Major declines of woody plant species ranges under climate change in Yunnan, China

Changing effects of energy and water on the richness distribution pattern of the Quercus genus in China

Climate varies along geographic gradients, causing spatial variations in the effects of energy and water on species richness and the explanatory power of different climatic factors. Species of the Quercus genus are important tree species in China with high ecological and socioeconomic value. To detect whether the effects of energy and water on species richness change along climatic gradients, this study built geographically weighted regression models based on species richness and climatic data. Variation partition analysis and hierarchical partitioning analysis were used to further explore the main climatic factors shaping the richness distribution pattern of Quercus in China. The results showed that Quercus species were mainly distributed in mountainous areas of southwestern China. Both energy and water were associated with species richness, with global slopes of 0.17 and 0.14, respectively. The effects of energy and water on species richness gradually increased as energy and water in the environment decreased. The interaction between energy and water altered the effect of energy, and in arid regions, the effects of energy and water were relatively stronger. Moreover, energy explained more variation in species richness in both the entire study area (11.5%) and different climate regions (up to 19.4%). The min temperature of coldest month was the main climatic variable forming the richness distribution pattern of Quercus in China. In conclusion, cold and drought are the critical climatic factors limiting the species richness of Quercus, and climate warming will have a greater impact in arid regions. These findings are important for understanding the biogeographic characteristics of Quercus and conserving biodiversity in China.

Differences in the Suitable Distribution Area between Northern and Southern China Landscape Plants

Climate change, a global biodiversity threat, largely influences the geographical distribution patterns of species. China is abundant in woody landscape plants. However, studies on the differences in the adaptive changes of plants under climate change between northern and southern China are unavailable. Therefore, herein, the MaxEnt model was used to predict changes in the suitable distribution area (SDA) and dominant environmental variables of 29 tree species under two climate change scenarios, the shared socioeconomic pathways (SSPs) 126 and 585, based on 29 woody plant species and 20 environmental variables in northern and southern China to assess the differences in the adaptive changes of plants between the two under climate change. Temperature factors dominated the SDA distribution of both northern and southern plants. Southern plants are often dominated by one climatic factor, whereas northern plants are influenced by a combination of climatic factors. Northern plants are under greater pressure from SDA change than southern plants, and their SDA shrinkage tendency is significantly higher. However, no significant difference was observed between northern and southern plants in SDA expansion, mean SDA elevation, and latitudinal change in the SDA mass center. Future climate change will drive northern and southern plants to migrate to higher latitudes rather than to higher elevations. Therefore, future climate change has varying effects on plant SDAs within China. The climate change intensity will drive northern landscape plants to experience greater SDA-change-related pressure than southern landscape plants. Therefore, northern landscape plants must be heavily monitored and protected.

Meta-analysis of the impact of future climate change on the area of woody plant habitats in China

Climate change poses a very serious threat to woody plants, and it is important to study its impact on the distribution dynamics of woody plants in China. However, there are no comprehensive quantitative studies on which factors influence the changes in the area of woody plant habitats in China under climate change. In this meta-analysis, we investigated the future suitable habitat area changes of 114 woody plant species in 85 studies based on MaxEnt model predictions to summarize the future climate change impacts on woody plant habitat area changes in China. It was found that climate change will result in a 3.66% increase in the overall woody plant suitable areas and a 31.33% decrease in the highly suitable areas in China. The mean temperature of the coldest quarter is the most important climatic factor, and greenhouse gas concentrations were inversely related to the area of future woody plant suitable areas. Meanwhile, shrubs are more climate-responsive than trees, drought-tolerant plants (e.g., Dalbergia, Cupressus, and Xanthoceras) and plants that can adapt quickly (e.g., Camellia, Cassia, and Fokienia) and their appearance will increase in the future. Old World temperate, Trop. Asia and Trop. Amer. disjuncted, and the Sino-Himalaya Floristic region are more vulnerable. Quantitative analysis of the possible risks to future climate change in areas suitable for woody plants in China is important for global woody plant diversity conservation.

