MaxEnt Algorithm Research Articles

Effect of study area extent on the potential distribution of Species: A case study with models for Raoiella indica Hirst (Acari: Tenuipalpidae)

Ecological niche models are used to quantify the relationships between known occurrence records of a given species and environmental variables at these locations. Maxent is among the most widely used algorithms for modeling species distribution and has demonstrated better performance compared to other methods. However, the extent of the study area is a critical issue in the development of presence-only species distribution models because it encompasses the region used to extract the background points employed to characterize the environments accessible to the species. Thus, this study evaluated the effect of the extension of the study area on the species distribution modeling with the Maxent algorithm and occurrence data from the invasive species Raoiella indica Hirst (Acari: Tenuipalpidae). The increase in the study area extent inflated most of the threshold-dependent and -independent metrics used to assess model performance. The selection of the study area also affected the predicted suitable areas for the species (its potential distribution). The analysis shows that models developed with smaller study areas resulted in model overfitting and an increase in false-negative predictions. The extent of the area used during model training has a strong influence on the model outputs, with significant consequences for predicting the potential distribution of invasive species and thus for the areas under risk of invasion.

Halyomorpha halys and its egg parasitoids Trissolcus japonicus and T. mitsukurii: the geographic dimension of the interaction

Halyomorpha halys(Stål) (Hemiptera, Pentatomidae) was accidentally introduced to North America and Europe, becoming a key pest of many important crops. In its native range, it is attacked by egg parasitoids, includingTrissolcus japonicus(Ashmead), considered to be the main species, andT. mitsukurii(Ashmead) (Hymenoptera, Scelionidae).Trissolcus japonicuswas detected in North America in 2014 and Europe in 2017, whileT. mitsukuriiwas detected in Australia in the early 20thcentury and in Europe in 2016. Both species now appear established in the new areas. The present study used the MaxEnt algorithm to clarify the geographic dimension of the potential interaction betweenH. halysand these two parasitoid species, and to indicate where the release of one or the other parasitoid species is more likely to be effective. We found that the suitability for the two parasitoids overlaps theH. halysnative range completely. In invaded areas,T. japonicusshowed higher potential habitat suitability at the global scale, compared toT. mitsukurii, and also higher potential suitability at lower latitudes at continental and national scales. These results can substantially improve the effectiveness of biological control againstH. halys, by targeting the releases of parasitoids to the areas where each species is most likely to succeed.

Environmental predictors may change at fine scale habitat suitability modelling: implications for conservation of Kashmir musk deer in three protected areas of Uttarakhand, India.

The Kashmir musk deer (Moschus cupreus, hereafter KMD) is one of the top conservation priority species which is facing population decline due to poaching, habitat loss, and climate change. Therefore, the long-term survival and viability of KMD populations in their natural habitat require conservation and management of suitable habitats. Hence, the present study attempted to assess the suitable habitat of KMD in three protected areas (PAs) of the Western Himalayan region of Uttarakhand using the Maxent modelling algorithm. Our results suggest that Kedarnath wildlife sanctuary (KWLS) possesses the maximum highly suitable habitats (22.55%) of KMD, followed by Govind Pashu Vihar National Park & Sanctuary (GPVNP&S; 8.33%) and Gangotri National Park (GNP; 5%). Among the environmental variables, altitude was the major contributing factor governing the distribution of KMD in KWLS. In contrast, human footprint in GPVNP&S and precipitation in GNP were the major contributing factors governing the distribution of KMD in these respective PAs. The response curve indicated that habitats with less disturbance falling in the altitudinal zone of 2000-4000m were the most suitable habitat range for the distribution of KMD in all three PAs. However, in the case of GNP suitable habitat of KMD increases with an increase in the value of variables bio_13 (precipitation of wettest month). Further, based on our results, we believe that the predictors of suitable habitat change are site specific and cannot be generalized in the entire distribution range of the species. Therefore, the present study will be helpful in making proper habitat management actions at fine scale for the conservation of KMD.

