Integrating animal tracking and trait data to facilitate global ecological discoveries
Jazyk angličtina Země Anglie, Velká Británie Médium print-electronic
Typ dokumentu časopisecké články, Research Support, U.S. Gov't, Non-P.H.S., práce podpořená grantem
Grantová podpora
IOS 2052497
National Science Foundation
Office of Naval Research
David and Lucile Packard Foundation
Arnold and Mabel Beckman Foundation
Elysea Fund
NE/X013766/1
Natural Environment Research Council
101044740
European Union
University of California
80NSSC21K1182
NASA - United States
PubMed
39973193
PubMed Central
PMC11883293
DOI
10.1242/jeb.247981
PII: 365554
Knihovny.cz E-zdroje
- Klíčová slova
- Biologging, Integration, Macroecology, Repository, Tracking data, Trait data,
- MeSH
- ekologie * metody MeSH
- faktografické databáze MeSH
- lokomoce MeSH
- migrace zvířat * MeSH
- zvířata MeSH
- Check Tag
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Research Support, U.S. Gov't, Non-P.H.S. MeSH
Understanding animal movement is at the core of ecology, evolution and conservation science. Big data approaches for animal tracking have facilitated impactful synthesis research on spatial biology and behavior in ecologically important and human-impacted regions. Similarly, databases of animal traits (e.g. body size, limb length, locomotion method, lifespan) have been used for a wide range of comparative questions, with emerging data being shared at the level of individuals and populations. Here, we argue that the proliferation of both types of publicly available data creates exciting opportunities to unlock new avenues of research, such as spatial planning and ecological forecasting. We assessed the feasibility of combining animal tracking and trait databases to develop and test hypotheses across geographic, temporal and biological allometric scales. We identified multiple research questions addressing performance and distribution constraints that could be answered by integrating trait and tracking data. For example, how do physiological (e.g. metabolic rates) and biomechanical traits (e.g. limb length, locomotion form) influence migration distances? We illustrate the potential of our framework with three case studies that effectively integrate trait and tracking data for comparative research. An important challenge ahead is the lack of taxonomic and spatial overlap in trait and tracking databases. We identify critical next steps for future integration of tracking and trait databases, with the most impactful being open and interlinked individual-level data. Coordinated efforts to combine trait and tracking databases will accelerate global ecological and evolutionary insights and inform conservation and management decisions in our changing world.
Department of Biological Sciences Goethe University 60323 Frankfurt am Main Germany
Department of Biology University of Konstanz 78464 Konstanz Germany
Department of Biology University of North Carolina at Greensboro Greensboro NC 27412 USA
Department of Biology University of Oxford Oxford OX1 3RB UK
Department of Migration Max Planck Institute of Animal Behavior 78315 Radolfzell Konstanz Germany
Institute of Marine Sciences University of California Santa Cruz Santa Cruz CA 95064 USA
School for Environment and Sustainability University of Michigan Ann Arbor MI 48109 USA
Senckenberg Biodiversity and Climate Research Centre 60325 Frankfurt am Main Germany
The University Centre in Svalbard Longyearbyen 9170 Svalbard Norway
Zobrazit více v PubMed
Abraham, J. O., Upham, N. S., Damian-Serrano, A. and Jesmer, B. R. (2022). Evolutionary causes and consequences of ungulate migration. PubMed DOI
Abrahms, B., Seidel, D. P., Dougherty, E., Hazen, E. L., Bograd, S. J., Wilson, A. M., Weldon McNutt, J., Costa, D. P., Blake, S., Brashares, J. S.et al. (2017). Suite of simple metrics reveals common movement syndromes across vertebrate taxa. PubMed DOI PMC
Abrahms, B., Aikens, E. O., Armstrong, J. B., Deacy, W. W., Kauffman, M. J. and Merkle, J. A. (2021). Emerging perspectives on resource tracking and animal movement ecology. PubMed DOI
Arnold, P. A., Delean, S., Cassey, P. and White, C. R. (2021). Meta-analysis reveals that resting metabolic rate is not consistently related to fitness and performance in animals. PubMed DOI
Balk, M. A., Deck, J., Emery, K. F., Walls, R. L., Reuter, D., LaFrance, R., Arroyo-Cabrales, J., Barrett, P., Blois, J., Boileau, A.et al. (2022). A solution to the challenges of interdisciplinary aggregation and use of specimen-level trait data. PubMed DOI PMC
Beltran, R., Kilpatrick, A. M., Picardi, S., Abrahms, B., Barrile, G., Oestreich, W., Smith, J., Czapanskiy, M., Favilla, A., Reisinger, R.et al. (2024). Biologging for the future: how biologgers can help solve fundamental questions, from individuals to ecosystems.
