Prediction of the potential distribution pattern of the great gerbil (Rhombomys opimus) under climate change based on ensemble modelling

Risk zoning of Gynaephora alpherakii (Lepidoptera: Lymantriidae) on the Qinghai-Tibetan Plateau

Gynaephora alpherakii (Grum-Grschimailo) (Lepidoptera: Lymantriidae) is a major pest in alpine meadow areas in the Qinghai-Tibetan Plateau (QTP) and causes severe losses in the local livestock production industry. Assessing areas at high risk for G. alpherakii infestation is critical for the effective management of this pest. In this study, an ensemble distribution model was used to analyze areas suitable for G. alpherakii on the QTP. Risk zoning was performed based on the vegetation and environmental conditions in areas with high-occurrence points, and differences between high-occurrence points and other occurrence points were compared. The results revealed that the suitable areas for G. alpherakii on the QTP amounted to 28.27 × 104 hm2, accounting for 10.94% of the total area of the QTP; the area of high-risk was 19.07 × 104 hm2, and these areas were located mainly in the eastern part of the QTP. Qinghai Province had the highest risk, accounting for 77% of the total area identified as high-risk. In terms of habitat, G. alpherakii preferred alpine Kobresia meadows, which have abundant sunshine, loose soil, and scarce precipitation. This study supports efforts to manage G. alpherakii outbreaks and contributes to the ecological protection of the QTP.

Comparative Study of Potential Habitats for Two Endemic Grassland Caterpillars on the Qinghai-Tibet Plateau Based on BIOMOD2 and Land Use Data

This study has systematically investigated and compared the geographical distribution patterns and population density of G. menyuanensis (Gm) and G. qinghaiensis (Gq), which are endemic to the QTP region and inflict severe damage. Using a method combining the BIOMOD2 integration model (incorporating nine ecological niche models) and current species distribution data, this study has compared changes in potential habitats and distribution centers of these two species during ancient, present, and future climate periods and conducted a correlation test on the prediction results with land use types. The study results indicate that there are differences in geographical distribution patterns, distribution elevations, and population density of these two species. Compared with single models, the integration model exhibits prominent accuracy and stability with higher KAPPA, TSS, and AUC values. The distribution of suitable habitats for these two species is significantly affected by climatic temperature and precipitation. There is a significant difference between the potential habitats of these two species. Gm and Gq are distributed in the northeastern boundary area and the central and eastern areas of the QTP, respectively. The areas of their suitable habitats are significantly and positively correlated with the area of grassland among all land use types of QTP, with no correlations with the areas of other land use types of QTP. The potential habitats of both species during the paleoclimate period were located in the eastern and southeastern boundary areas of the QTP. During the paleoclimate period, their potential habitats expanded towards the Hengduan Mountains (low-latitude regions) in the south compared with their current suitable habitats. With the subsequent temperature rising, their distribution centers shifted towards the northeast (high-latitude) regions, which could validate the hypothesis that the Hengduan Mountains were refuges for these species during the glacial period. In the future, there will be more potential suitable habitats for these two species in the QTP. This study elucidates the ecological factors affecting the current distribution of these grass caterpillars, provides an important reference for designating the prevention and control areas for Gm and Gq, and helps protect the alpine meadow ecosystem in the region.

Modeling a hot, dry future: Substantial range reductions in suitable environment projected under climate change for a semiarid riparian predator guild

An understanding of species-environmental relationships is invaluable for effective conservation and management under anthropogenic climate change, especially for biodiversity hotspots such as riparian habitats. Species distribution models (SDMs) assess present species-environmental relationships which can project potential suitable environments through space and time. An understanding of environmental factors associated with distributions can guide conservation management strategies under a changing climate. We generated 260 ensemble SDMs for five species of Thamnophis gartersnakes (n = 347)-an important riparian predator guild-in a semiarid and biogeographically diverse region under impact from climate change (Arizona, United States). We modeled present species-environmental relationships and projected changes to suitable environment under 12 future climate scenarios per species, including the most and least optimistic greenhouse gas emission pathways, through 2100. We found that Thamnophis likely advanced northward since the turn of the 20th century and overwinter temperature and seasonal precipitation best explained present distributions. Future ranges of suitable environment for Thamnophis are projected to decrease by ca. -37.1% on average. We found that species already threatened with extinction or those with warm trailing-edge populations likely face the greatest loss of suitable environment, including near or complete loss of suitable environment. Future climate scenarios suggest an upward advance of suitable environment around montane areas for some low to mid-elevation species, which may create pressures to ascend. The most suitable environmental areas projected here can be used to identify potential safe zones to prioritize conservation refuges, including applicable critical habitat designations. By bounding the climate pathway extremes to, we reduce SDM uncertainties and provide valuable information to help conservation practitioners mitigate climate-induced threats to species. Implementing informed conservation actions is paramount for sustaining biodiversity in important aridland riparian systems as the climate warms and dries.

