Integrating the Japanese vegetation categories and the IUCN global ecosystem typology – a high-resolution, terrestrial ecosystem dataset defining Subglobal ecosystem types under Ecosystem functional groups

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Data may be preliminary. 5 March 2026 V1 Latest version Share on Integrating the Japanese vegetation categories and the IUCN global ecosystem typology – a high-resolution, terrestrial ecosystem dataset defining Subglobal ecosystem types under Ecosystem functional groups Authors : Lea Végh 0000-0001-7948-480X , Jun Nishihiro , Hironori Toyama , Fumiko Ishihama 0000-0001-8515-5914 , Hiroyuki Kudo , Yuki Tanno , Taku Kadoya , Masato Yoshikawa , David Keith , and Yayoi Takeuchi 0000-0002-8402-7854 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.177269411.19684440/v1 395 views 137 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract The International Union for Conservation of Nature has recently developed a global ecosystem typology (IUCN typology) based on functional characteristics. However, the existing global maps for Level 3 of the typology ( Ecosystem functional groups , EFGs) have low spatial resolution and fail to recognize certain categories in Japan limiting precise ecosystem analysis for global comparisons. To address these, we developed Level 6 classification, Subglobal ecosystem types (SETs), of the IUCN typology in Japan, directly under EFGs, by using the Japanese vegetation maps provided by the Ministry of Environment. First, we systematically identified potential parent EFGs for each Japanese vegetation categories, then conducted repeated iterative expert reviews until consensus was reached. Finally, we incorporated the land-use classification developed by the National Institute for Environmental Studies. The resulting correspondence tables and high-resolution spatial dataset include 133 SETs, belonging to 28 EFGs, 14 Biomes , and 7 Realms , focusing on terrestrial and related ecosystems. Within these Realms , the Intensive land-use Biome had the largest surface area, followed by Temperate-boreal forests and woodlands. Compared to the global maps, we identified seven new EFGs in Japan and extended the northern geographical range of some subtropical EFGs. SETs along climatic and anthropogenic gradients were challenging to align with existing EFGs, as were SETs related to characteristic vegetation communities in Japan and Asia, such as bamboo forests. The SETs created in this study enhance national assessments by providing spatially explicit information on ecosystem distribution and land-use, therefore can form an integral part of regional and global biodiversity monitoring. Article type Research article Title Integrating the Japanese vegetation categories and the IUCN global ecosystem typology – a high-resolution, terrestrial ecosystem dataset defining Subglobal ecosystem types under Ecosystem functional groups Authors Lea Végh a , Jun Nishihiro b , Hironori Toyama c , Fumiko Ishihama a , Hiroyuki Kudo a , Yuki Tanno a , Taku Kadoya a , Masato Yoshikawa d , David A. Keith e,f , Yayoi Takeuchi a,g Affiliations a Biodiversity division, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan b Center for Climate Change Adaptation, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan c College of Arts and Sciences, J. F. Oberlin University, 3758 Tokiwa-machi, Machida, Tokyo 194-0294, Japan d Division of Environment Conservation, Institute of Agriculture, Tokyo University of Agriculture and Technology, 3-5-8 Saiwai-cho, Fuchu, Tokyo 183-8509, Japan e Centre for Ecosystem Science, University of New South Wales, Sydney, New South Wales, Australia f IUCN Commission on Ecosystem Management, Gland, Switzerland g Department of Biology, Graduate School of Science, Osaka Metropolitan University, Sugimoto Sumiyoshi-ku, Osaka 558-8585, Japan Correspondence Yayoi Takeuchi Department of Biology, Graduate School of Science, Osaka Metropolitan University, Sugimoto Sumiyoshi-ku, Osaka 558-8585, JapanPhone number: +81-6-6605-2579Email: [email protected] Abstract The International Union for Conservation of Nature has recently developed a global ecosystem typology (IUCN typology) based on functional characteristics. However, the existing global maps for Level 3 of the typology ( Ecosystem functional groups , EFGs) have low spatial resolution and fail to recognize certain categories in Japan limiting precise ecosystem analysis for global comparisons. To address these, we developed Level 6 classification, Subglobal ecosystem types (SETs) , of the IUCN typology in Japan, directly under EFGs, by using the Japanese vegetation maps provided by the Ministry of Environment. First, we systematically identified potential parent EFGs for each Japanese vegetation categories, then conducted repeated iterative expert reviews until consensus was reached. Finally, we incorporated the land-use classification developed by the National Institute for Environmental Studies. The resulting correspondence tables and high-resolution spatial dataset include 133 SETs, belonging to 28 EFGs, 14 Biomes , and 7 Realms , focusing on terrestrial and related ecosystems. Within these Realms , the Intensive land-use Biome had the largest surface area, followed by Temperate-boreal forests and woodlands. Compared to the global maps, we identified seven new EFGs in Japan and extended the northern geographical range of some subtropical EFGs. SETs along climatic and anthropogenic gradients were challenging to align with existing EFGs, as were SETs related to characteristic vegetation communities in Japan and Asia, such as bamboo forests. The SETs created in this study enhance national assessments by providing spatially explicit information on ecosystem distribution and land-use, therefore can form an integral part of regional and global biodiversity monitoring. Keywords Land-use map, SETs, Spatial data, Terrestrial ecosystems, Vegetation classification Introduction The loss of biodiversity is a major global concern; to halt the decline of species and their natural habitats, it is necessary to track the status of ecosystems from local to global scales (Nicholson et al. 2021). However, global studies are hampered by differences in ecosystem classifications at regional and national levels, which make comparative and global analysis difficult. Recently, the International Union for Conservation of Nature (IUCN) developed a global ecosystem typology (hereafter referred to as IUCN typology) based on the functional characteristics of ecosystems (Keith et al. 2020) and published indicative global maps showing the spatial distribution of broad ecosystem groups (Keith et al. 2023). This newly developed typology was built on the foundations of the Red List of Ecosystems (Keith et al. 2013; IUCN-CEM 2022) and aims to manage reporting on conservation targets in a form that enables global comparisons. In fact, the Kunming–Montreal Global Biodiversity Framework (KM-GBF) recommends using the IUCN typology when evaluating several indicators within its global biodiversity goals and targets (e.g., A.2 “Extent of natural