Activity patterns of tayra (Eira barbara) across their distribution

Species' activity patterns are driven by the need to meet basic requirements of food, social interactions, movement, and rest, but often are influenced by a variety of biotic and abiotic factors. We used camera-trap data to describe and compare the activity patterns of the relatively poorly studied tayra (Eira barbara) across 10 populations distributed from the south of Mexico to the north of Argentina, and attempted to identify biotic or abiotic factors that may be associated with variation in level of diurnality. In a subset of sites we also aimed to document potential seasonal variation in activity. We used a kernel density estimator based on the time of independent photographic events to calculate the proportion of diurnal, crepuscular, and nocturnal activity of each population. Tayras were mostly active during diurnal periods (79.31%, 759 records), with a lower proportion of crepuscular activity (18.07%, 173 records) yet we documented some variation in patterns across the 10 study areas (activity overlap coefficient varied from Δ4 = 0.64 to Δ1 = 0.95). In northern localities, activity peaked twice during the day (bimodal) with most activity ocurring in the morning, whereas closer to the geographical equator, activity was constant (unimodal) throughout the day, peaking at midday: activity either was unimodal or bimodal in southern localities. Despite investigating multiple potential abiotic and biotic predictors, only latitude was associated with variation in the proportion of diurnal activity by tayras across its range, with increased diurnal activity closer to the equator. Seasonal comparisons in activity showed a tendency to reduce diurnality in dry versus rainy seasons, but the pattern was not consistently significant. This is the most comprehensive description of tayra activity patterns to date, and lends novel insight into the potential flexibility of the species to adapt to local conditions.Fil: Villafañe Trujillo, Álvaro José. Universidad Autonoma de Queretaro.; MéxicoFil: Kolowski, Joseph M.. Instituto de Pesquisas Ecológicas; BrasilFil: Cove, Michael V.. University of Belize; BeliceFil: Medici, Emilia Patricia. Instituto de Pesquisas Ecológicas; BrasilFil: Harmsen, Bart J.. University of Belize; BeliceFil: Foster, Rebbeca J.. University of Belize; BeliceFil: Hidalgo Mihart, Mircea G.. Universidad Juárez Autónoma de Tabasco,; MéxicoFil: Espinosa, Santiago. Universidad Autónoma de San Luis Potosí; MéxicoFil: Ríos Alvear, Gorky. Universidad de Porto; PortugalFil: Reyes Puig, Carolina. Universidad de Porto; PortugalFil: Reyes Puig, Juan Pablo. Universidad de Porto; PortugalFil: Da Silva, Marina Xavier. Universidad Central del Ecuador; EcuadorFil: Paviolo, Agustin Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Universidad Nacional de Misiones. Instituto de Biología Subtropical; ArgentinaFil: Cruz, Paula Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Universidad Nacional de Misiones. Instituto de Biología Subtropical; ArgentinaFil: López González, Carlos Alberto. Universidad Autonoma de Queretaro.; Méxic

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

Evaluating expert-based habitat suitability information of terrestrial mammals with GPS-tracking data

