Predicting Effects of Climate Change on Habitat Suitability of Red Spruce (Picea rubens Sarg.) in the Southern Appalachian Mountains of the USA: Understanding Complex Systems Mechanisms through Modeling

Alpine, subalpine and boreal tree species, of low genetic diversity and adapted to low optimal temperatures, are vulnerable to the warming effects of global climate change. The accurate prediction of these species’ distributions in response to climate change is critical for effective planning and ma...

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Main Authors: Kyung Ah Koo, Bernard C. Patten, Marguerite Madden
Format: Article
Language:English
Published: MDPI AG 2015-04-01
Series:Forests
Subjects:
Online Access:http://www.mdpi.com/1999-4907/6/4/1208
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spelling doaj-a870a71b32da4bd7b0f795de5e30d49a2020-11-24T22:51:19ZengMDPI AGForests1999-49072015-04-01641208122610.3390/f6041208f6041208Predicting Effects of Climate Change on Habitat Suitability of Red Spruce (Picea rubens Sarg.) in the Southern Appalachian Mountains of the USA: Understanding Complex Systems Mechanisms through ModelingKyung Ah Koo0Bernard C. Patten1Marguerite Madden2Department of Geography, 26 Kyungheedae-ro, Dongdaemun-gu, Kyung Hee University, Seoul 130-701, KoreaOdum School of Ecology, 140 E. Green Street, University of Georgia, Athens, GA 30602-2202, USACenter for Geospatial Research (CGR), Department of Geography, University of Georgia, Athens, GA 30602-2305, USAAlpine, subalpine and boreal tree species, of low genetic diversity and adapted to low optimal temperatures, are vulnerable to the warming effects of global climate change. The accurate prediction of these species’ distributions in response to climate change is critical for effective planning and management. The goal of this research is to predict climate change effects on the distribution of red spruce (Picea rubens Sarg.) in the Great Smoky Mountains National Park (GSMNP), eastern USA. Climate change is, however, conflated with other environmental factors, making its assessment a complex systems problem in which indirect effects are significant in causality. Predictions were made by linking a tree growth simulation model, red spruce growth model (ARIM.SIM), to a GIS spatial model, red spruce habitat model (ARIM.HAB). ARIM.SIM quantifies direct and indirect interactions between red spruce and its growth factors, revealing the latter to be dominant. ARIM.HAB spatially distributes the ARIM.SIM simulations under the assumption that greater growth reflects higher probabilities of presence. ARIM.HAB predicts the future habitat suitability of red spruce based on growth predictions of ARIM.SIM under climate change and three air pollution scenarios: 10% increase, no change and 10% decrease. Results show that suitable habitats shrink most when air pollution increases. Higher temperatures cause losses of most low-elevation habitats. Increased precipitation and air pollution produce acid rain, which causes loss of both low- and high-elevation habitats. The general prediction is that climate change will cause contraction of red spruce habitats at both lower and higher elevations in GSMNP, and the effects will be exacerbated by increased air pollution. These predictions provide valuable information for understanding potential impacts of global climate change on the spatiotemporal distribution of red spruce habitats in GSMNP.http://www.mdpi.com/1999-4907/6/4/1208climate changephysiological mechanismsred spruce (Picea rubens Sarg.)habitat model (ARIM.HAB)simulation model (ARIM.SIM)
collection DOAJ
language English
format Article
sources DOAJ
author Kyung Ah Koo
Bernard C. Patten
Marguerite Madden
spellingShingle Kyung Ah Koo
Bernard C. Patten
Marguerite Madden
Predicting Effects of Climate Change on Habitat Suitability of Red Spruce (Picea rubens Sarg.) in the Southern Appalachian Mountains of the USA: Understanding Complex Systems Mechanisms through Modeling
Forests
climate change
physiological mechanisms
red spruce (Picea rubens Sarg.)
habitat model (ARIM.HAB)
simulation model (ARIM.SIM)
author_facet Kyung Ah Koo
Bernard C. Patten
Marguerite Madden
author_sort Kyung Ah Koo
title Predicting Effects of Climate Change on Habitat Suitability of Red Spruce (Picea rubens Sarg.) in the Southern Appalachian Mountains of the USA: Understanding Complex Systems Mechanisms through Modeling
title_short Predicting Effects of Climate Change on Habitat Suitability of Red Spruce (Picea rubens Sarg.) in the Southern Appalachian Mountains of the USA: Understanding Complex Systems Mechanisms through Modeling
title_full Predicting Effects of Climate Change on Habitat Suitability of Red Spruce (Picea rubens Sarg.) in the Southern Appalachian Mountains of the USA: Understanding Complex Systems Mechanisms through Modeling
title_fullStr Predicting Effects of Climate Change on Habitat Suitability of Red Spruce (Picea rubens Sarg.) in the Southern Appalachian Mountains of the USA: Understanding Complex Systems Mechanisms through Modeling
title_full_unstemmed Predicting Effects of Climate Change on Habitat Suitability of Red Spruce (Picea rubens Sarg.) in the Southern Appalachian Mountains of the USA: Understanding Complex Systems Mechanisms through Modeling
title_sort predicting effects of climate change on habitat suitability of red spruce (picea rubens sarg.) in the southern appalachian mountains of the usa: understanding complex systems mechanisms through modeling
publisher MDPI AG
series Forests
issn 1999-4907
publishDate 2015-04-01
description Alpine, subalpine and boreal tree species, of low genetic diversity and adapted to low optimal temperatures, are vulnerable to the warming effects of global climate change. The accurate prediction of these species’ distributions in response to climate change is critical for effective planning and management. The goal of this research is to predict climate change effects on the distribution of red spruce (Picea rubens Sarg.) in the Great Smoky Mountains National Park (GSMNP), eastern USA. Climate change is, however, conflated with other environmental factors, making its assessment a complex systems problem in which indirect effects are significant in causality. Predictions were made by linking a tree growth simulation model, red spruce growth model (ARIM.SIM), to a GIS spatial model, red spruce habitat model (ARIM.HAB). ARIM.SIM quantifies direct and indirect interactions between red spruce and its growth factors, revealing the latter to be dominant. ARIM.HAB spatially distributes the ARIM.SIM simulations under the assumption that greater growth reflects higher probabilities of presence. ARIM.HAB predicts the future habitat suitability of red spruce based on growth predictions of ARIM.SIM under climate change and three air pollution scenarios: 10% increase, no change and 10% decrease. Results show that suitable habitats shrink most when air pollution increases. Higher temperatures cause losses of most low-elevation habitats. Increased precipitation and air pollution produce acid rain, which causes loss of both low- and high-elevation habitats. The general prediction is that climate change will cause contraction of red spruce habitats at both lower and higher elevations in GSMNP, and the effects will be exacerbated by increased air pollution. These predictions provide valuable information for understanding potential impacts of global climate change on the spatiotemporal distribution of red spruce habitats in GSMNP.
topic climate change
physiological mechanisms
red spruce (Picea rubens Sarg.)
habitat model (ARIM.HAB)
simulation model (ARIM.SIM)
url http://www.mdpi.com/1999-4907/6/4/1208
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