Impacts of climate change and human activities on three Glires pests of the Qinghai-Tibet Plateau.

BACKGROUND: The range of Glires is influenced by human activities and climate change. However, the extent to which human activities and environmental changes have contributed to this relationship remains unclear. We examined alterations in the distribution changes and driving factors of the Himalayan marmot, plateau pika, and plateau zokor on the Qinghai-Tibet Plateau (QTP) using the maximum entropy (MaxEnt) model and a geographical detector (Geodetector). RESULTS: The MaxEnt model showed that the contribution rates of the human footprint index (HFI) to the distribution patterns of the three types of Glires were 46.70%, 58.70%, and 59.50%, respectively. The Geodetector results showed that the distribution pattern of the Himalayan marmot on the QTP was influenced by altitude and the normalized difference vegetation index (NDVI). The distribution patterns for plateau pikas and plateau zokors were driven by HFI and NDVI. Climate has played a substantial role in shaping suitable habitats for these three Glires on the QTP. Their suitable area is expected to decrease over the next 30-50 years, along with their niche breadth and overlap. Future suitable habitats for the three Glires tended to shift toward higher latitudes on the QTP. CONCLUSION: These findings underscore the impacts of environmental and human factors on the distribution of the three Glires on the QTP. They have enhanced our understanding of the intricate relationships between Glires niches and environments. This can aid in identifying necessary interventions for developing effective early warning systems and prevention strategies to mitigate Glires infestations and plague epidemics on the QTP. © 2024 Society of Chemical Industry.

Reconstructed Global Invasion and Spatio-Temporal Distribution Pattern Dynamics of Sorghum halepense under Climate and Land-Use Change.

Sorghum halepense competes with crops and grass species in cropland, grassland, and urban environments, increasing invasion risk. However, the invasive historical dynamics and distribution patterns of S. halepense associated with current and future climate change and land-use change (LUC) remain unknown. We first analyzed the invasive historical dynamics of S. halepense to explore its invasion status and expansion trends. We then used a species distribution model to examine how future climate change and LUC will facilitate the invasion of S. halepense. We reconstructed the countries that have historically been invaded by S. halepense based on databases with detailed records of countries and occurrences. We ran biomod2 based on climate data and land-use data at 5' resolution, assessing the significance of environmental variables and LUC. Sorghum halepense was widely distributed worldwide through grain trade and forage introduction, except in Africa. Europe and North America provided most potential global suitable habitats (PGSHs) for S. halepense in cropland, grassland, and urban environments, representing 48.69%, 20.79%, and 84.82%, respectively. The future PGSHs of S. halepense increased continuously in the Northern Hemisphere, transferring to higher latitudes. Environmental variables were more significant than LUC in predicting the PGSHs of S. halepense. Future PGSHs of S. halepense are expected to increase, exacerbating the invasion risk through agricultural LUC. These results provide a basis for the early warning and prevention of S. halepense worldwide.

Environmental factors influencing potential distribution of Schisandra sphenanthera and its accumulation of medicinal components.

Schisandrae Sphenantherae Fructus (SSF), the dry ripe fruit of Schisandra sphenanthera Rehd. et Wils., is a traditional Chinese medicine with wide application potential. The quality of SSF indicated by the composition and contents of secondary metabolites is closely related to environmental factors, such as regional climate and soil conditions. The aims of this study were to predict the distribution patterns of potentially suitable areas for S. sphenanthera in China and pinpoint the major environmental factors influencing its accumulation of medicinal components. An optimized maximum entropy model was developed and applied under current and future climate scenarios (SSP1-RCP2.6, SSP3-RCP7, and SSP5-RCP8.5). Results show that the total suitable areas for S. sphenanthera (179.58×104 km2) cover 18.71% of China's territory under the current climatic conditions (1981-2010). Poorly, moderately, and highly suitable areas are 119.00×104 km2, 49.61×104 km2, and 10.98×104 km2, respectively. The potentially suitable areas for S. sphenanthera are predicted to shrink and shift westward under the future climatic conditions (2041-2070 and 2071-2100). The areas of low climate impact are located in southern Shaanxi, northwestern Guizhou, southeastern Chongqing, and western Hubei Provinces (or Municipality), which exhibit stable and high suitability under different climate scenarios. The contents of volatile oils, lignans, and polysaccharides in SSF are correlated with various environmental factors. The accumulation of major secondary metabolites is primarily influenced by temperature variation, seasonal precipitation, and annual precipitation. This study depicts the potential distribution of S. sphenanthera in China and its spatial change in the future. Our findings decipher the influence of habitat environment on the geographical distribution and medicinal quality of S. sphenanthera, which could have great implications for natural resource conservation and artificial cultivation.

