Spatial Conservation Planning Research Articles

Spatial conservation planning of forest genetic resources in a Mediterranean multi-refugial area

The Kunming-Montreal Global Biodiversity Framework recognised the urgency of taking action to conserve intraspecific genetic diversity (IGD) as an insurance against habitat degradation and environmental change. Recent work suggests that 90–99 % of IGD should be conserved to safeguard viability of future generations.Here, we addressed such a conservation issue in three forest tree species in Italy: silver fir (Abies alba Mill.), Heldreich's pine (Pinus heldreichii H. Christ), and pedunculate oak (Quercus robur L.). We used microsatellite markers to measure IGD of 36 (A. alba), 15 (P. heldreichii) and 25 (Q. robur) natural sites, including several putative glacial refugia. We developed a spatial conservation planning (SCP) analysis to quantify the genetic irreplaceability of each site and identify the minimum set coverage ensuring IGD protection. Finally, we compared SCP results with the contributions to allelic diversity within and between sites, total allelic diversity and private allelic richness.We found that between 44 % and 73 % of sites were required to conserve 90–99 % of the alleles, and that this conservation effort held even when targeting lower percentages of alleles to protect (50–75 %). Glacial refugia were often included in the minimum set coverage, confirming biogeographical expectations. Finally, sites with high genetic irreplaceability were found to have higher private allelic richness on average. These results are discussed in the light of the biogeographic history of the species studied and the current policies for the conservation of forest genetic resources.

Dynamic marine spatial planning for conservation and fisheries benefits

AbstractThe increasing global demand for marine resources raises concerns about sustainable resource management and biodiversity conservation. Spatial closures, such as marine protected areas, can be valuable tools for maintaining and restoring exploited populations. When these spatial closures adopt a dynamic nature being adapted to the changing environment, they can effectively account for factors such as shifting species distributions, which enhances their potential to achieve ecological and socio‐economic objectives. Here, we adapted a decision‐support tool (the software Marxan), typically used for selecting static and permanent areas, to produce management recommendations that integrate permanent and temporal closures to fisheries. Our aim was to compare the outputs of a static network of permanent no‐take reserves with four other dynamic scenarios, including permanent and temporal closures that account for seasonal variations in the populations of species. All scenarios prioritized sites for the conservation of one of the most valuable European fishing stocks, the Norway lobster (Nephrops norvegicus). Additionally, we considered 12 other commercially exploited species captured by the Norway lobster fishery. The assessed outputs included retained biomass, area extent, closure type (permanent and seasonal) and opportunity costs within each scenario. We observed that all dynamic scenarios required fewer management areas permanently closed than the static scenario. This resulted in a lower opportunity cost for fisheries but also a higher capacity for biodiversity conservation. Therefore, complementing permanent with temporal closures could enhance biodiversity conservation and fisheries management. The novel dynamic planning method presented here could be applicable to other species, ecosystems and socio‐economic contexts.

OccTest: An integrated approach for quality control of species occurrence data

AbstractAimSpecies occurrence data are valuable information that enables one to estimate geographical distributions, characterize niches and their evolution, and guide spatial conservation planning. Rapid increases in species occurrence data stem from increasing digitization and aggregation efforts, and citizen science initiatives. However, persistent quality issues in occurrence data can impact the accuracy of scientific findings, underscoring the importance of filtering erroneous occurrence records in biodiversity analyses.InnovationWe introduce an R package, occTest, that synthesizes a growing open‐source ecosystem of biodiversity cleaning workflows to prepare occurrence data for different modelling applications. It offers a structured set of algorithms to identify potential problems with species occurrence records by employing a hierarchical organization of multiple tests. The workflow has a hierarchical structure organized in testPhases (i.e. cleaning vs. testing) that encompass different testBlocks grouping different testTypes (e.g. environmental outlier detection), which may use different testMethods (e.g. Rosner test, jacknife,etc.). Four different testBlocks characterize potential problems in geographic, environmental, human influence and temporal dimensions. Filtering and plotting functions are incorporated to facilitate the interpretation of tests. We provide examples with different data sources, with default and user‐defined parameters. Compared to other available tools and workflows, occTest offers a comprehensive suite of integrated tests, and allows multiple methods associated with each test to explore consensus among data cleaning methods. It uniquely incorporates both coordinate accuracy analysis and environmental analysis of occurrence records. Furthermore, it provides a hierarchical structure to incorporate future tests yet to be developed.Main conclusionsoccTest will help users understand the quality and quantity of data available before the start of data analysis, while also enabling users to filter data using either predefined rules or custom‐built rules. As a result, occTest can better assess each record's appropriateness for its intended application.