ecosystems”; UNSD 2025), recognizing that the IUCN typology provides a globally consistent foundation for classifying national-level ecosystems. In addition, because the IUCN typology represents fundamental information on ecosystem characteristics, it contributes to the development of national-scale Essential Biodiversity Variables (EBVs), which are used for monitoring biodiversity change and provide a framework for standardized and integrated data aligned with national and global conservation targets (Takeuchi et al. 2025). The IUCN typology organizes ecosystem types into a hierarchical structure with three upper levels: Level 1 – Realms , Level 2 – Biomes , and Level 3 – Ecosystem Functional groups (EFGs). The units within these levels are differentiated by ecosystem organization, ecological drivers, and ecosystem properties, respectively. Additionally, there are three lower levels that can be adapted by individual countries or regional users. Of these, Level 4 and 5 are both organized under Level 3 independently of each other, with Level 6 connected to Level 5 providing further subdivisions. Level 5 and Level 6 are classified based on their biotic compositions, environment, and functional processes at increasingly finer scales, while Level 4 – Regional subgroups represent distinct compositional variants of EFGs identified by proxy from suitable ecoregionalisations. The two lowest levels are intended to be defined from the bottom up based on local knowledge: Level 6 – Subglobal ecosystem types (SETs) represents national classifications (which may comprise multiple ‘sublevels’ within each unit), and Level 5 – Global ecosystem types represents regional classification which should be designated by consensus among multiple countries in a region (Keith et al. 2022). A global dataset compiled by Keith et al. (2023) indicates the distribution range of major and minor occurrences for each EFGs, while a web application (IUCN 2026) enables user-generated summaries of these occurrences of each EFG by country. However, the spatial resolution of these indicative maps varies between 10 minutes to 1 degree, marking several EFGs as not present in Japan, when they occur on a smaller spatial scale. In addition, due to the global focus of the study, it only provides the distribution range of major and minor occurrences instead of the accurate location of the EFGs. The limited spatial resolution, together with overlapping distributions of several EFGs, make the data unsuitable for detailed spatial analysis. In recent years, the demand for spatially accurate depictions of the IUCN typology has been increasing, particularly due to the indicators of the KM-GBF. Several countries started to explore the applicability of the IUCN typology, for example Korea have developed EFG maps of the country based on national databases and remote sensing (Lee et al. 2025), while Italy also created a crosswalk between the IUCN typology and its latest national classification (Capotorti et al. 2023). However, many countries are still limited to Level 3, which is sufficient for global reporting, but constrains detailed assessments needed to support national policy implementation and on-ground ecosystem management. In Japan, the Ministry of Environment (MOE) carries out regular vegetation surveys as part of the National Basic Survey on Natural Environment program and from the results publishes vegetation maps covering the entire country. These vegetation maps provide detailed insights into various vegetation types and the main drivers affecting them, particularly concerning human interventions. The categories are grounded in phytosociology and follow a four-level hierarchical structure where the highest level, Vegetation zones , indicates the potential range of vegetation types in relation to climate zones. The lower categories differentiate between natural and substitutional vegetation types based on the degree of human interventions and disturbances. However, this classification is not yet cross-referenced to the IUCN typology at Level 3 or to other classification schemes, which obstruct effective comparisons at both regional and global levels. To address this gap and facilitate global studies, this study aimed to develop Level 6 classification of the IUCN typology in Japan, directly under Level 3 (EFGs). Given its detailed hierarchical structure, the Japanese vegetation categories are quite sufficient for creating a crosswalk to Level 3 of the IUCN typology and even to define the more specific Level 6, therefore, we established a cross-referencing framework linking the IUCN typology with the existing national-level vegetation categories. First, we systematically identified potential parent EFGs for the Japanese vegetation categories, and second, conducted iterative expert reviews of these EFGs until consensus was reached. Then, we developed new units at Level 6, together with two-way correspondence tables and a high-resolution spatial dataset. We used Level 6 as it is the recommended level for incorporating national classifications (IUCN 2025); other countries engaged in developing a crosswalk between their national classification system and the IUCN typology also identified Level 5 and Level 6 as the most appropriate for integration (Toor et al. 2022; Sprague and Wiser 2024). Additionally, we linked the dataset to the latest version of the land-use classification system developed by the National Institute for Environmental Studies (Ogawa et al. 2020), which characterizes the degree of human impacts for different vegetation types, one of the most important drivers of vegetation changes and status of biodiversity. Since the MOE vegetation maps comprise information about terrestrial and some additional wetland ecosystem types, this study focuses on these ecosystems. Development of maps for aquatic freshwaters, marine, and subterranean ecosystems will require alternative sources of data. Methods Japanese vegetation maps and resources When developing the SETs of the IUCN typology for Japan, we referred to the Japanese vegetation classification categories used in the 1:25000 scale national vegetation maps developed by the Biodiversity Center of Japan, MOE, which has an official resolution of approximately 50 m × 50 m, but can identify smaller features due to satellite imagery integration (up to 7 m). These vegetation maps were created based on the 6 th and 7 th vegetation surveys, covering the periods between 1999–2004 and 2005–2024, respectively, and are freely available online in 10 km × 10 km tiles format (http://gis.biodic.go.jp/webgis/sc-025.html?kind=vg67, accessed on October 3, 2024). The map’s legend is based on species composition data and arranged according to a phytosociological classification system, with a four-tier hierarchical structure: Vegetation zone , Large , Middle , and Small categories. (Figure 1a). The highest level of the Japanese vegetation classification, Vegetation zone s, also known as ’class regions’, are defined by the dominant natural vegetation (e.g., the Camellia japonica class region). They indicate climatic patterns and differentiate