Bernard, C., Santos, G. S., Deere, J. A., Rodriguez-Caro, R., Capdevila, P., Kusch, E., Gascoigne, S. J. L., Jackson, J. and Salguero-Gómez, R. (2023). MOSAIC - a unified trait database to complement structured population models. PubMed DOI PMC
Bonin, F., Devaux, B. and Dupré, A. (2006).
Breed, G. A., Bowen, W., McMillan, J. and Leonard, M. L. (2006). Sexual segregation of seasonal foraging habitats in a non-migratory marine mammal. PubMed DOI PMC
Brown, J. M., Bouten, W., Camphuysen, K. C. J., Nolet, B. A. and Shamoun-Baranes, J. (2023). Energetic and behavioral consequences of migration: an empirical evaluation in the context of the full annual cycle. PubMed DOI PMC
Bryce, C. M., Dunford, C. E., Pagano, A. M., Wang, Y., Borg, B. L., Arthur, S. M. and Williams, T. M. (2022). Environmental correlates of activity and energetics in a wide-ranging social carnivore. DOI
Böhner, H., Kleiven, E. F., Ims, R. A. and Soininen, E. M. (2023). A semi-automatic workflow to process images from small mammal camera traps. DOI
Campbell, H. A., Beyer, H. L., Dennis, T. E., Dwyer, R. G., Forester, J. D., Fukuda, Y., Lynch, C., Hindell, M. A., Menke, N., Morales, J. M.et al. (2015). Finding our way: on the sharing and reuse of animal telemetry data in Australasia. PubMed DOI
Campbell, H. A., Urbano, F., Davidson, S., Dettki, H. and Cagnacci, F. (2016). A plea for standards in reporting data collected by animal-borne electronic devices. DOI
Chamberlain, S. A. and Szöcs, E. (2013). taxize: taxonomic search and retrieval in R. PubMed DOI PMC
Claramunt, S. (2021). Flight efficiency explains differences in natal dispersal distances in birds. PubMed DOI PMC
Colella, J. P., Stephens, R. B., Campbell, M. L., Kohli, B. A., Parsons, D. J. and Mclean, B. S. (2021). The open-specimen movement. DOI
Conde, D. A., Staerk, J., Colchero, F., Da Silva, R., Schöley, J., Baden, H. M., Jouvet, L., Fa, J. E., Syed, H., Jongejans, E.et al. (2019). Data gaps and opportunities for comparative and conservation biology. PubMed DOI PMC
Cooke, S. J., Hinch, S. G., Wikelski, M., Andrews, R. D., Kuchel, L. J., Wolcott, T. G. and Butler, P. J. (2004). Biotelemetry: a mechanistic approach to ecology. PubMed DOI
Culina, A., Adriaensen, F., Bailey, L. D., Burgess, M. D., Charmantier, A., Cole, E. F., Eeva, T., Matthysen, E., Nater, C. R., Sheldon, B. C.et al. (2021). Connecting the data landscape of long-term ecological studies: the SPI-Birds data hub. PubMed DOI PMC
Davidson, S. C., Bohrer, G., Gurarie, E., LaPoint, S., Mahoney, P. J., Boelman, N. T., Eitel, J. U. H., Prugh, L. R., Vierling, L. A., Jennewein, J.et al. (2020). Ecological insights from three decades of animal movement tracking across a changing Arctic. PubMed DOI
Davidson, S. C., Cagnacci, F., Newman, P., Dettki, H., Urbano, F., Desmet, P., Bajona, L., Bryant, E., Carneiro, A. P. B., Dias, M. P.et al. (2025). Establishing bio-logging data collections as dynamic archives of animal life on Earth. PubMed DOI
Dawson, S. K., Carmona, C. P., González-Suárez, M., Jönsson, M., Chichorro, F., Mallen-Cooper, M., Melero, Y., Moor, H., Simaika, J. P. and Duthie, A. B. (2021). The traits of “trait ecologists”: an analysis of the use of trait and functional trait terminology. PubMed DOI PMC
De Magalhães, J. P. and Costa, J. (2009). A database of vertebrate longevity records and their relation to other life-history traits. PubMed DOI
Des Roches, S., Post, D. M., Turley, N. E., Bailey, J. K., Hendry, A. P., Kinnison, M. T., Schweitzer, J. A. and Palkovacs, E. P. (2018). The ecological importance of intraspecific variation. PubMed DOI
Doherty, T. S., Hays, G. C. and Driscoll, D. A. (2021). Human disturbance causes widespread disruption of animal movement. PubMed DOI
