An integrated approach for predicting fates of reintroductions with demographic data from multiple populations

We devised a novel approach to model reintroduced populations whereby demographic data collected from multiple sites are integrated into a Bayesian hierarchical model. Integrating data from multiple reintroductions allows more precise population-growth projections to be made, especially for populations for which data are sparse, and allows projections that account for random site-to-site variation to be made before new reintroductions are attempted. We used data from reintroductions of the North Island Robin (Petroica longipes), an endemic New Zealand passerine, to 10 sites where non-native mammalian predators are controlled. A comparison of candidate models that we based on deviance information criterion showed that rat-tracking rate (an index of rat density) was a useful predictor of robin fecundity and adult female survival, that landscape connectivity and a binary measure of whether sites were on a peninsula were useful predictors of apparent juvenile survival (probably due to differential dispersal away from reintroduction sites), and that there was unexplained random variation among sites in all demographic rates. We used the two best supported models to estimate the finite rate of increase (λ) for populations at each of the 10 sites, and for a proposed reintroduction site, under different levels of rat control. Only three of the reintroduction sites had λ distributions completely >1 for either model. At two sites, λ was expected to be >1 if rat-tracking rates were <5%. At the other five reintroduction sites, λ was predicted to be close to 1, and it was unclear whether growth was expected. Predictions of λ for the proposed reintroduction site were less precise than for other sites because distributions incorporated the full range of site-to-site random variation in vital rates. Our methods can be applied to any species for which postrelease data on demographic rates are available and potentially can be extended to model multiple species simultaneously.     

Relation between Occupancy and Abundance for a Territorial Species,the California Spotted Owl

Land and resource managers often use detection–nondetection surveys to monitor the populations of species that may be affected by factors such as habitat alteration, climate change, and biological invasions. Relative to mark‐recapture studies, using detection–nondetection surveys is more cost‐effective, and recent advances in statistical analyses allow the incorporation of detection probability, covariates, and multiple seasons. We examined the efficacy of using detection–nondetection data (relative to mark‐recapture data) for monitoring population trends of a territorial species, the California Spotted Owl (Strix occidentalis occidentalis). We estimated and compared the finite annual rates of population change (λ_t) and the resulting realized population change (Δ_t) from both occupancy and mark‐recapture data collected over 18 years (1993–2010). We used multiseason, robust‐design occupancy models to estimate that territory occupancy declined during our study (Δ_t = 0.702, 95% CI 0.552–0.852) due to increasing territory extinction rates ( = 0.019 [SE 0.012]; = 0.134 [SE 0.043]) and decreasing colonization rates ( = 0.323 [SE 0.124]; = 0.242 [SE 0.058]). We used Pradel's temporal‐symmetry model for mark‐recapture data to estimate that the population trajectory closely matched the trends in territory occupancy (Δ_t = 0.725, 95% CI 0.445–1.004). Individual survival was constant during our study ( = 0.816 [SE 0.020]; = 0.815 [SE 0.019]), whereas recruitment declined slightly ( = 0.195 [SE 0.032]; = 0.160 [SE 0.023]). Thus, we concluded that detection–nondetection data can provide reliable inferences on population trends, especially when funds preclude more intensive mark‐recapture studies. Relación entre Ocupación y Abundancia en una Especie Territorial, el Búho Moteado de California     

Effects of Multiple Levels of Social Organization on Survival and Abundance

Abstract: Identifying how social organization shapes individual behavior, survival, and fecundity of animals that live in groups can inform conservation efforts and improve forecasts of population abundance, even when the mechanism responsible for group‐level differences is unknown. We constructed a hierarchical Bayesian model to quantify the relative variability in survival rates among different levels of social organization (matrilines and pods) of an endangered population of killer whales (Orcinus orca). Individual killer whales often participate in group activities such as prey sharing and cooperative hunting. The estimated age‐specific survival probabilities and survivorship curves differed considerably among pods and to a lesser extent among matrilines (within pods). Across all pods, males had lower life expectancy than females. Differences in survival between pods may be caused by a combination of factors that vary across the population's range, including reduced prey availability, contaminants in prey, and human activity. Our modeling approach could be applied to demographic rates for other species and for parameters other than survival, including reproduction, prey selection, movement, and detection probabilities.     

