Checklist of vascular plant species in Huangshui River Basin of Qinghai Province, China.

Background: The Huangshui River Basin is one of the most important water sources in the Qinghai Province and is of great importance for ecological protection measures, agricultural irrigation and tourism. Based on previous studies and fieldwork related to plant species in China, this study presents comprehensive data on vascular plants distributed in the Huangshui River Basin of Qinghai Province.Ethical Compliance: All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.Data Access Statement: Research data supporting this publication are available from the repository at located at https://www.scidb.cn/en/anonymous/QUpuZVEz.Conflict of Interest declaration: The authors declare that they have NO affiliations with or involvement in any organisation or entity with any financial interest in the subject matter or materials discussed in this manuscript. New information: The checklist of plants includes ferns, gymnosperms and angiosperms, covering three phyla, five classes, 49 orders, 139 families, 709 genera and 2,382 species. It includes numerous Asteraceae, Gramineae, Rosaceae and Fabaceae along with statistical data on the number of species distributed in different regions. The dataset presented in this article provides important background information on vascular plants in the Huangshui River Basin and, therefore, plays a crucial role in the protection and management of plant resources in this region.

A dataset of functional traits for compound pinnate leaves of plants in the Huangshui River Valley of Qinghai Province, China.

Background: Here, we present data collected from the Qinghai-Tibet Plateau that describes the variation of leaf functional traits across 32 plant species and could be used to investigate plant community functioning and predict the impact of climate change on biogeochemical cycles. The sampling area is located in Huangshui River Valley, in the southeast of Qinghai Province, China (36° 19' to 36° 53' N, 100° 59' to 102° 48' E). The area contains an alpine meadow typical of the Qinghai-Tibet Plateau. New information: This dataset includes field survey data on the functional properties of compound leaves from herbaceous species in the Huangshui River Basin of Qinghai Province, China, at altitudes from 1800 m to 4000 m in the summer of 2021. Data were collected from 326 plots, including 646 data points of compound leaf plants, spanning 32 compound leaf plant species belonging to 14 genera and four families. The study species were chosen from 47 families, 165 genera and 336 species present in the plots and all compound leaf plants were chosen within each plot. We picked the parts containing leaves, petioles and rachis from the study plants and separated the leaves from the plants. The cut compound leaf part was a leaflet, while the petiole and rachis were linear elements. The dataset includes information about the leaflet trait variation (i.e. leaflet area, leaflet dry mass, specific leaflet area and leaflet nitrogen content per unit dry mass) and linear elements' biomass and nitrogen content per unit dry mass (i.e. both petiole and rachis) of 646 compound leaves. This dataset can be used to analyse the evolution of leaf traits and the basic functioning of ecosystems. Moreover, the dataset provides an important basis for studying the species distribution and protection of biodiversity of the Qinghai-Tibet Plateau and evaluating ecosystem services. These data also support the high-quality development of the Yellow River Basin and have empirical and practical value for alpine biodiversity protection and ecosystem management.

Complete chloroplast genome data of Ranunculus membranaceus (Ranunculaceae), an important medicinal plant species.

The perennial alpine herb Ranunculus membranaceus (Ranunculaceae) has significant medicinal value. The complete chloroplast genome of R. membranaceus was sequenced by high-throughput Illumina sequencing Platform Illumina NovaSeq 6000. The circular genome is 156,028 bp in size, including two inverted repeats (IRs) of 25,361 bp, a large single-copy (LSC) region of 85,491 bp, and a small single-copy (SSC) region of 19,815 bp. A total of 128 genes were annotated, namely 84 protein-coding genes (PCGs), 36 tRNA genes, and eight rRNA genes. Two phylogenetic trees of 18 species of the tribe Ranunculeae species were constructed with Meconopsis punicea as the outgroup based on the whole chloroplast genomes and the concatenated sequence of PCGs, respectively. Phylogeny showed that R. membranaceus was closely related to R. yunnanensis. These data enrich knowledge of Ranunculaceae genetics and will contribute to further studies of R. membranaceus in molecular breeding, genetic transformation, species identification, genetic engineering and phylogenetic research.

