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

Multiscale ecological niche modeling exhibits varying climate change impacts on habitat suitability of Madrean Pine-Oak trees

Anthropogenic climate change and increasing greenhouse gas emissions are expected to globally impact the biological function, community structure, and spatial distribution of biodiversity. Many existing studies explore the effect of climate change on biodiversity, generally at a single spatial scale. This study explores the potential effects of climate change on the habitat suitability of seven tree species at two distinct spatial scales: the Coronado National Forest (CNF), a local management area, and the Sierra Madre Occidental (SMO), an ecoregional extent. Habitat suitability was determined by extrapolating Ecological Niche Models (ENMs) based on citizen-science tree occurrence records into future climatic conditions using projected 30-year normals for two anthropogenic emissions scenarios through the end of the century. These ENMs, examined at a spatial resolution of 1 km2, are constructed using a mean average ensemble of three commonly used machine learning algorithms. The results show that habitat suitability is expected to decrease for all seven tree species at varying degrees. Results also show that climate-forcing scenario choice appears to be far less important for understanding changes in species habitat suitability than the spatial scale of modeling extent. Additionally, we observed non-linear changes in tree species habitat suitability within the SMO and CNF dependent on forest community type, latitude, and elevational gradient. The paper concludes with a discussion of the necessary steps to verify the estimated alters of these tree species under climate change. Most importantly, provides a framework for characterizing habitat suitability across spatial scales.

Genomic, Habitat, and Leaf Shape Analyses Reveal a Possible Cryptic Species and Vulnerability to Climate Change in a Threatened Daisy

Olearia pannosa is a plant species listed as vulnerable in Australia. Two subspecies are currently recognised (O. pannosa subsp. pannosa (silver daisy) and O. pannosa subsp. cardiophylla (velvet daisy)), which have overlapping ranges but distinct leaf shape. Remnant populations face threats from habitat fragmentation and climate change. We analysed range-wide genomic data and leaf shape variation to assess population diversity and divergence and to inform conservation management strategies. We detected three distinct genetic groupings and a likely cryptic species. Samples identified as O. pannosa subsp. cardiophylla from the Flinders Ranges in South Australia were genetically distinct from all other samples and likely form a separate, range-restricted species. Remaining samples formed two genetic clusters, which aligned with leaf shape differences but not fully with current subspecies classifications. Levels of genetic diversity and inbreeding differed between the three genetic groups, suggesting each requires a separate management strategy. Additionally, we tested for associations between genetic and environmental variation and carried out habitat suitability modelling for O. pannosa subsp. pannosa populations. We found mean annual maximum temperature explained a significant proportion of genomic variance. Habitat suitability modelling identified mean summer maximum temperature, precipitation seasonality and mean annual rainfall as constraints on the distribution of O. pannosa subsp. pannosa, highlighting increasing aridity as a threat for populations located near suitability thresholds. Our results suggest maximum temperature is an important agent of selection on O. pannosa subsp. pannosa and should be considered in conservation strategies. We recommend taxonomic revision of O. pannosa and provide conservation management recommendations.

The Impact of Human Pressure and Climate Change on the Habitat Availability and Protection of Cypripedium (Orchidaceae) in Northeast China

Human pressure on the environment and climate change are two important factors contributing to species decline and overall loss of biodiversity. Orchids may be particularly vulnerable to human-induced losses of habitat and the pervasive impact of global climate change. In this study, we simulated the extent of the suitable habitat of three species of the terrestrial orchid genus Cypripedium in northeast China and assessed the impact of human pressure and climate change on the future distribution of these species. Cypripedium represents a genus of long-lived terrestrial orchids that contains several species with great ornamental value. Severe habitat destruction and overcollection have led to major population declines in recent decades. Our results showed that at present the most suitable habitats of the three species can be found in Da Xing’an Ling, Xiao Xing’an Ling and in the Changbai Mountains. Human activity was predicted to have the largest impact on species distributions in the Changbai Mountains. In addition, climate change was predicted to lead to a shift in distribution towards higher elevations and to an increased fragmentation of suitable habitats of the three investigated Cypripedium species in the study area. These results will be valuable for decision makers to identify areas that are likely to maintain viable Cypripedium populations in the future and to develop conservation strategies to protect the remaining populations of these enigmatic orchid species.

Climatic Change Can Influence Species Diversity Patterns and Potential Habitats of Salicaceae Plants in China

Salicaceae is a family of temperate woody plants in the Northern Hemisphere that are highly valued, both ecologically and economically. China contains the highest species diversity of these plants. Despite their widespread human use, how the species diversity patterns of Salicaceae plants formed remains mostly unknown, and these may be significantly affected by global climate warming. Using past, present, and future environmental data and 2673 georeferenced specimen records, we first simulated the dynamic changes in suitable habitats and population structures of Salicaceae. Based on this, we next identified those areas at high risk of habitat loss and population declines under different climate change scenarios/years. We also mapped the patterns of species diversity by constructing niche models for 215 Salicaceae species, and assessed the driving factors affecting their current diversity patterns. The niche models showed Salicaceae family underwent extensive population expansion during the Last Inter Glacial period but retreated to lower latitudes during and since the period of the Last Glacial Maximum. Looking ahead, as climate warming intensifies, suitable habitats will shift to higher latitudes and those at lower latitudes will become less abundant. Finally, the western regions of China harbor the greatest endemism and species diversity of Salicaceae, which are significantly influenced by annual precipitation and mean temperature, ultraviolet-B (UV-B) radiation, and the anomaly of precipitation seasonality. From these results, we infer water–energy dynamic equilibrium and historical climate change are both the main factors likely regulating contemporary species diversity and distribution patterns. Nevertheless, this work also suggests that other, possibly interacting, factors (ambient energy, disturbance history, soil condition) influence the large-scale pattern of Salicaceae species diversity in China, making a simple explanation for it unlikely. Because Southwest China likely served as a refuge for Salicaceae species during the Last Glacial Maximum, it is a current hotspot for endemisms. Under predicted climate change, Salicaceae plants may well face higher risks to their persistence in southwest China, so efforts to support their in-situ conservation there are urgently needed.