Etard, A., Morrill, S. and Newbold, T. (2020). Global gaps in trait data for terrestrial vertebrates. DOI
Faurby, S., Davis, M., Pedersen, R. Ø., Schowanek, S. D., Antonelli, A. and Svenning, J.-C. (2018). PHYLACINE 1.2: the phylogenetic atlas of mammal macroecology. PubMed DOI
Fournier, A., Boone, M., Stevens, F. and Bruna, E. (2020). refsplitr: author name disambiguation, author georeferencing, and mapping of coauthorship networks with Web of Science data. DOI
Fritz, S. A. and Purvis, A. (2010). Selectivity in mammalian extinction risk and threat types: a new measure of phylogenetic signal strength in binary traits. PubMed DOI
Gaillard, J.-M., Loison, A., Festa-Bianchet, M., Yoccoz, N. G. and Solberg, E. (2003). Ecological correlates of life span in populations of large herbivorous mammals.
Gainsbury, A. M., Tallowin, O. J. S. and Meiri, S. (2018). An updated global data set for diet preferences in terrestrial mammals: testing the validity of extrapolation. DOI
Gallagher, R. V., Falster, D. S., Maitner, B. S., Salguero-Gómez, R., Vandvik, V., Pearse, W. D., Schneider, F. D., Kattge, J., Poelen, J. H., Madin, J. S.et al. (2020). Open Science principles for accelerating trait-based science across the Tree of Life. PubMed DOI
Gascoigne, S. J. L., Rolph, S., Sankey, D., Nidadavolu, N., Stell Pičman, A. S., Hernández, C. M., Philpott, M. E. R., Salam, A., Bernard, C., Fenollosa, E.et al. (2023). A standard protocol to report discrete stage-structured demographic information. DOI
Grenié, M., Berti, E., Carvajal-Quintero, J., Dädlow, G. M. L., Sagouis, A. and Winter, M. (2023). Harmonizing taxon names in biodiversity data: a review of tools, databases and best practices. DOI
Gross, M. (2024). Migratory species in danger. DOI
Guralnick, R. (2017). Traits as essential biodiversity variables.
Guralnick, R., Zermoglio, P., Wieczorek, J., LaFrance, R., Bloom, D. and Russell, L. (2016). The importance of digitized biocollections as a source of trait data and a new VertNet resource. PubMed DOI PMC
Hantak, M. M., McLean, B. S., Li, D. and Guralnick, R. P. (2021). Mammalian body size is determined by interactions between climate, urbanization, and ecological traits. PubMed DOI PMC
Hardisty, A. R., Ellwood, E. R., Nelson, G., Zimkus, B., Buschbom, J., Addink, W., Rabeler, R. K., Bates, J., Bentley, A., Fortes, J. A. B.et al. (2022). Digital extended specimens: enabling an extensible network of biodiversity data records as integrated digital objects on the internet. PubMed DOI PMC
Hazen, E. L., Maxwell, S. M., Bailey, H., Bograd, S. J., Hamann, M., Gaspar, P., Godley, B. J. and Shillinger, G. L. (2012). Ontogeny in marine tagging and tracking science: technologies and data gaps. DOI
Healy, K., Guillerme, T., Finlay, S., Kane, A., Kelly, S. B. A., McClean, D., Kelly, D. J., Donohue, I., Jackson, A. L. and Cooper, N. (2014). Ecology and mode-of-life explain lifespan variation in birds and mammals. PubMed DOI PMC
Hein, A. M., Hou, C. and Gillooly, J. F. (2012). Energetic and biomechanical constraints on animal migration distance. PubMed DOI
Herberstein, M. E., McLean, D. J., Lowe, E., Wolff, J. O., Khan, M. K., Smith, K., Allen, A. P., Bulbert, M., Buzatto, B. A., Eldridge, M. D. B.et al. (2022). AnimalTraits - a curated animal trait database for body mass, metabolic rate and brain size. PubMed DOI PMC
Hindell, M. A., Reisinger, R. R., Ropert-Coudert, Y., Hückstädt, L. A., Trathan, P. N., Bornemann, H., Charrassin, J.-B., Chown, S. L., Costa, D. P. and Danis, B.et al. (2020). Tracking of marine predators to protect Southern Ocean ecosystems. PubMed DOI
Iverson, S. J., Fisk, A. T., Hinch, S. G., Mills Flemming, J., Cooke, S. J. and Whoriskey, F. G. (2018). The ocean tracking network: advancing frontiers in aquatic science and management.
