Areas Of High Conservation Value Research Articles

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.

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.

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.

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.

Biodiversity tourism: a concept for oil palm villages sustainable revitalization

Rural resilience has become an interestingly debated topic in recent years, with scholars offering opposing viewpoints. Studies have suggested that rural resilience is arguably better than that of urban. Especially in the context where the rural is supported economically by the existence of some businesses such as oil palm plantations. However, certain negative images are still linked to oil palm plantations, in particular with respect to biodiversity loss, despite many of the plantations having areas of high conservation value (HCV). HCVs are known to possess and attract wild species such as elephants, orangutans, and other primates, meaning that ecologically, HCV represents a significant added value of the oil palm plantations. This conceptual paper aims to contribute to this debate by envisioning feasible futures of biodiversity tourism for oil palm village revitalization by utilizing the biodiversity richness of HCVs. This study includes a conceptual model of biodiversity tourism for oil palm village revitalization that was developed using a causal loop diagram approach. The causal loop diagram depicts an overall understanding and describes the village system’s complexity. Positive and negative loops that form the reinforcement and balance circles represent the connection between the input and output variables. A systematic literature review and interviews with pilot village stakeholders were used to collect data. The potential of such a vision is discussed before finally concluding with an insight into the future of biodiversity tourism for oil palm village revitalization. This paper recognizes that biodiversity tourism for oil palm village revitalization can be done sustainably by presenting it as a complex system with its subsystems. It shows that oil palm villages and biodiversity are interdependent and interconnected. Moreover, biodiversity tourism can be recognized as a vehicle to promote the positive impacts of oil palm plantations in enhancing knowledge and awareness of biodiversity conservation beyond existing economic value.

The roles of high conservation value area to support biodiversity conservation in Indonesia

Oil palm plantations are often considered as one of the causes of the decline in biodiversity. Conversion of forest land to oil palm is the main factor. However, legally, land conversion can be carried out and oil palm plantation companies have also protected areas that have high conservation value, including important animal habitats. The purpose of this study is to assess the role of high conservation value areas in the conservation of biodiversity. The study was conducted on several oil palm plantations in Indonesia by conducting a literature review of high conservation value documents on several oil palm plantation companies. High conservation value areas in oil palm plantations are determined based on the presence of endangered and protected animals such as proboscis monkeys and orangutans. With the stipulation of the area as a HCV area, the presence of these animals becomes more concerned because the company has the responsibility to monitor the presence of these animals. In addition, the company also conducts socialization to the community and workers to take care of these animals. The existence of the HCV area also indirectly supports the government’s program in this case is the establishment of an Essential Ecosystem Area that functions to protect important animals outside the conservation area.

The role of high conservation value areas to maintaining ecological balance in oil palm plantations PT. Waimusi Agroindah, South Sumatera

Currently, oil palm plantations must carry out environmentally friendly plantation activities, one of which is by maintaining the biodiversity in or around the plantation area. Biodiversity can also reduce pest attacks that can reduce oil palm productivity. The research activities were carried out at PT. Waimusi Agroindah by conducting an inventory of plant, mammal, and bird species in HCV areas and oil palm plantations (young, medium, and mature palms). The results of the research in the HCV area showed that there were 4 types of trees, 10 types of poles, 7 types of saplings, 4 understorey plants and seedlings, 4 types of mammals, and 34 species of birds. Within the HCV area, three species of mammals protected by the government were found, namely the silvery lutung (Trachypithecus cristatus) as many as 3 individuals, and three species of birds, namely Haliastur indus, Elanus caerulaus, and Anhinga melanogaster. In the oil palm plantation area, only understorey stands were found, but various types of mammals and birds were found. The number of species of mammals and birds found in HCV areas is higher than in oil palm plantations. The number of vegetation types in the HCV area is more diverse so that it can be used as a place for wildlife to live, both for forage plants and nests. This shows the need for HCV areas in biodiversity conservation and as an ecological balancer in oil palm plantation areas.

