Prairie restoration is costly and complex with many methods and types. The use of technology to enhance, economize and simplify prairie restorations is highly desirable, as is the ability to gauge restoration success. The program Maxent allows for an interpretation of data that may facilitate the prediction of plant species composition from species functional traits in different ages of prairie restorations. The inexpensive and diverse nature of Maxent makes it advantageous to restoration managers allowing them to manage expenditures in the field. Maxent determines if specific species trait values and abundance concur with the aggregate trait values of a site. The aggregate trait values of a site are assumed to be the result of natural selection and are used to predict the species composition based on functional trait values of the different species. The objective of this this study was to apply this technique to plant functional traits in Midwest prairie restorations. The technique was applied to data from 11 sites in 8 restoration locations in Illinois. Restorations ranged from 3 to 45 years of age and two remnant site >100 years of age. Six functional traits were measured for 31 dominant perennial plant species. Plant functional traits can be used to estimate prairie restoration species composition by predicting the relative percent cover based on the age of a site Although Maxent’s performance in predicting plant species composition varied among sites, its performance in predicting relative percent cover of species present at sites was good (R2 = 0.62, P < 0.001). In restorations younger than 30 years the most abundant species were Solidago altissma, Poa pratensis, Solidago rigida, and Andropogon gerardii. Older sites were much more varied in their species composition with no species being dominant in the older sites. Maxent correctly predicted at least 50% of the dominant species in 7 out of 11 of the sites. The sites with most accurate predictions of species composition were from 13 to 45 years in age, with > 50% of the dominant species correctly predicted.
","abstract_html":"<p>Prairie restoration is costly and complex with many methods and types. The use of technology to enhance, economize and simplify prairie restorations is highly desirable, as is the ability to gauge restoration success. The program Maxent allows for an interpretation of data that may facilitate the prediction of plant species composition from species functional traits in different ages of prairie restorations. The inexpensive and diverse nature of Maxent makes it advantageous to restoration managers allowing them to manage expenditures in the field. Maxent determines if specific species trait values and abundance concur with the aggregate trait values of a site. The aggregate trait values of a site are assumed to be the result of natural selection and are used to predict the species composition based on functional trait values of the different species. The objective of this this study was to apply this technique to plant functional traits in Midwest prairie restorations. The technique was applied to data from 11 sites in 8 restoration locations in Illinois. Restorations ranged from 3 to 45 years of age and two remnant site >100 years of age. Six functional traits were measured for 31 dominant perennial plant species. Plant functional traits can be used to estimate prairie restoration species composition by predicting the relative percent cover based on the age of a site Although Maxent’s performance in predicting plant species composition varied among sites, its performance in predicting relative percent cover of species present at sites was good (R2 = 0.62, P < 0.001). In restorations younger than 30 years the most abundant species were Solidago altissma, Poa pratensis, Solidago rigida, and Andropogon gerardii. Older sites were much more varied in their species composition with no species being dominant in the older sites. Maxent correctly predicted at least 50% of the dominant species in 7 out of 11 of the sites. The sites with most accurate predictions of species composition were from 13 to 45 years in age, with > 50% of the dominant species correctly predicted.</p>","abstract_has_math":false,"creators":["Schreurs, Rebecca"],"institution":null,"degree_name":"Master of Science","degree_level":"Thesis","degree_discipline":"Environmental Biology","degree_department":null,"school":null,"contributors":["Mary E. Carrington, Ph.D.","Phyllis Klingensmith, Ph.D.","Erin Grey-Avis, Ph.D."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-07-01T07:00:00Z","date_published":"2015-07-01T07:00:00Z","updated_at":"2026-07-24T02:24:36Z","subjects":["Maxent","plant species composition","prairie restoration","Plant Sciences"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://opus.govst.edu/theses/64","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Mary E. Carrington, Ph.D.","Phyllis Klingensmith, Ph.D.","Erin Grey-Avis, Ph.D."]