Comparing the Performance of CMCC-BioClimInd and WorldClim Datasets in Predicting Global Invasive Plant Distributions.

Species distribution modeling (SDM) has been widely used to predict the distribution of invasive plant species based on bioclimatic variables. However, the specific selection of these variables may affect the performance of SDM. This investigation elucidates a new bioclimate variable dataset (i.e., CMCC-BioClimInd) for its use in SDM. The predictive performance of SDM that includes WorldClim and CMCC-BioClimInd was evaluated by AUC and omission rate and the explanatory power of both datasets was assessed by the jackknife method. Furthermore, the ODMAP protocol was used to record CMCC-BioClimInd to ensure reproducibility. The results indicated that CMCC-BioClimInd effectively simulates invasive plant species' distribution. Based on the contribution rate of CMCC-BioClimInd to the distribution of invasive plant species, it was inferred that the modified and simplified continentality and Kira warmth index from CMCC-BioClimInd had a strong explanatory power. Under the 35 bioclimatic variables of CMCC-BioClimInd, alien invasive plant species are mainly distributed in equatorial, tropical, and subtropical regions. We tested a new bioclimate variable dataset to simulate the distribution of invasive plant species worldwide. This method has great potential to improve the efficiency of species distribution modeling, thereby providing a new perspective for risk assessment and management of global invasive plant species.

Complete chloroplast genome data for Mimosa diplotricha and Mimosa diplotricha var. inermis from China.

Mimosa diplotricha (Fabaceae) and Mimosa diplotricha var. inermis are invasive taxa introduced in the Chinese mainland in the 19th century. M. diplotricha has been listed in the list of highly invasive species in China, which has seriously endangered the growth and reproduction of local species. As a poisonous plant, M. diplotricha var. inermis, a variant of M. diplotricha, will also endanger the safety of animals. We report the complete chloroplast genome sequence of M. diplotricha and M. diplotricha var. inermis. The chloroplast genome of M. diplotricha is 164,450 bp long and the chloroplast genome of M. diplotricha var. inermis is 164,445 bp long. Both M. diplotricha and M. diplotricha var. inermis contain a large single-copy region (LSC) of 89,807 bp and a small single-copy (SSC) region of 18,728 bp. The overall GC content of the two species is both 37.45%. A total of 84 genes were annotated in the two species, namely 54 protein-coding genes, 29 tRNA genes, and one rRNA gene. The phylogenetic tree based on the chloroplast genome of 22 related species showed that Mimosa diplotricha var. inermis is most closely related to M. diplotricha, while the latter clade is sister to Mimosa pudica, Parkia javanica, Faidherbia albida, and Acacia puncticulata. Our data provide a theoretical basis for the molecular identification, genetic relationships, and invasion risk monitoring of M. diplotricha and M. diplotricha var. inermis.

Predicting the distribution of plant associations under climate change: A case study on Larix gmelinii in China.

Association is the basic unit of plant community classification. Exploring the distribution of plant associations can help improve our understanding of biodiversity conservation. Different associations depend on different habitats and studying the association level is important for ecological restoration, regional ecological protection, regulating the ecological balance, and maintaining biodiversity. However, previous studies have only focused on suitable distribution areas for species and not on the distribution of plant associations. Larix gmelinii is a sensitive and abundant species that occurs along the southern margin of the Eurasian boreal forests, and its distribution is closely related to permafrost. In this study, 420 original plots of L. gmelinii forests were investigated. We used a Maxent model and the ArcGIS software to project the potential geographical distribution of L. gmelinii associations in the future (by 2050 and 2070) according to the climate scenarios RCP 2.6, RCP 4.5, and RCP 8.5. We used the multi-classification logistic regression analysis method to obtain the response of the suitable area change for the L. gmelinii alliance and associations to climate change under different climate scenarios. Results revealed that temperature is the most crucial factor affecting the distribution of L. gmelinii forests and most of its associations under different climate scenarios. Suitable areas for each association type are shrinking by varying degrees, especially due to habitat loss at high altitudes in special terrains. Different L. gmelinii associations should have different management measures based on the site conditions, composition structure, growth, development, and renewal succession trends. Subsequent research should consider data on biological factors to obtain more accurate prediction results.