Global trends in geospatial conservation planning: a review of priorities and missing dimensions

IntroductionBiodiversity underpins resilient ecosystems that sustain life. Despite international conservation efforts, biodiversity is still declining due to ongoing anthropogenic threats. Protected areas have been widely adopted as a strategy for conserving biodiversity. The use of spatial conservation planning, which prioritizes areas for protection based on geo-referenced biodiversity and ecological information as well as cost of action and their feasibility, has gained popularity in the conservation discipline in the last few decades. However, there remain gaps between plans and implementation, and negative social impacts on local communities can occur, such as tension and conflict between differing priorities, perspectives, and views.MethodsTo better understand the state of the spatial conservation field and support translating research into practice, a mixed-method approach of bibliometric (n=4133 documents) and content analysis (n=2456 documents) was used to analyze and identify key research priorities, collaborative networks, and geographic and thematic patterns.ResultsWe identified that research conducted by westernized nations dominated the field, with the United States, the United Kingdom, and Australia being responsible for almost two-thirds of the research globally, with research interest exponentially growing since 2010. Additionally, while there has been some refinement over time of algorithms and models, Zonation and Marxan methods developed in the 2000s remain the predominant choices of software, with a majority focus on marine ecosystems, birds, and mammals. We found a major gap in the use of social dimensions in spatial conservation case studies (only n=146; 6%).DiscussionThis gap highlights a lack of collaboration in conservation science between researchers and local communities who are affected by management decisions. We recommend including spatially explicit social dimensions from the onset of projects through participatory approaches, along with the acknowledgement by researchers of the importance of including diverse views in conservation planning to enhance implementation and outcomes that are relevant in local contexts. We suggest an increased reflection on types of data used for conservation but also on researchers’ personal values, biases, and positionality to encourage more ethical, applicable, and collaborative conservation science.

An ecosystem-based fisheries assessment for some coral fishes in the coastal Seram Laut Island, Maluku

As the Seram Laut Island (SLI) community relies on coral fish resources, changes in coral fish populations will impact their income and nutritional needs. This research aimed to investigate the SLI ecosystem's status using risk score indicators and the management implications for the sustainability of the coral fish fishery ecosystem. This research used the tier 2 approach semiquantitative ecosystem-based fishery assessment (EBFA) method based on a risk score of 0 to 3, with four objectives: sustainability, habitat, biodiversity, and socio-economy. Several high-risk scores in the red zone were found in the fishing efforts indicator of Lethrinus obsoletus, Siganus canaliculatus, and Cephalopolis miniata, catch per unit effort (cpue) indicator of S. canaliculatus, maturity proportion, and fishing gear impact of L. obsoletus and S. canaliculatus and habitat quality indicator of S. canaliculatus. Coral fish's species risk index (SRI) ranged from 1.28 to 1.64 (yellow zone), with L. obsoletus having the highest SRI. The coastal of SLI's ecosystem risk index was in the limited range (yellow zone). For ecosystem sustainability, proper management should be developed with a focus on the indicators in the high-risk state (red zone) by spatial planning for coral and habitat conservation, as well as policies based on local wisdom.

Identification of Ecological Restoration Priority Areas Integrating Human Activity Intensity and Multi-Criteria Decision Analysis

Restoration action is critical to ensure a safe environment for humans. Reasonable planning is essential to optimize the efficiency of ecological restoration inputs and outputs when implementing restoration measures. In this study, a method that combines human activity intensity assessment and multi-criteria decision analysis to determine ecological restoration priority (ERP) areas was developed to identify priority and feasible areas for ecological restoration in Shaanxi Province in 2020. The results showed that the total area involved in restoration feasibility assessment in Shaanxi is 10.89 × 104 km2. Among them, the percentage of regions with low feasibility (less than 0.2) is 68.86%, mainly located in Qinling area. High feasibility areas (more than 0.6) accounted for 2.47%, mainly located in the Loess Plateau area of northern Shaanxi. The spatial distribution of the human activity intensity is concentrated in urban areas and extended with the distribution of roads. In total, 10.69% of the regions showed high and very high intensity of human activity, including the Guanzhong urban agglomeration region. This study identified 6078 km2 and 671 km2 of medium and high ecological restoration priority areas, which are more concentrated in the north of the study area. The need for ecological restoration work is even more urgent in northern Shaanxi. In general, the framework in this study has spatially located the priority and feasible areas for restoration, and may provide a useful reference for landscape-scale spatial conservation planning.

