Trade-offs and efficiencies in optimal budget-constrained multispecies corridor networks

Restoration of linear disturbances from oil-and-gas exploration in boreal landscapes: How can network models help?

In western Canada, decades of oil-and-gas exploration have fragmented boreal landscapes with a dense network of linear forest disturbances (seismic lines). These seismic lines are implicated in the decline in wildlife populations that are adapted to function in unfragmented forest landscapes. In particular, anthropogenic disturbances have led to a decline of woodland caribou populations due to increasing predator access to core caribou habitat. Restoration of seismic lines aims to reduce the landscape fragmentation and stop the decline of caribou populations. However, planning restoration in complex landscapes can be challenging because it must account for a multitude of diverse aspects. To assist with restoration planning, we present a spatial network optimization approach that selects restoration locations in a fragmented landscape while addressing key environmental and logistical constraints. We applied the model to develop restoration scenarios in the Redrock-Prairie Creek caribou range in northwestern Alberta, Canada, which includes a combination of caribou habitat and active oil-and-gas and timber extraction areas. Our study applies network optimization at two distinct scales to address both the broad-scale restoration policy planning and project-level constraints at the level of individual forest sites. We first delineated a contiguous set of coarse-scale regions where restoration is most cost-effective and used this solution to solve a fine-scale network optimization model that addresses environmental and logistical planning constraints at the level of forest patches. Our two-tiered approach helps address the challenges of fine-scale spatial optimization of restoration activities. An additional coarse-scale optimization step finds a feasible starting solution for the fine-scale restoration problem, which serves to reduce the time to find an optimal solution. The added coarse-scale spatial constraints also make the fine-scale restoration solution align with the coarse-scale landscape features, which helps address the broad-scale restoration policies. The approach is generalizable and applicable to assist restoration planning in other regions fragmented by oil-and-gas activities.

Recolonization following past persecution questions the importance of persistent snow cover as a range limiting factor for wolverines

Globally, climate is changing rapidly, which causes shifts in many species' distributions, stressing the need to understand their response to changing environmental conditions to inform conservation and management. Northern latitudes are expected to experience strongest changes in climate, with milder winters and decreasing snow cover. The wolverine (Gulo gulo) is a circumpolar, threatened carnivore distributed in northern tundra, boreal, and subboreal habitats. Previous studies have suggested that wolverine distribution and reproduction are constrained by a strong association with persistent spring snow cover. We assess this hypothesis by relating spatial distribution of 1589 reproductive events, a fitness-related proxy for female reproduction and survival, to snow cover over two decades. Wolverine distribution has increased and number of reproductive events increased 20 times in areas lacking spring snow cover during our study period, despite low monitoring effort where snow is sparse. Thus, the relationship between reproductive events and persistent spring snow cover weakened during this period. These findings show that wolverine reproductive success and hence distribution are less dependent on spring snow cover than expected. This has important implications for projections of future habitat availability, and thus distribution, of this threatened species. Our study also illustrates how past persecution, or other factors, that have restricted species distribution to remote areas can mask actual effects of environmental parameters, whose importance reveals when populations expand beyond previously restricted ranges. Overwhelming evidence shows that climate change is affecting many species and ecological processes, but forecasting potential consequences on a given species requires longitudinal data to revisit hypotheses and reassess the direction and magnitude of climate effects with new data. This is especially important for conservation-oriented management of species inhabiting dynamic systems where environmental factors and human activities interact, a common scenario for many species in different ecosystems around the globe.

Lahaul–Zanskar–Sham Valley Corridor in Indian Trans Himalayan Region Facilitates Dispersal and Gene Flow in Himalayan Ibex