Modeling of present and future potential distribution areas of Thymus praecox opiz. in Turkey according to the Maxent algorithm

Thymus L. genus of the Lamiaceae family, which has a cosmopolitan distribution that includes annual or perennial herbs, rarely shrubs or trees, known for their pleasant smell, has medicinal and aromatic species. Although the ethnobotanical use of individuals of the genus Thymus is quite common, its consumption is often preferred as spice and medicinal tea. In this study, Thymus praecox Opiz. forms the material of the study. In this article, potential present and future distribution areas were modeled in MaxEnt 4.1 to determine the effects of climate change on the distribution areas of T. praecox in Türkiye. In the model, 2041-2060 (~2050) and 2081-2100 (~2090) periods of SSP2 4.5 and SSP5 8.5 scenarios in CanESM5.0.3 (The Canadian Earth System Model version 5) climate change model were used, together with sample points and bioclimatic variables. According to the study outputs, it is estimated that the estimated potential suitable and very suitable distribution areas of T. praecox today are 108411.705 km2 and according to the CanESM5.0.3 model, it will experience losses in very suitable and suitable distribution areas in the future, and very suitable distribution areas cannot be found in the SSP5 8.5 scenario 2081-2100 periods.

Predicting suitable habitat of swamp deer (Rucervus duvaucelii) across the Western Terai Arc Landscape of Nepal

Over the last few years, intensifying human impact and the deterioration of natural habitats have severely restricted the global distribution of large herbivores. Rucervus duvaucelii, commonly recognized as the swamp deer, is a habitat-specialist endemic large herbivore of the Indian Subcontinent. It is classified as vulnerable by the IUCN and listed in CITES Appendix I due to a steep decline in its population, which is primarily due to anthropogenic causes. In Nepal, the last remaining population of this species is confined to limited pocket areas within the western Terai Arc Landscape. We explored potential habitat for swamp deer across this landscape using species distribution modelling through the MaxEnt algorithm by using 173 field-verified presence points alongside six anthropogenic, four topographic, and four vegetation-related variables. Our study found that out of the total study area (9207 km2), only 6% (590 km2) was suitable for swamp deer. Approximately 45% of suitable habitat was incorporated within protected areas, with Shuklaphanta National Park harboring the largest habitat patch. The suitability of habitat was discovered to be positively associated with low-elevation areas, areas near water sources, and areas far from settlements, implying the need to conserve water sources and minimize the extension of anthropogenic pressure for their long-term conservation. Additionally, we suggest the implications of a swamp deer-centric conservation strategy, with an emphasis on increasing connectivity through the corridors and landscape-level population connectivity through trans-boundary conservation initiatives between Nepal and India. Moreover, considering large herbivores' high vulnerability to extinction, similar researche incorporating anthropogenic factors is of the utmost importance to produce vital information on habitat suitability for conserving other regionally and globally endemic, habitat-specialized herbivores.

Ecological niche modelling and population genetic analysis of Indian temperate bamboo Drepanostachyum falcatum in the western Himalayas.

The present study was conducted to understand the key ecological and biological questions of conservation importance in Drepanostachyum falcatum which aimed to map potential distribution in the western Himalayas and decipher spatial genetic structure. Eco-distribution maps were generated through ecological niche modelling using the Maximum Entropy (MaxEnt) algorithm implemented with 228 geocoordinates of species presence and 12 bioclimatic variables. Concomitantly, 26 natural populations in the western Himalayas were genetically analysed using ten genomic sequence-tagged microsatellite (STMS) markers. Model-derived distribution was adequately supported with appropriate statistical measures, such as area under the 'receiver operating characteristics (ROC)' curve (AUC; 0.917 ± 0.034)", Kappa (K; 0.418), normalized mutual information (NMI; 0.673) and true skill statistic (TSS; 0.715). Further, Jackknife test and response curves showed that the precipitation (pre- and post-monsoon) and temperature (average throughout the year and pre-monsoon) maximize the probabilistic distribution of D. falcatum. We recorded a wide and abundant (4096.86 km2) distribution of D. falcatum in the western Himalayas with maximum occurrence at 1500 to 2500m asl. Furthermore, marker analysis exemplified high gene diversity with low genetic differentiation in D. falcatum. Relatively, the populations of Uttarakhand are more genetically diverse than Himachal Pradesh, whereas within the Uttarakhand, the Garhwal region captured a higher allelic diversity than Kumaon. Clustering and structure analysis indicated two major gene pools, where genetic admixing appeared to be controlled by long-distance gene flow, horizontal geographical distance, aspect, and precipitation. Both the species distribution map and population genetic structure derived herein may serve as valuable resources for conservation and management of Himalayan hill bamboos.

