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.     

Wildlife impacts and vulnerable livelihoods in a transfrontier conservation landscape

Interactions between humans and wildlife resulting in negative impacts are among the most pressing conservation challenges globally. In regions of smallholder livestock and crop production, interactions with wildlife can compromise human well-being and motivate negative sentiment and retaliation toward wildlife, undermining conservation goals. Although impacts may be unavoidable when human and wildlife land use overlap, scant large-scale human data exist quantifying the direct costs of wildlife to livelihoods. In a landscape of global importance for wildlife conservation in southern Africa, we quantified costs for people living with wildlife through a fundamental measure of human well-being, food security, and we tested whether existing livelihood strategies buffer certain households against crop depredation by wildlife, predominantly elephants. To do this, we estimated Bayesian multilevel statistical models based on multicounty household data (n = 711) and interpreted model results in the context of spatial data from participatory land-use mapping. Reported crop depredation by wildlife was widespread. Over half of the sample households were affected and household food security was reduced significantly (odds ratio 0.37 [0.22, 0.63]). The most food insecure households relied on gathered food sources and welfare programs. In the event of crop depredation by wildlife, these 2 livelihood sources buffered or reduced harmful effects of depredation. The presence of buffering strategies suggests a targeted compensation strategy could benefit the region's most vulnerable people. Such strategies should be combined with dynamic and spatially explicit land-use planning that may reduce the frequency of negative human–wildlife impacts. Quantifying and mitigating the human costs from wildlife are necessary steps in working toward human–wildlife coexistence.     

Examining the relationship between local extinction risk and position in range

Over half of globally threatened animal species have experienced rapid geographic range loss. Identifying the parts of species’ distributions most vulnerable to local extinction would benefit conservation planning. However, previous studies give little consensus on whether ranges decline to the core or edge. We built on previous work by using empirical data to examine the position of recent local extinctions within species’ geographic ranges, address range position as a continuum, and explore the influence of environmental factors. We aggregated point‐locality data for 125 Galliform species from across the Palearctic and Indo‐Malaya into equal‐area half‐degree grid cells and used a multispecies dynamic Bayesian occupancy model to estimate rates of local extinctions. Our model provides a novel approach to identify loss of populations from within species ranges. We investigated the relationship between extinction rates and distance from range edge by examining whether patterns were consistent across biogeographic realm and different categories of land use. In the Palearctic, local extinctions occurred closer to the range edge than range core in both unconverted and human‐dominated landscapes. In Indo‐Malaya, no pattern was found for unconverted landscapes, but in human‐dominated landscapes extinctions tended to occur closer to the core than the edge. Our results suggest that local and regional factors override general spatial patterns of recent local extinction within species’ ranges and highlight the difficulty of predicting the parts of a species’ distribution most vulnerable to threat.     

Characterizing fish responses to a river restoration over 21 years based on species’ traits

Understanding restoration effectiveness is often impaired by a lack of high‐quality, long‐term monitoring data and, to date, few researchers have used species’ trait information to gain insight into the processes that drive the reaction of fish communities to restoration. We examined fish‐community responses with a highly resolved data set from 21 consecutive years of electrofishing (4 years prerestoration and 17 years postrestoration) at multiple restored and unrestored reaches from a river restoration project on the Lippe River, Germany. Fish abundance peaked in the third year after the restoration; abundance was 6 times higher than before the restoration. After 5–7 years, species richness and abundance stabilized at 2 and 3.5 times higher levels relative to the prerestoration level, respectively. However, interannual variability of species richness and abundance remained considerable, illustrating the challenge of reliably assessing restoration outcomes based on data from individual samplings, especially in the first years following restoration. Life‐history and reproduction‐related traits best explained differences in species’ responses to restoration. Opportunistic short‐lived species with early female maturity and multiple spawning runs per year exhibited the strongest increase in abundance, which reflected their ability to rapidly colonize new habitats. These often small‐bodied and fusiform fishes typically live in dynamic and ephemeral instream and floodplain areas that river‐habitat restorations often aim to create, and in this case their increases in abundance indicated successful restoration. Our results suggest that a greater consideration of species’ traits may enhance the causal understanding of community processes and the coupling of restoration to functional ecology. Trait‐based assessments of restoration outcomes would furthermore allow for easier transfer of knowledge across biogeographic borders than studies based on taxonomy.     