Changes in the Suitable Habitats of Three Endemic Fishes to Climate Change in Tibet.

As one of the most sensitive regions to global climate change, Tibet is subject to remarkable changes in biota over the past decades, including endemic fish species. However, no study has attempted to predict the changes in the distribution of Tibetan fishes, leaving a great blank for aquatic conservation in Tibet. Based on the Maximum Entropy model (MaxEnt), this study predicted the changes in the suitable habitats of three endemic fish species, including two species mainly inhabiting the rivers (Glyptosternon maculatum, Oxygymnocypris stewartii) and one species mainly inhabiting lakes (Gymnocypris selincuoensis) in Tibet under two representative concentration pathways (RCP2.6 and RCP8.5) under two future scenarios (2050 and 2090), and explored the impact of the barrier effects of hydropower projects on the suitable habitats of fish. The results showed that under the four scenarios, the net change in the suitable habitats of the G. maculatum was negative (-2.0--18.8%), while the suitable habitats of the O. stewartii and G. selincuoensis would be expanded, with the net change of 60.0-238.3% and 46.4-56.9%, respectively. Under different scenarios, the suitable habitats of the three species had a tendency to migrate to a higher elevation, and the largest expansion in the range of migration was projected to occur under the 2090-RCP8.5 scenario. In addition, due to the impact of the hydropower projects, the ability of G. maculatum to obtain new suitable habitats from climate change would be reduced by 2.0-8.1%, which was less than the loss induced by climate change (5.5-25.1%), while the suitable habitats of O. stewartii would be reduced by 3.0-9.7%, which was more than the impact of climate change (about 1%). The results of this study have guiding significance for the conservation and management of fish resources diversity in the Yarlung Tsangpo River basin and Siling Co basin of Tibet, and also provide a reference for the coordination and scientific planning of hydropower projects in Tibet.

[Applying Biomod2 for modeling of species suitable habitats:a case study of Paeonia lactiflora in China].

Paeonia lactiflora is an important medicinal resource in China. It is of great significance for the protection and cultivation of P. lactiflora resources to find the suitable habitats. The study was based on the information of 98 distribution sites and the data of 20 current environmental factors of wild P. lactiflora in China. According to the correlation and importance of environmental factors, we selected the main environmental factors affecting the potential suitable habitats. Then, BCC-CSM2-MR model was employed to predict the distribution range and center change of potential suitable habitat of wild P. lactiflora in the climate scenarios of SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 during 2021-2100. The ensemble model combined with GBM, GLM, MaxEnt, and RF showed improved prediction accuracy, with TSS=0.85 and AUC=0.95. Among the 20 environmental factors, annual mean temperature, monthly mean diurnal range of temperature, temperature seasonality, mean temperature of the warmest quarter, precipitation of the wettest month, precipitation seasonality, precipitation of the driest quarter, and elevation were the main factors that affected the suitable habitat distribution of P. lactiflora. At present, the potential suitable habitats of wild P. lactiflora is mainly distributed in Inner Mongolia, Heilongjiang, Jilin, Liaoning, Hebei, Beijing, Shaanxi, Shanxi, Shandong, Gansu, Xinjiang, Tibet, and Ningxia, and concentrated in the northeastern Inner Mongolia, central Heilongjiang, and northern Jilin. Under future climate conditions, the highly sui-table area of wild P. lactiflora will shrink, and the potential suitable habitat will mainly be lost to different degrees. However, in the SSP5-8.5 scenario, the low suitable area of wild P. lactiflora will partially increase in the highlands and mountains in western China including Xinjiang, Tibet, and Qinghai during 2061-2100. The distribution center of wild P. lactiflora migrated first to the northeast and then to the southwest. The total suitable habitats were stable and kept in the high-latitude zones. The prediction of the potential geo-graphical distribution of P. lactiflora is of great significance to the habitat protection and standardized cultivation of this plant in the future.