Predicting the potential impact of environmental factors on the distribution of Triplochiton scleroxylon (Malvaceae): An economically important tree species in Nigeria

Triplochiton scleroxylon is a lowland rainforest tree species distributed in Central and West Africa, with economic and medicinal importance. Given that its population is threatened by overexploitation for timber, poor seed production, and habitat destruction, it becomes important to project its distribution along environmental gradients to bolster our understanding of its conservation. This study thus examines the combined effect of overexploitation and climate change on its distribution in Nigeria. We used MaxEnt algorithm and spatial analysis module of ArcGIS to model the current and future habitat suitability of T. scleroxylon in Nigeria. We utilized 95 unique occurrence points and eight environmental variables (Bio7, Bio8, Bio9, Bio13, Bio14 & Bio18, elevation, and slope) to understand the response of the species to changing climates during the time periods 1970–2000, and to project species responses to temperature and precipitation in the years 2050 and 2070, using two Global Climate Models. Results indicated that the prediction of the suitable habitat for T. scleroxylon under the model was very reliable (AUC ≥ 0.9; TSS ≥ 0.6). Annual temperature range (Bio7) was the most influential bioclimatic variable for predicting habitat suitability and distribution for the species in Nigeria. Highly suitable habitat has an optimum temperature of 28.5 °C, precipitation ≤600 mm, an elevation of ≤400 m, and a slope of 90°; it is currently estimated at 23.3% of the total land cover, and predicted to reduce to <15% by the year 2050. The methods of SDM have a great potential in understanding species richness, and also provide data for the support of conservation strategies at local scales. Hence, this study advocates for the conservation of the remaining habitats of T. scleroxylon through the implementation of strategic plans, especially in South-western Nigeria where there is a high potential for its regeneration owing to favourable environmental conditions.

Reaching new environments through illegal trade: evidence of a widely traded turtle in Colombia

A major threat to biodiversity is illegal trade, with many unwanted wildlife pets released into exotic environments outside their native distribution. Therefore, many potential invasive species have established in new ecosystems. Ecological niche modeling (ENM) has been used to predict and compare the environmental conditions of natural and exotic population in many groups. We used ENM to compare the climatic niche between natural and exotic areas of Trachemys venusta callirostris, one of the most traded turtles in Colombia. We generated a niche model using the MaxEnt algorithm through the R package kuenm to test several parametrizations and four sets of fresh water environmental predictors. Models were calibrated in the native distribution and projected to non-native zones in Colombia to identify suitable areas for the species. Further, we use a niche similarity test to compare native and exotic environmental space. We found few suitable areas within the projected zone even when using extrapolation; there was a greater suitability in the Magdalena River basin than in the Cauca River basin. Low similarity was detected between the niche comparison of native and exotic areas, suggesting that exotic populations have reached different environmental conditions than the native zone through ilegal trade. Although there was low extrapolation in the exotic area, the models projected ideal conditions in localities with new records for this turtle. The generalist strategies for feeding, thermoregulation, and reproduction in changing conditions may help this T. v. callirostris establish in new ecosystems, and with no current knowledge on dynamics between this exotic species and local fauna, its effects on aquatic communities are unpredictable.

