Spatial interactions in habitat conservation: Evidence from prairie pothole easements

We examine the role of spatial interactions in conservation easements placed on prairie pothole habitat in western Canada. One of the goals of the conservation easement program we study is to protect contiguous habitat. We identify endogenous spatial interactions among conservation easements and government protected land, independent of spatially correlated landscape features and local economic shocks that influence easement enrollment. We present evidence that easements increase the likelihood of subsequent easements on neighboring land. Government-protected land appears to have little effect on the location of conservation easements. These results imply that conservation agencies have leveraged past conservation investment to enroll more contiguous habitat in permanent easements through a combination of targeting and positive social interactions among neighboring landowners.     

Conservation Easements: Biodiversity Protection and Private Use

Abstract:  Conservation easements are one of the primary tools for conserving biodiversity on private land. Despite their increasing use, little quantitative data are available on what species and habitats conservation easements aim to protect, how much structural development they allow, or what types of land use they commonly permit. To address these knowledge gaps, we surveyed staff responsible for 119 conservation easements established by the largest nonprofit easement holder, The Nature Conservancy, between 1985 and 2004. Most easements (80%) aimed to provide core habitat to protect species or communities on-site, and nearly all were designed to reduce development. Conservation easements also allowed for a wide range of private uses, which may result in additional fragmentation and habitat disturbance. Some residential or commercial use, new structures, or subdivision of the property were permitted on 85% of sampled conservation easements. Over half (56%) allowed some additional buildings, of which 60% restricted structure size or building area. Working landscape easements with ranching, forestry, or farming made up nearly half (46%) of the easement properties sampled and were more likely than easements without these uses to be designated as buffers to enhance biodiversity in the surrounding area. Our results demonstrate the need for clear restrictions on building and subdivision in easements, research on the compatibility of private uses on easement land, and greater public understanding of the trade-offs implicit in the use of conservation easements for biodiversity conservation.     

Factors associated with preemptive conservation under the U.S. Endangered Species Act

In recent decades, there has been an increasing emphasis on proactive efforts to conserve species being considered for listing under the U.S. Endangered Species Act (ESA) before they are listed (i.e., preemptive conservation). These efforts, which depend on voluntary actions by public and private land managers across the species’ range, aim to conserve species while avoiding regulatory costs associated with ESA listing. We collected data for a set of social, economic, environmental, and institutional factors that we hypothesized would influence voluntary decisions to promote or inhibit preemptive conservation of species under consideration for ESA listing. We used logistic regression to estimate the association of these factors with preemptive conservation outcomes based on data for a set of species that entered the ESA listing process and were either officially listed (n = 314) or preemptively conserved (n = 73) from 1996 to 2018. Factors significantly associated with precluded listing due to preemptive conservation included high baseline conservation status, low proportion of private land across the species’ range, small total range size, exposure to specific types of threats, and species’ range extending over several states. These results highlight strategies that can help improve conservation outcomes, such as allocating resources for imperiled species earlier in the listing process, addressing specific threats, and expanding incentives and coordination mechanisms for conservation on private lands.     

Motivations Influencing the Adoption of Conservation Easements

Abstract: The use of conservation easements as a conservation mechanism for private land has increased greatly in the past decade; conservation easements now protect over 15 million ha across the United States from residential and commercial development. We used a mailed survey and in‐depth telephone interviews to determine factors that motivate private landowners in Iowa, Illinois, Michigan, Ohio, and Wisconsin (U.S.A.) to place conservation easements on their properties. The mailed survey asked about characteristics of landowners, their properties, and their opinions on 9 factors related to the decision to place an easement. A follow‐up telephone interview was completed with 19 mail‐survey participants to gain an in‐depth understanding of the action and to triangulate the results with the questionnaire. Place attachment, which is a measure of personal connection to a location or property, was the greatest motivation for implementation of an easement. Results of a principal components analysis suggested contributing to the public good underlaid several of the strong motivational factors for participation. Financial reasons were the lowest ranked motivational factor; however, financial concerns may facilitate placement of an easement that would otherwise not be realized. We believe that our results may be transferable to places where land protected by easements is not dominated by traditional farming (row crops, pastures, and hay), timber harvesting, or nonextractive uses (e.g., habitat for wild animals, recreation, and protection of ecosystem services).     

