TY - JOUR
T1 - Evaluating expert-based habitat suitability information of terrestrial mammals with GPS-tracking data
AU - Broekman, Maarten J.E.
AU - Hilbers, Jelle P.
AU - Huijbregts, Mark A.J.
AU - Mueller, Thomas
AU - Ali, Abdullahi H.
AU - Andrén, Henrik
AU - Altmann, Jeanne
AU - Aronsson, Malin
AU - Attias, Nina
AU - Bartlam-Brooks, Hattie L.A.
AU - van Beest, Floris M.
AU - Belant, Jerrold L.
AU - Beyer, Dean E.
AU - Bidner, Laura
AU - Blaum, Niels
AU - Boone, Randall B.
AU - Boyce, Mark S.
AU - Brown, Michael B.
AU - Cagnacci, Francesca
AU - Černe, Rok
AU - Chamaillé-Jammes, Simon
AU - Dejid, Nandintsetseg
AU - Dekker, Jasja
AU - L. J. Desbiez, Arnaud
AU - Díaz-Muñoz, Samuel L.
AU - Fennessy, Julian
AU - Fichtel, Claudia
AU - Fischer, Christina
AU - Fisher, Jason T.
AU - Fischhoff, Ilya
AU - Ford, Adam T.
AU - Fryxell, John M.
AU - Gehr, Benedikt
AU - Goheen, Jacob R.
AU - Hauptfleisch, Morgan
AU - Hewison, A. J.Mark
AU - Hering, Robert
AU - Heurich, Marco
AU - Isbell, Lynne A.
AU - Janssen, René
AU - Jeltsch, Florian
AU - Kaczensky, Petra
AU - Kappeler, Peter M.
AU - Krofel, Miha
AU - LaPoint, Scott
AU - Latham, A. David M.
AU - Linnell, John D.C.
AU - Markham, A. Catherine
AU - Mattisson, Jenny
AU - Medici, Emilia Patricia
AU - de Miranda Mourão, Guilherme
AU - Van Moorter, Bram
AU - Morato, Ronaldo G.
AU - Morellet, Nicolas
AU - Mysterud, Atle
AU - Mwiu, Stephen
AU - Odden, John
AU - Olson, Kirk A.
AU - Ornicāns, Aivars
AU - Pagon, Nives
AU - Panzacchi, Manuela
AU - Persson, Jens
AU - Petroelje, Tyler
AU - Rolandsen, Christer Moe
AU - Roshier, David
AU - Rubenstein, Daniel I.
AU - Saïd, Sonia
AU - Salemgareyev, Albert R.
AU - Sawyer, Hall
AU - Schmidt, Niels Martin
AU - Selva, Nuria
AU - Sergiel, Agnieszka
AU - Stabach, Jared
AU - Stacy-Dawes, Jenna
AU - Stewart, Frances E.C.
AU - Stiegler, Jonas
AU - Strand, Olav
AU - Sundaresan, Siva
AU - Svoboda, Nathan J.
AU - Ullmann, Wiebke
AU - Voigt, Ulrich
AU - Wall, Jake
AU - Wikelski, Martin
AU - Wilmers, Christopher C.
AU - Zięba, Filip
AU - Zwijacz-Kozica, Tomasz
AU - Schipper, Aafke M.
AU - Tucker, Marlee A.