Current and Future Diversity of Thysanoptera Species in the Cereal Areas of the Lakes Region, Turkey

Field surveys were carried out to determine the thrips fauna in cereal production areas of the Lakes Region in Turkey in 2016 and 2017. Thysanoptera specimens were collected with destructive and strike methods in two periods (before and after spike) from each production field during the production season. Thrips specimens were identified based on morphological taxonomic characters. Species distribution maps, species richness, abundance, as well as Shannon–Wiener (H') index, species seasonal dynamic and species sex ratio were calculated to indicate the diversity of Thysanoptera species in the Lakes Region. We also calculated Pearson correlation coefficient to evaluate correlation between Thysanoptera species richness and host plant richness. Species Distribution Modelling, namely MaxEnt algorithm, was used in order to establish the current and future distributional patterns of Thysanoptera species collected in our research area. During the two years of the study, 27,603 specimens of Thysanoptera were collected in production fields of wheat, oat and barley. There were 51 different species from four families. Haplothrips tritici was the most abundant species with 15,284 specimens or 55.371% of all collected. The highest relative abundance within family Thripidae was recorded for Collembolothrips mediterraneus, Chirothrips manicatus, Thrips angusticeps, Thrips herricki and Limothrips cerealium. Considering the altitudinal gradient of the study area, the highest species richness and abundance were found between 950 and 1,050 m.a.s.l. with 40 species and 7,622 specimens recorded. Potential species richness of Thysanoptera revealed an increase in areas that predominantly encompass eastern parts of Burdur province, as well as central north parts of Isparta.

Predicting the suitable habitats of Elwendia persica in the Indian Himalayan Region (IHR)

Rare, Endemic and Threatened (RET) species with naturally small populations are always at high risk of extinction, especially during the climate change process. Climate change phenomena are also identified as a strong driver in the habitat shift of many medicinal and aromatic plants (MAPs). The expected consequences of climate change are so dangerous that some key species can move to extinction. Therefore, the quest for suitable habitats of such species is taken as a challenge by various ecologists and conservationists. This study aims to predict the suitable habitats of Elwendia persica (Boiss.) Pimenov & Kljuykov, a threatened species for current and future climatic scenarios in the Indian Himalayan Region (IHR). The assessments for current and future climatic scenarios are accessed on the optimistic Representative Concentration Pathway 4.5 (RCP 4.5). The MaxENT algorithm has helped to predict the suitable habitat of the species in the study area. The model has predicted 1.12%, 2.37%, and 0.98% of the total study area as highly suitable habitats in current (2000) and future (2050 and 2070) climatic scenarios. South-eastern facing slopes are considered as the most suitable areas for the species in the Indian Himalayan Region. Our results show that suitable habitats of the species may increase upto 2050, and subsequently decrease.

Potential Coffee Distribution in a Central-Western Region of Mexico

Currently, there is a world coffee production crisis which has been attributed, among other factors, to the COVID-19 pandemic that affected the development of productive agricultural activities. In this scenario, Mexico is in a declining situation by showing a reduction in coffee production areas in recent years. Therefore, it is necessary to promote actions that contribute to the recovery of the resource, particularly in the states with agricultural potential. In the present work, the potentially suitable areas for coffee cultivation are identified through the application of tools that allow for characterizing the biophysical conditions that define the current spatial distribution and, from the analysis of these characteristics, generate a Potential Distribution Model (PDM) of the suitable zones for coffee production. The methodology was developed through the application of the Maximum Entropy (MaxEnt) algorithm, starting with the collection and preparation of coffee presence records, followed by a correlation analysis and identification of significant variables, the subsequent execution of the model in various configurations to observe the contribution of each variable through a jackknife test, and finally validation of the model with a random sample selection of 30%, to achieve an AUC of 0.98 and TSS of 0.96. The present model was able to identify and quantify the environmentally suitable zones for coffee production, highlighting the regions with ideal potential for the specie. These results are intended to serve as a basis for the generation of planning strategies aimed at managing, improving, and increasing coffee production areas, as well as being used to establish biological corridors to promote biodiversity, conservation, and alternative economic activities such as tourism and furthermore for future work on the analysis of production scenarios and impacts of climate change. It is concluded that 30% of Nayarit’s territory has ideal conditions for coffee cultivation, especially the region delimited by the municipalities of Tepic and Xalisco, the eastern zone of Compostela, and the southwest of San Blas, which should be considered as a Priority Conservation Area (APC) for coffee cultivation in the state.

