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

Diurnal timing of nonmigratory movement by birds: the importance of foraging spatial scales

Timing of activity can reveal an organism's efforts to optimize foraging either by minimizing energy loss through passive movement or by maximizing energetic gain through foraging. Here, we assess whether signals of either of these strategies are detectable in the timing of activity of daily, local movements by birds. We compare the similarities of timing of movement activity among species using six temporal variables: start of activity relative to sunrise, end of activity relative to sunset, relative speed at midday, number of movement bouts, bout duration and proportion of active daytime hours. We test for the influence of flight mode and foraging habitat on the timing of movement activity across avian guilds. We used 64 570 days of GPS movement data collected between 2002 and 2019 for local (non‐migratory) movements of 991 birds from 49 species, representing 14 orders. Dissimilarity among daily activity patterns was best explained by flight mode. Terrestrial soaring birds began activity later and stopped activity earlier than pelagic soaring or flapping birds. Broad‐scale foraging habitat explained less of the clustering patterns because of divergent timing of active periods of pelagic surface and diving foragers. Among pelagic birds, surface foragers were active throughout all 24 hrs of the day while diving foragers matched their active hours more closely to daylight hours. Pelagic surface foragers also had the greatest daily foraging distances, which was consistent with their daytime activity patterns. This study demonstrates that flight mode and foraging habitat influence temporal patterns of daily movement activity of birds.We thank the Nature Conservancy, the Bailey Wildlife Foundation, the Bluestone Foundation, the Ocean View Foundation, Biodiversity Research Institute, the Maine Outdoor Heritage Fund, the Davis Conservation Foundation and The U.S. Department of Energy (DE‐EE0005362), and the Darwin Initiative (19-026), EDP S.A. ‘Fundação para a Biodiversidade’ and the Portuguese Foundation for Science and Technology (FCT) (DL57/2019/CP 1440/CT 0021), Enterprise St Helena (ESH), Friends of National Zoo Conservation Research Grant Program and Conservation Nation, ConocoPhillips Global Signature Program, Maryland Department of Natural Resources, Cellular Tracking Technologies and Hawk Mountain Sanctuary for providing funding and in-kind support for the GPS data used in our analyses

Diurnal timing of nonmigratory movement by birds: the importance of foraging spatial scales

This is the author accepted manuscript. The final version is available from Wiley via the DOI in this recordData Availability statement: R code used in analyses can be accessed at datadryad.com. Most of the data used are publicly available at www.movebank.orgTiming of activity can reveal an organism's efforts to optimize foraging either by minimizing energy loss through passive movement or by maximizing energetic gain through foraging. Here, we assess whether signals of either of these strategies are detectable in the timing of activity of daily, local movements by birds. We compare the similarities of timing of movement activity among species using six temporal variables: start of activity relative to sunrise, end of activity relative to sunset, relative speed at midday, number of movement bouts, bout duration, and proportion of active daytime hours. We test for the influence of flight mode and foraging habitat on the timing of movement activity across avian guilds. We used 64570 days of GPS movement data collected between 2002 and 2019 for local (non‐migratory) movements of 991 birds from 49 species, representing 14 orders. Dissimilarity among daily activity patterns was best explained by flight mode. Terrestrial soaring birds began activity later and stopped activity earlier than pelagic soaring or flapping birds. Broad‐scale foraging habitat explained less of the clustering patterns because of divergent timing of active periods of pelagic surface and diving foragers. Among pelagic birds, surface foragers were active throughout the day while diving foragers matched their active hours more closely to daylight hours. Pelagic surface foragers also had the greatest daily foraging distances, which was consistent with their daytime activity patterns. This study demonstrates that flight mode and foraging habitat influence temporal patterns of daily movement activity of birds.Nature ConservancyBailey Wildlife FoundationBluestone FoundationOcean View FoundationBiodiversity Research InstituteMaine Outdoor Heritage FundDavis Conservation FoundationUS Department of EnergyDarwin InitiativePortuguese Foundation for Science and Technology (FCT)Enterprise St Helena (ESH)Hawk Mountain Sanctuar

Patterns of Spatial Distribution of Golden Eagles Across North America: How Do They Fit into Existing Landscape-Scale Mapping Systems?

Conserving wide-ranging animals requires knowledge about their year-round movements and resource use. Golden Eagles (Aquila chrysaetos) exhibit a wide range of movement patterns across North America. We combined tracking data from 571 Golden Eagles from multiple independent satellite-telemetry projects from North America to provide a comprehensive look at the magnitude and extent of these movements on a continental scale. We compared patterns of use relative to four alternative administrative and ecological mapping systems, namely Bird Conservation Regions (BCRs), U.S. administrative migratory bird flyways, Migratory Bird Joint Ventures, and Landscape Conservation Cooperatives. Our analyses suggested that eagles initially captured in eastern North America used space differently than those captured in western North America. Other groups of eagles that exhibited distinct patterns in space use included long-distance migrants from northern latitudes, and southwestern and Californian desert residents. There were also several groupings of eagles in the Intermountain West. Using this collaborative approach, we have identified large-scale movement patterns that may not have been possible with individual studies. These results will support landscape-scale conservation measures for Golden Eagles across North America