Jetz, W., Sekercioglu, C. H. and Böhning-Gaese, K. (2008). The worldwide variation in avian clutch size across species and space. PubMed DOI PMC
Jetz, W., McGeoch, M. A., Guralnick, R., Ferrier, S., Beck, J., Costello, M. J., Fernandez, M., Geller, G. N., Keil, P., Merow, C.et al. (2019). Essential biodiversity variables for mapping and monitoring species populations. PubMed DOI
Joly, K., Gurarie, E., Sorum, M. S., Kaczensky, P., Cameron, M. D., Jakes, A. F., Borg, B. L., Nandintsetseg, D., Hopcraft, J. G. C., Buuveibaatar, B.et al. (2019). Longest terrestrial migrations and movements around the world. PubMed DOI PMC
Jones, K. E., Bielby, J., Cardillo, M., Fritz, S. A., O'Dell, J., Orme, C. D. L., Safi, K., Sechrest, W., Boakes, E. H. and Carbone, C.et al. (2009). PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals: ecological archives E090-184. DOI
Kays, R., McShea, W. J. and Wikelski, M. (2020). Born-digital biodiversity data: millions and billions. DOI
Kays, R., Davidson, S. C., Berger, M., Bohrer, G., Fiedler, W., Flack, A., Hirt, J., Hahn, C., Gauggel, D., Russell, B.et al. (2022). The Movebank system for studying global animal movement and demography. DOI
Kays, R., Hirsch, B., Caillaud, D., Mares, R., Alavi, S., Havmøller, R. W. and Crofoot, M. (2023). Multi-scale movement syndromes for comparative analyses of animal movement patterns. PubMed DOI PMC
Kentie, R., Morgan Brown, J., Camphuysen, K. C. J. and Shamoun-Baranes, J. (2023). Distance doesn't matter: migration strategy in a seabird has no effect on survival or reproduction. PubMed DOI PMC
Kooyman, G. L. (2004). Genesis and evolution of bio-logging devices: l963-2002.
Kranstauber, B., Cameron, A., Weinzerl, R., Fountain, T., Tilak, S., Wikelski, M. and Kays, R. (2011). The Movebank data model for animal tracking. DOI
Laws, R. M., Parker, I. S. and Johnstone, R. C. (1975). Elephants and their habitats. The ecology of elephants in North Bunyoro, Uganda. DOI
Levin, S. C., Evers, S., Potter, T., Guerrero, M. P., Childs, D. Z., Compagnoni, A., Knight, T. M. and Salguero-Gómez, R. (2022). Rpadrino: an R package to access and use PADRINO, an open access database of integral projection models. DOI
Lindstedt, S. L. and Calder, W. A. (1981). Body size, physiological time, and longevity of homeothermic animals. DOI
Martins, P. M., Anderson, M. J., Sweatman, W. L. and Punnett, A. J. (2024). Significant shifts in latitudinal optima of North American birds. PubMed DOI PMC
Mathot, K. J., Dingemanse, N. J. and Nakagawa, S. (2019). The covariance between metabolic rate and behaviour varies across behaviours and thermal types: meta-analytic insights. PubMed DOI
McLean, B. S. and Guralnick, R. P. (2021). Digital biodiversity data sets reveal breeding phenology and its drivers in a widespread North American mammal. PubMed DOI
McLean, B. S., Barve, N. and Guralnick, R. P. (2022). Sex-specific breeding phenologies in the North American deer mouse (Peromyscus maniculatus). DOI
McNab, B. K. (2008). An analysis of the factors that influence the level and scaling of mammalian BMR. PubMed DOI
Mundy, P., Butchart, D., Ledger, J. and Piper, S. (1992).
