Christophe Brabant, Nakiya Noorbhai, Mette Bendixen, Lars L. Iversen
Natural resource mining is a vital global industry serving sectors such as construction, infrastructure and electronics. The negative impacts of mining, exacerbated by poor governance and lax legislation, have detrimental consequences on the environment, especially in freshwater systems. Mining is shown to disrupt hydrological regimes, sediment dynamics and vegetation structure, which affect water quality, species composition and overall ecosystem health. However, little is known about the global extent of mining impacts on freshwater biodiversity, ultimately hindering mitigation efforts and effective policy implementation. Here, we address this knowledge gap by developing an impact probability model to generate global threat maps based on the impact of mining for freshwater fish, macrophytes and odonatan. We show that the impact of mining differs significantly between taxonomic groups, with hotspots of risk coinciding with high-biodiversity and wilderness areas. Using a random forest machine learning model, we show that the extent of mining impacts is driven primarily by environmental and anthropogenic variables, such as land surface runoff and the Human Development Index. This overview of the global distribution of mining's threat is urgently needed for conservation plans to mitigate the impact of mining on biodiversity.
{"title":"Mapping the Global Impact of Mining Activities on Freshwater Biodiversity to Inform Conservation Priorities","authors":"Christophe Brabant, Nakiya Noorbhai, Mette Bendixen, Lars L. Iversen","doi":"10.1002/aqc.70094","DOIUrl":"https://doi.org/10.1002/aqc.70094","url":null,"abstract":"<p>Natural resource mining is a vital global industry serving sectors such as construction, infrastructure and electronics. The negative impacts of mining, exacerbated by poor governance and lax legislation, have detrimental consequences on the environment, especially in freshwater systems. Mining is shown to disrupt hydrological regimes, sediment dynamics and vegetation structure, which affect water quality, species composition and overall ecosystem health. However, little is known about the global extent of mining impacts on freshwater biodiversity, ultimately hindering mitigation efforts and effective policy implementation. Here, we address this knowledge gap by developing an impact probability model to generate global threat maps based on the impact of mining for freshwater fish, macrophytes and odonatan. We show that the impact of mining differs significantly between taxonomic groups, with hotspots of risk coinciding with high-biodiversity and wilderness areas. Using a random forest machine learning model, we show that the extent of mining impacts is driven primarily by environmental and anthropogenic variables, such as land surface runoff and the Human Development Index. This overview of the global distribution of mining's threat is urgently needed for conservation plans to mitigate the impact of mining on biodiversity.</p>","PeriodicalId":55493,"journal":{"name":"Aquatic Conservation-Marine and Freshwater Ecosystems","volume":"35 3","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aqc.70094","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143481348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}