This study uses a scenario-based approach to ask what are the varying impacts to forest extent and biodiversity from sixteen climate change and forest conversion scenario combinations, and what do they suggest about future forest conservation policy directions? We projected these combinations onto existing forests in South Korea and grouped them into four forest categories. We used species distribution models for 1031 climate vulnerable plant species as a biodiversity index, and found that species richness loss due to forest conversion could be reduced significantly by deploying the scenarios which preserve forest areas that are climatically suitable for these species. Climate-suitable forest areas declined sharply and moved northward as future temperatures increase, and climate-suitable areas lost the highest proportion of forest extent under the current trend of forest conversion. We suggest climate refugia, defined as existing forests with suitable future climates, be protected from land use conversion as a way to preserve forest biodiversity. These spatially explicit results can be used for developing forest conservation policies, and the methods may be applicable to other forested regions. However, planners should consider the assumptions and uncertainties of climate projections, species distribution models, and land use trends when addressing forest biodiversity conservation.

The impacts of climate change traverse administrative borders, which calls for new strategies for forest ecosystem conservation and adaptive management. Despite relatively high biodiversity, the temperate forests in East Asia have lacked a comprehensive regional evaluation of potential climate change impacts. Here, we assess the level of climate change exposure of the Temperate Broadleaf and Mixed Forests Biome of East Asia by 2070. These temperate forests occupy 18 ecoregions, five countries, and 102 provinces. We categorize climate change exposure by classifying baseline (1960–1990) climate conditions for the current geographic distribution of five temperate forest types within each ecoregion and within the biome. We then measure the level of change under four future climates: a warmer or a hotter future climate and under reduced emissions (RCP4.5) or with emissions continuing unabated (RCP8.5). By 2070, using the RCP8.5 emission scenario, 24.5–65.7% of these forests enter non-analog or the most marginal 1% of baseline climate conditions. These results reveal the need for extensive transboundary governmental coordination, including forest preservation actions among 51 of 54 provinces that will retain some forest locations in climatically stable or low-risk conditions. Furthermore, among 96 provinces with forests that will be highly exposed, 90 will require transboundary climate change adaptation strategies because these forests span their borders, including the border areas of China, the Russian Federation, and North Korea. The analytical approach of this study could serve as a template for supporting transboundary institutional coordination to address climate change.

Governance of large cities requires local planning and administration, and most cities contain nested levels of government. There are challenges for coordinating urban planning and development among these local governments, which lead to the need to assess regional or city-wide contexts that can be used by smaller administrative units. Urban metabolism treats a city as a system within which the movement of resources can be estimated. In this study, we employed an urban metabolism approach to estimate the permeability of open space within an entire megacity, Seoul, the capital of South Korea. We provide district-level relative permeability scores for the 25 district governments to use in assessments and incentivize cooperation to improve the city’s overall open space connectivity. We analyzed the relative level of open space of 69 classes using Seoul’s land use map, and used Omniscape, a modeling tool that charts the level of suitability and resistance of every grid cell to every other grid cell using a moving window. This is an omnidirectional continuous approach that does not require open space “cores” or least-cost “paths”. We modeled two scenarios, one where open water is a barrier and contributes little to open space, and the other where open water is considered an attractive element to open space. We used the modeled outputs to define five levels of permeability and then compared the relative permeability scores for the 25 districts. Five districts had over 30% of their area in the lowest level, and eight of the 10 largest impermeable areas spanned across districts under water suitable scenario. The comparable metrics permit intra-district assessments to improve open space access, but also expect creative approaches to overcome issues including limited availability for open spaces.

Core Ideas: Field crop diversity in the US peaked between 1940 and 1960. Current levels of field crop diversity are similar to what they were in 1900. Field crop diversity in the Midwest has been very low throughout the past 142 years. Describing spatiotemporal patterns of agricultural biodiversity may be an important step toward better understanding its effect on agroecosystem services. We describe species-level field crop diversity at the national and state level for the United States, using annual survey data for a 142-yr period. National-level field crop diversity was very low around 1870 and peaked around 1960, after which time it began to decline. Many states had their highest levels of diversity between 1940 and 1960, but trends varied strongly among states. In 1900, the states with highest diversity were in the Northeast, but in 2012 the highest diversity was found in California, North Dakota, and the southeastern states. Diversity in the central US Corn Belt was very low throughout the 142-yr period studied. These results show that changes in diversity do not necessarily follow a simple continuous decline when moving from “traditional” to “industrial” agriculture.

