115 research outputs found
Seasonal species richness of birds on the world's islands and its geographical correlates
The presence of migratory birds on islands results in seasonal variation in species richness. These patterns and their geographical correlates within the context of island biogeography theory have not been examined. We used 21 years of bird observations on 690 islands from eBird to determine how seasonal species richness estimates vary as a function of island area, isolation and latitude. Species richness was highest on islands within the northern mid-latitudes during migration and on islands within tropical latitudes during the non-breeding season. Area defined positive, nonlinear relationships with species richness across seasons, with the steepest slopes occurring with islands greater than 1100 km2. Distance to mainland defined negative, nonlinear relationships with species richness across seasons, with the strongest slopes occurring with islands located greater than 150 km from the mainland. Species-area relationships were weakest for the most remote islands and strongest for islands at intermediate distances to the mainland. Intermediate proximity to other islands was a poor predictor of species richness. Our findings emphasize the presence of seasonally dynamic geographical relationships, the enhanced role of evolutionary processes on larger islands, the unique ecology of the world's most remote islands, and the importance of islands as stopover sites and wintering grounds for migratory bird species
Population-level scaling of avian migration speed with body size and migration distance for powered fliers
Optimal migration theory suggests specific scaling relationships between body size and migration speed for individual birds based on the minimization of time, energy, and risk. Here we test if the quantitative predictions originating from this theory can be detected when migration decisions are integrated across individuals. We estimated population-level migration trajectories and daily migration speeds for the combined period 2007–2011 using the eBird data set. We considered 102 North American bird species that use flapping or powered flight during migration. Many species, especially in eastern North America, had looped migration trajectories that traced a clockwise path with an eastward shift during autumn migration. Population-level migration speeds decelerated rapidly going into the breeding season, and accelerated more slowly during the transition to autumn migration. In accordance with time minimization predictions, spring migration speeds were faster than autumn migration speeds. In agreement with optimality predictions, migration speeds of powered flyers scaled negatively with body mass similarly during spring and autumn migration. Powered fliers with longer migration journeys also had faster migration speeds, a relationship that was more pronounced during spring migration. Our findings indicate that powered fliers employed a migration strategy that, when examined at the population level, was in compliance with optimality predictions. These results suggest that the integration of migration decisions across individuals does result in population-level patterns that agree with theoretical expectations developed at the individual level, indicating a role for optimal migration theory in describing the mechanisms underlying broadscale patterns of avian migration for species that use powered flight
Seasonal associations with light pollution trends for nocturnally migrating bird populations
This project was supported by The Leon Levy Foundation, The Wolf Creek Charitable Foundation, Lyda Hill Philanthropies, Amon G. Carter Foundation, National Aeronautics and Space Administration (80NSSC21K1143), and National Science Foundation (ABI sustaining DBI-1939187, GCR-2123405). Computing support was provided by the National Science Foundation (CNS-1059284 and CCF-1522054), and the Extreme Science and Engineering Discovery Environment (XSEDE; National Science Foundation, ACI-1548562) through allocation TG-DEB200010 run on Bridges at the Pittsburgh Supercomputing Center.Artificial light at night (ALAN) is adversely affecting natural systems worldwide, including the disorienting influence of ALAN on nocturnally migrating birds. Understanding how ALAN trends are developing across species' seasonal distributions will inform mitigation efforts, such as Lights Out programs. Here, we intersect ALAN annual trend estimates (1992-2013) with weekly estimates of relative abundance for 42 nocturnally migrating passerine bird species that breed in North America using observations from the eBird community science database for the combined period 2005-2020. We use a cluster analysis to identify species with similar weekly associations with ALAN trends. Our results identified three prominent clusters. Two contained species that occurred in northeastern and western North America during the breeding season. These species were associated with moderate ALAN levels and weak negative ALAN trends during the breeding season, and low ALAN levels and strong positive ALAN trends during the nonbreeding season. The difference between the breeding and nonbreeding seasons was lower for species that occurred in northern South America and greater for species that occurred in Central America during the nonbreeding season. For species that occurred in South America during the nonbreeding season, positive ALAN trends increased in strength as species migrated through Central America, especially in the spring. The third cluster contained species whose associations with positive ALAN trends remained high across the annual cycle, peaking during migration, especially in the spring. These species occurred in southeastern North America during the breeding season where they were associated with high ALAN levels, and in northern South America during the nonbreeding season where they were associated with low ALAN levels. Our findings suggest reversing ALAN trends in Central America during migration, especially in the spring, would benefit the most individuals of the greatest number of species. Reversing ALAN trends in southeastern North America during the breeding season and Central America during the nonbreeding season would generate the greatest benefits outside of migration.Publisher PDFPeer reviewe
Citizen‐science data provides new insight into annual and seasonal variation in migration patterns
Opportunities and challenges for big data ornithology
Recent advancements in information technology and data acquisition have created both new research opportunities and new challenges for using big data in ornithology. We provide an overview of the past, present, and future of big data in ornithology, and explore the rewards and risks associated with their application. Structured data resources (e.g., North American Breeding Bird Survey) continue to play an important role in advancing our understanding of bird population ecology, and the recent advent of semistructured (e.g., eBird) and unstructured (e.g., weather surveillance radar) big data resources has promoted the development of new empirical perspectives that are generating novel insights. For example, big data have been used to study and model bird diversity and distributions across space and time, explore the patterns and determinants of broad-scale migration strategies, and examine the dynamics and mechanisms associated with geographic and phenological responses to global change. The application of big data also holds a number of challenges wherein high data volume and dimensionality can result in noise accumulation, spurious correlations, and incidental endogeneity. In total, big data resources continue to add empirical breadth and detail to ornithology, often at very broad spatial extents, but how the challenges underlying this approach can best be mitigated to maximize inferential quality and rigor needs to be carefully considered.
