Areas Of High Conservation Value Research Articles

Identifying complementary conservation and restoration priority areas for plant species

The coverage of protected areas (PAs) remains far from the Kunming-Montreal target and degraded ecosystems are greatly limiting the conservation efficiency of PAs. Therefore, this paper proposes a method to identify conservation and restoration priority areas to supplement existing PAs. A case study was conducted focusing on Yunnan, southwestern China, which intersects with three world biodiversity hotspots. First, the spatial ranges for 3768 representative conservation plant species were mapped using species distribution models. Subsequently, planning units were classified into three restorability categories, namely no-need restoration, potentially restorable and non-restorable units, according to land cover changes between 2000 and 2020. Then, conservation and restoration priority areas were identified by applying a two-step systematic conservation planning process. Finally, replacement cost analysis was applied to compare the effectiveness of existing PAs and the overall 30 % priority areas. Northwestern, southwestern, and southeastern Yunnan have high biodiversity conservation values. Especially in eastern and southeastern Yunnan, large amounts of restoration priority areas were identified. Conservation and restoration priority areas account for 15.80 % and 3.69 % of Yunnan's land, respectively. Compared to existing PAs, conservation priority areas can increase the number of species covered from 2461 to 3277, and further to 3566 when including restoration priority areas. Compared to existing PAs, the mean species coverage in the overall 30 % priority areas has increased from 27.28 % to 72.69 %. Notably, 12.86 % of existing PAs were identified as restoration priority areas. This study indicates that in addition to conservation measures, implementing restoration strategies in high conservation-value areas is equally important.

Applying landscape ecological principles in comprehensive landscape protection: Šumava National Park as a case study

In the face of ongoing anthropogenic pressure and biodiversity loss, there is a need to protect nature more effectively. Therefore, we propose a comprehensive and consecutive approach utilising landscape ecological principles and methods for effective landscape protection and spatial nature conservation. Methods applicable in various conditions are exemplified through case studies from the Šumava National Park, the largest NP in Czechia. Using a set of spatial environmental, landscape ecological and geographical data we can: Characterise the area of interest from the physical-geographical, socioeconomic, and management point of view to create the concept´s framework and review important background information for analysis of the area. Therefore, the key factors for landscape protection and biodiversity conservation are defined. Analyse trends and processes of landscape dynamics in terms of land cover, landscape structure and habitat fragmentation and connectivity, which helps us to set main objectives of landscape protection and nature conservation. Use data about environment conditions and key species and habitat occurrence to model habitat suitability, identify their suitable areas, and thus improve their protection. As a result, areas of high conservation value are distinguished. Synthetize outputs of the above-mentioned steps and prioritise the target goals of landscape protection and biodiversity conservation in the area of interest. This leads to the effective zonation, which is a necessary condition for the application of appropriate management measures.

High Conservation Value area in oil palm landscape as a potential ecotourism destination for birdwatching activity

High Conservation Value area in oil palm landscape as a potential ecotourism destination for birdwatching activity

Prospect of the high conservation value areas as tourisms destination in the oil palm plantation, Pasangkayu Regency, West Sulawesi, Indonesia

Prospect of the high conservation value areas as tourisms destination in the oil palm plantation, Pasangkayu Regency, West Sulawesi, Indonesia

Ensemble modeling to identify high conservation value areas for endemic and elusive large-sized mammals of the Philippines

Bubalus mindorensis (tamaraw) and Sus oliveri (Mindoro warty pig) are emblematic of Mindoro Island as a faunal biodiversity hotspot in the Philippines. However, these endemic, red-listed mammals are of socioecological concern due to pressures within their contracting home ranges. Conservation efforts are logistically hindered by their elusive yet aggressive behavior and coexistence with indigenous tribes. This study aims to identify high conservation value areas (HCVAs), sites where both species are highly suitable. Ensemble species distribution modeling (SDM) based on nine algorithms was performed. For each species, three ensemble SDMs were calibrated following three proposed approaches in decreasing hyperparameter-based model complexity: standard, tuned, and limited. Across ensemble SDMs, complexity and True Skill Statistics (TSS)-based accuracy are positively associated. Still, the limited ensemble SDM of tamaraw (TSS = 0.740) and Mindoro warty pig (TSS = 0.855) retain good discriminatory performance. These coincidingly predict that known occurrence sites are areas of high suitability, which are spatially fragmented into four patches across the Mindoro Mountain Range: Mt. Calavite Wildlife Sanctuary, Upper Amnay Watershed, Aruyan-Malati, and Mts. Iglit-Baco National Park. In total, these prospective HCVAs cover 405.17 km2 (3.83%) of Mindoro Island, which represent areas of priority for the ongoing Mindoro Island Biodiversity (BD) Corridor Project. This study substantiates the need for strategic management of these HCVAs. Despite overarching study-specific limitations and uncertainties, this study advocates the informed use of ensemble SDMs for reserve selection, conservation planning, and wildlife-related policymaking in Mindoro Island.