Impact of Climate Change on the Distribution of Three Rare Salamanders (Liua shihi, Pseudohynobius jinfo, and Tylototriton wenxianensis) in Chongqing, China, and Their Conservation Implications

The Wushan Salamander (Liua shihi), Jinfo Salamander (Pseudohynobius jinfo), and Wenxian Knobby Salamander (Tylototriton wenxianensis) are rare national Class II protected wild animals in China. We performed MaxEnt modeling to predict and analyze the potential distribution and trends of these species in Chongqing under current and future climate conditions. Species distribution data were primarily obtained from field surveys, supplemented by museum collections and the existing literature. These efforts yielded 636 records, including 43 for P. jinfo, 23 for T. wenxianensis, and 570 for L. shihi. Duplicate records within the same 100 m × 100 m grid cell were removed using ENMTools, resulting in 10, 12, and 58 valid distribution points for P. jinfo, T. wenxianensis, and L. shihi, respectively. The optimization of feature class parameters (FC) and the regularization multiplier (RM) were applied using R package "ENMeval 2.0" to establish the optimal model with MaxEnt. The refined models were applied to simulate the suitable distribution areas for the three species. The results indicate that the current suitable habitat area for L. shihi accounted for 9.72% of the whole region of the Chongqing municipality. It is projected that, by 2050, the proportion of suitable habitat will increase to 12.54% but will decrease to 11.98% by 2070 and further decline to 8.80% by 2090. The current suitable habitat area for P. jinfo accounted for 1.08% of the whole region of the Chongqing municipality, which is expected to decrease to 0.31%% by 2050, 0.20% by 2070, and 0.07% by 2090. The current suitable habitat area for T. wenxianensis accounted for 0.81% of the whole region of the Chongqing municipality, which is anticipated to decrease to 0.37% by 2050, 0.21% by 2070, and 0.06% by 2090. Human disturbance, climate variables, and habitat characteristics are the primary factors influencing the distribution of three salamander species in Chongqing. The proximity to roads significantly impacts L. shihi, while climate conditions mainly affect P. jinfo, and the distance to water sources is crucial for T. wenxianensis. The following suggestions were made based on key variables identified for each species: (1) For L. shihi, it is imperative to minimize human disturbances and preserve areas without roads and the existing vegetation within nature reserves to ensure their continued existence. (2) For P. jinfo, the conservation of high-altitude habitats is of utmost importance, along with the reduction in disturbances caused by roads to maintain the species' ecological niche. (3) For T. wenxianensis, the protection of aquatic habitats is crucial. Additionally, efforts to mitigate the impacts of road construction and enhance public awareness are essential for the preservation of this species and the connectivity of its habitats.

Would future climate warming cause zoonotic diseases to spread over long distances?

Dipus sagitta is a major rodent found in arid environments and desert areas. They feed on plant seeds, young branches and some small insects, and have hibernating habits. Peak Dipus sagitta numbers impact the construction of the plant community in the environment, but also have a human impact as these rodents carry a variety of parasitic fleas capable of spreading serious diseases to humans. Based on 216 present distribution records of Dipus sagitta and seven environmental variables, this article simulates the potential distribution of Dipus sagitta during the Last Glacial Maximum, the mid-Holocene, the present and the future (2070s, RCP4.5, RCP8.5). This study also analyzes the geographic changes of the population distribution and evaluates the importance of climate factors by integrating contribution rate, replacement importance value and the jackknife test using the MaxEnt model. In this study, we opted to assess the predictive capabilities of our model using the receiver operating characteristic (ROC) and partial receiver operating characteristic (pROC) metrics. The findings indicate that the AUC value exceeds 0.9 and the AUC ratio is greater than 1, indicating superior predictive performance by the model. The results showed that the main climatic factors affecting the distribution of the three-toed jerboa were precipitation in the coldest quarter, temperature seasonality (standard deviation), and mean annual temperature. Under the two warming scenarios of the mid-Holocene and the future, there were differences in the changes in the distribution area of the three-toed jerboa. During the mid-Holocene, the suitable distribution area of the three-toed jerboa expanded, with a 93.91% increase in the rate of change compared to the Last Glacial Maximum. The size of the three-toed jerboa's habitat decreases under both future climate scenarios. Compared to the current period, under the RCP4.5 emission scenario, the change rate is -2.96%, and under the RCP8.5 emission scenario, the change rate is -7.41%. This indicates a trend of contraction in the south and expansion in the north. It is important to assess changes in the geographic population of Dipus sagitta due to climate change to formulate population control strategies of these harmful rodents and to prevent and control the long-distance transmission of zoonotic diseases.