Wildlife corridors that connect mosaic habitats in heterogeneous mountainous landscapes can be of high significance as they facilitate the genetic and demographic stability of free-ranging populations. Peripheral populations of widespread species are usually ignored in conservation planning. However, these populations retain locally common alleles and are genetic reservoir under the changing climatic conditions. Capra sibirica has widespread distribution, and its southern peripheral population is distributed in the Indian trans-Himalayan region (ITR). In the present study, we studied the spatial distribution and genetic make-up of Himalayan ibex from the ITR following the landscape genetics approach. We obtained 16 haplotypes at the mitochondrial d-loop region and found a stable demography in the past with a recent decline. With 10 nuclear microsatellites, we ascertained 111 unique individuals assigned into two clusters following Bayesian and non-Bayesian clustering analysis with several admixed individuals. We also recorded 25 first-generation migrants that reflected relatively high dispersal and gene-flow across the range. We identified a 19,835 sq.km suitable area with 13,311 sq.km in Ladakh and 6524 sq.km in Lahaul-Spiti. We identified a novel movement corridor for Himalayan ibex across the Lahaul–Zanskar–Sham valley (L–Z–SV) that displayed a fairly good conductance with low genetic divergence among the samples collected on the L–Z–SV corridor. We propose declaring a protected area in the Lahaul and Kargil districts to prioritize dedicated conservation efforts for the Himalayan ibex and other sympatric ungulates that impart a major role in the diet of large carnivore and balancing ecosystem services in the trans-Himalayan region.

A multispecies corridor in a fragmented landscape: Evaluating effectiveness and identifying high-priority target areas

While Misiones, Argentina contains one of the largest remnants of Upper Paraná Atlantic Forest ecoregion, one of the world's biodiversity hotspots, only ~50% of this native forest is protected. Each protected area is at risk of becoming an island of native forest surrounded by a matrix of altered habitats due to ongoing land conversion. In an effort to maximize long-term connectivity between existing protected areas, DeMatteo [1] used a multifaceted cost analysis to determine the optimal location for the region's first multispecies corridor using noninvasive data on jaguars (Panthera onca), pumas (Puma concolor), ocelots (Leopardus pardalis), southern tiger cats (Leopardus guttulus), and bush dogs (Speothos venaticus). This work builds on this framework by integrating new field data that broadens the scope of species-specific data across the region's heterogeneous landscape, which varies in vegetation, disturbance, human proximity, and protective status. In addition, two different land use layers are compared across the distributions of the five carnivores, the overlap in their independent distributions, and their relationship to the multispecies corridor. Interpretation of these land use data to species-specific habitat suitability goes beyond DeMatteo [1], with a subdivision of suitability into marginal and optimal areas. This refined scale allows a reanalysis of key areas in the multispecies corridor, where connectivity was previously defined as at highly-at-risk, allowing for a more directed development of management strategies. These analyses and their interpretation extend beyond northern-central Misiones, as the threats are not unique to this region. The need to develop management strategies that balance human-wildlife needs will continue to grow as humans expand their footprint. The techniques applied in this analysis provide a way to identify key areas that require specific management strategies, either through restoration, protection, or a combination of both.

Improving biodiversity protection through artificial intelligence

Over a million species face extinction, urging the need for conservation policies that maximize the protection of biodiversity to sustain its manifold contributions to people. Here we present a novel framework for spatial conservation prioritization based on reinforcement learning that consistently outperforms available state-of-the-art software using simulated and empirical data. Our methodology, CAPTAIN (Conservation Area Prioritization Through Artificial INtelligence), quantifies the trade-off between the costs and benefits of area and biodiversity protection, allowing the exploration of multiple biodiversity metrics. Under a limited budget, our model protects substantially more species from extinction than areas selected randomly or naively (such as based on species richness). CAPTAIN achieves substantially better solutions with empirical data than alternative software, meeting conservation targets more reliably and generating more interpretable prioritization maps. Regular biodiversity monitoring, even with a degree of inaccuracy characteristic of citizen science surveys, substantially improves biodiversity outcomes. Artificial intelligence holds great promise for improving the conservation and sustainable use of biological and ecosystem values in a rapidly changing and resourcelimited world.

Predicting wildlife corridors for multiple species in an East African ungulate community

