Comparison of WAIC and posterior predictive approaches 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.

Feeding en route: Prey availability and traits influence prey selection by an avian predator on migration.

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.

Durante la migración animal, las comunidades efímeras de taxones de todos los niveles tróficos coexisten en el espacio y el tiempo. Las interacciones entre depredadores y presas a lo largo de los corredores migratorios son significativas desde el punto de vista ecológica y evolutivo. Sin embargo, estas interacciones siguen siendo poco estudiadas en los sistemas terrestres y justifican más investigaciones utilizando enfoques novedosos. Investigamos las interacciones depredador­presa entre un depredador avívoro migratorio y una comunidad de presas aviares efímeras en la temporada migratoria otoñal. Probamos las asociaciones entre los rasgos de las aves y la selección de presas y planteamos la hipótesis de que los rasgos de las presas (tamaño relativo, comportamiento de bandada, hábitat, tendencia migratoria y disponibilidad) influirían en la selección de presas por parte de una rapaz sexualmente dimórfica durante la migración. Para documentar el consumo de presas, recogimos rastros de ADN de presas de picos y garras de Gavilán Americano Accipiter striatus (n = 588) migratorios. Determinamos la disponibilidad de presas en la comunidad de aves efímeras extrayendo índices de abundancia semanales de los datos de eBird Estado y Tendencias. Utilizamos modelos de elección discreta para evaluar la selección de presas y visualizamos la frecuencia de las presas en la dieta y la disponibilidad en el paisaje durante la temporada migratoria otoñal. Utilizando el metacódigo de barras del ADN ambiental, detectamos especies de presas en el 94,1% de los halcones muestreados (n = 525/588), comprendiendo 1396 detecciones de 65 especies de presas. La frecuencia de presas en la dieta y la abundancia relativa de especies de presas en eBird se correlacionaron a lo largo de la temporada de migración para las principales especies de presas seleccionadas, lo que sugiere que la disponibilidad de presas es un componente importante de las interacciones entre aves rapaces y aves canoras durante el otoño. El tamaño de las presas, el comportamiento de las bandadas y la asociación con el hábitat no reproductivo fueron rasgos de presa que influyeron significativamente en la elección de los depredadores. Encontramos diferencias entre la selección de presas de gavilán hembra y macho, lo que sugiere que el dimorfismo sexual de tamaño ha conducido a distintas estrategias de alimentación durante la migración. Esta investigación integró datos de campo recopilados por una estación de monitoreo de migración de rapaces impulsada por voluntarios y datos generados públicamente por eBird para revelar la esquiva dinámica depredador­presa que ocurre en una comunidad efímera de rapaces y aves canoras durante la migración otoñal. Comprender las interacciones dinámicas entre rapaces y aves canoras a lo largo de las rutas migratorias sigue siendo una frontera relativamente inexplorada en la ecología animal y es necesaria para los esfuerzos de conservación y gestión de las comunidades migratorias y residentes.

Climate and biodiversity change constrain the flow of cultural ecosystem services to people: A case study modeling birding across Africa under future climate scenarios.

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.

Assessing adequacy of citizen science datasets for biodiversity monitoring.

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.

Spatial and seasonal variation in thermal sensitivity within North American bird species.

Responses of wildlife to climate change are typically quantified at the species level, but physiological evidence suggests significant intraspecific variation in thermal sensitivity given adaptation to local environments and plasticity required to adjust to seasonal environments. Spatial and temporal variation in thermal responses may carry important implications for climate change vulnerability; for instance, sensitivity to extreme weather may increase in specific regions or seasons. Here, we leverage high-resolution observational data from eBird to understand regional and seasonal variation in thermal sensitivity for 21 bird species. Across their ranges, most birds demonstrated regional and seasonal variation in both thermal peak and range, or the temperature and range of temperatures when observations peaked. Some birds demonstrated constant thermal peaks or ranges across their geographical distributions, while others varied according to local and current environmental conditions. Across species, birds typically demonstrated either geographical or seasonal adaptation to climate. Local adaptation and phenotypic plasticity are likely important but neglected aspects of organismal responses to climate change.