Effects of preference heterogeneity among landowners on spatial conservation prioritization

The participation of private landowners in conservation is crucial to efficient biodiversity conservation. This is especially the case in settings where the share of private ownership is large and the economic costs associated with land acquisition are high. We used probit regression analysis and historical participation data to examine the likelihood of participation of Danish forest owners in a voluntary conservation program. We used the results to spatially predict the likelihood of participation of all forest owners in Denmark. We merged spatial data on the presence of forest, cadastral information on participation contracts, and individual‐level socioeconomic information about the forest owners and their households. We included predicted participation in a probability model for species survival. Uninformed and informed (included land owner characteristics) models were then incorporated into a spatial prioritization for conservation of unmanaged forests. The choice models are based on sociodemographic data on the entire population of Danish forest owners and historical data on their participation in conservation schemes. Inclusion in the model of information on private landowners’ willingness to supply land for conservation yielded at intermediate budget levels up to 30% more expected species coverage than the uninformed prioritization scheme. Our landowner‐choice model provides an example of moving toward more implementable conservation planning.     

How decisions about fitting species distribution models affect conservation outcomes

Species distribution models (SDMs) are increasingly used in conservation and land-use planning as inputs to describe biodiversity patterns. These models can be built in different ways, and decisions about data preparation, selection of predictor variables, model fitting, and evaluation all alter the resulting predictions. Commonly, the true distribution of species is unknown and independent data to verify which SDM variant to choose are lacking. Such model uncertainty is of concern to planners. We analyzed how 11 routine decisions about model complexity, predictors, bias treatment, and setting thresholds for predicted values altered conservation priority patterns across 25 species. Models were created with MaxEnt and run through Zonation to determine the priority rank of sites. Although all SDM variants performed well (area under the curve >0.7), they produced spatially different predictions for species and different conservation priority solutions. Priorities were most strongly altered by decisions to not address bias or to apply binary thresholds to predicted values; on average 40% and 35%, respectively, of all grid cells received an opposite priority ranking. Forcing high model complexity altered conservation solutions less than forcing simplicity (14% and 24% of cells with opposite rank values, respectively). Use of fewer species records to build models or choosing alternative bias treatments had intermediate effects (25% and 23%, respectively). Depending on modeling choices, priority areas overlapped as little as 10–20% with the baseline solution, affecting top and bottom priorities differently. Our results demonstrate the extent of model-based uncertainty and quantify the relative impacts of SDM building decisions. When it is uncertain what the best SDM approach and conservation plan is, solving uncertainty or considering alterative options is most important for those decisions that change plans the most.     

Assessing the Ecological and Social Benefits of Private Land Conservation in Colorado

Abstract: Conservation of private land through conservation easements, development agreements, and clustered housing has increased greatly as have criticisms of the laws, public programs, and incentives that motivate landowners to use them. Rapid land‐use change at the urban–rural interface in Larimer County, Colorado, has given rise to programs that provide a variety of land‐conservation options for landowners. As of January 2005, roughly 60% of Larimer County was publicly owned, and 3% or 16,200 ha was privately owned with some form of protection. We used document analysis, a landowner survey, targeted interviews, and a landscape‐level spatial analysis to analyze the patterns, quantities, and qualities of private land conservation. We created a jurisdiction‐specific typology of desired benefits from local government‐planning documents to help evaluate conservation parcels. Most easements and other conservation documents used general terms and did not describe the site‐specific values of the land being conserved. Landowners were able to describe some benefits not included in parcel‐specific documents, and our spatial analysis revealed parcel‐specific and cumulative conservation benefits such as the amount of buffering, infill, connectivity, protected agricultural land, riparian protection, and other benefits not referenced by either documents or landowners. Conservation benefits provided by a parcel varied depending on its geographic location, the specific institution such as a land trust or open space program that a landowner worked with, and the conservation mechanism used, such as voluntary easement or residential clustering requirements. The methods we used provide a template for jurisdictions wishing to undertake a similar analysis. Our findings may assist other jurisdictions and institutions interested in improving how land‐conservation benefits are described; justify and inform future investments in private land conservation; assist local governments and other institutions with the assessment of program effectiveness; and be useful for conservation planners who wish to become more involved in on‐the‐ground implementation of conservation actions.     

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.     