N1 - Funding Information:
M.J.E.B., J.P.H. and M.A.J.H. were financed by a grant from the Dutch research foundation (016.Vici.170.190). M.A.T. was supported by a Radboud Excellence Initiative Fellowship. N.D. was supported by the German Federal Ministry of Education and Research (BMBF, 01LC1820A). M.S.B. was funded by Natural Sciences and Engineering Research Council of Canada, Alberta Conservation Association. Data collection at Zackenberg, NE Greenland, was supported by the 15 June Foundation. J.L.B. was supported by Federal Aid in Wildlife Restoration, Safari Club International Foundation, Safari Club International Michigan Involvement Committee. Funding to L.A.I. was provided by the National Science Foundation (grant nos. BCS 99–03949, BCS 1266389), the L.S.B. Leakey Foundation, and the Committee on Research, University of California, Davis. The study from LTSER ZA Pyrénées Garonne was funded in part by the ANR grant Mov‐It (ANR‐16‐CE02‐0010). Data on European brown hare (Ch.F., F.J., J.S., N.B., W.U.) were collected within the DFG funded research training group ‘BioMove’ (RTG 2118–1). N.A. was supported by scholarships from Capes (number 1575316) and Fundect (process 23/200.715/2013). N.S., A.S., F.Z., T.Z.K. were supported by the Polish‐Norwegian Research Programme operated by the National Centre for Research and Development in Poland under the Norwegian Financial Mechanism 2009–2014 in the frame of project contract no. POL‐NOR/198352/85/2013 (GLOBE). N.S. was also supported by the BearConnect project funded by the National Science Centre in Poland (2016/22/Z/NZ8/00121) through the BiodivERsA COFUND call for research proposals, with the national funders ANR/DLR‐PT/UEFISCDI/NCN/RCN. R.G.M. was supported by FAPESP (2014/24921–0). Data provided by S.C.J. were collected thanks to grants ANR‐2010‐BLAN‐1718, ANR‐11‐CEPS‐003 and ANR‐16‐CE02‐0001‐01 and support from the Zone Atelier Hwange CNRS program of the CNRS. Springbok, kudu and eland data are part of the ORYCS project funded by the German Federal Ministry of Education and Research (Grant FKZ 01LL1804A). For the study of (baboons) in Amboseli, please visit http://amboselibaboons.nd.edu/acknowledgements/ for a complete set of funding sources. The data on Lynx from Slovenia were partly financed by the European Union (INTERREG IIIA Neighborhood Program Slovenia/Hungary/Croatia 2004–2006, project ‘DinaRis’) and the European Commission (LIFE16 NAT/SL/000634 project ‘LIFE Lynx’). M.K. was supported by the Slovenian Research Agency (grants no. P4‐0059 and N1‐0163). F.C. was supported by the Autonomous Province of Trento (Grant no. 3479 BECOCERWI) and by Institutional funds during the collection of roe deer data in the Alps. Funding for the GPS fisher collar data from Alberta, Canada, was provided by InnoTech Alberta, the Natural Science and Engineering Research Council of Canada, MITACS Accelerate and the Friends of Elk Island Society, the Beaver Hills Initiative, Alberta Environment and Parks, Royal Canadian Geographic Society, TD Friends of the Environment Foundation, Fur Institute of Canada, University of Victoria, and Alberta Conservation Association Funding information Papio cynocephalus
Funding Information:
We are grateful to M. Kauffman for contributing data. D.R. is grateful to the supporters of Australian Wildlife Conservancy and the Australian Government's National Environmental Science Program. L.A.I. thanks the Kenya Wildlife Service for local affiliation, D. Simpson, S. Ekwanga, M. Mutinda, G. Omondi, W. Longor, M. Iwata, A. Surmat, M. Snider, W. Fox and K. VanderWaal for field assistance, L. Frank for the use of their field equipment, and M. Kinnaird and T. Young for logistical support in the field. R.G.M. is grateful to the Taiamã Ecological Reserve Team for supporting the jaguar capturing and handling. Springbok, kudu and eland data acquisition was supported by Etosha Heights Private Reserve (Outjo, Namibia). Some roe deer, red deer, and Eurasian lynx datasets were collated from the Euromammals database: https://euromammals.org/. For the study of Papio cynocephalus (baboons) in Amboseli see, please visit http://amboselibaboons.nd.edu/acknowledgements/ for a complete set of acknowledgments.
Funding Information:
We are grateful to M. Kauffman for contributing data. D.R. is grateful to the supporters of Australian Wildlife Conservancy and the Australian Government's National Environmental Science Program. L.A.I. thanks the Kenya Wildlife Service for local affiliation, D. Simpson, S. Ekwanga, M. Mutinda, G. Omondi, W. Longor, M. Iwata, A. Surmat, M. Snider, W. Fox and K. VanderWaal for field assistance, L. Frank for the use of their field equipment, and M. Kinnaird and T. Young for logistical support in the field. R.G.M. is grateful to the Taiamã Ecological Reserve Team for supporting the jaguar capturing and handling. Springbok, kudu and eland data acquisition was supported by Etosha Heights Private Reserve (Outjo, Namibia). Some roe deer, red deer, and Eurasian lynx datasets were collated from the Euromammals database: https://euromammals.org/ . For the study of (baboons) in Amboseli see, please visit http://amboselibaboons.nd.edu/acknowledgements/ for a complete set of acknowledgments. Papio cynocephalus
Publisher Copyright:
© 2022 The Authors. Global Ecology and Biogeography published by John Wiley & Sons Ltd.