Application of Machine Learning in Ecological Red Line Identification: A Case Study of Chengdu–Chongqing Urban Agglomeration

China’s Ecological Protection Red Lines (ERLs) policy has proven effective in constructing regional ecological security patterns and protecting ecological space. However, the existing methods for the identification of high conservation value areas (HCVAs) usually use physical models, whose parameters and processes are complex and only for a single service, affecting the ERL delineation. In this study, the data-driven machine learning (ML) models were innovatively applied to construct a framework for ERL identification. First, the One-Class Support Vector Machine (OC-SVM) was used to generate negative samples from natural reserves and ecological factors. Second, the supervised ML models were applied to predict the HCVAs by using samples. Third, by applying the same ecological factors, the traditional physical models were used to assess the ecological services of the study area for reference and comparison. Take Chengdu–Chongqing Urban Agglomeration (CY) as a case study, wherein data from 11 factors and 1822 nature reserve samples were prepared for feasibility verification of the proposed framework. The results showed that the area under the receiver operating characteristic curve (AUC) of all ML models was more than 97%, and random forest (RF) achieved the best performance at 99.57%. Furthermore, the land cover had great contributions to the HCVAs prediction, which is consistent with the land use pattern of CY. High-value areas are distributed in the surrounding mountains of CY, with lush vegetation. All of the above results indicated that the proposed framework can accurately identify HCVAs, and that it is more suitable and simpler than the traditional physical model. It can help improve the effectiveness of ERL delimitation and promote the implementation of ERL policies.

Establishing a protected area network in Xinlong with other effective area-based conservation measures.

Protected areas (PAs) are pivotal to biodiversity conservation, yet their efficacy is compromised by insufficient funding and management. So-called other effective area-based conservation measures (OECMs) present a paradigm shift and address PA limitations. Such measures can expand conservation areas, enhance connectivity, and improve the existing system. To assess the conservation status of biodiversity in Tibetan cultural areas in China, we investigated the spatial distribution of wildlife vulnerable to human disturbance (large- and medium-sized mammals and terrestrial birds) in Xinlong, a traditional Tibetan cultural area. In particular, we compared a PA (Xionglongxi Nature Reserve) and OECMs targeting species conservation. We also investigated the relationship of wildlife with human temporal and spatial activities. The OECMs complemented areas not covered by PA, especially in rich understory biodiversity regions. More species in OECMs tolerated human presence than species in the PA. Existing biodiversity reserves failed to cover areas of high conservation value in Tibet and offered limited protection capacity. Expanding PAs and identifying OECMs improved Xinlong's system by covering most biodiversity hotspots. Building on the tradition of wildlife conservation in Tibet, harnessing OECMs may be an effective means of augmenting biodiversity conservation capacity. We recommend further evaluation of OECMs effectiveness and coverage in Tibetan area as a way to enhance the current PA system.

Where east meets west: Phylogeography of the high Arctic North American brant goose.

Genetic variation in Arctic species is often influenced by vicariance during the Pleistocene, as ice sheets fragmented the landscape and displaced populations to low- and high-latitude refugia. The formation of secondary contact or suture zones during periods of ice sheet retraction has important consequences on genetic diversity by facilitating genetic connectivity between formerly isolated populations. Brant geese (Branta bernicla) are a maritime migratory waterfowl (Anseriformes) species that almost exclusively uses coastal habitats. Within North America, brant geese are characterized by two phenotypically distinct subspecies that utilize disjunct breeding and wintering areas in the northern Pacific and Atlantic. In the Western High Arctic of Canada, brant geese consist of individuals with an intermediate phenotype that are rarely observed nesting outside this region. We examined the genetic structure of brant geese populations from each subspecies and areas consisting of intermediate phenotypes using mitochondrial DNA (mtDNA) control region sequence data and microsatellite loci. We found a strong east-west partition in both marker types consistent with refugial populations. Within subspecies, structure was also observed at mtDNA while microsatellite data suggested the presence of only two distinct genetic clusters. The Western High Arctic (WHA) appears to be a secondary contact zone for both Atlantic and Pacific lineages as mtDNA and nuclear genotypes were assigned to both subspecies, and admixed individuals were observed in this region. The mtDNA sequence data outside WHA suggests no or very restricted intermixing between Atlantic and Pacific wintering populations which is consistent with published banding and telemetry data. Our study indicates that, although brant geese in the WHA are not a genetically distinct lineage, this region may act as a reservoir of genetic diversity and may be an area of high conservation value given the potential of low reproductive output in this species.