between natural and substitutional vegetation types based on the degrees of human intervention, which is a unique feature of this classification. The Large category is based on the formation, structure and life-forms of vegetation (physiognomy), rather than on species composition. Next, the Middle category corresponds to alliances or community groups classified by dominant species. Finally, the Small category reflects phytosociological associations, which are defined by particular species compositions with “character species” and named according to the international nomenclature code (Theurillat et al. 2021). When there is insufficient evidence to identify the particular association, “community” equivalent to associations can also be used as Small category. Each level is coded by numbers; Large categories have unique names and codes, but Middle and Small categories’ names and codes can overlap. The codes range from ‘00’, indicating undefined Middle or Small categories, to ‘99’, indicating areas not yet surveyed. The two-digit codes of the Large , Middle , and Small categories form the final Identification code, a six digits number which uniquely identifies the vegetation category (names and codes among the categories can overlap, but the Identification code remains unique). Unidentified or yet to be surveyed areas are assigned a final Identification code of 9999. There were 958 different Identification codes in the final data prepared here not including the code 9999. A Japanese explanation of the system can be found at: http://gis.biodic.go.jp/webgis/sc-015.html, with descriptions of the different categories at http://gis.biodic.go.jp/webgis/sc-016.html. The land-use classification categories were prepared by Ogawa et al. (2020) and matched to each unique Identification code. We used the upper two levels of their classification, which largely correspond to land cover and degree of naturalness (Supporting Table S1). Identification codes which were not present in the MOE vegetation maps (categories without spatial representation) or the land-use classification table were not used in this study. IUCN global ecosystem typology and resources We used the ecosystem descriptions and explanations of the ‘IUCN Global Ecosystem Typology 2.1’ (Keith et al. 2022; https://global-ecosystems.org/). The IUCN typology only specifies and describes units in its top three levels ( Realms , Biome , EFGs), leaving the three lower levels ( Regional subgroups, Global ecosystem types , SETs) to be specified by individual countries or regions (Figure 1b). Our aim was to develop a correspondence table that links the Japanese vegetation classification categories to the IUCN typology, by cross-referencing Level 3 – EFGs, to newly defined Level 6 – SETs units. We targeted EFGs, the lowest defined level at the current IUCN typology, as their alignment with the Japanese vegetation classification categories automatically included the integration of higher IUCN typology levels. However, recognizing that EFGs may not adequately describe unique Japanese vegetation types, we also created Level 6 units, SETs, condensing information from the more detailed Japanese vegetation categories. While the Large and Middle categories in the Japanese vegetation classification roughly correspond to EFGs and SETs, these Japanese categories are highly interwoven and cannot be directly translated into the IUCN typology. The Japanese classification has a much finer resolution, so its hierarchical units needed to be combined in order to translate them into the IUCN typology. We left Level 4 – Regional subgroups and Level 5 – Global ecosystem types undefined. Level 4 is distinguished by ecoregions, and is not directly connected to the lower levels, thus cannot be directly linked to national classifications. Level 5, on the other hand, employs a bottom-up approach to integrate multiple national SETs on a regional scale. Therefore, it requires the synthesis of national-level SETs across several countries regionally; such integration has not yet been conducted in East Asia. Consequently, in this study, national SETs are directly linked to the EFGs. Establishing the correspondence table To assign the Japanese vegetation categories into their corresponding EFGs in the IUCN typology and to develop the SETs, we first established a framework (Figure 1c). Within this framework, we considered all existing EFGs in the IUCN typology, not only those currently shown as occurring in Japan on global-scale indicative maps by Keith et al (2023). We focused on the Large and Middle categories of the Japanese classification, as the Large categories provided sufficient information for assigning initial EFGs, and the combination of Large and Middle categories provided adequate details for corrections and defining SETs. Notably, some narrowly defined Middle categories, characterized by single dominant species; were considered too detailed for describing SETs, thus were not used. This treatment yielded similar results to the examples of Chile and Myanmar provided by Keith et al. (2022), where species-level information was not available for some of the units. Our framework consisted of the following five steps (Figure 1c): 1, The primary interpreter systematically compared the ecosystem characteristics and visual examples between the Large categories of the Japanese vegetation classification and EFGs in the IUCN typology, then identified the EFG which could serve as a parent EFG to each Large category. 2, Next, the interpreter examined the Middle categories in each Large category, to determine whether they further clarified the relationships based on Large categories without including species-level information. Middle categories that were named after dominant species were excluded in this step, because these categories represent particularly fine and detailed subdivisions of the classification. Their exclusion made it possible to focus on a manageable number of categories (117 in contrast to 411) in a concise manner. 3 , The Middle categories selected in this way and the Large categories from the previous step were treated as candidate SET units under their respective EFGs. 4 , This initial, systematic correspondence table prepared by the primary interpreter was distributed to the experts (co-authors), who, based on the available resources and in-depth knowledge of plant communities, submitted their modifications independently of each other. As in Step 3 (not shown in Figure 1c), the experts could recommend a different parent EFG for SET units based on Middle categories than the one they inherited from their Large category (e.g., Middle categories 01 and 02 from the Large category 09 received various EFG suggestions). 