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

Moving in the anthropocene: global reductions in terrestrial mammalian movements

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

Assessing the viability of lowland tapir populations in a fragmented landscape

This thesis aimed to assess the ecological factors that determine the long-term persistence and viability of animal populations across severely fragmented landscapes. The lowland tapir, Tapirus terrestris, and the fragmented Atlantic Forests of the Interior of the Pontal do Paranapanema Region, Sao Paulo State, Brazil, were used as a model to illustrate this assessment. Both empirical and modelling approaches were used. The empirical approach focused on aspects of tapir spatial ecology, intra-specific interactions, spatial and temporal interactions between tapirs and the landscape, as well as estimates of tapir abundance in Morro do Diabo State Park (370 km2) and seven smaller forest fragments (4-18 km2) where tapirs were present. The modelling approach consisted of a Population Viability Analysis (PVA) using the software VORTEX. Spatial ecology, intra-specific interactions, and interactions between tapirs and the landscape were estimated by radio-telemetry. Population sizes were derived from tapir densities obtained by radio-telemetry, nocturnal line-transect sampling, and Footprint Identification Technique (FIT). Lowland tapirs in Morro do Diabo had very large home ranges (4.7 km2) when compared to other sites, particularly contiguous habitats. Tapir home ranges had very complex internal structures, including multiple core areas of use, which comprised a very small proportion of the home range (50% core area, 17% of the home range; 25% core area, 6% of the home range). Little seasonal variation in size and location of home ranges and core areas of use were observed. These patterns were consistent for both sexes and different age classes. Telemetry results have shown that a minimum of 20 months of data collection and approximately 300 locations are necessary to determine home range size for adult lowland tapirs. Tapirs exhibited extensive home range overlap (30%), as well as overlap of core areas of use (20%). No evidence of spatial territoriality was noted. Tapirs incorporated portions of all available habitat types within their home ranges and core areas of use, but significantly selected riparian habitats, where they performed most of their main activities, particularly foraging. Tapirs avoided areas of agricultural and pastoral land, as well as secondary growth forests. It was estimated that Morro do Diabo hosts a population of 130 tapirs and, altogether, the seven forest fragments host 22 additional individuals. Tapirs have low population growth rates and so are very susceptible to threats such as road-kill, infectious disease, and fire, particularly in the small forest fragments. Results from the PVA model projected that the tapir population in Morro do Diabo has zero probability of extinction and is likely to persist over the next 100 years. However, the population is not large enough to maintain 95% of genetic diversity over the long-term. A Minimum Viable Population of 200 tapirs would be required to ensure long-term viability. The model showed that, without dispersal of tapirs from Morro do Diabo, tapirs in the small fragments will go extinct over the next 100 years. However, this study showed that tapirs in the Pontal do Paranapanema Region moved fairly easily through areas of non-natural habitat in between patches of forest, indicating a certain level of landscape functional connectivity. This provided evidence of a tapir metapopulation scenario, which proved to be a determinant factor for the persistence and viability of lowland tapirs in the Atlantic Forest of the Interior. Overall, the long-term persistence and viability of animal populations across severely fragmented landscapes appears to be dependent on the maintenance and full protection of complex landscape networks. These networks must include some large patches of habitat that can host larger animal populations and function as source areas for dispersal of individuals to smaller populations in sink habitats. Patches of forest comprising these networks must incorporate required habitat types where animals can find the resources they need in order to survive and persist. Most essentially, there must be an appropriate level of landscape connectivity, either structurally or functionally, in order to facilitate biological fluxes between patches and promote the maintenance of a demographically and genetically healthy metapopulation

Assessing the viability of lowland tapir populations in a fragmented landscape

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Data from: Overcoming the challenge of small effective sample sizes in home-range estimation

Technological advances have steadily increased the detail of animal tracking datasets, yet fundamental data limitations exist for many species that cause substantial biases in home‐range estimation. Specifically, the effective sample size of a range estimate is proportional to the number of observed range crossings, not the number of sampled locations. Currently, the most accurate home‐range estimators condition on an autocorrelation model, for which the standard estimation frame‐works are based on likelihood functions, even though these methods are known to underestimate variance—and therefore ranging area—when effective sample sizes are small. Residual maximum likelihood (REML) is a widely used method for reducing bias in maximum‐likelihood (ML) variance estimation at small sample sizes. Unfortunately, we find that REML is too unstable for practical application to continuous‐time movement models. When the effective sample size N is decreased to N ≤ urn:x-wiley:2041210X:media:mee313270:mee313270-math-0001(10), which is common in tracking applications, REML undergoes a sudden divergence in variance estimation. To avoid this issue, while retaining REML’s first‐order bias correction, we derive a family of estimators that leverage REML to make a perturbative correction to ML. We also derive AIC values for REML and our estimators, including cases where model structures differ, which is not generally understood to be possible. Using both simulated data and GPS data from lowland tapir (Tapirus terrestris), we show how our perturbative estimators are more accurate than traditional ML and REML methods. Specifically, when urn:x-wiley:2041210X:media:mee313270:mee313270-math-0002(5) home‐range crossings are observed, REML is unreliable by orders of magnitude, ML home ranges are ~30% underestimated, and our perturbative estimators yield home ranges that are only ~10% underestimated. A parametric bootstrap can then reduce the ML and perturbative home‐range underestimation to ~10% and ~3%, respectively. Home‐range estimation is one of the primary reasons for collecting animal tracking data, and small effective sample sizes are a more common problem than is currently realized. The methods introduced here allow for more accurate movement‐model and home‐range estimation at small effective sample sizes, and thus fill an important role for animal movement analysis. Given REML’s widespread use, our methods may also be useful in other contexts where effective sample sizes are small

