Using climate envelope models to identify potential ecological trajectories on the Kenai Peninsula, Alaska.

Managers need information about the vulnerability of historical plant communities, and their potential future conditions, to respond appropriately to landscape change driven by global climate change. We model the climate envelopes of plant communities on the Kenai Peninsula in Southcentral Alaska an...

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Published in:PLOS ONE
Main Authors: Dawn Robin Magness, John M Morton
Format: Article in Journal/Newspaper
Language:English
Published: Public Library of Science (PLoS) 2018
Subjects:
R
Q
Online Access:https://doi.org/10.1371/journal.pone.0208883
https://doaj.org/article/1ffb8eeecbaf4a9492f1597ce1b8cf70
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spelling ftdoajarticles:oai:doaj.org/article:1ffb8eeecbaf4a9492f1597ce1b8cf70 2023-05-15T18:40:28+02:00 Using climate envelope models to identify potential ecological trajectories on the Kenai Peninsula, Alaska. Dawn Robin Magness John M Morton 2018-01-01T00:00:00Z https://doi.org/10.1371/journal.pone.0208883 https://doaj.org/article/1ffb8eeecbaf4a9492f1597ce1b8cf70 EN eng Public Library of Science (PLoS) https://doi.org/10.1371/journal.pone.0208883 https://doaj.org/toc/1932-6203 1932-6203 doi:10.1371/journal.pone.0208883 https://doaj.org/article/1ffb8eeecbaf4a9492f1597ce1b8cf70 PLoS ONE, Vol 13, Iss 12, p e0208883 (2018) Medicine R Science Q article 2018 ftdoajarticles https://doi.org/10.1371/journal.pone.0208883 2022-12-31T12:50:03Z Managers need information about the vulnerability of historical plant communities, and their potential future conditions, to respond appropriately to landscape change driven by global climate change. We model the climate envelopes of plant communities on the Kenai Peninsula in Southcentral Alaska and forecast to 2020, 2050, and 2080. We assess 6 model outputs representing downscaled climate data from 3 global climate model outputs and 2 representative concentration pathways. We use two lines of evidence, model convergence and empirically measured rates of change, to identify the following plausible ecological trajectories for the peninsula: (1.) alpine tundra and sub-alpine shrub decrease, (2.) perennial snow and ice decrease, (3.) forests remain on the Kenai Lowlands, (4.) the contiguous white-Lutz-Sitka spruce complex declines, and (5.) mixed conifer afforestation occurs along the Gulf of Alaska coast. We suggest that converging models in the context of other lines of evidence is a viable approach to increase certainty for adaptation planning. Extremely dynamic areas with multiple outcomes (i.e., disagreement) among models represent ecological risk, but may also represent opportunities for facilitated adaptation and other managerial approaches to help tip the balance one way or another. By reducing uncertainty, this eclectic approach can be used to inform expectations about the future. Article in Journal/Newspaper Tundra Alaska Directory of Open Access Journals: DOAJ Articles Gulf of Alaska PLOS ONE 13 12 e0208883
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Dawn Robin Magness
John M Morton
Using climate envelope models to identify potential ecological trajectories on the Kenai Peninsula, Alaska.
topic_facet Medicine
R
Science
Q
description Managers need information about the vulnerability of historical plant communities, and their potential future conditions, to respond appropriately to landscape change driven by global climate change. We model the climate envelopes of plant communities on the Kenai Peninsula in Southcentral Alaska and forecast to 2020, 2050, and 2080. We assess 6 model outputs representing downscaled climate data from 3 global climate model outputs and 2 representative concentration pathways. We use two lines of evidence, model convergence and empirically measured rates of change, to identify the following plausible ecological trajectories for the peninsula: (1.) alpine tundra and sub-alpine shrub decrease, (2.) perennial snow and ice decrease, (3.) forests remain on the Kenai Lowlands, (4.) the contiguous white-Lutz-Sitka spruce complex declines, and (5.) mixed conifer afforestation occurs along the Gulf of Alaska coast. We suggest that converging models in the context of other lines of evidence is a viable approach to increase certainty for adaptation planning. Extremely dynamic areas with multiple outcomes (i.e., disagreement) among models represent ecological risk, but may also represent opportunities for facilitated adaptation and other managerial approaches to help tip the balance one way or another. By reducing uncertainty, this eclectic approach can be used to inform expectations about the future.
format Article in Journal/Newspaper
author Dawn Robin Magness
John M Morton
author_facet Dawn Robin Magness
John M Morton
author_sort Dawn Robin Magness
title Using climate envelope models to identify potential ecological trajectories on the Kenai Peninsula, Alaska.
title_short Using climate envelope models to identify potential ecological trajectories on the Kenai Peninsula, Alaska.
title_full Using climate envelope models to identify potential ecological trajectories on the Kenai Peninsula, Alaska.
title_fullStr Using climate envelope models to identify potential ecological trajectories on the Kenai Peninsula, Alaska.
title_full_unstemmed Using climate envelope models to identify potential ecological trajectories on the Kenai Peninsula, Alaska.
title_sort using climate envelope models to identify potential ecological trajectories on the kenai peninsula, alaska.
publisher Public Library of Science (PLoS)
publishDate 2018
url https://doi.org/10.1371/journal.pone.0208883
https://doaj.org/article/1ffb8eeecbaf4a9492f1597ce1b8cf70
geographic Gulf of Alaska
geographic_facet Gulf of Alaska
genre Tundra
Alaska
genre_facet Tundra
Alaska
op_source PLoS ONE, Vol 13, Iss 12, p e0208883 (2018)
op_relation https://doi.org/10.1371/journal.pone.0208883
https://doaj.org/toc/1932-6203
1932-6203
doi:10.1371/journal.pone.0208883
https://doaj.org/article/1ffb8eeecbaf4a9492f1597ce1b8cf70
op_doi https://doi.org/10.1371/journal.pone.0208883
container_title PLOS ONE
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