The spatial patterns of species richness can be used as indicators for conservation and restoration, but data problems, including the lack of species surveys and geographical data gaps, are obstacles to mapping species richness across large areas. Lack of species data can be overcome with remote sensing because it covers extended geographic areas and generates recurring data. We developed a Deep Learning (DL) framework using Moderate Resolution Imaging Spectroradiometer (MODIS) products and modeled potential species richness by stacking species distribution models (S-SDMs) to ask, “What are the spatial patterns of potential plant species richness across the Korean Peninsula, including inaccessible North Korea, where survey data are limited?” First, we estimated plant species richness in South Korea by combining the probability-based SDM results of 1574 species and used independent plant surveys to validate our potential species richness maps. Next, DL-based species richness models were fitted to the species richness results in South Korea, and a time-series of the normalized difference vegetation index (NDVI) and leaf area index (LAI) from MODIS. The individually developed models from South Korea were statistically tested using datasets that were not used in model training and obtained high accuracy outcomes (0.98, Pearson correlation). Finally, the proposed models were combined to estimate the richness patterns across the Korean Peninsula at a higher spatial resolution than the species survey data. From the statistical feature importance tests overall, growing season NDVI-related features were more important than LAI features for quantifying biodiversity from remote sensing time-series data.

Context: Climate change adaptive management strategies for isolated habitats such as wetlands are urgently needed. Conservation areas managed for wildlife refuges can be considered a network, permitting the tracking of current climate conditions within the network under projected future climates. Objectives: We ask how many classes of temporal climate dynamics exist within a set of 48 refuges that comprise a network of conservation areas. Methods: We identified the current-climate conditions of 48 US National Wildlife Refuges using their annual average of minimum temperature and annual precipitation. We then mapped the movement of analogous climates for each refuge from current to future-time periods under four climate projections. We identified distinct types of analog climate dynamics among the network of wildlife refuges that can inform climate-adaptive natural resource planning. Results: We identified five analogous climate categories: (1) disappearing climates; (2) single-analogous climates; (3) multiple-analogous climates; (4) enduring climates; and (5) climate hubs, with some refuges occupying up to three classes. Using four climate projections, we found 10–25 refuges are climatically disappeared; 8–16 whose climate conditions appear in only one other unit; three whose current climate appears in many other refuges; three that are climatically stable; and four that are climate hubs. Conclusions: The relative geographic isolation of refuges makes them particularly appropriate for use as nodes in a network-based climate assessment. The climate classification of the nodes can help inform selection from among multiple refuge management strategies based on their relative analogous climate dynamics. For example, new refuges could be identified to account for species inhabiting climatically disappearing refuges.

Accurate information on the distribution of existing species is crucial to assess regional biodiversity. However, data inventories are insufficient in many areas. We examine the ability of Multivariate Adaptive Regression Splines (MARS) multi-response species distribution model to overcome species' data limitations and portray plant species distribution patterns for 199 South Korean plant species. The study models species with two or more observations, examines their contribution to national patterns of species richness, provides a sensitivity analysis of different range threshold cutoff approaches for modeling species' ranges, and presents considerations for species modeling at fine spatial resolution. We ran MARS models for each species and tested four threshold methods to transform occurrence probabilities into presence or absence range maps. Modeled occurrence probabilities were extracted at each species' presence points, and the mean, median, and one standard deviation (SD) calculated to define data-driven thresholds. A maximum sum of sensitivity and specificity threshold was also calculated, and the range maps from the four cutoffs were tested using independent plant survey data. The single SD values were the best threshold tested for minimizing omission errors and limiting species ranges to areas where the associated occurrence data were correctly classed. Eight individual species range maps for rare plant species were identified that are potentially affected by resampling predictor variables to fine spatial scales. We portray spatial patterns of high species richness by assessing the combined range maps from three classes of species: all species, endangered and endemic species, and range-size rarity of all species, which could be used in conservation planning for South Korea. The MARS model is promising for addressing the common problem of few species occurrence records. However, projected species ranges are highly dependent on the threshold and scale criteria, which should be assessed on a per-project basis.