Desert Locust (Schistocerca gregaria) Invasion Risk and Vegetation Damage in a Key Upsurge Area

In the recent past, the Horn of Africa witnessed an upsurge in the desert locust (Schistocerca gregaria) invasion. This has raised major concerns over the massive food insecurity, socioeconomic impacts, and livelihood losses caused by these recurring invasions. This study determined the potential vegetation damage due to desert locusts (DLs) and predicted the suitable habitat at high risk of invasion by the DLs using current and future climate change scenarios in Kenya. The normalized difference vegetation index (NDVI) for the period 2018–2020 was computed using multi-date Sentinel-2 imagery in the Google Earth Engine platform. This was performed to assess the vegetation changes that occurred between May and July of the year 2020 when northern Kenya was the hotspot of the DL upsurge. The maximum entropy (MaxEnt) algorithm was used together with 646 DL occurrence records and six bioclimatic variables to predict DL habitat suitability. The current (2020) and two future climatic scenarios for the shared socioeconomic pathways SSP2-4.5 and SSP5-8.5 from the model for interdisciplinary research on climate (MIROC6) were utilized to predict the future potential distribution of DLs for the year 2030 (average for 2021–2040). Using Turkana County as a case, the NDVI analysis indicated the highest vegetation damage between May and July 2020. The MaxEnt model produced an area under the curve (AUC) value of 0.87 and a true skill statistic (TSS) of 0.61, while temperature seasonality (Bio4), mean diurnal range (Bio2), and precipitation of the warmest quarter (Bio18) were the most important bioclimatic variables in predicting the DL invasion suitability. Further analysis demonstrated that currently 27% of the total area in Turkana County is highly suitable for DL invasion, and the habitat coverage is predicted to potentially decrease to 20% in the future using the worst-case climate change scenario (SSP5-8.5). These results have demonstrated the potential of remotely sensed data to pinpoint the magnitude and location of vegetation damage caused by the DLs and the potential future risk of invasion in the region due to the available favorable vegetational and climatic conditions. This study provides a scalable approach as well as baseline information useful for surveillance, development of control programs, and monitoring of DL invasions at local and regional scales.

Predicting the distribution of European Hop Hornbeam: application of MaxEnt algorithm and climatic suitability models

Predicting the distribution of European Hop Hornbeam: application of MaxEnt algorithm and climatic suitability models

Molecular data, ecological niche, and dispersal models reveal a trans-Atlantic shallow-water octopus species

The tropical Octopus insularis is a shallow-water species widely distributed in the western Atlantic. Recent studies of niche models have identified suitable habitats for its settlement also on the east coast of the Atlantic. Considering the pelagic larval period and the high tolerance of this species to environmental variations, this study aimed to analyze the possibility of O. insularis occurrence in the West Atlantic (São Tomé Island) through molecular analyses, dispersion, and niche models. The molecular analyses were performed using fragments of 481 bp of the mitochondrial gene (cox1) from three muscle samples collected in São Tomé Island. The O. insularis long-range connectivity between South America and Western Africa was analyzed using a Lagrangian particle tracking model. Additionally, O. insularis records across its entire known distribution were applied to run the ecological niche model (ENM) using the Maxent algorithm. The Bayesian phylogenetic reconstruction showed that two of the three octopus sequences from São Tomé island (Central-Western Africa) belong to a monophyletic and well-supported O. insularis clade. The third octopus sample revealed a new species related to the clade with the Octopus vulgaris species complex. The dispersal models pointed out that passive particles could potentially reach the seamounts region at Africa coast via oceanic currents (mainly the North Equatorial Countercurrent) from São Pedro and São Paulo archipelago (Central-Western Region of the Atlantic) in a period of ∼30–60 days. This suggests that São Pedro and São Paulo archipelago could act as a potential source of paralarvae to Western Africa, although we hypothesize that this connection was more common during the Pleistocene, when sea level was around 120 m lower. In addition to the already known areas of O. insularis occurrence, the ENM pointed suitable habitats to the octopus settlement from Guinea-Bissau down to Equatorial Guinea and Gabon, and African Islands, such as São Tomé and Príncipe. The new record of O. insularis in Africa raises important questions regarding regional fisheries management. Considering that O. insularis is highly tolerant to environmental variations and very adapted to warm shallow waters, there is a possibility that octopus fisheries stocks on the African coast have a mixed composition (O. vulgaris, O. insularis, and Octopus sp.) and therefore the fisheries must follow management measures suitable for each species. In addition, further studies should be carried out in order to characterize and describe the potential new octopus species found only in São Tomé Island according to our genetic survey.