Wildlife corridors are typically designed for single species, yet holistic conservation approaches require corridors suitable for multiple species. Modelling habitat linkages for wildlife is based on several modelling steps (each involving multiple choices), and in the case of multi-species corridors, an approach to optimize single species corridors to few or a single functional corridor for multiple species. To model robust corridors for multiple species and simultaneously evaluate the impact of methodological choices, we develop a multi-method approach to delineate corridors that effectively capture movement of multiple wildlife species, while limiting the area required. Using wildlife presence data collected along ground-based line transects between Lake Manyara and Tarangire National Parks, Tanzania, we assessed species-habitat association in both ensemble and stacked species distribution frameworks and used these to estimate linearly and non-linearly scaled landscape resistances for seven ungulate species. We evaluated habitat suitability and least-cost and circuit theory-based connectivity models for each species individually and generated a multi-species corridor. Our results revealed that species-habitat relationships and subsequent corridors differed across species, but the pattern of predicted landscape connectivity across the study area was similar for all seven species regardless of method (circuit theory or least-cost) and scaling of the habitat suitability-based cost surface (linear or non-linear). Stacked species distribution models were highly correlated with the seven species for all model outputs (r = 0.79 to 0.97), while having the greatest overlap with the individual species least-cost corridors (linear model: 61.6%; non-linear model: 60.2%). Zebra was the best single-species proxy for landscape connectivity. Overall, we show that multi-species corridors based on stacked species distribution models achieve relatively low cumulative costs for savanna ungulates as compared to their respective single-species corridors. Given the challenges and costs involved in acquiring data and parameterizing corridor models for multiple species, zebra may act as a suitable proxy species for ungulate corridor conservation in this system.

A biogeographical study of red listed lichen species at temporal and spatial scales within protected and non-protected areas

The present study is focused on the temporal and spatial distribution of red listed lichen (RLL) species identified in both non-protected areas (NPAs) and protected areas (PAs) in Romania. This study revealed different scenarios of RLL based on two major patterns: (1) the fate of RLL before and after their designation in the red list in Romania and (2) the fate of RLL before and after the designation of PAs in Romania. Generally, the occurrences of RLL were well represented in time and space in both NPAs and PAs through geomorphological and biogeographical units. In particular, the occurrences of RLL were well represented, especially in hilly areas within PAs before and after their official designation, and this was an important aspect over a long period of time. Although NPAs were not less important regarding the occurrences of RLL species, it was observed that they followed the same pattern as PAs, namely, they were well represented in hilly areas and over a long period of time. The bioregions were significant for RLL species in both NPAs (continental and stepic) and PAs (continental, panonic, and stepic). As a significant finding of this study, NPAs and PAs should be subjected to an adequate conservation regime due to their biotical traditional heritage.

A framework for collaborative wolverine connectivity conservation

Maintaining connectivity between high-elevation public lands is important for wolverines and other species of conservation concern. This work represents the first effort to prioritize wolverine connectivity under future climate conditions using a systematic conservation planning framework. We optimized 10, 15, 20, and 50% of habitat features for wolverines using integer linear programming. We identified 369 privately owned areas in the 10% solution, 572 in the 15% solution, 822 in the 20% solution, and 3,996 in the 50% solution where voluntary landowner easements would improve the long-term landscape functionality for wolverine connectivity. The median estimated easements ranged from $8,762 to $12,220 across the four solutions (total costs $14,874,371 to $196,346,714). Overall, this effort demonstrates the utility of optimization problems for conserving connectivity, provides a proactive tool to engage potential collaborators, identifies easements that will likely protect various subalpine species, and offers a framework for the conservation of additional species.

Multispecies landscape functional connectivity enhances local bird species' diversity in a highly fragmented landscape

Local species assemblages are likely the result of habitat and landscape filtering. However, there is still limited knowledge on how landscape functional connectivity complements habitat attributes in mediating local species assemblages in real-world fragmented landscapes. In this study, we set up a non-manipulative experimental design in a standard production forest to demonstrate how functional connectivity determines the spatial distribution of a bird community. We test single- and multispecies spatially explicit, landscape functional connectivity models framed within the circuit theory, considering also patch attributes describing habitat size and quality, to weight their effects on species occurrence and community assemblage. We found that single-species functional connectivity effects contributed positively for occurrence of each species. However, they rarely provided competing alternatives in predicting community parameters when compared to multispecies connectivity models. Incorporating multispecies connectivity showed more consistent effects for all community parameters, than single-species models, since the overlap between species' dispersal abilities in the landscape shows poor agreement. Habitat size and quality, though less important, were also determinant in explaining community parameters while possibly relating to the provision of suitable nesting and foraging conditions. Both habitat and landscape filters concur to govern community assembly, though likely influencing different processes: while landscape connectivity determines which species can reach a patch, habitat quality determines which species settle in the patch. Our results also suggest that surrogating multispecies connectivity from single species has potential to source bias by assuming species perceive landscape and its barriers similarly. Inference on this issue must be gathered from as much species as possible.