Increasingly large presence-only survey datasets are becoming available for use in conservation assessments. Potentially, these records could be used to determine spatial patterns of plant species rarity and endemism. We test the integration of a large South Korean species record database with Rabinowitz rarity classes. Rabinowitz proposed seven classes of species rarity using three variables: geographic range, habitat specificity, and local population size. We estimated the range size and local abundance of 2,215 plant species from species occurrence records and habitat specificity as the number of landcover types each species' records were found in. We classified each species into a rarity class or as common, compared species composition by class to national lists, and mapped the spatial pattern of species richness for each rarity class. Species were classed to narrow or wide geographic ranges using 315 km, the average from a range size index of all species (D _max), based on maximum distance between observations. There were four classes each within the narrow and wide range groups, sorted using cutoffs of local abundance and habitat specificity. Nationally listed endangered species only appeared in the narrow-range classes, while nationally listed endemic species appeared in almost all classes. Species richness in most rarity classes was high in northeastern South Korea especially for species with narrow ranges. Policy implications. Large presence-only surveys may be able to estimate some classes of rarity better than others, but modification to include estimates of local abundance and habitat types, could greatly increase their utility. Application of the Rabinowitz rarity framework to such surveys can extend their utility beyond species distribution models and can identify areas that need further surveys and for conservation priority. Future studies should be aware of the subjectivity of the rarity classification and that regional scale implementations of the framework may differ.

Natural resource managers need information about the risks associated with climate change to provide guidance on where to implement various management practices on natural lands. The spatial variation of projected impacts within a vegetation type can be used to target climate-adaptive management actions because different locations will be exposed to different levels of climatic stress. Vegetation refugia are areas that retain non-stressful climate conditions under future climates. Consensus vegetation refugia – areas retaining suitable climates under both wetter and drier future projections – represent only 14.6% of California's natural vegetation. One state and one federal government agency have incorporated vegetation refugia maps into conservation planning for 522 vertebrate species and for post-wildfire reforestation. Monitoring how vegetation responds to management actions at sites within vegetation refugia can improve the conservation of plants subjected to a changing climate.

Protected areas (PAs) are often considered the most important biodiversity conservation areas in national plans, but PAs often do not represent national-scale biodiversity. We evaluate the current conservation status of plant biodiversity within current existing PAs, and identify potential additional PAs for South Korea. We modeled species ranges for 2,297 plant species using Multivariate Adaptive Regression Splines and compared the level of mean range representation in South Korea's existing PAs, which comprise 5.7% of the country's mainland area, with an equal-area alternative PA strategy selected with the reserve algorithm Marxan. We also used Marxan to model two additional conservation scenarios that add lands to approach the Aichi Biodiversity Target objectives (17% of the country). Existing PAs in South Korea contain an average of 6.3% of each plant species' range, compared to 5.9% in the modeled equal-area alternative. However, existing PAs primarily represent a high percentage of the ranges for high-elevation and small range size species. The additional PAs scenario that adds lands to the existing PAs covers 14,587.55 km2, and would improve overall plant range representation to a mean of 16.8% of every species' range. The other additional PAs scenario, which selects new PAs from all lands and covers 13,197.35 km2, would improve overall plant range representation to a mean of 13.5%. Even though the additional PAs that includes existing PAs represents higher percentages of species' ranges, it is missing many biodiversity hotspots in non-mountainous areas and the additional PAs without locking in the existing PAs represent almost all species' ranges evenly, including low-elevation ones with larger ranges. Some priority conservation areas we identified are expansions of, or near, existing PAs, especially in northeastern and southern South Korea. However, lowland coastal areas and areas surrounding the capital city, Seoul, are also critical for biodiversity conservation in South Korea.