Forecasting Alpine Vegetation Change using Repeat Sampling and a Novel Modeling Approach
Global change affects alpine ecosystems by, among many effects, by altering plant distributions and community composition. However, forecasting alpine vegetation change is challenged by a scarcity of studies observing change in fixed plots spanning decadal-time scales. We present in this article a p...
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Royal Swedish Academy of Sciences
2011
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ftbioone:10.1007/s13280-011-0175-z 2024-06-02T08:15:26+00:00 Forecasting Alpine Vegetation Change using Repeat Sampling and a Novel Modeling Approach David R. Johnson Diane Ebert-May Patrick J. Webber Craig E. Tweedie David R. Johnson Diane Ebert-May Patrick J. Webber Craig E. Tweedie world 2011-09-01 text/HTML https://doi.org/10.1007/s13280-011-0175-z en eng Royal Swedish Academy of Sciences doi:10.1007/s13280-011-0175-z All rights reserved. https://doi.org/10.1007/s13280-011-0175-z Text 2011 ftbioone https://doi.org/10.1007/s13280-011-0175-z 2024-05-07T00:47:03Z Global change affects alpine ecosystems by, among many effects, by altering plant distributions and community composition. However, forecasting alpine vegetation change is challenged by a scarcity of studies observing change in fixed plots spanning decadal-time scales. We present in this article a probabilistic modeling approach that forecasts vegetation change on Niwot Ridge, CO using plant abundance data collected from marked plots established in 1971 and resampled in 1991 and 2001. Assuming future change can be inferred from past change, we extrapolate change for 100 years from 1971 and correlate trends for each plant community with time series environmental data (1971–2001). Models predict a decreased extent of Snowbed vegetation and an increased extent of Shrub Tundra by 2071. Mean annual maximum temperature and nitrogen deposition were the primary a posteriori correlates of plant community change. This modeling effort is useful for generating hypotheses of future vegetation change that can be tested with future sampling efforts. Text Tundra BioOne Online Journals AMBIO 40 6 693 704 |
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ftbioone |
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English |
description |
Global change affects alpine ecosystems by, among many effects, by altering plant distributions and community composition. However, forecasting alpine vegetation change is challenged by a scarcity of studies observing change in fixed plots spanning decadal-time scales. We present in this article a probabilistic modeling approach that forecasts vegetation change on Niwot Ridge, CO using plant abundance data collected from marked plots established in 1971 and resampled in 1991 and 2001. Assuming future change can be inferred from past change, we extrapolate change for 100 years from 1971 and correlate trends for each plant community with time series environmental data (1971–2001). Models predict a decreased extent of Snowbed vegetation and an increased extent of Shrub Tundra by 2071. Mean annual maximum temperature and nitrogen deposition were the primary a posteriori correlates of plant community change. This modeling effort is useful for generating hypotheses of future vegetation change that can be tested with future sampling efforts. |
author2 |
David R. Johnson Diane Ebert-May Patrick J. Webber Craig E. Tweedie |
format |
Text |
author |
David R. Johnson Diane Ebert-May Patrick J. Webber Craig E. Tweedie |
spellingShingle |
David R. Johnson Diane Ebert-May Patrick J. Webber Craig E. Tweedie Forecasting Alpine Vegetation Change using Repeat Sampling and a Novel Modeling Approach |
author_facet |
David R. Johnson Diane Ebert-May Patrick J. Webber Craig E. Tweedie |
author_sort |
David R. Johnson |
title |
Forecasting Alpine Vegetation Change using Repeat Sampling and a Novel Modeling Approach |
title_short |
Forecasting Alpine Vegetation Change using Repeat Sampling and a Novel Modeling Approach |
title_full |
Forecasting Alpine Vegetation Change using Repeat Sampling and a Novel Modeling Approach |
title_fullStr |
Forecasting Alpine Vegetation Change using Repeat Sampling and a Novel Modeling Approach |
title_full_unstemmed |
Forecasting Alpine Vegetation Change using Repeat Sampling and a Novel Modeling Approach |
title_sort |
forecasting alpine vegetation change using repeat sampling and a novel modeling approach |
publisher |
Royal Swedish Academy of Sciences |
publishDate |
2011 |
url |
https://doi.org/10.1007/s13280-011-0175-z |
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world |
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Tundra |
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Tundra |
op_source |
https://doi.org/10.1007/s13280-011-0175-z |
op_relation |
doi:10.1007/s13280-011-0175-z |
op_rights |
All rights reserved. |
op_doi |
https://doi.org/10.1007/s13280-011-0175-z |
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AMBIO |
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40 |
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