Using community‐level metrics to monitor the effects of marine protected areas on biodiversity

Marine protected areas (MPAs) are used to protect species, communities, and their associated habitats, among other goals. Measuring MPA efficacy can be challenging, however, particularly when considering responses at the community level. We gathered 36 abundance and 14 biomass data sets on fish assemblages and used meta‐analysis to evaluate the ability of 22 distinct community diversity metrics to detect differences in community structure between MPAs and nearby control sites. We also considered the effects of 6 covariates—MPA size and age, MPA size and age interaction, latitude, total species richness, and level of protection—on each metric. Some common metrics, such as species richness and Shannon diversity, did not differ consistently between MPA and control sites, whereas other metrics, such as total abundance and biomass, were consistently different across studies. Metric responses derived from the biomass data sets were more consistent than those based on the abundance data sets, suggesting that community‐level biomass differs more predictably than abundance between MPA and control sites. Covariate analyses indicated that level of protection, latitude, MPA size, and the interaction between MPA size and age affect metric performance. These results highlight a handful of metrics, several of which are little known, that could be used to meet the increasing demand for community‐level indicators of MPA effectiveness.     

Mechanistic understanding of human–wildlife conflict through a novel application of dynamic occupancy models

Crop and livestock depredation by wildlife is a primary driver of human–wildlife conflict, a problem that threatens the coexistence of people and wildlife globally. Understanding mechanisms that underlie depredation patterns holds the key to mitigating conflicts across time and space. However, most studies do not consider imperfect detection and reporting of conflicts, which may lead to incorrect inference regarding its spatiotemporal drivers. We applied dynamic occupancy models to elephant crop depredation data from India between 2005 and 2011 to estimate crop depredation occurrence and model its underlying dynamics as a function of spatiotemporal covariates while accounting for imperfect detection of conflicts. The probability of detecting conflicts was consistently <1.0 and was negatively influenced by distance to roads and elevation gradient, averaging 0.08–0.56 across primary periods (distinct agricultural seasons within each year). The probability of crop depredation occurrence ranged from 0.29 (SE 0.09) to 0.96 (SE 0.04). The probability that sites raided by elephants in primary period t would not be raided in primary period t + 1 varied with elevation gradient in different seasons and was influenced negatively by mean rainfall and village density and positively by distance to forests. Negative effects of rainfall variation and distance to forests best explained variation in the probability that sites not raided by elephants in primary period t would be raided in primary period t + 1. With our novel application of occupancy models, we teased apart the spatiotemporal drivers of conflicts from factors that influence how they are observed, thereby allowing more reliable inference on mechanisms underlying observed conflict patterns. We found that factors associated with increased crop accessibility and availability (e.g., distance to forests and rainfall patterns) were key drivers of elephant crop depredation dynamics. Such an understanding is essential for rigorous prediction of future conflicts, a critical requirement for effective conflict management in the context of increasing human–wildlife interactions.     

Spatiotemporal trends of illegal activities from ranger‐collected data in a Ugandan national park

Within protected areas, biodiversity loss is often a consequence of illegal resource use. Understanding the patterns and extent of illegal activities is therefore essential for effective law enforcement and prevention of biodiversity declines. We used extensive data, commonly collected by ranger patrols in many protected areas, and Bayesian hierarchical models to identify drivers, trends, and distribution of multiple illegal activities within the Queen Elizabeth Conservation Area (QECA), Uganda. Encroachment (e.g., by pastoralists with cattle) and poaching of noncommercial animals (e.g., snaring bushmeat) were the most prevalent illegal activities within the QECA. Illegal activities occurred in different areas of the QECA. Poaching of noncommercial animals was most widely distributed within the national park. Overall, ecological covariates, although significant, were not useful predictors for occurrence of illegal activities. Instead, the location of illegal activities in previous years was more important. There were significant increases in encroachment and noncommercial plant harvesting (nontimber products) during the study period (1999–2012). We also found significant spatiotemporal variation in the occurrence of all activities. Our results show the need to explicitly model ranger patrol effort to reduce biases from existing uncorrected or capture per unit effort analyses. Prioritization of ranger patrol strategies is needed to target illegal activities; these strategies are determined by protected area managers, and therefore changes at a site‐level can be implemented quickly. These strategies should also be informed by the location of past occurrences of illegal activity: the most useful predictor of future events. However, because spatial and temporal changes in illegal activities occurred, regular patrols throughout the protected area, even in areas of low occurrence, are also required.     