PY - 2022/8
Y1 - 2022/8
N2 - Aim: Macroecological studies that require habitat suitability data for many species often derive this information from expert opinion. However, expert-based information is inherently subjective and thus prone to errors. The increasing availability of GPS tracking data offers opportunities to evaluate and supplement expert-based information with detailed empirical evidence. Here, we compared expert-based habitat suitability information from the International Union for Conservation of Nature (IUCN) with habitat suitability information derived from GPS-tracking data of 1,498 individuals from 49 mammal species. Location: Worldwide. Time period: 1998–2021. Major taxa studied: Forty-nine terrestrial mammal species. Methods: Using GPS data, we estimated two measures of habitat suitability for each individual animal: proportional habitat use (proportion of GPS locations within a habitat type), and selection ratio (habitat use relative to its availability). For each individual we then evaluated whether the GPS-based habitat suitability measures were in agreement with the IUCN data. To that end, we calculated the probability that the ranking of empirical habitat suitability measures was in agreement with IUCN's classification into suitable, marginal and unsuitable habitat types. Results: IUCN habitat suitability data were in accordance with the GPS data (> 95% probability of agreement) for 33 out of 49 species based on proportional habitat use estimates and for 25 out of 49 species based on selection ratios. In addition, 37 and 34 species had a > 50% probability of agreement based on proportional habitat use and selection ratios, respectively. Main conclusions: We show how GPS-tracking data can be used to evaluate IUCN habitat suitability data. Our findings indicate that for the majority of species included in this study, it is appropriate to use IUCN habitat suitability data in macroecological studies. Furthermore, we show that GPS-tracking data can be used to identify and prioritize species and habitat types for re-evaluation of IUCN habitat suitability data.
AB - Aim: Macroecological studies that require habitat suitability data for many species often derive this information from expert opinion. However, expert-based information is inherently subjective and thus prone to errors. The increasing availability of GPS tracking data offers opportunities to evaluate and supplement expert-based information with detailed empirical evidence. Here, we compared expert-based habitat suitability information from the International Union for Conservation of Nature (IUCN) with habitat suitability information derived from GPS-tracking data of 1,498 individuals from 49 mammal species. Location: Worldwide. Time period: 1998–2021. Major taxa studied: Forty-nine terrestrial mammal species. Methods: Using GPS data, we estimated two measures of habitat suitability for each individual animal: proportional habitat use (proportion of GPS locations within a habitat type), and selection ratio (habitat use relative to its availability). For each individual we then evaluated whether the GPS-based habitat suitability measures were in agreement with the IUCN data. To that end, we calculated the probability that the ranking of empirical habitat suitability measures was in agreement with IUCN's classification into suitable, marginal and unsuitable habitat types. Results: IUCN habitat suitability data were in accordance with the GPS data (> 95% probability of agreement) for 33 out of 49 species based on proportional habitat use estimates and for 25 out of 49 species based on selection ratios. In addition, 37 and 34 species had a > 50% probability of agreement based on proportional habitat use and selection ratios, respectively. Main conclusions: We show how GPS-tracking data can be used to evaluate IUCN habitat suitability data. Our findings indicate that for the majority of species included in this study, it is appropriate to use IUCN habitat suitability data in macroecological studies. Furthermore, we show that GPS-tracking data can be used to identify and prioritize species and habitat types for re-evaluation of IUCN habitat suitability data.
KW - GPS
KW - IUCN
KW - expert opinion
KW - habitat suitability
KW - habitat type
KW - habitat use
KW - mammals
KW - movement
KW - selection ratio
KW - telemetry
UR - http://www.scopus.com/inward/record.url?scp=85129731736&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85129731736&partnerID=8YFLogxK
U2 - 10.1111/geb.13523
DO - 10.1111/geb.13523
M3 - Article
C2 - 36247232
AN - SCOPUS:85129731736
SN - 1466-822X
VL - 31
SP - 1526
EP - 1541
JO - Global Ecology and Biogeography
JF - Global Ecology and Biogeography
IS - 8
ER -