Los avances recientes en la tecnolog´ıa de la informaci ´on y la adquisici ´on de datos han creado tanto nuevas oportunidades de investigaci ´on como desaf´ıos para el uso de datos masivos (big data) en ornitolog´ıa. Brindamos una visi ´on general del pasado, presente y futuro de los datos masivos en ornitolog´ıa y exploramos las recompensas y desaf´ıos asociados a su aplicaci ´ on. Los recursos de datos estructurados (e.g., Muestreo de Aves Reproductivas de Am´erica del Norte) siguen jugando un rol importante en el avance de nuestro entendimiento de la ecolog´ıa de poblaciones de las aves, y el advenimiento reciente de datos masivos semi-estructurados (e.g., eBird) y desestructurados (e.g., radar de vigilancia clima´tica) han promovido el desarrollo de nuevas perspectivas emp´ıricas que esta´n generando miradas novedosas. Por ejemplo, los datos masivos han sido usados para estudiar y modelar la diversidad y distribuci ´on de las aves a trav´es del tiempo y del espacio, explorar los patrones y los determinantes de las estrategias de migraci ´on a gran escala, y examinar las dina´micas y los mecanismos asociados con las respuestas geogra´ficas y fenol ´ ogicas al cambio global. La aplicaci ´on de datos masivos tambi´en contiene una serie de desaf´ıos donde el gran volumen de datos y la dimensionalidad pueden generar una acumulaci ´on de ruido, correlaciones espurias y endogeneidad incidental. En total, los recursos de datos masivos contin ´uan agregando amplitud y detalle emp´ırico a la ornitolog´ıa, usualmente a escalas espaciales muy amplias, pero necesita considerarse cuidadosamente c ´omo los desaf´ıos que subyacen este enfoque pueden ser mitigados del mejor modo para maximizar su calidad inferencial y rigor
The role of artificial light at night and road density in predicting the seasonal occurrence of nocturnally migrating birds
The Leon Levy Foundation; The Wolf Creek Charitable Foundation; Lyda Hill Philanthropies; Amon G. Carter Foundation; National Science Foundation, Grant/Award Number: ABI sustaining DBI-1939187 and ICER-1927743. Computing support was provided by the National Science Foundation, Grant/Award Number: CNS-1059284 and CCF-1522054, and the Extreme Science and Engineering Discovery Environment (XSEDE), National Science Foundation, Grant/Award Number: ACI-1548562, through allocation TG-DEB200010 run on Bridges at the Pittsburgh Supercomputing Center.Aim: Artificial light at night (ALAN) and roads are known threats to nocturnally migrating birds. How associations with ALAN and roads are defined in combination for these species at the population level across the full annual cycle has not been explored. Location: Western Hemisphere. Methods: We estimated range‐wide exposure, predictor importance and the prevalence of positive associations with ALAN and roads at a weekly temporal resolution for 166 nocturnally migrating bird species in three orders: Passeriformes (n = 104), Anseriformes (n = 27) and Charadriiformes (n = 35). We clustered Passeriformes based on the prevalence of positive associations. Results: Positive associations with ALAN and roads were more prevalent for Passeriformes during migration when exposure and importance were highest. Positive associations with ALAN and roads were more prevalent for Anseriformes and Charadriiformes during the breeding season when exposure was lowest. Importance was uniform for Anseriformes and highest during migration for Charadriiformes. Our cluster analysis identified three groups of Passeriformes, each having similar associations with ALAN and roads. The first occurred in eastern North America during migration where exposure, prevalence, and importance were highest. The second wintered in Mexico and Central America where exposure, prevalence and importance were highest. The third occurred throughout North America where prevalence was low, and exposure and importance were uniform. The first and second were comprised of dense habitat specialists and long‐distance migrants. The third was comprised of open habitat specialists and short distance migrants. Main conclusions: Our findings suggest ALAN and roads pose the greatest risk during migration for Passeriformes and during the breeding season for Anseriformes and Charadriiformes. Our results emphasise the close relationship between ALAN and roads, the diversity of associations dictated by taxonomy, exposure, migration strategy and habitat and the need for more informed and comprehensive mitigation strategies where ALAN and roads are treated as interconnected threats.Publisher PDFPeer reviewe
Citizen-science data provides new insight into annual and seasonal variation in migration patterns