Optimizing conservation in species-specific agricultural landscapes

Recovery of grassland birds in agricultural landscapes is a global imperative. Agricultural landscapes are complex, and the value of resource patches may vary substantially among species. The spatial extent at which landscape features affect populations (i.e., scale of effect) may also differ among species. There is a need for regional-scale conservation planning that considers landscape-scale and species-specific responses of grassland birds to environmental change. We developed a spatially explicit approach to optimizing grassland conservation in the context of species-specific landscapes and prioritization of species recovery and applied it to a conservation program in Kentucky (USA). We used a hierarchical distance-sampling model with an embedded scale of effect predictor to estimate the relationship between landscape structure and abundance of eastern meadowlarks (Sturnella magna), field sparrows (Spizella pusilla), and northern bobwhites (Colinus virginianus). We used a novel spatially explicit optimization procedure rooted in multi-attribute utility theory to design alternative conservation strategies (e.g., prioritize only northern bobwhite recovery or assign equal weight to each species’ recovery). Eastern meadowlarks and field sparrows were more likely to respond to landscape-scale resource patch adjacencies than landscape-scale patch densities. Northern bobwhite responded to both landscape-scale resource patch adjacencies and densities and responded strongly to increased grassland density. Effects of landscape features on local abundance decreased as distance increased and had negligible influence at 0.8 km for eastern meadowlarks (0.7–1.2 km 95% Bayesian credibility intervals [BCI]), 2.5 km for field sparrows (1.5–5.8 km 95% BCI), and 8.4 km for bobwhite (6.4–26 km 95% BCI). Northern bobwhites were predicted to benefit greatly from future grassland conservation regardless of conservation priorities, but eastern meadowlark and field sparrow were not. Our results suggest similar species can respond differently to broad-scale conservation practices because of species-specific, distance-dependent relationships with landscape structure. Our framework is quantitative, conceptually simple, customizable, and predictive and can be used to optimize conservation in heterogeneous ecosystems while considering landscape-scale processes and explicit prioritization of species recovery.     

Understanding the effects of different social data on selecting priority conservation areas

Conservation success is contingent on assessing social and environmental factors so that cost‐effective implementation of strategies and actions can be placed in a broad social–ecological context. Until now, the focus has been on how to include spatially explicit social data in conservation planning, whereas the value of different kinds of social data has received limited attention. In a regional systematic conservation planning case study in Australia, we examined the spatial concurrence of a range of spatially explicit social values and land‐use preferences collected using a public participation geographic information system and biological data. We used Zonation to integrate the social data with the biological data in a series of spatial‐prioritization scenarios to determine the effect of the different types of social data on spatial prioritization compared with biological data alone. The type of social data (i.e., conservation opportunities or constraints) significantly affected spatial prioritization outcomes. The integration of social values and land‐use preferences under different scenarios was highly variable and generated spatial prioritizations 1.2–51% different from those based on biological data alone. The inclusion of conservation‐compatible values and preferences added relatively few new areas to conservation priorities, whereas including noncompatible economic values and development preferences as costs significantly changed conservation priority areas (48.2% and 47.4%, respectively). Based on our results, a multifaceted conservation prioritization approach that combines spatially explicit social data with biological data can help conservation planners identify the type of social data to collect for more effective and feasible conservation actions.     

Assessing the local economic impacts of land protection

Land protection, whether public or private, is often controversial at the local level because residents worry about lost economic activity. We used panel data and a quasi-experimental impact-evaluation approach to determine how key economic indicators were related to the percentage of land protected. Specifically, we estimated the impacts of public and private land protection based on local area employment and housing permits data from 5 periods spanning 1990–2015 for all major towns and cities in New England. To generate rigorous impact estimates, we modeled economic outcomes as a function of the percentage of land protected in the prior period, conditional on town fixed effects, metro-region trends, and controls for period and neighboring protection. Contrary to narratives that conservation depresses economic growth, land protection was associated with a modest increase in the number of people employed and in the labor force and did not affect new housing permits, population, or median income. Public and private protection led to different patterns of positive employment impacts at distances close to and far from cities, indicating the importance of investing in both types of land protection to increase local opportunities. The greatest magnitude of employment impacts was due to protection in more rural areas, where opportunities for both visitation and amenity-related economic growth may be greatest. Overall, we provide novel evidence that land protection can be compatible with local economic growth and illustrate a method that can be broadly applied to assess the net economic impacts of protection.     