5 , The primary interpreter summarized the comments, prepared the updated correspondence table, and repeated step 4-5 until consensus was reached among all the experts. The SET names were translated with some modifications from the Japanese Large and Middle categories, and then climatically referenced using the Vegetation zone levels. The coding order of the SETs followed the coding order of the Japanese classification system (from 0101 – Large code 01, Middle code 01 – to 9951). An example for the classification outcome can be seen for Vegetation zone 3 (Figure 3). As the framework was based on the Large and Middle categories, all the Small categories were automatically assigned to the same SET and to the same upper levels of IUCN typology (EFGs, Biomes , and Realms ) as their corresponding Middle or Large category. After the final correspondence table was established, we used the Japanese Identification codes to append the land-use categories (Ogawa et al. 2020) to the dataset. Final dataset for IUCN global ecosystem typology in Japan To analyse the spatial distribution of IUCN typology in Japan and provide the corresponding data product, spatial data was processed using ArcGIS Pro 3.1 (Esri 2023) and data analysis was conducted using R (R Core Team 2023) and related packages (Wickham et al. 2019; Pedersen 2020; Wilke and Wiernik 2022; Sjoberg 2023). The national vegetation maps are provided for each prefecture based on the second order mesh grid system of Japan (Yaguchi 1990; Akasaka et al. 2014). The data was prepared in six steps; 1, all tiles were merged by prefecture; 2, coordinate system was defined as JGD 2000 if it was missing; 3, spatial inconsistencies were corrected by the ‘Repair geometry function’; 4, the polygons were dissolved based on the Identification codes and codes of the Large , and Middle categories together with their names; 5, naming and coding errors were corrected (Supporting Table S2) and polygons were dissolved based on the Identification codes to be later joined with the correspondence table; 6, after joining, the spatial SET map of individual prefectures were visually checked and inconsistencies corrected (Supporting Table S2). For area-based calculations, we used UTM Zone 54N (WGS84) projection. Consequently, the final dataset includes all terrestrial ecosystems and vegetation, covering the full extent of Japan, based on the spatial and temporal coverage of the 6 th and 7 th national vegetation surveys (bounding coordinates: SW [24° 0’N, 122°52’E], NE [45° 36’N, 145°53’E], time period: 2006 – 2024, coordinate system: JGD 2000). Results Refinement of the correspondence table through the expert review cycle A comparison between the first and final correspondence table showed that the majority of EFGs systematically identified were unchanged through the review process, except for six discarded and seven added EFGs, which were related to transitional and the subterranean Realms (Supporting Figure S1a). There were several instances where experts recommended multiple EFGs as a parent EFG for the same Japanese category (Supporting Figure S1b), because some Japanese categories had characteristics from more than one EFG. For example, there were debates between T1.1 and T1.3 for areas distributed in the Ogasawara and Okinawa islands, between TF categories such as TF1.4 and TF1.7 Japan-wide, or between MFT1.2 and MT2.1, at the border of intertidal and supratidal zones. The expert review cycle increased the total number of SETs, from 115 to 133 not including open water and areas not yet surveyed. The increase was due to the extraction of more Middle categories from their respective Large categories (Supporting Figure S1b). In some cases, all Middle categories became separate SET units (see Figure 1c), while in other cases, when the parent EFG of the Large category was originally different from the subsequent parent EFG recommended for its Middle categories, the parent EFG of the Large category was adapted to that of the Middle categories, resulting in the Middle categories re-immersed into the SET of the Large category (e.g., Large category 39 or 47). In cases where two or more Middle categories in a given Large category formed a distinct group from the other Middle categories, they could be also merged into a single SET (e.g., Middle categories 08 and 09 in Large category 39). The history of changes and suggestions is summarized in Supporting Table S3 (changes of the SET names are not shown). Overview of the IUCN typology established in Japan – EFGs and SETs We established 133 SETs, belonging to 28 different EFGs, 14 Biomes and 7 Realms (three core and four transitional, Table 1). According to the indicative global maps (Keith et al. 2023), 46 EFGs were identified in Japan belonging to 19 Biomes , three core Realms and six transitional Realms . Compared to them, we found seven new EFGs (T1.3, T6.1, T6.2, TF1.6, TF1.7, MT2.2, and M1.1), most with relatively restricted distributions in Japan. On the other hand, 25 EFGs from the global analysis did not appear in our data as they were related to subterranean or water features that were largely beyond the scope of our terrestrial vegetation-focused classification and base maps (Supporting Table S4), although uncharacterized water surfaces were placed in the temporary Realm F/M – Open water (Freshwater or Marine). The Biomes with the largest surface area were T7 (Intensive land-use) and T2 (Temperate-boreal forests and woodlands) with 46.5 % and 40.7 % cover over all Realms (F/M excluded), respectively (Figure 2a). The spatial distribution of Terrestrial Biomes followed a distinct North-South gradient for the T1 and T6 Biomes , which specify tropical and alpine regions, respectively (Figure 2b). Northern prefectures of Japan had larger area belonging to Biome T6, while the southern prefectures had significant portions of T1, pushing the geographical range of this EFG further north than previously recognised in the global indicative maps (Keith et al. 2023). All prefectures had high cover of temperate-boreal forests (T2) and intensive land-use (T7) Biomes . The number of SETs was highest in the MT2.1 EFG (Coastal shrublands and grasslands) with 16 units, followed by T6.4 (Temperate alpine grasslands and shrublands) EFG with 15 units (Supporting Figure S1a). The largest surface area among SETs within the Terrestrial Realm belonged to T7.3.1 (Evergreen coniferous plantations) and T2.2.6 (Cool-temperate deciduous broad-leaved secondary forest) which covered 25.9 % and 15.4 %, respectively (Figure 3). The lowest surface area belonged to T7.5.1 (2.12 km 2 ) and to T6.4.10 (2.65 km 2 ), this latter belonging to one of the newly identified EFGs for Japan. The newly identified EFGs for Japan had small area, collectively accounting for less than 1 % of land surface identified by the base maps (excluding F/M but including other Realms ): MT2.2 (22.8 ha), M1.1 (47.6 ha), T6.1 (255 ha), T6.2 (314 ha), T1.3 (974 ha), while TF1.6 and TF1.7 covered 5039 ha (0.01 %) and 104,751 ha (0.28%), respectively. However, since our data did not fully cover marine, marine-terrestrial and terrestrial-freshwater ecosystems, these values are more indicative of areas closely connected to terrestrial ecosystems rather than the true areas of marine and freshwater ecosystems. The spatial data published alongside this study is available at [placeholder for final location] and covers entire Japan divided into prefectures. The complete version of the attribute