Living at the Edge: Local versus Positional Factors in the Long‐Term Population Dynamics of an Endangered Orchid

Abstract: Populations at the margin of geographic ranges of distribution have been considered more vulnerable than central ones, but recent reviews have caste doubt on this generalization. We examined the reproductive and demographic performance of a rare Euroasiatic orchid (Cypripedium calceolus) at its southwesterly range limit and compared our findings with those of previous studies of nine central populations at the center of the orchid's range. We sought to test the central‐marginal model and to evaluate factors involved in long‐term performance of forest Eurosiberian species with peripheral populations in southern European mountains. We characterized (structure, temporal fluctuations, herbivory, reproductive success, and recruitment at different habitats) four Pyrenean populations of C. calceolus of different sizes (5–3500 ramets) and monitored three of them for up to 13 years. Two quantitative stochastic models (count data and matrix models) were used to assess population trends and viability and the effect of herbivory. Contrary to expectations, and despite the negative effect of sporadic events of herbivory, the peripheral populations we studied (except the smallest one) performed similarly or better than populations occurring in central part of the species’ range in terms of reproductive success and population growth rates. Landscape changes over the last 50 years suggest that natural reforestation could be involved in the success of this plant at its southern limit. Forest expansion in the mountain regions of southern Europe may provide new opportunities for plants with geographic distributions centered mainly at higher latitudes and give some hope for their recovery in future scenarios dominated by biodiversity loss.     

Re-creating missing population baselines for Pacific reef sharks

Sharks and other large predators are scarce on most coral reefs, but studies of their historical ecology provide qualitative evidence that predators were once numerous in these ecosystems. Quantifying density of sharks in the absence of humans (baseline) is, however, hindered by a paucity of pertinent time-series data. Recently researchers have used underwater visual surveys, primarily of limited spatial extent or nonstandard design, to infer negative associations between reef shark abundance and human populations. We analyzed data from 1607 towed-diver surveys (>1 ha transects surveyed by observers towed behind a boat) conducted at 46 reefs in the central-western Pacific Ocean, reefs that included some of the world's most pristine coral reefs. Estimates of shark density from towed-diver surveys were substantially lower (<10%) than published estimates from surveys along small transects (<0.02 ha), which is not consistent with inverted biomass pyramids (predator biomass greater than prey biomass) reported by other researchers for pristine reefs. We examined the relation between the density of reef sharks observed in towed-diver surveys and human population in models that accounted for the influence of oceanic primary productivity, sea surface temperature, reef area, and reef physical complexity. We used these models to estimate the density of sharks in the absence of humans. Densities of gray reef sharks (Carcharhinus amblyrhynchos), whitetip reef sharks (Triaenodon obesus), and the group "all reef sharks" increased substantially as human population decreased and as primary productivity and minimum sea surface temperature (or reef area, which was highly correlated with temperature) increased. Simulated baseline densities of reef sharks under the absence of humans were 1.1-2.4/ha for the main Hawaiian Islands, 1.2-2.4/ha for inhabited islands of American Samoa, and 0.9-2.1/ha for inhabited islands in the Mariana Archipelago, which suggests that density of reef sharks has declined to 3-10% of baseline levels in these areas.     

Potential Misuse of Avian Density as a Conservation Metric

Abstract: Effective conservation metrics are needed to evaluate the success of management in a rapidly changing world. Reproductive rates and densities of breeding birds (as a surrogate for reproductive rate) have been used to indicate the quality of avian breeding habitat, but the underlying assumptions of these metrics rarely have been examined. When birds are attracted to breeding areas in part by the presence of conspecifics and when breeding in groups influences predation rates, the effectiveness of density and reproductive rate as indicators of habitat quality is reduced. It is beneficial to clearly distinguish between individual‐ and population‐level processes when evaluating habitat quality. We use the term reproductive rate to refer to both levels and further distinguish among levels by using the terms per capita fecundity (number of female offspring per female per year, individual level) and population growth rate (the product of density and per capita fecundity, population level). We predicted how density and reproductive rate interact over time under density‐independent and density‐dependent scenarios, assuming the ideal free distribution model of how birds settle in breeding habitats. We predicted population density of small populations would be correlated positively with both per capita fecundity and population growth rate due to the Allee effect. For populations in the density‐dependent growth phase, we predicted no relation between density and per capita fecundity (because individuals in all patches will equilibrate to the same success rate) and a positive relation between density and population growth rate. Several ecological theories collectively suggest that positive correlations between density and per capita fecundity would be difficult to detect. We constructed a decision tree to guide interpretation of positive, neutral, nonlinear, and negative relations between density and reproductive rates at individual and population levels.     