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.

Planning priority conservation areas under climate change for six plant species with extremely small populations in China

The concept of Plant Species with Extremely Small Populations (PSESP) has been employed to guide conservation of threatened plant species in China. Climate change has a high potential to threaten PSESP. As a result, it is necessary to integrate climate change effects on PSESP into conservation planning in China. Here, ecological niche modelling is used to project current and future habitat distributions of six PSESP in China under climate change scenarios and conservation planning software is applied to identify priority conservation areas (PCAs) for these PSESP based on habitat distributions. These results were used to provide proposals for in-situ and ex-situ conservation measures directed at PSESP. It was found that annual precipitation was important for habitat distributions for all six PSESP (with the percentage contribution to habitat distributions ranging from 18.1 % to 74.9 %) and non-climatic variables including soil and altitude have a large effect on habitat suitability of PSESP. Large quantities of PCAs occurred within some provincial regions for these six PSESP (e.g. Sichuan and Jilin for the PSESP Cathaya argyrophylla, Taxus cuspidata, Annamocarya sinensis and Madhuca pasquieri), indicating that these are likely to be appropriate areas for in-situ and ex-situ conservation measures directed at these PSESP. Those nature reserves with large quantities of PCAs were identified as promising sites for in-situ conservation measures of PSESP; such reserves include Yangzie and Dongdongtinghu for C. argyrophylla, Songhuajiangsanhu and Changbaishan for T. cuspidata and Shiwandashanshuiyuanlian for Tsoongiodendron odorum. These results suggest that existing seed banks and botanical gardens occurring within identified PCAs should allocate more resources and space to ex-situ conservation of PSESP. In addition, there should be additional botanical gardens established for ex-situ conservation of PSESP in PCAs outside existing nature reserves. To address the risk of negative effects of climate change on PSESP, it is necessary to integrate in-situ and ex-situ conservation as well as climate change monitoring in PSESP conservation planning.

Contemporary Remotely Sensed Data Products Refine Invasive Plants Risk Mapping in Data Poor Regions

Invasive weeds are a serious problem worldwide, threatening biodiversity and damaging economies. Modeling potential distributions of invasive weeds can prioritize locations for monitoring and control efforts, increasing management efficiency. Forecasts of invasion risk at regional to continental scales are enabled by readily available downscaled climate surfaces together with an increasing number of digitized and georeferenced species occurrence records and species distribution modeling techniques. However, predictions at a finer scale and in landscapes with less topographic variation may require predictors that capture biotic processes and local abiotic conditions. Contemporary remote sensing (RS) data can enhance predictions by providing a range of spatial environmental data products at fine scale beyond climatic variables only. In this study, we used the Global Biodiversity Information Facility (GBIF) and empirical maximum entropy (MaxEnt) models to model the potential distributions of 14 invasive plant species across Southeast Asia (SEA), selected from regional and Vietnam's lists of priority weeds. Spatial environmental variables used to map invasion risk included bioclimatic layers and recent representations of global land cover, vegetation productivity (GPP), and soil properties developed from Earth observation data. Results showed that combining climate and RS data reduced predicted areas of suitable habitat compared with models using climate or RS data only, with no loss in model accuracy. However, contributions of RS variables were relatively limited, in part due to uncertainties in the land cover data. We strongly encourage greater adoption of quantitative remotely sensed estimates of ecosystem structure and function for habitat suitability modeling. Through comprehensive maps of overall predicted area and diversity of invasive species, we found that among lifeforms (herb, shrub, and vine), shrub species have higher potential invasion risk in SEA. Native invasive species, which are often overlooked in weed risk assessment, may be as serious a problem as non-native invasive species. Awareness of invasive weeds and their environmental impacts is still nascent in SEA and information is scarce. Freely available global spatial datasets, not least those provided by Earth observation programs, and the results of studies such as this one provide critical information that enables strategic management of environmental threats such as invasive species.

Potential effects of climate change on geographic distribution of the Tertiary relict tree species Davidia involucrata in China

This study, using species distribution modeling (involving a new approach that allows for uncertainty), predicts the distribution of climatically suitable areas prevailing during the mid-Holocene, the Last Glacial Maximum (LGM), and at present, and estimates the potential formation of new habitats in 2070 of the endangered and rare Tertiary relict tree Davidia involucrata Baill. The results regarding the mid-Holocene and the LGM demonstrate that south-central and southwestern China have been long-term stable refugia, and that the current distribution is limited to the prehistoric refugia. Given future distribution under six possible climate scenarios, only some parts of the current range of D. involucrata in the mid-high mountains of south-central and southwestern China would be maintained, while some shift west into higher mountains would occur. Our results show that the predicted suitable area offering high probability (0.5‒1) accounts for an average of only 29.2% among the models predicted for the future (2070), making D. involucrata highly vulnerable. We assess and propose priority protected areas in light of climate change. The information provided will also be relevant in planning conservation of other paleoendemic species having ecological traits and distribution ranges comparable to those of D. involucrata.