table of the spatial data (Supporting Table S5) includes the unique Identification code of the Japanese vegetation maps, to facilitate comparisons or updates. The dataset enables visualisation and analysis at four hierarchical classification levels in the IUCN typology the Realms , Biomes , EFGs, and SETs, illustrated in Figure 4 (a) – (d) respectively. At Level 6, the map demonstrates the distribution of various SETs, focusing on the southern part of Tsukuba city (Ibaraki). From among the water-related SET units, tall fens, rice paddies and abandoned rice paddies are shown in blue shades, surrounded by other types of cultivated land, plantations, and urban areas in shades of purple (codes starting with T7). Urban parks and other green areas are depicted in shades of green (codes starting with T2). We also provided a full classification table (Supporting information Table S6) which includes all relevant Japanese vegetation categories and the IUCN typology, preserving Japanese names and codes for the Vegetation zone , Large and Middle categories to aid comparison with the original categories. For the same reason, we also provided the Japanese names of the land-use categories developed by NIES (Supporting information Table S1). Discussion Effectiveness of the framework for establishing the IUCN global ecosystem typology from the Japanese vegetation categories The framework developed here for integrating the Japanese vegetation classification and maps into the IUCN typology assigned the vegetation categories to EFGs effectively and established new units at the SET level. The engagement of multiple experts who worked independently to interpret classification units and the iterative cycle of review aligns with recently published IUCN cross-referencing standards (IUCN 2025) and produced a rigorous national ecosystem inventory integrated with the IUCN typology. As the initial classification was refined, the delineation and assignment of SETs improved. The review cycle also identified those categories which were more difficult to assign to the IUCN typology, and highlighted the EFGs, whose descriptions or names may require clarification to accommodate the variation in ecosystems represented in Japan. The iterative expert review cycle allowed us to explore formerly unacknowledged EFGs in Japan (e.g., T1.3) and to establish their relationships to SETs in the correspondence table. The Japanese vegetation maps on which our study was based, were the product of combined field and remote-sensing observations and provided reliable data at 50 m resolution, enabling some features to be mapped in even higher detail (up to 7 m resolution). A further advantage of the MOE’s vegetation map was that its categories are based on species composition, making it possible to estimate habitat conditions and determine SETs properly by flora-based vegetation types. This could have been impossible by landscape-based or dominant species-based maps and contributes to the originality of our study. These advantages made it possible to account for ecosystems with small area patches and match them with the most appropriate EFGs. In comparison, a recent study in South Korea used national maps and satellite imagery to identify EFGs appearing in the country via random forest modeling and developed a high-resolution (30 m), national-scale ecosystem typology (Lee et al. 2025). While their study subdivided T2.2 to three categories based on forest composition (broadleaved, deciduous, mixed), it did not establish more detailed SET units. Their example shows the potential of using remote sensing to produce up-to-date typology maps, but also acknowledged that the resolution of freely available, national-scale satellite images might be insufficient to accurately map occurrences of ecosystems with small areas. Due to limited data availability, they also focused on a pre-agreed set of EFGs, whereas the actual number of EFGs occurring in the study area might be higher. An other study in Italy (Capotorti et al. 2023) also found that small-scale ecosystems representing unique EFGs are harder to identify due to being below their minimum mapping area requirement (25 ha). The IUCN global ecosystem typology in Japan The detailed classification and dataset of terrestrial Japanese ecosystem types presented here, demonstrate a significant advance in the development of the lower hierarchical levels of the IUCN typology envisioned by Keith et al. (2022). By progressing beyond indicative maps developed for visualizing global distributions of EFGs (Level 3), the Level 6 classification and dataset for Japan offer uniformly high spatial resolution and precise spatial boundaries required to support ecosystem management decisions at the national scale. The robust cross-referencing of Level 6 SETs to EFGs, enables them to be placed in a regional and global context, while also enabling generalisations about their responses to environmental change and management action (Keith et al. 2022). Overall, Japan was characterized by a wide range of Biomes from T1 to T6, due to its distinct north–south gradient, similarly to Chile (Keith et al. 2022), although neither countries possess all terrestrial Biomes due to geographical differences. According to our results, T7.3 (Plantations) and T2.2 (Deciduous temperate forests) were the most dominant terrestrial EFGs in Japan, followed by T2.4 (Warm temperate laurophyll forests), whereas the global analysis by Keith et al. (2023) indicated that T2.4 had the second largest major occurrence area after T7.3 in Japan with T2.2 only coming fifth place, preceded by other intensive land use Biomes (T7.2 and T7.4). Apart from the fact that the global maps only report probability of occurrence, this discrepancy is likely due to different interpretations of plantations, resulting in large areas of plantations (T7.3) classified as native forest in warm-temperate regions (specifically as T2.4) but not in cold-temperate regions. At the SET level, T7.3.1 (Evergreen coniferous plantations) and T2.2.7 (Cool-temperate deciduous broad-leaved secondary forest) were the most widespread, providing more detailed information on ecosystem types and land use than the EFG level. We also found a large number and wide variety of SETs, particularly within MT2.1 (Coastal shrublands and grasslands) and T6.4 (Temperate alpine grasslands and shrublands), which indicates that these EFGs hold substantial ecological and biogeographical diversity. This may be because these EFGs are usually established in geographically complex and highly heterogeneous landscapes in Japan. In comparison to the global dataset which identified 46 EFGs from all Realms in Japan, we identified 28 EFGs. This discrepancy was due to the Freshwater, Marine, and other transitional or non-terrestrial Realms being largely absent from the vegetation mapping data in Japan, which included detailed data only for terrestrial ecosystems. Therefore, these missing EFGs do not indicate absence of these ecosystem units but simply reflect that they were outside the scope of our dataset and are potentially represented in Japan based