A conservation planning strategy applied to the evolutionary history of the mantellid frogs of Madagascar

Phylogenetic diversity is an increasingly applied metric used to maximize the representation of evolutionary history in spatial conservation planning. When following this approach, researchers commonly overlook sites with a relatively higher proportion of recently diverged endemic species, also known as centers of neo-endemism. Here we aim to demonstrate how targeting the conservation of different facets of diversity (taxonomic diversity, phylogenetic diversity and centers of endemism) can provide more cost-effective solutions to the conservation of the all evolutionary spectrum of biodiversity. We do so by using the mantellid frogs of Madagascar as a case study. Our results confirm that areas with high concentrations of neo-endemism can be effectively identified as conservation planning priorities only if we specifically target them. Neglecting areas that are poor in phylogenetic diversity may therefore compromise the maintenance of diversification processes, particularly when lesser proportions of the landscape are protected. This approach can be of particular interest to island ecosystems, since they often harbor unique and restricted evolutionary radiations.

Avoiding an unjust transition to sustainability: An equity metric for spatial conservation planning

The need for rapid and ambitious conservation and restoration is widely acknowledged, yet concern exists that the widespread reallocation of land to nature would disproportionately affect the world's poor. Conservation and restoration may limit nutrition and livelihood options and thus negatively affect social development objectives. Although much research looks into global-scale scenarios and planning of conservation and restoration, spatial evaluations of these trade-offs in terms of equity remain limited. We fill this gap by identifying areas where conservation or restoration under different future scenarios and prioritization maps expand nature into landscapes that likely support land-dependent communities in their local food security. By contrasting the expansion of nature into areas supporting land-dependent communities vs. places where the food system is supported by regional to global markets, we highlight the need for disaggregated indicators that reflect the diversity of human land-use needs in order to identify more equitable pathways. Conservation prioritizations were found to result in more equitable land-use outcomes than the land-use outcomes of widely used socioeconomic scenarios. Accounting for differentiated social impacts in model-based conservation and restoration planning and global scale scenario assessment can help achieve a more inclusive transition to sustainability as well as reduce barriers to meaningful change.

Bridging local and scientific knowledge for area-based conservation of useful plants in Colombia

While the importance of interdisciplinary approaches is increasingly recognised in conservation, bridging knowledge systems across scales remains a fundamental challenge. Focusing on the Important Plant Areas (IPA) approach, we evaluate how complementing scientific and local knowledge can better inform the conservation of useful plants in Colombia. We worked in three municipalities to investigate knowledge on useful plant richness, species composition and use types, as well as perceptions on area-based plant conservation approaches. Participatory focus groups and ethnobotanical walks-in-the-woods were undertaken with local communities, while scientific data were represented by occurrence records from global data aggregators and digitised collections. A total of 1190 species with human uses were reported. Combining knowledge systems provided the richest understanding of useful plants but the relative contribution of each system varied between study areas, influenced by the history of scientific studies, socio-ecological context and study design. Meanwhile, local perceptions of how conservation areas should be selected differed from global IPA criteria. These results show that working with local communities can improve biological understanding for spatial conservation planning. Additionally, participatory approaches must move beyond community-based conservation and data collection, to inform the design of global conservation programmes.

Marine spatial planning for connectivity and conservation through ecological corridors between marine protected areas and other effective area-based conservation measures

Maritime Spatial Planning (MSP) promotes the sustainable human activities development and uses in the marine space, playing a role in their effective management. The enhancement of connectivity is crucial for the conservation of biodiversity and landscape planning. Ecological Corridors (ECs) are an important type of connectivity for biodiversity conservation in fragmented habitats. The EU Biodiversity Strategy 2030 includes ECs into the network of protected areas and allows for the creation of additional protected areas. MSP studies considering ECs remain still lacking, especially for the design of networks between Marine Protected Areas (MPAs) and Other Effective area-based Conservation Measures (OECMs). In this paper, knowledge, and tools for investigating marine ECs were reviewed, with a systematic bibliometric analysis to summarize the current scientific research. Previous studies integrating ecological connectivity into planning for marine conservation have focused on models of larval dispersal, adult movements, and dispersal of single species by using benthic habitat proxies. Few studies were found on ECs in marine environments: in the coral Caribbean reef systems in the Gulf of Mexico; within benthic habitats along the Pacific coast of Canada; between MPAs in British Columbia (Canada); and by analyzing migratory species in the Yangtze estuary (China). Commonly used approaches to project and map ECs in marine environments are least-cost and circuit theories allowing to incorporate movement with cost or resistance to movement, depending on species and preferred habitats. The systematic bibliometric analysis returned 25 studies, most of which were from North America (40%) and European countries (36%) and the largest share of papers (68%) from 2018 to 2022. This review pinpointed the need of integrating different disciplines to investigate connectivity and the need by policymakers and practitioners to recognize the importance of ecological connectivity, even there are significant challenges for integrating connectivity into policies, planning, and conservation.

