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Assessment on latitudinal tree species richness using environmental factors in the southeastern United States

The southeastern region of the United States exhibits an unusual trend of decreasing tree species richness (TSR) from higher to lower latitudes over the Florida peninsula. This trend contradicts the widely marked latitudinal diversity gradient where species richness is highest in tropical zones and...

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Autores principales: Kwon, Youngsang, Lee, Taesoo, Lang, Alison, Burnette, Dorian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6475148/
https://www.ncbi.nlm.nih.gov/pubmed/31024776
http://dx.doi.org/10.7717/peerj.6781
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author Kwon, Youngsang
Lee, Taesoo
Lang, Alison
Burnette, Dorian
author_facet Kwon, Youngsang
Lee, Taesoo
Lang, Alison
Burnette, Dorian
author_sort Kwon, Youngsang
collection PubMed
description The southeastern region of the United States exhibits an unusual trend of decreasing tree species richness (TSR) from higher to lower latitudes over the Florida peninsula. This trend contradicts the widely marked latitudinal diversity gradient where species richness is highest in tropical zones and decreases towards extratropical regions. This study aims to assess the environmental factors that prompt this atypical inverse latitudinal gradient seen in TSR using the USDA Forest Service’s Forest Inventory and Analysis (FIA) database. Fifteen variables under four categories of forested area, groundwater, soil properties, and climate groups were examined to model TSR in the region. Generalized linear models (GLMs) with Poisson distributions first assessed individual variables to test explanatory power then the LASSO regularization method was utilized to extract two subsets of the most influential variables to predict TSR. Forest area and four climate variables (mean annual temperature, precipitation seasonality, mean temperature of coldest quarter, and mean precipitation of driest quarter) were the top five variables during the initial GLM assessment implying their potential individual influence in regulating TSR. Two subsets of LASSO models contained seven and three predictor variables, respectively. Frist subset includes seven predictors, presented in highest to low standardized coefficient, mean temperature of coldest quarter, forested area, precipitation seasonality, mean precipitation of driest quarter, water table depth, spodosol, and available water storage. The other subset further excluded four lowest influential variables from the first set, leaving the top three variables from the first subset. The first subset of the LASSO model predicted TSR with 63.4% explained deviance while the second subset reproduced 60.2% of deviance explained. With only three variables used, the second model outperformed the first model evaluated by the AIC value. We conclude that forest patch area, mean temperature of coldest quarter, and precipitation seasonality are the highly influential variables of TSR among environmental factors in the southeastern region of U.S., but evolutionary or historic cause should be further incorporated to fully understand tree species diversity pattern in this region.
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spelling pubmed-64751482019-04-25 Assessment on latitudinal tree species richness using environmental factors in the southeastern United States Kwon, Youngsang Lee, Taesoo Lang, Alison Burnette, Dorian PeerJ Biogeography The southeastern region of the United States exhibits an unusual trend of decreasing tree species richness (TSR) from higher to lower latitudes over the Florida peninsula. This trend contradicts the widely marked latitudinal diversity gradient where species richness is highest in tropical zones and decreases towards extratropical regions. This study aims to assess the environmental factors that prompt this atypical inverse latitudinal gradient seen in TSR using the USDA Forest Service’s Forest Inventory and Analysis (FIA) database. Fifteen variables under four categories of forested area, groundwater, soil properties, and climate groups were examined to model TSR in the region. Generalized linear models (GLMs) with Poisson distributions first assessed individual variables to test explanatory power then the LASSO regularization method was utilized to extract two subsets of the most influential variables to predict TSR. Forest area and four climate variables (mean annual temperature, precipitation seasonality, mean temperature of coldest quarter, and mean precipitation of driest quarter) were the top five variables during the initial GLM assessment implying their potential individual influence in regulating TSR. Two subsets of LASSO models contained seven and three predictor variables, respectively. Frist subset includes seven predictors, presented in highest to low standardized coefficient, mean temperature of coldest quarter, forested area, precipitation seasonality, mean precipitation of driest quarter, water table depth, spodosol, and available water storage. The other subset further excluded four lowest influential variables from the first set, leaving the top three variables from the first subset. The first subset of the LASSO model predicted TSR with 63.4% explained deviance while the second subset reproduced 60.2% of deviance explained. With only three variables used, the second model outperformed the first model evaluated by the AIC value. We conclude that forest patch area, mean temperature of coldest quarter, and precipitation seasonality are the highly influential variables of TSR among environmental factors in the southeastern region of U.S., but evolutionary or historic cause should be further incorporated to fully understand tree species diversity pattern in this region. PeerJ Inc. 2019-04-17 /pmc/articles/PMC6475148/ /pubmed/31024776 http://dx.doi.org/10.7717/peerj.6781 Text en ©2019 Kwon et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Biogeography
Kwon, Youngsang
Lee, Taesoo
Lang, Alison
Burnette, Dorian
Assessment on latitudinal tree species richness using environmental factors in the southeastern United States
title Assessment on latitudinal tree species richness using environmental factors in the southeastern United States
title_full Assessment on latitudinal tree species richness using environmental factors in the southeastern United States
title_fullStr Assessment on latitudinal tree species richness using environmental factors in the southeastern United States
title_full_unstemmed Assessment on latitudinal tree species richness using environmental factors in the southeastern United States
title_short Assessment on latitudinal tree species richness using environmental factors in the southeastern United States
title_sort assessment on latitudinal tree species richness using environmental factors in the southeastern united states
topic Biogeography
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6475148/
https://www.ncbi.nlm.nih.gov/pubmed/31024776
http://dx.doi.org/10.7717/peerj.6781
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