On the Mechanistic Connection of Forest Canopy Structure with Productivity and Demography in the Amazon

Persistent Link:
http://hdl.handle.net/10150/265347
Title:
On the Mechanistic Connection of Forest Canopy Structure with Productivity and Demography in the Amazon
Author:
Stark, Scott C.
Issue Date:
2012
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
Canopy structure has long been thought to influence the productivity and ecological dynamics of tropical forests by altering the availability of light to leaves. Theories and methods that can connect detailed quantitative observations of canopy structure with forest dynamics, however, have been lacking. There is urgent need to resolve this uncertainty because human-caused climate change may alter canopy structure and function in the Amazon. This work addresses this problem by, first, developing methods based on LiDAR remote sensing of fine-scale structural variation to predict the spatial structure of leaf area and light in forest canopies of the central Amazon (Appendices B&C). I show that LiDAR-based leaf area and light estimates can be used to predict the productivity of tree size groups and one-hectare forest plots--as well as differences between 2 sites separated by 500km (App. B). Sites also differed in canopy structure and the distribution of tree frequencies over size (size or diameter distribution). A model based on tree architecture, however, was able to connect observed differences in canopy architecture with size distributions to predict plot and site differences (App. D). This model showed that tree architecture is plastic in different light environments. While plasticity may increase light absorption, the smallest size groups appeared light limited. Absorption over size groups in one site, but not the other, agreed with the hypothesis of energetic equivalence across size structure. Ultimately, the performance of individual trees of different sizes in different canopy environments links forest demography with canopy structure and ecosystem function--I present a study aimed at improving tests of individual level theories for the role of light dependence in tree growth (App. A). Together, this work quantitatively connects canopy structure with forest carbon dynamics and demographic structure and further develops LiDAR as premier tool for studying forest ecological dynamics. Assessing variation in biomass growth and demographic structure over tropical landscapes with remote sensing will improve understanding of ecosystem function and the role of the Amazon in global Carbon dynamics.
Type:
text; Electronic Dissertation
Keywords:
Carbon Dynamics; Forest Demography; LiDAR Remote Sensing; Tree Growth; Ecology & Evolutionary Biology; Amazon Rainforest; Canopy Architecture
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Graduate College; Ecology & Evolutionary Biology
Degree Grantor:
University of Arizona
Advisor:
Saleska, Scott R.; Enquist, Brian J.

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleOn the Mechanistic Connection of Forest Canopy Structure with Productivity and Demography in the Amazonen_US
dc.creatorStark, Scott C.en_US
dc.contributor.authorStark, Scott C.en_US
dc.date.issued2012-
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractCanopy structure has long been thought to influence the productivity and ecological dynamics of tropical forests by altering the availability of light to leaves. Theories and methods that can connect detailed quantitative observations of canopy structure with forest dynamics, however, have been lacking. There is urgent need to resolve this uncertainty because human-caused climate change may alter canopy structure and function in the Amazon. This work addresses this problem by, first, developing methods based on LiDAR remote sensing of fine-scale structural variation to predict the spatial structure of leaf area and light in forest canopies of the central Amazon (Appendices B&C). I show that LiDAR-based leaf area and light estimates can be used to predict the productivity of tree size groups and one-hectare forest plots--as well as differences between 2 sites separated by 500km (App. B). Sites also differed in canopy structure and the distribution of tree frequencies over size (size or diameter distribution). A model based on tree architecture, however, was able to connect observed differences in canopy architecture with size distributions to predict plot and site differences (App. D). This model showed that tree architecture is plastic in different light environments. While plasticity may increase light absorption, the smallest size groups appeared light limited. Absorption over size groups in one site, but not the other, agreed with the hypothesis of energetic equivalence across size structure. Ultimately, the performance of individual trees of different sizes in different canopy environments links forest demography with canopy structure and ecosystem function--I present a study aimed at improving tests of individual level theories for the role of light dependence in tree growth (App. A). Together, this work quantitatively connects canopy structure with forest carbon dynamics and demographic structure and further develops LiDAR as premier tool for studying forest ecological dynamics. Assessing variation in biomass growth and demographic structure over tropical landscapes with remote sensing will improve understanding of ecosystem function and the role of the Amazon in global Carbon dynamics.en_US
dc.typetexten_US
dc.typeElectronic Dissertationen_US
dc.subjectCarbon Dynamicsen_US
dc.subjectForest Demographyen_US
dc.subjectLiDAR Remote Sensingen_US
dc.subjectTree Growthen_US
dc.subjectEcology & Evolutionary Biologyen_US
dc.subjectAmazon Rainforesten_US
dc.subjectCanopy Architectureen_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineEcology & Evolutionary Biologyen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorSaleska, Scott R.en_US
dc.contributor.advisorEnquist, Brian J.en_US
dc.contributor.committeememberVenable, D. Lawrenceen_US
dc.contributor.committeememberChesson, Peteren_US
dc.contributor.committeememberHuxman, Travis E.en_US
dc.contributor.committeememberSaleska, Scott R.en_US
dc.contributor.committeememberEnquist, Brian J.en_US
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