Opportunities for Biodiversity Conservation via Urban Ecosystem Regeneration

Conservation traditionally focuses on at-risk species and relatively intact ecosystems. As the human population and our global impact have risen, many more species and ecosystems are at risk and fewer intact ecosystems remain, with urbanization being a major contributing factor. Cities and their inhabitants are here to stay, and the prevalence of urbanization, often in the vicinity of areas of high conservation value, requires reconsideration of the conservation value of urban ecosystems and urban green spaces. Our aim is to explore the practical aspects of such actions. Urban ecosystem regeneration will require the incorporation of strategies for urban ecosystem regeneration into an overall conservation policy. The novel paradigm of urban ecosystem regeneration, advocated here, maximizes the capacity of urban spaces to support biodiversity while reducing undesirable outcomes and enhancing human wellbeing. The potential for cities to exacerbate biological invasion, climate change, and other ecosystem-degrading factors requires particular attention in devising a strategy for conservation in urban spaces, made essential by the predicted further spread of cities across the globe.

An underwater clash of spears: Public engagement in Mediterranean lionfish control efforts

Abstract Invasive alien species pose a great challenge in conservation ecology. Rapid establishment of common lionfish (Pterois miles) in the eastern Mediterranean Sea and its ongoing westward expansion raises many questions about how to sustainably combat this invasion in the long term. Drawing on experiences from the western Atlantic invasion, citizen scientists were engaged and demonstrated the efficiency of long‐term coordinated removals for the first time in the Mediterranean Sea. Findings reveal a sustained participation and interest throughout the coordinated removal events that encourage the organization of future events. Removal Action Teams were found effective at reducing lionfish numbers in small (less than half a hectare) areas of high conservation value, when removals were repeated systematically. Single‐day lionfish derbies, operated at greater spatial scales, succeeded in a 50% reduction in lionfish abundance while removing most large (>30 cm) individuals from an area after three consecutive events. Given the recreational character of such activities, coordinated removals are useful options for management and conservation when guided by competent authorities and supported by citizens, as they promote marine environmental awareness and help develop a sense of stewardship among members of the public.

Mortality on the tracks: spatiotemporal patterns to rail‐kill in the Balule Nature Reserve, South Africa

The global dependency on railways as an economical and environmentally‐friendly option for transportation is steadily increasing. Despite their numerous benefits, railways and train traffic can have negative impacts on wildlife, particularly through the risk of mortality due to collisions with trains, entrapment in rails, or electrocution at overhead powerlines. In most cases, these impacts are under‐investigated, thus remain unmitigated. In this study, we describe patterns of rail‐mortality of the local fauna in Balule Nature Reserve, South Africa. In addition to exploring which species are most vulnerable to rail‐mortality, we explore the role that seasonal variation, the daily activity patterns of the species, and the surrounding habitat type have on the occurrence of wildlife‐rail‐mortality. From 25 May 2020–29 March 2021, we conducted carcass surveys over three 5 km railway segments, corresponding to the three dominant habitat types in the nature reserve: open grassland, open woodland and mixed shrubland. Each 5 km segment of railway was surveyed during the wet season (November–March) and the dry season (May–September) to account for seasonal variation. We recorded 99 rail‐kills, of which 29% were mammals, 26% were birds, 26% were reptiles, and 18% were amphibians. Mammal carcasses were found most frequently in the dry season, while amphibians were only detected in the wet season. Amphibian carcasses were all nocturnal species, while diurnal species dominated the bird carcasses found. Finally, most rail‐kill carcasses were found in mixed shrublands, while open woodlands had the lowest frequency of rail‐kill. The detrimental impacts of railway‐mortality on wildlife may be more pronounced in areas of high conservation value, such as nature reserves, and it is essential to study and mitigate these impacts, in order to foster successful co‐existence of wildlife and humans in the landscape.