Effects of Land‐Use Change on Community Composition of Tropical Amphibians and Reptiles in Sulawesi,Indonesia

Abstract: Little is known about the effects of anthropogenic land‐use change on the amphibians and reptiles of the biodiverse tropical forests of Southeast Asia. We studied a land‐use modification gradient stretching from primary forest, secondary forest, natural‐shade cacao agroforest, planted‐shade cacao agroforest to open areas in central Sulawesi, Indonesia. We determined species richness, abundance, turnover, and community composition in all habitat types and related these to environmental correlates, such as canopy heterogeneity and thickness of leaf litter. Amphibian species richness decreased systematically along the land‐use modification gradient, but reptile richness and abundance peaked in natural‐shade cacao agroforests. Species richness and abundance patterns across the disturbance gradient were best explained by canopy cover and leaf‐litter thickness in amphibians and by canopy heterogeneity and cover in reptiles. Amphibians were more severely affected by forest disturbance in Sulawesi than reptiles. Heterogeneous canopy cover and thick leaf litter should be maintained in cacao plantations to facilitate the conservation value for both groups. For long‐term and sustainable use of plantations, pruned shade trees should be permanently kept to allow rejuvenation of cacao and, thus, to prevent repeated forest encroachment.     

Use of Community‐Composition Data to Predict the Fecundity and Abundance of Species

Abstract: Species distribution models are critical tools for the prediction of invasive species spread and conservation of biodiversity. The majority of species distribution models have been built with environmental data. Community ecology theory suggests that species co‐occurrence data could also be used to predict current and potential distributions of species. Species assemblages are the products of biotic and environmental constraints on the distribution of individual species and as a result may contain valuable information for niche modeling. We compared the predictive ability of distribution models of annual grassland plants derived from either environmental or community‐composition data. Composition‐based models were built with the presence or absence of species at a site as predictors of site quality, whereas environment‐based models were built with soil chemistry, moisture content, above‐ground biomass, and solar radiation as predictors. The reproductive output of experimentally seeded individuals of 4 species and the abundance of 100 species were used to evaluate the resulting models. Community‐composition data were the best predictors of both the site‐specific reproductive output of sown individuals and the site‐specific abundance of existing populations. Successful community‐based models were robust to omission of data on the occurrence of rare species, which suggests that even very basic survey data on the occurrence of common species may be adequate for generating such models. Our results highlight the need for increased public availability of ecological survey data to facilitate community‐based modeling at scales relevant to conservation.     

Use of Spatial Capture‐Recapture Modeling and DNA Data to Estimate Densities of Elusive Animals

Abstract: Assessment of abundance, survival, recruitment rates, and density (i.e., population assessment) is especially challenging for elusive species most in need of protection (e.g., rare carnivores). Individual identification methods, such as DNA sampling, provide ways of studying such species efficiently and noninvasively. Additionally, statistical methods that correct for undetected animals and account for locations where animals are captured are available to efficiently estimate density and other demographic parameters. We collected hair samples of European wildcat (Felis silvestris) from cheek‐rub lure sticks, extracted DNA from the samples, and identified each animals’ genotype. To estimate the density of wildcats, we used Bayesian inference in a spatial capture‐recapture model. We used WinBUGS to fit a model that accounted for differences in detection probability among individuals and seasons and between two lure arrays. We detected 21 individual wildcats (including possible hybrids) 47 times. Wildcat density was estimated at 0.29/km² (SE 0.06), and 95% of the activity of wildcats was estimated to occur within 1.83 km from their home‐range center. Lures located systematically were associated with a greater number of detections than lures placed in a cell on the basis of expert opinion. Detection probability of individual cats was greatest in late March. Our model is a generalized linear mixed model; hence, it can be easily extended, for instance, to incorporate trap‐ and individual‐level covariates. We believe that the combined use of noninvasive sampling techniques and spatial capture‐recapture models will improve population assessments, especially for rare and elusive animals.     

Assessing the Risk of Ships Striking Large Whales in Marine Spatial Planning

Marine spatial planning provides a comprehensive framework for managing multiple uses of the marine environment and has the potential to minimize environmental impacts and reduce conflicts among users. Spatially explicit assessments of the risks to key marine species from human activities are a requirement of marine spatial planning. We assessed the risk of ships striking humpback (Megaptera novaeangliae), blue (Balaenoptera musculus), and fin (Balaenoptera physalus) whales in alternative shipping routes derived from patterns of shipping traffic off Southern California (U.S.A.). Specifically, we developed whale‐habitat models and assumed ship‐strike risk for the alternative shipping routes was proportional to the number of whales predicted by the models to occur within each route. This definition of risk assumes all ships travel within a single route. We also calculated risk assuming ships travel via multiple routes. We estimated the potential for conflict between shipping and other uses (military training and fishing) due to overlap with the routes. We also estimated the overlap between shipping routes and protected areas. The route with the lowest risk for humpback whales had the highest risk for fin whales and vice versa. Risk to both species may be ameliorated by creating a new route south of the northern Channel Islands and spreading traffic between this new route and the existing route in the Santa Barbara Channel. Creating a longer route may reduce the overlap between shipping and other uses by concentrating shipping traffic. Blue whales are distributed more evenly across our study area than humpback and fin whales; thus, risk could not be ameliorated by concentrating shipping traffic in any of the routes we considered. Reducing ship‐strike risk for blue whales may be necessary because our estimate of the potential number of strikes suggests that they are likely to exceed allowable levels of anthropogenic impacts established under U.S. laws. Evaluación del Riesgo de Colisiones de Barcos y Ballenas en la Planificación Marina Espacial     