Predicting current and future potential distributions of the greater bandicoot rat (Bandicota indica) under climate change conditions

BACKGROUND

Rodent infestation is a global problem. Rodents cause huge harm to agriculture, forestry, and animal husbandry around the world and spread various zoonoses. In this study, we simulated the potentially suitable habitats of Bandicota indica and predicted the impact of future climate change on its distribution under different socio-economic pathway scenarios of CMIP6 using a parameter-optimized maximum entropy (MaxEnt) model.

RESULTS

The average area under the receiver operating characteristic curve (AUC) value (0.958 ± 0.006) after ten repetitions proved the high accuracy of the MaxEnt model. Model results show that the annual mean temperature (≥ 15.93 °C), isothermality (28.52-80.49%), annual precipitation (780.13-3863.13 mm), precipitation of the warmest quarter (≥ 204.37 mm), and nighttime light (≥ 3.38) were important limiting environmental variables for the distribution of B. indica. Under current climate conditions, the projected potential suitable habitats for B. indica were mainly in India, China, Myanmar, Thailand, and Vietnam, which cover a total area of 301.70 × 104  km2 . The potentially suitable areas of B. indica in the world will expand under different future climate change scenarios by 1.61-17.65%.

CONCLUSIONS

These results validate the potential influence of climate change on the distribution of B. indica and aid in understanding the linkages between B. indica niches and the relevant environment, thereby identifying urgent management areas where interventions may be necessary to develop feasible early warning and prevention strategies to protect against this rodent's spread. © 2023 Society of Chemical Industry.

Himalayan Marmot (Marmota himalayana) Redistribution to High Latitudes under Climate Change

Climate warming and human activities impact the expansion and contraction of species distribution. The Himalayan marmot (Marmota himalayana) is a unique mammal and an ecosystem engineer in the Qinghai-Tibet Plateau (QTP). This pest aggravates grassland degradation and is a carrier and transmitter of plagues. Therefore, exploring the future distribution of Himalayan marmots based on climate change and human activities is crucial for ecosystem management, biodiversity conservation, and public health safety. Here, a maximum entropy model was explored to forecast changes in the distribution and centroid migration of the Himalayan marmot in the 2050s and 2070s. The results implied that the human footprint index (72.80%) and altitude (16.40%) were the crucial environmental factors affecting the potential distribution of Himalayan marmots, with moderately covered grassland being the preferred habitat of the Himalayan marmot. Over the next 30-50 years, the area of suitable habitat for the Himalayan marmot will increase slightly and the distribution center will shift towards higher latitudes in the northeastern part of the plateau. These results demonstrate the influence of climate change on Himalayan marmots and provide a theoretical reference for ecological management and plague monitoring.

Time to Step Up Conservation: Climate Change Will Further Reduce the Suitable Habitats for the Vulnerable Species Marbled Polecat (Vormela peregusna)

Habitat loss and human threats are putting the marbled polecat (Vormela peregusna) on the brink of extinction. Numerous recent studies have found that climate change will further deteriorate the living environment of endangered species, leading to their eventual extinction. In this study, we used the results of infrared camera surveys in China and worldwide distribution data to construct an ensemble model consisting of 10 commonly used ecological niche models to specify potential suitable habitat areas for V. peregusna under current conditions with similar environments to the sighting record sites. Changes in the suitable habitat for V. peregusna under future climate change scenarios were simulated using mid-century (2050s) and the end of the century (2090s) climate scenarios provided by the Coupled Model Intercomparison Project Phase 6 (CMIP6). We evaluated the accuracy of the model to obtain the environmental probability values (cutoff) of the V. peregusna distribution, the current distribution of suitable habitats, and future changes in moderately and highly suitable habitat areas. The results showed that the general linear model (GLM) was the best single model for predicting suitable habitats for V. peregusna, and the kappa coefficient, area under the curve (AUC), and true skill statistic (TSS) of the ensemble model all exceeded 0.9, reflecting greater accuracy and stability than single models. Under the current conditions, the area of suitable habitat for V. peregusna reached 3935.92 × 10⁴ km², suggesting a wide distribution range. In the future, climate change is predicted to severely affect the distribution of V. peregusna and substantially reduce the area of suitable habitats for the species, with 11.91 to 33.55% of moderately and highly suitable habitat areas no longer suitable for the survival of V. peregusna. This shift poses an extremely serious challenge to the conservation of this species. We suggest that attention be given to this problem in Europe, especially the countries surrounding the Black Sea, Asia, China, and Mongolia, and that measures be taken, such as regular monitoring and designating protected areas for the conservation of vulnerable animals.