Prioritizing global tall forests toward the 30 × 30 goals.

The Global Deal for Nature sets an ambitious goal to protect 30% of Earth's land and ocean by 2030. The 30 × 30 initiative is a way to allocate conservation resources and extend protection to conserve vulnerable and underprotected ecosystems while reducing carbon emissions to combat climate change. However, most prioritization methods for identifying high-value conservation areas are based on thematic attributes and do not consider vertical habitat structure. Global tall forests represent a rare vertical habitat structure that harbors high species richness in various taxonomic groups and is associated with large amounts of aboveground biomass. Global tall forests should be prioritized when planning global protected areas toward reaching the 30 × 30 goals. We examined the spatial distribution of global tall forests based on the Global Canopy Height 2020 product. We defined global tall forests as areas with the average canopy height above 3 thresholds (20, 25, and 30m). We quantified the spatial distribution and protection level of global tall forests in high-protection zones, where the 30 × 30 goals are being met or are within reach, and low-protection zones, where there is a low chance of reaching 30 × 30 goals. We quantified the protection level by computing the percentage of global tall forest area protected based on the 2017 World Database on Protected Areas. We also determined the global extent and protection level of undisturbed, mature, tall forests based on the 2020 Global Intact Forest Landscapes mask. In most cases, the percentage of protection decreased as forest height reached the top strata. In the low-protection zones, <30% of forests were protected in almost all tall forest strata. In countries such as Brazil, tall forests had a higher percentage of protection (consistently >30%) compared to forests of lower height, presenting a more effective conservation model than in countries such as the United States, where forest protection was almost uniformly <30% across height strata. Our results show an urgent need to target forest conservation in the greatest height strata, particularly in high-protection areas, where most global tall forests are found. Vegetation vertical structure can inform the decision-making process toward the 30 × 30 goals because it can be used to identify areas of high conservation value for biodiversity protection which also contribute to carbon sequestration.

Integrating climate change into agroforestry conservation: A case study on native plant species in the Brazilian Atlantic Forest

Abstract Designing multispecies systems with suitable climatic affinity and identifying species' vulnerability under human‐driven climate change are current challenges to achieve successful adaptation of natural systems. To address this problem, we need to (1) identify groups of species with climatic similarity under climate scenarios and (2) identify areas with high conservation value under predicted climate change. To recognize species with similar climatic niche requirements that can be grouped for mixed cropping in Brazil, we employed ecological niche models (ENMs) and Spearman's ρ for overlap. We also used prioritization algorithms to map areas of high conservation value using two Shared Socioeconomic Pathways (SSP2‐4.5 and SSP5‐8.5) to assess mid‐term (2041–2060) and long‐term (2061–2080) climate change impacts. We identified 15 species groups with finer climatic affinities at different times depicted on hierarchical clustering dendrograms, which can be combined into agroecological agroforestry systems. Furthermore, we highlight the climatically suitable areas for these groups of species, thus providing an outlook of where different species will need to be planted over time to be conserved. In addition, we observed that climate change is predicted to modify the spatial association of these groups under different future climate scenarios, causing a mean negative change in species climatic similarity of 9.5% to 13.7% under SSP2‐4.5 scenario and 9.5% to 10.5% under SSP5‐8.5, for 2041–2060 and 2061–2080, respectively. Synthesis and applications. Our findings provide a framework for agroforestry conservation. The groups of species with finer climatic affinities identified and the climatically suitable areas can be combined into agroecological productive systems, and provide an outlook of where different species may be planted over time. In addition, the conservation priority zones displaying high climate stability for each species individually and all at once can be incorporated into Brazil's conservation plans by policymakers to prioritize specific sites. Lastly, we urge policymakers, conservation organizations and donors to promote interventions involving farmers and local communities, since the species' evaluated have proven to maintain landscapes with productive forest fragments and can be conserved in different Brazilian ecosystems.