Multispecies hierarchical modeling reveals variable responses of African carnivores to management alternatives

A multispecies hierarchical model to integrate count and distance-sampling data

Integrated community models-an emerging framework in which multiple data sources for multiple species are analyzed simultaneously-offer opportunities to expand inferences beyond the single-species and single-data-source approaches common in ecology. We developed a novel integrated community model that combines distance sampling and single-visit count data; within the model, information is shared among data sources (via a joint likelihood) and species (via a random-effects structure) to estimate abundance patterns across a community. Parameters relating to abundance are shared between data sources, and the model can specify either shared or separate observation processes for each data source. Simulations demonstrated that the model provided unbiased estimates of abundance and detection parameters even when detection probabilities varied between the data types. The integrated community model also provided more accurate and more precise parameter estimates than alternative single-species and single-data-source models in many instances. We applied the model to a community of 11 herbivore species in the Masai Mara National Reserve, Kenya, and found considerable interspecific variation in response to local wildlife management practices: Five species showed higher abundances in a region with passive conservation enforcement (median across species: 4.5× higher), three species showed higher abundances in a region with active conservation enforcement (median: 3.9× higher), and the remaining three species showed no abundance differences between the two regions. Furthermore, the community average of abundance was slightly higher in the region with active conservation enforcement but not definitively so (posterior mean: higher by 0.20 animals; 95% credible interval: 1.43 fewer animals, 1.86 more animals). Our integrated community modeling framework has the potential to expand the scope of inference over space, time, and levels of biological organization, but practitioners should carefully evaluate whether model assumptions are met in their systems and whether data integration is valuable for their applications.

Integrated community models: A framework combining multispecies data sources to estimate the status, trends and dynamics of biodiversity

Data deficiencies among rare or cryptic species preclude assessment of community-level processes using many existing approaches, limiting our understanding of the trends and stressors for large numbers of species. Yet evaluating the dynamics of whole communities, not just common or charismatic species, is critical to understanding and the responses of biodiversity to ongoing environmental pressures. A recent surge in both public science and government-funded data collection efforts has led to a wealth of biodiversity data. However, these data collection programmes use a wide range of sampling protocols (from unstructured, opportunistic observations of wildlife to well-structured, design-based programmes) and record information at a variety of spatiotemporal scales. As a result, available biodiversity data vary substantially in quantity and information content, which must be carefully reconciled for meaningful ecological analysis. Hierarchical modelling, including single-species integrated models and hierarchical community models, has improved our ability to assess and predict biodiversity trends and processes. Here, we highlight the emerging 'integrated community modelling' framework that combines both data integration and community modelling to improve inferences on species- and community-level dynamics. We illustrate the framework with a series of worked examples. Our three case studies demonstrate how integrated community models can be used to extend the geographic scope when evaluating species distributions and community-level richness patterns; discern population and community trends over time; and estimate demographic rates and population growth for communities of sympatric species. We implemented these worked examples using multiple software methods through the R platform via packages with formula-based interfaces and through development of custom code in JAGS, NIMBLE and Stan. Integrated community models provide an exciting approach to model biological and observational processes for multiple species using multiple data types and sources simultaneously, thus accounting for uncertainty and sampling error within a unified framework. By leveraging the combined benefits of both data integration and community modelling, integrated community models can produce valuable information about both common and rare species as well as community-level dynamics, allowing for holistic evaluation of the effects of global change on biodiversity.

An environmental habitat gradient and within-habitat segregation enable co-existence of ecologically similar bird species

Niche theory predicts that ecologically similar species can coexist through multidimensional niche partitioning. However, owing to the challenges of accounting for both abiotic and biotic processes in ecological niche modelling, the underlying mechanisms that facilitate coexistence of competing species are poorly understood. In this study, we evaluated potential mechanisms underlying the coexistence of ecologically similar bird species in a biodiversity-rich transboundary montane forest in east-central Africa by computing niche overlap indices along an environmental elevation gradient, diet, forest strata, activity patterns and within-habitat segregation across horizontal space. We found strong support for abiotic environmental habitat niche partitioning, with 55% of species pairs having separate elevation niches. For the remaining species pairs that exhibited similar elevation niches, we found that within-habitat segregation across horizontal space and to a lesser extent vertical forest strata provided the most likely mechanisms of species coexistence. Coexistence of ecologically similar species within a highly diverse montane forest was determined primarily by abiotic factors (e.g. environmental elevation gradient) that characterize the Grinnellian niche and secondarily by biotic factors (e.g. vertical and horizontal segregation within habitats) that describe the Eltonian niche. Thus, partitioning across multiple levels of spatial organization is a key mechanism of coexistence in diverse communities.

