Journal
TREE PHYSIOLOGY
Volume 32, Issue 10, Pages 1183-1198Publisher
OXFORD UNIV PRESS
DOI: 10.1093/treephys/tps078
Keywords
crown dominance; Douglas-fir; relative humidity; stable isotopes; stomatal conductance; tree rings; water-use efficiency
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Funding
- Oregon State University Institute for Water and Watersheds
- American Geophysical Union Horton Research Grant
- Ford Foundation Fellowships Office
- U.S. Environmental Protection Agency
- Direct For Biological Sciences
- Division Of Environmental Biology [1440409] Funding Source: National Science Foundation
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The inter-relationships among delta C-13 and delta O-18 in tree ring cellulose and ring width have the potential to illuminate long-term physiological and environmental information in forest stands that have not been monitored. We examine how within-stand competition and environmental gradients affect ring widths and the stable isotopes of cellulose. We utilize a natural climate gradient across a catchment dominated by Douglas-fir and temporal changes in climate over an 8-year period. We apply a dual-isotope approach to infer physiological response of trees in differing crown dominance classes to temporal and spatial changes in environmental conditions using a qualitative conceptual model of the C-13-O-18 relationship and by normalizing the data to minimize other variance. The delta C-13 and delta O-18 of cellulose were correlated with year-to-year variation in relative humidity and consistent with current isotope theory. Using a qualitative conceptual model of the C-13-O-18 relationship and physiological knowledge about the species, we interpreted these changes as stomatal conductance responses to evaporative demand. Spatial variance between plots was not strong and seemed related to leaf nitrogen rather than any other environmental variable. Dominant trees responded to environmental gradients more consistently with current isotope theory as compared with other classes within the same stand. We found a correlation of stable isotopes with environmental variables is useful for assessing the impacts of environmental change over short time series and where growth varies only minimally with climate.
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