},{"key":"dc:creator","label":"Author","values":["Schreurs, Rebecca"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2015-08-31T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Environmental Biology"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Maxent","plant species composition","prairie restoration","Plant Sciences"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://opus.govst.edu/theses/64"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Prairie restoration is costly and complex with many methods and types. The use of technology to enhance, economize and simplify prairie restorations is highly desirable, as is the ability to gauge restoration success. The program Maxent allows for an interpretation of data that may facilitate the prediction of plant species composition from species functional traits in different ages of prairie restorations. The inexpensive and diverse nature of Maxent makes it advantageous to restoration managers allowing them to manage expenditures in the field. Maxent determines if specific species trait values and abundance concur with the aggregate trait values of a site. The aggregate trait values of a site are assumed to be the result of natural selection and are used to predict the species composition based on functional trait values of the different species. The objective of this this study was to apply this technique to plant functional traits in Midwest prairie restorations. The technique was applied to data from 11 sites in 8 restoration locations in Illinois. Restorations ranged from 3 to 45 years of age and two remnant site >100 years of age. Six functional traits were measured for 31 dominant perennial plant species. Plant functional traits can be used to estimate prairie restoration species composition by predicting the relative percent cover based on the age of a site Although Maxent’s performance in predicting plant species composition varied among sites, its performance in predicting relative percent cover of species present at sites was good (R2 = 0.62, P < 0.001). In restorations younger than 30 years the most abundant species were Solidago altissma, Poa pratensis, Solidago rigida, and Andropogon gerardii. Older sites were much more varied in their species composition with no species being dominant in the older sites. Maxent correctly predicted at least 50% of the dominant species in 7 out of 11 of the sites. The sites with most accurate predictions of species composition were from 13 to 45 years in age, with > 50% of the dominant species correctly predicted.
"]},{"key":"dc:title","label":"Title","values":["Using Plant Functional Traits to Estimate Prairie Restoration Species Composition"]}]}],"canonical_facts":{"dc:contributor":["Mary E. Carrington, Ph.D.","Phyllis Klingensmith, Ph.D.","Erin Grey-Avis, Ph.D."],"dc:creator":["Schreurs, Rebecca"],"dc:date.available":["2015-08-31T07:00:00Z"],"dc:description.abstract":["Prairie restoration is costly and complex with many methods and types. The use of technology to enhance, economize and simplify prairie restorations is highly desirable, as is the ability to gauge restoration success. The program Maxent allows for an interpretation of data that may facilitate the prediction of plant species composition from species functional traits in different ages of prairie restorations. The inexpensive and diverse nature of Maxent makes it advantageous to restoration managers allowing them to manage expenditures in the field. Maxent determines if specific species trait values and abundance concur with the aggregate trait values of a site. The aggregate trait values of a site are assumed to be the result of natural selection and are used to predict the species composition based on functional trait values of the different species. The objective of this this study was to apply this technique to plant functional traits in Midwest prairie restorations. The technique was applied to data from 11 sites in 8 restoration locations in Illinois. Restorations ranged from 3 to 45 years of age and two remnant site >100 years of age. Six functional traits were measured for 31 dominant perennial plant species. Plant functional traits can be used to estimate prairie restoration species composition by predicting the relative percent cover based on the age of a site Although Maxent’s performance in predicting plant species composition varied among sites, its performance in predicting relative percent cover of species present at sites was good (R2 = 0.62, P < 0.001). In restorations younger than 30 years the most abundant species were Solidago altissma, Poa pratensis, Solidago rigida, and Andropogon gerardii. Older sites were much more varied in their species composition with no species being dominant in the older sites. Maxent correctly predicted at least 50% of the dominant species in 7 out of 11 of the sites. The sites with most accurate predictions of species composition were from 13 to 45 years in age, with > 50% of the dominant species correctly predicted.
"],"dc:identifier":["https://opus.govst.edu/theses/64"],"dc:subject":["Maxent","plant species composition","prairie restoration","Plant Sciences"],"dc:title":["Using Plant Functional Traits to Estimate Prairie Restoration Species Composition"],"thesis:degree_discipline":["Environmental Biology"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["Master of Science"]},"updated_at":"2026-07-24T02:24:36Z"}