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Introduction: Mangroves are an important component of coastal ecosystems, and determining the spatial dispersion of prevalent mangrove species and the most suitable land-use source for mangrove growth is of great importance for judicious restoration and effective conservation approaches. Maximum entropy (MaxEnt) models are well suited for this task; however, the default parameterization such models for distribution prediction has limitations and may produce results with low accuracy, requiring elucidation of useful parameter settings. Further, a focus on predicting only the mangrove distribution is insufficient for mangrove restoration, and clarification of suitable habitats is required. Here, we examined the geographical distribution of six mangrove species in Beihai, China (Aricennia marina, Aegiceras corniculatum, Kandelia obovata, Rhizophora stylosa, Bruguiera gymnorrhiza, and Acanthus ilicifolius). Methods: We used the ENMTools tool to select 16 variables from environmental factors, including bioclimate, terrain, sediment type, land-use classification, and sea-surface salinity and temperature. Using the selected variables and mangrove distribution data, a MaxEnt model optimized using the "kuenm" package in R was used to establish a mangrove prediction distribution model for Beihai City. Transition analyses of land-use types within suitable zones further clarified their current and potential functional roles. Results and discussion: The spatial occurrences of A. marina, A. corniculatum, and K. obovata were strongly driven by topographical features, those of R. stylosa and B. gymnorrhiza mostly depended on bioclimatic variables, and that of A. ilicifolius was driven mostly by edaphic conditions, notably the substrate type. The predicted optimal suitable area for mangrove growth in Beihai City was 50.76km2, of which 55.04% are currently officially protected. Unprotected areas suitable for mangrove growth were mainly located in Lianzhou Bay, Tieshangang Bay, Dafengjiang, and Xicun Port. The majority of these regions were derived from land-use transitions from wetlands and aquaculture ponds to forested ecosystems. We suggest that careful development of selected wetland ecosystems and transmutation of aquaculture ponds into forested landscapes are crucial for effective mangrove restoration. Our results will assist in selecting suitable species for mangrove restoration sites and improving mangrove restoration efficiency. [ABSTRACT FROM AUTHOR]

Chestnut, Castanea sativa Miller (Fagales: Fagaceae), is an ecologically and economically important tree species of the forest ecosystem in Southern Europe, North-Western Europe, Western Asia, North Africa, and the Caucasus. The distributional range of chestnut in Europe has been highly modified by humans since ancient times. Biotic and abiotic factors have dramatically changed its distribution. Historic anthropogenic range expansion makes it difficult to identify habitat requirements for natural stands of chestnut. In the Caucasus, natural stands of chestnut survived in glacial forest refugia and landscapes that have been difficult for humans to colonize. To identify the species reliable habitat requirements, we estimated the relationship between climatic variables and 620 occurrence locations of natural chestnut stands from the Caucasus and validated the model using GBIF data from outside the Caucasus. We found that our best model is reasonably accurate and the data from the Caucasus characterize chestnut stands throughout the species range well. [ABSTRACT FROM AUTHOR]

Sardinops melanostictus and Scomber japonicus, as the main associated species in the northwest Pacific Ocean, are of great scientific significance for the management and sustainable use of fishery resources to study their potential habitat distribution and differences in response to environmental changes in this area. The fishery data of S. melanostictus and S. japonicus in the northwest Pacific Ocean from May to November in 2017-2021 were used, combined with sea surface temperature (SST), sea surface salinity (SSS), sea surface height (SSH ), chlorophyll-a (Chl. a), eddy kinetic energy (EKE ), and water temperature at different depths (50, 100, 150, 200 m) to construct a maximum entropy model. According to the response curves of the two to the key environmental factors of each month, the inter-month changes of the key factors on the potential habitats of S. melanostictus and S. japonicus were obtained, and the map of potential habitat distribution from May to November for S. melanostictus and S. japonicus was stimulated. The key factors affecting the change of suitable habitats from June and August to October were SSH, SST, and Chi. a, and their suitable ranges were not much different. The results show that the potential habitat changes of S. melanostictus and S. japonicus are consistent with the actual operating location, and with the increase of months, and they all show a trend of moving first to the northeast and turning back in the southwest direction, and their potential habitat positions overlap widely in each month. The key factors affecting the change of suitable habitat in May, July and November are different. The key factors affecting the change of suitable habitat in May, July and November are different, and the key factors of S. melanostictus are SSH, EKE, SST, the key factors in July are SSH, SST, Chl. a. The key factors in November are EKE, SST, Chl. a, while the key factors of S. japonicus are SSH, EKE, Chl. a in May, and the key factors in July are SST and Chl. a, SSS, while the key factors in November are SSH, SST, Chl. a, and the suitable range of environmental factors varies from month to month. In addition, as the number of months increases, the optimal habitat area of S. japonicus gradually decreases northward, with a minimum area in July and November, while the optimal habitat area of S. melanostictus tends to increase, extending to the area north of 37° north latitude in November. The study showed the changes of SSH, SST and Chi. a have an important impact on the distribution of potential habitats of S. japonicus and S. melanostictus in the northwest Pacific Ocean, and EKE and SSS are the main causes for the difference in the distribution of potential habitats. [ABSTRACT FROM AUTHOR]

