monitored by private individuals (79 of 166 taxa assessed). Despite improvements in monitoring since 1990, only a minority of taxa had high-quality monitoring in the most recent assessment period. Monitoring is a powerful tool in conservation, justifying investment in improving how it is conducted. We draw on our results and examples of high-quality monitoring programmes to develop a set of priority actions to improve monitoring of Australia's threatened birds. Although monitoring of Australia's threatened birds has improved greatly over the last 30 years, most-threatened bird taxa still have inadequate monitoring and systemic changes are required to improve monitoring quality on the scale required. We recommend priority actions to improve monitoring including funding reforms, targeted improvements of poor performing monitoring components and actions to boost some of the current strengths in monitoring programmes. Private individuals conduct monitoring for more taxa than any other group, so boosting the quality of their monitoring is especially important. [ABSTRACT FROM AUTHOR]

Citizen science projects are valuable tools since they provide substantial amounts of data on different animal species. Currently, there are a wide variety of platforms and objectives for diverse citizen science projects. Despite these advances, the approaches and contributions of citizen science platforms for collecting data on a particular species, and in a specific site or region, have been poorly explored. Thus, in this article, we compare the number of participants and the amount of data collected by three platforms on the Toco toucan (Ramphastos toco) in San Salvador de Jujuy city, located in northwestern Argentina. This particular bird species is very charismatic and frequents urban areas all year round; so that, it is interesting to know what contributions (e.g. participant numbers, ecological and distribution data) are being made about this species on citizen science platforms. Thus, we examined data reported by two global citizen science platforms, iNaturalist and eBird, and one local platform, Tucanes en mi Jujuy (TEMJ). We found that the local, focal TEMJ project had a greater number of participants (n = 193), greater presence records (n = 614) and a wide spatial distribution of data in the city. In the iNaturalist and eBird platforms, the number of participants was smaller (n = 9 and 36, respectively), with fewer presence records (n = 12 and 178, respectively), and even fewer reports of species‐specific ecological data (feeding, behaviour and age). This reflected clear differences between the three platforms, as TEMJ not only reported more presence data but also more detailed information on age and behaviour. Based on this research, we highlight the commitment of citizens to this particular project and the study of species. Therefore, we recommend the implementation of new local and focal citizen science platforms for more detailed ecological data on other charismatic and focal species. [ABSTRACT FROM AUTHOR]

The Ruddy Shelduck (Tadorna ferruginea) is a vagrant passage and wintering species whose presence and distribution in Serbia have been inadequately studied. This study presents new findings of T. ferruginea in Serbia based on two sources of data: unpublished eBird checklists from 2014 to 2019 and new data collected from 2020 to 2023. Observations were conducted at various localities across Serbia, including Jezero Ćelije, Begečka Jama, Smilovci Lake, Aleksandrovačko Lake, Sava shipyard, fish farms of Novi Kneževac, Bečej, and Čenta, as well as the Special Nature Reserve Slano Kopovo. These sightings contribute to our understanding of the species' distribution within Serbia and underscore the importance of ongoing monitoring efforts. The potential impacts of these results on upcoming research and conservation initiatives, which are focused on safeguarding the populations of T. ferruginea within the area, are examined.

Identifying rates at which birders engage with different species can inform the impact and efficacy of conservation outreach and the scientific use of community-collected biodiversity data. Species that are thought to be “charismatic” are often prioritized in conservation, and previous researchers have used sociological experiments and digital records to estimate charisma indirectly. In this study, we take advantage of community science efforts as another record of human engagement with animals that can reveal observer biases directly, which are in part driven by observer preference. We apply a multistage analysis to ask whether opportunistic birders contributing to iNaturalist engage more with larger, more colorful, and rarer birds relative to a baseline approximated from eBird contributors. We find that body mass, color contrast, and range size all predict overrepresentation in the opportunistic dataset. We also find evidence that, across 472 modeled species, 52 species are significantly overreported and 158 are significantly underreported, indicating a wide variety of species-specific effects. Understanding which birds are highly engaging can aid conservationists in creating impactful outreach materials and engaging new naturalists. The quantified differences between two prominent community science efforts may also be of use for researchers leveraging the data from one or both of them to answer scientific questions of interest.

Anthropogenic habitat modification is a leading contributor to biodiversity change, but it is unclear what factors, including scale, influence the magnitude of change. Changes in species richness and its scaling relationship across an anthropogenic gradient can be influenced by changes in the total number of individuals in each sample, the species abundance distribution, and/or the spatial arrangement of conspecific individuals. Here, we integrated continental‐scale citizen science data on bird occurrences across the contiguous United States – from eBird – with an analytical framework capable of dissecting the aforementioned biodiversity components to quantify bird diversity changes along an anthropogenic landscape habitat modification gradient. We found an overall decline in bird diversity along an anthropogenic modification gradient, with peak levels of bird diversity at low to moderate levels of modification. The magnitude of biodiversity change was greater at gamma than at alpha scales and was most strongly associated with a declining number of individuals along the anthropogenic gradient. Spatial species turnover was lower at higher impacted sites, but this was also due to the sampling of fewer individuals rather than changes in spatial species patchiness. Our results suggest that local‐scale management can promote bird diversity, especially at the natural–rural–suburban interface. Management efforts (e.g. managing natural habitat or preserving urban greenspaces against development) should be focused on creating, restoring, and preserving resources (e.g. nesting habitat, foraging resources) necessary for a large number of individuals, as this is the primary influence of diversity change along an anthropogenic gradient. [ABSTRACT FROM AUTHOR]

Effective solutions to conserve biodiversity require accurate community‐ and species‐level information at relevant, actionable scales and across entire species' distributions. However, data and methodological constraints have limited our ability to provide such information in robust ways. Herein we employ a Deep‐Reasoning Network implementation of the Deep Multivariate Probit Model (DMVP‐DRNets), an end‐to‐end deep neural network framework, to exploit large observational and environmental data sets together and estimate landscape‐scale species diversity and composition at continental extents. We present results from a novel year‐round analysis of North American avifauna using data from over nine million eBird checklists and 72 environmental covariates. We highlight the utility of our information by identifying critical areas of high species diversity for a single group of conservation concern, the North American wood warblers, while capturing spatiotemporal variation in species' environmental associations and interspecific interactions. In so doing, we demonstrate the type of accurate, high‐resolution information on biodiversity that deep learning approaches such as DMVP‐DRNets can provide and that is needed to inform ecological research and conservation decision‐making at multiple scales. [ABSTRACT FROM AUTHOR]