Where to restore ecological connectivity? Detecting barriers and quantifying restoration benefits

Landscape connectivity is crucial for many ecological processes, including dispersal, gene flow, demographic rescue, and movement in response to climate change. As a result, governmental and non-governmental organizations are focusing efforts to map and conserve areas that facilitate movement to maintain population connectivity and promote climate adaptation. In contrast, little focus has been placed on identifying barriers—landscape features which impede movement between ecologically important areas—where restoration could most improve connectivity. Yet knowing where barriers most strongly reduce connectivity can complement traditional analyses aimed at mapping best movement routes. We introduce a novel method to detect important barriers and provide example applications. Our method uses GIS neighborhood analyses in conjunction with effective distance analyses to detect barriers that, if removed, would significantly improve connectivity. Applicable in least-cost, circuit-theoretic, and simulation modeling frameworks, the method detects both complete (impermeable) barriers and those that impede but do not completely block movement. Barrier mapping complements corridor mapping by broadening the range of connectivity conservation alternatives available to practitioners. The method can help practitioners move beyond maintaining currently important areas to restoring and enhancing connectivity through active barrier removal. It can inform decisions on trade-offs between restoration and protection; for example, purchasing an intact corridor may be substantially more costly than restoring a barrier that blocks an alternative corridor. And it extends the concept of centrality to barriers, highlighting areas that most diminish connectivity across broad networks. Identifying which modeled barriers have the greatest impact can also help prioritize error checking of land cover data and collection of field data to improve connectivity maps. Barrier detection provides a different way to view the landscape, broadening thinking about connectivity and fragmentation while increasing conservation options

Landscape-level Analysis of Mountain Goat Population Connectivity in Washington and Southern British Columbia

Habitat fragmentation and habitat loss diminish population connectivity, reducing genetic diversity and increasing extinction risk over time. Improving connectivity is widely recommended to preserve the long-term viability of populations, but this requires accurate knowledge of how landscapes influence connectivity. Detectability of landscape effects on gene flow is highly dependent on landscape context, and drawing conclusions from single landscape studies may lead to ineffective management strategies. We present a novel approach to elucidate regional variation in the relative importance of landscape variable effects on gene flow. We demonstrate this approach by evaluating gene flow between isolated, genetically impoverished mountain goat (Oreamnos americanus) populations in Washington and much larger, genetically robust populations in southern British Columbia. We used GENELAND to identify steep genetic gradients and then employed individual-based landscape genetics in a causal modeling framework to independently evaluate landscape variables that may be generating each of these genetic gradients. Our results support previous findings that freeways, highways, water, agriculture and urban landcover limit gene flow in this species. Additionally, we found that a previously unsupported landscape variable, distance to escape terrain, also limits gene flow in some contexts. By integrating GENELAND and individual-based methods we effectively identified regional limiting factors that have landscape-level implications for population viability

Comparison of Bayesian Clustering and Edge Detection Methods for Inferring Boundaries in Landscape Genetics

Recently, techniques available for identifying clusters of individuals or boundaries between clusters using genetic data from natural populations have expanded rapidly. Consequently, there is a need to evaluate these different techniques. We used spatially-explicit simulation models to compare three spatial Bayesian clustering programs and two edge detection methods. Spatially-structured populations were simulated where a continuous population was subdivided by barriers. We evaluated the ability of each method to correctly identify boundary locations while varying: (i) time after divergence, (ii) strength of isolation by distance, (iii) level of genetic diversity, and (iv) amount of gene flow across barriers. To further evaluate the methods’ effectiveness to detect genetic clusters in natural populations, we used previously published data on North American pumas and a European shrub. Our results show that with simulated and empirical data, the Bayesian spatial clustering algorithms outperformed direct edge detection methods. All methods incorrectly detected boundaries in the presence of strong patterns of isolation by distance. Based on this finding, we support the application of Bayesian spatial clustering algorithms for boundary detection in empirical datasets, with necessary tests for the influence of isolation by distance

Can Orchards Help Connect Mediterranean Ecosystems? Animal Movement Data Alter Conservation Priorities