Deep learning with citizen science data enables estimation of species diversity and composition at continental extents.

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.

Region-wide retreats from lower elevations of range-restricted birds across the Northern Andes.

Local studies show upslope shifts in the distribution of tropical birds in response to warming temperatures. Unanswered is whether these upward shifts occur regionally across many species. We considered a nearly 2000-km length of the Northern Andes, where deforestation, temperature, and extreme weather events have increased during the past decades. Range-restricted bird species are particularly vulnerable to such events and occur in exceptionally high numbers in this region. Using abundant crowd-sourced data from the Cornell Lab of Ornithology database, eBird, and the Global Biodiversity Information Facility, we documented distributions of nearly 200 such species. We examined whether species shifted their elevational ranges over time by comparing observed versus expected occurrences below a low elevational threshold and above a high elevational threshold for 2 periods: before and after 2005. We predicted fewer observations at lower elevations (those below the threshold) and more at upper elevations (those above the threshold) after 2005. We also tested for deforestation effects at lower elevations within each species' distribution ranges. We compared relative forest loss with the differences between observed and expected occurrences across the elevational range. Species' retreats from lower elevations were ubiquitous and involved a 23-40% decline in prevalence at the lowest elevations. Increases at higher elevations were not consistent. The retreats occurred across a broad spectrum of species, from predominantly lowland to predominantly highland. Because deforestation showed no relationship with species retreats, we contend that a warming climate is the most parsimonious explanation for such shifts.

Repliegues regionales desde elevaciones más bajas de aves de distribución restringida en los Andes septentrionales Resumen Los estudios locales muestran cambios en la distribución altitudinal de las aves tropicales como respuesta al aumento de la temperatura. No sabemos si estos cambios suceden en muchas especies a nivel regional. Consideramos casi 2000 km de los Andes septentrionales, en donde la deforestación y los eventos climáticos extremos han incrementado en las últimas décadas. Las aves con distribución restringida son particularmente vulnerables a dichos eventos y su presencia es numerosa en esta región. Usamos datos abundantes de origen colectivo tomados de la base de datos del Laboratorio de Ornitología de Cornell, eBird y el Sistema Global de Información sobre Biodiversidad para documentar la distribución de aproximadamente 200 de estas especies. Analizamos si las especies cambiaron su distribución altitudinal con el tiempo al comparar entre la presencia observada y la esperada bajo un umbral de elevación reducida y por encima de un umbral de elevación alta durante dos periodos: antes y después de 2005. Pronosticamos una cantidad menor de observaciones por debajo del umbral y una mayor cantidad por encima del umbral para después de 2005. También analizamos los efectos de la deforestación en elevaciones más bajas dentro de los rangos de distribución de las especies y comparamos la pérdida relativa del bosque con las diferencias entre la presencia observada y la esperada en todo el rango altitudinal. El repliegue de las especies a partir de las elevaciones más bajas fue ubicuo e involucró una declinación del 23-40% de la prevalencia en las elevaciones más bajas. Los incrementos en las elevaciones más altas no fueron uniformes. Los repliegues ocurrieron a lo largo de un espectro amplio de especies, desde las que predominan en las tierras bajas hasta las que predominan en las tierras altas. Ya que la deforestación no se relacionó con el repliegue, sostenemos que un clima más cálido es la explicación más parsimoniosa para estos cambios.

Avian diversity and function across the world's most populous cities.

