Hierarchical Bayesian Spatial Models for Multispecies Conservation Planning and Monitoring

Abstract: Biologists who develop and apply habitat models are often familiar with the statistical challenges posed by their data's spatial structure but are unsure of whether the use of complex spatial models will increase the utility of model results in planning. We compared the relative performance of nonspatial and hierarchical Bayesian spatial models for three vertebrate and invertebrate taxa of conservation concern (Church's sideband snails [Monadenia churchi], red tree voles [Arborimus longicaudus], and Pacific fishers [Martes pennanti pacifica]) that provide examples of a range of distributional extents and dispersal abilities. We used presence–absence data derived from regional monitoring programs to develop models with both landscape and site‐level environmental covariates. We used Markov chain Monte Carlo algorithms and a conditional autoregressive or intrinsic conditional autoregressive model framework to fit spatial models. The fit of Bayesian spatial models was between 35 and 55% better than the fit of nonspatial analogue models. Bayesian spatial models outperformed analogous models developed with maximum entropy (Maxent) methods. Although the best spatial and nonspatial models included similar environmental variables, spatial models provided estimates of residual spatial effects that suggested how ecological processes might structure distribution patterns. Spatial models built from presence–absence data improved fit most for localized endemic species with ranges constrained by poorly known biogeographic factors and for widely distributed species suspected to be strongly affected by unmeasured environmental variables or population processes. By treating spatial effects as a variable of interest rather than a nuisance, hierarchical Bayesian spatial models, especially when they are based on a common broad‐scale spatial lattice (here the national Forest Inventory and Analysis grid of 24 km² hexagons), can increase the relevance of habitat models to multispecies conservation planning.     

Habitat Suitability Models and the Shortfall in Conservation Planning for African Vertebrates

Abstract:  Ongoing loss of biodiversity requires identifying large-scale conservation priorities, but the detailed information on the distribution of species required for this purpose is often missing. We present a systematic reserve selection for 1223 African mammals and amphibians in which habitat suitability models are used as estimates of the area occupied by species. In the framework of the World Conservation Union (IUCN) Global Amphibian Assessment and IUCN Global Mammal Assessment, we collected the geographic range (extent of occurrence) and habitat preferences for each species. We used the latter to build species-specific habitat suitability models inside geographic ranges, and for 181 species we verified the models by comparing suitability levels to presence-absence data collected in the field. We then used the suitable areas as estimators of the area of occupancy and compared the results of systematic reserve selection based on geographic ranges to those based on estimated areas of occupancy. Our results showed that the reserve system would need a 30-100% expansion to achieve minimal conservation targets, concentrated in the tropics, where species richness reaches a maximum. Comparative analyses revealed that using geographic ranges, which overestimate the area occupied by species, underestimates the total amount of area that needs to be conserved. The area selected for conservation doubled when we used the estimated area of occupancy in place of the geographic ranges. This happened because the suitable areas potentially occupied by each species overlapped less than their geographic ranges. As a result, any given protected area contained fewer species than predicted by the analysis of ranges. Because species are more specialized than our estimates of distribution based on extent of occurrence suggest, we propose that this is a general effect in systematic conservation planning.     

Some Interpolation Estimators in Environmental Risk Assessment for Spatially Misaligned Health Data

Ecological regression studies are widely used in geographical epidemiology to assess the relationships between health hazard and putative risk factors. Very often, health data are measured at an aggregate level because of confidentiality restrictions, while putative risk factors are measured on a different grid, i.e., independent (exposure) variable and response (counts) variable are spatially misaligned. To perform a regression of risk on exposure, one needs to realign the spatial support of the variables. Bayesian hierarchical models constitute a natural approach to the problem because of their ability to model the exposure field and the relationship between exposure and relative risk at different levels of the hierarchy, taking proper account of the variability induced by the covariate estimation. In the current paper, we propose two fully Bayesian solutions to the problem. The first one is based on the kernel-smoothing technique, while the second one is built on the tessellation of the study region. We illustrate our methods by assessing the relationship between exposure to uranium in drinkable waters and cancer incidence, in South Carolina (USA).     

Assessing Risk and Guidance on Monitoring of Batrachochytrium dendrobatidis in Europe through Identification of Taxonomic Selectivity of Infection

Amphibians are globally threatened, but not all species are affected equally by different threatening processes. This is true for the threat posed by the chytridiomycete fungus (Batrachochytrium dendrobatidis). We compiled a European data set for B. dendrobatidis to analyze the trends of infection in European amphibians. The risk of infection was not randomly distributed geographically or taxonomically across Europe. Within countries with different prevalence, infection was nonrandom in certain amphibian taxa. Brown frogs of the genus Rana were unlikely to be infected, whereas frogs in the families Alytidae and Bombinatoridae were significantly more likely to be infected than predicted by chance. Frogs in the 2 families susceptible to B. dendrobatidis should form the core of attempts to develop spatial surveillance studies of chytridiomycosis in Europe. Ideally, surveys for B. dendrobatidis should be augmented by sampling the widespread genus Pelophylax because this taxon exhibits geographically inconsistent overinfection with B. dendrobatidis and surveillance of it may facilitate recognition of factors causing spatial variability of infection intensity. Several European amphibian taxa were not represented in our data set; however, surveillance of unsampled species should also occur when warranted. Evaluación de Riesgo y Orientación para el Monitoreo de Batrachochytrium dendrobatidis en Europa Mediante la Identificación de la Selectividad Taxonómica de la Infección     