Integrating Biological and Social Values When Prioritizing Places for Biodiversity Conservation

The consideration of information on social values in conjunction with biological data is critical for achieving both socially acceptable and scientifically defensible conservation planning outcomes. However, the influence of social values on spatial conservation priorities has received limited attention and is poorly understood. We present an approach that incorporates quantitative data on social values for conservation and social preferences for development into spatial conservation planning. We undertook a public participation GIS survey to spatially represent social values and development preferences and used species distribution models for 7 threatened fauna species to represent biological values. These spatially explicit data were simultaneously included in the conservation planning software Zonation to examine how conservation priorities changed with the inclusion of social data. Integrating spatially explicit information about social values and development preferences with biological data produced prioritizations that differed spatially from the solution based on only biological data. However, the integrated solutions protected a similar proportion of the species’ distributions, indicating that Zonation effectively combined the biological and social data to produce socially feasible conservation solutions of approximately equivalent biological value. We were able to identify areas of the landscape where synergies and conflicts between different value sets are likely to occur. Identification of these synergies and conflicts will allow decision makers to target communication strategies to specific areas and ensure effective community engagement and positive conservation outcomes. Integración de Valores Biológicos y Sociales al Priorizar Sitios para la Conservación de la Biodiversidad     

Value of protected areas to avian persistence across 20 years of climate and land-use change

Establishing protected areas, where human activities and land cover changes are restricted, is among the most widely used strategies for biodiversity conservation. This practice is based on the assumption that protected areas buffer species from processes that drive extinction. However, protected areas can maintain biodiversity in the face of climate change and subsequent shifts in distributions have been questioned. We evaluated the degree to which protected areas influenced colonization and extinction patterns of 97 avian species over 20 years in the northeastern United States. We fitted single-visit dynamic occupancy models to data from Breeding Bird Atlases to quantify the magnitude of the effect of drivers of local colonization and extinction (e.g., climate, land cover, and amount of protected area) in heterogeneous landscapes that varied in the amount of area under protection. Colonization and extinction probabilities improved as the amount of protected area increased, but these effects were conditional on landscape context and species characteristics. In this forest-dominated region, benefits of additional land protection were greatest when both forest cover in a grid square and amount of protected area in neighboring grid squares were low. Effects did not vary with species’ migratory habit or conservation status. Increasing the amounts of land protection benefitted the range margins species but not the core range species. The greatest improvements in colonization and extinction rates accrued for forest birds relative to open-habitat or generalist species. Overall, protected areas stemmed extinction more than they promoted colonization. Our results indicate that land protection remains a viable conservation strategy despite changing habitat and climate, as protected areas both reduce the risk of local extinction and facilitate movement into new areas. Our findings suggest conservation in the face of climate change favors creation of new protected areas over enlarging existing ones as the optimal strategy to reduce extinction and provide stepping stones for the greatest number of species.     

A Bayesian hierarchical approach to quantifying stakeholder attitudes toward conservation in the presence of reporting error

Stakeholder support is vital for achieving conservation success, yet there are few reliable mechanisms to monitor stakeholder attitudes toward conservation. Approaches used to assess attitudes rarely account for bias arising from reporting error, which can lead to falsely reporting a positive attitude toward conservation (false-positive error) or not reporting a positive attitude when the respondent has a positive attitude toward conservation (false-negative error). Borrowing from developments in applied conservation science, we used a Bayesian hierarchical model to quantify stakeholder attitudes as the probability of having a positive attitude toward wildlife notionally (or in abstract terms) and at localized scales while accounting for reporting error. We compared estimates from our model, Likert scores, and naïve estimates (i.e., proportion of respondents reporting a positive attitude in at least 1 question that was only susceptible to false-negative error) with true stakeholder attitudes through simulations. We then applied the model in a survey of tea estate staff on their attitudes toward Asian elephants (Elephas maximus) in the Kaziranga–Karbi Anglong landscape of northeast India. In simulations, Bayesian model estimates of stakeholder attitudes toward wildlife were less biased than naïve estimates or Likert scores. After accounting for reporting errors, we estimated the probability of having a positive attitude toward elephants notionally as 0.85 in the Kaziranga landscape, whereas the proportion of respondents who had positive attitudes toward elephants at a localized scale was 0.50. In comparison, without accounting for reporting errors, naïve estimates of proportions of respondents with positive attitudes toward elephants were 0.69 and 0.23 notionally and at local scales, respectively. False (positive and negative) reporting probabilities were consistently not 0 (0.22–0.68). Regular and reliable assessment of stakeholder attitudes–combined with inference on drivers of positive attitudes–can help assess the success of initiatives aimed at facilitating human behavioral change and inform conservation decision making.     