A Global review of cumulative effects assessments of disturbances on forest ecosystems

This paper reviews trends in the academic literature on cumulative effects assessment (CEA) of disturbance on forest ecosystems to advance research in the broader context of impact assessments. Disturbance is any distinct spatiotemporal event that disrupts the structure and composition of an ecosystem affecting resource availability. We developed a Python package to automate search term selection, write search strategies, reduce bias and improve the efficient and effective selection of articles from academic databases and grey literature. We identified 148 peer-reviewed literature published between 1986 and 2022 and conducted an inductive and deductive thematic analysis of the results. Our findings revealed that CEA studies are concentrated in the global north, with most publications from authors affiliated with government agencies in the USA and Canada. Methodological and analytical approaches are less interdisciplinary but mainly quantitative and expert-driven, involving modeling the impacts of disturbances on biophysical valued components. Furthermore, the assessment of socioeconomic valued components, including the effects of disturbance on Indigenous wellbeing connected to forests, has received less attention. Even though there is a high preference for regional assessment, challenges with data access, quality, and analysis, especially baseline data over long periods, are hampering effective CEA. Few articles examined CEA - policy/management nexus. Of the few studies, challenges such as the inadequate implementation of CEA mitigation strategies due to policy drawbacks and resource constraints, the high cost of monitoring multiple indicators, and poor connections between scenarios/modeling and management actions were paramount. Future CEA research is needed to broaden our understanding of how multiple disturbance affects forests in the global south and coupled social and ecological systems and their implications for sustainable forest management.

Alterations in Population Distribution of Liriodendron chinense (Hemsl.) Sarg. and Liriodendron tulipifera Linn. Caused by Climate Change

Climate change has a significant impact on species population size and distribution, global biodiversity, and ecological status. The Liriodendron genus contains two species: Liriodendron chinense and Liriodendron tulipifera, both playing important roles in timber, medicinal, and landscape purposes. However, little is known about their population distribution characteristics and important climatic factors shaping their suitability. In this research, we used the geological record data, 19 climate components, MaxEnt, and ArcGIS to recreate and analyze the potential population distribution and their alterations of Liriodendron within the world beneath the current and future scenarios of RCP 2.6, RCP 4.5, and RCP 8.5 in 2050 and 2070. Our results showed that: Liriodendron is suitable to grow in subtropical monsoon climate areas, and that the climatic factor of precipitation of warmest quarter exerts the greatest impact on L. chinense, with a contribution rate of 57.6%. Additionally, we showed that the climatic factor of precipitation of the driest month exerts the greatest impact on L. tulipifera, with a contribution rate of 60.5%. Further analysis exhibited that low temperature and temperature fluctuations are major temperature factors affecting L. chinense and L. tulipifera, respectively. Therefore, we predicted that by the 2050s and 2070s, the areas of Liriodendron suitable habitats would increase first and then decrease in three scenarios; except the area of L. tulipifera suitable habitats under RCP8.5, which shows a slight increase. We then conclude that the Liriodendron suitable areas would shift to high latitudes due to global climate warming. The information gained from this study will provide a reference for developing forest cultivation, management, and conservation strategies for these two important tree species, and also a basis for subsequent biogeographic research.

Monthly rather than annual climate variation determines plant diversity change in four temperate grassland nature reserves

Plant diversity is changing in the world; climate variation at annual scale is believed to drive these changes; however, the effects of climate variation at month scale are still unknown. Anxi, West Ordos, Xilingol, and Tumuji grassland nature reserves, located in northern China, have been well protected from human disturbance, are ideal areas to identify the drive forces for plant diversity change. Using Landsat images from 1982 to 2017, we analyzed the evolution of month- and annual-climate variables and spectral plant diversity indices, and explored the effects of the variability of temperature and precipitation on plant diversity and their relationship. The results showed that the diversity of the four grasslands was decreasing. Climate variables, in particular temperature at month scale, significantly related to grassland plant diversity. These results enlarge our understanding in how climate change driving plant diversity during a long term. Measurements coping with plant diversity decreasing may be more effective and earlier based on monthly climate variables.

Maxent Modelling Predicts a Shift in Suitable Habitats of a Subtropical Evergreen Tree (Cyclobalanopsis glauca (Thunberg) Oersted) under Climate Change Scenarios in China

Climate change has caused substantial shifts in the geographical distribution of many species. There is growing evidence that many species are migrating in response to climate change. Changes in the distribution of dominant tree species induced by climate change can have an impact not only on organisms such as epiphytes and understory vegetation, but also on the whole ecosystem. Cyclobalanopsis glauca is a dominant tree species in the mingled evergreen and deciduous broadleaf forests of China. Understanding their adaptive strategies against climate change is important for understanding the future community structure. We employed the Maxent framework to model current suitable habitats of C. glauca under current climate conditions and predicted it onto the climate scenarios for 2041–2060 and 2081–2100 using 315 occurrence data. Our results showed that annual precipitation was the most critical factor for the distribution of C. glauca. In the future, increasing precipitation would reduce the limitation of water on habitats, leading to an expansion of the distribution to a higher latitude and higher altitude. At the same time, there were habitat contractions at the junction of the Jiangxi and Fujian Provinces. This study can provide vital information for the management of C. glauca, and serve as a reminder for managers to protect C. glauca in the range contraction areas.