Predicting current and future high-risk areas for vectors and reservoirs of cutaneous leishmaniasis in Iran

Climate change will affect the distribution of species in the future. To determine the vulnerable areas relating to CL in Iran, we applied two models, MaxEnt and RF, for the projection of the future distribution of the main vectors and reservoirs of CL. The results of the models were compared in terms of performance, species distribution maps, and the gain, loss, and stable areas. The models provided a reasonable estimate of species distribution. The results showed that the Northern and Southern counties of Iran, which currently do not have a high incidence of CL may witness new foci in the future. The Western, and Southwestern regions of the Country, which currently have high habitat suitability for the presence of some vectors and reservoirs, will probably significantly decrease in the future. Furthermore, the most stable areas are for T. indica and M. hurrianae in the future. So that, this species may remain a major reservoir in areas that are present under current conditions. With more local studies in the field of identifying vulnerable areas to CL, it can be suggested that the national CL control guidelines should be revised to include a section as a climate change adaptation plan.

Priority conservation area of Larix gmelinii under climate change: application of an ensemble modeling

Larix gmelinii (Rupr.) Kuzen is a major tree species with high economic and ecological value in the Greater Khingan Mountains coniferous forest of Northeast China. Reconstructing the priority Conservation Area of Larix gmelinii under Climate could provide a scientific basis for its germplasm conservation and management. The present study used ensemble and Marxan model simulations to predict species distribution areas and delineate priority conservation areas for Larix gmelinii in relation to productivity characteristics, understory plant diversity characteristics, and climate change impacts. The study revealed that the Greater Khingan Mountains and the Xiaoxing'an Mountains, with an area of approximately 300 974.2 km², were the most suitable for L. gmelinii. The stand productivity of L. gmelinii in the most suitable area was significantly higher than that in the less suitable and marginally suitable areas, but understory plant diversity was not dominant. The increase in temperature under future climate change scenarios will reduce the potential distribution and area under L. gmelinii; the species will migrate to higher latitudes of the Greater Khingan Mountains, while the degree of niche migration will gradually increase. Under the 2090s-SSP585 climate scenario, the most suitable area for L. gmelinii will completely disappear, and the climate model niche will be completely separated. Therefore, the protected area of L. gmelinii was demarcated with a target of the productivity characteristics, understory plant diversity characteristics and climate change sensitive area, and the current key protected area was 8.38 × 10⁴ km². Overall, the study's findings will lay a foundation for the protection and rational development and utilization of cold temperate coniferous forests dominated by L. gmelinii in the northern forested region of the Greater Khingan Mountains.

Ecological niche modeling based on ensemble algorithms to predicting current and future potential distribution of African swine fever virus in China

African swine fever (ASF) is a tick-borne infectious disease initially described in Shenyang province China in 2018 but is now currently present nationwide. ASF has high infectivity and mortality rates, which often results in transportation and trade bans, and high expenses to prevent and control the, hence causing huge economic losses and a huge negative impact on the Chinese pig farming industry. Ecological niche modeling has long been adopted in the epidemiology of infectious diseases, in particular vector-borne diseases. This study aimed to establish an ecological niche model combined with data from ASF incidence rates in China from August 2018 to December 2021 in order to predict areas for African swine fever virus (ASFV) distribution in China. The model was developed in R software using the biomod2 package and ensemble modeling techniques. Environmental and topographic variables included were mean diurnal range (°C), isothermality, mean temperature of wettest quarter (°C), precipitation seasonality (cv), mean precipitation of warmest quarter(mm), mean precipitation of coldest quarter (mm), normalized difference vegetation index, wind speed (m/s), solar radiation (kJ /day), and elevation/altitude (m). Contribution rates of the variables normalized difference vegetation index, mean temperature of wettest quarter, mean precipitation of coldest quarter, and mean precipitation of warmest quarter were, respectively, 47.61%, 28.85%, 10.85%, and 7.27% (according to CA), which accounted for over 80% of contribution rates related to variables. According to model prediction, most of areas revealed as suitable for ASF distribution are located in the southeast coast or central region of China, wherein environmental conditions are suitable for soft ticks’ survival. In contrast, areas unsuitable for ASFV distribution in China are associated with arid climate and poor vegetation, which are less conducive to soft ticks’ survival, hence to ASFV transmission. In addition, prediction spatial suitability for future ASFV distribution suggests narrower areas for ASFV spread. Thus, the ensemble model designed herein could be used to conceive more efficient prevention and control measure against ASF according to different geographical locations in China.