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Quantifying Environmental Limiting Factors on Tree Cover Using Geospatial Data
Environmental limiting factors (ELFs) are the thresholds that determine the maximum or minimum biological response for a given suite of environmental conditions. We asked the following questions: 1) Can we detect ELFs on percent tree cover across the eastern slopes of the Lake Tahoe Basin, NV? 2) Ho...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4333833/ https://www.ncbi.nlm.nih.gov/pubmed/25692604 http://dx.doi.org/10.1371/journal.pone.0114648 |
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author | Greenberg, Jonathan A. Santos, Maria J. Dobrowski, Solomon Z. Vanderbilt, Vern C. Ustin, Susan L. |
author_facet | Greenberg, Jonathan A. Santos, Maria J. Dobrowski, Solomon Z. Vanderbilt, Vern C. Ustin, Susan L. |
author_sort | Greenberg, Jonathan A. |
collection | PubMed |
description | Environmental limiting factors (ELFs) are the thresholds that determine the maximum or minimum biological response for a given suite of environmental conditions. We asked the following questions: 1) Can we detect ELFs on percent tree cover across the eastern slopes of the Lake Tahoe Basin, NV? 2) How are the ELFs distributed spatially? 3) To what extent are unmeasured environmental factors limiting tree cover? ELFs are difficult to quantify as they require significant sample sizes. We addressed this by using geospatial data over a relatively large spatial extent, where the wall-to-wall sampling ensures the inclusion of rare data points which define the minimum or maximum response to environmental factors. We tested mean temperature, minimum temperature, potential evapotranspiration (PET) and PET minus precipitation (PET-P) as potential limiting factors on percent tree cover. We found that the study area showed system-wide limitations on tree cover, and each of the factors showed evidence of being limiting on tree cover. However, only 1.2% of the total area appeared to be limited by the four (4) environmental factors, suggesting other unmeasured factors are limiting much of the tree cover in the study area. Where sites were near their theoretical maximum, non-forest sites (tree cover < 25%) were primarily limited by cold mean temperatures, open-canopy forest sites (tree cover between 25% and 60%) were primarily limited by evaporative demand, and closed-canopy forests were not limited by any particular environmental factor. The detection of ELFs is necessary in order to fully understand the width of limitations that species experience within their geographic range. |
format | Online Article Text |
id | pubmed-4333833 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-43338332015-02-24 Quantifying Environmental Limiting Factors on Tree Cover Using Geospatial Data Greenberg, Jonathan A. Santos, Maria J. Dobrowski, Solomon Z. Vanderbilt, Vern C. Ustin, Susan L. PLoS One Research Article Environmental limiting factors (ELFs) are the thresholds that determine the maximum or minimum biological response for a given suite of environmental conditions. We asked the following questions: 1) Can we detect ELFs on percent tree cover across the eastern slopes of the Lake Tahoe Basin, NV? 2) How are the ELFs distributed spatially? 3) To what extent are unmeasured environmental factors limiting tree cover? ELFs are difficult to quantify as they require significant sample sizes. We addressed this by using geospatial data over a relatively large spatial extent, where the wall-to-wall sampling ensures the inclusion of rare data points which define the minimum or maximum response to environmental factors. We tested mean temperature, minimum temperature, potential evapotranspiration (PET) and PET minus precipitation (PET-P) as potential limiting factors on percent tree cover. We found that the study area showed system-wide limitations on tree cover, and each of the factors showed evidence of being limiting on tree cover. However, only 1.2% of the total area appeared to be limited by the four (4) environmental factors, suggesting other unmeasured factors are limiting much of the tree cover in the study area. Where sites were near their theoretical maximum, non-forest sites (tree cover < 25%) were primarily limited by cold mean temperatures, open-canopy forest sites (tree cover between 25% and 60%) were primarily limited by evaporative demand, and closed-canopy forests were not limited by any particular environmental factor. The detection of ELFs is necessary in order to fully understand the width of limitations that species experience within their geographic range. Public Library of Science 2015-02-18 /pmc/articles/PMC4333833/ /pubmed/25692604 http://dx.doi.org/10.1371/journal.pone.0114648 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration, which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. |
spellingShingle | Research Article Greenberg, Jonathan A. Santos, Maria J. Dobrowski, Solomon Z. Vanderbilt, Vern C. Ustin, Susan L. Quantifying Environmental Limiting Factors on Tree Cover Using Geospatial Data |
title | Quantifying Environmental Limiting Factors on Tree Cover Using Geospatial Data |
title_full | Quantifying Environmental Limiting Factors on Tree Cover Using Geospatial Data |
title_fullStr | Quantifying Environmental Limiting Factors on Tree Cover Using Geospatial Data |
title_full_unstemmed | Quantifying Environmental Limiting Factors on Tree Cover Using Geospatial Data |
title_short | Quantifying Environmental Limiting Factors on Tree Cover Using Geospatial Data |
title_sort | quantifying environmental limiting factors on tree cover using geospatial data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4333833/ https://www.ncbi.nlm.nih.gov/pubmed/25692604 http://dx.doi.org/10.1371/journal.pone.0114648 |
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