TY - JOUR A1 - Tucker, Marlee A. A1 - Boehning-Gaese, Katrin A1 - Fagan, William F. A1 - Fryxell, John M. A1 - Van Moorter, Bram A1 - Alberts, Susan C. A1 - Ali, Abdullahi H. A1 - Allen, Andrew M. A1 - Attias, Nina A1 - Avgar, Tal A1 - Bartlam-Brooks, Hattie A1 - Bayarbaatar, Buuveibaatar A1 - Belant, Jerrold L. A1 - Bertassoni, Alessandra A1 - Beyer, Dean A1 - Bidner, Laura A1 - van Beest, Floris M. A1 - Blake, Stephen A1 - Blaum, Niels A1 - Bracis, Chloe A1 - Brown, Danielle A1 - de Bruyn, P. J. Nico A1 - Cagnacci, Francesca A1 - Calabrese, Justin M. A1 - Camilo-Alves, Constanca A1 - Chamaille-Jammes, Simon A1 - Chiaradia, Andre A1 - Davidson, Sarah C. A1 - Dennis, Todd A1 - DeStefano, Stephen A1 - Diefenbach, Duane A1 - Douglas-Hamilton, Iain A1 - Fennessy, Julian A1 - Fichtel, Claudia A1 - Fiedler, Wolfgang A1 - Fischer, Christina A1 - Fischhoff, Ilya A1 - Fleming, Christen H. A1 - Ford, Adam T. A1 - Fritz, Susanne A. A1 - Gehr, Benedikt A1 - Goheen, Jacob R. A1 - Gurarie, Eliezer A1 - Hebblewhite, Mark A1 - Heurich, Marco A1 - Hewison, A. J. Mark A1 - Hof, Christian A1 - Hurme, Edward A1 - Isbell, Lynne A. A1 - Janssen, Rene A1 - Jeltsch, Florian A1 - Kaczensky, Petra A1 - Kane, Adam A1 - Kappeler, Peter M. A1 - Kauffman, Matthew A1 - Kays, Roland A1 - Kimuyu, Duncan A1 - Koch, Flavia A1 - Kranstauber, Bart A1 - LaPoint, Scott A1 - Leimgruber, Peter A1 - Linnell, John D. C. A1 - Lopez-Lopez, Pascual A1 - Markham, A. Catherine A1 - Mattisson, Jenny A1 - Medici, Emilia Patricia A1 - Mellone, Ugo A1 - Merrill, Evelyn A1 - Mourao, Guilherme de Miranda A1 - Morato, Ronaldo G. A1 - Morellet, Nicolas A1 - Morrison, Thomas A. A1 - Diaz-Munoz, Samuel L. A1 - Mysterud, Atle A1 - Nandintsetseg, Dejid A1 - Nathan, Ran A1 - Niamir, Aidin A1 - Odden, John A1 - Oliveira-Santos, Luiz Gustavo R. A1 - Olson, Kirk A. A1 - Patterson, Bruce D. A1 - de Paula, Rogerio Cunha A1 - Pedrotti, Luca A1 - Reineking, Bjorn A1 - Rimmler, Martin A1 - Rogers, Tracey L. A1 - Rolandsen, Christer Moe A1 - Rosenberry, Christopher S. A1 - Rubenstein, Daniel I. A1 - Safi, Kamran A1 - Said, Sonia A1 - Sapir, Nir A1 - Sawyer, Hall A1 - Schmidt, Niels Martin A1 - Selva, Nuria A1 - Sergiel, Agnieszka A1 - Shiilegdamba, Enkhtuvshin A1 - Silva, Joao Paulo A1 - Singh, Navinder A1 - Solberg, Erling J. A1 - Spiegel, Orr A1 - Strand, Olav A1 - Sundaresan, Siva A1 - Ullmann, Wiebke A1 - Voigt, Ulrich A1 - Wall, Jake A1 - Wattles, David A1 - Wikelski, Martin A1 - Wilmers, Christopher C. A1 - Wilson, John W. A1 - Wittemyer, George A1 - Zieba, Filip A1 - Zwijacz-Kozica, Tomasz A1 - Mueller, Thomas T1 - Moving in the Anthropocene BT - global reductions in terrestrial mammalian movements JF - Science N2 - Animal movement is fundamental for ecosystem functioning and species survival, yet the effects of the anthropogenic footprint on animal movements have not been estimated across species. Using a unique GPS-tracking database of 803 individuals across 57 species, we found that movements of mammals in areas with a comparatively high human footprint were on average one-half to one-third the extent of their movements in areas with a low human footprint. We attribute this reduction to behavioral changes of individual animals and to the exclusion of species with long-range movements from areas with higher human impact. Global loss of vagility alters a key ecological trait of animals that affects not only population persistence but also ecosystem processes such as predator-prey interactions, nutrient cycling, and disease transmission. Y1 - 2018 U6 - https://doi.org/10.1126/science.aam9712 SN - 0036-8075 SN - 1095-9203 VL - 359 IS - 6374 SP - 466 EP - 469 PB - American Assoc. for the Advancement of Science CY - Washington ER - TY - JOUR A1 - Noonan, Michael J. A1 - Fleming, Christen H. A1 - Tucker, Marlee A. A1 - Kays, Roland A1 - Harrison, Autumn-Lynn A1 - Crofoot, Margaret C. A1 - Abrahms, Briana A1 - Alberts, Susan C. A1 - Ali, Abdullahi H. A1 - Blaum, Niels T1 - Effects of body size on estimation of mammalian area requirements JF - Conservation Biology N2 - Accurately quantifying species' area requirements is a prerequisite for effective area-based conservation. This typically involves collecting tracking data on species of interest and then conducting home-range analyses. Problematically, autocorrelation in tracking data can result in space needs being severely