Practical actions for applied systematic conservation planning

Systematic conservation planning is intended to inform spatially explicit decision making. Doing so requires that it be integrated into complex regulatory and governance processes, and there are limited instances where this has been achieved effectively. South Africa is a global leader in the application of conservation plans, the outputs of which are widely used for spatial planning and decision making in many spheres of government. We aimed to determine how conservation planning in the country progressed from theory to implementation, and to identify practical actions that enabled this transition, by assessing temporal trends in the characteristics of conservation plans (1990–2017, n = 94). Since 2010 conservation planning has entered an operational period characterized by government leadership of plans, administrative rather than ecological planning domains, decreasing size of planning units, increasing emphasis on end-user products, and scheduled revision of plans. Key actions that enabled this progression include transitioning leadership of plans from scientists to practitioners, building capacity within implementing agencies, creating opportunities to integrate plans in legislative processes, establishing a strong community of practice, adopting implementation-focused methods, and balancing standardization with innovation. Learning from this model will allow other countries, particularly those with a similar megadiverse, developing context, to operationalize conservation planning into spatial planning and decision making.     

Microtargeting for conservation

Widespread human action and behavior change is needed to achieve many conservation goals. Doing so at the requisite scale and pace will require the efficient delivery of outreach campaigns. Conservation gains will be greatest when efforts are directed toward places of high conservation value (or need) and tailored to critical actors. Recent strategic conservation planning has relied primarily on spatial assessments of biophysical attributes, largely ignoring the human dimensions. Elsewhere, marketers, political campaigns, and others use microtargeting—predictive analytics of big data—to identify people most likely to respond positively to particular messages or interventions. Conservationists have not yet widely capitalized on these techniques. To investigate the effectiveness of microtargeting to improve conservation, we developed a propensity model to predict restoration behavior among 203,645 private landowners in a 5,200,000 ha study area in the Chesapeake Bay Watershed (U.S.A.). To isolate the additional value microtargeting may offer beyond geospatial prioritization, we analyzed a new high-resolution land-cover data set and cadastral data to identify private owners of riparian areas needing restoration. Subsequently, we developed and evaluated a restoration propensity model based on a database of landowners who had conducted restoration in the past and those who had not (n = 4978). Model validation in a parallel database (n = 4989) showed owners with the highest scorers for propensity to conduct restoration (i.e., top decile) were over twice as likely as average landowners to have conducted restoration (135%). These results demonstrate that microtargeting techniques can dramatically increase the efficiency and efficacy of conservation programs, above and beyond the advances offered by biophysical prioritizations alone, as well as facilitate more robust research of many social–ecological systems.     

Mapping Human and Social Dimensions of Conservation Opportunity for the Scheduling of Conservation Action on Private Land

Abstract Spatial prioritization techniques are applied in conservation‐planning initiatives to allocate conservation resources. Although typically they are based on ecological data (e.g., species, habitats, ecological processes), increasingly they also include nonecological data, mostly on the vulnerability of valued features and economic costs of implementation. Nevertheless, the effectiveness of conservation actions implemented through conservation‐planning initiatives is a function of the human and social dimensions of social‐ecological systems, such as stakeholders’ willingness and capacity to participate. We assessed human and social factors hypothesized to define opportunities for implementing effective conservation action by individual land managers (those responsible for making day‐to‐day decisions on land use) and mapped these to schedule implementation of a private land conservation program. We surveyed 48 land managers who owned 301 land parcels in the Makana Municipality of the Eastern Cape province in South Africa. Psychometric statistical and cluster analyses were applied to the interview data so as to map human and social factors of conservation opportunity across a landscape of regional conservation importance. Four groups of landowners were identified, in rank order, for a phased implementation process. Furthermore, using psychometric statistical techniques, we reduced the number of interview questions from 165 to 45, which is a preliminary step toward developing surrogates for human and social factors that can be developed rapidly and complemented with measures of conservation value, vulnerability, and economic cost to more‐effectively schedule conservation actions. This work provides conservation and land management professionals direction on where and how implementation of local‐scale conservation should be undertaken to ensure it is feasible.     