Myhrvold, N. P., Baldridge, E., Chan, B., Sivam, D., Freeman, D. L. and Ernest, S. K. M. (2015). An amniote life-history database to perform comparative analyses with birds, mammals, and reptiles. DOI
Nagy, K. A., Girard, I. A. and Brown, T. K. (1999). Energetics of free-ranging mammals, reptiles, and birds. PubMed DOI
Nathan, R., Getz, W. M., Revilla, E., Holyoak, M., Kadmon, R., Saltz, D. and Smouse, P. E. (2008). A movement ecology paradigm for unifying organismal movement research. PubMed DOI PMC
Neate-Clegg, M. H. C., Tonelli, B. A., Youngflesh, C., Wu, J. X., Montgomery, G. A., Şekercioğlu, Ç. H. and Tingley, M. W. (2023). Traits shaping urban tolerance in birds differ around the world. PubMed DOI
Odlyzko, A. (2002). The rapid evolution of scholarly communication. DOI
Paniw, M., James, T. D., Ruth Archer, C., Römer, G., Levin, S., Compagnoni, A., Che-Castaldo, J., Bennett, J. M., Mooney, A., Childs, D. Z.et al. (2021). The myriad of complex demographic responses of terrestrial mammals to climate change and gaps of knowledge: a global analysis. PubMed DOI
Passoni, G., Coulson, T., Ranc, N., Corradini, A., Hewison, A. J. M., Ciuti, S., Gehr, B., Heurich, M., Brieger, F., Sandfort, R.et al. (2021). Roads constrain movement across behavioural processes in a partially migratory ungulate. PubMed DOI PMC
Payne, A., Hale, C., Kendall-Bar, J. and Beltran, R. S. (2024). Minimum reporting standards can promote animal welfare and data quality in biologging research. DOI
Pierce, A. K., Yanco, S. W. and Wunder, M. B. (2024). Seasonal migration alters energetic trade-off optimization and shapes life history. PubMed DOI
Pigot, A. L., Sheard, C., Miller, E. T., Bregman, T. P., Freeman, B. G., Roll, U., Seddon, N., Trisos, C. H., Weeks, B. C. and Tobias, J. A. (2020). Macroevolutionary convergence connects morphological form to ecological function in birds. PubMed DOI
Pottier, P., Noble, D. W. A., Seebacher, F., Wu, N. C., Burke, S., Lagisz, M., Schwanz, L. E., Drobniak, S. M. and Nakagawa, S. (2024). New horizons for comparative studies and meta-analyses. PubMed DOI
Ramachandran, R., Bugbee, K. and Murphy, K. (2021). From open data to open science. DOI
Reboredo Segovia, A. L., Romano, D. and Armsworth, P. R. (2020). Who studies where? Boosting tropical conservation research where it is most needed. DOI
Ropert-Coudert, Y., Van de Putte, A. P., Reisinger, R. R., Bornemann, H., Charrassin, J.-B., Costa, D. P., Danis, B., Hückstädt, L. A., Jonsen, I. D., Lea, M.-A.et al. (2020). The retrospective analysis of Antarctic tracking data project. PubMed DOI PMC
Ruckstuhl, K. E. and Neuhaus, P. (2000). Sexual segregation in ungulates: a new approach. DOI
Rutz, C. (2022). Register animal-tracking tags to boost conservation. PubMed DOI
Rutz, C. and Hays, G. C. (2009). New frontiers in biologging science. PubMed DOI PMC
Salguero-Gómez, R., Jones, O. R., Archer, C. R., Bein, C., de Buhr, H., Farack, C., Gottschalk, F., Hartmann, A., Henning, A., Hoppe, G.et al. (2016). COMADRE: a global data base of animal demography. PubMed DOI PMC
Salguero-Gómez, R., Jackson, J. and Gascoigne, S. J. L. (2021). Four key challenges in the open-data revolution. PubMed DOI PMC
Santini, L., Isaac, N. J. B. and Ficetola, G. F. (2018). TetraDENSITY: a database of population density estimates in terrestrial vertebrates. DOI