Quantifying the conservation status and abundance trends of wildlife communities with detection-nondetection data

Effective conservation requires understanding species' abundance patterns and demographic rates across space and time. Ideally, such knowledge should be available for whole communities because variation in species' dynamics can elucidate factors leading to biodiversity losses. However, collecting data to simultaneously estimate abundance and demographic rates of communities of species is often prohibitively time intensive and expensive. We developed a multispecies dynamic N-occupancy model to estimate unbiased, community-wide relative abundance and demographic rates. In this model, detection-nondetection data (e.g., repeated presence-absence surveys) are used to estimate species- and community-level parameters and the effects of environmental factors. To validate our model, we conducted a simulation study to determine how and when such an approach can be valuable and found that our multispecies model outperformed comparable single-species models in estimating abundance and demographic rates in many cases. Using data from a network of camera traps across tropical equatorial Africa, we then used our model to evaluate the statuses and trends of a forest-dwelling antelope community. We estimated relative abundance, rates of recruitment (i.e., reproduction and immigration), and apparent survival probabilities for each species' local population. The antelope community was fairly stable (although 17% of populations [species-park combinations] declined over the study period). Variation in apparent survival was linked more closely to differences among national parks than to individual species' life histories. The multispecies dynamic N-occupancy model requires only detection-nondetection data to evaluate the population dynamics of multiple sympatric species and can thus be a valuable tool for examining the reasons behind recent biodiversity loss.

Data-integration of opportunistic species observations into hierarchical modeling frameworks improves spatial predictions for urban red squirrels

The prevailing trend of increasing urbanization and habitat fragmentation makes knowledge of species’ habitat requirements and distribution a crucial factor in conservation and urban planning. Species distribution models (SDMs) offer powerful toolboxes for discriminating the underlying environmental factors driving habitat suitability. Nevertheless, challenges in SDMs emerge if multiple data sets - often sampled with different intention and therefore sampling scheme – can complement each other and increase predictive accuracy. Here, we investigate the potential of using recent data integration techniques to model potential habitat and movement corridors for Eurasian red squirrels (Sciurus vulgaris), in an urban area. We constructed hierarchical models integrating data sets of different quality stemming from unstructured on one side and semi-structured wildlife observation campaigns on the other side in a combined likelihood approach and compared the results to modeling techniques based on only one data source - wherein all models were fit with the same selection of environmental variables. Our study highlights the increasing importance of considering multiple data sets for SDMs to enhance their predictive performance. We finally used Circuitscape (version 4.0.5) on the most robust SDM to delineate suitable movement corridors for red squirrels as a basis for planning road mortality mitigation measures. Our results indicate that even though red squirrels are common, urban habitats are rather small and partially lack connectivity along natural connectivity corridors in Berlin. Thus, additional fragmentation could bring the species closer to its limit to persist in urban environments, where our results can act as a template for conservation and management implications.

Trends in bird abundance differ among protected forests but not bird guilds

Improved monitoring and associated inferential tools to efficiently identify declining bird populations, particularly of rare or sparsely distributed species, is key to informed conservation and management across large spatiotemporal regions. We assess abundance trends for 106 bird species in a network of eight forested national parks located within the northeast United States from 2006 to 2019 using a novel hierarchical model. We develop a multispecies, multiregion, removal-sampling model that shares information across species and parks to enable inference on rare species and sparsely sampled parks and to evaluate the effects of local forest structure. Trends in bird abundance over time varied widely across parks, but species showed similar trends within parks. Three parks (Acadia National Park and Marsh-Billings-Rockefeller and Morristown National Historical Parks [NHP]) decreased in bird abundance across all species, while three parks (Saratoga NHP and Roosevelt-Vanderbilt and Weir-Farm National Historic Sites) increased in abundance. Bird abundance peaked at medium levels of basal area and high levels of percent forest and forest regeneration, with percent forest having the largest effect. Variation in these effects across parks could be a result of differences in forest structural stage and diversity. By sharing information across both communities and parks, our novel hierarchical model enables uncertainty-quantified estimates of abundance across multiple geographical (i.e., network, park) and taxonomic (i.e., community, guild, species) levels over a large spatiotemporal region. We found large variation in abundance trends across parks but not across bird guilds, suggesting that local forest condition might have a broad and consistent effect on the entire bird community within a given park. Research should target the three parks with overall decreasing trends in bird abundance to further identify what specific factors are driving observed declines across the bird community. Understanding how bird communities respond to local forest structure and other stressors (e.g., pest outbreaks, climate change) is crucial for informed and lasting management.

Integrating distance sampling and presence-only data to estimate species abundance

Integrated models combine multiple data types within a unified analysis to estimate species abundance and covariate effects. By sharing biological parameters, integrated models improve the accuracy and precision of estimates compared to separate analyses of individual data sets. We developed an integrated point process model to combine presence-only and distance sampling data for estimation of spatially explicit abundance patterns. Simulations across a range of parameter values demonstrate that our model can recover estimates of biological covariates, but parameter accuracy and precision varied with the quantity of each data type. We applied our model to a case study of black-backed jackals in the Masai Mara National Reserve, Kenya, to examine effects of spatially varying covariates on jackal abundance patterns. The model revealed that jackals were positively affected by anthropogenic disturbance on the landscape, with highest abundance estimated along the Reserve border near human activity. We found minimal effects of landscape cover, lion density, and distance to water source, suggesting that human use of the Reserve may be the biggest driver of jackal abundance patterns. Our integrated model expands the scope of ecological inference by taking advantage of widely available presence-only data, while simultaneously leveraging richer, but typically limited, distance sampling data.