Forecasting suitable areas for wind turbine occurrence to proactively improve wildlife conservation

The United States is rapidly expanding production of renewable energy to meet increased energy demands and reduce greenhouse gas emissions. Wind energy is at the forefront of this transition. A central challenge is understanding the nexus between wind energy development and its capacity for negative effects on wildlife causing population declines and habitat loss. Collaboration among conservationists and developers, early in the planning process, is crucial for minimizing wind-wildlife conflicts. Such collaborations require data showing where wind and wildlife impacts occur. To meet this challenge and inform decision-making, we provide natural resource agencies and stakeholders information regarding where future wind turbines may occur, and the potential affects on natural resource management, including the conservation of priority species and their habitats. We developed a machine learning model predicting suitability of wind turbine occurrence (hereafter, wind turbine suitability) across an eight-state region in the United States, representing some of the richest areas of wind potential. Our model incorporates predictor variables related to infrastructure, land ownership, meteorology, and topography. We additionally created a constraint layer indicating areas where wind would likely not be developed because of zoning, protected lands, and restricted federal agency proximity guidelines. We demonstrate how the predictive wind turbine suitability model informs conservation planning by incorporating animal movement models, relative abundance models coupled with spatial conservation planning software, and population density models for three exemplar, high priority species often affected by wind energy: whooping cranes (Grus americana), golden eagles (Aquila chrysaetos), and lesser prairie-chickens (Tympanuchus pallidicinctus). By merging the wind turbine and biological models, we identified conservation priority areas (i.e., places sharing high suitability for wind turbines and species use), and places where wind expansion could minimally affect these species. We use our “species-wind turbine occurrence relationships” to demonstrate applications, illustrating how forecasting areas of wind turbine suitability promotes wildlife conservation. These relationships inform wind energy siting to reduce negative ecological impacts while promoting environmental and economic viability.

Habitat functionality: Integrating environmental and geographic space in niche modeling for conservation planning.

Niche modeling is typically used to assess the effects of anthropogenic land use and climate change on species distributions and to inform spatial conservation planning. These models focus on the suitability of local biotic and abiotic conditions for a species in environmental space (E-space). Although movements also affect species occurrence, efforts to formally integrate geographic space (G-space) into niche modeling have been hindered by the lack of comprehensive theoretical frameworks. We propose the "functional habitat" framework to define areas that are simultaneously of high quality in E-space, and functionally connected to other suitable habitats in G-space. Originating in metapopulation ecology, approaches have been developed to assess the amount of suitable connected habitats, based on the proximity between pairs of locations. Using network theory, which operates in topological space (T-space, defined by a network), we extended these metapopulation approaches to integrate movement constraints in G-space with niche modeling in E-space. We demonstrate the functional habitat framework using empirical data (GPS tracking and population monitoring) throughout the European wild mountain reindeer (Rangifer t. tarandus) distribution range. We show that functional habitat outperforms traditional suitability in explaining the species' distribution. This approach integrates effects from habitat loss and fragmentation for spatial conservation planning, and avoids overemphasizing small, inaccessible areas with locally suitable habitats. The functional habitat framework formally integrates biotic, abiotic, and movement constraints in niche modeling using network theory, thus opening a wide range of applications in spatial conservation planning.

Benefits of genetic data for spatial conservation planning in coastal habitats

Benefits of genetic data for spatial conservation planning in coastal habitats

Linking plant and vertebrate species to Nature’s Contributions to People in the Swiss Alps

Since the late 1990s, Nature’s Contributions to People (NCPs; i.e. ecosystem services) were used as a putative leverage for fostering nature preservation. NCPs have largely been defined and mapped at the landscape level using land use and cover classifications. However, NCP mapping attempts based directly on individual species are still uncommon. Given that species shape ecosystems and ultimately deliver NCPs, mapping NCPs based on species distribution data should deliver highly meaningful results. This requires first establishing a census of the species-to-NCP relationships. However, datasets quantifying these relationships across several species and NCPs are rare. Here, we fill this gap by compiling literature and expert knowledge to establish the relationships of 1816 tracheophyte and 250 vertebrate species with 17 NCPs in the Swiss Alps. We illustrated the 31,098 identified species-NCP relationships for the two lineages and discuss why such a table is a key initial step in building spatial predictions of NCPs directly from species data, e.g. to ultimately complement spatial conservation planning.