Sawyer, H., LeBeau, C. W., McDonald, T. L., Xu, W. and Middleton, A. D. (2019). All routes are not created equal: an ungulate's choice of migration route can influence its survival. DOI
Schneider, F. D., Fichtmueller, D., Gossner, M. M., Güntsch, A., Jochum, M., König-Ries, B., Le Provost, G., Manning, P., Ostrowski, A., Penone, C.et al. (2019). Towards an ecological trait-data standard. DOI
Sequeira, A. M. M., O'Toole, M., Keates, T. R., McDonnell, L. H., Braun, C. D., Hoenner, X., Jaine, F. R. A., Jonsen, I. D., Newman, P., Pye, J.et al. (2021). A standardisation framework for bio-logging data to advance ecological research and conservation. DOI
Sheard, C., Neate-Clegg, M. H. C., Alioravainen, N., Jones, S. E. I., Vincent, C., MacGregor, H. E. A., Bregman, T. P., Claramunt, S. and Tobias, J. A. (2020). Ecological drivers of global gradients in avian dispersal inferred from wing morphology. PubMed DOI PMC
Sillett, T. S. and Holmes, R. T. (2002). Variation in survivorship of a migratory songbird throughout its annual cycle. DOI
Skinner, J. D. and Chimimba, C. T. (2005).
Smith, F. A., Lyons, S. K., Ernest, S. K. M., Jones, K. E., Kaufman, D. M., Dayan, T., Marquet, P. A., Brown, J. H. and Haskell, J. P. (2003). Body mass of late quaternary mammals. DOI
Soria, C. D., Pacifici, M., Di Marco, M., Stephen, S. M. and Rondinini, C. (2021). COMBINE: a coalesced mammal database of intrinsic and extrinsic traits. PubMed DOI
Streit, R. P. and Bellwood, D. R. (2023). To harness traits for ecology, let's abandon ‘functionality.’ PubMed DOI
Sutherland, W. J., Freckleton, R. P., Godfray, H. C. J., Beissinger, S. R., Benton, T., Cameron, D. D., Carmel, Y., Coomes, D. A., Coulson, T. and Emmerson, M. C.et al. (2013). Identification of 100 fundamental ecological questions. DOI
Tacutu, R., Craig, T., Budovsky, A., Wuttke, D., Lehmann, G., Taranukha, D., Costa, J., Fraifeld, V. E. and de Magalhães, J. P. (2013). Human ageing genomic resources: integrated databases and tools for the biology and genetics of ageing. PubMed DOI PMC
Teitelbaum, C. S., Fagan, W. F., Fleming, C. H., Dressler, G., Calabrese, J. M., Leimgruber, P. and Mueller, T. (2015). How far to go? Determinants of migration distance in land mammals. PubMed DOI
Titley, M. A., Snaddon, J. L. and Turner, E. C. (2017). Scientific research on animal biodiversity is systematically biased towards vertebrates and temperate regions. PubMed DOI PMC
Tobias, J. A., Sheard, C., Pigot, A. L., Devenish, A. J. M., Yang, J., Sayol, F., Neate-Clegg, M. H. C., Alioravainen, N., Weeks, T. L., Barber, R. A.et al. (2022). AVONET: morphological, ecological and geographical data for all birds. PubMed DOI
Tombak, K. J., Hex, S. B. S. W. and Rubenstein, D. I. (2024). New estimates indicate that males are not larger than females in most mammal species. PubMed DOI PMC
Trimble, M. J. and van Aarde, R. J. (2012). Geographical and taxonomic biases in research on biodiversity in human-modified landscapes. DOI
Troudet, J., Grandcolas, P., Blin, A., Vignes-Lebbe, R. and Legendre, F. (2017). Taxonomic bias in biodiversity data and societal preferences. PubMed DOI PMC
Tucker, M. A., Böhning-Gaese, K., Fagan, W. F., Fryxell, J. M., Van Moorter, B., Alberts, S. C., Ali, A. H., Allen, A. M., Attias, N., Avgar, T.et al. (2018). Moving in the anthropocene: global reductions in terrestrial mammalian movements. PubMed DOI