Understanding the composition of urban wildlife communities is crucial to promote biodiversity, ecosystem function and links between nature and people. Using crowdsourced data from over five million eBird checklists, we examined the influence of urban characteristics on avian richness and function at 8443 sites within and across 137 global cities. Under half of the species from regional pools were recorded in cities, and we found a significant phylogenetic signal for urban tolerance. Site-level avian richness was positively influenced by the extent of open forest, cultivation and wetlands and avian functional diversity by wetlands. Functional diversity co-declined with richness, but groups including granivores and aquatic birds occurred even at species-poor sites. Cities in arid areas held a higher percentage of regional species richness. Our results indicate commonalities in the influence of habitat on richness and function, as well as lower niche availability, and phylogenetic diversity across the world's cities.

Species traits and observer behaviors that bias data assimilation and how to accommodate them.

Datasets that monitor biodiversity capture information differently depending on their design, which influences observer behavior and can lead to biases across observations and species. Combining different datasets can improve our ability to identify and understand threats to biodiversity, but this requires an understanding of the observation bias in each. Two datasets widely used to monitor bird populations exemplify these general concerns: eBird is a citizen science project with high spatiotemporal resolution but variation in distribution, effort, and observers, whereas the Breeding Bird Survey (BBS) is a structured survey of specific locations over time. Analyses using these two datasets can identify contradictory population trends. To understand these discrepancies and facilitate data fusion, we quantify species-level reporting differences across eBird and the BBS in three regions across the United States by jointly modeling bird abundances using data from both datasets. First, we fit a joint Species Distribution Model that accounts for environmental conditions and effort to identify reporting differences across the datasets. We then examine how these differences in reporting are related to species traits. Finally, we analyze species reported to one dataset but not the other and determine whether traits differ between reported and unreported species. We find that most species are reported more in the BBS than eBird. Specifically, we find that compared to eBird, BBS observers tend to report higher counts of common species and species that are usually detected by sound. We also find that species associated with water are reported less in the BBS. Species typically identified by sound are reported more at sunrise than later in the morning. Our results quantify reporting differences in eBird and the BBS to enhance our understanding of how each captures information and how they should be used. The reporting rates we identify can also be incorporated into observation models through detectability or effort to improve analyses across species and datasets. The method demonstrated here can be used to compare reporting rates across any two or more datasets to examine biases.

Bicolored Hawk, Accipiter bicolor in Guayaquil city (Western Ecuador): new preys-species records and citizen science urban records

Accipiter bicolor is a widely distributed Neotropical raptor but knowledge about its ecology is poor, particularly in urban areas. In this work, we document the presence of A. bicolor in the city of Guayaquil and in nearby forested areas, in addition, we provide new records on its diet and discuss possible foraging strategies in synanthropic environments. Also, reports of this species are considered on citizen science platforms. Accipiter bicolor was observed consuming an individual of Columbina bluckeyi and another of Artibeus fraterculus; near a colony of this species of bat. Finally, we found 59 records of A. bicolor between 2007 and 2022 for Guayaquil and its surrounding areas, 14 records were in urban habitats. Observations in different urban and peri-urban habitats are discussed, as well as their feeding habits.

Accipiter bicolor es una rapaz Neotropical ampliamente distribuida pero el conocimiento sobre su ecología es escaso en particular en zonas urbanas. En este trabajo, documentamos la presencia de A. bicolor en la ciudad de Guayaquil y en áreas boscosas cercanas, además, proveemos nuevos registros sobre su dieta y discutimos posibles estrategias de forrajeo en ambientes sinantrópicas. También, se consideran reportes de esta especie en plataformas de ciencia ciudadana. Accipiter bicolor fue observada consumiendo un individuo de Columbina bluckeyi y otro de Artibeus fraterculus; cerca de una colonia de esta especie de murciélago. Finalmente, se encontraron 59 registros de A. bicolor entre el 2007 y 2022 para Guayaquil y sus áreas circundantes, 14 registros fueron en hábitat urbanos. Se discute las observaciones en diferentes hábitats urbanos y periurbanos, así como sus hábitos de alimenticios.

Opportunities for the conservation of migratory birds to benefit threatened resident vertebrates in the Neotropics.

