Matches in SemOpenAlex for { <https://semopenalex.org/work/W2324316112> ?p ?o ?g. }
- W2324316112 endingPage "174" @default.
- W2324316112 startingPage "159" @default.
- W2324316112 abstract "MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 500:159-174 (2014) - DOI: https://doi.org/10.3354/meps10659 Multivariate random forest models of estuarine-associated fish and invertebrate communities Katharine Miller1,*, Falk Huettmann2, Brenda Norcross3, Mitch Lorenz1 1Auke Bay Laboratories, National Marine Fisheries Service, Juneau, Alaska, USA 2Institute of Arctic Biology, University of Alaska, Fairbanks, Alaska, USA 3School of Fishery and Ocean Science, University of Alaska, Fairbanks, Alaska, USA *Corresponding author: katharine.miller@noaa.gov ABSTRACT: Models that evaluate species-habitat relationships at the community level have been gaining attention with increasing interest in ecosystem management. Developing models that can incorporate both a large number of predictor variables and a multivariate response (a vector of individual species occurrences or abundances) is challenging. One promising new approach is multivariate random forests (MRF), a method that combines multivariate regression trees with bootstrap resampling and predictor subsampling from traditional random forests. Random forest models have been shown to be highly accurate and powerful in their predictive ability in a wide variety of applications. They can effectively model nonlinear and interacting variables. Our research evaluated change in estuarine assemblage composition along habitat gradients in Southeast Alaska using landscape-scale habitat variables and MRF. For 541 estuaries, we identified 24 predictor variables describing the geomorphic and habitat environment on land and in the estuary. MRF models were constructed in R software for combined fish and invertebrate assemblages. Cluster analysis of model proximities revealed strong spatial variation in community composition in relation to differences in tidal range, precipitation, percent of eelgrass, and amount of intertidal habitat. This research presents a new science-based management template that can be used to inform and assess species management and protection strategies, as well as to guide future research on species distributions. KEY WORDS: Estuaries · Multivariate models · Random forest Full text in pdf format PreviousNextCite this article as: Miller K, Huettmann F, Norcross B, Lorenz M (2014) Multivariate random forest models of estuarine-associated fish and invertebrate communities. Mar Ecol Prog Ser 500:159-174. https://doi.org/10.3354/meps10659 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 500. Online publication date: March 17, 2014 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2014 Inter-Research." @default.
- W2324316112 created "2016-06-24" @default.
- W2324316112 creator A5036964649 @default.
- W2324316112 creator A5044649152 @default.
- W2324316112 creator A5070097821 @default.
- W2324316112 creator A5070138135 @default.
- W2324316112 date "2014-03-17" @default.
- W2324316112 modified "2023-10-18" @default.
- W2324316112 title "Multivariate random forest models of estuarine-associated fish and invertebrate communities" @default.
- W2324316112 cites W1493454437 @default.
- W2324316112 cites W1539593569 @default.
- W2324316112 cites W1571991676 @default.
- W2324316112 cites W1582127161 @default.
- W2324316112 cites W1907754837 @default.
- W2324316112 cites W1969293743 @default.
- W2324316112 cites W1976482792 @default.
- W2324316112 cites W1985157821 @default.
- W2324316112 cites W1987971958 @default.
- W2324316112 cites W1995621854 @default.
- W2324316112 cites W2007250969 @default.
- W2324316112 cites W2014063077 @default.
- W2324316112 cites W2015385415 @default.
- W2324316112 cites W2017833632 @default.
- W2324316112 cites W2017940013 @default.
- W2324316112 cites W2018932184 @default.
- W2324316112 cites W2021449370 @default.
- W2324316112 cites W2022126091 @default.
- W2324316112 cites W2023003096 @default.
- W2324316112 cites W2025992337 @default.
- W2324316112 cites W2026842372 @default.
- W2324316112 cites W2034742551 @default.
- W2324316112 cites W2035338334 @default.
- W2324316112 cites W2046250663 @default.
- W2324316112 cites W2046573926 @default.
- W2324316112 cites W2056099846 @default.
- W2324316112 cites W2064203403 @default.
- W2324316112 cites W2066962270 @default.
- W2324316112 cites W2077604304 @default.
- W2324316112 cites W2079119691 @default.
- W2324316112 cites W2080086266 @default.
- W2324316112 cites W2084714454 @default.
- W2324316112 cites W2086233955 @default.
- W2324316112 cites W2091039482 @default.
- W2324316112 cites W2093178337 @default.
- W2324316112 cites W2097601813 @default.
- W2324316112 cites W2098004420 @default.
- W2324316112 cites W2100845728 @default.
- W2324316112 cites W2102746137 @default.
- W2324316112 cites W2106752684 @default.
- W2324316112 cites W2108564216 @default.
- W2324316112 cites W2110830553 @default.
- W2324316112 cites W2118831643 @default.
- W2324316112 cites W2126047128 @default.
- W2324316112 cites W2139086914 @default.
- W2324316112 cites W2141145624 @default.
- W2324316112 cites W2144749488 @default.
- W2324316112 cites W2150523054 @default.
- W2324316112 cites W2155261478 @default.
- W2324316112 cites W2155734613 @default.
- W2324316112 cites W2164595573 @default.
- W2324316112 cites W2166708527 @default.
- W2324316112 cites W2167332176 @default.
- W2324316112 cites W2483640719 @default.
- W2324316112 cites W2911964244 @default.
- W2324316112 cites W323945736 @default.
- W2324316112 doi "https://doi.org/10.3354/meps10659" @default.
- W2324316112 hasPublicationYear "2014" @default.
- W2324316112 type Work @default.
- W2324316112 sameAs 2324316112 @default.
- W2324316112 citedByCount "18" @default.
- W2324316112 countsByYear W23243161122014 @default.
- W2324316112 countsByYear W23243161122015 @default.
- W2324316112 countsByYear W23243161122016 @default.
- W2324316112 countsByYear W23243161122017 @default.
- W2324316112 countsByYear W23243161122018 @default.
- W2324316112 countsByYear W23243161122019 @default.
- W2324316112 countsByYear W23243161122020 @default.
- W2324316112 countsByYear W23243161122021 @default.
- W2324316112 countsByYear W23243161122022 @default.
- W2324316112 countsByYear W23243161122023 @default.
- W2324316112 crossrefType "journal-article" @default.
- W2324316112 hasAuthorship W2324316112A5036964649 @default.
- W2324316112 hasAuthorship W2324316112A5044649152 @default.
- W2324316112 hasAuthorship W2324316112A5070097821 @default.
- W2324316112 hasAuthorship W2324316112A5070138135 @default.
- W2324316112 hasConcept C119857082 @default.
- W2324316112 hasConcept C161584116 @default.
- W2324316112 hasConcept C185933670 @default.
- W2324316112 hasConcept C18903297 @default.
- W2324316112 hasConcept C205649164 @default.
- W2324316112 hasConcept C39432304 @default.
- W2324316112 hasConcept C41008148 @default.
- W2324316112 hasConcept C505870484 @default.
- W2324316112 hasConcept C86803240 @default.
- W2324316112 hasConcept C88160329 @default.
- W2324316112 hasConceptScore W2324316112C119857082 @default.
- W2324316112 hasConceptScore W2324316112C161584116 @default.
- W2324316112 hasConceptScore W2324316112C185933670 @default.