Current rates of global environmental and climate change pose potential challenges for migratory species that must cope with or adapt to new conditions and different rates of change across broad spatial scales throughout their annual life cycle. North American migratory hummingbirds may be especially sensitive to changes in environment and climate due to their extremely small body size, high metabolic rates, and dependence on nectar as a main resource. We used occurrence information from the eBird citizen-science database to track migratory movements of five North American hummingbird species (Archilochus alexandri, A. colubris, Selasphorus calliope, S. platycercus, and S. rufus) across 6 years (2008–2013) at a daily temporal resolution to describe annual and seasonal variation in migration patterns. Our findings suggest that the timing of the onset of spring migration generally varies less than the arrival on the wintering grounds. Species follow similar routes across years, but exhibit more variation in daily longitude than latitude. Long distance migrants generally had less annual variation in geographic location and timing than shorter distance migrants. Our study is among the first to examine variation in migration routes and timing for hummingbirds, but more work is needed to understand the capacity of these species to respond to different rates of environmental change along their migratory routes
Can Observation Skills of Citizen Scientists Be Estimated Using Species Accumulation Curves?
Volunteers are increasingly being recruited into citizen science projects to collect observations for scientific studies. An additional goal of these projects is to engage and educate these volunteers. Thus, there are few barriers to participation resulting in volunteer observers with varying ability to complete the project’s tasks. To improve the quality of a citizen science project’s outcomes it would be useful to account for inter-observer variation, and to assess the rarely tested presumption that participating in a citizen science projects results in volunteers becoming better observers. Here we present a method for indexing observer variability based on the data routinely submitted by observers participating in the citizen science project eBird, a broad-scale monitoring project in which observers collect and submit lists of the bird species observed while birding. Our method for indexing observer variability uses species accumulation curves, lines that describe how the total number of species reported increase with increasing time spent in collecting observations. We find that differences in species accumulation curves among observers equates to higher rates of species accumulation, particularly for harder-to-identify species, and reveals increased species accumulation rates with continued participation. We suggest that these properties of our analysis provide a measure of observer skill, and that the potential to derive post-hoc data-derived measurements of participant ability should be more widely explored by analysts of data from citizen science projects. We see the potential for inferential results from analyses of citizen science data to be improved by accounting for observer skill
Urban biodiversity : State of the science and future directions
Since the 1990s, recognition of urban biodiversity research has increased steadily. Knowledge of how ecological communities respond to urban pressures can assist in addressing global questions related to biodiversity. To assess the state of this research field in meeting this aim, we conducted a systematic review of the urban biodiversity literature published since 1990. We obtained data from 1209 studies that sampled ecological communities representing 12 taxonomic groups. While advances have been made in the field over the last 30 years, we found that urban biodiversity research has primarily been conducted in single cities within the Palearctic and Nearctic realms, within forest remnants and residential locations, and predominantly surveys plants and birds, with significant gaps in research within the Global South and little integration of multi-species and multi-trophic interactions. Sample sizes remain limited in spatial and temporal scope, but citizen science and remote sensing resources have broadened these efforts. Analytical approaches still rely on taxonomic diversity to describe urban plant and animal communities, with increasing numbers of integrated phylogenetic and trait-based analyses. Despite the implementation of nature-based solutions across the world's cities, only 5% of studies link biodiversity to ecosystem function and services, pointing to substantial gaps in our understanding of such solutions. We advocate for future research that encompasses a greater diversity of taxonomic groups and urban systems, focusing on biodiversity hotspots. Implementing such research would enable researchers to move forward in an equitable and multidisciplinary way to tackle the complex issues facing global urban biodiversity.Peer reviewe
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