underestimated. Based on the previous work, we hypothesized the magnitude of underestimation varies with body mass, a relationship that could have serious conservation implications. To evaluate this hypothesis for terrestrial mammals, we estimated home-range areas with global positioning system (GPS) locations from 757 individuals across 61 globally distributed mammalian species with body masses ranging from 0.4 to 4000 kg. We then applied block cross-validation to quantify bias in empirical home-range estimates. Area requirements of mammals <10 kg were underestimated by a mean approximately15%, and species weighing approximately100 kg were underestimated by approximately50% on average. Thus, we found area estimation was subject to autocorrelation-induced bias that was worse for large species. Combined with the fact that extinction risk increases as body mass increases, the allometric scaling of bias we observed suggests the most threatened species are also likely to be those with the least accurate home-range estimates. As a correction, we tested whether data thinning or autocorrelation-informed home-range estimation minimized the scaling effect of autocorrelation on area estimates. Data thinning required an approximately93% data loss to achieve statistical independence with 95% confidence and was, therefore, not a viable solution. In contrast, autocorrelation-informed home-range estimation resulted in consistently accurate estimates irrespective of mass. When relating body mass to home range size, we detected that correcting for autocorrelation resulted in a scaling exponent significantly >1, meaning the scaling of the relationship changed substantially at the upper end of the mass spectrum. KW - allometry KW - animal movement KW - area-based conservation KW - autocorrelation KW - home range KW - kernel density estimation KW - reserve design KW - scaling Y1 - 2019 VL - 34 IS - 4 PB - Wiley-Blackwell CY - Oxford ER - TY - GEN A1 - Noonan, Michael J. A1 - Fleming, Christen H. A1 - Tucker, Marlee A. A1 - Kays, Roland A1 - Harrison, Autumn-Lynn A1 - Crofoot, Margaret C. A1 - Abrahms, Briana A1 - Alberts, Susan C. A1 - Ali, Abdullahi H. A1 - Blaum, Niels T1 - Effects of body size on estimation of mammalian area requirements T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Accurately quantifying species' area requirements is a prerequisite for effective area-based conservation. This typically involves collecting tracking data on species of interest and then conducting home-range analyses. Problematically, autocorrelation in tracking data can result in space needs being severely underestimated. Based on the previous work, we hypothesized the magnitude of underestimation varies with body mass, a relationship that could have serious conservation implications. To evaluate this hypothesis for terrestrial mammals, we estimated home-range areas with global positioning system (GPS) locations from 757 individuals across 61 globally distributed mammalian species with body masses ranging from 0.4 to 4000 kg. We then applied block cross-validation to quantify bias in empirical home-range estimates. Area requirements of mammals <10 kg were underestimated by a mean approximately15%, and species weighing approximately100 kg were underestimated by approximately50% on average. Thus, we found area estimation was subject to autocorrelation-induced bias that was worse for large species. Combined with the fact that extinction risk increases as body mass increases, the allometric scaling of bias we observed suggests the most threatened species are also likely to be those with the least accurate home-range estimates. As a correction, we tested whether data thinning or autocorrelation-informed home-range estimation minimized the scaling effect of autocorrelation on area estimates. Data thinning required an approximately93% data loss to achieve statistical independence with 95% confidence and was, therefore, not a viable solution. In contrast, autocorrelation-informed home-range estimation resulted in consistently accurate estimates irrespective of mass. When relating body mass to home range size, we detected that correcting for autocorrelation resulted in a scaling exponent significantly >1, meaning the scaling of the relationship changed substantially at the upper end of the mass spectrum. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1206 KW - allometry KW - animal movement KW - area-based conservation KW - autocorrelation KW - home range KW - kernel density estimation KW - reserve design KW - scaling Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-526824 SN - 1866-8372 IS - 4 ER - TY - JOUR A1 - Noonan, Michael J. A1 - Tucker, Marlee A. A1 - Fleming, Christen H. A1 - Akre, Thomas S. A1 - Alberts, Susan C. A1 - Ali, Abdullahi H. A1 - Altmann, Jeanne A1 - Antunes, Pamela Castro A1 - Belant, Jerrold L. A1 - Beyer, Dean A1 - Blaum, Niels A1 - Boehning-Gaese, Katrin A1 - Cullen Jr, Laury A1 - de Paula, Rogerio Cunha A1 - Dekker, Jasja A1 - Drescher-Lehman, Jonathan A1 - Farwig, Nina A1 - Fichtel, Claudia A1 - Fischer, Christina A1 - Ford, Adam T. A1 - Goheen, Jacob R. A1 - Janssen, Rene A1 - Jeltsch, Florian A1 - Kauffman, Matthew A1 - Kappeler, Peter M. A1 - Koch, Flavia A1 - LaPoint, Scott A1 - Markham, A. Catherine A1 - Medici, Emilia Patricia A1 - Morato, Ronaldo G. A1 - Nathan, Ran A1 - Oliveira-Santos, Luiz Gustavo R. A1 - Olson, Kirk A. A1 - Patterson, Bruce D. A1 - Paviolo, Agustin A1 - Ramalho, Emiliano Estero A1 - Rosner, Sascha A1 - Schabo, Dana G. A1 - Selva, Nuria A1 - Sergiel, Agnieszka A1 - da Silva, Marina Xavier A1 - Spiegel, Orr A1 - Thompson, Peter A1 - Ullmann, Wiebke A1 - Zieba, Filip A1 - Zwijacz-Kozica, Tomasz A1 - Fagan, William F. A1 - Mueller, Thomas A1 - Calabrese, Justin M. T1 - A comprehensive analysis of autocorrelation and bias in home range estimation JF - Ecological monographs : a publication of the Ecological Society of America. N2 - Home range estimation is routine practice in ecological research. While advances in animal tracking technology have increased our capacity to collect data to support home range analysis, these same advances have also resulted in increasingly autocorrelated data. Consequently, the question of which home range estimator to use on modern, highly autocorrelated tracking data remains open. This question is particularly relevant given that most estimators assume independently sampled data. Here, we provide a comprehensive evaluation of the effects of autocorrelation on home range estimation. We base our study on an extensive data set of GPS locations from 369 individuals representing 27 species distributed across five continents. We first assemble a broad array of home range estimators, including Kernel Density Estimation (KDE) with four bandwidth optimizers (Gaussian reference function, autocorrelated‐Gaussian reference function [AKDE], Silverman's rule of thumb, and least squares cross‐validation), Minimum Convex Polygon, and Local Convex Hull methods. Notably, all of these estimators except AKDE assume independent and identically distributed (IID) data. We then employ half‐sample cross‐validation to objectively quantify estimator performance, and the recently introduced effective sample size for home range area estimation ( N̂ area ) to quantify the information content of each data set. We found that AKDE 95% area estimates were larger than conventional IID‐based estimates by a mean factor of 2. The median number of cross‐validated locations included in the hold‐out sets by AKDE 95% (or 50%) estimates was 95.3% (or 50.1%), confirming the larger AKDE ranges were appropriately selective at the specified quantile. Conversely, conventional estimates exhibited negative bias that increased with decreasing N̂ area. To contextualize our empirical results, we performed a detailed simulation study to tease apart how sampling frequency, sampling duration, and the focal animal's movement conspire to affect range estimates. Paralleling our empirical results, the simulation study demonstrated that AKDE was generally more accurate than conventional methods, particularly for small N̂ area. While 72% of the 369 empirical data sets had >1,000 total observations, only 4% had an N̂ area >1,000, where 30% had an N̂ area <30. In this frequently encountered scenario of small N̂ area, AKDE was the only estimator capable of producing an accurate home range estimate on autocorrelated data. KW - animal movement KW - kernel density estimation KW - local convex hull KW - minimum convex polygon KW - range distribution KW - space use KW - telemetry KW - tracking data Y1 - 2018 U6 - https://doi.org/10.1002/ecm.1344 SN - 0012-9615 SN - 1557-7015 VL - 89 IS - 2 PB - Wiley CY - Hoboken ER -