Development of novel polymorphic microsatellite markers for Picea brachytyla.

BACKGROUND: Picea brachytyla is a unique tree species in China. Due to being extensively exploited in the past, it is listed as Vulnerable in the IUCN Red List. It is mainly distributed across the Hengduan and Daba-Qinglin mountains and has been found in other areas including Sichuan Province and Qinghai Province, China. Microsatellites, or simple sequence repeats (SSRs), are widely used in correlational studies of genetic protection. Few markers have been developed for P. brachytyla because of the small number of trees and scholarly resources available for study. METHODS AND RESULTS: The genomic DNA of P. brachytyla was sequenced using the DNBSEQ platform, and unigenes were obtained after assembly and deredundancy. Of the 100 primer pairs screened, we isolated 10 useful microsatellite loci from P. brachytyla genes. The observed and expected heterozygosity values ranged from 0.173 (P24) to 0.788 (P79; mean 0.469) and 0.199 (P87) to 0.911 (P79; mean 0.700), respectively. Polymorphism-information content (PIC) ranged from 0.190 (P84) to 0.904 (P79; mean 0.666). Only P84 and P72 were in a Hardy-Weinberg equilibrium (P > 0.05) in the different P. brachytyla populations. All the levels of linkage disequilibrium (LD) were high for the 10 SSR loci indicating that there were no autocorrelations among the 10 SSR loci. CONCLUSIONS: The novel polymorphic microsatellite markers showed high polymorphism for P. brachytyla. These polymorphic microsatellites can provide a basis for future conservation and genetic research on this rare plant species.

Using Consensus Land Cover Data to Model Global Invasive Tree Species Distributions.

Invasive tree species threaten ecosystems, natural resources, and managed land worldwide. Land cover has been widely used as an environmental variable for predicting global invasive tree species distributions. Recent studies have shown that consensus land cover data can be an effective tool for species distribution modelling. In this paper, consensus land cover data were used as prediction variables to predict the distribution of the 11 most aggressive invasive tree species globally. We found that consensus land cover data could indeed contribute to modelling the distribution of invasive tree species. According to the contribution rate of land cover to the distribution of invasive tree species, we inferred that the cover classes of open water and evergreen broadleaf trees have strong explanatory power regarding the distribution of invasive tree species. Under consensus land cover changes, invasive tree species were mainly distributed near equatorial, tropical, and subtropical areas. In order to limit the damage caused by invasive tree species to global biodiversity, human life, safety, and the economy, strong measures must be implemented to prevent the further expansion of invasive tree species. We suggest the use of consensus land cover data to model global invasive tree species distributions, as this approach has strong potential to enhance the performance of species distribution modelling. Our study provides new insights into the risk assessment and management of invasive tree species globally.

Risk assessment of insect pest expansion in alpine ecosystems under climate change.

BACKGROUND: Growth in insect pest populations poses a significant threat to ecosystem functions and services, societal development, and food security in alpine regions under climate change. Risk assessments are important prioritization tools for pest management, which must be used to study insect pest expansion in alpine ecosystems under global warming. We used species distribution modeling to simulate the current and future distribution probabilities of 58 insect pest species in the Qinghai Province, China, based on a comprehensive field investigation. Subsequently, general linear modeling was used to explore the relationship between the distribution probability of these species and the damage caused by them. Finally, we assessed the ecological risk of insect pest expansion across different alpine ecosystems under climate change. RESULTS: Climate change could increase the distribution probabilities of insect pest species across different alpine ecosystems. However, the presence of insect pest species may not correspond to the damage occurrence in alpine ecosystems based on percent leaf loss, amount of stunting, and seedling death of their host species. Significant positive relationships between distribution probability and damage occurrence were found for several of the examined insect pest species. Insect pest expansion is likely to increase extensively in alpine ecosystems under increasing carbon dioxide (CO2 ) emission scenarios. CONCLUSION: The relationships between distribution probability and damage occurrence should be considered in species distribution modeling for risk assessment of insect pest expansion under climate change. Our study could improve the effectiveness of risk assessment of insect pest expansion under changing climate conditions. © 2021 Society of Chemical Industry.