Sanjiangyuan National Park (SNP), the first national park in China, is one of the most important biodiversity conservation areas in the Sanjiangyuan National Nature Reserve (SNNR) and even the world. The threatened ungulates play an irreplaceable role in maintaining the ecosystem diversity and stability in SNNR. Here, based on 1434 occurrence records of six ungulates, the maximum entropy model, with two different strategies, was utilized to determine the priority reserves. The results indicated that the priority reserves in SNNR was mainly located in and around SNP, which were mainly distributed in the middle east, middle west, and southwest of SNNR. Six ungulates shared preference for altitude ranging 4000–5000 m, the average annual temperature below −3.0°C, and average annual precipitation ranging 200–400 mm on meadow, steppe, and unused land. The proportion of high and medium suitable areas for ungulates in SNP was higher than that in SNNR. As the SNP is not contiguously spaced in space, and some core wildlife habitats are not included, it is suggested to optimize the functional areas and adjust the boundary range on the basis of the pilot scope of SNP, so as to enhance the integrity and connectivity of each functional area. [ABSTRACT FROM AUTHOR]

Simple Summary: We use maximum entropy (MaxEnt) model, modelling to predict habitat change and inform on potential prevention and control of locust disasters. Our research work is based on three kinds of migratory locusts in a niche overlap and the geographic distribution of preliminary forecast of the locust, the geographical distribution of typical quantitative habitat suitability change, understanding the China–Kazakhstan border areas, the concentrated distribution area of typical locusts and its future expansion area. The scope of the initial assessment of typical locusts confirms the emphases of the locust control between the two countries in the region, to provide a basis for future monitoring work. Large-scale locust monitoring measures are difficult to implement in practice; therefore, this study will provide a regional monitoring focus for locust control efforts. Our study complements this by assessing priority areas for prevention. Climate change, especially climate extremes, can increase the uncertainty of locust outbreaks. The Italian locust (Calliptamus italicus (Linnaeus, 1758)), Asian migratory locust (Locusta migratoria migratoria Linnaeus, 1758), and Siberian locust (Gomphocerus sibiricus (Linnaeus, 1767)) are common pests widely distributed in the semidesert grasslands of Central Asia and its surrounding regions. Predicting the geographic distribution changes and future habitats of locusts in the context of climate warming is essential to effectively prevent large and sudden locust outbreaks. In this study, the optimized maximum entropy (MaxEnt) model, employing a combination of climatic, soil, and topographic factors, was used to predict the potential fitness areas of typical locusts in the 2030s and 2050s, assuming four shared socioeconomic pathways (SSP126, SSP245, SSP370, and SSP585) in the CMIP6 model. Modeling results showed that the mean area under the curve (AUC) and true statistical skill (TSS) of the MaxEnt model reached 0.933 and 0.7651, respectively, indicating that the model exhibited good prediction performance. Our results showed that soil surface sand content, slope, mean precipitation during the hottest season, and precipitation seasonality were the key environmental variables affecting locust distribution in the region. The three locust species were mainly distributed in the upstream region of the Irtysh River, the Alatao Mountain region, the northern slopes of the Tianshan Mountains, around Sayram Lake, the eastern part of the Alakol Lake region, the Tekes River region, the western part of Ulungur Lake, the Ili River, and the upstream region of the Tarim River. According to several climate projections, the area of potential habitat for the three most common locust species will decrease by 3.9 × 104–4.6 × 104 km2 by the 2030s and by 6.4 × 104–10.6 × 104 km2 by the 2050s. As the climate becomes more extreme, the suitable area will shrink, but the highly suitable area will expand; thus, the risk of infestation should be taken seriously. Our study present a timely investigation to add to extensive literature currently appearing regarding the myriad ways climate change may affect species. While this naturally details a limited range of taxa, methods and potential impacts may be more broadly applicable to other locust species. [ABSTRACT FROM AUTHOR]

