Favourableness and connectivity of a Western Iberian landscape for the reintroduction of the iconic Iberian ibex Capra pyrenaica

A methodology framework for bipartite network modeling

The graph-theoretic based studies employing bipartite network approach mostly focus on surveying the statistical properties of the structure and behavior of the network systems under the domain of complex network analysis. They aim to provide the big-picture-view insights of a networked system by looking into the dynamic interaction and relationship among the vertices. Nonetheless, incorporating the features of individual vertex and capturing the dynamic interaction of the heterogeneous local rules governing each of them in the studies is lacking. The methodology in achieving this could hardly be found. Consequently, this study intends to propose a methodology framework that considers the influence of heterogeneous features of each node to the overall network behavior in modeling real-world bipartite network system. The proposed framework consists of three main stages with principal processes detailed in each stage, and three libraries of techniques to guide the modeling activities. It is iterative and process-oriented in nature and allows future network expansion. Two case studies from the domain of communicable disease in epidemiology and habitat suitability in ecology employing this framework are also presented. The results obtained suggest that the methodology could serve as a generic framework in advancing the current state of the art of bipartite network approach.

Distribution model transferability for a wide-ranging species, the Gray Wolf

Using existing data can be a reliable and cost-effective way to predict species distributions, and particularly useful for recovering or expanding species. We developed a current gray wolf (Canis lupus) distribution model for the western Great Lakes region, USA, and evaluated the spatial transferability of single-state models to the region. This study is the first assessment of transferability in a wide-ranging carnivore, as well as one of few developed for large spatial extents. We collected 3500 wolf locations from winter surveys in Minnesota (2017–2019), Wisconsin (2019–2020), and Michigan (2017–2020). We included 10 variables: proportion of natural cover, pastures, and crops; distance to natural cover, agriculture, developed land, and water; major and minor road density; and snowfall (1-km res.). We created a regional ensemble distribution by weight-averaging eight models based on their performance. We also developed single-state models, and estimated spatial transferability using two approaches: state cross-validation and extrapolation. We assessed performance by quantifying correlations, receiver operating characteristic curves (ROC), sensitivities, and two niche similarity indices. The regional area estimated to be most suitable for wolves during winter (threshold = maximum sensitivity/specificity) was 106,465 km² (MN = 48,083 km², WI = 27,757 km², MI = 30,625 km²) and correctly predicted 88% of wolf locations analyzed. Increasing natural cover and distance to crops were consistently important for determining regional and single-state wolf distribution. Extrapolation (vs. cross-validation) produced results with the greatest performance metrics, and were most similar to the regional model, yet good internal performance was unrelated to greater extrapolation performance. Factors influencing species distributions are scale-dependent and can vary across areas due to behavioral plasticity. When extending inferences beyond the current occurrence of individuals, assessing variation in ecology such as habitat selection, as well as methodological factors including model performance, will be critical to avoid poor scientific interpretations and develop effective conservation applications. In particular, accurate distribution models for recovering or recovered carnivores can be used to develop plans for habitat management, quantify potential of unoccupied habitat, assess connectivity modeling, and mitigate conflict, facilitating long-term species persistence.

Evaluating the legacy of multiple introductions of American martens on spatiotemporal patterns of genetic diversity