Can polyploidy confer invasive plants with a wider climatic tolerance? A test using Solidago canadensis.

Polyploidy can cause variation in plant functional traits and thereby generate individuals that can adapt to fluctuating environments and exploit new environments. However, few empirical studies have tested for an association between ploidy level and climatic tolerance of invasive cytotypes relative to conspecific native-range cytotypes. Here, we used an invasive plant Solidago canadensis to test whether invasive populations had a higher proportion of polyploids, greater height and stem-base diameter, and occupied a wider range of climatic conditions than conspecific native-range populations. We also tested whether the invasive populations had overcome genetic founder effects. We sampled a total of 80 populations in parts of the invaded range in China and native range in North America for in situ measurements of plant height and stem-base diameter in the field and for population genetic and cytotype analyses. To examine climatic correlates, we augmented our field-sampled data with occurrence records obtained from Global Biodiversity Information Facility. All, except one, of the populations that we sampled in China occurred in a humid subtropical climate. In contrast, the North American populations occurred in humid continental, humid subtropical, and semi-arid climatic zones. All populations of S. canadensis in China were purely hexaploid, while the North American populations were diploid, tetraploid, and hexaploid. The invasive hexaploids were significantly taller and had a larger stem-base diameter than native hexaploids. Native hexaploids were significantly taller and had larger stem-base diameter than native diploids. Climatic correlate assessment found that invasive and native populations occupied different climatic envelopes, with invasive populations occurring in warmer and less seasonal climates than native populations. However, there was no significant correlation between ploidy level and climatic envelope of S. canadensis. Molecular phylogeography data suggest reduced genetic founder effects in the invaded range. Overall, these results suggest that polyploidy does not influence S. canadensis climatic tolerance.

Determining key monitoring areas for the 10 most important weed species under a changing climate.

On a global level, weed species have a large potential to threaten ecosystems under a changing climate. The determination of key monitoring areas is an effective approach to prevent and control the spread of such species. The 10 most important weeds have been listed on a global scale. It is therefore crucial to delineate the areas with high monitoring ranks for the 10 most important weed species under climate change. We coupled conservation prioritization analysis with habitat suitability modelling to determine key monitoring areas for these species, based on different types and vulnerability levels of biomes under current and future (i.e., 2040-2069 and 2070-2099) scenarios. We determined some specific biomes (i.e., tropical and subtropical biomes, flooded grasslands and savannas, Mediterranean forests, woodlands and scrub, and mangroves) as key monitoring areas for the 10 most important weed species under a changing climate. These biomes are distributed in most regions of Latin America, the United States, Europe, central and south Africa, south and southeast Asia, southeast Australia, and New Zealand, including large vulnerable ecoregions. Tropical and subtropical grasslands, savannas, and shrublands were particularly vulnerable, because these biomes had the largest area with a high monitoring rank, and this rank was predicted to further increase in the near future. Our study highlights the importance of effective management strategies for the prevention and control of these species across different biomes on a global scale.

Potential invasive plant expansion in global ecoregions under climate change.

