Regional mapping of species‐level continuous foliar cover: beyond categorical vegetation mapping

The ability to quantify spatial patterns and detect change in terrestrial vegetation across large landscapes depends on linking ground‐based measurements of vegetation to remotely sensed data. Unlike non‐overlapping categorical vegetation types (i.e., typical vegetation and land cover maps), species...

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Published in:Ecological Applications
Main Authors: Nawrocki, Timm W., Carlson, Matthew L., Osnas, Jeanne L. D., Trammell, E. Jamie, Witmer, Frank D. W.
Format: Text
Language:English
Published: John Wiley and Sons Inc. 2020
Subjects:
Online Access:http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7317374/
http://www.ncbi.nlm.nih.gov/pubmed/31971646
https://doi.org/10.1002/eap.2081
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spelling ftpubmed:oai:pubmedcentral.nih.gov:7317374 2023-05-15T15:00:54+02:00 Regional mapping of species‐level continuous foliar cover: beyond categorical vegetation mapping Nawrocki, Timm W. Carlson, Matthew L. Osnas, Jeanne L. D. Trammell, E. Jamie Witmer, Frank D. W. 2020-02-24 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7317374/ http://www.ncbi.nlm.nih.gov/pubmed/31971646 https://doi.org/10.1002/eap.2081 en eng John Wiley and Sons Inc. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7317374/ http://www.ncbi.nlm.nih.gov/pubmed/31971646 http://dx.doi.org/10.1002/eap.2081 © 2020 The Authors. Ecological Applications published by Wiley Periodicals, Inc. on behalf of Ecological Society of America This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. CC-BY Ecol Appl Articles Text 2020 ftpubmed https://doi.org/10.1002/eap.2081 2020-07-05T00:46:10Z The ability to quantify spatial patterns and detect change in terrestrial vegetation across large landscapes depends on linking ground‐based measurements of vegetation to remotely sensed data. Unlike non‐overlapping categorical vegetation types (i.e., typical vegetation and land cover maps), species‐level gradients of foliar cover are consistent with the ecological theories of individualistic response of species and niche space. We collected foliar cover data for vascular plant, bryophyte, and lichen species and 17 environmental variables in the Arctic Coastal Plain and Brooks Foothills of Alaska from 2012 to 2017. We integrated these data into a standardized database with 13 additional vegetation survey and monitoring data sets in northern Alaska collected from 1998 to 2017. To map the patterns of foliar cover for six dominant and widespread vascular plant species in arctic Alaska, we statistically associated ground‐based measurements of species distribution and abundance to environmental and multi‐season spectral covariates using a Bayesian statistical learning approach. For five of the six modeled species, our models predicted 36% to 65% of the observed species‐level variation in foliar cover. Overall, our continuous foliar cover maps predicted more of the observed spatial heterogeneity in species distribution and abundance than an existing categorical vegetation map. Mapping continuous foliar cover at the species level also revealed ecological patterns obscured by aggregation in existing plant functional type approaches. Species‐level analysis of vegetation patterns enables quantifying and monitoring landscape‐level changes in species, vegetation communities, and wildlife habitat independently of subjective categorical vegetation types and facilitates integrating spatial patterns across multiple ecological scales. The novel species‐level foliar cover mapping approach described here provides spatial information about the functional role of plant species in vegetation communities and wildlife habitat that are ... Text Arctic Brooks Foothills Alaska PubMed Central (PMC) Arctic Ecological Applications 30 4
institution Open Polar
collection PubMed Central (PMC)
op_collection_id ftpubmed
language English
topic Articles
spellingShingle Articles
Nawrocki, Timm W.
Carlson, Matthew L.
Osnas, Jeanne L. D.
Trammell, E. Jamie
Witmer, Frank D. W.
Regional mapping of species‐level continuous foliar cover: beyond categorical vegetation mapping
topic_facet Articles
description The ability to quantify spatial patterns and detect change in terrestrial vegetation across large landscapes depends on linking ground‐based measurements of vegetation to remotely sensed data. Unlike non‐overlapping categorical vegetation types (i.e., typical vegetation and land cover maps), species‐level gradients of foliar cover are consistent with the ecological theories of individualistic response of species and niche space. We collected foliar cover data for vascular plant, bryophyte, and lichen species and 17 environmental variables in the Arctic Coastal Plain and Brooks Foothills of Alaska from 2012 to 2017. We integrated these data into a standardized database with 13 additional vegetation survey and monitoring data sets in northern Alaska collected from 1998 to 2017. To map the patterns of foliar cover for six dominant and widespread vascular plant species in arctic Alaska, we statistically associated ground‐based measurements of species distribution and abundance to environmental and multi‐season spectral covariates using a Bayesian statistical learning approach. For five of the six modeled species, our models predicted 36% to 65% of the observed species‐level variation in foliar cover. Overall, our continuous foliar cover maps predicted more of the observed spatial heterogeneity in species distribution and abundance than an existing categorical vegetation map. Mapping continuous foliar cover at the species level also revealed ecological patterns obscured by aggregation in existing plant functional type approaches. Species‐level analysis of vegetation patterns enables quantifying and monitoring landscape‐level changes in species, vegetation communities, and wildlife habitat independently of subjective categorical vegetation types and facilitates integrating spatial patterns across multiple ecological scales. The novel species‐level foliar cover mapping approach described here provides spatial information about the functional role of plant species in vegetation communities and wildlife habitat that are ...
format Text
author Nawrocki, Timm W.
Carlson, Matthew L.
Osnas, Jeanne L. D.
Trammell, E. Jamie
Witmer, Frank D. W.
author_facet Nawrocki, Timm W.
Carlson, Matthew L.
Osnas, Jeanne L. D.
Trammell, E. Jamie
Witmer, Frank D. W.
author_sort Nawrocki, Timm W.
title Regional mapping of species‐level continuous foliar cover: beyond categorical vegetation mapping
title_short Regional mapping of species‐level continuous foliar cover: beyond categorical vegetation mapping
title_full Regional mapping of species‐level continuous foliar cover: beyond categorical vegetation mapping
title_fullStr Regional mapping of species‐level continuous foliar cover: beyond categorical vegetation mapping
title_full_unstemmed Regional mapping of species‐level continuous foliar cover: beyond categorical vegetation mapping
title_sort regional mapping of species‐level continuous foliar cover: beyond categorical vegetation mapping
publisher John Wiley and Sons Inc.
publishDate 2020
url http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7317374/
http://www.ncbi.nlm.nih.gov/pubmed/31971646
https://doi.org/10.1002/eap.2081
geographic Arctic
geographic_facet Arctic
genre Arctic
Brooks Foothills
Alaska
genre_facet Arctic
Brooks Foothills
Alaska
op_source Ecol Appl
op_relation http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7317374/
http://www.ncbi.nlm.nih.gov/pubmed/31971646
http://dx.doi.org/10.1002/eap.2081
op_rights © 2020 The Authors. Ecological Applications published by Wiley Periodicals, Inc. on behalf of Ecological Society of America
This is an open access article under the terms of the http://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 CC-BY
op_doi https://doi.org/10.1002/eap.2081
container_title Ecological Applications
container_volume 30
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