Conservation planning on China's borders with Myanmar, Laos, and Vietnam

Transboundary conservation is playing an increasingly important role in maintaining ecosystem integrity and halting biodiversity loss caused by anthropogenic activities. However, lack of information on species distributions in transboundary regions and understanding of the threats in these areas impairs conservation. We developed a spatial conservation plan for the transboundary areas between Yunnan province, southwestern China, and neighboring Myanmar, Laos, and Vietnam in the Indo-Burma biodiversity hotspot. To identify priority areas for conservation and restoration, we determined species distribution patterns and recent land-use changes and examined the spatiotemporal dynamics of the connected natural forest, which supports most species. We assessed connectivity with equivalent connected area (ECA), which is the amount of reachable habitat for a species. An ECA incorporates the presence of habitat in a patch and the amount of habitat in other patches within dispersal distance. We analyzed 197,845 locality records from specimen collections and monographs for 21,004 plant and vertebrate species. The region of Yunnan immediately adjacent to the international borders had the highest species richness, with 61% of recorded species and 56% of threatened vertebrates, which suggests high conservation value. Satellite imagery showed the area of natural forest in the border zone declined by 5.2% (13,255 km² ) from 1995 to 2018 and monoculture plantations increased 92.4%, shrubland 10.1%, and other cropland 6.2%. The resulting decline in connected natural forest reduced the amount of habitat, especially for forest specialists with limited dispersal abilities. The most severe decline in connectivity was along the Sino-Vietnamese border. Many priority areas straddle international boundaries, indicating demand and potential for establishing transboundary protected areas. Our results illustrate the importance of bi- and multilateral cooperation to protect biodiversity in this region and provide guidance for future conservation planning and practice.

Macroecological context predicts species' responses to climate warming

Context-dependencies in species' responses to the same climate change frustrate attempts to generalize and make predictions based on experimental and observational approaches in biodiversity science. Here, we propose predictability may be enhanced by explicitly incorporating macroecological context into analyses of species' responses to climate manipulations. We combined vascular plant species' responses to an 8-year, 12-site turf transplant climate change experiment set in southwestern Norway with climate niche data from the observed 151 species. We used the difference between a species' mean climate across their range and climate conditions at the transplant site ("climate differences") to predict colonization probability, extinction probability, and change in abundance of a species at a site. In analyses across species that ignore species-specific patterns, colonization success increased as species' distribution optima were increasingly warmer than the experimental target site. Extinction probability increased as species' distribution optima were increasingly colder than the target site. These patterns were reflected in change in abundance analyses. We found weak responses to increased precipitation in these oceanic climates. Climate differences were better predictors of species' responses to climate manipulations than range size. Interestingly, similar patterns were found when analyses focused on variation in species-specific responses across sites. These results provide an experimental underpinning to observational studies that report thermophilization of communities and suggest that space-for-time substitutions may be valid for predicting species' responses to climate warming, given other conditions are accounted for (e.g., soil nutrients). Finally, we suggest that this method of putting climate change experiments into macroecological context has the potential to generalize and predict species' responses to climate manipulations globally.

Predicting range shifts of three endangered endemic plants of the Khorassan-Kopet Dagh floristic province under global change

