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Species with narrow ranges, particularly rare and endangered ones, are more vulnerable to rapid climate change. The endangered Pinaceae species Picea smithiana (Wall.) Boiss. (P. smithiana), endemic to the Himalayan region, is of significant economic and ecological importance. Understanding how its distribution responds to climate change is crucial for effective biodiversity conservation. Our research integrates three species distribution models, i.e. MaxEnt, Random Forest, and Support Vector Machine, to predict the suitable habitat of P. smithiana in the past, present, and future, and to analyze changes in their spatial distribution patterns. Our study also interprets its geographical distribution patterns through an analysis of multiple environmental factors within its suitable habitat. Our results indicate that, since the last glacial maximum, the suitable habitat of P. smithiana has been shifting towards high latitudes and altitudes, corresponding with its cold tolerance traits. Besides the Himalayan region, suitable habitat of P. smithiana were also predicted in Southwest China, despite a lack of observed occurrences, suggesting possible speciation events linked to the uplift of the Qinghai−Tibetan Plateau. Our study warns that the actual distribution of P. smithiana might be more pessimistic than predictions indicate, with protected areas encompassing less than 27 % of its suitable habitat. This highlights the critical need for intensified conservation and management measures to secure the long-term persistence of P. smithiana.

Invasion risk assessments are essential for making informed decisions, allocating resources, and implementing targeted strategies to prevent or minimize the harmful effects of invasive species on native biodiversity, agricultural productivity, and natural ecosystems. In this study, the random forest algorithm was used to assess the spatial invasion risk of Lantana camara, one of the world’s top 100 worst invasive weeds, across all continents under current and future environmental conditions. The current invasion risk was relatively high on four continents (i.e., Africa, Australia, Oceania, and South America) within approximately 35°N and 35°S latitude, estimated to cover at least 68.98 % of the total land surface. Furthermore, projections for future environmental changes suggested a substantial increase in invasion risk across all continents, with the most significant changes (251.52 %) observed in Europe compared with current invasion levels. Additionally, invasion risk was predicted to extend beyond 35°N latitude. Categorizing 200 countries and territories into distinct risk levels, 27 countries had current invasion potential, and introduction and establishment was predicted in 114 countries. Moreover, at least 45 countries, including Canada, India, Italy, and United States, were projected to transition from no or low invasion risk to high invasion risk and 28 countries had a risk increase of over 50 %. Current study provides valuable insights into the global invasion risk posed by L. camara. These results are expected to be of great utility for invasive weed management, facilitating the development of control and sustainable management strategies for this notorious weed at both global and local scales.

Populus, one of the most extensively cultivated tree species in China, holds substantial potential for carbon sequestration potential and economic value. However, the effects of climate change on different Populus species remain unclear. Consequently, there is an urgency to investigate the potential distribution and dynamics of Populus under current and future climate scenarios. This study employed four ecological niche models and integrated data from multiple environmental sources to analyze the potential distribution patterns of three key Populus species—Populus tomentosa, Populus cathayana, and Populus lasiocarpa—under current and various future climate scenarios (2050, 2070, and 2090). Furthermore, the study identified the primary factors influencing their potential distribution. The occurrence of P. tomentosa was primarily influenced by the minimum temperature of the coldest month. Conversely, human population density was the most important factor for P. cathayana, showing strong positive effects on both P. tomentosa and P. cathayana occurrences. Soil total nitrogen had the strongest positive effect on P. lasiocarpa. The study found P. cathayana primarily in northern and northwestern China (105.45 × 104 km2), P. tomentosa in the northern and central regions (82.85 × 104 km2), and P. lasiocarpa in the southwest (49.17 × 104 km2). Under future climate scenarios, P. tomentosa and P. cathayana may shift towards higher latitudes, while P. lasiocarpa may shift towards lower latitudes. Future elevated temperatures are expected to positively affect Populus, especially P. tomentosa and P. lasiocarpa, thereby increasing their carbon sequestration capacity and carbon market value, which is maximized under a low-concentration scenario (SSP245). This study highlights the importance of climate change in Populus distribution and provides quantified potential distribution maps for three Populus species under current and future climate conditions in China. Based on the different adaptation strategies of Populus species to climate change, we recommend a ''site-specific, categorical planting'' approach to guide effective forest management practices in response to China's dual carbon goals.