Panax notoginseng is an important medicinal plant in China, but there are some limitations in the ecological suitability study, such as incomplete investigation of species distribution, single regionalization modeling, and lack of collaborative evaluation of ecological suitability, and quality suitability. In this study, the maximum entropy model was used to analyze the ecological suitability of P. notoginseng under current and future climates. The multi-source chemical information of samples was collected to evaluate the uniformity between quality and ecology. The results showed that the current suitable habitat was mainly in southwest China. In the future climate scenarios, the high suitable habitat will be severely degraded. Modeling based on different regionalization could predict larger suitable habitat areas. The samples in the high suitable habitat had both quality suitability and ecological suitability, and the accumulation of chemical components had different responses to different environmental factors. Two-dimensional correlation spectroscopy combined with deep learning could achieve rapid identification of samples from different suitable habitats. In conclusion, global warming is not conducive to the distribution and spread of P. notoginseng. The high suitable habitat was conducive to the cultivation of high-quality medicinal materials. Actual regionalization modeling had more guiding significance for the selection of suitable habitats in a small area. The multi-regionalization modeling theory proposed in this study could provide a new perspective for the ecological suitability study of similar medicinal plants. The results provided a reference for the introduction and cultivation, and lay the foundation for the scientific and standardized production of high-quality P. notoginseng. [ABSTRACT FROM AUTHOR]

The Indian Golden Gecko Calodactylodes aureus (Beddome 1870) is an endemic reptile species largely confined to the Eastern Ghats, India. To estimate its potential habitat suitability, species distribution modelling (SDM) was carried out based on occurrence data and climatic and topographic datasets. We used Maximum Entropy (MaxEnt) model for predicting potential habitat suitability for C. aureus. The MaxEnt model predicted potential suitable habitat for C. aureus mainly in the northern and southern parts of Eastern Ghats spread across Odisha, Andhra Pradesh and Tamil Nadu states. Majority of the suitable habitat areas identified by MaxEnt are outside the protected areas and experience high anthropogenic pressure. Slope and mean diurnal range in temperature were the strongest predictors of C. aureus habitat suitability in the Eastern Ghats. Our results can be effective tools in exploring new ways of understanding C. aureus ecology and biogeography, and for planning and future surveys, and prioritizing conservation activities. [ABSTRACT FROM AUTHOR]

• Mapping geographical distributions of N. crispa Willd. In its distribution area. • MaxEnt model showed high accuracy in modeling distribution of N. crispa. • Elevation an annual mean temperature are more important variables in distribution of N. crispa. • Climate change would expand the habitat range of N. crispa in the study area. Nepeta crispa Willd. is a very rare medicinal plant that grows in a very limited habitat in western Iran. In recent years, due to climate change, many plants have become endangered, which poses a very serious threat to very rare species such as N. crispa Willd. In the present study, we aimed to model the current and future potential geographical distributions and identify the most relevant environmental factors influencing the distribution of N. crispa Willd. an endemic plant species in west of Iran. The species distribution was modeled with the maximum entropy model by using presence data (160 sampling points) and a total of 15 climatic and environmental variables. To predict possible shifts in the geographical distribution due to climate change, we used the Representative Concentration Pathway (RCP) 2.6 and RCP 8.5 for 2050 and 2070 for two Global Climate Models (GCMs). The jackknifing method was used to evaluate the contribution of the environmental variables to the model. We found that elevation, annual mean temperature, geology and precipitation of the driest quarter were the most important variables in determining the habitat of N. crispa. The species habitat suitability maps and models were efficient in predicting the habitat suitability distribution for N. crispa in the current conditions with an Area Under the ROC Curve (AUC) of 0.983. Our modeling approach also demonstrated that climate change would expand the habitat range of N. crispa in the Alvand mountain areas in Iran towards higher elevation (above 2000 m.a.s.l). Conservation measures should therefore predominantly concentrate on the elevation range between 2000 and 3500 m.a.s.l. Knowledge of current distribution of the N. crispa and predicting its potential future geographical distribution under different climate change scenarios provide useful information for conservation actions in Iran. [ABSTRACT FROM AUTHOR]

