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We monitored the breeding performance (territory occupancy, nest success, productivity) of a reintroduced hybrid population of Falco peregrinus anatum (Peregrine Falcon) in western North Carolina during the 13-y post-delisting period of 2003–2015. Peregrine Falcons nested at 18 sites (17 cliffs, 1 building), 6 of which were newly discovered sites. Eight to 13 territories were occupied annually. We documented 139 nesting attempts and production of 171 young. Mean nest success (55%) during the period 2003–2015 fell below the 1999–2002 national average, but was more than double earlier (1987–1992) efforts in western North Carolina. Likewise, mean productivity (1.23 young/year/pair) was more than double earlier efforts in North Carolina, but reflects the disproportionately high contribution of ~5 sites. Throughout the study, subadult birds were members of a pair (13.7% of nesting attempts) and had lower nest success than adult pairs. High variability in nest success and productivity underscore the need for continued monitoring and protection from disturbance and other threats, especially at the most vulnerable and least productive sites.

American Oystercatchers (Haematopus palliatus) are present in North Carolina, USA, year-round. About 6–7% of the total Western Atlantic population winters in North Carolina. To estimate numbers of American Oystercatchers present during the non-breeding season, four major concentration areas were surveyed in North Carolina, each with multiple roost sites, from 2008–2013. Abundance of American Oystercatchers remained generally stable during the study period. The Lower Cape Fear River area had the greatest number of American Oystercatchers in all seasons. Mean peak abundance was greatest during winter at all concentration areas. Peak winter abundance was 158 at Ocracoke Inlet, 265 in Back Sound, 187 in Masonboro Sound, and 470 on the Lower Cape Fear River. Fall abundance was generally greater than spring abundance at all concentration areas except Masonboro Sound. Most banded individuals observed were marked in North Carolina as chicks or nesting adults, and they exhibited fidelity to concentration...

Mesopredators play an increasingly important role in ecosystems where apex predators have been eliminated, but population ecology of these midsized mammalian carnivores remains poorly understood. We applied Pradel's temporal symmetry models to > 6 years of monthly capture–mark–recapture data and investigated factors influencing apparent survival, recruitment, and realized population growth rate of the Virginia opossum (Didelphis virginiana), an important mesopredator with unique life-history characteristics. Apparent survival did not vary temporally; monthly survival probabilities were 0.86 ± 0.01 (SE) for females and 0.76 ± 0.02 for males. Recruitment rate varied monthly, with the highest recruitment in December (0.32 ± 0.12 for females and 0.57 ± 0.22 for males). Realized population growth rate varied monthly and was also highest in December (1.30 ± 0.17). Both recruitment and population growth rate were positively influenced by the monthly coefficient of variation of precipitation. There was n...

The extraordinary growth of human populations and development in coastal areas over the last half century has eliminated and degraded coastal habitats and threatened the persistence of associated wildlife. Moreover, human-induced sea-level rise (SLR) is projected to further eliminate and alter the same coastal ecosystems, especially low-lying regions. Whereas habitat loss and wildlife population declines from development are well documented, contemporary SLR has not yet been implicated in declines of coastal faunal populations. In addition, the projection of severe synergistic impacts from the combination of development and SLR is well described, yet the scientific literature offers little empirical evidence of the influence of these forces on coastal wildlife. Analysis of aerial photographs from 1959 to 2006 provided evidence of a 64% net loss of the endangered Lower Keys marsh rabbit’s (Sylvilagus palustris hefneri; LKMR) habitat, the majority due to SLR (>48%). Furthermore, there was a strong negative relationship between the proportion of development per island and the amount of new habitat formed. Islands with modest development (less than 8% of land area) saw formation of new areas of marsh vegetation suitable for rabbits, whereas islands with 8% or more of their lands developed between 1959 and 2006 saw little to no addition of LKMR habitat. Only 8% of habitat loss was directly due to conversion to impervious surfaces, indicating that the greatest threats from development were indirect, including blocking of the inland migration of habitat triggered by SLR. Our results were consistent with an ongoing squeeze of coastal ecosystems between rising seas and development as a threat to LKMR habitat, which raises concern for a wide variety of coastal species. Our results provide evidence that SLR has become a contemporary conservation concern, one that is exacerbated by development, and expected to increase in magnitude as ocean waters continue to rise.

Undergraduate and graduate programs in natural resource management focus on interventions to sustainably manage wildlife, fisheries, and forests. Coursework usually provides in-depth content on the biology and ecology of species and ecosystems. Topics such as climate change are framed as environmental problems, and risks and impacts to the natural world are emphasized. Relatively few courses incorporate concepts from psychology, or more specifically ecopsychology, to present an underlying framework to help students understand the basis of why people's individual and collective actions may reflect denial, exacerbation, or problem-solving solutions to environmental hazards such as climate change. Incorporating a psychological approach into students' exploration of climate change issues provides the basis for learning about climate change risks and impacts in the context of daily life, communication in mass media, and in policy formation. Incorporating a psychological approach can improve the effect...

