Optimal Function Explains Forest Responses to Global Change
Plant responses to global changes in carbon dioxide (CO2), nitrogen, and water availability are critical to future atmospheric CO2 concentrations, hydrology, and hence climate. Our understanding of those responses is incomplete, however. Multiple-resource manipulation experiments and empirical obser...
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Published in | Bioscience Vol. 59; no. 2; pp. 127 - 139 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Circulation, AIBS, 1313 Dolley Madison Blvd., Suite 402, McLean, VA 22101. USA
University of California Press
01.02.2009
American Institute of Biological Sciences Oxford University Press |
Subjects | |
Online Access | Get full text |
ISSN | 0006-3568 1525-3244 |
DOI | 10.1525/bio.2009.59.2.6 |
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Summary: | Plant responses to global changes in carbon dioxide (CO2), nitrogen, and water availability are critical to future atmospheric CO2 concentrations, hydrology, and hence climate. Our understanding of those responses is incomplete, however. Multiple-resource manipulation experiments and empirical observations have revealed a diversity of responses, as well as some consistent patterns. But vegetation models—currently dominated by complex numerical simulation models—have yet to achieve a consensus among their predicted responses, let alone offer a coherent explanation of the observed ones. Here we propose an alternative approach based on relatively simple optimization models (OMs). We highlight the results of three recent forest OMs, which together explain a remarkable range of observed forest responses to altered resource availability. We conclude that OMs now offer a simple yet powerful approach to predicting the responses of forests—and, potentially, other plant types—to global change. We recommend ways in which OMs could be developed further in this direction. |
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Bibliography: | http://dx.doi.org/10.1525/bio.2009.59.2.6 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-2 content type line 23 ObjectType-Article-1 ObjectType-Feature-2 |
ISSN: | 0006-3568 1525-3244 |
DOI: | 10.1525/bio.2009.59.2.6 |