on their indicative global distribution maps (Keith et al. 2023). When focusing on Terrestrial and Terrestrial-transitional Realms , all EFGs in the global study were also present in our data, except for the EFGs MT1.1, MT1.2, and MFT1.1, which all belonged to transitional Realms . We identified seven EFGs which were not represented in the current global indicative distribution maps (Keith et al. 2023). These included geographically restricted EFGs from the Terrestrial (T1.3, T6.1, T6.2), Terrestrial-Freshwater (TF1.6, TF1.7), Marine-Terrestrial (MT2.2) and Marine (M1.1) Realms . These new EFGs could be reliably identified as new to Japan due to the high resolution of the Japanese vegetation map and iterative expert review process. This study identified occurrences of T1.3 (Tropical/Subtropical montane rainforests) and T1.1 (Tropical/Subtropical lowland rainforests) further north than previously documented in the indicative global distribution maps (Keith et al. 2023). This could be a significant discovery as it establishes more accurate baseline distribution of these EFGs to assess possible changes in the future due to climate change. While the SET units within EFG T1.3, Cloud and scrub forests with Melicope and Machilus spp. together with their related liana communities in Ogasawara, had small area overall, the expert review identified further potential categories with cloud forest characteristics in the Okinawa island chain, pending further analysis. EFG T1.1 is characterized with higher biodiversity, multilayered forest, and buttress roots, which are present especially in the Nansei islands (Ryukyu) area of Japan, but also found here more northward, in the Kyushu and Shikoku region. This EFG likely exists in a more degraded form at these locations, or as an intermediate state between T1.1 and T2.4 (Warm temperate laurophyll forest) EFGs, an interpretation supported by multiple rounds of experts’ discussions. Challenges During the establishment of the IUCN typology for Japan, we identified several vegetation types that are unique to Japan and are not fully represented in the current descriptions of EFGs. This posed some challenges in finding the most suitable EFG for the SETs of these vegetation types. One example includes bamboo and dwarf bamboo communities. Some bamboo species are native to Japan, while one of the common species, Phyllostachys edulis , was introduced from China during the Edo period (in 1726 or 1736; Kitamura and Murata 1979). At the time of its introduction, this species was extensively planted, as were native bamboo species, thus these plantations rapidly expanded. Reflecting this history, several bamboo communities were categorized by the Japanese vegetation classification as cultivated bamboo forests or plantations and were therefore assigned to EFG T7.3. However, in recent decades, reduced management and spontaneous spread of the bamboo blurred their status as plantations. Because the native and introduced species frequently co-occur in forests and spread through vegetative reproduction, it was difficult to clearly distinguish whether these communities should be classified as bamboo forests, degraded forms of native ecosystems, or as bamboo plantations. Consequently, in addition to T7.3, those bamboo communities which reached a high level of naturalness were assigned to EFGs T6.4 and MT2.1, reflecting their origins and habitat characteristics. Another group of these communities which faced challenges consisted of substitutional vegetation types in Japan, which are widespread all over the country and represent communities formed via natural succession after human disturbances. Despite their anthropogenic transformation in the past, these communities retain relatively higher levels of naturalness, thus did not clearly align with any existing EFGs in the IUCN typology. We addressed these challenges by paying particular attention to the environmental constraints and descriptions when matching these Japanese vegetation categories to EFGs. We also encountered difficulties in matching transitional vegetation types with EFGs, and in some cases, it took multiple review cycles for the experts to reach a consensus interpretation. This is an inherent problem associated with a model that categorizes continuous variation in nature into discrete units. While very useful for communication, management and policy applications, it creates inevitable uncertainties for ecosystems whose properties fall within the boundary zones between two or more categories (Keith et al. 2022). In this study, examples include climatic transitions between natural ecosystems like T1.1 and T2.4, and also anthropogenic transitions along the naturalness gradient between degraded natural ecosystems and intensive land use Biomes (e.g., T6.4 and T7.5). Furthermore, when matching EFGs from Terrestrial transitional Biomes , it also required several expert review cycles to reach consensus, for example, deciding between TF1.4 and TF1.7 or between MFT1.2 and MT2.1. These problems could be addressed with more detailed definitions and examples when describing elements of the IUCN typology, therefore we recommend further clarifications and guidelines on how to differentiate these cases. As more countries in East Asia adapt their national classification and characteristic ecosystems to the IUCN typology, these needs will become clearer prompting further development of the IUCN typology and adoption of new approaches to dealing with inevitable uncertainties. Although extensive modifications are not expected, the IUCN typology is not static; currently there are five EFGs which are proposed to change in the near future (https://red-list-ecosystem.github.io/GET-data-hub/), generally making the typology units more inclusive. Since this study was based on the MOE vegetation map and its categories, it focused exclusively on terrestrial ecosystems, so several of the Freshwater and Marine core and transitional Biomes which are present in Japan are not included in the dataset published here. Also, those terrestrial categories which were missing from the MOE map (mostly belonging to the Middle and Small categories), are missing here as well. A second constraint is that our methodology used only the Large and Middle categories to keep the SET units succinct, thus the detailed information on species composition provided by the Small category was beyond the focus of this study. We recommend future users of the dataset to use the SET assigned to the level above when working with Japanese categories not covered here, or to appoint further subunits in the given SET. Although the IUCN typology ends at Level 6, the use of more detailed national subcategories is accepted. These finer categories could form the foundation of further subunits within the SETs developed in this study and, if sufficiently demonstrated, could change current SETs and EFG pairing in future versions. Conclusion The correspondence table and spatial dataset from the study provides an up-to-date, high-resolution crosswalk between the IUCN typology and the Japanese vegetation classification, containing