Planning for Dynamic Connectivity: Operationalizing Robust Decision-Making and Prioritization Across Landscapes Experiencing Climate and Land-Use Change

Preserving landscape connectivity is one of the most frequently recommended strategies to address the synergistic threats of climate change, habitat fragmentation, and intensifying disturbances. Although assessments to develop plans for linked and connected landscapes in response to climate and land-use change have been increasingly employed in the last decade, efforts to operationalize and implement these plans have been limited. Here, we present a framework using existing, available biological data to design an implementable, comprehensive multispecies connectivity plan. This framework uses a scenario-based approach to consider how ecosystems, habitats, and species may need to adapt to future conditions with an ensemble of connectivity models. We use the south coast ecoregion of California as an example to evaluate and prioritize linkages by combining linked metapopulation models and key landscape features (e.g., conservation planning status and implementation feasibility) to identify and prioritize a multispecies linkage network. Our analyses identified approximately 30,000 km2 of land, roughly one-fifth of our study area, where actions to preserve or enhance connectivity may support climate adaptation, nearly half of which is already conserved. By developing and implementing a dynamic connectivity assessment with an eye towards projected changes, our analysis demonstrates how dynamic connectivity can be integrated into feasible regional conservation and management plans that account for demographic as well as landscape change. We observed overlap across multiple models, reinforcing the importance of areas that appeared across methods. We also identified unique areas important for connectivity captured by our complementary models. By integrating multiple approaches, the resultant linkage network is robust, building on the strengths of a variety of methods to identify model consensus and reduce uncertainty. By linking quantitative connectivity metrics with prioritized areas for conservation, our approach supports transparent and robust decision-making for landscape planning, despite uncertainties of climate and land-use change.

Supporting Adaptive Connectivity in Dynamic Landscapes

A central tenet of landscape conservation planning is that natural communities can be supported by a connected landscape network that supports many species and habitat types. However, as the planning environment, ecological conditions, and risks and stressors change over time, the areas needed to support landscape connectivity may also shift. We demonstrate an approach designed to assess functional and structural connectivity of an established protected area network that has experienced landscape and planning changes over time. Here we present an approach designed to inform adaptive planning for connectivity with a complementary suite of analytical techniques. Using existing occurrence, movement, and genetic data for six focal species, we create a spatially explicit connectivity assessment based on landscape resistance, paired with a landscape feature geodiversity analysis. Although factors such as cost, conservation goals, and land management strategies must be taken into account, this approach provides a template for leveraging available empirical data and robust analyses to evaluate and adapt planning for protected area networks that can preserve and promote both functional and structural connectivity in dynamic landscapes.

Optimizing conservation planning for multiple cohabiting species

Conservation planning often involves multiple species occupying large areas including habitat sites with varying characteristics. For a given amount of financial resources, designing a spatially coherent nature reserve system that provides the best possible protection to targeted species is an important ecological and economic problem. In this paper, we address this problem using optimization methods. Incorporating spatial criteria in an optimization framework considering spatial habitat needs of multiple species poses serious challenges because of modeling and computational complexities. We present a novel linear integer programming model to address this issue considering spatial contiguity and compactness of the reserved area. The model uses the concept of path in graph theory to ensure contiguity and minimizes the sum of distances between selected sites and a central site in individual reserves to promote compactness. We test the computational efficiency of the model using randomly generated data sets. The results show that the model can be solved quite efficiently in most cases. We also present an empirical application of the model to simultaneous protection of two cohabiting species, Gopher Tortoise and Gopher Frogs, in a military installation in Georgia, USA.