Neotropical countries receive financing and effort from temperate nations to aid the conservation of migratory species that move between temperate and tropical regions. If allocated strategically, these resources could simultaneously contribute to other conservation initiatives. In this study, we use novel distribution maps to show how those resources could aid planning for the recovery of threatened resident vertebrates.Using eBird-based relative abundance estimates, we first identified areas with high richness of Neotropical migrant landbirds of conservation concern (23 species) during the stationary non-breeding period. Within these areas, we then identified threatened species richness, projected forest loss and conducted a prioritization for 1,261 red-listed vertebrates using Terrestrial Area-of-Habitat maps.Richness for migrants was greatest along a corridor from the Yucatan peninsula south to the northern Andes but also included south-west Mexico and Hispaniola. Protected areas account for 22% of this region while 21% is at risk of forest loss. Within this focal region for migrants, all four vertebrate groups showed hotspots of threatened species richness along the west and east Andean slopes. Taxa-specific hotspots included montane areas of southern Mexico and central Guatemala (amphibians/reptiles) and the entire east slope of the Colombian East Andes (mammals).Our prioritization highlighted several areas of importance for conservation due to high threatened species richness and projected forest loss including (a) the Pacific dry forests of south-west Mexico, (b) montane regions of northern Central America and (c) the west Andean slope of Colombia and Ecuador. At a landscape scale in southern Colombia, we show how conservation efforts for six Neotropical migrants could benefit 56 threatened residents that share a similar elevational range. Synthesis and applications. Funding and effort for migratory bird conservation also has potential to benefit threatened resident vertebrates in the Neotropics. Our study highlights how novel, high-resolution information on species distributions and risk of forest loss can be integrated to identify priority areas for the two groups at regional and landscape scales. The approach and data can be further modified for more specific goals, such as within-country initiatives.

Los países neotropicales reciben financiamiento y recursos esfuerzos de países templados para ayudar a la conservación de las aves migratorias que se mueven entre estas dos regiones. Si se asignan estratégicamente, estos recursos podrían beneficiar simultáneamente a otras iniciativas de conservación. En esta investigación, usamos novedosos mapas de distribución para mostrar cómo esos recursos podrían ayudar a planificar la conservación de especies residentes amenazadas.Utilizando estimaciones de abundancia de eBird, delineamos la Región Focal con la mayor riqueza de aves migratorias neotropicales de interés para la conservación durante el periodo invernal (23 especies). Dentro de esta región, determinamos la riqueza de especies residentes amenazadas, la proyección de pérdida de bosque, y realizamos una priorización para 1261 especies de vertebrados incluidos en la lista roja de la IUCN utilizando mapas del área de hábitat terrestre.En la Región Focal, la riqueza de aves migratorias fue mayor a lo largo de un corredor desde el sur de la península de Yucatán hasta el norte de los Andes, y en el suroeste de México y la isla La Española. Las áreas protegidas representan 22% de esta región mientras que el 21% está en riesgo de pérdida de bosque. Dentro de la Región Focal para las aves migratorias, todos los vertebrados residentes mostraron puntos de mayor riqueza de especies amenazadas en los Andes occidentales y orientales. Las regiones con mayor riqueza para taxones específicos incluyeron las montañas del sur de México y del centro de Guatemala (anfibios y reptiles) y la vertiente oriental de la cordillera oriental de Colombia (mamíferos).La priorización destacó varias áreas de importancia para la conservación debido a la alta riqueza de especies amenazadas y a la pérdida de bosque proyectada incluyendo 1) los bosques secos del Pacífico del suroeste de México, 2) las regiones montañosas del norte de Centroamérica y 3) la vertiente occidental de los Andes Occidental de Colombia y Ecuador. A escala del paisaje en el sur de Colombia, mostramos cómo los esfuerzos para la conservación de 6 aves migratorias podrían beneficiar a 56 especies residentes amenazadas que comparten un rango altitudinal similar. Síntesis y aplicaciones. La financiación y esfuerzos para la conservación de las aves migratorias tienen el potencial a beneficiar a los vertebrados residentes amenazados en el Neotrópico. Nuestro estudio resalta como se puede integrar información novedosa y de alta resolución acerca de la distribución de especies y el riesgo de pérdida de bosques para identificar áreas prioritarias para los dos grupos a escala regional y paisajística. El enfoque y los datos se pueden modificar para objetivos más específicos, como por ejemplo iniciativas dentro de cada país.

