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Understanding forest landscape respo...

Xu, Chonggang.

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Understanding forest landscape response to global climatic change: An uncertainty evaluation based on spatial modeling.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Understanding forest landscape response to global climatic change: An uncertainty evaluation based on spatial modeling./
Author:	Xu, Chonggang.
Description:	226 p.
Notes:	Source: Dissertation Abstracts International, Volume: 70-06, Section: B, page: 3399.
Contained By:	Dissertation Abstracts International70-06B.
Subject:	Agriculture, Forestry and Wildlife. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3363116
ISBN:	9781109219357

Understanding forest landscape response to global climatic change: An uncertainty evaluation based on spatial modeling.
Xu, Chonggang.

Understanding forest landscape response to global climatic change: An uncertainty evaluation based on spatial modeling. - 226 p.

Source: Dissertation Abstracts International, Volume: 70-06, Section: B, page: 3399.

Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2009.

The forest ecosystem is one of the world's most important ecosystems that would be substantially affected by future global climatic changes in temperature, CO2, precipitation and radiation. Climatic changes may affect tree species physiology, abundance, distribution; forest community characteristics (e.g., species richness and diversity); forest landscape composition and pattern; and biome distributions. In this study, potential forest landscape responses in the Boundary Waters Canoe Area (BWCA) due to climatic change were examined based on hierarchical responses of the forest ecosystem at different levels, including physiology (e.g. net primary production) and seedling establishment response at the species level, the colonization and competition response at the forest succession level, and the species composition response at the community level. For this purpose, a forest landscape model (LANDIS-II) was coupled with a forest ecosystem process model (PnET-II) to examine how small-scale processes can affect large-scale processes and patterns using different statistical methods. Specifically, three questions were addressed in this study: (1) how uncertainties in global climatic change predictions propagate from the small-scale processes to the large-scale forest landscape response predictions; (2) what is the importance of different successional drivers (successional driver of competition due to the modification of aboveground net primary production, and successional driver of colonization due to the modification of seedling establishment) in forest landscape response to global climatic change; and (3) what are important transition pathways among different forest types driving forest landscape response to climatic change. An improved uncertainty analysis technique, and an elasticity and loop analysis technique for transient dynamics were proposed to address the above questions. Results showed that major source of uncertainty for forest landscape prediction is from temperature predication. If the optimum photosynthetic temperature rises due to CO2 enrichment, the forest landscape response to climatic change measured by forest type composition may be substantially reduced. Results showed that, given moderate disturbances, competition is the dominant driver for short-term (<100 years) forest landscape response while colonization is the dominant driver for long-term (>100 years) forest landscape response. If there were more frequent disturbances, colonization can be the dominant driver for short-term forest landscape response. The important transition pathways responsible for forest landscape response to climatic change include transition pathways from fir and aspen to white pine. The proposed analysis methods (i.e., uncertainty and sensitivity analysis, and elasticity and loop analysis) can be general tools to study the effects of climatic change on forests. The results presented in this study can help us better understand forest landscape response to climatic change and direct field experiments.

ISBN: 9781109219357Subjects--Topical Terms:

783690
Agriculture, Forestry and Wildlife.

Understanding forest landscape response to global climatic change: An uncertainty evaluation based on spatial modeling.
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100 1 $a Xu, Chonggang. $3 1676714
245 1 0 $a Understanding forest landscape response to global climatic change: An uncertainty evaluation based on spatial modeling.
300 $a 226 p.
500 $a Source: Dissertation Abstracts International, Volume: 70-06, Section: B, page: 3399.
500 $a Adviser: George Z. Gertner.
502 $a Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2009.
520 $a The forest ecosystem is one of the world's most important ecosystems that would be substantially affected by future global climatic changes in temperature, CO2, precipitation and radiation. Climatic changes may affect tree species physiology, abundance, distribution; forest community characteristics (e.g., species richness and diversity); forest landscape composition and pattern; and biome distributions. In this study, potential forest landscape responses in the Boundary Waters Canoe Area (BWCA) due to climatic change were examined based on hierarchical responses of the forest ecosystem at different levels, including physiology (e.g. net primary production) and seedling establishment response at the species level, the colonization and competition response at the forest succession level, and the species composition response at the community level. For this purpose, a forest landscape model (LANDIS-II) was coupled with a forest ecosystem process model (PnET-II) to examine how small-scale processes can affect large-scale processes and patterns using different statistical methods. Specifically, three questions were addressed in this study: (1) how uncertainties in global climatic change predictions propagate from the small-scale processes to the large-scale forest landscape response predictions; (2) what is the importance of different successional drivers (successional driver of competition due to the modification of aboveground net primary production, and successional driver of colonization due to the modification of seedling establishment) in forest landscape response to global climatic change; and (3) what are important transition pathways among different forest types driving forest landscape response to climatic change. An improved uncertainty analysis technique, and an elasticity and loop analysis technique for transient dynamics were proposed to address the above questions. Results showed that major source of uncertainty for forest landscape prediction is from temperature predication. If the optimum photosynthetic temperature rises due to CO2 enrichment, the forest landscape response to climatic change measured by forest type composition may be substantially reduced. Results showed that, given moderate disturbances, competition is the dominant driver for short-term (<100 years) forest landscape response while colonization is the dominant driver for long-term (>100 years) forest landscape response. If there were more frequent disturbances, colonization can be the dominant driver for short-term forest landscape response. The important transition pathways responsible for forest landscape response to climatic change include transition pathways from fir and aspen to white pine. The proposed analysis methods (i.e., uncertainty and sensitivity analysis, and elasticity and loop analysis) can be general tools to study the effects of climatic change on forests. The results presented in this study can help us better understand forest landscape response to climatic change and direct field experiments.
590 $a School code: 0090.
650 4 $a Agriculture, Forestry and Wildlife. $3 783690
650 4 $a Environmental Sciences. $3 676987
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710 2 $a University of Illinois at Urbana-Champaign. $3 626646
773 0 $t Dissertation Abstracts International $g 70-06B.
790 1 0 $a Gertner, George Z., $e advisor
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791 $a Ph.D.
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856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3363116