The fall armyworm (FAW; Spodoptera frugiperda) has been a persistent threat to global food security due to its strong migratory ability and wide range of host plants. However, most current studies on the suitability distribution of FAW focus on extracting suitable areas in specific regions on an annual basis. Consequently, research on the suitability distribution of FAW at a larger scale and with higher temporal resolution is urgently needed to provide data support for early prevention and control. This study differentiated the historical occurrence records of FAW into annual distribution points and seasonal distribution points. By integrating multi-factor environmental data, including climate, soil, topography, and vegetation, we used MaxEnt to establish annual and monthly models. The annual model extracted the annual suitability distribution of FAW worldwide. Among the nine selected environmental factors, temperature seasonality had the greatest impact on the suitability distribution of FAW, with a single-factor contribution rate of 39.87%. The monthly models analyzed the inter-monthly variations in the global suitability distribution of FAW from January to December. The results indicated that FAW's suitability was highest in July and lowest in March. Under the dominant influence of dynamic environmental factors such as temperature, precipitation, and vegetation index, the expansion and contraction of FAW's suitability distribution corresponded with seasonal changes, exhibiting significant seasonal fluctuations. Our results can provide FAW control personnel with more practical references for formulating preventive strategies in advance, helping to prevent the potentially incalculable damage FAW could cause to crops in invaded areas.

Palsas and peat plateaus occur in various environmental conditions, but their driving environmental factors have not been examined across the Northern Hemisphere with harmonized datasets. Such comparisons can deepen our understanding of these landforms and their response to climate change. We conducted a comparative study between four regions: Hudson Bay, Iceland, Northern Fennoscandia, and Western Siberia by integrating landform observations and geospatial data into a MaxEnt model. Climate and hydrological conditions were identified as primary, yet regionally divergent, factors affecting palsa and peat plateau occurrence. Suitable conditions for these landforms entail specific temperature ranges (500-1500 thawing degree days, 500-4000 freezing degree days), around 300 mm of rainfall, and high soil moisture accumulation potential. Iceland's conditions, in particular, differ due to higher precipitation, a narrower temperature range, and the significance of soil organic carbon content. The annual thermal balance is a critical factor in understanding the occurrence of permafrost peatlands and should be considered when comparing different regions. We conclude that palsas and peat plateaus share similar topographic conditions but occupy varying soil conditions and climatic niches across the Northern Hemisphere. These findings have implications for understanding the climatic sensitivity of permafrost peatlands and identifying potential greenhouse gas emitters.

Simple Summary: The fruit fly, Neoceratitis asiatica Becker, is a frugivorous pest that causes substantial losses in the production of the goji berry, Lycium barbarum L. Identifying its distribution is significant for the monitoring and prevention of the pest. In this study, the MaxEnt model with optimized parameters was employed to predict the current and future (2050s and 2070s) distribution of the pest. We found that temperature and precipitation were the primary environmental factors influencing its distribution. The suitable habitats were predominantly distributed in northwestern China under various climate scenarios, and the projected suitable area in the future generally exhibited a decrease compared with the current projections. Climate warming affects the growth and development of pests, resulting in changes in their geographical distribution, which increases the difficulty in terms of prevention and control. The fruit fly, Neoceratitis asiatica (Becker), is a predominant frugivorous pest that causes serious yield loss in the goji berry, Lycium barbarum L. In recent years, with the expansion of cultivation area, the damage induced by the pest has become increasingly severe, significantly impeding the production of the goji berry. In this study, the potential suitable habitats of N. asiatica under current and future climate scenarios were simulated and predicted using the optimal MaxEnt model, based on the screening distribution records and environmental factors. The changes in the pest distribution under climate change were determined using ArcGIS. The results showed that the best combination of parameters for MaxEnt were feature combination (FC) = LQPT and regularization multiplier (RM) = 1. The dominant environmental factors influencing pest distribution were mean temperature of driest quarter, mean temperature of coldest quarter and precipitation of coldest quarter. Under different climate conditions, the suitable habitats of the pest primarily ranged between 27 degrees-47 degrees N and 73 degrees-115 degrees E. Under current climate conditions, the area of moderately and highly suitable habitats was 42.18 x 10(4) km(2), and mainly distributed in Inner Mongolia (13.68 x 10(4) km(2)), Gansu (9.40 x 10(4) km(2)), Ningxia (5.07 x 10(4) km(2)), Qinghai (4.10 x 10(4) km(2)), and Xinjiang (3.97 x 10(4) km(2)) Provinces. Under future climate scenarios, the suitable area was projected to be lower than the current ones, except SSP245-2050s and SSP370-2070s, and the centroids of suitable habitats were mainly shifted to the northeast, except SSP370-2050s and SSP585-2070s. Our results provide valuable guidance for the monitoring and management of N. asiatica, as well as the selection of pest-free goji berry cultivation sites.