Estimates of species-level tolerance of urban habitat in North American birds.

Species vary in their responses to urban habitat; most species avoid these environments, whereas others tolerate or even thrive in them. To better characterize the extent to which species vary in their responses to urban habitat (from this point forwards "urban tolerance"), we used several methods to quantify these responses at a continental scale across all birds. Using open access community science-derived data from the eBird Status and Trends Products and two different types of high-resolution geospatial data that quantify urbanization of landscapes, we calculated urban tolerance for 432 species with breeding ranges that overlap large cities in Canada or the USA. We developed six different calculations to characterize species-level urban tolerance, allowing us to assess how each species' relative abundance across their breeding range varied with estimates of urban habitat use and intensity. We assessed correlations among these six indices, then compressed the two best-performing indices into a single principal component (multivariate urban tolerance index) that captured variation in urban tolerance among species. We assessed the accuracy of our single and multivariate urban tolerance indices using 24 test species that have been well characterized for their tolerance or avoidance of the urban habitat, as well as with previously published, independent urban tolerance estimates. Here, we provide this new dataset of species-level urban tolerance estimates that improves upon previous metrics by incorporating continental-scale, continuous estimates that better differentiate species' tolerance of urban habitat compared with existing, categorical methods. These refined metrics can be used to test hypotheses that link ecological, life history, and behavioral traits to avian urban tolerance. The dataset is licensed as CC-By Attribution 4.0 International. Users must appropriately cite the data paper and dataset if used in publications and scientific presentations.

Citizen science reveals waterfowl responses to extreme winter weather.

Global climate change is increasing the frequency and severity of extreme climatic events (ECEs) which may be especially detrimental during late-winter when many species are surviving on scarce resources. However, monitoring animal populations relative to ECEs is logistically challenging. Crowd-sourced datasets may provide opportunity to monitor species' responses to short-term chance phenomena such as ECEs. We used 14 years of eBird-a global citizen science initiative-to examine distribution changes for seven wintering waterfowl species across North America in response to recent extreme winter polar vortex disruptions. To validate inferences from eBird, we compared eBird distribution changes against locational data from 362 GPS-tagged Mallards (Anas platyrhynchos) in the Mississippi Flyway. Distributional shifts between eBird and GPS-tagged Mallards were similar following an ECE in February 2021. In general, the ECE affected continental waterfowl population distributions; however, responses were variable across species and flyways. Waterfowl distributions tended to stay near wintering latitudes or moved north at lesser distances compared with non-ECE years, suggesting preparedness for spring migration was a stronger "pull" than extreme weather was a "push" pressure. Surprisingly, larger-bodied waterfowl with grubbing foraging strategies (i.e., geese) delayed their northward range shift during ECE years, whereas smaller-bodied ducks were less affected. Lastly, wetland obligate species shifted southward during ECE years. Collectively, these results suggest specialized foraging strategies likely related to resource limitations, but not body size, necessitate movement from extreme late-winter weather in waterfowl. Our results demonstrate eBird's potential to monitor population-level effects of weather events, especially severe ECEs. eBird and other crowd-sourced datasets can be valuable to identify species which are adaptable or vulnerable to ECEs and thus, begin to inform conservation policy and management to combat negative effects of global climate change.

Integrating data types to estimate spatial patterns of avian migration across the Western Hemisphere.