Effects of Different Types of Agricultural Land Use on the Occurrence of Common Aquatic Bugs (Nepomorpha, Heteroptera) in Habitats with Slow Flowing Water in Bulgaria, Southeast Europe

Agricultural activities can have a significant impact on aquatic organisms, including aquatic insects. Most of the aquatic Heteroptera are known as moderately tolerant to low oxygen and high nutrient concentrations. Nevertheless, the complex effects of agriculture (source of both pesticides and nutrient loads) on this group are still unclear. Therefore, the relationship between six agricultural land use classes and the occurrence of common aquatic bugs in Bulgaria was studied. In order to avoid detection bias, presence-only models were applied; Maxent algorithm was used. According to the results, land use practices connected to arable land (annual crops) have stronger influence on the occurrence of the selected aquatic Heteroptera species than those connected to perennial crops (vineyards and fruit trees). Higher sensitivity to the effects of agriculture was indicated for species preferring microhabitats without macrophyte vegetation, Aphelocheirus aestivalis (Fabricius, 1794) and Micronecta griseola Horváth, 1899, compared to species preferring macrophyte dominated sites, Nepa cinerea Linnaeus, 1758, Ilyocoris cimicoides (Linnaeus, 1758) and Sigara striata (Linnaeus, 1758).

Modelling Distributions of Asian and African Rice Based on MaxEnt

Rice landraces, including Asian rice (Oryza sativa L.) and African rice (Oryza glaberrima Steud.), provide important genetic resources for rice breeding to address challenges related to food security. Due to climate change and farm destruction, rice landraces require urgent conservation action. Recognition of the geographical distributions of rice landraces will promote further collecting efforts. Here we modelled the potential distributions of eight rice landrace subgroups using 8351 occurrence records combined with environmental predictors with Maximum Entropy (MaxEnt) algorithm. The results showed they were predicted in eight sub-regions, including the Indus, Ganges, Meghna, Mekong, Yangtze, Pearl, Niger, and Senegal river basins. We then further revealed the changes in suitable areas of rice landraces under future climate change. Suitable areas showed an upward trend in most of study areas, while sub-regions of North and Central China and West Coast of West Africa displayed an unsuitable trend indicating rice landraces are more likely to disappear from fields in these areas. The above changes were mainly determined by changing global temperature and precipitation. Those increasingly unsuitable areas should receive high priority in further collections. Overall, these results provide valuable references for further collecting efforts of rice landraces, while shedding light on global biodiversity conservation.

Modeling current and future distribution patterns of Uvaria chamae in Benin (West Africa): Challenges and opportunities for its sustainable management

Uvaria chamae is a wild shrub species widely used as a source for traditional medicine, food and fuel in West Africa. The species is threatened by uncontrolled harvesting of its roots for pharmaceutical applications and by the extension of agricultural land. This study assessed the role of environmental variables for the current distribution and the potential impact of climate change on the future spatial distribution of U. chamae in Benin. We used data related to climate, soil, topography and land cover to model the distribution of the species. Occurrence data were combined with six least correlated bioclimatic variables derived from the WorldClim database, data on soil layers (texture and pH) and topography (slope) obtained from the FAO world database and land cover from the DIVA-GIS site. Random Forest (RF), Generalized Additive Models (GAM), Generalized Linear Models (GLM) and the Maximum Entropy (MaxEnt) algorithm were used to predict the current and future (2050–2070) distribution of the species. Two climate change scenarios (SSP245 and SSP585) were considered for the future predictions. The results showed that climate (i.e., water availability) and soil type are the key predictors of the distribution of the species. Based on future climate projections, RF, GLM and GAM models predict that the Guinean-Congolian and Sudano-Guinean zones of Benin will remain suitable for U. chamae, while it will decline in these zones according to the MaxEnt model. These results call for a timely management effort for the species in Benin through its introduction into agroforestry systems to ensure the continuity of its ecosystem services.

