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.
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.
As human populations move into cities they are increasingly isolated from the natural world, with associated negative impacts on health and well-being. However, as cities renew themselves through ...urban redevelopment and climate-adaptation, opportunities arise to improve people's access to urban green areas that can be informed by modeling the network of urban open spaces. Recent research identified the need for multi-criteria indices of access to urban green spaces. Including open spaces such as empty lots, ground- and air-spaces surrounding buildings, and spaces associated with roads and other linear features can improve planning for urban greenspaces by identifying areas of opportunity for additional greening. Further, the gradient of interconnections among open spaces can be used to prioritize urban greening locations to build green networks. We modelled all open-space connections across 605 km2 in Seoul, population 10.3 million, using Omniscape, a landscape connectivity model. We combined the resulting open-space connectivity map with distance-based indices for existing urban parks and street trees. Combining these criteria permits rank-prioritization of locations where new green spaces would most improve residents' access. We found 2910 of 3375 (86.2%) locations where urban green spaces already exist within 300 m for city residents. Of the remaining 465 locations, 276 are in areas with the lowest-open space connections. For urban street trees, 44.3% of the 2588 km of the city's major roads are already planted with street trees. Of the remainder, 210 km (8.1%) are located in the areas with the least connections to green spaces. Nine new urban parks would provide relief for the most highly-impacted areas, where the flow of open space is lowest and where no green spaces are available within 300 m. The integration of a spatial model typically used for conservation assessments with city planning provides useful additional context for building urban health.
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.
Protected areas (PAs) planning often encounters obstacles globally due to the scarcity of reliable and systematic biodiversity data covering wide areas. Understanding the interaction between climate ...and biodiversity patterns can offer a novel approach to spatial conservation prioritization, considering the impact of climate on species distributions and the global availability of climate data. Here we used climate-based planning to develop national networks of PAs by prioritizing “climate space”, which represents the multidimensional climatic conditions in a specific area. We assessed four climate-selecting strategies using Marxan to enhance average plant species richness and species composition’ s complementarity in candidate PAs: (1) random selection; (2) prioritizing rare climates; (3) prioritizing common climates; and (4) equal representation for each climate condition. We identified the spatial heterogeneity of national climate conditions in South Korea, with unique climates shaped by geographic and topographic diversity. Notably, prioritizing rare climates consistently resulted in higher average plant species richness and complementarity within candidate PAs. Rare climates exhibited high spatial similarity with high plant species richness and showed significant overlaps and strong connectivity to existing PAs. Rare climatic zones in South Korea have greater geodiversity and lower human population density, providing opportunities for distinct ecosystems and habitats for rare species. Our methodology, which can be easily replicated, offers spatial-explicit and quantitative prioritization of resource allocation in a nation or region with limited biological data.
•Climate space is used as the conservation target to design national protected areas.•Rare climates coincide with high biodiversity areas in South Korea.•Prioritizing rare climates can enhance biodiversity representation.•This method is easily replicable and complements biodiversity data gaps.
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.
This study evaluates how resilient farmers’ livelihoods are to climate change and what factors influence this resilience. To measure resilience, we constructed an indicator system based on the ...livelihood resilience analysis framework. We surveyed 42 experts and 630 farmers after a climate change disturbance in Aohan Banner, Inner Mongolia, from August to October 2021, and analyzed these data using the comprehensive index method. Meanwhile, we used a multiple linear regression model to analyze the key factors affecting farmer livelihood resilience across different livelihood types and towns. We found that farmers who primarily worked in agriculture had the highest resilience scores and that livelihood resilience differed by geographical location; specifically, livelihood resilience gradually declines from southern to northern areas and from forest and forest-grassland to grassland locations. The results also show that education level, agricultural technology training, transportation infrastructure, accessibility of information, awareness of climate change, climate change perception, change in livelihood strategies, family size, and the holding size of the arable area are positively associated with farmer livelihood resilience, while household head age is negatively associated with resilience. We therefore advise that policymakers should diversify agricultural livelihoods, afforest surrounding arable areas, improve transportation infrastructure, increase learning activities and skill training for farmers, and publicize climate change knowledge.
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 (Dmax), 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.
Increasingly available large species observation datasets provide opportunity for greater insights about landscape biodiversity and patterns of species rarity than simply applying species distribution models. We assess the species rarity classification and spatial results of integrating Rabinowitz (1981) species rarity classes with 2,215 plant species from a national‐scale survey.
Bio-control strategies and the application of eco-friendly nanoparticles to enhance drought tolerance in plants have attained great interest in arid and semi-arid water resource management. This ...study aims to determine the effects of Trichoderma koningiopsis and the combination of T. koningiopsis and iron oxide nanoparticles (FeO-NPs) on the biochemical, physiological, and anatomical responses of Arabidopsis thaliana under drought stress. Compared with the untreated control, T. koningiopsis and its co-inoculation with FeO-NPs promoted fresh biomass and root length. Moreover, exposure to both T. koningiopsis and FeO-NPs significantly decreased electrolytic leakage, indicating a decrease in reactive oxygen species accumulation and lipid peroxidation levels in plants. In the plants, the activity of superoxide dismutase, antioxidant enzymes, and catalase was significantly increased with T. koningiopsis and FeO-NP application. The findings show that T. koningiopsis and FeO-NPs can considerably reduce the water requirement of A. thaliana and enhance their drought tolerance ability, particularly in drought-prone areas. KCI Citation Count: 0
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.
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