Ecological niche modelling of a critically endangered species Commiphora wightii (Arn.) Bhandari using bioclimatic and non-bioclimatic variables
Abstract 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 suit...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2023-02-01
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| Series: | Ecological Processes |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13717-023-00423-2 |
| _version_ | 1797865522617909248 |
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| author | Manish Mathur Preet Mathur Harshit Purohit |
| author_facet | Manish Mathur Preet Mathur Harshit Purohit |
| author_sort | Manish Mathur |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-04-09T23:10:32Z |
| format | Article |
| id | doaj.art-29a6ca50a26f4ba5b388e05894f2b11a |
| institution | Directory Open Access Journal |
| issn | 2192-1709 |
| language | English |
| last_indexed | 2024-04-09T23:10:32Z |
| publishDate | 2023-02-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Ecological Processes |
| spelling | doaj.art-29a6ca50a26f4ba5b388e05894f2b11a2023-03-22T10:26:02ZengSpringerOpenEcological Processes2192-17092023-02-0112113010.1186/s13717-023-00423-2Ecological niche modelling of a critically endangered species Commiphora wightii (Arn.) Bhandari using bioclimatic and non-bioclimatic variablesManish Mathur0Preet Mathur1Harshit Purohit2ICAR-Central Arid Zone Research InstituteJodhpur Institute of Engineering and TechnologyNeal AnalyticsAbstract 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.https://doi.org/10.1186/s13717-023-00423-2Commiphora wightiiCritically endangeredMaxentHabitat heterogeneity indexNiche hypervolumeArea of extent |
| spellingShingle | Manish Mathur Preet Mathur Harshit Purohit Ecological niche modelling of a critically endangered species Commiphora wightii (Arn.) Bhandari using bioclimatic and non-bioclimatic variables Ecological Processes Commiphora wightii Critically endangered Maxent Habitat heterogeneity index Niche hypervolume Area of extent |
| title | Ecological niche modelling of a critically endangered species Commiphora wightii (Arn.) Bhandari using bioclimatic and non-bioclimatic variables |
| title_full | Ecological niche modelling of a critically endangered species Commiphora wightii (Arn.) Bhandari using bioclimatic and non-bioclimatic variables |
| title_fullStr | Ecological niche modelling of a critically endangered species Commiphora wightii (Arn.) Bhandari using bioclimatic and non-bioclimatic variables |
| title_full_unstemmed | Ecological niche modelling of a critically endangered species Commiphora wightii (Arn.) Bhandari using bioclimatic and non-bioclimatic variables |
| title_short | Ecological niche modelling of a critically endangered species Commiphora wightii (Arn.) Bhandari using bioclimatic and non-bioclimatic variables |
| title_sort | ecological niche modelling of a critically endangered species commiphora wightii arn bhandari using bioclimatic and non bioclimatic variables |
| topic | Commiphora wightii Critically endangered Maxent Habitat heterogeneity index Niche hypervolume Area of extent |
| url | https://doi.org/10.1186/s13717-023-00423-2 |
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