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Predicting ecosystem components in the Gulf of Mexico and their responses to climate variability with a dynamic Bayesian network model
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CITE Title : Predicting ecosystem components in the Gulf of Mexico and their responses to climate variability with a dynamic Bayesian network model Personal Author(s) : Trifonova, N.;Karnauskas, M.;Kelble, C.; Published Date : 2019 Source : PLOS ONE, 14(1), 23. DOI : http://dx.doi.org/10.1371/journal.pone.0209257 Journal Title : PLOS ONE
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Trifonova, N. ; Karnauskas, M. ; ...
2019 | PLOS ONE, 14(1), 23.
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The Gulf of Mexico is an ecologically and economically important marine ecosystem that is affected by a variety of natural and anthropogenic pressures...
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Uncovering ecological state dynamics with hidden Markov models
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CITE Title : Uncovering ecological state dynamics with hidden Markov models Personal Author(s) : McClintock, B.T.;Langrock, R.;Gimenez, O.;Cam, E.;Borchers, D. L.;Glennie, R.;Patterson, T. A.; Published Date : 2020 Source : Ecology Letters, 23(12), 1878-1903 DOI : https://doi.org/10.1111/ele.13610 Journal Title : Ecology Letters
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McClintock, B.T. ; Langrock, R. ; ...
2020 | Ecology Letters, 23(12), 1878-1903
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Ecological systems can often be characterised by changes among a finite set of underlying states pertaining to individuals, populations, communities o...
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[PDF - 2.44 MB]