Diet analysis using generalized linear models derived from foraging processes using R package mvtweedie
Diet analysis integrates a wide variety of visual, chemical, and biological identification of prey. Samples are often treated as compositional data, where each prey is analyzed as a continuous percentage of the total. However, analyzing compositional data results in analytical challenges, for exampl...
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2022
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Online Access: | http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9286827/ http://www.ncbi.nlm.nih.gov/pubmed/35060624 https://doi.org/10.1002/ecy.3637 |
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ftpubmed:oai:pubmedcentral.nih.gov:9286827 2023-05-15T15:50:33+02:00 Diet analysis using generalized linear models derived from foraging processes using R package mvtweedie Thorson, James T. Arimitsu, Mayumi L. Levi, Taal Roffler, Gretchen H. 2022-03-16 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9286827/ http://www.ncbi.nlm.nih.gov/pubmed/35060624 https://doi.org/10.1002/ecy.3637 en eng John Wiley & Sons, Inc. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9286827/ http://www.ncbi.nlm.nih.gov/pubmed/35060624 http://dx.doi.org/10.1002/ecy.3637 © 2022 The Authors. Ecology published by Wiley Periodicals LLC on behalf of The Ecological Society of America. This article has been contributed to by US Government employees and their work is in the public domain in the USA. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. PDM CC-BY Ecology Statistical Reports Text 2022 ftpubmed https://doi.org/10.1002/ecy.3637 2022-07-31T01:45:07Z Diet analysis integrates a wide variety of visual, chemical, and biological identification of prey. Samples are often treated as compositional data, where each prey is analyzed as a continuous percentage of the total. However, analyzing compositional data results in analytical challenges, for example, highly parameterized models or prior transformation of data. Here, we present a novel approximation involving a Tweedie generalized linear model (GLM). We first review how this approximation emerges from considering predator foraging as a thinned and marked point process (with marks representing prey species and individual prey size). This derivation can motivate future theoretical and applied developments. We then provide a practical tutorial for the Tweedie GLM using new package mvtweedie that extends capabilities of widely used packages in R (mgcv and ggplot2) by transforming output to calculate prey compositions. We demonstrate this approach and software using two examples. Tufted Puffins (Fratercula cirrhata) provisioning their chicks on a colony in the northern Gulf of Alaska show decadal prey switching among sand lance and prowfish (1980–2000) and then Pacific herring and capelin (2000–2020), while wolves (Canis lupus ligoni) in southeast Alaska forage on mountain goats and marmots in northern uplands and marine mammals in seaward island coastlines. Text Canis lupus fratercula Alaska PubMed Central (PMC) Gulf of Alaska Pacific Ecology 103 5 |
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English |
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Statistical Reports |
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Statistical Reports Thorson, James T. Arimitsu, Mayumi L. Levi, Taal Roffler, Gretchen H. Diet analysis using generalized linear models derived from foraging processes using R package mvtweedie |
topic_facet |
Statistical Reports |
description |
Diet analysis integrates a wide variety of visual, chemical, and biological identification of prey. Samples are often treated as compositional data, where each prey is analyzed as a continuous percentage of the total. However, analyzing compositional data results in analytical challenges, for example, highly parameterized models or prior transformation of data. Here, we present a novel approximation involving a Tweedie generalized linear model (GLM). We first review how this approximation emerges from considering predator foraging as a thinned and marked point process (with marks representing prey species and individual prey size). This derivation can motivate future theoretical and applied developments. We then provide a practical tutorial for the Tweedie GLM using new package mvtweedie that extends capabilities of widely used packages in R (mgcv and ggplot2) by transforming output to calculate prey compositions. We demonstrate this approach and software using two examples. Tufted Puffins (Fratercula cirrhata) provisioning their chicks on a colony in the northern Gulf of Alaska show decadal prey switching among sand lance and prowfish (1980–2000) and then Pacific herring and capelin (2000–2020), while wolves (Canis lupus ligoni) in southeast Alaska forage on mountain goats and marmots in northern uplands and marine mammals in seaward island coastlines. |
format |
Text |
author |
Thorson, James T. Arimitsu, Mayumi L. Levi, Taal Roffler, Gretchen H. |
author_facet |
Thorson, James T. Arimitsu, Mayumi L. Levi, Taal Roffler, Gretchen H. |
author_sort |
Thorson, James T. |
title |
Diet analysis using generalized linear models derived from foraging processes using R package mvtweedie |
title_short |
Diet analysis using generalized linear models derived from foraging processes using R package mvtweedie |
title_full |
Diet analysis using generalized linear models derived from foraging processes using R package mvtweedie |
title_fullStr |
Diet analysis using generalized linear models derived from foraging processes using R package mvtweedie |
title_full_unstemmed |
Diet analysis using generalized linear models derived from foraging processes using R package mvtweedie |
title_sort |
diet analysis using generalized linear models derived from foraging processes using r package mvtweedie |
publisher |
John Wiley & Sons, Inc. |
publishDate |
2022 |
url |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9286827/ http://www.ncbi.nlm.nih.gov/pubmed/35060624 https://doi.org/10.1002/ecy.3637 |
geographic |
Gulf of Alaska Pacific |
geographic_facet |
Gulf of Alaska Pacific |
genre |
Canis lupus fratercula Alaska |
genre_facet |
Canis lupus fratercula Alaska |
op_source |
Ecology |
op_relation |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9286827/ http://www.ncbi.nlm.nih.gov/pubmed/35060624 http://dx.doi.org/10.1002/ecy.3637 |
op_rights |
© 2022 The Authors. Ecology published by Wiley Periodicals LLC on behalf of The Ecological Society of America. This article has been contributed to by US Government employees and their work is in the public domain in the USA. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
op_rightsnorm |
PDM CC-BY |
op_doi |
https://doi.org/10.1002/ecy.3637 |
container_title |
Ecology |
container_volume |
103 |
container_issue |
5 |
_version_ |
1766385522151784448 |