Brian D. Gerber

Activity patterns of carnivores in the rain forests of Madagascar: implications for species coexistence.

Abstract Temporal partitioning of activity among sympatric species can be an important mechanism for species coexistence. Further, if exotic and native species overlap temporally, there is potential for direct competition and antagonism, which may lead to native species extirpation. We 1st assessed if ecologically similar native carnivores of Madagascar demonstrated activity pattern overlap and then explored whether overlap in activity might lead to negative impacts of exotic carnivores on native carnivores. We used photographic sampling to quantify the temporal activity patterns of carnivores at 4 study sites. The activity of the 2 smaller-bodied native species, Galidia elegans and Galidictis fasciata, overlapped minimally; these 2 carnivores share a similar generalist diet, which may drive their divergent temporal activity. In contrast, the medium-sized native species, Fossa fossana and Eupleres goudotii, were both highly nocturnal; these 2 species appear segregated in their diets. The largest native carnivore, Cryptoprocta ferox, selectively used crepuscular hours, but overall was cathemeral; it was notably absent or basically so at sites where dogs were most abundant and active throughout the diel cycle. We found G. elegans to shift from preferred activity periods in the presence of dogs and the exotic Viverricula indica. Our results suggest that the presence and activity of exotic carnivores can negatively impact native carnivores in fragmented rain forests.

An assessment of carnivore relative abundance and density in the eastern rainforests of Madagascar using remotely-triggered camera traps.

Despite major efforts to understand and conserve Madagascars unique biodiversity, relatively little is known about the islands carnivore populations. We therefore deployed 43 camera-trap stations in Ranomafana National Park, Madagascar during June-August 2007 to evaluate the efficacy of this method for studying Malagasy carnivores and to estimate the relative abundance and density of carnivores in the eastern rainforest. A total of 755 camera- trap nights provided 1,605 photographs of four endemic carnivore species (fossa Cryptoprocta ferox, Malagasy civet Fossa fossana, ring-tailed mongoose Galidia elegans and broad-striped mongoose Galidictus fasciata), the exotic Indian civet Viverricula indica and the domestic dog Canis familiaris. We identified 38 individual F. fossana and 10 individual C. ferox. We estimated density using both capture- recapture analyses, with a buffer of full mean-maximum- distance-moved, and a spatially-explicit maximum-likelihood method (F. fossana :3 .03 and 2.23 km -2 , respectively; C. ferox: 0.15 and 0.17 km -2 , respectively). Our estimated densities of C. ferox in rainforest are lower than published estimates for conspecifics in the western dry forests. Within Ranoma- fana National Park species richness of native carnivores did not vary among trail systems located in secondary, selec- tively-logged and undisturbed forest. These results provide the first assessment of carnivore population parameters using camera-traps in the eastern rainforests of Madagascar.

The impact of forest logging and fragmentation on carnivore species composition, density and occupancy in Madagascar's rainforests

Forest carnivores are threatened globally by logging and forest fragmentation yet we know relatively little about how such change affects predator populations. This is especially true in Madagascar, where carnivores have not been extensively studied. To understand better the effects of logging and fragmentation on Malagasy carnivores we evaluated species composition, density of fossa Cryptoprocta ferox and Malagasy civet Fossa fossana , and carnivore occupancy in central-eastern Madagascar. We photographically-sampled carnivores in two contiguous (primary and selectively-logged) and two fragmented rainforests (fragments 15 km from intact forest). Species composition varied, with more native carnivores in the contiguous than fragmented rainforests. F. fossana was absent from fragmented rainforests and at a lower density in selectively-logged than in primary rainforest (mean 1.38±SE 0.22 and 3.19±SE 0.55 individuals km −2 , respectively). C. ferox was detected in fragments −2 , respectively) but was absent in fragments >15 km from forest. We identified only two protected areas in Madagascar that may maintain >300 adult C. ferox . Occupancy of broad-striped mongoose Galidictis fasciata was positively related to fragment size whereas occupancy of ring-tailed mongoose Galidia elegans elegans was negatively associated with increasing exotic wild cat ( Felis spp.) activity at a camera site. Degraded rainforest fragments are difficult environments for Malagasy carnivores to occupy; there is a need to prioritize the reconnection and maintenance of contiguous forest tracts.

