A comprehensive analysis of autocorrelation and bias in home range estimation

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 ((Formula presented.)) 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 (Formula presented.). 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 (Formula presented.). While 72% of the 369 empirical data sets had >1,000 total observations, only 4% had an (Formula presented.) >1,000, where 30% had an (Formula presented.) <30. In this frequently encountered scenario of small (Formula presented.), AKDE was the only estimator capable of producing an accurate home range estimate on autocorrelated data.Fil: Noonan, Michael J.. National Zoological Park; Estados Unidos. University of Maryland; Estados UnidosFil: Tucker, Marlee A.. Senckenberg Gesellschaft Für Naturforschung; . Goethe Universitat Frankfurt; AlemaniaFil: Fleming, Christen H.. University of Maryland; Estados Unidos. National Zoological Park; Estados UnidosFil: Akre, Thomas S.. National Zoological Park; Estados UnidosFil: Alberts, Susan C.. University of Duke; Estados UnidosFil: Ali, Abdullahi H.. Hirola Conservation Programme. Garissa; KeniaFil: Altmann, Jeanne. University of Princeton; Estados UnidosFil: Antunes, Pamela Castro. Universidade Federal do Mato Grosso do Sul; BrasilFil: Belant, Jerrold L.. State University of New York; Estados UnidosFil: Beyer, Dean. Universitat Phillips; AlemaniaFil: Blaum, Niels. Universitat Potsdam; AlemaniaFil: Böhning Gaese, Katrin. Senckenberg Gesellschaft Für Naturforschung; Alemania. Goethe Universitat Frankfurt; AlemaniaFil: Cullen Jr., Laury. Instituto de Pesquisas Ecológicas; BrasilFil: de Paula, Rogerio Cunha. National Research Center For Carnivores Conservation; BrasilFil: Dekker, Jasja. Jasja Dekker Dierecologie; Países BajosFil: Drescher Lehman, Jonathan. George Mason University; Estados Unidos. National Zoological Park; Estados UnidosFil: Farwig, Nina. Michigan State University; Estados UnidosFil: Fichtel, Claudia. German Primate Center; AlemaniaFil: Fischer, Christina. Universitat Technical Zu Munich; AlemaniaFil: Ford, Adam T.. University of British Columbia; CanadáFil: Goheen, Jacob R.. University of Wyoming; Estados UnidosFil: Janssen, René. Bionet Natuuronderzoek; Países BajosFil: Jeltsch, Florian. Universitat Potsdam; AlemaniaFil: Kauffman, Matthew. University Of Wyoming; Estados UnidosFil: Kappeler, Peter M.. German Primate Center; AlemaniaFil: Koch, Flávia. German Primate Center; AlemaniaFil: LaPoint, Scott. Max Planck Institute für Ornithologie; Alemania. Columbia University; Estados UnidosFil: Markham, A. Catherine. Stony Brook University; Estados UnidosFil: Medici, Emilia Patricia. Instituto de Pesquisas Ecológicas (IPE) ; BrasilFil: Morato, Ronaldo G.. Institute For Conservation of The Neotropical Carnivores; Brasil. National Research Center For Carnivores Conservation; BrasilFil: Nathan, Ran. The Hebrew University of Jerusalem; IsraelFil: Oliveira Santos, Luiz Gustavo R.. Universidade Federal do Mato Grosso do Sul; BrasilFil: Olson, Kirk A.. Wildlife Conservation Society; Estados Unidos. National Zoological Park; Estados UnidosFil: Patterson, Bruce. Field Museum of National History; Estados UnidosFil: Paviolo, Agustin Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste; ArgentinaFil: Ramalho, Emiliano Esterci. Institute For Conservation of The Neotropical Carnivores; Brasil. Instituto de Desenvolvimento Sustentavel Mamirauá; BrasilFil: Rösner, Sascha. Michigan State University; Estados UnidosFil: Schabo, Dana G.. Michigan State University; Estados UnidosFil: Selva, Nuria. Institute of Nature Conservation of The Polish Academy of Sciences; PoloniaFil: Sergiel, Agnieszka. Institute of Nature Conservation of The Polish Academy of Sciences; PoloniaFil: Xavier da Silva, Marina. Parque Nacional do Iguaçu; BrasilFil: Spiegel, Orr. Universitat Tel Aviv; IsraelFil: Thompson, Peter. University of Maryland; Estados UnidosFil: Ullmann, Wiebke. Universitat Potsdam; AlemaniaFil: Ziḝba, Filip. Tatra National Park; PoloniaFil: Zwijacz Kozica, Tomasz. Tatra National Park; PoloniaFil: Fagan, William F.. University of Maryland; Estados UnidosFil: Mueller, Thomas. Senckenberg Gesellschaft Für Naturforschung; . Goethe Universitat Frankfurt; AlemaniaFil: Calabrese, Justin M.. National Zoological Park; Estados Unidos. University of Maryland; Estados Unido

Mammal responses to global changes in human activity vary by trophic group and landscape

Wildlife must adapt to human presence to survive in the Anthropocene, so it is critical to understand species responses to humans in different contexts. We used camera trapping as a lens to view mammal responses to changes in human activity during the COVID-19 pandemic. Across 163 species sampled in 102 projects around the world, changes in the amount and timing of animal activity varied widely. Under higher human activity, mammals were less active in undeveloped areas but unexpectedly more active in developed areas while exhibiting greater nocturnality. Carnivores were most sensitive, showing the strongest decreases in activity and greatest increases in nocturnality. Wildlife managers must consider how habituation and uneven sensitivity across species may cause fundamental differences in human–wildlife interactions along gradients of human influence.Peer reviewe