For many avian species, spatial migration patterns remain largely undescribed, especially across hemispheric extents. Recent advancements in tracking technologies and high-resolution species distribution models (i.e., eBird Status and Trends products) provide new insights into migratory bird movements and offer a promising opportunity for integrating independent data sources to describe avian migration. Here, we present a three-stage modeling framework for estimating spatial patterns of avian migration. First, we integrate tracking and band re-encounter data to quantify migratory connectivity, defined as the relative proportions of individuals migrating between breeding and nonbreeding regions. Next, we use estimated connectivity proportions along with eBird occurrence probabilities to produce probabilistic least-cost path (LCP) indices. In a final step, we use generalized additive mixed models (GAMMs) both to evaluate the ability of LCP indices to accurately predict (i.e., as a covariate) observed locations derived from tracking and band re-encounter data sets versus pseudo-absence locations during migratory periods and to create a fully integrated (i.e., eBird occurrence, LCP, and tracking/band re-encounter data) spatial prediction index for mapping species-specific seasonal migrations. To illustrate this approach, we apply this framework to describe seasonal migrations of 12 bird species across the Western Hemisphere during pre- and postbreeding migratory periods (i.e., spring and fall, respectively). We found that including LCP indices with eBird occurrence in GAMMs generally improved the ability to accurately predict observed migratory locations compared to models with eBird occurrence alone. Using three performance metrics, the eBird + LCP model demonstrated equivalent or superior fit relative to the eBird-only model for 22 of 24 species-season GAMMs. In particular, the integrated index filled in spatial gaps for species with over-water movements and those that migrated over land where there were few eBird sightings and, thus, low predictive ability of eBird occurrence probabilities (e.g., Amazonian rainforest in South America). This methodology of combining individual-based seasonal movement data with temporally dynamic species distribution models provides a comprehensive approach to integrating multiple data types to describe broad-scale spatial patterns of animal movement. Further development and customization of this approach will continue to advance knowledge about the full annual cycle and conservation of migratory birds.

Identifying engaging bird species and traits with community science observations.

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.

Leveraging community science data for population assessments during a pandemic.

The COVID-19 pandemic has disrupted field research programs, making conservation and management decision-making more challenging. However, it may be possible to conduct population assessments using integrated models that combine community science data with existing data from structured surveys. We developed a space-time integrated model to characterize spatial and temporal variability in population distribution. We fit our integrated model to 10 years of eBird (2010-2020) and 9 years of aerial survey (2010-2019) Mottled Duck count data to forecast 2020 population size along the western Gulf Coast of Texas and Louisiana. Estimates of Mottled Duck abundance were similar in magnitude to estimates calculated using previous methods but were more precise and showed evidence of a declining population. The spatial distribution for Mottled Ducks each year was characterized by several concentrations of relatively high abundance, although the location of these abundance "hotspots" varied over time. Expected abundance was higher for areas with a higher proportion of area covered by marsh habitat. By leveraging large-scale community science data, we were able to conduct a population assessment despite the disruption in structured surveys caused by the pandemic. As participation in community science platforms continues to increase, we anticipate modeling frameworks, like the integrated model we developed here, will become increasingly useful for informing conservation and management decision-making.

A response to estimating hybridization in the wild using community science data: A path forward.

When working with a citizen science database like eBird, there are many possible ways to filter or subsample observations. Here, we discuss the potential biases and assumptions that surround different subsampling approaches or filtering that can be done to the eBird database. Restricting observations to species that are known to frequently hybridize, a specific time of the year, or a specific location, has the potential to greatly inflate the calculated per-individual rate of hybridization. Such filtering also assumes that researchers know a birds' capacity to hybridize with all other species in its range, which we argue is an unfounded assumption. We ultimately conclude that a limited filtering approach is ideal when using a citizen science database to attempt to address a broad question such as: what is the per individual rate of hybridization across all of the bird species in the United States?

Estimating hybridization in the wild using citizen science data: A path forward.