Landslides are widespread geomorphological phenomena with complex mechanisms that have caused extensive causalities and property damage worldwide. The scale and frequency of landslides are presently increasing owing to the warming effects of climate change, which further increases the associated safety risks. In this study, the relationship between historical landslides and environmental variables in the Hanjiang River Basin was determined and an optimized model was used to constrain the relative contribution of variables and best spatial response curve. The optimal MaxEnt model was used to predict the current distribution of landslides and influence of future rainfall changes on the landslide susceptibility. The results indicate that environmental variables in the study area statistically correlate with landslide events over the past 20 years. The MaxEnt model evaluation was applied to landslide hazards in the Hanjiang River Basin based on current climate change scenarios. The results indicate that 25.9% of the study area is classified as a high-risk area. The main environmental variables that affect the distribution of landslides include altitude, slope, normalized difference vegetation index, annual precipitation, distance from rivers, and distance from roads, with a cumulative contribution rate of approximately 90%. The annual rainfall in the Hanjiang River Basin will continue to increase under future climate warming scenarios. Increased rainfall will further increase the extent of high- and medium-risk areas in the basin, especially when following the RCP8.5 climate prediction, which is expected to increase the high-risk area by 10.7% by 2070. Furthermore, high landslide risk areas in the basin will migrate to high-altitude areas in the future, which poses new challenges for the prevention and control of landslide risks. This study demonstrates the usefulness of the MaxEnt model as a tool for landslide susceptibility prediction in the Hanjiang River Basin caused by global warming and yields robust prediction results. This approach therefore provides an important reference for river basin management and disaster reduction and prevention. The study on landslide risks also supports the hypothesis that global climate change will further enhance the frequency and intensity of landslide activity throughout the course of the 21st Century.

Nowadays, in addition to the destruction and fragmentation of the world's habitats, invasive species, and damage caused by them, are one of the most important factors in the destruction of ecosystems. The raccoon (Procyon lotor) is a medium-sized mammal that is placed in mid-levels of the food web and can affect a wide range of species. Considering the damage done to local ecosystems by this invasive species, habitat assessment and determining the factors affecting its habitat suitability would be a key step in managing this species. In this study, using the MaxEnt model and examining 12 environmental parameters (elevation, slope, aspect, geological units, soil type, vegetation, land use, distance to villages, distance to main roads, distance to waterways, average temperature, and rainfall) in the west of Guilan Province, habitat suitability of this alien species was determined, and the most important factors affecting this suitability were investigated. Results showed that the validity value of the model (AUC) was estimated to be 0.852 and parameters such as distance to village (34.5%), elevation (24.2%), and land use (15.9%) are among the most important and effective factors. Also, the results showed that 0.60% of the study area has high suitability, 6.14% moderate, 24.87% low, and 68.36% unsuitable areas for raccoons. The overall result shows that despite the lack of vast favorable areas for this invasive species, an increase in the number and expansion of this species is very likely because of its omnivorous diet, high adaptability to different environments and conditions, as well as extensive niche. All of these factors cause raccoons to spread further in the region and consequently increase the risks and damages to the native ecosystem.