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.     

A Behaviorally Explicit Demographic Model Integrating Habitat Selection and Population Dynamics in California Sea Lions

Abstract: Although there has been a call for the integration of behavioral ecology and conservation biology, there are few tools currently available to achieve this integration. Explicitly including information about behavioral strategies in population viability analyses may enhance the ability of conservation biologists to understand and estimate patterns of extinction risk. Nevertheless, most behavioral‐based PVA approaches require detailed individual‐based data that are rarely available for imperiled species. We present a mechanistic approach that incorporates spatial and demographic consequences of behavioral strategies into population models used for conservation. We developed a stage‐structured matrix model that includes the costs and benefits of movement associated with 2 habitat‐selection strategies (philopatry and direct assessment). Using a life table for California sea lions (Zalophus californianus), we explored the sensitivity of model predictions to the inclusion of these behavioral parameters. Including behavioral information dramatically changed predicted population sizes, model dynamics, and the expected distribution of individuals among sites. Estimated population sizes projected in 100 years diverged up to 1 order of magnitude among scenarios that assumed different movement behavior. Scenarios also exhibited different model dynamics that ranged from stable equilibria to cycles or extinction. These results suggest that inclusion of behavioral data in viability models may improve estimates of extinction risk for imperiled species. Our approach provides a simple method for incorporating spatial and demographic consequences of behavioral strategies into population models and may be easily extended to other species and behaviors to understand the mechanisms of population dynamics for imperiled populations.     

An Adaptive‐Management Framework for Optimal Control of Hiking Near Golden Eagle Nests in Denali National Park

Abstract: Unintended effects of recreational activities in protected areas are of growing concern. We used an adaptive‐management framework to develop guidelines for optimally managing hiking activities to maintain desired levels of territory occupancy and reproductive success of Golden Eagles (Aquila chrysaetos) in Denali National Park (Alaska, U.S.A.). The management decision was to restrict human access (hikers) to particular nesting territories to reduce disturbance. The management objective was to minimize restrictions on hikers while maintaining reproductive performance of eagles above some specified level. We based our decision analysis on predictive models of site occupancy of eagles developed using a combination of expert opinion and data collected from 93 eagle territories over 20 years. The best predictive model showed that restricting human access to eagle territories had little effect on occupancy dynamics. However, when considering important sources of uncertainty in the models, including environmental stochasticity, imperfect detection of hares on which eagles prey, and model uncertainty, restricting access of territories to hikers improved eagle reproduction substantially. An adaptive management framework such as ours may help reduce uncertainty of the effects of hiking activities on Golden Eagles.     

Effectiveness of conservation easements in agricultural regions

Conservation easements are a standard technique for preventing habitat loss, particularly in agricultural regions with extensive cropland cultivation, yet little is known about their effectiveness. I developed a spatial econometric approach to propensity‐score matching and used the approach to estimate the amount of habitat loss prevented by a grassland conservation easement program of the U.S. federal government. I used a spatial autoregressive probit model to predict tract enrollment in the easement program as of 2001 based on tract agricultural suitability, habitat quality, and spatial interactions among neighboring tracts. Using the predicted values from the model, I matched enrolled tracts with similar unenrolled tracts to form a treatment group and a control group. To measure the program's impact on subsequent grassland loss, I estimated cropland cultivation rates for both groups in 2014 with a second spatial probit model. Between 2001 and 2014, approximately 14.9% of control tracts were cultivated and 0.3% of treated tracts were cultivated. Therefore, approximately 14.6% of the protected land would have been cultivated in the absence of the program. My results demonstrate that conservation easements can significantly reduce habitat loss in agricultural regions; however, the enrollment of tracts with low cropland suitability may constrain the amount of habitat loss they prevent. My results also show that spatial econometric models can improve the validity of control groups and thereby strengthen causal inferences about program effectiveness in situations when spatial interactions influence conservation decisions.     

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.