both the original Japanese categories and their English equivalents. This framework resulted in a two-way gateway for local and global studies. On the one hand, by including the Identification codes of Japanese vegetation categories and the land-use classification categories of Japan, users of the dataset can review the categories based on their specific purposes and adapt it to their needs if required. The codes also ensure interoperability with other MOE vegetation map-derived studies, such as those focusing on forest ecosystems (Noriyuki et al. 2021), enabling alignment with more detailed classification in the IUCN typology framework. On the other hand, by including English translations and nomenclature, the dataset also contributes to the development and implementation of EBVs at the national scale, particularly those related to Ecosystem distribution, and to the calculation of KM-GBF indicators (Takeuchi et al. 2025). Furthermore, these characteristics enhance the future applicability of the dataset to emerging policy- and finance-oriented frameworks. For example, within the State of Nature metrics developed by the Nature Positive Initiative (https://www.naturepositive.org/metrics/), data on ecosystem extent are fundamental for identifying key ecosystems and intensive land-use biomes. This ecosystem typology presented here can directly contribute to the calculation of these metrics by providing consistent and spatially explicit information on ecosystem distribution. The spatially explicit and global standardized ecosystem typology further facilitates, not only for national scale, but regional and global biodiversity observation for biodiversity conservation. Data accessibility Data published alongside this study is available temporarily for review at https://nies.box.com/s/jlzxmve64c6n2px7hn7xo34omb18kbvo under the CC BY 4.0 license. Acknowledgements This study was supported by the Climate Change Adaptation Research Program of NIES. We also extend our gratitude to Hibiki Noda, Petteri Vihervaara, Kristin Böttcher, and Jamie M. Kass, as the idea of this study was initially conceived through discussions with them on how to adapt Essential Biodiversity Variables across multiple countries. We thank the anonymous reviewers whose suggestions greatly improved the manuscript, and Jose Ferrer Paris for their valuable comments. Funding information Climate Change Adaptation Research Program, National Institute for Environmental Studies, Japan Conflict of interests The authors declare no conflicts of interest. References https://doi.org/10.5281/zenodo.10081251 Akasaka M, Takenaka A, Ishihama F, et al (2014) Development of a National Land-Use/Cover Dataset to Estimate Biodiversity and Ecosystem Services. In: Nakano S, Yahara T, Nakashizuka T (eds) Integrative Observations and Assessments. Springer Japan, Tokyo, pp 209–229Capotorti G, Del Vico,Eva, Copiz,Riccardo, et al (2023) Ecosystems of Italy. Updated mapping and typology for the implementation of national and international biodiversity-related policies. 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T1.1 Tropical-subtropical lowland rainforests Yes T1.1.1 Subtropical evergreen broad-leaved forest T1.1.2 Subtropical palm communities with Livistona spp. T1.1.3 Subtropical evergreen broad-leaved forest on limestone T1.1.4 Subtropical evergreen coniferous forest T1.1.5 Subtropical deciduous broad-leaved forest T1.1.6 Subtropical evergreen broad-leaved secondary forest T1.1.7 Subtropical deciduous broad-leaved secondary forest T1.1.8 Subtropical evergreen coniferous secondary forest T1.1.9 Subtropical woody fern community T1.3 Tropical-subtropical montane rainforests New T1.3.1 Cloud and scrub forests with Melicope and Machilus spp. in Ogasawara T1.3.2 Cloud and scrub forests with liana community of Freycinetia spp. in Ogasawara T2.1 Boreal and temperate high montane forests and woodlands Yes T2.1.1 Subalpine coniferous forest in Hokkaido T2.1.2 Subalpine coniferous forest T2.1.3 Subalpine broad-leaved forest T2.1.4 Subalpine secondary forest T2.1.5 Cool-temperate coniferous forest T2.1.6 Cool-temperate coniferous forest on rocky sites T2.1.7 Cool-temperate evergreen coniferous secondary forest T2.2 Deciduous temperate forests Yes T2.2.1 Cool-temperate deciduous broad-leaved forest on Japan Sea side T2.2.2 Cool-temperate coniferous and broad-leaved mixed forest T2.2.3 Cool-temperate deciduous broad-leaved forest on Pacific Ocean side T2.2.4 Riverbank forest T2.2.5 Cool-temperate windswept shrubland on rocky sites T2.2.6 Cool-temperate deciduous broad-leaved secondary forest T2.2.7 Cool-temperate deciduous broad-leaved secondary shrubland T2.4 Warm temperate laurophyll forests Yes T2.4.1 Warm-temperate evergreen broad-leaved forest T2.4.2 Warm-temperate evergreen coniferous forest T2.4.3 Warm-temperate coniferous forests on rocky sites and coastal boulders T2.4.4 Warm-temperate deciduous broad-leaved forest T2.4.5 Warm-temperate evergreen broad-leaved secondary forest T2.4.6 Warm-temperate deciduous broad-leaved secondary forest T2.4.7 Warm-temperate evergreen coniferous secondary forest T2.4.8 Warm-temperate secondary shrubland T2.4.9 Warm-temperate disturbed shrubland and liana community with Pueraria spp. T2.4.10 Exotic shrubland or liana communities T2.4.11 Shrubland with Hydrangea spp. T3.4 Young rocky pavements, lava flows and screes Yes T3.4.1 Subalpine windswept shrubland on rocky sites T3.4.2 Cool-temperate natural shrubland along avalanche paths T3.4.3 Natural shrubland T3.4.4 Vegetation on rocky sites, limestones, and serpentines T3.4.5 Vegetation around wind holes T3.4.6 Vegetation on volcanic ejecta T3.4.7 Solfatara vegetation T3.4.8 Vegetation around volcanic fumaroles and sulfur vents T3.4.9 Natural barelands T6.1 Ice sheets, glaciers and perennial snowfields New T6.1.1 Perennial snow patches T6.2 Polar-alpine cliffs, screes, outcrops and lava flows New T6.2.1 Vegetation on alpine rocks and boulders T6.4 Temperate alpine grasslands and shrublands Yes T6.4.1 Alpine shrubland T6.4.2 Alpine heather and windswept grassland T6.4.3 Alpine serpentine vegetation T6.4.4 Structured soil community complex T6.4.5 Snowpatch grassland T6.4.6 Windswept tall-forb grassland T6.4.7 Subalpine dwarf bamboo communities T6.4.8 Subalpine heavily grazed grassland T6.4.9 Subalpine or cool-temperate secondary dwarf bamboo communities T6.4.10 Wet grassland with Senecio spp. T6.4.11 Cool-temperate natural grassland T6.4.12 Cool-temperate dwarf bamboo communities T6.4.13 Cool-temperate natural grassland along avalanche paths T6.4.14 Grassland with Miscanthus spp. T6.4.15 Cool-temperate secondary dwarf bamboo communities T7.1 Annual croplands Yes T7.1.1 Cultivated land T7.2 Sown livestock pastures T7.2.1 Golf courses and lawns T7.2.2 Pastures T7.3 Plantations Yes T7.3.1 Evergreen coniferous plantation T7.3.2 Deciduous coniferous plantation T7.3.3 Exotic plantations T7.3.4 Other plantations T7.3.5 Deciduous broad-leaved plantation T7.3.6 Evergreen broad-leaved plantation T7.3.7 Bamboo forests and plantations T7.3.8 Orchards T7.4 Urban and industrial ecosystems Yes T7.4.1 Urban