Species reintroductions are successful when established populations maintain both demographic stability and genetic diversity. Such a result may be obtained by ensuring both structural habitat connectivity and genetic connectivity among reintroduced and remnant populations. Nevertheless, prezygotic barriers such as assortative mating can prevent the flow of genetic material between populations, even when migration between populations is high. Limited gene flow may be particularly relevant for reintroductions that were sourced either from captive-bred populations or from disparate locations in the wild. American martens (Martes americana) have been reintroduced repeatedly in the Upper Midwestern United States in an effort to establish self-sustaining populations. We quantified levels of genetic diversity within and spatial genetic variance among four marten populations during two time periods separated by 10 years. Spatially informed and naïve discriminant analysis of principal components were used to assign individuals to populations. Results indicate that heterozygosity declined and inbreeding coefficients increased between the two collection periods, while genetic structure among populations also increased. Data are consistent with assortative mating contributing to reapportioning of genetic variation. Population assignment tests show that migration among populations is apparent, but admixture (based on cluster membership probabilities) is low and declined over time. Specifically, martens may be successfully dispersing between populations but a lack of admixture indicates a lack of reproductive contributions to genetic diversity by migrants. Because marten reintroductions in this region are well-documented and well-monitored, lessons can be derived from results to inform future reintroductions. We encourage a careful balance of supplementing genetic diversity via augmentation while avoiding translocation of animals from disparate populations that may result in reproductive isolation of migrants. In combination with the maintenance of a functionally connected landscape, this strategy would maximize the likelihood of a successful reintroduction in terms both of demography and genetics.

Reintroducing species when threats still exist: assessing the suitability of contemporary landscapes for island endemics

Reintroducing species into landscapes with persistent threats is a conservation challenge. Although historic threats may not be eliminated, they should be understood in the context of contemporary landscapes. Regenerating landscapes often contain newly emergent habitat, creating opportunities for reintroductions. The Endangered St Croix ground lizard Pholidoscelis polops was extirpated from the main island of St Croix, U.S. Virgin Islands, as a result of habitat conversion to agriculture and predation by the small Indian mongoose Herpestes auropunctatus. The species survived on two small cays and was later translocated to two islands. Since the 1950s, new land-cover types have emerged on St Croix, creating a matrix of suitable habitat throughout the island. Here we examined whether the new habitat is sufficient for a successful reintroduction of the St Croix ground lizard, utilizing three complementary approaches. Firstly, we compared a map from 1750 to the current landscape of St Croix and found statistical similarity of land-cover types. Secondly, we determined habitat suitability based on a binomial mixture population model developed as part of the programme monitoring the largest extant population of the St Croix ground lizard. We estimated the habitat to be sufficient for > 142,000 lizards to inhabit St Croix. Thirdly, we prioritized potential reintroduction sites and planned for reintroductions to take place during 2020–2023. Our case study demonstrates how changing landscapes alter the spatial configuration of threats to species, which can create opportunities for reintroduction. Presuming that areas of degraded habitat may never again be habitable could fail to consider how regenerating landscapes can support species recovery. When contemporary landscapes are taken into account, opportunities for reintroducing threatened species can emerge.

Applying circuit theory and landscape linkage maps to reintroduction planning for California Condors

Conservation practitioners are increasingly looking to species translocations as a tool to recover imperiled taxa. Quantitative predictions of where animals are likely to move when released into new areas would allow managers to better address the social, institutional, and ecological dimensions of conservation translocations. Using >5 million California condor (Gymnogyps californianus) occurrence locations from 75 individuals, we developed and tested circuit-based models to predict condor movement away from release sites. We found that circuit-based models of electrical current were well calibrated to the distribution of condor movement data in southern and central California (continuous Boyce Index = 0.86 and 0.98, respectively). Model calibration was improved in southern California when additional nodes were added to the circuit to account for nesting and feeding areas, where condor movement densities were higher (continuous Boyce Index = 0.95). Circuit-based projections of electrical current around a proposed release site in northern California comported with the condor’s historical distribution and revealed that, initially, condor movements would likely be most concentrated in northwestern California and southwest Oregon. Landscape linkage maps, which incorporate information on landscape resistance, complement circuit-based models and aid in the identification of specific avenues for population connectivity or areas where movement between populations may be constrained. We found landscape linkages in the Coast Range and the Sierra Nevada provided the most connectivity to a proposed reintroduction site in northern California. Our methods are applicable to conservation translocations for other species and are flexible, allowing researchers to develop multiple competing hypotheses when there are uncertainties about landscape or social attractants, or uncertainties in the landscape conductance surface.