Human-induced land use changes are causing extensive habitat fragmentation. As a result, many species are not able to shift their ranges in response to climate change and will likely need to adapt in situ to changing climate conditions. Consequently, a prudent strategy to maintain the ability of populations to adapt is to focus conservation efforts on areas where levels of intraspecific variation are high. By doing so, the potential for an evolutionary response to environmental change is maximized. Here, we use modeling approaches in conjunction with environmental variables to model species distributions and patterns of genetic and morphological variation in seven Ecuadorian amphibian, bird, and mammal species. We then used reserve selection software to prioritize areas for conservation based on intraspecific variation or species-level diversity. Reserves selected using species richness and complementarity showed little overlap with those based on genetic and morphological variation. Priority areas for intraspecific variation were mainly located along the slopes of the Andes and were largely concordant among species, but were not well represented in existing reserves. Our results imply that in order to maximize representation of intraspecific variation in reserves, genetic and morphological variation should be included in conservation prioritization.

Species distribution models are commonly used to predict species responses to climate change. However, their usefulness in conservation planning and policy is controversial because they are difficult to validate across time and space. Here we capitalize on small mammal surveys repeated over a century in Yosemite National Park, USA, to assess accuracy of model predictions. Historical (1900-1940) climate, vegetation, and species occurrence data were used to develop single- and multi-species multivariate adaptive regression spline distribution models for three species of chipmunk. Models were projected onto the current (1980-2007) environmental surface and then tested against modern field resurveys of each species. We evaluated models both within and between time periods and found that even with the inclusion of biotic predictors, climate alone is the dominant predictor explaining the distribution of the study species within a time period. However, climate was not consistently an adequate predictor of the distributional change observed in all three species across time. For two of the three species, climate alone or climate and vegetation models showed good predictive performance across time. The stability of the distribution from the past to present observed in the third species, however, was not predicted by our modeling approach. Our results demonstrate that correlative distribution models are useful in understanding species' potential responses to environmental change, but also show how changes in species-environment correlations through time can limit the predictive performance of models.

To better understand how environment shapes phenotypic and genetic variation, we explore the relationship between environmental variables across Ecuador and genetic and morphological variation in the wedge-billed woodcreeper (Glyphorynchus spirurus), a common Neotropical rainforest bird species. Generalized dissimilarity models show that variation in amplified fragment length polymorphism markers was strongly associated with environmental variables on both sides of the Andes, but could also partially be explained by geographic distance on the western side of the Andes. Tarsus, wing, tail, and bill lengths and bill depth were well explained by environmental variables on the western side of the Andes, whereas only tarsus length was well explained on the eastern side. Regions that comprise the highest rates of genetic and phenotypic change occur along steep elevation gradients in the Andes. Such environmental gradients are likely to be particularly important for maximizing adaptive diversity to minimize the impacts of climate change. Using a framework for conservation prioritization based on preserving ecological and evolutionary processes, we found little overlap between currently protected areas in Ecuador and regions we predicted to be important in maximizing adaptive variation.