Endemic plants of the Khorassan-Kopet Dagh (KK) floristic province in northeastern Iran, southern Turkmenistan, and northwestern Afghanistan are often rare and range-restricted. Because of these ranges, plants in the KK are vulnerable to the effects of climate change. Species distribution modelling (SDM) can be used to assess the vulnerability of species under climate change. Here, we evaluated range size changes for three (critically) endangered endemic species that grow at various elevations (Nepeta binaloudensis, Phlomoides binaludensis, and Euphorbia ferdowsiana) using species distribution modelling. Using the HadGEM2-ES general circulation model and two Representative Concentration Pathways Scenarios (RCP 2.6 and RCP 8.5), we predicted potential current and future (2050 and 2070) suitable habitats for each species. The ensemble model of nine algorithms was used to perform this prediction. Our results indicate that while two of species investigated would benefit from range expansion in the future, P. binaludensis will experience range contraction. The range of E. ferdowsiana will remain limited to the Binalood mountains, but the other species will have suitable habitats in mountain ranges across the KK. Using management efforts (such as fencing) with a focus on providing elevational migration routes at local scales in the KK is necessary to conserve these species. Additionally, assisted migration among different mountains in the KK would be beneficial to conserve these plants. For E. ferdowsiana, genetic diversity storage employing seed banks and botanical garden preservation should be considered.

The effect of climate change on the richness distribution pattern of oaks (Quercus L.) in China

Increased concentration of greenhouse gases in the air is acknowledged as one of the main reason for observed global climatic change. This phenomenon significantly affects the species geographical distribution, and changes their richness distribution pattern. Oak (Quercus L.) is an important component of forests in China, and it has significant ecological value. Based on the distribution data of 35 species and 19 bioclimatic variables, the potential richness distribution of Quercus L. in China was predicted using the MaxEnt model under present climatic conditions and three different emission scenarios in the years 2050 and 2070 with six General Circulation Models (GCMs). The results revealed that Quercus L. at present was primarily distributed in the mountainous areas of southwestern China. The simulations indicated that climate change could affect the spatial pattern of the richness distribution, and if climate change intensified, its impact would gradually increase. As temperatures rise, the distribution of Quercus L. was predicted to be concentrated, and suitable areas of certain species would contract. These species may migrate to high altitudes or high latitudes. The high percentage of species lost is the reason for the higher turnover values in the mountainous areas, while other regions are mostly be influenced by the high percentage of species gained associated with the northward shift of species. Predicting changes in the richness distribution pattern of Quercus L. as a result of climate change can help us understand the biogeography of Quercus L. and enact conservation strategies to minimize the impacts of climate change.

Climate change-induced migration patterns and extinction risks of Theaceae species in China

Theaceae, an economically important angiosperm family, is widely distributed in tropical and subtropical forests in Asia. In China, Theaceae has particularly high abundances and endemism, comprising ~75% of the total genera and ~46% of the total species worldwide. Therefore, predicting the response of Theaceae species to climate change is vital. In this study, we collected distribution data for 200 wild Theaceae species in China, and predicted their distribution patterns under current and future climactic conditions by species distribution modeling (SDM). We revealed that Theaceae species richness is highest in southeastern China and on Hainan Island, reaching its highest value (137 species) in Fujian Province. According to the IUCN Red List criteria for assessing species threat levels under two dispersal assumptions (no dispersal and full dispersal), we evaluated the conservation status of all Theaceae species by calculating loss of suitable habitat under future climate scenarios. We predicted that nine additional species will become threatened due to climate change in the future; one species will be classified as critically endangered (CR), two as endangered (EN), and six as vulnerable (VU). Given their extinction risks associated with climate change, we recommended that these species be added to the Red List. Our investigation of migration patterns revealed regional differences in the number of emigrant, immigrant, and persistent species, indicating the need for targeted conservation strategies. Regions containing numerous emigrants are concentrated in Northern Taiwan and coastal regions of Zhejiang and Fujian provinces, while regions containing numerous immigrants include central Sichuan Province, the southeastern Tibet Autonomous Region, southwest Yunnan Province, northwest Sichuan Province, and the junction of Guangxi and Hunan provinces. Lastly, regions containing persistent species are widely distributed in southern China. Importantly, regions with high species turnover are located on the northern border of the entire Theaceae species distribution ranges owing to upwards migration; these regions are considered most sensitive to climate change and conservation planning should therefore be prioritized here. This study will contribute valuable information for reducing the negative impacts of climate change on Theaceae species, which will ultimately improve biodiversity conservation efficiency.