Baiting for carnivores might negatively affect capture rates of prey species in camera-trap studies

Surveying and monitoring of elusive animals with naturally low densities and large home ranges, such as many medium- and large-sized mammals, is challenging. Low capture rates can preclude detailed analyses. The use of bait has been used as a strategy to increase carnivore capture rates in many camera-trap surveys. Here, we test the effect of one carnivore bait type (mix of fresh sardine and egg) on the capture rates of carnivores and prey species in a camera-trap survey in the Central Brazilian Amazon. We also test if the quality of records of naturally marked felids for individual identification is enhanced by the use of bait. We found that the bait had no apparent effect on the carnivore capture rates, but it might have repelled some prey species. The number of suitable photos for individual identification of naturally marked felids was greater at baited stations than at unbaited stations, but this did not result in practical advantages for individual identification. We recommend that the use of carnivore bait should be carefully considered at the planning stage of camera-trap studies as it can negatively affect recording of prey species. © 2016 The Zoological Society of Londo

Depredation by jaguars on caimans and importance of reptiles in the diet of jaguar

The jaguar (Panthera onca) is the largest Neotropical felid and in many parts of its range reptiles form a significant but relatively minor component of its diet. However, in the seasonally flooded varzea forests of the Amazon, terrestrial mammals, which form an important component of jaguar diet in other habitats, are largely absent and jaguars switch to alternative prey, including arboreal mammals and reptiles. In the Mamirau Sustainable Development Reserve in the western Brazilian Amazon, we document predation by jaguars on two species of caiman (Caiman crocodilus and Melanosuchus niger), which are abundant in this varzea habitat. The smaller C. crocodilus seems to be particularly vulnerable because of its size and tendency to spend more time on land than the larger M. niger. Jaguars not only kill and eat caiman but are also a significant predator on eggs of both species. We place our findings into the context of jaguar predation on reptiles by reviewing studies of jaguar diet in a variety of biomes. © 2010 Society for the Study of Amphibians and Reptiles

Records of the bush dog (Speothos venaticus) in Central Amazonia, Brazil

The bush dog (Speothos venaticus) is a small Neotropical canid. Although its distribution covers the entire Amazon basin, the occurrence of bush dogs in vast areas of the Amazon remains hypothetical. The records of bush dogs presented in this study reduce a large gap in the known distribution of the species in Central Amazonia and include the 1st documentation of the species from forest seasonally flooded by black water (Igapó). © 2015 American Society of Mammalogists

Avaliação do risco de extinção da onça-pintada Panthera onca (Linnaeus, 1758) no Brasil

Panthera onca ocorre em quase todos os biomas brasileiros, com exceção do Pampa, sendo que 50% da área do país ainda é considerada adequada à ocorrência da espécie. Apesar desta ampla distribuição, o tamanho populacional efetivo estimado é menor do que 10.000 indivíduos. As principais ameaças à espécie são a perda e fragmentação de habitat associadas principalmente à expansão agrícola, mineração, implantação de hidrelétricas, ampliação da malha viária e a eliminação de indivíduos por caça ou retaliação por predação de animais domésticos. A diminuição iminente dos remanescentes florestais, resultante das mudanças efetuadas no Código Florestal Brasileiro, também representa uma ameaça à subpopulação de onça-pintada no Brasil. O declínio populacional da espécie em decorrência de perda de habitat associada ao abate de indivíduos foi estimado em aproximadamente 30% nos últimos 27 anos ou três gerações, e um declínio equivalente pode ser projetado para os próximos 27 anos. Portanto, a espécie é categorizada como Vulnerável pelos critérios A2bcd+3cd+C1. Existe conectividade com as subpopulações dos países vizinhos, porém sem trocas significativas que justifiquem uma alteração na categoria indicada para a avaliação brasileira. Assim, a categoria indicada na avaliação regional não foi alterada. As informações sobre a conservação desta espécie foram analisadas separadamente para cada um dos principais biomas brasileiros. Espera-se, com isto, fundamentar políticas de conservação apropriadas a esta espécie em cada região do país

Ocelot density estimate with standard error (SE) and 95% confidence interval (Lower and Upper) of parameters for spatial capture recapture model fit to camera trapping data from Amanã Reserve.

<p>Data from the three surveys were used to estimate the shared movement parameter σ and encounter rate λ_0. Density is reported in ocelots per 100 km².</p

Ocelot (<i>Leopardus pardalis</i>) Density in Central Amazonia

<div><p>Ocelots (<i>Leopardus pardalis</i>) are presumed to be the most abundant of the wild cats throughout their distribution range and to play an important role in the dynamics of sympatric small-felid populations. However, ocelot ecological information is limited, particularly for the Amazon. We conducted three camera-trap surveys during three consecutive dry seasons to estimate ocelot density in Amanã Reserve, Central Amazonia, Brazil. We implemented a spatial capture-recapture (SCR) model that shared detection parameters among surveys. A total effort of 7020 camera-trap days resulted in 93 independent ocelot records. The estimate of ocelot density in Amanã Reserve (24.84 ± SE 6.27 ocelots per 100 km²) was lower than at other sites in the Amazon and also lower than that expected from a correlation of density with latitude and rainfall. We also discuss the importance of using common parameters for survey scenarios with low recapture rates. This is the first density estimate for ocelots in the Brazilian Amazon, which is an important stronghold for the species.</p></div