Climate change is increasing the risk of invasive plant expansion worldwide. However, few studies have specified the relationship between invasive plant expansion and ecoregions at the global scale under climate change. To address this gap, we provide risk maps highlighting the response of invasive plant species (IPS), with a focus on terrestrial and freshwater ecoregions to climate change, and further explore the climatic features of ecosystems with a high potential for invasive plant expansion under climate change. We use species distribution modelling to predict the suitable habitats of IPS with records at the global scale. Hotspots with a potential risk of IPS (such as aquatic plants, trees, and herbs) expanding in global ecoregions were distributed in Northern Europe, the UK, South America, North America, southwest China, and New Zealand. Temperature changes were related to the potential of IPS expansion in global ecoregions under climate change. Coastal and high latitude ecoregions, such as temperate forests, alpine vegetation, and coastal rivers, were severely infiltrated by IPS under climate change. Monitoring strategies should be defined for climate change for IPS, particularly for aquatic plants, trees, and herbs in the biomes of regions with coastal or high latitudes. The role of climate change on the potential for IPS expansion should be taken into consideration for biological conservation and risk evaluation of IPS at ecoregional scales.

Large-scale environmental niche variation between clonal and non-clonal plant species: Roles of clonal growth organs and ecoregions.

Clonal plant species can produce genetically identical and potentially independent offspring, and dominate a variety of habitats. The divergent evolutionary mechanisms between clonal and non-clonal plants are interesting areas of ecological research. A number of studies have shown that the environmental niche theory can support the mechanisms of evolution across plant species clades at large scales. However, few studies have explored large-scale environmental niche variation between clonal and non-clonal plant species. Here, we used principal component analysis to quantify the environmental niche of 137 plant species belonging to 13 genera, including 87 clonal species and 50 non-clonal species. We then used a standardized effect size to assess environmental niche variation between clonal and non-clonal plant species within each genus, based on types of clonal growth organs and ecoregions. Our study provided the first evidence that there were significant environmental niche differences between clonal and non-clonal plant species at large scales. Such differences varied depending on the types of clonal growth organs and ecoregions. Clonal plants with different growth organs (i.e., epigeogenous stems, hypogeogenous stems, root-splitters, and adventitious buds on roots) contributed greatly to differences in climatic niches between clonal and non-clonal plants. Differences in environmental niches between clonal and non-clonal plant species also depended on ecoregion types. Specifically, the ecoregions of temperate broadleaf and mixed forests can lead to environmental niche variation between clonal and non-clonal plant species. Our results provide new insights into the evolutionary divergence between clonal and non-clonal plant species.

Identifying potential distributions of 10 invasive alien trees: implications for conservation management of protected areas.

Tree invasion has the potential to negatively affect biodiversity and ecosystems, with invasive alien trees (IATs) expanding widely in protected areas (PAs) across different habitats. Thus, the effectiveness of PAs might be reduced. Investigation of the distributions of IAT is urgently required to improve the effective conservation management of PAs. We projected the potential distributions of 10 IATs, which included Acacia mearnsii, Ardisia elliptica, Cecropia peltata, Cinchona pubescens, Leucaena leucocephala, Melaleuca quinquenervia, Miconia calvescens, Morella faya, Prosopis glandulosa, and Spathodea campanulata, that have a serious influence on global biodiversity and assessed the distribution possibilities of these IATs in PAs based on the PA categories of the International Union for Conservation of Nature (IUCN). The overall potential distributions of these 10 IATs included Latin America, central and southern Africa, southeastern Asia, eastern Australia and New Zealand, and western Europe. Annual mean temperature, temperature seasonality, annual precipitation, and soil bulk density were found to be important environmental variables for the potential distributions of these IATs. Overall, A. mearnsii, A. elliptica, C. peltata, L. leucocephala, M. quinquenervia, M. calvescens, and S. campanulata were distributed mainly in the IUCN PA categories of national parks and PAs with sustainable use of natural resources. We proposed the following for conservation management of PAs: (1) completion of species inventories for PAs, (2) better understanding of factors driving invasions in PAs, (3) assessment of the efficiency of management within particular PAs, and (4) evaluation of changes in trends regarding plant invasions in PAs under climate change conditions.

