Identifying potential protected areas is increasingly important as freshwater fishes and associated aquatic organisms are under increasing peril. Human population, growth and subsequent landscape alteration, is degrading water quality and changing the physical characteristics of streams, potentially threatening aquatic species. The goal is to assess the capacity for protected areas to maintain diverse stream fish communities within the Mobile River Basin, including the upper Coosa River basin, by overlaying projections of fish species distributions and footprints of protected areas. Tools for identifying fish species distributions, environmental predictors, and potential protected areas include spatial conservation prioritization algorithms combined with open access electronic databases (Troia and McManamay 2016). These libraries provide a list of species inventories built up over time, cover a wide range of geographic areas and environments, and help to check for presence and distribution of species. I developed environmental niche models (hereafter “ENMs”) using the Maximum Entropy algorithm (MaxEnt) and spatial conservation prioritization algorithm (Marxan) to map the fish presence maps of 176 species over 66,509 reaches using open-source species occurrence records from the IchthyMaps dataset and stream-reach environmental predictors from the StreamCat dataset. ENMs are fit for 172-target species, with high model accuracy (mean AUC = 0.89 range 0.65 to 0.99). Geospatial analysis evaluates if protected areas overlap in the diverse and unique reaches. Lastly, potential priority protected areas for conservation planning are identified.
","abstract_html":"<p>Identifying potential protected areas is increasingly important as freshwater fishes and associated aquatic organisms are under increasing peril. Human population, growth and subsequent landscape alteration, is degrading water quality and changing the physical characteristics of streams, potentially threatening aquatic species. The goal is to assess the capacity for protected areas to maintain diverse stream fish communities within the Mobile River Basin, including the upper Coosa River basin, by overlaying projections of fish species distributions and footprints of protected areas. Tools for identifying fish species distributions, environmental predictors, and potential protected areas include spatial conservation prioritization algorithms combined with open access electronic databases (Troia and McManamay 2016). These libraries provide a list of species inventories built up over time, cover a wide range of geographic areas and environments, and help to check for presence and distribution of species. I developed environmental niche models (hereafter “ENMs”) using the Maximum Entropy algorithm <em>(MaxEnt)</em> and spatial conservation prioritization algorithm (<em>Marxan</em>) to map the fish presence maps of 176 species over 66,509 reaches using open-source species occurrence records from the <em>IchthyMaps</em> dataset and stream-reach environmental predictors from the <em>StreamCat</em> dataset. ENMs are fit for 172-target species, with high model accuracy (mean AUC = 0.89 range 0.65 to 0.99). Geospatial analysis evaluates if protected areas overlap in the diverse and unique reaches. Lastly, potential priority protected areas for conservation planning are identified. </p>","abstract_has_math":false,"creators":["Carl, James R"],"institution":null,"degree_name":"Master of Science in Integrative Biology (MSIB)","degree_level":"Thesis","degree_discipline":"Biology","degree_department":null,"school":null,"contributors":["Mario Bretfeld","Heather Sutton"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2020,"date_issued":"2020-07-03T07:00:00Z","date_published":"2020-07-03T07:00:00Z","updated_at":"2026-07-24T02:43:42Z","subjects":["Priority protected land","ENMs","Freshwater fish","Mobile River Basin","Biology","Integrative Biology"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalcommons.kennesaw.edu/integrbiol_etd/52","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Mario Bretfeld","Heather Sutton"]},{"key":"dc:creator","label":"Author","values":["Carl, James R"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2020-07-14T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Biology"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science in Integrative Biology (MSIB)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Priority protected land","ENMs","Freshwater fish","Mobile River Basin","Biology","Integrative Biology"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalcommons.kennesaw.edu/integrbiol_etd/52"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Identifying potential protected areas is increasingly important as freshwater fishes and associated aquatic organisms are under increasing peril. Human population, growth and subsequent landscape alteration, is degrading water quality and changing the physical characteristics of streams, potentially threatening aquatic species. The goal is to assess the capacity for protected areas to maintain diverse stream fish communities within the Mobile River Basin, including the upper Coosa River basin, by overlaying projections of fish species distributions and footprints of protected areas. Tools for identifying fish species distributions, environmental predictors, and potential protected areas include spatial conservation prioritization algorithms combined with open access electronic databases (Troia and McManamay 2016). These libraries provide a list of species inventories built up over time, cover a wide range of geographic areas and environments, and help to check for presence and distribution of species. I developed environmental niche models (hereafter “ENMs”) using the Maximum Entropy algorithm (MaxEnt) and spatial conservation prioritization algorithm (Marxan) to map the fish presence maps of 176 species over 66,509 reaches using open-source species occurrence records from the IchthyMaps dataset and stream-reach environmental predictors from the StreamCat dataset. ENMs are fit for 172-target species, with high model accuracy (mean AUC = 0.89 range 0.65 to 0.99). Geospatial analysis evaluates if protected areas overlap in the diverse and unique reaches. Lastly, potential priority protected areas for conservation planning are identified.
"]},{"key":"dc:title","label":"Title","values":["High-Resolution Mapping of Fish Conservation Priorities within the Mobile River Basin"]}]}],"canonical_facts":{"dc:contributor":["Mario Bretfeld","Heather Sutton"],"dc:creator":["Carl, James R"],"dc:date.available":["2020-07-14T07:00:00Z"],"dc:description.abstract":["Identifying potential protected areas is increasingly important as freshwater fishes and associated aquatic organisms are under increasing peril. Human population, growth and subsequent landscape alteration, is degrading water quality and changing the physical characteristics of streams, potentially threatening aquatic species. The goal is to assess the capacity for protected areas to maintain diverse stream fish communities within the Mobile River Basin, including the upper Coosa River basin, by overlaying projections of fish species distributions and footprints of protected areas. Tools for identifying fish species distributions, environmental predictors, and potential protected areas include spatial conservation prioritization algorithms combined with open access electronic databases (Troia and McManamay 2016). These libraries provide a list of species inventories built up over time, cover a wide range of geographic areas and environments, and help to check for presence and distribution of species. I developed environmental niche models (hereafter “ENMs”) using the Maximum Entropy algorithm (MaxEnt) and spatial conservation prioritization algorithm (Marxan) to map the fish presence maps of 176 species over 66,509 reaches using open-source species occurrence records from the IchthyMaps dataset and stream-reach environmental predictors from the StreamCat dataset. ENMs are fit for 172-target species, with high model accuracy (mean AUC = 0.89 range 0.65 to 0.99). Geospatial analysis evaluates if protected areas overlap in the diverse and unique reaches. Lastly, potential priority protected areas for conservation planning are identified.
"],"dc:identifier":["https://digitalcommons.kennesaw.edu/integrbiol_etd/52"],"dc:subject":["Priority protected land","ENMs","Freshwater fish","Mobile River Basin","Biology","Integrative Biology"],"dc:title":["High-Resolution Mapping of Fish Conservation Priorities within the Mobile River Basin"],"thesis:degree_discipline":["Biology"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["Master of Science in Integrative Biology (MSIB)"]},"updated_at":"2026-07-24T02:43:42Z"}