AbstractAnimal 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.

AbstractHome 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 dataset of GPS locations from 369 individuals representing 27 species distributed across 5 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 ($\hat{N}\mathrm{area}$) to quantify the information content of each dataset. 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 holdout 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 $\hat{N}\mathrm{area}$. 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 $\hat{N}\mathrm{area}$. While 72% of the 369 empirical datasets had \textgreater1000 total observations, only 4% had an $\hat{N}\mathrm{area}$ \textgreater1000, where 30% had an $\hat{N}\mathrm{area}$ \textless30. In this frequently encountered scenario of small $\hat{N}\mathrm{area}$, AKDE was the only estimator capable of producing an accurate home range estimate on autocorrelated data.

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.

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 dataset of GPS locations from 369 individuals representing 27 species distributed across 5 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 ($\hat{N}\mathrm{area}$) to quantify the information content of each dataset. 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 holdout 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 $\hat{N}\mathrm{area}$. 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 $\hat{N}\mathrm{area}$. While 72% of the 369 empirical datasets had \textgreater1000 total observations, only 4% had an $\hat{N}\mathrm{area}$ \textgreater1000, where 30% had an $\hat{N}\mathrm{area}$ \textless30. In this frequently encountered scenario of small $\hat{N}\mathrm{area}$, AKDE was the only estimator capable of producing an accurate home range estimate on autocorrelated data.

Some primate populations include both trichromatic and dichromatic (red–green colour blind) individuals due to allelic variation at the X-linked opsin locus. This polymorphic trichromacy is well described in day-active New World monkeys. Less is known about colour vision in Malagasy lemurs, but, unlike New World monkeys, only some day-active lemurs are polymorphic, while others are dichromatic. The evolutionary pressures underlying these differences in lemurs are unknown, but aspects of species ecology, including variation in activity pattern, are hypothesized to play a role. Limited data on X-linked opsin variation in lemurs make such hypotheses difficult to evaluate. We provide the first detailed examination of X-linked opsin variation across a lemur clade (Indriidae). We sequenced the X-linked opsin in the most strictly diurnal and largest extant lemur, Indri indri, and nine species of smaller, generally diurnal indriids (Propithecus). Although nocturnal Avahi (sister taxon to Propithecus) lacks a polymorphism, at least eight species of diurnal indriids have two or more X-linked opsin alleles. Four rainforest-living taxa—I. indri and the three largest Propithecus species—have alleles not previously documented in lemurs. Moreover, we identified at least three opsin alleles in Indri with peak spectral sensitivities similar to some New World monkeys.

Implementation of the coalescent model in a Bayesian framework is an emerging strength in genetically based species delimitation studies. By providing an objective measure of species diagnosis, these methods represent a quantitative enhancement to the analysis of multilocus data, and complement more traditional methods based on phenotypic and ecological characteristics. Recognized as two species 20 years ago, mouse lemurs (genus Microcebus) now comprise more than 20 species, largely diagnosed from mtDNA sequence data. With each new species description, enthusiasm has been tempered with scientific scepticism. Here, we present a statistically justified and unbiased Bayesian approach towards mouse lemur species delimitation. We perform validation tests using multilocus sequence data and two methodologies: (i) reverse-jump Markov chain Monte Carlo sampling to assess the likelihood of different models defined a priori by a guide tree, and (ii) a Bayes factor delimitation test that compares different species-tree models without a guide tree. We assess the sensitivity of these methods using randomized individual assignments, which has been used in bpp studies, but not with Bayes factor delimitation tests. Our results validate previously diagnosed taxa, as well as new species hypotheses, resulting in support for three new mouse lemur species. As the challenge of multiple researchers using differing criteria to describe diversity is not unique to Microcebus, the methods used here have significant potential for clarifying diversity in other taxonomic groups. We echo previous studies in advocating that multiple lines of evidence, including use of the coalescent model, should be trusted to delimit new species.

Large-scale monitoring schemes are essential in assessing global mammalian biodiversity, and in this framework leeches have recently been promoted as an indirect source of DNA from terrestrial mammal species. Carrion feeding flies are ubiquitous and can be expected to feed on many vertebrate carcasses. Hence, we tested whether fly-derived DNA analysis may also serve as a novel tool for mammalian diversity surveys. We screened DNA extracted from 201 carrion flies collected in tropical habitats of Côte d’Ivoire and Madagascar for mammal DNA using multiple PCR systems and retrieved DNA sequences from a diverse set of species (22 in Côte d’Ivoire, 4 in Madagascar) exploiting distinct forest strata and displaying a broad range of body sizes. Deep-sequencing of amplicons generated from pools of flies performed equally well as individual sequencing approaches. We conclude that the analysis of fly-derived DNA can be implemented in a very rapid and cost-effective manner and will give a relatively unbiased picture of local mammal diversity. Carrion flies therefore represent an extraordinary and thus far unexploited resource of mammal DNA, which will likely prove useful for future inventories of wild mammal communities.

The systematics and speciation literature is rich with discussion relating to the potential for gene tree/species tree discordance. Numerous mechanisms have been proposed to generate discordance, including differential selection, long-branch attraction, gene duplication, genetic introgression, and/or incomplete lineage sorting. For speciose clades in which divergence has occurred recently and rapidly, recovering the true species tree can be particularly problematic due to incomplete lineage sorting. Unfortunately, the availability of multi-locus or “phylogenomic” data sets does not simply solve the problem, particularly when the data are analyzed with standard concatenation techniques. In our study, we conduct a phylogenetic study for a nearly complete species sample of the dwarf and mouse lemur clade, Cheirogaleidae. Mouse lemurs (genus, Microcebus) have been intensively studied over the past decade for reasons relating to their high level of cryptic species diversity, and although there has been emerging consensus regarding the evolutionary diversity contained within the genus, there is no agreement as to the inter-specific relationships within the group. We attempt to resolve cheirogaleid phylogeny, focusing especially on the mouse lemurs, by employing a large multi-locus data set. We compare the results of Bayesian concordance methods with those of standard gene concatenation, finding that though concatenation yields the strongest results as measured by statistical support, these results are found to be highly misleading. By employing an approach where individual alleles are treated as OTUs, we show that phylogenetic results are substantially influenced by the selection of alleles in the concatenation process.

In mammals with female philopatry, co-resident females inevitably compete with each other for resources or reproductive opportunities, thereby reducing the kin-selected benefits of altruism towards relatives. These counteracting forces of cooperation and competition among kin should be particularly pronounced in plurally breeding species with limited alternative breeding opportunities outside the natal group. However, little is still known about the costs of reproductive competition on females’ fitness and the victims’ potential counter-strategies. Here we summarize long-term behavioral, demographic and genetic data collected on a plurally breeding primate from Madagascar to illuminate mechanisms and effects of female reproductive competition, focusing on forcible eviction and potential reproductive restraint. The main results of our study indicate that females in groups of redfronted lemurs (Eulemur rufifrons) above a critical size suffer from competition from their close relatives: females in larger groups face an increased probability of not giving birth as well as a higher probability of being evicted, especially during the annual mating and birth seasons. Eviction is not predicted by the number of adult females, the number of close female relatives, female age or inter-annual variation in rainfall but only by total group size. Thus, eviction in this species is clearly linked with reproductive competition, it cannot be forestalled by reproductive restraint or having many relatives in the group, and it occurs in the absence of a clear dominance hierarchy. Our study therefore also underscores the notion that potential inclusive fitness benefits from living with relatives may have been generally over-rated and should not be taken for granted.