As natural habitats become fragmented by human activities, animals must increasingly move through human-dominated systems, particularly agricultural landscapes. Mapping areas important for animal movement has therefore become a key part of conservation planning. Models of landscape connectivity are often parameterized using expert opinion and seldom distinguish between the risks and barriers presented by different crop types. Recent research, however, suggests different crop types, such as row crops and orchards, differ in the degree to which they facilitate or impede species movements. Like many mammalian carnivores, bobcats (Lynx rufus) are sensitive to fragmentation and loss of connectivity between habitat patches. We investigated how distinguishing between different agricultural land covers might change conclusions about the relative conservation importance of different land uses in a Mediterranean ecosystem. Bobcats moved relatively quickly in row crops but relatively slowly in orchards, at rates similar to those in natural habitats of woodlands and scrub. We found that parameterizing a connectivity model using empirical data on bobcat movements in agricultural lands and other land covers, instead of parameterizing the model using habitat suitability indices based on expert opinion, altered locations of predicted animal movement routes. These results emphasize that differentiating between types of agriculture can alter conservation planning outcomes

Systematic Conservation Planning in the Face of Climate Change: Bet-Hedging on the Columbia Plateau

Systematic conservation planning efforts typically focus on protecting current patterns of biodiversity. Climate change is poised to shift species distributions, reshuffle communities, and alter ecosystem functioning. In such a dynamic environment, lands selected to protect today's biodiversity may fail to do so in the future. One proposed approach to designing reserve networks that are robust to climate change involves protecting the diversity of abiotic conditions that in part determine species distributions and ecological processes. A set of abiotically diverse areas will likely support a diversity of ecological systems both today and into the future, although those two sets of systems might be dramatically different. Here, we demonstrate a conservation planning approach based on representing unique combinations of abiotic factors. We prioritize sites that represent the diversity of soils, topographies, and current climates of the Columbia Plateau. We then compare these sites to sites prioritized to protect current biodiversity. This comparison highlights places that are important for protecting both today's biodiversity and the diversity of abiotic factors that will likely determine biodiversity patterns in the future. It also highlights places where a reserve network designed solely to protect today's biodiversity would fail to capture the diversity of abiotic conditions and where such a network could be augmented to be more robust to climate-change impacts

Identifying riparian climate corridors to inform climate adaptation planning.

Riparian habitats have been frequently identified as priority areas for conservation under climate change because they span climatic gradients and have cool, moist microclimates relative to surrounding areas. They are therefore expected to act as dispersal corridors for climate-induced species range shifts and to provide microclimatic refugia from warming. Despite recognition of these values, rigorous methods to identify which riparian areas are most likely to facilitate range shifts and provide refugia are currently lacking. We completed a novel analysis across the Pacific Northwest, USA, that identifies potential riparian corridors featuring characteristics expected to enhance their ability to facilitate range shifts and provide refugia. These features include large temperature gradients, high canopy cover, large relative width, low exposure to solar radiation, and low levels of human modification. These variables were used to calculate a riparian climate-corridor index using a multi-scale approach that incorporates results ranging in scale from local watersheds to the entire Pacific Northwest. Resulting index values for potential riparian corridors in the Pacific Northwest were highest within mountainous areas and lowest within relatively flat, lowland regions. We also calculated index values within ecoregions, to better identify high-value riparian climate corridors within the relatively flat, degraded areas where they may most contribute to climate adaptation. We found that high-value riparian climate-corridors are least protected in flat, lowland areas, suggesting that such corridors should be high priorities for future conservation effort. Our analysis provides critical information on valuable riparian climate-corridors to guide climate adaptation efforts (and riparian management and restoration efforts) in the Pacific Northwest, while offering a novel approach that may be applied to similar efforts in other geographies

Data from: Projected climate-driven faunal movement routes

Historically, many species moved great distances as climates changed. However, modern movements will be limited by the patterns of human-dominated landscapes. Here, we use a combination of projected climate-driven shifts in the distributions of 2903 vertebrate species, estimated current human impacts on the landscape, and movement models, to determine through which areas in the western hemisphere species will likely need to move to track suitable climates. Our results reveal areas with projected high densities of climate-driven movements – including, the Amazon Basin, the southeastern United States and southeastern Brazil. Some of these regions, such as southern Bolivia and northern Paraguay, contain relatively intact landscapes, whereas others such as the southeastern United States and Brazil are heavily impacted by human activities. Thus, these results highlight both critical areas for protecting lands that will foster movement, and barriers where human land-use activities will likely impede climate-driven shifts in species distributions