The Scops Owl Otus scops (L., 1758) is a species of European concern, which suffered a noticeable decrease in distribution in the last decades, and changes in agricultural practices have been proposed as a major threat for this owl. We studied the habitat preference of the Scops Owl by assessing the habitat occupancy of 401 territories distributed in a large area in northwest Italy, with a special focus on 98 territories located in a high-density area (Monferrato). Habitat characteristics were analyzed with maximum entropy (MAXENT) models that included both vegetational (16 land use categories) and physical features estimated from a Digital Terrain Model (DTM) (altitude, slope, hillshade). In the Monferrato area, a comparison of 2009 landcover was also made with year 1954/55 characteristics obtained from aerial photographs. In the full northwest Italy area, the Scops Owl preferred areas located at middle altitude with intermediate slope. The preferred habitats included riparian areas and pasture-grassland, while woodlands and zones with Robinia pseudoacacia shrublands were avoided. In the Monferrato area, Scops Owl occupancy occurred in sites where the landuse (croplands/vineyard mosaic) had changed little since the mid-1950s. Our study suggests that conservation activity should focus on interventions halting riparian zone transformation and subsidies promoting agricultural practices favouring pastures and grassland. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of our study was to identify major hillslope sediment sources in a partially urbanized coastal watershed supporting salmonid habitat and to evaluate the use of physical and maximum entropy models in predicting sites of greatest concern. Questions include when and where increased runoff from trail and unpaved road surfaces has influenced patterns of landslides and gullies to a greater degree than what would be expected from background processes and controls, such as precipitation intensity, vegetation, soils, and slope characteristics. Materials and methods: San Pedro Creek Watershed, USA, provides habitat for Oncorhynchus mykiss despite 33% of the watershed being urbanized. The watershed drains steep hillslopes with a median slope of 21°, with the steepest slopes on the 578-m North Peak of Montara Mountain. We inventoried hillslope sediment sources based on field surveys and aerial photographic interpretation in 1941, 1955, 1975, 1983, and 1997. We interpreted causative factors using precipitation records, geologic and soil mapping, digital elevation derivatives, land cover, and road/trail network changes and applied a physical landslide susceptibility model (Stability Index Approach to Terrain Stability Hazard Mapping (SINMAP)) for hillslope stability and a maximum entropy model for assessing gully and landslide centroids. Results and discussion: Maps of landslide and gullies reveal an association with land use changes over time. Agricultural land uses led to the development of extensive gullies in parts of the watershed, and some of these continue to contribute significant sediment to the stream system; others were built-over in residential developments. The most significant remaining gullies result from impervious runoff from roads built into steep hillslopes. Although the best single predictor of landslide susceptibility is physically modelled hillslope stability (SINMAP), slope equally contributed to multivariate MAXENT models (area under the receiver operator characteristic curve (AUC) = 0.74 in 1941, 0.65 in 1975, and 0.79 in 1983). Other covariates in the maximum entropy models include plan curvature, trail distance in 1975, geology in 1983 (favoring colluvium), and vegetation. Conclusions: Combining physical hillslope stability with a maximum entropy model appears promising, although overall slope angle also contributed equally. Landslides are episodic and linked to major precipitation/runoff events, such as ENSO events in 1962, 1972, and 1982, but road and trail development from 1955 to 1975 also contributed equally. As by count most gullies relate to earlier agricultural practices, they represent ongoing sediment sources. [ABSTRACT FROM AUTHOR]

The article presents a study which determines measures to mitigate anthropogenic disturbance among wintering Black Grouse and mountain ecosystems. It outlines the method of the study which applies spatial modeling to localize conflict zones and estimate the amount of habitat reduction caused by winter sports and recreation activities. The study found out the effectiveness of spatial modeling to accurately identify zones of potential conflict to help create measures to minimize such risks.

Simple Summary: Spatial distribution of wild boar damage risk is important and can be informative to wildlife habitat management. Hunchun is an important active area of Siberian tiger in China. The wild boar damage has brought barriers to the conservation and management of the Siberian tiger in this region. We predicted the spatial distribution of wild boar damage risk in Hunchun in terms of home range and feeding sites scales, and explored the spatial interaction between tiger habitats and the damage risk of wild boar. The results show the distance to the forest edge is an important factor affecting the wild boar damage, and 38.68% of the high-risk areas are overlapped with tiger habitats in Hunchun. Therefore, precise and differentiated management strategies should be adopted in the management of wild boar population. Hunchun, a typical area suffering wild boar (Sus scrofa) damage, is an important region for the Siberian Tiger (Panthera tigris) in China. By incorporating the maximum entropy model with 22 variables in the home range scale (12 variables) and in the feeding site scale (10 variables), we predicted wild boar damage risks in this area of China and analyzed how spatial factors influence damage risk. Damage risk was found to be high in areas close to the forest edge, areas with a higher forest cover and lower to medium deciduous forest proportion, low road density, and a medium river density and farmland proportion. The proportion of farmland which was identified as being in the high damage risk zone was 23.55%, of which 38.68% was within the habitat area of the Siberian Tiger. Finally, we propose wild boar damage prevention based on different management goals. [ABSTRACT FROM AUTHOR]