Potential distribution of Notopterygium incisum Ting ex H. T. Chang and its predicted responses to climate change based on a comprehensive habitat suitability model

Notopterygium incisum Ting ex H. T. Chang is a rare and endangered traditional Chinese medicinal plant. In this research, we built a comprehensive habitat suitability (CHS) model to analyze the potential suitable habitat distribution of this species in the present and future in China. First, using nine different algorithms, we built an ensemble model to explore the possible impacts of climate change on the habitat distribution of this species. Then, based on this model, we built a CHS model to further identify the distribution characteristics of N. incisum-suitable habitats in three time periods (current, 2050s, and 2070s) while considering the effects of soil and vegetation conditions. The results indicated that the current suitable habitat for N. incisum covers approximately 83.76 × 103 km2, and these locations were concentrated in the Tibet Autonomous Region, Gansu Province, Qinghai Province, and Sichuan Province. In the future, the areas of suitable habitat for N. incisum would significantly decrease and would be 69.53 × 103 km2 and 60.21 × 103 km2 in the 2050s and 2070s, respectively. However, the area of marginally suitable habitat would remain relatively stable. This study provides a more reliable and comprehensive method for modelling the current and future distributions of N. incisum, and it provides valuable insights for highlighting priority areas for medicinal plant conservation and resource utilization.

Habitat preference and potential distribution of Magnolia officinalis subsp. officinalis and M. o. subsp. biloba in China

Magnolia officinalis subsp. officinalis and M. officinalis subsp. biloba are important medicinal plants in China. The bark of these two subspecies is commonly used in the production of a widely-used Chinese traditional medicine named ‘Houpu’. In recent years, M. o. subsp. officinalis and M. o. subsp. biloba have become increasingly threatened owing to the over-harvesting of their bark and the fragmentation of their habitats. In this study, we aimed to support the conservation and cultivation of these two subspecies in China by: (1) assessing the relationship between numerous environmental variables and the geographical distributions of the subspecies; (2) analysing the environmental characteristics of suitable habitats for both subspecies and predicting the spatial distribution of these habitats in China; and (3) identifying conservation areas of both subspecies in China via overlay analysis. We also assessed the degree of human disturbance within suitable habitats. We found that temperature was a major determinant for the distribution of M. o. subsp. officinalis. Conversely, the distribution of M. o. subsp. biloba was primarily dependent on precipitation rather than temperature. Distinct habitat preferences were observed between M. o. subsp. officinalis and M. o. subsp. biloba. Suitable habitats of M. o. subsp. officinalis were primarily distributed in the northern subtropical areas of China, with greater fluctuations in ambient temperature, lower extreme temperatures, less precipitation and greater fluctuations in precipitation. Habitats suitable for M. o. subsp. biloba were highly fragmented and were distributed in the central subtropical areas of China. We found that a large proportion of suitable habitats were not in the protected areas and that they were significantly disturbed by human activity. This analysis could provide useful information for the conservation of both M. o. subsp. officinalis and M. o. subsp. biloba and could aid in the selection of cultivation sites.

GIS assessment of the risk of gene flow from Brassica napus to its wild relatives in China

Risk of gene flow from canola (Brassica napus) to species of wild relatives was used as an example to evaluate the risk of gene flow of transgenic crops. B. juncea and B. rapa were the most common weedy Brassica species in China, which were both sexually compatible with canola. Data on canola cultivation in China were collected and analyzed using geographic information system (GIS), and the distribution of its wild relatives was predicted by MaxEnt species distribution model. Based on biological and phenological evidence, our results showed that gene flow risk exists in most parts of the country, especially in places with higher richness of wild Brassica species. However, risk in dominant canola cultivation regions is relatively low owing to the reduced distribution density of wild species in these regions. Three regions of higher risk of gene flow had been identified. Risk of gene flow is relatively high in certain areas. China has been assumed to be the original center of B. juncea and B. rapa, and gene flow may lead to negative effects on the conservation of biodiversity of local species. Strategies had been proposed to reduce the possibility of gene flow either by monitoring introgression from crops to wild relatives in the areas of high adoption of the crop or by taking measures to limit the releasing of new crops or varieties in the areas with abundant wild relatives.

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.

Vulnerability and impacts of climate change on forest and freshwater wetland ecosystems in Nepal: A review

Climate change (CC) threatens ecosystems in both developed and developing countries. As the impacts of CC are pervasive, global, and mostly irreversible, it is gaining worldwide attention. Here we review vulnerability and impacts of CC on forest and freshwater wetland ecosystems. We particularly look at investigations undertaken at different geographic regions in order to identify existing knowledge gaps and possible implications from such vulnerability in the context of Nepal along with available adaptation programs and national-level policy supports. Different categories of impacts which are attributed to disrupting structure, function, and habitat of both forest and wetland ecosystems are identified and discussed. We show that though still unaccounted, many facets of forest and freshwater wetland ecosystems of Nepal are vulnerable and likely to be impacted by CC in the near future. Provisioning ecosystem services and landscape-level ecosystem conservation are anticipated to be highly threatened with future CC. Finally, the need for prioritizing CC research in Nepal is highlighted to close the existing knowledge gap along with the implementation of adaptation measures based on existing location specific traditional socio-ecological system.