Upham, N. S., Esselstyn, J. A. and Jetz, W. (2019). Inferring the mammal tree: species-level sets of phylogenies for questions in ecology, evolution, and conservation. PubMed DOI PMC
Urbano, F., Cagnacci, F. and Initiative, E. C. (2021). Data management and sharing for collaborative science: lessons learnt from the Euromammals initiative. DOI
van der Kolk, H.-J., Desmet, P., Oosterbeek, K., Allen, A. M., Baptist, M. J., Bom, R. A., Davidson, S. C., de Jong, J., de Kroon, H., Dijkstra, B.et al. (2022). GPS tracking data of Eurasian oystercatchers ( PubMed DOI PMC
Violle, C., Navas, M.-L., Vile, D., Kazakou, E., Fortunel, C., Hummel, I. and Garnier, E. (2007). Let the concept of trait be functional!. DOI
Watanabe, Y. Y. and Papastamatiou, Y. P. (2023). Biologging and biotelemetry: tools for understanding the lives and environments of marine animals. PubMed DOI
Weeks, B. C., Willard, D. E., Zimova, M., Ellis, A. A., Witynski, M. L., Hennen, M. and Winger, B. M. (2020). Shared morphological consequences of global warming in North American migratory birds. PubMed DOI
Weeks, B. C., O'Brien, B. K., Chu, J. J., Claramunt, S., Sheard, C. and Tobias, J. A. (2022). Morphological adaptations linked to flight efficiency and aerial lifestyle determine natal dispersal distance in birds. DOI
Weeks, B. C., Zhou, Z., O'Brien, B. K., Darling, R., Dean, M., Dias, T., Hassena, G., Zhang, M. and Fouhey, D. F. (2023). A deep neural network for high-throughput measurement of functional traits on museum skeletal specimens. DOI
Weller, A. K., Chapman, O. S., Gora, S. L., Guralnick, R. P. and McLean, B. S. (2024). New insight into drivers of mammalian litter size from individual-level traits. DOI
White, C. R., Marshall, D. J., Chown, S. L., Clusella-Trullas, S., Portugal, S. J., Franklin, C. E. and Seebacher, F. (2021). Geographical bias in physiological data limits predictions of global change impacts. DOI
Wieczorek, J., Bloom, D., Guralnick, R., Blum, S., Döring, M., Giovanni, R., Robertson, T. and Vieglais, D. (2012). Darwin core: an evolving community-developed biodiversity data standard. PubMed DOI PMC
Williams, H. J., Taylor, L. A., Benhamou, S., Bijleveld, A. I., Clay, T. A., de Grissac, S., Demšar, U., English, H. M., Franconi, N., Gómez-Laich, A.et al. (2020). Optimizing the use of biologgers for movement ecology research. PubMed DOI PMC
Wilman, H., Belmaker, J., Simpson, J., de la Rosa, C., Rivadeneira, M. M. and Jetz, W. (2014). EltonTraits 1.0: species-level foraging attributes of the world's birds and mammals. DOI
Winger, B. M. and Pegan, T. M. (2021). Migration distance is a fundamental axis of the slow-fast continuum of life history in boreal birds. DOI
Wu, N. C. and Seebacher, F. (2022). Physiology can predict animal activity, exploration, and dispersal. PubMed DOI PMC
Zheng, S., Hu, J., Ma, Z., Lindenmayer, D. and Liu, J. (2023). Increases in intraspecific body size variation are common among North American mammals and birds between 1880 and 2020. PubMed DOI
Zimova, M., Weeks, B. C., Willard, D. E., Giery, S. T., Jirinec, V., Burner, R. C. and Winger, B. M. (2023). Body size predicts the rate of contemporary morphological change in birds. PubMed DOI PMC