Avaliação do risco de extinção do cateto Pecari tajacu Linnaeus, 1758, no Brasil.

O estado de conservação do cateto, Pecari tajacu (Linnaeus, 1758) foi avaliado de acordo com os critérios da IUCN (2001), com base nos dados disponíveis até 2010. Síntese do processo de avaliação pode ser encontrada em Peres et al. (2011) e em Beisiegel et al. (2012). No Brasil como um todo, a espécie foi considerada Menos preocupante (Least concern – LC). Justificativa – Os catetos, Pecari tajacu, como outras espécies com uma ampla distribuição geográfica, sofrem diferentes impactos e estão sob diferentes graus de ameaça ao longo de sua distribuição no território brasileiro. Avaliar estas espécies como unidades para todo o país pode resultar em excesso de otimismo em relação a seu estado de conservação, baseado em grandes populações remanescentes nos biomas ainda menos degradados. Estas avaliações podem, por um lado, impedir que políticas específicas sejam adotadas para estas espécies em ecossistemas em que as mesmas despertam alarme quanto às suas condições de conservação e, por outro lado, mascarar a possibilidade de que as populações ainda saudáveis não estão livres de sofrer o mesmo destino daquelas em ambientes mais impactados, dada a intensificação das atuais pressões sobre biomas ainda bastante conservados, como o Pantanal e a Amazônia. Desta forma, as informações sobre a conservação desta espécie foram analisadas separadamente para cada um dos principais biomas brasileiros, e uma avaliação regional do estado de conservação (IUCN 2003) foi feita para cada um deles. Espera-se, com isto, fundamentar políticas de conservação apropriadas a esta espécie em cada região do país (ver Desbiez 2010, para uma aplicação prévia da mesma metodologia). São também apresentados dados populacionais e de distribuição geográfica, bem como hábitos e características ecológicas que fundamentam ou complementam a presente análise

Avaliação do risco de extinção do queixada Tayassu pecari Link, 1795, no Brasil.

O estado de conservação do queixada, Tayassu pecari (Link, 1795), foi avaliado de acordo com os critérios da IUCN (2001), com base nos dados disponíveis até 2010. Síntese do processo de avaliação pode ser encontrada em Peres et al. (2011) e em Beisiegel et al. (2012). 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. Os queixadas, como outras espécies com ampla distribuição geográfica, sofrem diferentes impactos e estão sob diferentes graus de ameaça ao longo de sua distribuição no território brasileiro. Avaliar estas espécies como unidades para todo o país pode resultar em excesso de otimismo em relação a seu estado de conservação, baseado em grandes populações remanescentes nos biomas ainda menos degradados. Estas avaliações podem, por um lado, impedir que políticas específicas sejam adotadas para estas espécies em ecossistemas em que as mesmas despertam alarme quanto às suas condições de conservação e, por outro lado, mascarar a possibilidade de que as populações ainda saudáveis não estão livres de sofrer o mesmo destino daquelas em ambientes mais impactados, dada a intensificação das atuais pressões sobre biomas ainda bastante conservados, como o Pantanal e a Amazônia