Long-distance dispersal or postglacial contraction? Insights into disjunction between Himalaya-Hengduan Mountains and Taiwan in a cold-adapted herbaceous genus, Triplostegia.

Current disjunct patterns can result from long-distance dispersal or postglacial contraction. We herein investigate the evolutionary history of Triplostegia to elucidate the disjunction between the Himalaya-Hengduan Mountain region (HHM) and Taiwan (TW). Genetic structure of Triplostegia was investigated for 48 populations using sequences from five chloroplast loci and the ribosomal nuclear internal transcribed spacer. Divergence time estimation, ancestral area reconstruction, and species distribution modeling (SDM) were employed to examine the biogeographic history of Triplostegia. Substantial genetic differentiation among populations from southwestern China (SW), Central China (CC), and TW was detected. Triplostegia was inferred to have originated in SW, and diversification began during the late Miocene; CC was colonized in the mid-Pliocene, and TW was finally colonized in the early Pleistocene. SDM suggested an expansion of climatically suitable areas during the Last Glacial Maximum and range contraction during the Last interglacial in Triplostegia. Disjunction between HHM and TW in Triplostegia is most likely the consequence of topographic isolation and postglacial contraction. The potential climatic suitability areas for Triplostegia by 2070s (2061-2080) are predicted to slightly shrink and move northward. With continued global warming and human-induced deforestation, extinction risk may increase for the cold-adapted species, and appropriate strategies should be employed for ecosystem conservation.

Vulnerability of forest vegetation to anthropogenic climate change in China.

China has large areas of forest vegetation that are critical to biodiversity and carbon storage. It is important to assess vulnerability of forest vegetation to anthropogenic climate change in China because it may change the distributions and species compositions of forest vegetation. Based on the equilibrium assumption of forest communities across different spatial and temporal scales, we used species distribution modelling coupled with endemics-area relationship to assess the vulnerability of 204 forest communities across 16 vegetation types under different climate change scenarios in China. By mapping the vulnerability of forest vegetation to climate change, we determined that 78.9% and 61.8% of forest vegetation should be relatively stable in the low and high concentration scenarios, respectively. There were large vulnerable areas of forest vegetation under anthropogenic climate change in northeastern and southwestern China. The vegetation of subtropical mixed broadleaf evergreen and deciduous forest, cold-temperate and temperate mountains needleleaf forest, and temperate mixed needleleaf and broadleaf deciduous forest types were the most vulnerable under climate change. Furthermore, the vulnerability of forest vegetation may increase due to high greenhouse gas concentrations. Given our estimates of forest vegetation vulnerability to anthropogenic climate change, it is critical that we ensure long-term monitoring of forest vegetation responses to future climate change to assess our projections against observations. We need to better integrate projected changes of temperature and precipitation into climate-adaptive conservation strategies for forest vegetation in China.

Climatic niche divergence and habitat suitability of eight alien invasive weeds in China under climate change.

Testing climatic niche divergence and modeling habitat suitability under conditions of climate change are important for developing strategies to limit the introduction and expansion of alien invasive weeds (AIWs) and providing important ecological and evolutionary insights. We assessed climatic niches in both native and invasive ranges as well as habitat suitability under climate change for eight representative Chinese AIWs from the American continent. We used climatic variables associated with occurrence records and developed ecological niche models with Maxent. Interestingly, the climatic niches of all eight AIWs diverged significantly between the native and invasive ranges (the American continent and China). Furthermore, the AIWs showed larger climatic niche breadths in the invasive ranges than in the native ranges. Our results suggest that climatic niche shifts between native and invasive ranges occurred. Thus, the occurrence records of both native and invasive regions must be considered when modeling and predicting the spatial distributions of AIWs under current and future climate scenarios. Owing to high habitat suitability, AIWs were more likely to expand into regions of low latitude, and future climate change was predicted to result in a shift in the AIWs in Qinghai and Tibet (regions of higher altitude) as well as Heilongjiang, Jilin, Liaoning, Inner Mongolia, and Gansu (regions of higher latitude). Our results suggest that we need measures to prevent and control AIW expansion at the country-wide level.