Tradeoffs in the value of biodiversity feature and cost data in conservation prioritization

Decision-support tools are commonly used to maximize return on investments (ROI) in conservation. We evaluated how the relative value of information on biodiversity features and land cost varied with data structure and variability, attributes of focal species and conservation targets, and habitat suitability thresholds for contrasting bird communities in the Pacific Northwest of North America. Specifically, we used spatial distribution maps for 20 bird species, land values, and an integer linear programming model to prioritize land units (1 km²) that met conservation targets at the lowest estimated cost (hereafter ‘efficiency’). Across scenarios, the relative value of biodiversity data increased with conservation targets, as higher thresholds for suitable habitat were applied, and when focal species occurred disproportionately on land of high assessed value. Incorporating land cost generally improved planning efficiency, but at diminishing rates as spatial variance in biodiversity features relative to land cost increased. Our results offer a precise, empirical demonstration of how spatially-optimized planning solutions are influenced by spatial variation in underlying feature layers. We also provide guidance to planners seeking to maximize efficiency in data acquisition and resolve potential trade-offs when setting targets and thresholds in financially-constrained, spatial planning efforts aimed at maximizing ROI in biodiversity conservation.

Reserve design to optimize functional connectivity and animal density

Ecological distance-based spatial capture-recapture models (SCR) are a promising approach for simultaneously estimating animal density and connectivity, both of which affect spatial population processes and ultimately species persistence. We explored how SCR models can be integrated into reserve-design frameworks that explicitly acknowledge both the spatial distribution of individuals and their space use resulting from landscape structure. We formulated the design of wildlife reserves as a budget-constrained optimization problem and conducted a simulation to explore 3 different SCR-informed optimization objectives that prioritized different conservation goals by maximizing the number of protected individuals, reserve connectivity, and density-weighted connectivity. We also studied the effect on our 3 objectives of enforcing that the space-use requirements of individuals be met by the reserve for individuals to be considered conserved (referred to as home-range constraints). Maximizing local population density resulted in fragmented reserves that would likely not aid long-term population persistence, and maximizing the connectivity objective yielded reserves that protected the fewest individuals. However, maximizing density-weighted connectivity or preemptively imposing home-range constraints on reserve design yielded reserves of largely spatially compact sets of parcels covering high-density areas in the landscape with high functional connectivity between them. Our results quantify the extent to which reserve design is constrained by individual home-range requirements and highlight that accounting for individual space use in the objective and constraints can help in the design of reserves that balance abundance and connectivity in a biologically relevant manner.

Circuit-theory applications to connectivity science and conservation

Conservation practitioners have long recognized ecological connectivity as a global priority for preserving biodiversity and ecosystem function. In the early years of conservation science, ecologists extended principles of island biogeography to assess connectivity based on source patch proximity and other metrics derived from binary maps of habitat. From 2006 to 2008, the late Brad McRae introduced circuit theory as an alternative approach to model gene flow and the dispersal or movement routes of organisms. He posited concepts and metrics from electrical circuit theory as a robust way to quantify movement across multiple possible paths in a landscape, not just a single least-cost path or corridor. Circuit theory offers many theoretical, conceptual, and practical linkages to conservation science. We reviewed 459 recent studies citing circuit theory or the open-source software Circuitscape. We focused on applications of circuit theory to the science and practice of connectivity conservation, including topics in landscape and population genetics, movement and dispersal paths of organisms, anthropogenic barriers to connectivity, fire behavior, water flow, and ecosystem services. Circuit theory is likely to have an effect on conservation science and practitioners through improved insights into landscape dynamics, animal movement, and habitat-use studies and through the development of new software tools for data analysis and visualization. The influence of circuit theory on conservation comes from the theoretical basis and elegance of the approach and the powerful collaborations and active user community that have emerged. Circuit theory provides a springboard for ecological understanding and will remain an important conservation tool for researchers and practitioners around the globe.

Identifying wildlife corridors for the restoration of regional habitat connectivity: A multispecies approach and comparison of resistance surfaces

Many large-scale connectivity initiatives have been proposed around the world with the aim of maintaining or restoring connectivity to offset the impacts on biodiversity of habitat loss and fragmentation. Frequently, these are based on the requirements of a single focal species of concern, but there is growing attention to identifying connectivity requirements for multi-species assemblages. A number of methods for modelling connectivity have been developed; likewise, different approaches have been used to construct resistance surfaces, the basic input data for connectivity analyses. In this study we modelled connectivity for a multi-species group of vertebrates representative of heavily fragmented forests in north-central Victoria, Australia. For each species, we used least-cost modelling and compared two alternate resistance surfaces, based on species distribution models and on expert opinion, respectively. We integrated the connectivity results across individual species to obtain a multi-species connectivity map for the region. A resistance surface based on expert assessment of the relative use of land-cover classes by the target species was more informative than one based on species distribution models. The former resulted in pathways more strongly aligned with existing patches and strips of native vegetation. In this region, pathways aligned with streams and their associated riparian vegetation have relatively high ecological potential and feasibility to contribute to regional connectivity for the assemblage of forest vertebrates.