Spatial capture–recapture model performance with known small‐mammal densities

Abundance and density of wild animals are important ecological metrics. However, estimating either is fraught with challenges; spatial capture-recapture (SCR) models are a relatively new class of models that attempt to ameliorate common challenges, providing a statistically coherent framework to estimate abundance and density. SCR models are increasingly being used in ecological and conservation studies of mammals worldwide, but have received little testing with empirical field data. We use data collected via a web and grid sampling design to evaluate the basic SCR model where small-mammal abundance (N) and density (D) are known (via exhaustive sampling). We fit the basic SCR model with and without a behavioral effect to 11 small-mammal populations for each sampling design using a Bayesian and likelihood SCR modeling approach. We compare SCR and ad hoc density estimators using frequentist performance measures. We found Bayesian and likelihood SCR estimates of density (D) and abundance (N) to be similar. We also found SCR models to have moderately poor frequentist coverage of D and N (45-73%), high deviation from truth (i.e., accuracy; D, 17-29%; N, 16-29%), and consistent negative bias across inferential paradigms, sampling designs, and models. With the trapping grid data, the basic SCR model generally performed more poorly than the best ad hoc estimator (behavior CR super-population estimate divided by the full mean maximum distance moved estimate of the effective trapping area), whereas with the trapping web data, the best-performing SCR model (null) was comparable to the best distance model. Relatively poor frequentist SCR coverage resulted from higher precision (SCR coefficients of variation [CVs] < ad hoc CVs); however D and D were fairly well correlated (r2 range of 0.77-0.96). SCRs negative relative bias (i.e., average underestimation of the true density) suggests additional heterogeneity in detection and/or that small mammals maintained asymmetric home ranges. We suggest caution in the use of the basic SCR model when trapping animals in a sampling grid and more generally when small sample sizes necessitate the spatial scale parameter (σ) apply to all individuals. When possible, researchers should consider variation in detection and incorporate individual biological and/or ecological variation at the trap level when modeling σ.

Recommended survey designs for occupancy modelling using motion-activated cameras: insights from empirical wildlife data

Motion-activated cameras are a versatile tool that wildlife biologists can use for sampling wild animal populations to estimate species occurrence. Occupancy modelling provides a flexible framework for the analysis of these data; explicitly recognizing that given a species occupies an area the probability of detecting it is often less than one. Despite the number of studies using camera data in an occupancy framework, there is only limited guidance from the scientific literature about survey design trade-offs when using motion-activated cameras. A fuller understanding of these trade-offs will allow researchers to maximise available resources and determine whether the objectives of a monitoring program or research study are achievable. We use an empirical dataset collected from 40 cameras deployed across 160 km2 of the Western Slope of Colorado, USA to explore how survey effort (number of cameras deployed and the length of sampling period) affects the accuracy and precision (i.e., error) of the occupancy estimate for ten mammal and three virtual species. We do this using a simulation approach where species occupancy and detection parameters were informed by empirical data from motion-activated cameras. A total of 54 survey designs were considered by varying combinations of sites (10–120 cameras) and occasions (20–120 survey days). Our findings demonstrate that increasing total sampling effort generally decreases error associated with the occupancy estimate, but changing the number of sites or sampling duration can have very different results, depending on whether a species is spatially common or rare (occupancy = ψ) and easy or hard to detect when available (detection probability = p). For rare species with a low probability of detection (i.e., raccoon and spotted skunk) the required survey effort includes maximizing the number of sites and the number of survey days, often to a level that may be logistically unrealistic for many studies. For common species with low detection (i.e., bobcat and coyote) the most efficient sampling approach was to increase the number of occasions (survey days). However, for common species that are moderately detectable (i.e., cottontail rabbit and mule deer), occupancy could reliably be estimated with comparatively low numbers of cameras over a short sampling period. We provide general guidelines for reliably estimating occupancy across a range of terrestrial species (rare to common: ψ = 0.175–0.970, and low to moderate detectability: p = 0.003–0.200) using motion-activated cameras. Wildlife researchers/managers with limited knowledge of the relative abundance and likelihood of detection of a particular species can apply these guidelines regardless of location. We emphasize the importance of prior biological knowledge, defined objectives and detailed planning (e.g., simulating different study-design scenarios) for designing effective monitoring programs and research studies.