Modeling Ganges river dolphin distribution and prioritizing areas for efficient conservation planning- a range-wide assessment

The Endangered Ganges river dolphin is a flagship species that inhabits the Ganges-Brahmaputra-Meghna and Karnaphuli-Sangu river systems. Exposed to a multitude of environmental stresses and anthropogenic perturbations, the species has experienced severe population decline and shrinking of potential habitat in much of its distribution range. A range-wide mapping of its potential habitat and assessment of factors associated with species occurrence therefore bears immense relevance for conservation planning. We used an ensemble of species distribution models (SDM) using occurrence data to investigate dolphin distribution in relation to hydrological, climatic, physiographic, land cover and anthropogenic variables across the species entire range. We followed a systematic prioritization approach to identify highly suitable habitat patches (potential hotspots) for dolphins that require immediate protection. We identified nearly 7945 sq. km of river area as highly suitable for dolphins as habitat refugia for the species, more than 93% of which are outside the protected area regime, thus demanding immediate conservation attention. This study is a step towards delivering evidence required for spatial risk assessments and conservation planning wherein the habitat suitability maps will help in developing better management plans and strategies, and the predicted three tier classification of suitable habitats will facilitate decision making and prioritization of river segments for inclusion in the protected area network. We recommend that the inferences drawn from our study must be implemented on priority to ensure species conservation in the riverscape. Besides, our study provides huge scope for fine scale assessment and validation of the predicted suitable areas for model improvement.

Applying ensemble ecosystem model projections to future-proof marine conservation planning in the Northwest Atlantic Ocean

Climate change is altering marine ecosystems across the globe and is projected to do so for centuries to come. Marine conservation agencies can use short- and long-term projections of species-specific or ecosystem-level climate responses to inform marine conservation planning. Yet, integration of climate change adaptation, mitigation, and resilience into marine conservation planning is limited. We analysed future trajectories of climate change impacts on total consumer biomass and six key physical and biogeochemical drivers across the Northwest Atlantic Ocean to evaluate the consequences for Marine Protected Areas (MPAs) and Other Effective area-based Conservation Measures (OECMs) in Atlantic Canada. We identified climate change hotspots and refugia, where the environmental drivers are projected to change most or remain close to their current state, respectively, by mid- and end-century. We used standardized outputs from the Fisheries and Marine Ecosystem Model Intercomparison Project and the 6th Coupled Model Intercomparison Project. Our analysis revealed that, currently, no existing marine conservation areas in Atlantic Canada overlap with identified climate refugia. Most (75%) established MPAs and more than one-third (39%) of the established OECMs lie within cumulative climate hotspots. Our results provide important long-term context for adaptation and future-proofing spatial marine conservation planning in Canada and the Northwest Atlantic region.

Protected areas of Brazil’s coastal- marine system: spatial modeling and conservation planning on biomes – ocean interface

The limits of the six biomes of the Brazilian territory (i.g. Amazon, Atlantic Forest, Cerrado, Caatinga, Pampa and Pantanal) were recently revised,1 and a new territorial section of the ocean-continent interface, called Marine Coastal System (CMS) was presented. However, despite being a central theme for conservation planning, the spatial relationship between federal conservation units of Brazil (FCU) and CMS remained without integration. In this work we investigate ecological and territorial representativeness of FCU on Brazil's four geopolitical regions with biomes and ocean interface by developing spatial modeling (five models) encompassing a broad biogeographic context. The objective was to determine the spatial relationship between CMS and FCU, through the application of a set of topological and algebraic rules. Maps of spatial distribution of the FCU in the 5 biomes and in the 4 geopolitical regions shows overlapping CMS. The results indicate that among the 63 FCU found by the M_5 model, 51 FCU present a territorial sharing area with 5 biomes: Amazon, Pampa, Atlantic Forest, Caatinga and Cerrado. In the Amazon and Pampa biomes occur the largest area of overlap with the CMS, but the highest concentration of FCU occurs in the Atlantic Forest biome. The CMS area in the Northeastern region presented the highest environmental heterogeneity, and overlaps four biomes, encompassed most of the FCU of the ocean-continent interface, and also evidenced that the lack of integration of both legal concepts and government databases might cause differences on ecological and territorial representativeness of FCU on Brazil's four geopolitical regions with biomes-ocean interface.

