{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,19]],"date-time":"2026-10-19T03:23:26Z","timestamp":1792380206102,"version":"4.4.0"},"reference-count":41,"publisher":"PeerJ","license":[{"start":{"date-parts":[[2019,11,12]],"date-time":"2019-11-12T00:00:00Z","timestamp":1573516800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/publicdomain\/zero\/1.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:p>Lake trophic state classifications provide information about the condition of lentic ecosystems and are indicative of both ecosystem services (e.g., clean water, recreational opportunities, and aesthetics) and disservices (e.g., cyanobacteria blooms). The current classification schemes have been criticized for developing indices that are single-variable based (vs. a complex aggregate of multi-variables), discrete (vs. a continuous), and\/or deterministic (vs. an inherently random). We present an updated lake trophic classification model using a Bayesian multilevel ordered categorical regression. The model consists of a proportional odds logistic regression (POLR) that models ordered, categorical, lake trophic state using Secchi disk depth, elevation, nitrogen concentration (N), and phosphorus concentration (P). The overall accuracy, when compared to existing classifications of trophic state index (TSI), for the POLR model was 0.68 and the balanced accuracy ranged between 0.72 and 0.93. This work delivers an index that is multi-variable based, continuous, and classifies lakes in probabilistic terms. While our model addresses aforementioned limitations of the current approach to lake trophic classification, the addition of uncertainty quantification is important, because the trophic state response to predictors varies among lakes. Our model successfully addresses concerns with the current approach and performs well across trophic states in a large spatial extent.<\/jats:p>","DOI":"10.7717\/peerj.7936","type":"journal-article","created":{"date-parts":[[2019,11,12]],"date-time":"2019-11-12T06:08:31Z","timestamp":1573538911000},"page":"e7936","source":"Crossref","is-referenced-by-count":22,"title":["Rethinking the lake trophic state index"],"prefix":"10.7717","volume":"7","author":[{"given":"Farnaz","family":"Nojavan A.","sequence":"first","affiliation":[{"name":"ORISE, Environmental Protection Agency, Office of Research and Development, Center for Environmental Measurement and Modeling, Atlantic Coastal Environmental Sciences Division,  Narragansett, RI, United States of America"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Betty J.","family":"Kreakie","sequence":"additional","affiliation":[{"name":"Environmental Protection Agency, Office of Research and Development, Center for Environmental Measurement and Modeling, Atlantic Coastal Environmental Sciences Division, Narragansett, RI,  United States of America"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jeffrey W.","family":"Hollister","sequence":"additional","affiliation":[{"name":"Environmental Protection Agency, Office of Research and Development, Center for Environmental Measurement and Modeling, Atlantic Coastal Environmental Sciences Division, Narragansett, RI,  United States of America"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Song S.","family":"Qian","sequence":"additional","affiliation":[{"name":"Department of Environmental Sciences, The University of Toledo, Toledo, OH, United States of America"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"4443","published-online":{"date-parts":[[2019,11,12]]},"reference":[{"issue":"1","key":"10.7717\/peerj.7936\/ref-1","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Machine Learning"},{"issue":"1","key":"10.7717\/peerj.7936\/ref-2","doi-asserted-by":"publisher","first-page":"441","DOI":"10.1080\/07438148409354553","article-title":"Trophic state indices: rationale for multivariate approaches","volume":"1","author":"Brezonik","year":"1984","journal-title":"Lake and Reservoir Management"},{"issue":"2","key":"10.7717\/peerj.7936\/ref-3","doi-asserted-by":"publisher","first-page":"361","DOI":"10.4319\/lo.1977.22.2.0361","article-title":"A trophic state index for lakes","volume":"22","author":"Carlson","year":"1977","journal-title":"Limnology and Oceanography"},{"issue":"1","key":"10.7717\/peerj.7936\/ref-4","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1080\/07438140509354418","article-title":"Simple graphical methods for the interpretation of relationships between trophic state variables","volume":"21","author":"Carlson","year":"2005","journal-title":"Lake and Reservoir Management"},{"key":"10.7717\/peerj.7936\/ref-5","first-page":"305","article-title":"A coordinators guide to volunteer lake monitoring methods","volume":"96","author":"Carlson","year":"1996","journal-title":"North American Lake Management Society"},{"issue":"5917","key":"10.7717\/peerj.7936\/ref-6","doi-asserted-by":"publisher","first-page":"1014","DOI":"10.1126\/science.1167755","article-title":"Controlling eutrophication: nitrogen and phosphorus","volume":"323","author":"Conley","year":"2009","journal-title":"Science"},{"issue":"15","key":"10.7717\/peerj.7936\/ref-7","doi-asserted-by":"publisher","first-page":"2865","DOI":"10.1002\/sim.3107","article-title":"Scaling regression inputs by dividing by two standard deviations","volume":"27","author":"Gelman","year":"2008","journal-title":"Statistics in Medicine"},{"key":"10.7717\/peerj.7936\/ref-8","volume-title":"Bayesian data analysis","volume":"Vol. 2","author":"Gelman","year":"2014"},{"key":"10.7717\/peerj.7936\/ref-9","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9780511790942","volume-title":"Data analysis using regression and multilevel\/hierarchical models","author":"Gelman","year":"2006"},{"key":"10.7717\/peerj.7936\/ref-10","volume-title":"Data analysis using regression and multilevel\/hierarchical models","author":"Gelman","year":"2007"},{"key":"10.7717\/peerj.7936\/ref-11","first-page":"1","article-title":"Package \u2018arm\u2019: data analysis using regression and multilevel\/hierarchical models. 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