Predicting the potential global distribution of Sapindus mukorossi under climate change based on MaxEnt modelling.

Sapindus mukorossi (S. mukorossi) is an important biological washing material and biomass energy tree species whose peel is rich in saponins, and its kernels have a high oil content. We used the maximum entropy model (MaxEnt) to predict the suitable habitats of S. mukorossi globally, screen the dominant environmental factors affecting its distribution and analyse the changes in its suitable habitats under climate change from prehistory to the future, and the results will provide a scientific basis for germplasm resource collection, protection, introduction and cultivation. Twenty-two environmental variables and global distribution data for S. mukorossi were used to construct the species distribution model, and the receiver operating characteristic (ROC) curve was used to verify the accuracy of the model. The dominant environmental factors were screened through the jackknife method, and then, the geographical information system (ArcGIS) was used to complete the grade of suitable habitat division and area calculation. The results showed that the MaxEnt model had an excellent predictive effect, and the area under the ROC curve (AUC) value was as high as 0.969. The precipitation of the warmest quarter (Bio18), the minimum temperature of the coldest month (Bio6), temperature seasonality (Bio4) and isothermality (Bio3) were the dominant environmental factors that affected the distribution of S. mukorossi. The largest area of the world's suitable habitats occurred during the last interglacial (LIG) (772.69 × 104 km2), and the area decreased sharply (614.46 × 104 km2) during the last glacial maximum (LGM). The area of suitable habitat showed an increasing trend during the Mid-Holocene (MH) and currently, with areas of 631.06 × 104 km2 and 706.82 × 104 km2, respectively. The area of suitable habitats for S. mukorossi globally was 718.35 × 104 km2 (SSP1-2.6), 636.85 × 104 km2 (SSP2-4.5), 657.64 × 104 km2 (SSP3-7.0) and 675.89 × 104 km2 (SSP5-8.5) under the four scenarios of the future climate. The area increased only in the SSP1 scenario. In summary, globally, the suitable area of S. mukorossi tended to migrate to higher latitudes and decrease in area with future climate change.

Applying Biomod2 for modeling of species suitable habitats:a case study of Paeonia lactiflora in China / 中国中药杂志

Paeonia lactiflora is an important medicinal resource in China. It is of great significance for the protection and cultivation of P. lactiflora resources to find the suitable habitats. The study was based on the information of 98 distribution sites and the data of 20 current environmental factors of wild P. lactiflora in China. According to the correlation and importance of environmental factors, we selected the main environmental factors affecting the potential suitable habitats. Then, BCC-CSM2-MR model was employed to predict the distribution range and center change of potential suitable habitat of wild P. lactiflora in the climate scenarios of SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 during 2021-2100. The ensemble model combined with GBM, GLM, MaxEnt, and RF showed improved prediction accuracy, with TSS=0.85 and AUC=0.95. Among the 20 environmental factors, annual mean temperature, monthly mean diurnal range of temperature, temperature seasonality, mean temperature of the warmest quarter, precipitation of the wettest month, precipitation seasonality, precipitation of the driest quarter, and elevation were the main factors that affected the suitable habitat distribution of P. lactiflora. At present, the potential suitable habitats of wild P. lactiflora is mainly distributed in Inner Mongolia, Heilongjiang, Jilin, Liaoning, Hebei, Beijing, Shaanxi, Shanxi, Shandong, Gansu, Xinjiang, Tibet, and Ningxia, and concentrated in the northeastern Inner Mongolia, central Heilongjiang, and northern Jilin. Under future climate conditions, the highly sui-table area of wild P. lactiflora will shrink, and the potential suitable habitat will mainly be lost to different degrees. However, in the SSP5-8.5 scenario, the low suitable area of wild P. lactiflora will partially increase in the highlands and mountains in western China including Xinjiang, Tibet, and Qinghai during 2061-2100. The distribution center of wild P. lactiflora migrated first to the northeast and then to the southwest. The total suitable habitats were stable and kept in the high-latitude zones. The prediction of the potential geo-graphical distribution of P. lactiflora is of great significance to the habitat protection and standardized cultivation of this plant in the future.

