Background The aim of this study is to examine the effects of four different bioclimatic predictors (current, 2050, 2070, and 2090 under Shared Socioeconomic Pathways SSP2-4.5) and non-bioclimatic variables (soil, habitat heterogeneity index, land use, slope, and aspect) on the habitat suitability and niche dimensions of the critically endangered plant species Commiphora wightii in India. We also evaluate how niche modelling affects its extent of occurrence (EOO) and area of occupancy (AOO). Results The area under the receiver operating curve (AUC) values produced by the maximum entropy (Maxent) under various bioclimatic time frames were more than 0.94, indicating excellent model accuracy. Non-bioclimatic characteristics, with the exception of terrain slope and aspect, decreased the accuracy of our model. Additionally, Maxent accuracy was the lowest across all combinations of bioclimatic and non-bioclimatic variables (AUC = 0.75 to 0.78). With current, 2050, and 2070 bioclimatic projections, our modelling revealed the significance of water availability parameters (BC-12 to BC-19, i.e. annual and seasonal precipitation as well as precipitation of wettest, driest, and coldest months and quarters) on habitat suitability for this species. However, with 2090 projection, energy variables such as mean temperature of wettest quarter (BC-8) and isothermality (BC-3) were identified as governing factors. Excessive salt, rooting conditions, land use type (grassland), characteristics of the plant community, and slope were also noticed to have an impact on this species. Through distribution modelling of this species in both its native (western India) and exotic (North-east, Central Part of India, as well as northern and eastern Ghat) habitats, we were also able to simulate both its fundamental niche and its realized niche. Our EOO and AOO analysis reflects the possibility of many new areas in India where this species can be planted and grown. Conclusion According to the calculated area under the various suitability classes, we can conclude that C. wightii's potentially suitable bioclimatic distribution under the optimum and moderate classes would increase under all future bioclimatic scenarios (2090 > 2050 ≈ current), with the exception of 2070, demonstrating that there are more suitable habitats available for C. wightii artificial cultivation and will be available for future bioclimatic projections of 2050 and 2090. Predictive sites indicated that this species also favours various types of landforms outside rocky environments, such as sand dunes, sandy plains, young alluvial plains, saline areas, and so on. Our research also revealed crucial information regarding the community dispersion variable, notably the coefficient of variation that, when bioclimatic + non-bioclimatic variables were coupled, disguised the effects of bioclimatic factors across all time frames.

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The goal of this study was to identify the global geographical distribution patterns of a lesser known indigenous legume species, Indigofera oblongifolia, using three bio-climatic timeframes (current, 2050, and 2070) and four greenhouse gas scenarios (RCPs 2.6, 4.5, 6.0, and 8.5), as well as non-climatic predictors like global livestock population, human modification of terrestrial ecosystem (GHMTE), global fertilizers application (nitrogen and phosphorus). In addition, we assess the degree of indigenousness using the area, habitat suitability categories, and number of polygons, and we identify the temporal effects of various bio-climatic variables on its fundamental and realized niche. The AUC for models built using current climate data and RCPs for the years 2050 and 2070 was 0.90. This research reveals that climatic predictors outperform non-climatic predictors in terms of improving model quality. Precipitation Seasonality is one of the most important factors influencing this species’ optimum habitat suitability up to 150 mm for the current, 2050-RCP 8.5, and 2070-RCPs 2.6, 4.5, and 8.5. The range of this parameter has altered from 79–176.9 to 85–196 as the climatic conditions and RCPs have improved. Our ellipsoid niche modelling extends the range of these bioclimatic variables to 637 mm and 26.5-31.80 degrees Celsius, respectively. India has a higher indigenous score in the optimal class than the African region. These findings indicate that this species inhabits more continuous areas in Africa, whereas it is fragmented into a number of smaller meta-populations in India (group of spatially separated population of the same species).

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