Since 1980, 30 to 69% of species have shown reductions in mass, increases in wing length, and decreases in mass:wing ratio.

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.

Stable understory microclimates within undisturbed rainforests are often considered refugia against climate change. However, this assumption contrasts with emerging evidence of Neotropical bird population declines in intact rainforests. We assessed the vulnerability of resident rainforest birds to climatic variability, focusing on dry season severity characterized by hotter temperatures and reduced rainfall. Analyzing 4264 individual bird captures over 27 years, we found that harsher Amazonian dry seasons significantly reduced apparent survival for 24 of 29 species, with longer-lived species being more strongly affected. Our model predicted that a 1°C increase in average dry season temperature would reduce the mean apparent survival of the understory bird community by 63%. These findings directly link climate change to declining bird survival in the Amazon, challenging the notion that pristine rainforests can fully protect their biodiversity under increasingly severe climate conditions.

Recent long-term studies in protected areas have revealed the loss of biodiversity, yet the ramifications for ecosystem health and resilience remain unknown. Here, we investigate how the loss of understory birds, in the lowest stratum of the forest, affects avian biomass and functional diversity in the Amazon rainforest. Across approximately 30 years in the Biological Dynamics of Forest Fragments Project, we used a historical baseline of avian communities to contrast the avian communities in today's primary forest with those in modern disturbed habitat. We found that in primary rainforest, the reduced abundance of insectivorous species led to reduced functional diversity, but no reduction of biomass, indicating that species with similar functional traits are less likely to coexist in modern primary forests. Because today's forests contain fewer functionally redundant species—those with similar traits—we argue that avian communities in modern primary Amazonian rainforests are less resilient, which may ultimately disrupt the ecosystem in dynamic and unforeseen ways.

Species accounts for all the birds of the world.