Climate change may threaten habitat suitability of threatened plant species within Chinese nature reserves.

Climate change has the potential to alter the distributions of threatened plant species, and may therefore diminish the capacity of nature reserves to protect threatened plant species. Chinese nature reserves contain a rich diversity of plant species that are at risk of becoming more threatened by climate change. Hence, it is urgent to identify the extent to which future climate change may compromise the suitability of threatened plant species habitats within Chinese nature reserves. Here, we modelled the climate suitability of 82 threatened plant species within 168 nature reserves across climate change scenarios. We used Maxent modelling based on species occurrence localities and evaluated climate change impacts using the magnitude of change in climate suitability and the degree of overlap between current and future climatically suitable habitats. There was a significant relationship between overlap with current and future climate suitability of all threatened plant species habitats and the magnitude of changes in climate suitability. Our projections estimate that the climate suitability of more than 60 threatened plant species will decrease and that climate change threatens the habitat suitability of plant species in more than 130 nature reserves under the low, medium, and high greenhouse gas concentration scenarios by both 2050s and 2080s. Furthermore, future climate change may substantially threaten tree plant species through changes in annual mean temperature. These results indicate that climate change may threaten plant species that occur within Chinese nature reserves. Therefore, we suggest that climate change projections should be integrated into the conservation and management of threatened plant species within nature reserves.

Identifying appropriate protected areas for endangered fern species under climate change.

The management of protected areas (PAs) is widely used in the conservation of endangered plant species under climate change. However, studies that have identified appropriate PAs for endangered fern species are rare. To address this gap, we must develop a workflow to plan appropriate PAs for endangered fern species that will be further impacted by climate change. Here, we used endangered fern species in China as a case study, and we applied conservation planning software coupled with endangered fern species distribution data and distribution modeling to plan conservation areas with high priority protection needs under climate change. We identified appropriate PAs for endangered fern species under climate change based on the IUCN protected area categories (from Ia to VI) and planned additional PAs for endangered fern species. The high priority regions for protecting the endangered fern species were distributed throughout southern China. With decreasing temperature seasonality, the priority ranking of all endangered fern species is projected to increase in existing PAs. Accordingly, we need to establish conservation areas with low climate vulnerability in existing PAs and expand the conservation areas for endangered fern species in the high priority conservation regions.

Model-based conservation planning of the genetic diversity of Phellodendron amurense Rupr due to climate change.

Climate change affects both habitat suitability and the genetic diversity of wild plants. Therefore, predicting and establishing the most effective and coherent conservation areas is essential for the conservation of genetic diversity in response to climate change. This is because genetic variance is a product not only of habitat suitability in conservation areas but also of efficient protection and management. Phellodendron amurense Rupr. is a tree species (family Rutaceae) that is endangered due to excessive and illegal harvesting for use in Chinese medicine. Here, we test a general computational method for the prediction of priority conservation areas (PCAs) by measuring the genetic diversity of P. amurense across the entirety of northeast China using a single strand repeat analysis of twenty microsatellite markers. Using computational modeling, we evaluated the geographical distribution of the species, both now and in different future climate change scenarios. Different populations were analyzed according to genetic diversity, and PCAs were identified using a spatial conservation prioritization framework. These conservation areas were optimized to account for the geographical distribution of P. amurense both now and in the future, to effectively promote gene flow, and to have a long period of validity. In situ and ex situ conservation, strategies for vulnerable populations were proposed. Three populations with low genetic diversity are predicted to be negatively affected by climate change, making conservation of genetic diversity challenging due to decreasing habitat suitability. Habitat suitability was important for the assessment of genetic variability in existing nature reserves, which were found to be much smaller than the proposed PCAs. Finally, a simple set of conservation measures was established through modeling. This combined molecular and computational ecology approach provides a framework for planning the protection of species endangered by climate change.