Strategic Rat Control for Restoring Populations of Native Species in Forest Fragments

Forest fragments have biodiversity value that may be enhanced through management such as control of non‐native predators. However, such efforts may be ineffective, and research is needed to ensure that predator control is done strategically. We used Bayesian hierarchical modeling to estimate fragment‐specific effects of experimental rat control on a native species targeted for recovery in a New Zealand pastoral landscape. The experiment was a modified BACI (before‐after‐control‐impact) design conducted over 6 years in 19 forest fragments with low‐density subpopulations of North Island Robins (Petroica longipes). The aim was to identify individual fragments that not only showed clear benefits of rat control, but also would have a high probability of subpopulation growth even if they were the only fragment managed. We collected data on fecundity, adult and juvenile survival, and juvenile emigration, and modeled the data in an integrated framework to estimate the expected annual growth rate (λ) of each subpopulation with and without rat control. Without emigration, subpopulation growth was estimated as marginal (λ = 0.95–1.05) or negative (λ = 0.74–0.90) without rat control, but it was estimated as positive in all fragments (λ = 1.4–2.1) if rats were controlled. This reflected a 150% average increase in fecundity and 45% average increase in adult female survival. The probability of a juvenile remaining in its natal fragment was 0.37 on average, but varied with fragment connectivity. With juvenile emigration added, 6 fragments were estimated to have a high (>0.8) probability of being self‐sustaining (λ > 1) with rat control. The key factors affecting subpopulation growth rates under rat control were low connectivity and stock fencing because these factors were associated with lower juvenile emigration and higher fecundity, respectively. However, there was also substantial random variation in adult survival among fragments, illustrating the importance of hierarchical modeling for fragmentation studies. Control Estratégico de Ratas para Restaurar Poblaciones de Especies Nativas en Fragmentos de Bosque     

Multimethod,multistate Bayesian hierarchical modeling approach for use in regional monitoring of wolves

In many cases, the first step in large‐carnivore management is to obtain objective, reliable, and cost‐effective estimates of population parameters through procedures that are reproducible over time. However, monitoring predators over large areas is difficult, and the data have a high level of uncertainty. We devised a practical multimethod and multistate modeling approach based on Bayesian hierarchical‐site‐occupancy models that combined multiple survey methods to estimate different population states for use in monitoring large predators at a regional scale. We used wolves (Canis lupus) as our model species and generated reliable estimates of the number of sites with wolf reproduction (presence of pups). We used 2 wolf data sets from Spain (Western Galicia in 2013 and Asturias in 2004) to test the approach. Based on howling surveys, the naïve estimation (i.e., estimate based only on observations) of the number of sites with reproduction was 9 and 25 sites in Western Galicia and Asturias, respectively. Our model showed 33.4 (SD 9.6) and 34.4 (3.9) sites with wolf reproduction, respectively. The number of occupied sites with wolf reproduction was 0.67 (SD 0.19) and 0.76 (0.11), respectively. This approach can be used to design more cost‐effective monitoring programs (i.e., to define the sampling effort needed per site). Our approach should inspire well‐coordinated surveys across multiple administrative borders and populations and lead to improved decision making for management of large carnivores on a landscape level. The use of this Bayesian framework provides a simple way to visualize the degree of uncertainty around population‐parameter estimates and thus provides managers and stakeholders an intuitive approach to interpreting monitoring results. Our approach can be widely applied to large spatial scales in wildlife monitoring where detection probabilities differ between population states and where several methods are being used to estimate different population parameters.     

Incorporating Climate Science in Applications of the U.S. Endangered Species Act for Aquatic Species

Aquatic species are threatened by climate change but have received comparatively less attention than terrestrial species. We gleaned key strategies for scientists and managers seeking to address climate change in aquatic conservation planning from the literature and existing knowledge. We address 3 categories of conservation effort that rely on scientific analysis and have particular application under the U.S. Endangered Species Act (ESA): assessment of overall risk to a species; long‐term recovery planning; and evaluation of effects of specific actions or perturbations. Fewer data are available for aquatic species to support these analyses, and climate effects on aquatic systems are poorly characterized. Thus, we recommend scientists conducting analyses supporting ESA decisions develop a conceptual model that links climate, habitat, ecosystem, and species response to changing conditions and use this model to organize analyses and future research. We recommend that current climate conditions are not appropriate for projections used in ESA analyses and that long‐term projections of climate‐change effects provide temporal context as a species‐wide assessment provides spatial context. In these projections, climate change should not be discounted solely because the magnitude of projected change at a particular time is uncertain when directionality of climate change is clear. Identifying likely future habitat at the species scale will indicate key refuges and potential range shifts. However, the risks and benefits associated with errors in modeling future habitat are not equivalent. The ESA offers mechanisms for increasing the overall resilience and resistance of species to climate changes, including establishing recovery goals requiring increased genetic and phenotypic diversity, specifying critical habitat in areas not currently occupied but likely to become important, and using adaptive management. Incorporación de las Ciencias Climáticas en las Aplicaciones del Acta Estadunidense de Especies en Peligro para Especies Acuáticas