Genomic evidence of introgression in natural populations has reinvigorated the study of hybridization in recent years. Still, it is largely unknown how frequently individual organisms mate across species lines. Recently, Justyn et al. suggested that eBird, one of the world's largest citizen science databases, may supply adequate data for estimating hybridization rates. Here, we compare Justyn et al.'s estimates-and their conclusions that hybridization is rare-with estimates from museum and molecular data. We also estimate hybridization using eBird observations from areas and times when hybridization is possible, namely, in contact zones during the breeding season. These estimates are all considerably higher than those reported in Justyn et al., emphasizing that inferences from multiple datasets can differ radically. Finally, we demonstrate an approach for predicting the location of hybrid zones using eBird data, which can be done with high confidence and with unprecedented resolution. We show that citizen science data, far from settling the question of how frequently bird species hybridize, instead offer a promising step toward more focused study of hybrid zones.

The correlation between eBird community science and weather surveillance radar-based estimates of migration phenology.

Aim: Measuring avian migration can prove challenging given the spatial scope and the diversity of species involved. No one monitoring technique provides all the pertinent measures needed to capture this macroscale phenomenon - emphasizing the need for data integration. Migration phenology is a key metric characterizing large-scale migration dynamics and has been successfully quantified using weather surveillance radar (WSR) data and community science observations. Separately, both platforms have their limitations and measure different aspects of bird migration. We sought to make a formal comparison of the migration phenology estimates derived from WSR and eBird data - of which we predict a positive correlation. Location: Contiguous United States. Time period: 2002-2018. Major taxa studied: Migratory birds. Methods: We estimated spring and autumn migration phenology at 143 WSR stations aggregated over a 17-year period (2002-2018), which we contrast with eBird-based estimates of spring and autumn migration phenology for 293 nocturnally migrating bird species at the 143 WSR stations. We compared phenology metrics derived from all species and WSR stations combined, for species in three taxonomic orders (Anseriformes, Charadriiformes and Passeriformes), and for WSR stations in three North American migration flyways (western, central and eastern). Results: We found positive correlations between WSR and eBird-based estimates of migration phenology and differences in the strength of correlations among taxonomic orders and migration flyways. The correlations were stronger during spring migration, for Passeriformes, and generally for WSR stations in the eastern flyway. Autumn migration showed weaker correlation, and in Anseriformes correlations were weakest overall. Lastly, eBird-based estimates slightly preceded those derived from WSR in the spring, but trailed WSR in the autumn, suggesting that the two data sources measure different components of migration phenology. Main conclusions: We highlight the complementarity of these two approaches, but also reveal strong taxonomic and geographic differences in the relationships between the platforms.

Estimating the movements of terrestrial animal populations using broad-scale occurrence data.

As human and automated sensor networks collect increasingly massive volumes of animal observations, new opportunities have arisen to use these data to infer or track species movements. Sources of broad scale occurrence datasets include crowdsourced databases, such as eBird and iNaturalist, weather surveillance radars, and passive automated sensors including acoustic monitoring units and camera trap networks. Such data resources represent static observations, typically at the species level, at a given location. Nonetheless, by combining multiple observations across many locations and times it is possible to infer spatially continuous population-level movements. Population-level movement characterizes the aggregated movement of individuals comprising a population, such as range contractions, expansions, climate tracking, or migration, that can result from physical, behavioral, or demographic processes. A desire to model population movements from such forms of occurrence data has led to an evolving field that has created new analytical and statistical approaches that can account for spatial and temporal sampling bias in the observations. The insights generated from the growth of population-level movement research can complement the insights from focal tracking studies, and elucidate mechanisms driving changes in population distributions at potentially larger spatial and temporal scales. This review will summarize current broad-scale occurrence datasets, discuss the latest approaches for utilizing them in population-level movement analyses, and highlight studies where such analyses have provided ecological insights. We outline the conceptual approaches and common methodological steps to infer movements from spatially distributed occurrence data that currently exist for terrestrial animals, though similar approaches may be applicable to plants, freshwater, or marine organisms.