Pastoralist activities affect the movement patterns of a large African carnivore, the spotted hyena (Crocuta crocuta)

Populations of large carnivores are declining in many parts of the world due to anthropogenic activity. Some species of large carnivores, however, are able to coexist with people by altering their behavior. Altered behaviors may be challenging to identify in large carnivores because these animals are typically cryptic, nocturnal, live at low densities, and because changes in their behavior may be subtle or emerge slowly over many years. We studied the effects of livestock presence on the movements of one large carnivore, the spotted hyena (Crocuta crocuta). We fit 22 adult female spotted hyenas with GPS collars to quantify their movements in areas with and without livestock or herders present, in and around a protected area in southwestern Kenya. We investigated anthropogenic, social, and ecological effects on the speed of movement, distances traveled, long-distance movements, and extraterritorial excursions by spotted hyenas. Hyenas living primarily within the protected area, but in the presence of livestock and herders, moved faster, traveled over longer distances, and were more likely to be within their territories than did conspecifics living in areas without livestock and herders. Hyenas of low social rank were more likely than hyenas of high social rank to engage in long-distance travel events, and these were more likely to occur when prey were scarce. The movement patterns of this large African carnivore indicate a flexibility that may allow them to persist in landscapes that are becoming increasingly defined by people.

Can hyena behaviour provide information on population trends of sympatric carnivores?

Mammalian carnivores are declining worldwide owing to human activities. Behavioural indicators have the potential to help identify population trends and inform conservation actions, although this area of research is understudied. We investigate whether behaviour is linked to abundance in a community of carnivores in the Masai Mara National Reserve, Kenya. Anthropogenic disturbance increased exponentially in parts of the Reserve between 1988 and 2017, mainly owing to daily incursions by large numbers of livestock and tourists. Previous research showed that hyena behaviour changed markedly during this period. Through a series of vignettes, we inquire whether hyena behaviours correlate with changes in abundance of hyenas themselves, or those of other carnivore species in the region. We find that changes in spotted hyena behaviour in disturbed areas, but not in undisturbed areas, can be linked to changes in their demography (vignette 1). We also find that declines in observed lion-hyena interactions, as well as increases in spotted hyena abundance, are probably caused by competitive release of hyenas from declining lion abundance (vignette 2). Finally, we demonstrate that in some cases, hyena behaviour and demography is linked to the density and distribution of sympatric carnivores, and that behavioural changes in hyenas can provide information on shifts within the carnivore community (vignettes 3 and 4). Our vignettes reveal intriguing relationships between behaviour and demography that should be explored in future research. Pairing behavioural studies with more traditional monitoring efforts can yield useful insights regarding population and community trends, and aid wildlife conservation and management. This article is part of the theme issue 'Linking behaviour to dynamics of populations and communities: application of novel approaches in behavioural ecology to conservation'.

Analyzing community structure subject to incomplete sampling: hierarchical community model vs. canonical ordinations

Recently developing hierarchical community models (HCMs) accounting for incomplete sampling are promising approaches to understand community organization. However, pros and cons of incorporating incomplete sampling in the analysis and related design issues remain unknown. In this study, we compared HCM and canonical redundancy analysis (RDA) carried out with 10 different dissimilarity coefficients to evaluate how each approach restores true community abundance data sampled with imperfect detection. We conducted simulation experiments with varying numbers of sampling sites, visits, mean detectability and mean abundance. Performance of HCM was measured by estimates of "expected" (mean) abundance ( λ ^ ij ) and realized abundance ( N ^ ij : direct estimate of site- and species-specific abundance). We also compared HCM and different types of RDA (normal, partial, and weighted), all performed with the same ten different dissimilarity coefficients, with unequal number of visits to sampling sites. In addition, we applied the models to a virtual survey carried out on the Barro Colorado Island tree plot data for which we know true community abundance. Simulation experiments showed that N ^ ij yielded by HCM best restored the underlying abundance of constituent species among 12 abundance estimates by HCM and RDA regardless if the sampling was equal or unequal. Mean abundance predominantly affected the performance of HCM and RDA while λ ^ ij yielded by HCM had comparable performance to percentage difference and Gower dissimilarity coefficients of RDA. Relative performance of RDA types depended on the combination of dissimilarity coefficients and the distribution of sampling effort. Best performance of N ^ ij followed by λ ^ ij , percentage difference and Gower dissimilarity were also observed for the analysis of tree plot data, and graphical plots (triplots) based on λ ^ ij rather than N ^ ij clearly separated the effects of two environmental covariates on the abundance of constituent species. Under our conditions of model evaluation and the method, we concluded that, in terms of assessing the environmental dependence of abundance, HCMs and RDA can have comparable performance if we can choose appropriate dissimilarity coefficients for RDA. However, since HCMs provide straightforward biological interpretations of parameter estimates and flexibility of the analysis, HCMs would be useful in many situations as well as conventional canonical ordinations.