Across the planet, biodiversity is facing ever-growing threats including habitat loss, climate change, overexploitation, and pollution. Pangolins of the order Pholidota are the only scaly mammal species worldwide and are considered the most trafficked wild mammals in the world, being widely exploited for their meat and scales. The giant pangolin (Smutsia gigantea, GP) is one of the least studied species of this order, with little being known about their response to environmental and anthropogenic variables, as well as their distribution patterns in forest-savannah transition areas. Our study aimed to increase ecological knowledge about GP by investigating the environmental factors associated with the distribution of suitable habitat for GP within a protected forest/savannah transition area of Cameroon. Using data on the locations of GP resting burrows collected using line transects and employing a maximum entropy (MaxEnt) modelling approach, we explored GP habitat suitability within a forest-savannah transition area of Cameroon. Our model revealed a good level of accuracy based on the average test area under the Receiver Operator Curve metric. The jackknife test found that Euclidian distance to the national park’s boundaries, normalized difference vegetation index, elevation, and distance to river were the most important predictors determining the distribution of GP burrows. Areas predicted to be suitable for GP burrows were patchily distributed within dense forests, ecotone and savannah, with 19.24% of the study area being suitable and 1% very suitable. Overall, our study shows the possible importance of habitat suitability modeling for understanding GP distribution, as well as planning and prioritising their conservation actions.

Isoetes L. is a relict genus of Isoetaceae which is of great value to study the systematic evolution of ferns and the flora of East Asia. Due to the impact of human activities on aquatic habitats, the population of Isoetes L. in China is decreasing. In this paper, based on environmental variables including bioclimate, soil factors, elevation, UV-B radiation and human footprint index, the potential distribution of Isoetes L. was simulated using MaxEnt and GARP. Results showed that the AUC and Kappa values of MaxEnt and GARP under human activities were higher than that without human activities. The suitable habitat of Isoetes L. simulated by GARP was much wider than by MaxEnt. By comparison, MaxEnt had more accurate prediction results. Furthermore, the MaxEnt model results showed that, the highly suitable habitats were mainly distributed in western Sichuan, central and northern Yunnan, eastern Tibet, central and eastern Hunan, most of Zhejiang, western Guizhou, southern Anhui and eastern Hebei, with a total area of 55.45 × 104 km2. Under the influence of human activities, the area of highly, moderately and poorly suitable habitats decreased by 61.14%, 44.28% and 56.72%, respectively. Protection gap areas of Isoetes L. were mainly located in western Sichuan, northern Yunnan, western Guizhou, eastern Tibet, central and eastern Hunan and most of Zhejiang. Precipitation of warmest quarter, human footprint index, min temperature of coldest month, precipitation seasonality, elevation and mean UV-B of highest month were the main variables influencing the distribution of Isoetes L. Our results provide a favorable basis for the effective conservation of wild resources of Isoetes L. in China.

Liziping National Nature Reserve in the Xiaoxiangling Mountain, Sichuan Province, is a core distribution area and critical habitat of the giant pandas (Ailuropoda melanoleuca). Determining a suitable habitat distribution pattern within the protected area is essential to formulate a scientific and reasonable giant pandas’ conservation and management plan. Habitat suitability, influencing factors, and habitat selection of giant pandas were surveyed from May 2016 to July 2017 in Liziping National Nature Reserve. These data were assessed using the maximum entropy model (MaxEnt) and environmental factor evaluation analysis. Results show that the habitat suitable for the giant pandas is mainly concentrated in the east of the reserve, with a coverage of about 127.19 km2 (26.58% of the total area). Meanwhile, the model results show that factors including road interference, average annual temperature, altitude, and slope gradient greatly influence giant pandas' distribution. In this region, habitat selection results show wild giant pandas prefer areas far from anthropogenic interference with an average annual temperature of 10–11 ℃, gentle slope, and high altitude. The findings provide a reference for scientists to formulate practical habitat conservation and management measures for giant pandas in the reserve.

Climate change has been regarded as one of the major threats to endangered species, and offers a wide variety of challenges to current conservation strategies. Assessing species’ vulnerability to climate change is a critical initial step for improving in-situ conservation planning. In this study, we used MaxEnt to predict the impacts of climate change on habitat suitability for wild camel (Camelus ferus) in the Kumtag Desert both during the current period and projected into the 2050 s. Our results showed that (i) suitable habitat for wild camel was predicted to decrease by 43.81% by the 2050 s; (ii) currently established nature reserves protected 57.86% of currently suitable habitat; (iii) 44.15% of currently suitable habitat was predicted to be vulnerable to future climate change, with a minor increase in newly suitable habitat by the 2050 s; (iv) climate refuge areas amounted to 21,601 km2 and were mainly located in the core area of the desert. Given these results, we propose conservation implications to mitigate the impacts of climate change on wild camel, including intergrating the suitable habitat into the planning of a proposed national park, constructing habitat corridors, restoring water sources, and implementing long-term monitoring.

