{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/108137"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/108137","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Determining vegetation metric robustness to environmental and methodological variables, and coefficients of conservatism for the flora of the Middle Rio Grande, New Mexico","abstract":"Common vegetation metrics used in monitoring of ecological restorations include measures of vegetation structure and measures of species diversity and composition. Metrics of species diversity and composition are often used as proxies for overall biological diversity of a site, but some metrics may be misleading in their ability to fully capture the integrity of ecological interactions of that site. Understanding metric sensitivity to external variables is deeply important to restoration ecology and applied land management. If a metric is influenced by changes in sample size, differences among community types, differences between regions, or potential observer bias, then it calls into question the metric’s strength for measuring ecological integrity, specifically the metric’s usefulness when comparing among sites or within a given site through time. I focused on vegetation metrics and their use in applied land management for my thesis. My research is based on vegetation data collected from four regions across the United States over two years, in collaboration with regional botanists, land managers, and land management agencies. In Chapter 2, I used the vegetation data collected across the four regions of the United States to answer two questions regarding commonly used vegetation metrics: 1) Are commonly used vegetation metrics robust, or insensitive to, common environmental variables and methodological choices used in different monitoring regimes, and 2) based on region, what is the adequate sample size for these commonly used vegetation metrics? To be able to adequately compare metrics among all regions, I first needed to create C-values within the study region in New Mexico that lacked those values. In Chapter 3, I collaborated with botanists from New Mexico to develop Coefficients of Conservatism for the Middle Rio Grande region. These values provide an easy and accessible tool for land managers to use when evaluating sites for riparian restorations, or for long term monitoring of previously restored sites. For this study, I compiled a comprehensive floral species list within the Middle Rio Grande floodplain, and assigned Coefficients of Conservatism to 624 of those species.","abstract_html":"Common vegetation metrics used in monitoring of ecological restorations include measures of vegetation structure and measures of species diversity and composition. Metrics of species diversity and composition are often used as proxies for overall biological diversity of a site, but some metrics may be misleading in their ability to fully capture the integrity of ecological interactions of that site. Understanding metric sensitivity to external variables is deeply important to restoration ecology and applied land management. If a metric is influenced by changes in sample size, differences among community types, differences between regions, or potential observer bias, then it calls into question the metric’s strength for measuring ecological integrity, specifically the metric’s usefulness when comparing among sites or within a given site through time. I focused on vegetation metrics and their use in applied land management for my thesis. My research is based on vegetation data collected from four regions across the United States over two years, in collaboration with regional botanists, land managers, and land management agencies. In Chapter 2, I used the vegetation data collected across the four regions of the United States to answer two questions regarding commonly used vegetation metrics: 1) Are commonly used vegetation metrics robust, or insensitive to, common environmental variables and methodological choices used in different monitoring regimes, and 2) based on region, what is the adequate sample size for these commonly used vegetation metrics? To be able to adequately compare metrics among all regions, I first needed to create C-values within the study region in New Mexico that lacked those values. In Chapter 3, I collaborated with botanists from New Mexico to develop Coefficients of Conservatism for the Middle Rio Grande region. These values provide an easy and accessible tool for land managers to use when evaluating sites for riparian restorations, or for long term monitoring of previously restored sites. For this study, I compiled a comprehensive floral species list within the Middle Rio Grande floodplain, and assigned Coefficients of Conservatism to 624 of those species.","abstract_has_math":false,"creators":["Stern, Jess L"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Natural Res & Env Sciences","degree_department":null,"school":null,"contributors":["Matthews, Jeffrey W"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2020,"date_issued":"2020-08-26T23:57:20Z","date_published":"2020-08-26T23:57:20Z","updated_at":"2026-07-22T22:24:47Z","subjects":["Restoration ecology","coefficients of conservatism"],"languages":["en"],"rights":["Copyright 2020 Jess Stern"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/108137","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Matthews, Jeffrey W"]},{"key":"dc:creator","label":"Author","values":["Stern, Jess L"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2020-08-26T23:57:20Z","2022-08-26T23:58:55Z","2020-05-05","2020-05"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Natural