Grasshoppers have profound effects on both grassland ecosystems and livestock production. Despite commendable efforts made by China in grasshopper control, completely eradicating or preventing them still remains a distant prospect. This study aims to analyze the ecological distribution and patterns of grasshopper occurrences in order to provide more accurate monitoring techniques and preventive measures. By considering four types of environmental determinants-meteorology, vegetation, soil, and topography-we systematically identified 18 key influencing factors. These factors encompass various developmental stages of grasshoppers, including variables such as temperature, precipitation, vegetation coverage, vegetation type, soil moisture, soil salinity, soil type, and terrain characteristics. The MaxEnt model is employed in this study to comprehensively capture complex ecological interactions. Omission curves, Receiver Operating Characteristic curves (ROC curves), and the Area Under the Curve (AUC values) demonstrate the robustness and high accuracy of the MaxEnt model. Our research results indicate that meteorological factors are the primary influencing factors for the distribution of grasshoppers, surpassing the effects of vegetation, soil, and terrain. Precipitation and vegetation type emerge as key factors shaping their distributional patterns. Integrating the Sen-MK trend method, our findings identify the epicenter of damage primarily within the central, southern, and northeastern regions, notably affecting locales such as New Barag East County and the Ewenki Autonomous Banner. While their impact in 2012 was particularly severe, temporal trends indicate a decreasing risk of grasshoppers in specific regions, with escalated activity observed in other areas. The empirical insights from this study lay a solid foundation for the development of monitoring and control strategies concerning grasshoppers. Furthermore, the derived theoretical framework serves as a valuable foundation for future research endeavors addressing grasshopper infestations.

Groundwater constitutes a vital resource for public water supply, and thus, it is imperative to recognize the areas of highest potential for increasing availability. The present study employs the MaxEnt model to discern the most favorable areas for locating high -yield wells in Caxias do Sul, Rio Grande do Sul, southern Brazil, where the Serra Geral Aquifer System, a fractured volcanic aquifer, emerges. This aquifer system is characterized by its heterogeneous, discontinuous, and highly anisotropic nature. A dataset comprising 83 wells with high flow rates (>= 10 m3/h) was selected from the municipal registry of deep tubular wells, along with 14 factors that influence groundwater occurrence (specific capacity, transmissivity, altitude, slope, horizontal curvature, vertical curvature, relief dis index, drainage density, distance to drainage, topographic wetness index, distance to lineament, lineament density, precipitation, and soil hydrological group). The model output was a Groundwater Potential Map, which stochastically expresses the probability of obtaining flow rates >= 10 m3/h. The map was validated through cross -validation, resulting in an average accuracy of 65.14%, and by the Receiver Operating Characteristic analysis, resulting in an Area Under the Curve value of 0.911, indicating satisfactory validation. While the MaxEnt model is widely used in ecology to model species distribution, its application in groundwater prediction remains limited, particularly in fractured aquifers associated with volcanic rocks. Apart from optimizing the use of groundwater resources, this study also enhances the understanding of natural phenomena in this type of aquifer.

Bryophytes play important roles in high altitude-latitude ecosystem owing to their extensive geographical coverage. Particularly, the insulating effect prevent permafrost degradation with the rapidly climate warming on the QTP. However, few studies investigated how Bryophytes will react to environmental change at the global scale. In this study, a maximum entropy (Maxent) model was utilized to predict the potential impact of climate change on the distribution of Bryophytes on the QTP. Predictions were based on the under historical (years of 1970-2000) and future climate scenarios (years of 2041-2060 and 2081-2100) using the average climate data of nine global climate models (GCMs) for shared socio-economic pathways (SSP2-4.5) of CMIP6 and other environmental variables. In addition, the key environmental factors affecting the habitat distribution and range shifts of Bryophytes were examined. The results revealed that Bryophytes occupied an area of approximately 179.97 (+/- 0.87) x 10(4 )km(2), 77 (+/- 0.44)% of the total areal extent of QTP in the past. Niche suitability of the Bryophytes was dominated by soil moisture, ultraviolet-B radiation seasonality, temperature seasonality and precipitation of the coldest quarter. Under future climate scenarios, the occupied area increased continuously towards the relatively higher elevation regions. Moreover, permafrost regions would become the buffer zone for the range shifts of niches and covers of Bryophytes on the QTP. This paper will improve our understanding of vegetable potential impact on the permafrost climate feedback.