Scarce resources and competing land-use goals necessitate efficient biodiversity conservation. Combining multicriteria analysis with conservation decision-support tools improves efficiency of conservation planning by maximizing outcomes for biodiversity while minimizing opportunity costs to society. An opportunity cost is the benefit that could have been received by taking an alternative course of action (i.e., costs to society of protecting an area for biodiversity rather than developing it for some other use). Although different ways of integrating multiple opportunity costs into conservation planning have been suggested, there have been no tests as to which method is most efficient. We compared the relative efficiency of 3 such procedures(Faith & Walker [1996], Sarkar et al. [2004], and a procedure of our own design) in a systematic conservation-planning framework for the Milne Bay Province of Papua New Guinea. We devised 14 opportunity costs and assigned these to 3 scenarios representing different conservation planning concerns: food security, macro-economic development, and biodiversity persistence. For each scenario, we compared the efficiency of the 3 methods in terms of amount of biodiversity protected relative to total expenditure for each opportunity cost. All 3 methods captured similar amounts of biodiversity, but differed in total cost. Our method had the least overall cost and was therefore most efficient. Nevertheless, there was a high correlation and geographical concordance among all 3 methods, indicating a high degree of spatial overlap. This suggests that choosing an appropriate approach may often depend on contextual factors related to the design of the planning question, rather than efficiency alone. Resumen: La escasez de recursos y la competencia de metas de uso de suelo requieren de eficiencia en la conservacion de la biodiversidad. La combinacion del analisis de criterios multiples con herramientas de decision en conservacion mejora la eficiencia de la planificacion de la conservacion mediante la maximizacion de resultados para la biodiversidad y la minimizacion de costos de oportunidad para la sociedad. Un costo de oportunidad es el beneficio que se pudiera haber recibido de haberse tomado una linea de accion alternativa (i. e., costos a la sociedad por la proteccion de un area para biodiversidad en lugar de desarrollarla para otro uso). Aunque se han sugerido diferentes maneras de integrar costos de oportunidad multiples a la planificacion de la conservacion, no se ha probado cual metodo es mas eficiente. Comparamos la eficiencia relativa de 3 de esos procedimientos (Faith & Walker [1996], Sarkar et al. [2004] y un procedimiento disenado por nosotros) en un marco de planificacion sistematica de conservacion para la Provincia Milne Bay en Papua Nueva Guinea. Disenamos 14 costos de oportunidad y los asignamos a 3 escenarios representando diferentes intereses de planificacion de la conservacion: seguridad alimentaria, desarrollo macroeconomico y persistencia de la biodiversidad. Comparamos la eficiencia de los 3 metodos en cada escenario en terminos de la cantidad de biodiversidad protegida en relacion con el gasto total de cada costo de oportunidad. Los 3 metodos capturaron cantidades similares de biodiversidad, pero difirieron en el costo total. Nuestro metodo tuvo el menor costo total y por lo tanto fue mas eficiente. Sin embargo, hubo una fuerte correlacion y concordancia geografica entre los 3 metodos, lo que indica un alto grado de traslape espacial. Esto sugiere que la seleccion de un metodo apropiado puede depender de los factores contextuales relacionados con el diseno de la pregunta de planificacion, y no solo la eficiencia.

We developed interpolated climate surfaces for global land areas (excluding Antarctica) at a spatial resolution of 30 arc s (often referred to as 1-km spatial resolution). The climate elements considered were monthly precipitation and mean, minimum, and maximum temperature. Input data were gathered from a variety of sources and, where possible, were restricted to records from the 1950–2000 period. We used the thin-plate smoothing spline algorithm implemented in the ANUSPLIN package for interpolation, using latitude, longitude, and elevation as independent variables. We quantified uncertainty arising from the input data and the interpolation by mapping weather station density, elevation bias in the weather stations, and elevation variation within grid cells and through data partitioning and cross validation. Elevation bias tended to be negative (stations lower than expected) at high latitudes but positive in the tropics. Uncertainty is highest in mountainous and in poorly sampled areas. Data partitioning showed high uncertainty of the surfaces on isolated islands, e.g. in the Pacific. Aggregating the elevation and climate data to 10 arc min resolution showed an enormous variation within grid cells, illustrating the value of high-resolution surfaces. A comparison with an existing data set at 10 arc min resolution showed overall agreement, but with significant variation in some regions. A comparison with two high-resolution data sets for the United States also identified areas with large local differences, particularly in mountainous areas. Compared to previous global climatologies, ours has the following advantages: the data are at a higher spatial resolution (400 times greater or more); more weather station records were used; improved elevation data were used; and more information about spatial patterns of uncertainty in the data is available. Owing to the overall low density of available climate stations, our surfaces do not capture of all variation that may occur at a resolution of 1 km, particularly of precipitation in mountainous areas. In future work, such variation might be captured through knowledgebased methods and inclusion of additional co-variates, particularly layers obtained through remote sensing. Copyright  2005 Royal Meteorological Society.

We analyse optimal and heuristic place prioritization algorithms for biodiversity conservation area network design which can use probabilistic data on the distribution of surrogates for biodiversity. We show how an Expected Surrogate Set Covering Problem (ESSCP) and a Maximal Expected Surrogate Covering Problem (MESCP) can be linearized for computationally efficient solution. For the ESSCP, we study the performance of two optimization software packages (XPRESS and CPLEX) and five heuristic algorithms based on traditional measures of complementarity and rarity as well as the Shannon and Simpson indices of α-diversity which are being used in this context for the first time. On small artificial data sets the optimal place prioritization algorithms often produced more economical solutions than the heuristic algorithms, though not always ones guaranteed to be optimal. However, with large data sets, the optimal algorithms often required long computation times and produced no better results than heuristic ones. Thus there is generally little reason to prefer optimal to heuristic algorithms with probabilistic data sets.