Res & Env Sciences"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Restoration ecology","coefficients of conservatism"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2020 Jess Stern"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/108137"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Common vegetation metrics used in monitoring of ecological restorations include measures of vegetation structure and measures of species diversity and composition. Metrics of species diversity and composition are often used as proxies for overall biological diversity of a site, but some metrics may be misleading in their ability to fully capture the integrity of ecological interactions of that site. Understanding metric sensitivity to external variables is deeply important to restoration ecology and applied land management. If a metric is influenced by changes in sample size, differences among community types, differences between regions, or potential observer bias, then it calls into question the metric’s strength for measuring ecological integrity, specifically the metric’s usefulness when comparing among sites or within a given site through time. I focused on vegetation metrics and their use in applied land management for my thesis. My research is based on vegetation data collected from four regions across the United States over two years, in collaboration with regional botanists, land managers, and land management agencies. In Chapter 2, I used the vegetation data collected across the four regions of the United States to answer two questions regarding commonly used vegetation metrics: 1) Are commonly used vegetation metrics robust, or insensitive to, common environmental variables and methodological choices used in different monitoring regimes, and 2) based on region, what is the adequate sample size for these commonly used vegetation metrics? To be able to adequately compare metrics among all regions, I first needed to create C-values within the study region in New Mexico that lacked those values. In Chapter 3, I collaborated with botanists from New Mexico to develop Coefficients of Conservatism for the Middle Rio Grande region. These values provide an easy and accessible tool for land managers to use when evaluating sites for riparian restorations, or for long term monitoring of previously restored sites. For this study, I compiled a comprehensive floral species list within the Middle Rio Grande floodplain, and assigned Coefficients of Conservatism to 624 of those species.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2022-05-01","The student, Jess Stern, accepted the attached license on 2020-04-29 at 15:39.","The student, Jess Stern, submitted this Thesis for approval on 2020-04-29 at 15:45.","This Thesis was approved for publication on 2020-05-05 at 11:53.","DSpace SAF Submission Ingestion Package generated from Vireo submission #15121 on 2020-08-25 at 17:28:30","Made available in DSpace on 2020-08-26T23:57:20Z (GMT). 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Metrics of species diversity and composition are often used as proxies for overall biological diversity of a site, but some metrics may be misleading in their ability to fully capture the integrity of ecological interactions of that site. Understanding metric sensitivity to external variables is deeply important to restoration ecology and applied land management. If a metric is influenced by changes in sample size, differences among community types, differences between regions, or potential observer bias, then it calls into question the metric’s strength for measuring ecological integrity, specifically the metric’s usefulness when comparing among sites or within a given site through time. I focused on vegetation metrics and their use in applied land management for my thesis. My research is based on vegetation data collected from four regions across the United States over two years, in collaboration with regional botanists, land managers, and land management agencies. In Chapter 2, I used the vegetation data collected across the four regions of the United States to answer two questions regarding commonly used vegetation metrics: 1) Are commonly used vegetation metrics robust, or insensitive to, common environmental variables and methodological choices used in different monitoring regimes, and 2) based on region, what is the adequate sample size for these commonly used vegetation metrics? To be able to adequately compare metrics among all regions, I first needed to create C-values within the study region in New Mexico that lacked those values. In Chapter 3, I collaborated with botanists from New Mexico to develop Coefficients of Conservatism for the Middle Rio Grande region. These values provide an easy and accessible tool for land managers to use when evaluating sites for riparian restorations, or for long term monitoring of previously restored sites. For this study, I compiled a comprehensive floral species list within the Middle Rio Grande floodplain, and assigned Coefficients of Conservatism to 624 of those species.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2022-05-01","The student, Jess Stern, accepted the attached license on 2020-04-29 at 15:39.","The student, Jess Stern, submitted this Thesis for approval on 2020-04-29 at 15:45.","This Thesis was approved for publication on 2020-05-05 at 11:53.","DSpace SAF Submission Ingestion Package generated from Vireo submission #15121 on 2020-08-25 at 17:28:30","Made available in DSpace on 2020-08-26T23:57:20Z (GMT). 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