Landscape-scale benefits of protected areas for tropical biodiversity.

The United Nations recently agreed to major expansions of global protected areas (PAs) to slow biodiversity declines1. However, although reserves often reduce habitat loss, their efficacy at preserving animal diversity and their influence on biodiversity in surrounding unprotected areas remain unclear2-5. Unregulated hunting can empty PAs of large animals6, illegal tree felling can degrade habitat quality7, and parks can simply displace disturbances such as logging and hunting to unprotected areas of the landscape8 (a phenomenon called leakage). Alternatively, well-functioning PAs could enhance animal diversity within reserves as well as in nearby unprotected sites9 (an effect called spillover). Here we test whether PAs across mega-diverse Southeast Asia contribute to vertebrate conservation inside and outside their boundaries. Reserves increased all facets of bird diversity. Large reserves were also associated with substantially enhanced mammal diversity in the adjacent unprotected landscape. Rather than PAs generating leakage that deteriorated ecological conditions elsewhere, our results are consistent with PAs inducing spillover that benefits biodiversity in surrounding areas. These findings support the United Nations goal of achieving 30% PA coverage by 2030 by demonstrating that PAs are associated with higher vertebrate diversity both inside their boundaries and in the broader landscape.

Carnivore Contact: A Species Fracture Zone Delineated Amongst Genetically Structured North American Marten Populations (Martes americana and Martes caurina).

North American martens are forest dependent, influenced by human activity, and climate vulnerable. They have long been managed and harvested throughout their range as the American marten (Martes americana). Recent work has expanded evidence for the original description of two species in North America - M. americana and the Pacific Coast marten, M. caurina - but the geographic boundary between these groups has not been described in detail. From 2010 to 2016 we deployed 734 multi-taxa winter bait stations across a 53,474 km2 study area spanning seven mountain ranges within the anticipated contact zone along the border of Canada and the United States. We collected marten hair samples and developed genotypes for 15 polymorphic microsatellite loci for 235 individuals, and 493 base-pair sequences of the mtDNA gene COI for 175 of those individuals. Both nuclear and mitochondrial genetic structure identified a sharp break across the Clark Fork Valley, United States with M. americana and M. caurina occurring north and south of the break, respectively. We estimated global effective population size (N e ) for each mountain range, clinal genetic neighborhood sizes (NS), calculated observed (H o ) and expected (H e ) heterozygosity, fixation index (F ST ), and clinal measures of allelic richness (Ar), H o , and inbreeding coefficient (F IS ). Despite substantial genetic structure, we detected hybridization along the fracture zone with both contemporary (nuclear DNA) and historic (mtDNA) gene flow. Marten populations in our study area are highly structured and the break across the fracture zone being the largest documented in North America (F ST range 0.21-0.34, mean = 0.27). With the exception of the Coeur d'Alene Mountains, marten were well distributed across higher elevation portions of our sampling area. Clinal NS values were variable suggesting substantial heterogeneity in marten density and movement. For both M. americana and M. caurina, elevationaly dependent gene flow and high genetic population structure suggest that connectivity corridors will be important to ensuring long-term population persistence. Our study is an example of how a combination of global and clinal molecular data analyses can provide important information for natural resource management.

A simulation-based evaluation of methods for inferring linear barriers to gene flow.

Different analytical techniques used on the same data set may lead to different conclusions about the existence and strength of genetic structure. Therefore, reliable interpretation of the results from different methods depends on the efficacy and reliability of different statistical methods. In this paper, we evaluated the performance of multiple analytical methods to detect the presence of a linear barrier dividing populations. We were specifically interested in determining if simulation conditions, such as dispersal ability and genetic equilibrium, affect the power of different analytical methods for detecting barriers. We evaluated two boundary detection methods (Monmonier's algorithm and WOMBLING), two spatial Bayesian clustering methods (TESS and GENELAND), an aspatial clustering approach (STRUCTURE), and two recently developed, non-Bayesian clustering methods [PSMIX and discriminant analysis of principal components (DAPC)]. We found that clustering methods had higher success rates than boundary detection methods and also detected the barrier more quickly. All methods detected the barrier more quickly when dispersal was long distance in comparison to short-distance dispersal scenarios. Bayesian clustering methods performed best overall, both in terms of highest success rates and lowest time to barrier detection, with GENELAND showing the highest power. None of the methods suggested a continuous linear barrier when the data were generated under an isolation-by-distance (IBD) model. However, the clustering methods had higher potential for leading to incorrect barrier inferences under IBD unless strict criteria for successful barrier detection were implemented. Based on our findings and those of previous simulation studies, we discuss the utility of different methods for detecting linear barriers to gene flow.