areas T7.4.2 Parks and other urban green areas T7.4.3 Industrial areas T7.4.4 Reclaimed land T7.5 Derived semi-natural pastures and old fields Yes T7.5.1 Subalpine secondary grasslands with Calamagrostis spp. T7.5.2 Subalpine clear-cut community T7.5.3 Cool-temperate disturbed shrubland and liana community with Pueraria spp. T7.5.4 Cool-temperate secondary grassland T7.5.5 Heavy metal tolerant grassland T7.5.6 Heavily grazed grassland T7.5.7 Cool-temperate clear-cut community T7.5.8 Warm-temperate secondary grassland T7.5.9 Subtropical or warm-temperate exotic secondary grassland T7.5.10 Warm-temperate clear-cut communities T7.5.11 Plant communities after wildfires T7.5.12 Weed communities on abandoned land TF1.2 Subtropical-temperate forested wetlands Yes TF1.2.1 Cool-temperate swamp forest TF1.2.2 Cool-temperate riparian forest TF1.2.3 Warm-temperate swamp forest TF1.2.4 Warm-temperate riparian forest TF1.4 Seasonal floodplain marshes Yes TF1.4.1 Riverbed and gravel vegetation TF1.4.2 Riparian annual herbaceous vegetation TF1.6 Boreal, temperate and montane peat bogs New TF1.6.1 Sphagnum mosses with Vaccinium spp. TF1.6.2 Nutrient poor wetland communities TF1.6.3 Peat bog shrubland TF1.7 Boreal and temperate fens New TF1.7.1 Wetland, riverside, and marsh vegetation TF1.7.2 Fen with Moliniopsis spp. TF1.7.3 Tall fens with Phragmites spp. TF1.7.4 Fens with Cirsium and Isachne spp. F1.1 Permanent upland streams Yes F1.1.1 Streamside vegetation F1.1.2 Submerged Podostemaceae community F2.2 Small permanent freshwater lakes Yes F2.2.1 Pondweed communities F3.3 Rice paddies Yes F3.3.1 Rice paddies and their weed communities F3.3.2 Weed communities on abandoned rice paddies MT1.1 Rocky Shorelines Yes MT1.1.1 Vegetation on boulders MT2.1 Coastal shrublands and grasslands Yes MT2.1.1 Coastal shrubland in supralittoral zone MT2.1.2 Coastal windswept shrubland MT2.1.3 Subtropical coastal shrubland MT2.1.4 Coastal windswept shrubland in Ogasawara MT2.1.5 Subtropical shrubland on cliffs and boulders MT2.1.6 Coastal evergreen broad-leaved secondary forest MT2.1.7 Subtropical coastal secondary forest MT2.1.8 Subtropical or warm-temperate bamboo and dwarf bamboo communities MT2.1.9 Subtropical coastal secondary shrubland MT2.1.10 Heavily grazed shrubland on sand dunes MT2.1.11 Sand dunes vegetation MT2.1.12 Pristine flower meadows MT2.1.13 Exotic herbaceous communities MT2.1.14 Vegetation on coastal cliffs MT2.1.15 Coastal herbaceous communities MT2.1.16 Raised coral reef vegetation MT2.2 Large seabird and pinniped colonies New MT2.2.1 Plant communities at nesting sites of seabirds MFT1.2 Intertidal forests and shrublands Yes MFT1.2.1 Coastal shrubland in intertidal zone MFT1.2.2 Subtropical mangrove forest MFT1.2.3 Subtropical coastal shrubland with Pandanus spp. MFT1.2.4 Subtropical shrubland at the mangrove edge MFT1.3 Coastal saltmarshes and reedbeds Yes MFT1.3.1 Saltmarsh vegetation MFT1.3.2 Annual saltmarsh vegetation with Salicornia spp. FM1.3 Intermittently closed and open lakes and lagoons Yes FM1.3.1 Submerged plant communities in brackish water M1.1 Seagrass meadows New M1.1.1 Eelgrass meadow F/M0.0 Open water NA F/M0.0.0 Open water Captions Figure 1. Structure of the Japanese and IUCN classification and the workflow to combine them. (a) Hierarchical structure of the Japanese vegetation categories consisting of Vegetation zone, Large , Middle , and Small categories (Japanese names are shown in parentheses). An example is shown for Vegetation zone 3 with its Large and Middle categories. (b) Hierarchical structure of the IUCN ecosystem typology. At Level 1, four core Realms (in black letters) and six transitional Realms (in white letters) are defined. Level 2 consists of Biomes ; here two examples (T2 and T7) in Terrestrial Realm are shown as examples. Each Biome contains EFGs ( Ecosystem Functional Groups ), forming Level 3 of the typology. Under Level 3, Level 4 ( Regional subgroups ) and Level 5 ( Global ecosystem types ) are defined independently from each other. Level 6, SETs, ( Subglobal ecosystem types ) is listed under Level 5 (see text for more details). (c) Framework for defining the IUCN typology from the Japanese vegetation classification. For an explanation of the different steps, refer to section 2.3. An example is shown for Vegetation zone 3, where letters are placeholders for the final SET ID in case of identical EFGs. Figure 2. Surface area and percentage coverages of Biomes and EFGs (a) Total surface area of Biomes in Japan. The low values for water related Realms are the result of these features generally not present in the dataset and not indicative for their real area. (b) Distribution and percentage coverage of Terrestrial EFGs in the 47 prefectures of Japan, listed from north to south. Land surface of the prefectures was calculated using only Terrestrial core and transitional Realms (T, TF, MT, and MFT). Note the difference in scale on the x axis. The full names of the EFGs are provided in Table 1. Figure 3. Comparison of the surface area (in percentage) among SETs within the Terrestrial Biome . Note the difference in scale on the x axis. The full names of EFGs and SETs are provided in Table 1. Figure 4. Map of the IUCN typology in Japan. (a) Realms , (b) Biomes , (c) EFGs, and (d) SETs. Extent indicator of the next level is marked on each map. Detailed names for the IDs on (c, d) are provided in Table 1. Realms IDs: T – Terrestrial, TF – Terrestrial-Freshwater, F – Freshwater, MT – Marine-Terrestrial, MFT – Marine-Freshwater-Terrestrial, FM – Freshwater-Marine, M – Marine. The full names of Biomes are shown in Supporting Table S5. Figures Figure 1. Figure 2. Figure 3. Figure 4. Information & Authors Information Version history V1 Version 1 05 March 2026 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords 36: biodiversity 7: ecosystem ecology 8: vegetation sciences land-use map sets spatial data terrestrial ecosystem vegetation classification Authors Affiliations Lea Végh 0000-0001-7948-480X National Institute for Environmental Studies View all articles by this author Jun Nishihiro National Institute for Environmental Studies View all articles by this author Hironori Toyama J F Oberlin University View all articles by this author Fumiko Ishihama 0000-0001-8515-5914 National Institute for Environmental Studies View all articles by this author Hiroyuki Kudo National Institute for Environmental Studies View all articles by this author Yuki Tanno National Institute for Environmental Studies View all articles by this author Taku Kadoya National Institute for Environmental Studies View all articles by this author Masato Yoshikawa Tokyo University of Agriculture and Technology View all articles by this author David Keith University of New South Wales View all articles by this author Yayoi Takeuchi 0000-0002-8402-7854 [email protected] Osaka Metropolitan University View all articles by this author Metrics & Citations Metrics Article Usage 395 views 137 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Lea Végh, Jun Nishihiro, Hironori Toyama, et al. 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