Investigating the planning efficiency of species richness- and complementarity-based algorithms in data deficient areas

Efficient conservation planning is a necessary approach for protecting endangered species with deficient distribution data and reducing biodiversity loss. Richness- and complementarity-based algorithms can improve conservation planning efficiency to different degrees, but differences in planning efficiency caused by data availability and algorithms are often disregarded and require clarification. Here, we classified endangered, endemic, and national key protected plant species based on their occurrence data availability for species distribution modeling. We implemented species richness- (SRA), species number complementarity- (SNCA) and species value complementarity-based algorithms (SVCA) to identify priority conservation areas (PCAs) in the Southeast Himalaya Biodiversity Priority Conservation Area. We established six scenarios and compared their planning efficiencies. The spatial distribution of PCAs and their conservation efficiency varied depending on data availability and optimization algorithms. The 17%, 30%, and 45% PCAs identified in the six scenarios differed in geographical pattern, whereas differences in species occurrences had less effect on their conservation efficiency. Specifically, the PCAs identified by using species with sufficient data as surrogates captured species with high conservation value. Additionally, SNCA was better suited for capturing species number, and SVCA was more cost-effective for protecting species area and species of high conservation value, but SRA distribution pattern presented less fragmented and well-connected. Nevertheless, 50.11% area of the optimized PCAs remained uncovered by existing protected areas. Our analysis reveals the influence of species occurrence data availability, and algorithms on planning efficiency, and provides a cost-effective solution for improving planning efficiency and optimizing protected area network in data deficient areas.

Mapping soil corrosivity potential to exclusion fencing using pedotransfer functions and open‐source soil data

AbstractSoil corrosivity is a term used to describe the corroding susceptibility (risk) of metal infrastructure in different soil environments. Soil corrosivity mapping is a crucial step in identifying potentially problematic, high‐maintenance fence lines and can help improve fence longevity by identifying soil environments where the use of more expensive, corrosion‐resistant materials would be more cost‐effective in the long term. Soil corrosion damage sustained on exclusion fences can be a serious management issue for conservation programs and initiatives, as it weakens the fence netting and provides opportunities for invasive animal migration and occupation (e.g. feral cats and foxes) into areas of high conservation value. The increasing accessibility of geospatial analysis software and the availability of open‐source soil data provide land managers with the opportunity to implement digital soil databases and pedotransfer functions to produce fence corrosion risk maps using commonly measured soil attributes. This paper uses open‐source government agency soil data (shapefiles) to map fence corrosion risk in the southern part of the Yorke Peninsula in South Australia, with the intention to assist with the installation of a new barrier (exclusion) fence as part of the Marna Banggara rewilding project. The risk classifications (low, moderate and high risk) made by this map were compared with rates of zinc corrosion (μm/year zinc loss) observed at field sites and correctly predicted the amount of fence damage sustained at five of the eight sites. The mapping approach outlined in this study can be implemented by environmental managers in other areas to inform strategies for enhancing fence longevity.

Comparison of traditional and molecular surveys of fish biodiversity in southern Te Wāhipounamu/Fiordland (Aotearoa/New Zealand)

AbstractEffective management of biodiversity requires regular surveillance of multiple species. Analysis of environmental DNA (eDNA) by metabarcoding holds promise to achieve this relatively easily. However, taxonomy‐focused eDNA surveys need suitable molecular reference data, which are often lacking, particularly at the species level and for remote locations. To evaluate the comparability of environmental DNA surveys and traditional surveys in a real‐life case study in a marine area of high conservation value, we conducted a biodiversity survey of the fish in remote and pristine Te Wāhipounamu/Fiordland (Aotearoa/New Zealand), incorporating multiple data sources. We compared eDNA‐derived species identifications against Baited Remote Underwater Video (BRUV) data collected at the same time and locations as eDNA. We also cross‐referenced both eDNA and BRUV data against literature and the Ocean Biodiversity Information System (OBIS), with literature and OBIS data representing a summary of multiple traditional surveying approaches. In total, we found 116 fish species in our study area. Environmental DNA detected 43 species; however, only three of those species overlap with species known from the literature, OBIS, or our BRUV analyses. A total of 61 fish species were known from the region from the literature, while OBIS listed 28 species, and our BRUV analyses picked up 26 species. BRUV data coincided more strongly than eDNA data with literature and OBIS data. Twenty of the 26 species detected by BRUV were known from literature and OBIS. We argue that limitated DNA reference databases are the main cause of this discrepancy, and our results indicate that eDNA of rare and endangered species can be detected if matching reference data were available. Environmental DNA analyses can only identify species present among reference data and with relaxed taxonomic assignment parameters may converge on relatives of detected species if the actually existing species themselves are missing among reference data. However, the high number of species detected by our eDNA analyses confirms that eDNA could be a powerful tool for biodiversity surveys if suitable investments in local reference databases were made.