Predicting the distributions of Egypt's medicinal plants and their potential shifts under future climate change

Climate change is one of the most difficult of challenges to conserving biodiversity, especially for countries with few data on the distributions of their taxa. Species distribution modelling is a modern approach to the assessment of the potential effects of climate change on biodiversity, with the great advantage of being robust to small amounts of data. Taking advantage of a recently validated dataset, we use the medicinal plants of Egypt to identify hotspots of diversity now and in the future by predicting the effect of climate change on the pattern of species richness using species distribution modelling. Then we assess how Egypt's current Protected Area network is likely to perform in protecting plants under climate change. The patterns of species richness show that in most cases the A2a 'business as usual' scenario was more harmful than the B2a 'moderate mitigation' scenario. Predicted species richness inside Protected Areas was higher than outside under all scenarios, indicating that Egypt's PAs are well placed to help conserve medicinal plants.

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.

Distribution pattern of poisonous plant species in arid grasslands: a case from Xinjiang, Northwestern China

Poisonous plants threaten the ecosystem health of grasslands and the sustainability of animal husbandry. In arid lands, grassland ecosystems tend to be vulnerable and have been degraded due to the influence of human activities. The total area of the natural grasslands in Xinjiang, a large region in arid north-western China, ranks third in terms of area in China. In the process of grassland degradation, poisonous plants have spread widely and quickly in this region. During recent years, increasing economic losses have been caused by poisonous plants in Xinjiang. Although poisonous plants have been reported at some specific locations, their spatial patterns have rarely been investigated at a large regional scale. To understand the current status of hazards and assess the invasion risks of poisonous plants, we sampled ~150 poisonous plant species from Xinjiang and modelled the present and the future (the 2050s and the 2070s) distribution of 90 species using species distribution modelling. Based on the distribution maps of these poisonous plants, four diversity hotspots of poisonous plants were identified in Xinjiang. The results showed that northern Xinjiang had higher levels of poisonous plant diversity compared with the other part of Xinjiang. The precipitation factors had the most influence on prediction of the poisonous plants distributions in the species distribution modelling. Under the scenarios of future climate change, the results of modelling showed that regions close to the four hotspots of poisonous plants in Xinjiang displayed higher risks of invasion by poisonous plants in the future. In addition, these areas with a high risk of plant invasion will become increasingly large. We propose that policy makers consider implementing monitoring and prevention measures in areas identified as having a high risk of future invasion by poisonous plants.

Predictions of potential geographical distribution and quality of Schisandra sphenanthera under climate change

Climate change will significantly affect plant distribution as well as the quality of medicinal plants. Although numerous studies have analyzed the effect of climate change on future habitats of plants through species distribution models (SDMs), few of them have incorporated the change of effective content of medicinal plants. Schisandra sphenanthera Rehd. et Wils. is an endangered traditional Chinese medical plant which is mainly located in the Qinling Mountains. Combining fuzzy theory and a maximum entropy model, we obtained current spatial distribution of quality assessment for S. spenanthera. Moreover, the future quality and distribution of S. spenanthera were also projected for the periods 2020s, 2050s and 2080s under three different climate change scenarios (SRES-A1B, SRES-A2 and SRES-B1 emission scenarios) described in the Special Report on Emissions Scenarios (SRES) of IPCC (Intergovernmental Panel on Climate Change). The results showed that the moderately suitable habitat of S. sphenanthera under all climate change scenarios remained relatively stable in the study area. The highly suitable habitat of S. sphenanthera would gradually decrease in the future and a higher decline rate of the highly suitable habitat area would occur under climate change scenarios SRES-A1B and SRES-A2. The result suggested that in the study area, there would be no more highly suitable habitat areas for S. sphenanthera when the annual mean temperature exceeds 20 °C or its annual precipitation exceeds 1,200 mm. Our results will be influential in the future ecological conservation and management of S. sphenanthera and can be taken as a reference for habitat suitability assessment research for other medicinal plants.

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.

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.