Using niche-modelling and species-specific cost analyses to determine a multispecies corridor in a fragmented landscape

Misiones, Argentina, contains the largest remaining tract of Upper Paraná Atlantic Forest ecoregion; however, ~50% of native forest is unprotected and located in a mosaic of plantations, agriculture, and pastures. Existing protected areas are becoming increasingly isolated due to ongoing habitat modification. These factors, combined with lower than expected regional carnivore densities, emphasize the need to understand the effect of fragmentation on animal movement and connectivity between protected areas. Using detection dogs and genetic analyses of scat, we collected data on jaguars (Panthera onca), pumas (Puma concolor), ocelots (Leopardus pardalis), oncillas (Leopardus tigrinus), and bush dogs (Speothos venaticus) across habitats that varied in vegetation, disturbance, human proximity, and protective status. With MaxEnt we evaluated habitat use, habitat suitability, and potential species richness for the five carnivores across northern-central Misiones, Argentina. Through a multifaceted cost analysis that included unique requirements of each carnivore and varying degrees of overlap among them, we determined the optimal location for primary/secondary corridors that would link the northern-central zones of the Green Corridor in Misiones and identified areas within these corridors needing priority management. A secondary analysis, comparing these multispecies corridors with the jaguar’s unique requirements, demonstrated that this multispecies approach balanced the preferences of all five species and effectively captured areas required by this highly restricted and endangered carnivore. We emphasize the potential importance of expanding beyond a single umbrella or focal species when developing biological corridors that aim to capture the varied ecological requirements of coexisting species and ecological processes across the landscape. Detection dogs and genetic analyses of scat allow data on multiple species to be collected efficiently across multiple habitat types independent of the degree of legal protection. These data used with multifocal GIS analyses balance the varying degree of overlap and unique properties among them allowing for comprehensive conservation strategies to be developed relatively rapidly. Our comprehensive approach serves as a model to other regions faced with habitat loss and lack of data. The five carnivores focused on in our study have wide ranges, so the results from this study can be expanded and combined with surrounding countries, with analyses at the species or community level.

Multi-species genetic connectivity in a terrestrial habitat network

BACKGROUND

Habitat fragmentation reduces genetic connectivity for multiple species, yet conservation efforts tend to rely heavily on single-species connectivity estimates to inform land-use planning. Such conservation activities may benefit from multi-species connectivity estimates, which provide a simple and practical means to mitigate the effects of habitat fragmentation for a larger number of species. To test the validity of a multi-species connectivity model, we used neutral microsatellite genetic datasets of Canada lynx (Lynx canadensis), American marten (Martes americana), fisher (Pekania pennanti), and southern flying squirrel (Glaucomys volans) to evaluate multi-species genetic connectivity across Ontario, Canada.

RESULTS

We used linear models to compare node-based estimates of genetic connectivity for each species to point-based estimates of landscape connectivity (current density) derived from circuit theory. To our knowledge, we are the first to evaluate current density as a measure of genetic connectivity. Our results depended on landscape context: habitat amount was more important than current density in explaining multi-species genetic connectivity in the northern part of our study area, where habitat was abundant and fragmentation was low. In the south however, where fragmentation was prevalent, genetic connectivity was correlated with current density. Contrary to our expectations however, locations with a high probability of movement as reflected by high current density were negatively associated with gene flow. Subsequent analyses of circuit theory outputs showed that high current density was also associated with high effective resistance, underscoring that the presence of pinch points is not necessarily indicative of gene flow.

CONCLUSIONS

Overall, our study appears to provide support for the hypothesis that landscape pattern is important when habitat amount is low. We also conclude that while current density is proportional to the probability of movement per unit area, this does not imply increased gene flow, since high current density tends to be a result of neighbouring pixels with high cost of movement (e.g., low habitat amount). In other words, pinch points with high current density appear to constrict gene flow.