Ecological niche modelling to estimate the distribution of Culicoides, potential vectors of bluetongue virus in Senegal.

BACKGROUND: Vector-borne diseases are among the leading causes of morbidity and mortality in humans and animals. In the Afrotropical region, some are transmitted by Culicoides, such as Akabane, bluetongue, epizootic haemorrhagic fever and African horse sickness viruses. Bluetongue virus infection has an enormous impact on ruminant production, due to its high morbidity and mortality rates. METHODS: A nationwide Culicoides trapping campaign was organized at the end of the 2012 rainy season in Senegal. A Maximum Entropy approach (MaxEnt), Boosted Regression Tree (BRT) method and Ecological Niche Factor Analysis (ENFA) were used to develop a predictive spatial model for the distribution of Culicoides, using bio-climatic variables, livestock densities and altitude. RESULTS: The altitude, maximum temperature of the warmest month, precipitation of the warmest quarter, mean temperature of the wettest quarter, temperature seasonality, precipitation of the wettest quarter and livestock density were among the most important factors to predict suitable habitats of Culicoides. Culicoides occurrences were, in most of the cases, positively correlated to precipitation variables and livestock densities; and negatively correlated to the altitude and temperature indices. The Niayes area and the Groundnut basin were the most suitable habitats predicted. CONCLUSION: We present ecological niche models for different Culicoides species, namely C. imicola, C. oxystoma, C. enderleini and C. miombo, potential vectors of bluetongue virus, on a nationwide scale in Senegal. Through our modelling approach, we were able to determine the effect of bioclimatic variables on Culicoides habitats and were able to generate maps for the occurrence of Culicoides species. This information will be helpful in developing risk maps for disease outbreaks.

Identifying and Predicting the Geographical Distribution Patterns of Oncomelania hupensis.

Schistosomiasis is a snail-borne parasitic disease endemic to the tropics and subtropics, whose distribution depends on snail prevalence as determined by climatic and environmental factors. Here, dynamic spatial and temporal patterns of Oncomelania hupensis distributions were quantified using general statistics, global Moran's I, and standard deviation ellipses, with Maxent modeling used to predict the distribution of habitat areas suitable for this snail in Gong'an County, a severely affected region of Jianghan Plain, China, based on annual average temperature, humidity of the climate, soil type, normalized difference vegetation index, land use, ditch density, land surface temperature, and digital elevation model variables; each variable's contribution was tested using the jackknife method. Several key results emerged. First, coverage area of O. hupensis had changed little from 2007 to 2012, with some cities, counties, and districts alternately increasing and decreasing, with ditch and bottomland being the main habitat types. Second, although it showed a weak spatial autocorrelation, changing negligibly, there was a significant east-west gradient in the O. hupensis habitat area. Third, 21.9% of Gong'an County's area was at high risk of snail presence; and ditch density, temperature, elevation, and wetting index contributed most to their occurrence. Our findings and methods provide valuable and timely insight for the control, monitoring, and management of schistosomiasis in China.