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      Linking mountaintop removal mining to water quality for imperiled species using satellite data

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          Abstract

          Environmental laws need sound data to protect species and ecosystems. In 1996, a proliferation of mountaintop removal coal mines in a region home to over 50 federally protected species was approved under the Endangered Species Act. Although this type of mining can degrade terrestrial and aquatic habitats, the available data and tools limited the ability to analyze spatially extensive, aggregate effects of such a program. We used two large, public datasets to quantify the relationship between mountaintop removal coal mining and water quality measures important to the survival of imperiled species at a landscape scale across Kentucky, Tennessee, Virginia, and West Virginia. We combined an annual map of the extent of surface mines in this region from 1985 to 2015 generated from Landsat satellite imagery with public water quality data collected over the same time period from 4,260 monitoring stations within the same area. The water quality data show that chronic and acute thresholds for levels of aluminum, arsenic, cadmium, conductivity, copper, lead, manganese, mercury, pH, selenium, and zinc safe for aquatic life were exceeded thousands of times between 1985 and 2015 in streams that are important to the survival and recovery of species on the Endangered Species List. Linear mixed models showed that levels of manganese, sulfate, sulfur, total dissolved solids, total suspended solids, and zinc increased by 6.73E+01 to 6.87E+05 μg/L and conductivity by 3.30E+06 μS /cm for one percent increase in the mined proportion of the area draining into a monitoring station. The proportion of a drainage area that was mined also increased the likelihood that chronic thresholds for copper, lead, and zinc required to sustain aquatic life were exceeded. Finally, the proportion of a watershed that was mined was positively related to the likelihood that a waterway would be designated as impaired under the Clean Water Act. Together these results demonstrate that the extent of mountaintop removal mining, which can be derived from public satellite data, is predictive of water quality measures important to imperiled species—effects that must be considered under environmental law. These findings and the public data used in our analyses are pertinent to ongoing re-evaluations of the effects of current mine permitting regulations to the recovery and survival of federally protected species.

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: Project administrationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: InvestigationRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: InvestigationRole: Writing – review & editing
                Role: Data curationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                4 November 2021
                2021
                : 16
                : 11
                : e0239691
                Affiliations
                [1 ] Center for Conservation Innovation, Defenders of Wildlife, Washington, DC, United States of America
                [2 ] Environmental Science and Policy Dept., George Mason University, Fairfax, VA, United States of America
                [3 ] SkyTruth, Shepherdstown, WV, United States of America
                University of Waikato, NEW ZEALAND
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0001-9048-6611
                Article
                PONE-D-20-28542
                10.1371/journal.pone.0239691
                8568141
                bdb24f77-0066-480a-94bf-b2c3cef8ee62
                © 2021 Evans et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 10 September 2020
                : 13 October 2021
                Page count
                Figures: 3, Tables: 3, Pages: 14
                Funding
                The authors received no specific funding for this work.
                Categories
                Research Article
                Ecology and Environmental Sciences
                Water Quality
                Computer and Information Sciences
                Data Management
                Data Mining
                Biology and Life Sciences
                Conservation Biology
                Endangered Species
                Ecology and Environmental Sciences
                Conservation Science
                Conservation Biology
                Endangered Species
                Physical Sciences
                Chemistry
                Chemical Elements
                Manganese
                Biology and Life Sciences
                Agriculture
                Biology and Life Sciences
                Ecology
                Ecosystems
                Ecology and Environmental Sciences
                Ecology
                Ecosystems
                Earth Sciences
                Geography
                Physical Geography
                Watersheds
                Social Sciences
                Law and Legal Sciences
                Environmental Law
                Custom metadata
                The data underlying the results presented in the study are available through an Open Science Framework repository: https://doi.org/10.17605/OSF.IO/A2Z34.

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                Uncategorized

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