Species distribution modelling of Monotheca buxifolia (Falc.) A. DC.: Present distribution and impacts of potential climate change

Species distribution modelling (SDM) is an important tool to examine the possible change in the population range and/or niche-shift under current environment and predicted climate change. Monotheca buxifolia is an economically and ecologically important tree species inhabiting Pakistan and Afghanistan in dense patches, and species range is contracting rapidly. This study hypothesize that predicted climate change might remarkably influence the existing distribution pattern of M. buxifolia in the study area. A total of 75 occurrence locations were identified comprising M. buxifolia as a dominant tree species. The Maximum Entropy (MaxEnt) algorithm was utilized to perform the SDM under current (the 1970s–2000s) and two future climate change scenarios (shared socioeconomic pathways: SSPs 245 and 585) of two time periods (the 2050s and 2070s). The optimal model settings were assessed, and simulation precision was assessed by examining the partial area under the receiver operating characteristic curve (pAUC-ROC). The results showed that out of 39 considered bio-climatic, topographic, edaphic, and remote sensing variables which were utilized in the preliminary model, 6 variables including precipitation of warmest quarter, topographic diversity, global human modification of terrestrial land, normalized difference vegetation index, isothermality, and elevation (in order) were the most influential drivers, and utilized in all reduced SDMs. A high predictive performance (pAUC-ROC; >0.9) of all the considered SDMs was recorded. A total of about 67,684 km2 of geographical area was predicted as suitable habitat (p > 0.8) for M. buxifolia, and Pakistan is the leading country (with about 54,975 km2 of suitable land area) under the current climate scenario. Overall, the existing distribution of the tree species in the study area might face considerable loss (i.e. rate of change %; −27 to −107) in future, and simultaneously a northward (high elevation) niche shift is predicted for all the considered future climate change scenarios. Hence, development and implementation of a coordinated conservation program is required on priority basis to save the tree species in its native geographic range.

Modeling the potential distribution of two immortality flora in the Philippines: Applying MaxEnt and GARP algorithms under different climate change scenarios

Modeling the potential distribution of two immortality flora in the Philippines: Applying MaxEnt and GARP algorithms under different climate change scenarios

Prediction of Native Seed Habitat Distribution According to SSP Scenario and Seed Transfer Zones: A Focus on Acer pictum subsp. mono and Quercus acuta

Acer pictum and Quercus acuta are native species recommended for restoration. To restore ecosystem functions and maintain natural ecosystems, it is suggested to deploy well-adapted and locally adapted plant material, and this notion is gaining interest. Studying how species change in response to climate change is an important part of forest restoration planning. Our method uses climate data to define the habitat range of species and to identify regions with relatively similar climates through Seed Transfer Zones (STZs). Potential habitat suitability changes of A. pictum and Q. acuta were identified under various environmental scenarios using seven climatic factors and five topographical factors. The MaxEnt algorithm was used to predict potential habitat suitability in current and future (1980–2100) climate change scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5). STZs are maps of areas with comparable climates and have been used to determine the climates of potentially habitable areas. This helps to minimize the maladaptation of seed movement within the same area. As a result, A. pictum growth increased along the southern coastal area and drainage was the paramount factor influencing A. pictum distribution. By checking the climate of regions with high habitability in STZs (Winter Minimum Temperature (WMT) 15–20 °F, Annual Heat: Moisture (AHM) 16–19 °C/m zone, WMT 20–25 °F, AHM 16–19 °C/m located in the zone), Q. acuta was shown to move northward with climate change centering on the southern coastal area. Additionally, Annual Precipitation (Bio12) was the most significant factor influencing Q. acuta distribution. In confirming the climate of areas with high habitability in STZs, we verified that habitat density was high in the WMT 10–15 °F, AHM 19–21 °C/m zone and WMT 20–25 °F, AHM 19–21 °C/m zone. This study establishes that the potential distributions of A. pictum and Q. acuta are affected by climate change. It supplies evidence for ecological restoration and sustainable development, and can formulate future conservation and management plans for economically valuable species.