MaxEnt modeling to predict the current and future distribution of Clerodendrum infortunatum L. under climate change scenarios in Dehradun district, India

Purohit, Saurabh; Rawat, Neelam

doi:10.1007/s40808-021-01205-5

Cited by 26 publications

(22 citation statements)

References 74 publications

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“…Noticeably, the reduction in suitability areas was observed in regions of central India. Similar species range expansions and contractions have been reported in various species (Qin et al 2017;Purohit and Rawat 2021), including NTFP species in the tropics (Yadav et al 2022).…”

Section: Current and Future Distributions Of R Serpentinasupporting

confidence: 77%

Habitat suitability mapping for a high-value non-timber forest product: A case study of <i>Rauvolfia serpentina</i>

Mandal

Okuda

Mon

et al. 2023

Tropics

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Non-timber forest products (NTFPs) are essential for rural livelihoods but are often threatened by deforestation and overexploitation. Rauvolfia serpentina is a critical NTFP species; however, there have been no studies on the impact of future climate change on its potential habitat distribution. We used the Maxent modeling approach to address this knowledge gap and determine this species current and future suitability under climate change scenarios. The areas more suitable to its occurrence were mainly located near the southwestern coastal regions of Myanmar and India. Based on our predictions, these very high suitability areas are likely to decrease in 2070 under both low and high CO 2 emission scenarios, indicating the future vulnerability of this species habitat to the impact of climate change. This species is a highly valued NTFP species in the study region; therefore, such a reduction in habitat suitability may result in reductions in NTFP production and economic benefits for the dependent populations. Our findings can help define and conserve areas containing the natural habitats of this high-valued NTFP species.

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Section: Current and Future Distributions Of R Serpentinasupporting

confidence: 77%

Habitat suitability mapping for a high-value non-timber forest product: A case study of <i>Rauvolfia serpentina</i>

Mandal

Okuda

Mon

et al. 2023

Tropics

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“…However, since our sole objective was to understand habitat suitability under the current and two potential future climatic conditions, we chose to use only these variables. In such forecasting studies, it is common to use bioclimatic variables with topographic variables [20,21,49]. Our results indicate that temperature seasonality is the most important climatic variable influencing parthenium weed distribution over our studied area, suggesting that the extreme annual temperature differences are likely to favor parthenium infestation in our study area.…”

Section: Discussionmentioning

confidence: 67%

Predicting Current and Future Potential Distributions of Parthenium hysterophorus in Bangladesh Using Maximum Entropy Ecological Niche Modelling

et al. 2022

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Parthenium weed (Parthenium hysterophorus L.) is among the most noxious invasive alien plant species, which can pose a threat to agro- and native-ecosystems. Despite potential parthenium infestation risks at the south-western regions of the Ganges–Brahmaputra floodplains of Bangladesh, no studies exist that document parthenium infestation. Using field surveys and a maximum entropy (Maxent) modelling approach, the present study tries to address the problem in the concerned region comprised of five Districts: Jashore, Jhenaidah, Chuadanga, Meherpur, and Khustia. The results revealed high infestation in the Jashore, Jhenaidah, and Chuadanga Districts, mainly along roadsides, in grasslands, and in fallow and cropped fields. The greatest abundance of the weed (ca. 30 plants m−2) occurred at the Indian border area, suggesting cross-border spreading, possibly through the linking road systems. Furthermore, we found that under both low and high emissions scenarios (Representative Concentration Pathways 2.6 and 8.5), parthenium weed suitability areas were likely to expand, suggesting an increased threat to the agro-ecosystems of Bangladesh. The present study is the first attempt to survey and model potential parthenium weed distribution affecting one of the major hubs of agricultural production in Bangladesh. The findings of this study can help land managers to make judicious decisions towards the future management of these agro-ecosystems.

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“…Compared to other SDM tools, a maximum entropy algorithm can develop a good model with small number of occurrences (Harapan et al 2020). Because of this reason, many studies on threatened plants, which typically have small amounts of occurrence data, use MaxEnt to model species distributions (Adhikari et al 2012;Yang et al 2013;Padalia et al 2014;Pradhan 2015;Remya et al 2015;Yuan et al 2015;Yi et al 2016;Pranata et al 2019;Ito et al 2020;Anand et al 2021;Du et al 2021;Felix et al 2021;Liu et al 2021;Mahatara et al 2021;Nguyen et al 2021;Purohit and Rawat 2021;Su et al 2021;Yang et al 2021;Ye et al 2021). With effective conservation planning focused on ensuring redundancy and resiliency for sustainable future populations (Redford et al 2011), SDMs are a valuable tool for the conservation community (Mcshea 2014).…”

Section: Introductionmentioning

confidence: 99%

Identifying the potential geographic distribution for Castanopsis argentea and C. tungurrut (Fagaceae) in the Sumatra Conservation Area Network, Indonesia

et al. 2022

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Abstract. Harapan TS, Nurainas, Syamsuardi, Taufiq A. 2022. Identifying the potential geographic distribution for Castanopsis argentea and Castanopsis tungurrut (Family: Fagaceae) in the Sumatra Conservation Area Network, Indonesia. Biodiversitas 23: 1726-1733. Recently, Castanopsis argentea (Blume) A.DC. and Castanopsis tungurrut (Blume) A.DC. have been listed as endangered species by the International Union for the Conservation of Nature (IUCN). For conservation planning, it is important to know the full distribution of species. This study aimed to predict the potential distribution of C. argentea and C. tungurrut using MaxEnt, and understand key factors responsible for the distribution of these species. A total of 53 occurrences and six environmental variables were used to model their distribution. The AUC values of C. argentea and C. tungurrut were 0.86 and 0.91, respectively, and the models suggest the distribution of both species is mainly influenced by elevation, and temperature seasonality for C. tungurrut. The predicted distributions of the species are in the mountains of the western part of Sumatra, and their range includes 12 conservation areas that have highly suitable habitats for both species. After generating the MaxEnt prediction map, we conducted field validation to validate the model predictions. Field surveys in two predicted areas showed that the predicted distribution maps accurately estimated the distribution of C. argentea and C. tungurrut at those localities.

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MaxEnt modeling to predict the current and future distribution of Clerodendrum infortunatum L. under climate change scenarios in Dehradun district, India

Cited by 26 publications

References 74 publications

Habitat suitability mapping for a high-value non-timber forest product: A case study of <i>Rauvolfia serpentina</i>

Habitat suitability mapping for a high-value non-timber forest product: A case study of <i>Rauvolfia serpentina</i>

Predicting Current and Future Potential Distributions of Parthenium hysterophorus in Bangladesh Using Maximum Entropy Ecological Niche Modelling

Identifying the potential geographic distribution for Castanopsis argentea and C. tungurrut (Fagaceae) in the Sumatra Conservation Area Network, Indonesia

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