Large birds travel farther in homogeneous environments

Aim: Animal movement is an important determinant of individual survival, population dynamics and ecosystem structure and function. Nonetheless, it is still unclear how local movements are related to resource availability and the spatial arrangement of resources. Using resident bird species and migratory bird species outside the migratory period, we examined how the distribution of resources affects the movement patterns of both large terrestrial birds (e.g., raptors, bustards and hornbills) and waterbirds (e.g., cranes, storks, ducks, geese and flamingos). Location: Global. Time period: 2003–2015. Major taxa studied: Birds. Methods: We compiled GPS tracking data for 386 individuals across 36 bird species. We calculated the straight‐line distance between GPS locations of each individual at the 1‐hr and 10‐day time‐scales. For each individual and time‐scale, we calculated the median and 0.95 quantile of displacement. We used linear mixed‐effects models to examine the effect of the spatial arrangement of resources, measured as enhanced vegetation index homogeneity, on avian movements, while accounting for mean resource availability, body mass, diet, flight type, migratory status and taxonomy and spatial autocorrelation. Results: We found a significant effect of resource spatial arrangement at the 1‐hr and 10‐day time‐scales. On average, individual movements were seven times longer in environments with homogeneously distributed resources compared with areas of low resource homogeneity. Contrary to previous work, we found no significant effect of resource availability, diet, flight type, migratory status or body mass on the non‐migratory movements of birds. Main conclusions: We suggest that longer movements in homogeneous environments might reflect the need for different habitat types associated with foraging and reproduction. This highlights the importance of landscape complementarity, where habitat patches within a landscape include a range of different, yet complementary resources. As habitat homogenization increases, it might force birds to travel increasingly longer distances to meet their diverse needs.National Trust for Scotland; Penguin Foundation; The U.S. Department of Energy, Grant/Award Number: DE-EE0005362; Australian Research Council; NASA's Arctic Boreal Vulnerability Experiment (ABoVE), Grant/Award Number: NNX15AV92A; Netherlands Organization for Scientific Research, Grant/Award Number: VIDI 864.10.006; BCC; NSF Award, Grant/Award Number: ABI-1458748; U.K. Department for Energy and Climate Change; ‘Juan de la Cierva ‐ Incorporación’ postdoctoral grant; Irish Research Council, Grant/Award Number: GOIPD/2015/81 ; DECC; Goethe International Postdoctoral Programme, People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme FP7/2007‐2013/ under REA grant agreement no [291776]; German Aerospace Center Award, Grant/Award Number: 50JR1601; Scottish Natural Heritage; Solway Coast AONB Sustainable Development Fund; COWRIE Ltd.; Heritage Lottery Fund; Robert Bosch Stiftung; NSF Division of Biological Infrastructure Award, Grant/Award Number: 1564380; Spanish Ministry of Economy and Competitiveness, Grant/Award Number: IJCI-2014-19190; Energinet.dk; NASA Award, Grant/Award Number: NNX15AV92A; MAVA Foundation; Fundação para a Ciência e Tecnologia, Grant/Award Number: SFRH/BPD/118635/2016; National Key R&D Program of China, Grant/Award Number: 2016YFC0500406; Green Fund of the Greek Ministry of Environmen

Diurnal timing of nonmigratory movement by birds: the importance of foraging spatial scales

Timing of activity can reveal an organism’s efforts to optimize foraging either by minimizing energy loss through passive movement or by maximizing energetic gain through foraging. Here, we assess whether signals of either of these strategies are detectable in the timing of activity of daily, local movements by birds. We compare the similarities of timing of movement activity among species using six temporal variables: start of activity relative to sunrise, end of activity relative to sunset, relative speed at midday, number of movement bouts, bout duration, and proportion of active daytime hours. We test for the influence of flight mode and foraging habitat on the timing of movement activity across avian guilds. We used 64570 days of GPS movement data collected between 2002 and 2019 for local (non-migratory) movements of 991 birds from 49 species, representing 14 orders. Dissimilarity among daily activity patterns was best explained by flight mode. Terrestrial soaring birds began activity later and stopped activity earlier than pelagic soaring or flapping birds. Broad-scale foraging habitat explained less of the clustering patterns because of divergent timing of active periods of pelagic surface and diving foragers. Among pelagic birds, surface foragers were active throughout the day while diving foragers matched their active hours more closely to daylight hours. Pelagic surface foragers also had the greatest daily foraging distances, which was consistent with their daytime activity patterns. This study demonstrates that flight mode and foraging habitat influence temporal patterns of daily movement activity of birds. Methods Data were compiled from previously collected GPS movement datasets. We include days with 8+ h of data, and exclude migrations > 500 km long. For colonial nesting pelagic birds, we compare only days with known foraging trips. Dataset here includes the six temporal variables used in our study, measured at the hourly and daily scale. Usage Notes Mallon et al. 2020. Diurnal timing of nonmigratory movement by birds: the importance of foraging spatial scales. Journal of Avian Biology The dryad repository contents include the following data: 1. Final dataset used in analysis: mallon2020_trait_data.csv 2. Original hourly data measures of several temporal variables: mallon2020_hr_data.csv 3. Original daily data measures of several temporal variables: mallon2020_day_data.csv 4. Final morphological data used in analysis: mallon2020_morpho_data.csv Data columns of note: active.hr = if individual is active or inactive, based on threshold defined in Mallon et al. 2020 mspeed = mean speed during active hours n.hrs = number of location hours per day dsunrise.min = first activity, relative to sunrise dsunset.max = last activity, relative to sunset midday.speed = hourly speed nearest to solar noon prop.diel = proportion of active hours between sunrise and sunset n.periods.activity = number of movement bouts activity.dur = mean duration of movement bouts r2n = maximum net squared displacement from the beginning of the day (m) mean.r2n = mean net squared displacement from the beginning of the day (m) median.r2n = median net squared displacement from the beginning of the day (m