Economics and Land-Use Change in Prioritizing Private Land Conservation

Abstract:  Incentive-based strategies such as conservation easements and short-term management agreements are popular tools for conserving biodiversity on private lands. Billions of dollars are spent by government and private conservation organizations to support land conservation. Although much of conservation biology focuses on reserve design, these methods are often ineffective at optimizing the protection of biological benefits for conservation programs. Our review of the recent literature on protected-area planning identifies some of the reasons why. We analyzed the site-selection process according to three important components: biological benefits, land costs, and likelihood of land-use change. We compared our benefit-loss-cost targeting approach with more conventional strategies that omit or inadequately address either land costs or likelihood of land-use change. Our proposed strategy aims to minimize the expected loss in biological benefit due to future land-use conversion while considering the full or partial costs of land acquisition. The implicit positive correlation between the likelihood of land-use conversion and cost of land protection means high-vulnerability sites with suitable land quality are typically more expensive than low-vulnerability sites with poor land quality. Therefore, land-use change and land costs need to be addressed jointly to improve spatial targeting strategies for land conservation. This approach can be extended effectively to land trusts and other institutions implementing conservation programs.     

Effects of Private‐Land Use,Livestock Management,and Human Tolerance on Diversity,Distribution, and Abundance of Large African Mammals

Successful conservation of large terrestrial mammals (wildlife) on private lands requires that landowners be empowered to manage wildlife so that benefits outweigh the costs. Laikipia County, Kenya, is predominantly unfenced, and the land uses in the area allow wide‐ranging wildlife to move freely between different management systems on private land. We used camera traps to sample large mammals associated with 4 different management systems (rhinoceros sanctuaries, no livestock; conservancies, intermediate stocking level; fenced ranches, high stocking level; and group ranches, high stocking level, no fencing, pastoralist clan ownership) to examine whether management and stocking levels affect wildlife. We deployed cameras at 522 locations across 8 properties from January 2008 through October 2010 and used the photographs taken during this period to estimate richness, occupancy, and relative abundance of species. Species richness was highest in conservancies and sanctuaries and lowest on fenced and group ranches. Occupancy estimates were, on average, 2 and 5 times higher in sanctuaries and conservancies as on fenced and group ranches, respectively. Nineteen species on fenced ranches and 25 species on group ranches were considered uncommon (occupancy < 0.1). The relative abundance of most species was highest or second highest in sanctuaries and conservancies. Lack of rights to manage and utilize wildlife and uncertain land tenure dampen many owners’ incentives to tolerate wildlife. We suggest national conservation strategies consider landscape‐level approaches to land‐use planning that aim to increase conserved areas by providing landowners with incentives to tolerate wildlife. Possible incentives include improving access to ecotourism benefits, forging agreements to maintain wildlife habitat and corridors, resolving land‐ownership conflicts, restoring degraded rangelands, expanding opportunities for grazing leases, and allowing direct benefits to landowners through wildlife harvesting. Efectos del Uso Privado de Suelo, Manejo de Ganado y la Tolerancia Humana sobre la Diversidad, Distribución y Abundancia de Mamíferos Mayores Africanos     

Validating graph-based connectivity models with independent presence–absence and genetic data sets

Habitat connectivity is a key objective of current conservation policies and is commonly modeled by landscape graphs (i.e., sets of habitat patches [nodes] connected by potential dispersal paths [links]). These graphs are often built based on expert opinion or species distribution models (SDMs) and therefore lack empirical validation from data more closely reflecting functional connectivity. Accordingly, we tested whether landscape graphs reflect how habitat connectivity influences gene flow, which is one of the main ecoevolutionary processes. To that purpose, we modeled the habitat network of a forest bird (plumbeous warbler [Setophaga plumbea]) on Guadeloupe with graphs based on expert opinion, Jacobs’ specialization indices, and an SDM. We used genetic data (712 birds from 27 populations) to compute local genetic indices and pairwise genetic distances. Finally, we assessed the relationships between genetic distances or indices and cost distances or connectivity metrics with maximum-likelihood population-effects distance models and Spearman correlations between metrics. Overall, the landscape graphs reliably reflected the influence of connectivity on population genetic structure; validation R² was up to 0.30 and correlation coefficients were up to 0.71. Yet, the relationship among graph ecological relevance, data requirements, and construction and analysis methods was not straightforward because the graph based on the most complex construction method (species distribution modeling) sometimes had less ecological relevance than the others. Cross-validation methods and sensitivity analyzes allowed us to make the advantages and limitations of each construction method spatially explicit. We confirmed the relevance of landscape graphs for conservation modeling but recommend a case-specific consideration of the cost-effectiveness of their construction methods. We hope the replication of independent validation approaches across species and landscapes will strengthen the ecological relevance of connectivity models.