Teeth, Sex, and Testosterone: Aging in the World's Smallest Primate

Mouse lemurs (Microcebus spp.) are an exciting new primate model for understanding human aging and disease. In captivity, Microcebus murinus develops human-like ailments of old age after five years (e.g., neurodegeneration analogous to Alzheimers disease) but can live beyond 12 years. It is believed that wild Microcebus follow a similar pattern of senescence observed in captive animals, but that predation limits their lifespan to four years, thus preventing observance of these diseases in the wild. Testing whether this assumption is true is informative about both Microcebus natural history and environmental influences on senescence, leading to interpretation of findings for models of human aging. Additionally, the study of Microcebus longevity provides an opportunity to better understand mechanisms of sex-biased longevity. Longevity is often shorter in males of species with high male-male competition, such as Microcebus, but mouse lemurs are sexually monomorphic, suggesting similar lifespans. We collected individual-based observations of wild brown mouse lemurs (Microcebus rufus) from 2003–2010 to investigate sex-differences in survival and longevity. Fecal testosterone was measured as a potential mechanism of sex-based differences in survival. We used a combination of high-resolution tooth wear techniques, mark-recapture, and hormone enzyme immunoassays. We found no dental or physical signs of senescence in M. rufus as old as eight years (N = 189, ages 1–8, mean = 2.59±1.63 SE), three years older than captive, senescent congeners (M. murinus). Unlike other polygynandrous vertebrates, we found no sex difference in age-dependent survival, nor sex or age differences in testosterone levels. While elevated male testosterone levels have been implicated in shorter lifespans in several species, this is one of the first studies to show equivalent testosterone levels accompanying equivalent lifespans. Future research on captive aged individuals can determine if senescence is partially a condition of their captive environment, and studies controlling for various environmental factors will further our understanding of senescence.

Optimal population prediction of sandhill crane recruitment based on climate‐mediated habitat limitations

1. Prediction is fundamental to scientific enquiry and application; however, ecologists tend to favour explanatory modelling. We discuss a predictive modelling framework to evaluate ecological hypotheses and to explore novel/unobserved environmental scenarios to assist conservation and management decision-makers. We apply this framework to develop an optimal predictive model for juvenile (<1 year old) sandhill crane Grus canadensis recruitment of the Rocky Mountain Population (RMP). We consider spatial climate predictors motivated by hypotheses of how drought across multiple time-scales and spring/summer weather affects recruitment. 2. Our predictive modelling framework focuses on developing a single model that includes all relevant predictor variables, regardless of collinearity. This model is then optimized for prediction by controlling model complexity using a data-driven approach that marginalizes or removes irrelevant predictors from the model. Specifically, we highlight two approaches of statistical regularization, Bayesian least absolute shrinkage and selection operator (LASSO) and ridge regression. 3. Our optimal predictive Bayesian LASSO and ridge regression models were similar and on average 37% superior in predictive accuracy to an explanatory modelling approach. Our predictive models confirmed a priori hypotheses that drought and cold summers negatively affect juvenile recruitment in the RMP. The effects of long-term drought can be alleviated by short-term wet spring-summer months; however, the alleviation of long-term drought has a much greater positive effect on juvenile recruitment. The number of freezing days and snowpack during the summer months can also negatively affect recruitment, while spring snowpack has a positive effect. 4. Breeding habitat, mediated through climate, is a limiting factor on population growth of sandhill cranes in the RMP, which could become more limiting with a changing climate (i.e. increased drought). These effects are likely not unique to cranes. The alteration of hydrological patterns and water levels by drought may impact many migratory, wetland nesting birds in the Rocky Mountains and beyond. 5. Generalizable predictive models (trained by out-of-sample fit and based on ecological hypotheses) are needed by conservation and management decision-makers. Statistical regularization improves predictions and provides a general framework for fitting models with a large number of predictors, even those with collinearity, to simultaneously identify an optimal predictive model while conducting rigorous Bayesian model selection. Our framework is important for understanding population dynamics under a changing climate and has direct applications for making harvest and habitat management decisions.