Optimization of a soil type prediction method based on the deep learning model and vegetation characteristics

The structure and composition of forest vegetation plays an important role in different ecosystem functions and services. This study aimed to identifying soil types based on vegetation characteristics using a deep learning model in the High Conservation Value (HCV) area of Central Kalimantan, spanning 632.04 hectares. The data on vegetation were collected using a combination method between line transect and quadratic plots were placed. The development of a deep learning model was based on the results of a vegetation survey and the processing of aerial photos using the Feature Classifier method. The results of applying a deep learning model could provide a relatively accurate and consistent prediction in identifying soil types (Entisols 62%, Spodosols 90%, Ultisols 90% accuracy). The composition of vegetation community in Ultisols was dominated of seedling and tree (closed canopy), meanwhile in Entisols and Spodosols was dominated of seedling and sapling (dominantly open canopy). Ultisols exhibited the highest species richness (57 species), followed by Spodosols (31 species) and Entisols (14 species). Ultisols, Entisols, and Spodosols displayed even species distribution(J' close to 1) without dominance of certain species(D < 0.5). The species diversity index was at a low to moderate level(H' < 3), while the species richness index remained at a very low level(D_mg > 3.5).

Enhancing the Sustainability of Oil Palm Plantations Through the Application of Principles and Adaptive Management of High Conservation Value Areas in Central Kalimantan

The rapid development of oil palm plantations raises environmental issues related to biodiversity and conservation. Thus, a holistic and integrated approach is needed to manage high conservation values (HCV). This holistic and integrated approach involves various stakeholders in implementing sustainability principles. This study aims to analyze the effectiveness of applying the principles and evaluating the adaptive management practices of HCV areas applied to oil palm plantations. The research was conducted on an oil palm plantation in Seruyan District, Central Kalimantan Province, Indonesia, with HCV 1 – 5 criteria covering an area of 5379 ha. Employing an observational method, the data were collected via field observations and interviews with relevant stakeholders, including oil palm plantation management, environmental organizations and local communities. The findings show that by protecting HCV, oil palm plantations can operate sustainably and reduce environmental negative impacts. The application of the principles of HCV areas in the company involves identifying, assessing and protecting areas with high ecological, social, and cultural values. These are then used as the basis for recommendations for adaptive management in oil palm plantations. Through adaptive management, oil palm plantations can adapt their practices to local conditions, reduce negative impacts, assess impacts, and take appropriate steps according to the conditions. The success of adaptive management carried out by the company can be seen based on data on the decline in HCV openings and the maintenance of HCV 1 - 5 areas. Thus, by applying adaptive principles and management, oil palm plantations in Central Kalimantan can increase sustainability, protect the environment, and provide sustainable social and economic benefits. Having important implications for the palm oil industry, this research can be used as a guide in policy-making that supports the development of environmentally responsible oil palm plantations.

Projecting the dynamics of invading deer with pattern‐oriented modelling to support management decision‐making

Abstract Avoiding the undesirable impacts of invasive species requires robustly evaluating the effects of alternative management scenarios. Such evaluations depend on reliable spatio‐temporal projections of changes in the distribution and abundance of the invasive species under different scenarios. However, commonly used modelling approaches are constrained for this purpose because they do not incorporate demographic processes and are seldom validated. We develop a spatially and temporally explicit grid‐based population model for invasive fallow deer Dama dama in Tasmania, Australia, validated against observed distribution and abundance ‘targets’ using a pattern‐oriented approach. We use this validated model to project the future invasion patterns of deer, including encroachment into areas of high conservation value, under eight harvest and habitat suitability scenarios. Projected population sizes of deer differ greatly depending on harvest and habitat suitability scenarios. Without harvest, the population grows sixfold, from about 80,000 deer in 2019 to over 500,000 by 2100. In contrast, the population stabilises at 32,000–41,000 deer with 25% annual harvest. Abundance in the environmentally sensitive Tasmanian Wilderness World Heritage Area (TWWHA), a region of high conservation value, increases in all scenarios. We identify likely areas in the expanding range of deer where targeted removal should be most effective at minimising deer numbers in the TWWHA. Synthesis and applications: Using a pattern‐oriented model validated with spatio‐temporal data, we show how the future distribution and abundance of invasive fallow deer in Tasmania can be substantially reduced by targeted increases in harvest and prioritising areas for removal around high conservation value regions. Our approach can be used to project likely effects of management interventions on future distributions and abundances for a range of invasive taxa.

