Vincent Okelo Wanga, Boniface K Ngarega, Millicent Akinyi Oulo, Elijah Mbandi Mkala, Veronicah Mutele Ngumbau, Guy Eric Onjalalaina, Wyclif Ochieng Odago, Consolata Nanjala, Clintone Onyango Ochieng, Moses Kirega Gichua, Robert Wahiti Gituru, Guang-Wan Hu
{"title":"Projected impacts of climate change on the habitat of <i>Xerophyta</i> species in Africa.","authors":"Vincent Okelo Wanga, Boniface K Ngarega, Millicent Akinyi Oulo, Elijah Mbandi Mkala, Veronicah Mutele Ngumbau, Guy Eric Onjalalaina, Wyclif Ochieng Odago, Consolata Nanjala, Clintone Onyango Ochieng, Moses Kirega Gichua, Robert Wahiti Gituru, Guang-Wan Hu","doi":"10.1016/j.pld.2023.05.001","DOIUrl":null,"url":null,"abstract":"<p><p>Climate change poses a serious long-term threat to biodiversity. To effectively reduce biodiversity loss, conservationists need to have a thorough understanding of the preferred habitats of species and the variables that affect their distribution. Therefore, predicting the impact of climate change on species-appropriate habitats may help mitigate the potential threats to biodiversity distribution. <i>Xerophyta</i>, a monocotyledonous genus of the family Velloziaceae is native to mainland Africa, Madagascar, and the Arabian Peninsula. The key drivers of <i>Xerophyta</i> habitat distribution and preference are unknown. Using 308 species occurrence data and eight environmental variables, the MaxEnt model was used to determine the potential distribution of six <i>Xerophyta</i> species in Africa under past, current and future climate change scenarios. The results showed that the models had a good predictive ability (Area Under the Curve and True Skill Statistics values for all SDMs were more than 0.902), indicating high accuracy in forecasting the potential geographic distribution of <i>Xerophyta</i> species. The main bioclimatic variables that impacted potential distributions of most <i>Xerophyta</i> species were mean temperature of the driest quarter (Bio9) and precipitation of the warmest quarter (Bio18). According to our models, tropical Africa has zones of moderate and high suitability for <i>Xerophyta</i> taxa, which is consistent with the majority of documented species localities. The habitat suitability of the existing range of the <i>Xerophyta</i> species varied based on the climate scenario, with most species experiencing a range loss greater than the range gain regardless of the climate scenario. The projected spatiotemporal patterns of <i>Xerophyta</i> species help guide recommendations for conservation efforts.</p>","PeriodicalId":48419,"journal":{"name":"Economic Modelling","volume":"39 1","pages":"91-100"},"PeriodicalIF":4.2000,"publicationDate":"2023-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10851299/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Economic Modelling","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1016/j.pld.2023.05.001","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
Climate change poses a serious long-term threat to biodiversity. To effectively reduce biodiversity loss, conservationists need to have a thorough understanding of the preferred habitats of species and the variables that affect their distribution. Therefore, predicting the impact of climate change on species-appropriate habitats may help mitigate the potential threats to biodiversity distribution. Xerophyta, a monocotyledonous genus of the family Velloziaceae is native to mainland Africa, Madagascar, and the Arabian Peninsula. The key drivers of Xerophyta habitat distribution and preference are unknown. Using 308 species occurrence data and eight environmental variables, the MaxEnt model was used to determine the potential distribution of six Xerophyta species in Africa under past, current and future climate change scenarios. The results showed that the models had a good predictive ability (Area Under the Curve and True Skill Statistics values for all SDMs were more than 0.902), indicating high accuracy in forecasting the potential geographic distribution of Xerophyta species. The main bioclimatic variables that impacted potential distributions of most Xerophyta species were mean temperature of the driest quarter (Bio9) and precipitation of the warmest quarter (Bio18). According to our models, tropical Africa has zones of moderate and high suitability for Xerophyta taxa, which is consistent with the majority of documented species localities. The habitat suitability of the existing range of the Xerophyta species varied based on the climate scenario, with most species experiencing a range loss greater than the range gain regardless of the climate scenario. The projected spatiotemporal patterns of Xerophyta species help guide recommendations for conservation efforts.
期刊介绍:
Economic Modelling fills a major gap in the economics literature, providing a single source of both theoretical and applied papers on economic modelling. The journal prime objective is to provide an international review of the state-of-the-art in economic modelling. Economic Modelling publishes the complete versions of many large-scale models of industrially advanced economies which have been developed for policy analysis. Examples are the Bank of England Model and the US Federal Reserve Board Model which had hitherto been unpublished. As individual models are revised and updated, the journal publishes subsequent papers dealing with these revisions, so keeping its readers as up to date as possible.