Estimating the abundance of rare and elusive carnivores from photographic-sampling data when the population size is very small

Conservation and management agencies require accurate and precise estimates of abundance when considering the status of a species and the need for directed actions. Due to the proliferation of remote sampling cameras, there has been an increase in capture–recapture studies that estimate the abundance of rare and/or elusive species using closed capture–recapture estimators (C–R). However, data from these studies often do not meet necessary statistical assumptions. Common attributes of these data are (1) infrequent detections, (2) a small number of individuals detected, (3) long survey durations, and (4) variability in detection among individuals. We believe there is a need for guidance when analyzing this type of sparse data. We highlight statistical limitations of closed C–R estimators when data are sparse and suggest an alternative approach over the conventional use of the Jackknife estimator. Our approach aims to maximize the probability individuals are detected at least once over the entire sampling period, thus making the modeling of variability in the detection process irrelevant, estimating abundance accurately and precisely. We use simulations to demonstrate when using the unconditional-likelihood M0 (constant detection probability) closed C–R estimator with profile-likelihood confidence intervals provides reliable results even when detection varies by individual. If each individual in the population is detected on average of at least 2.5 times, abundance estimates are accurate and precise. When studies sample the same species at multiple areas or at the same area over time, we suggest sharing detection information across datasets to increase precision when estimating abundance. The approach suggested here should be useful for monitoring small populations of species that are difficult to detect.

Primates and Cameras

Field-based primate studies often make population inferences using count-based indices (e.g., individuals/plot) or distance sampling; the first does not account for the probability of detection and thus can be biased, while the second requires large sample sizes to obtain precise estimates, which is difficult for many primate studies. We discuss photographic sampling and occupancy modeling to correct for imperfect detection when estimating system states and dynamics at the landscape level, specifically in relation to primate ecology. We highlight the flexibility of the occupancy framework and its many applications to studying low-density primate populations or species that are difficult to detect. We discuss relevant sampling and estimation procedures with special attention to data collection via photographic sampling. To provide tangible meaning to terminology and clarify subtleties, we use illustrative examples. Photographic sampling can have many advantages over observer-based sampling, especially when studying rare or elusive species. Combining photographic sampling with an occupancy framework allows inference to larger scales than is common in primate studies, addresses uncertainty due to the observation process, and allows researchers to examine questions of how landscape-level anthropogenic changes affect primate distributions.

A biogeographical perspective on the variation in mouse lemur density throughout Madagascar

Madagascar is home to the smallest primates in the world, the mouse lemurs (Microcebus species). Twenty-four species of mouse lemur are currently recognised and are found in variable ecosystems, from dry forests and spiny deserts to humid forests. Due to their widespread distribution and the large number of sympatric species, mouse lemurs can be used as a model to understand the linkages among species richness, population density, and habitat. As all lemurs are threatened by habitat loss and fragmentation, this information can also be used to inform conservation management. We hypothesise that on an island-wide scale, we will find higher population densities in western dry forests than in eastern humid forests because the western dry forests exhibit lower species richness, more sympatric habitat use, and lower resource stability than the eastern humid forests. We conducted a literature review of population density estimates of known mouse lemur species, and used those data to conduct a meta-analysis and estimate overall average population density by geographic region. Our findings suggest that mouse lemur species living in western dry forest generally exhibit higher densities than those in eastern humid forests. This may be partly explained by higher habitat fragmentation in western dry forests, where species co-occur, but is likely to be a function of the magnitude and variability in seasonally available resources in each forest type. Higher seasonality results in less constant food availability and lower levels of environmental predictability, fostering species capable of coping with environmental change and maintaining high densities throughout periods of resource paucity. Our study highlights the importance of conducting Microcebus population density research that adheres to standardised methodological approaches. We point to the need for population density estimates for several species for which data are lacking. Such knowledge is important to assess the conservation status of these species, but also to enhance our ability to identify the macro-biogeographical and local ecological drivers of interspecific and intraspecific variability in population density.