The Western Atlantic population of the American Oystercatcher (Haematopus palliatus) is of conservation concern, and much effort has been exerted to determine impacts of conservation efforts and identify important sites that need increased protection within the breeding range. Monitoring numbers of nesting pairs and distribution and habitat selection of nesting pairs provides data for conservation programs. The breeding population of American Oystercatchers in North Carolina has been estimated four times since 2004. Locations of territories and nests were recorded and mapped, and sites were categorized according to habitat type (barrier, dredged-material, or natural sand-shell or marsh island) and management responsibility (Federal, State, Audubon North Carolina, private landowner). Estimates indicate the number of nesting pairs changed slightly: 324 in 2004, 346 in 2007, 373 in 2010, and 351 in 2013. Total numbers of individual American Oystercatchers during the breeding season changed from 703...

Understanding the biotic consequences of Pleistocene range shifts and fragmentation remains a fundamental goal in historical biogeography and evolutionary biology. Here, we combine species distribution models (SDM) from the present and two late Quaternary time periods with multilocus genetic data (mitochondrial DNA and microsatellites) to evaluate the effect of climate-induced habitat shifts on population genetic structure in the Large-blotched Ensatina (Ensatina eschscholtzii klauberi), a plethodontid salamander endemic to middle and high-elevation conifer forest in the Transverse and Peninsular Ranges of southern California and northern Baja California. A composite SDM representing the range through time predicts two disjunct refugia, one in southern California encompassing the core of the species range and the other in the Sierra San Pedro Martir of northern Baja California at the southern limit of the species range. Based on our spatial model, we would expect a pattern of high connectivity among populations within the northern refugium and, conversely, a pattern of isolation due to long-term persistence of the Sierra San Pedro Martir population. Our genetic results are consistent with these predictions based on the hypothetical refugia in that (i) historical measures of population connectivity among stable areas are correlated with gene flow estimates; and (ii) there is strong geographical structure between separate refugia. These results provide evidence for the role of recent climatic change in shaping patterns of population persistence and connectivity within the Transverse and Peninsular Ranges, an evolutionary hotspot.

To better understand how environment shapes phenotypic and genetic variation, we explore the relationship between environmental variables across Ecuador and genetic and morphological variation in the wedge-billed woodcreeper (Glyphorynchus spirurus), a common Neotropical rainforest bird species. Generalized dissimilarity models show that variation in amplified fragment length polymorphism markers was strongly associated with environmental variables on both sides of the Andes, but could also partially be explained by geographic distance on the western side of the Andes. Tarsus, wing, tail, and bill lengths and bill depth were well explained by environmental variables on the western side of the Andes, whereas only tarsus length was well explained on the eastern side. Regions that comprise the highest rates of genetic and phenotypic change occur along steep elevation gradients in the Andes. Such environmental gradients are likely to be particularly important for maximizing adaptive diversity to minimize the impacts of climate change. Using a framework for conservation prioritization based on preserving ecological and evolutionary processes, we found little overlap between currently protected areas in Ecuador and regions we predicted to be important in maximizing adaptive variation.

Global conservation assessments require information on the distribution of biodiversity across the planet. Yet this information is often mapped at a very coarse spatial resolution relative to the scale of most land-use and management decisions. Furthermore, such mapping tends to focus selectively on better-known elements of biodiversity (e.g., vertebrates). We introduce a new approach to describing and mapping the global distribution of terrestrial biodiversity that may help to alleviate these problems. This approach focuses on estimating spatial pattern in emergent properties of biodiversity (richness and compositional turnover) rather than distributions of individual species, making it well suited to lesser-known, yet highly diverse, biological groups. We have developed a global biodiversity model linking these properties to mapped ecoregions and fine-scale environmental surfaces. The model is being calibrated progressively using extensive biological data sets for a wide variety of taxa. We also describe an analytical approach to applying our model in global conservation assessments, illustrated with a preliminary analysis of the representativeness of the world's protected-area system. Our approach is intended to complement, not compete with, assessments based on individual species of particular conservation concern.

Predicting where threatened species occur is useful for making informed conservation decisions. However, because they are usually rare, surveying threatened species is often expensive and time intensive. Here, we show how regions where common species exhibit high genetic and morphological divergence among populations can be used to predict the occurrence of species of conservation concern. Intraspecific variation of common species of birds, bats and frogs from Ecuador were found to be a significantly better predictor for the occurrence of threatened species than suites of environmental variables or the occurrence of amphibians and birds. Fully 93 per cent of the threatened species analysed had their range adequately represented by the geographical distribution of the morphological and genetic variation found in seven common species. Both higher numbers of threatened species and greater genetic and morphological variation of common species occurred along elevation gradients. Higher levels of intraspecific divergence may be the result of disruptive selection and/or introgression along gradients. We suggest that collecting data on genetic and morphological variation in common species can be a cost effective tool for conservation planning, and that future biodiversity inventories include surveying genetic and morphological data of common species whenever feasible.