Habitat loss and fragmentation are serious threats to biodiversity worldwide. In order to promote animal movement and gene flow between habitat islands, it is important to identify and evaluate the ecological network of species. In Tieli Forestry Bureau (TFB) in Northeast China, we simulated and evaluated the ecological network of roe deer, aiming to provide theoretical support to population conservation. By using three sources of roe deer occurrence data and 15 environmental variables, we simulated the suitability of habitats using the Maximum Entropy Model (MaxEnt). Then, the corridor design model Linkage Mapper was used to identify and evaluate the linkages between habitat cores which are defined by the home range size of roe deer. The results showed that, of the terrain, land cover, vegetation, and anthropogenic interference factors, the anthropogenic interference factors played the most important and complex role in roe deer habitat selection, creating large-area suitable habitats by farming. Two innovative variables of farmland-forest edge length/patch perimeter (FFE:PP) and viewshed introduced in simulation contributed 8.5% and 2.3%, respectively. Surrounded by the unsuitable habitats, the suitable habitats mainly distributed along both sides of the river, covering 41.8% of the total area of TFB. The ecological network of roe deer was composed of 11 habitat cores and 17 linkages. Three linkages connecting the key habitat cores had low quality and linkage suitability ratios, which were probably due to barrier effect of the HeHa expressway intersecting with the linkages. Our study suggests the priority areas for protecting roe deer and the key locations where the wildlife road-crossing structures or animal guidance measures are needed.

Changes in future climate will have an important impact on biodiversity. Taiwania cryptomerioides has important scientific value for the study of paleogeography, paleoclimate and paleobotany. Based on the environmental data and future scenarios provided by previous studies, the present and future suitable habitat for Taiwania cryptomerioides was modeled, and the significance of environmental factors that shape its distribution were evaluated in this study. Furthermore, a maximum entropy model (MaxEnt) and geographical information system (ArcGIS) were used to identify suitable regions under climate change scenarios in China. The 112 occurrence records and nine environmental factors were further analyzed in this work. Our results show that Taiwania cryptomerioides has a suitable habitat of 211.21 × 104 km2 across most of northeast China. Moreover, the altitude, annual mean temperature, precipitation of the driest month and precipitation of the wettest quarter were identified as the essential factors shaping habitat availability for Taiwania cryptomerioides. Furthermore, the area under the curve (AUC) of the train was 0.944, placing the model in the “excellent” category. As predicted by concentrations of four greenhouse gases from increasing emissions, ranges of species may decrease as global warming intensifies. Overall, the range shift to higher latitudes would gradually become significant. Our research offers suggestions for conservation both in theory and in application, as well as long-term management strategies for the species.

To mitigate the ongoing biodiversity crisis in Tropical Asia, caused by extensive deforestation and wildlife poaching, we will need to take more strategic approaches towards identifying and prioritizing meaningful conservation interventions. This, however, can prove difficult for data-limited species. Focusing on the little-studied mainland clouded leopard (Neofelis nebulosa), a potential umbrella species in the region, we demonstrate an accessible, flexible, and scalable approach applicable to any species. First, we model the species’ range-wide local extirpation threat using a Bayesian Belief Network, taking into account the distribution of remaining suitable habitat and major anthropogenic threats (habitat loss and poaching). We then identify remaining habitat strongholds (defined as large contiguous areas of high quality habitat where the species could survive over the mid-to-long term) and grouped them into stronghold complexes, which we categorized based on local extirpation threat and recent camera-trap survey status. Our results show a 34% decline in the range-wide area categorized as a stronghold due to forest cover changes between 2000 and 2018, with 80% of remaining strongholds identified as having a high or very high average threat of local extirpation. Based on published records, only 60% of remaining strongholds had at least one site surveyed by camera-traps in the last 10 years, highlighting an important knowledge gap concerning the species’ current distribution and population status. Combined, the results of our survey review and threat analysis suggest the species is likely extirpated from all of Vietnam, most of China, and large parts of Cambodia and Laos. Finally, we synthesize our findings, highlight tangible conservation needs, and propose actions for each stronghold complex based on the area’s specific threats, protection level, and survey status, paving the way for the detailed local investigations needed to implement meaningful interventions on the ground.

Global climate change could pose an additional threat to the already vulnerable Gentiana macrophylla. To reduce this emerging climate-related threat, we applied ArcGIS and the maximum entropy method (MaxEnt) to analyse the consequences of climate change on the distribution of G. macrophylla and the vulnerability of this species in China. The modelling results indicate the following: (1) the suitable range of G. macrophylla in China is mainly located in the Loess Plateau hinterland, including the provinces of Shaanxi, Gansu, Shanxi, Ningxia, Hebei and Inner Mongolia, under the current climate conditions; (2) the unsuitable habitats for G. macrophylla in China would increase by 11.92% under the moderate greenhouse gas emissions/climate scenario (RCP4.5) by the 2050s, while significant losses of suitable habitat are predicted to occur; (3) the current suitable habitat mainly located in the Loess Plateau, Great Xingan Mountains, Changbai Mountains and Hengduan Mountains (with a total area of 135.09×104 km2) is predicted to be vulnerable. Climate change will further accelerate the speed of the fragmentation of the vast majority of G. macrophylla suitable habitat, threatening the survival and reproduction of this species in this region. Therefore, some proactive conservation measures should be undertaken to mitigate the adverse effects of climate change. Our findings can be used to provide background information related to the long-term conservation of G. macrophylla.