Spatially Explicit Power Analyses for Occupancy‐Based Monitoring of Wolverine in the U.S. Rocky Mountains

Conservation scientists and resource managers often have to design monitoring programs for species that are rare or patchily distributed across large landscapes. Such programs are frequently expensive and seldom can be conducted by one entity. It is essential that a prospective power analysis be undertaken to ensure stated monitoring goals are feasible. We developed a spatially based simulation program that accounts for natural history, habitat use, and sampling scheme to investigate the power of monitoring protocols to detect trends in population abundance over time with occupancy‐based methods. We analyzed monitoring schemes with different sampling efforts for wolverine (Gulo gulo) populations in 2 areas of the U.S. Rocky Mountains. The relation between occupancy and abundance was nonlinear and depended on landscape, population size, and movement parameters. With current estimates for population size and detection probability in the northern U.S. Rockies, most sampling schemes were only able to detect large declines in abundance in the simulations (i.e., 50% decline over 10 years). For small populations reestablishing in the Southern Rockies, occupancy‐based methods had enough power to detect population trends only when populations were increasing dramatically (e.g., doubling or tripling in 10 years), regardless of sampling effort. In general, increasing the number of cells sampled or the per‐visit detection probability had a much greater effect on power than the number of visits conducted during a survey. Although our results are specific to wolverines, this approach could easily be adapted to other territorial species. Poder de Análisis Espacialmente Explícito para el Monitoreo Basado en Ocupación del Glotón (Gulo gulo) en las Montañas Rocallosas de Estados Unidos     

A geological perspective on the degradation and conservation of western Atlantic coral reefs

Continuing coral‐reef degradation in the western Atlantic is resulting in loss of ecological and geologic functions of reefs. With the goal of assisting resource managers and stewards of reefs in setting and measuring progress toward realistic goals for coral‐reef conservation and restoration, we examined reef degradation in this region from a geological perspective. The importance of ecosystem services provided by coral reefs—as breakwaters that dissipate wave energy and protect shorelines and as providers of habitat for innumerable species—cannot be overstated. However, the few coral species responsible for reef building in the western Atlantic during the last approximately 1.5 million years are not thriving in the 21st century. These species are highly sensitive to abrupt temperature extremes, prone to disease infection, and have low sexual reproductive potential. Their vulnerability and the low functional redundancy of branching corals have led to the low resilience of western Atlantic reef ecosystems. The decrease in live coral cover over the last 50 years highlights the need for study of relict (senescent) reefs, which, from the perspective of coastline protection and habitat structure, may be just as important to conserve as the living coral veneer. Research is needed to characterize the geological processes of bioerosion, reef cementation, and sediment transport as they relate to modern‐day changes in reef elevation. For example, although parrotfish remove nuisance macroalgae, possibly promoting coral recruitment, they will not save Atlantic reefs from geological degradation. In fact, these fish are quickly nibbling away significant quantities of Holocene reef framework. The question of how different biota covering dead reefs affect framework resistance to biological and physical erosion needs to be addressed. Monitoring and managing reefs with respect to physical resilience, in addition to ecological resilience, could optimize the expenditure of resources in conserving Atlantic reefs and the services they provide.     

Assessing Multiregion Avian Benefits from Strategically Targeted Agricultural Buffers

Mounting evidence of wildlife population gains from targeted conservation practices has prompted the need to develop and evaluate practices that are integrated into production agriculture systems and targeted toward specific habitat objectives. However, effectiveness of targeted conservation actions across broader landscapes is poorly understood. We evaluated multiregion, multispecies avian densities on row‐crop fields with native grass field margins (i.e., buffers) as part of the first U.S. agricultural conservation practice designed to support habitat and population recovery objectives of a national wildlife conservation initiative. We coordinated breeding season point transect surveys for 6 grassland bird species on 1151 row‐crop fields with and without native grass buffers (9–37 m) in 14 U.S. states (10 ecoregions) from 2006 to 2011. In most regions, breeding season densities of 5 of 6 targeted bird species were greater in the 500‐m surrounding survey points centered on fields with native grass buffers than in landscapes without buffers. Relative effect sizes were greatest for Northern Bobwhite (Colinus virginianus), Dickcissel (Spiza americana), and Field Sparrow (Spizella pusilla) in the Mississippi Alluvial Valley and Eastern Tallgrass Prairie regions. Other species (e.g., Eastern Meadowlark [Sturnella magna], Grasshopper Sparrow [Ammodramus savannarum]) exhibited inconsistent relative effect sizes. Bird densities on fields with and without buffers were greatest in the Central Mixed‐grass Prairie region. Our results suggest that strategic use of conservation buffers in regions with the greatest potential for relative density increases in target species will elicit greater range‐wide population response than diffuse, uninformed, and broadly distributed implementation of buffers. We recommend integrating multiple conservation practices in broader agricultural landscapes to maximize conservation effectiveness for a larger suite of species. Evaluación de los Beneficios de la Mutliregionalidad de Aves a Partir de Amortiguadores Agriculturales Estratégicamente Señalados