An expeditious low-cost method for the acoustic characterization of seabeds in a Mediterranean coastal protected area

Posidonia oceanica meadows are ecosystem engineers which, despite their ecological relevance, are experiencing habitat fragmentation and area decrease. Cartography and information on the ecological status of these habitats is key to an effective maritime spatial planning and management for habitat conservation. In this work we apply an acoustic methodology to map benthic habitats (substrate and vegetation) in an archipelago of the Natura 2000 Network close to the coast of Murcia (SE Spain) where dense and sparse areas of P. oceanica, and patches of Cymodocea nodosa appear over a sandy and had bottom. The methodology uses dual frequency information (200 kHz and 38 kHz) acquired with a single-beam echosounder to develop a bathymetry, and performs sea bottom and vegetation supervised classifications, using video and scuba diver observations as groundtruthing data. Sea bottom was classified from acoustic features of the first and second 200 kHz echoes into 5 substrate classes using a random forest classifier: sand, fine sand, coarse sand, hard bottoms and hard bottoms with sandy patches. The vegetation was classified from features extracted from the "above-bottom" part of the echo (height and backscattering intensity) in both frequencies, resulting also in a 5 class classification: C. nodosa meadows, dense P. oceanica meadows, dispersed P. oceanica meadows, dense P. oceanica with sand patches, and no-vegetation; according to the random-forest Gini index, 38 kHz features were the most informational variables for this classification. The validation accuracies of both classifications were 85% (substrates) and 70% (vegetation), close to accuracies reported in the literature when using a similar number of classes. The results of this article (including bathymetric, and substrate and vegetation thematic maps), together with the acoustic methodology described and used, are contributions that can improve the continuous monitoring of Mediterranean seagrasses.

Spatial coalescent connectivity through multi-generation dispersal modelling predicts gene flow across marine phyla

Gene flow governs the contemporary spatial structure and dynamic of populations as well as their long-term evolution. For species that disperse using atmospheric or oceanic flows, biophysical models allow predicting the migratory component of gene flow, which facilitates the interpretation of broad-scale spatial structure inferred from observed allele frequencies among populations. However, frequent mismatches between dispersal estimates and observed genetic diversity prevent an operational synthesis for eco-evolutionary projections. Here we use an extensive compilation of 58 population genetic studies of 47 phylogenetically divergent marine sedentary species over the Mediterranean basin to assess how genetic differentiation is predicted by Isolation-By-Distance, single-generation dispersal and multi-generation dispersal models. Unlike previous approaches, the latter unveil explicit parents-to-offspring links (filial connectivity) and implicit links among siblings from a common ancestor (coalescent connectivity). We find that almost 70 % of observed variance in genetic differentiation is explained by coalescent connectivity over multiple generations, significantly outperforming other models. Our results offer great promises to untangle the eco-evolutionary forces that shape sedentary population structure and to anticipate climate-driven redistributions, altogether improving spatial conservation planning.

Mapping habitats sensitive to overgrazing in the Swiss Northern Alps using habitat suitability modeling

Unsuitable livestock farming is considered as a main driver of biodiversity loss. In the high elevation areas across the world, many subalpine and alpine natural herbaceous communities are highly sensitive to sheep overgrazing. Such habitats of high biogeographic and conservation value are refugia for slow-growing, locally rare, and cold-adapted species. However, at a regional scale, no maps of these sensitive habitats exist that the authorities could refer to for regulating grazing. We therefore studied the possibility of using habitat suitability modeling (HSM) to map five selected habitats that are potentially threatened by overgrazing in the Northern Alps of the Swiss canton of Fribourg. For each habitat, we defined a group of characteristic species and gathered their occurrences from national data centers. These occurrences were pooled within each group and used as presences to calibrate the HSM. High-resolution predictors (10 m) were used to achieve fine-scale modeling. The models predicted accurate and ecologically relevant distributions for three of the habitats: alpine swards and heaths on exposed ridges and peaks, unstable calcareous screes and vegetated snow patches. These results show that habitats that are topographically and environmentally well-defined can be finely predicted by HSM using distributions of characteristic species for use in spatial conservation planning. In the context of summer pasture management, this helped us to translate the Swiss legal basis onto maps of authorized grazing pressure.