Analysis of Vegetation and Plant Diversity in High Conservation Value Areas in Oil Palm Plantations

The expansion of oil palm plantations is often rumored to impact the destruction of forests and other ecosystems with high conservation value (HCV). This study aimed to analyze the vegetation and plant diversity in the HCV area of oil palm plantations. The research was conducted on an oil palm plantation in Seruyan District, Central Kalimantan Province, Indonesia with an HCV area of 5379 ha. The research was carried out using the grid transect method on various types of vegetation, divided into four plots: seedlings, saplings, poles and trees. Parameters observed included the number of species, the number of individuals and the level of plant diversity. The results showed that the research location had good vegetation and plant diversity in the HCV area. There were 25 plant species from 17 families with a total of 355 plants. The number of species found in the seedling plots was 11 species (6 families) with a total of 38 plants; in the sapling plots was 16 species (12 families) with a total of 159 plants; in the pole plots was 14 species (11 families) with a total of 43 plants, and in the tree plots was 13 species (10 families) 115 plants. There was variation in the number of species and families in each plot. The overall plant diversity index was low. The diversity index of plants in the plots of seedlings, saplings, poles and trees (and the average) was in the low category.

Identifying conservation values: a case study in trans-Himalayan region of Thanpattan, Lahaul-Spiti, Himachal Pradesh

The rugged topography, harsh climate and limited livelihood options have resulted in pastoralism being the predominant land use in the Himalayan landscape. To identify the most significant sites in this landscape, we employed the concept of ‘High Conservation Value Areas’ (HCVAs) in Thanpattan, one of the largest pastureland in Lahaul-Spiti. We have examined this region as a potential HCVA, providing information on biological diversity, pastoralism and related threats. The Gaddi community of Chamba and Bharmour districts relies on these pastures for their livelihoods, and several threatened flora and fauna species also call the area home. We found that Thanpattan fulfils all six criteria for HCVAs and is undoubtedly an HCVA due to its biodiversity values and the dependency of the indigenous communities on the region.

Jurisdictional approaches to High Conservation Value area designation using regulatory instruments: an Indonesian pilot project

Agricultural expansion is the primary driver of tropical deforestation and ecological degradation. Certification schemes for sustainable agricultural supply chains, such that of the Roundtable on Sustainable Palm Oil (RSPO), seek to address this issue by identifying and protecting High Conservation Value (HCV) areas within concessions. Although RSPO certification of individual concessions has been beneficial, it has had limited efficacy in arresting systemic ecological degradation at larger scales. In response, certification at a regional, ‘jurisdictional’ scale concordant with local environmental regulation has been proposed as an alternative to conventional, piecemeal certification. Jurisdictional certification schemes require alignment with local legislation to ensure integration with governmental environmental and land-use planning; yet, questions of which legislation, and at which level of government, have remained unaddressed. Here, we report on a pilot jurisdictional RSPO certification scheme implemented by an Indonesian district, based on environmental carrying capacity assessments (ECCA) as legislated by the district government. Using the ECCA, we identified likely HCV areas across the district and considered their distributions with respect to three factors of feasible HCV management: (a) similarity with alternative HCV areas identified by a conventional HCV Screening method, (b) sensitivity to aspects of underlying legislation, and (c) scope for unilateral district-wide management. Likely HCV areas were generally similar between the ECCA and HCV Screening method, as each set spanned ∼90% of the district. However, higher-confidence HCV areas according to the ECCA were much less extensive, at 51% of the district, and uniquely extensive across oil-palm concessions. HCV area designation was highly sensitive to the legislated parameters of the ECCA, namely, the selection and estimation of key ecosystem services. Potentially, subtle variations to ECCA implementation, such as those proposed by agro-industrial lobbyists, would significantly affect jurisdictional HCV designations. Finally, some three-quarters of all HCV areas and higher-confidence HCV areas designated by the ECCA fell outside of the exclusive administrative authority of the district government, being confined to agricultural zones. In politically-decentralised Indonesia, jurisdictional HCV area management would therefore be narrowly confined to agricultural areas, or cooperation between district, provincial, and central governments would be essential to the protection of HCV areas generally across districts.