Alan K Knapp1, Philippe Ciais2, Melinda D Smith1. 1. Department of Biology and Graduate Degree Program in Ecology, Colorado State University, Fort Collins, CO, 80523, USA. 2. Laboratoire des Sciences du Climat et de l'Environnement, CEA CNRS UVSQ, Gif-sur-Yvette, 91191, France.
Abstract
Contents 41 I. 41 II. 42 III. 43 IV. 44 V. 45 Acknowledgements 46 References 46 SUMMARY: Precipitation (PPT) is a primary climatic determinant of plant growth and aboveground net primary production (ANPP) over much of the globe. Thus, PPT-ANPP relationships are important both ecologically and to land-atmosphere models that couple terrestrial vegetation to the global carbon cycle. Empirical PPT-ANPP relationships derived from long-term site-based data are almost always portrayed as linear, but recent evidence has accumulated that is inconsistent with an underlying linear relationship. We review, and then reconcile, these inconsistencies with a nonlinear model that incorporates observed asymmetries in PPT-ANPP relationships. Although data are currently lacking for parameterization, this new model highlights research needs that, when met, will improve our understanding of carbon cycle dynamics, as well as forecasts of ecosystem responses to climate change.
Contents 41 I. 41 II. 42 III. 43 IV. 44 V. 45 Acknowledgements 46 References 46 SUMMARY: Precipitation (PPT) is a primary climatic determinant of plant growth and aboveground net primary production (ANPP) over much of the globe. Thus, PPT-ANPP relationships are important both ecologically and to land-atmosphere models that couple terrestrial vegetation to the global carbon cycle. Empirical PPT-ANPP relationships derived from long-term site-based data are almost always portrayed as linear, but recent evidence has accumulated that is inconsistent with an underlying linear relationship. We review, and then reconcile, these inconsistencies with a nonlinear model that incorporates observed asymmetries in PPT-ANPP relationships. Although data are currently lacking for parameterization, this new model highlights research needs that, when met, will improve our understanding of carbon cycle dynamics, as well as forecasts of ecosystem responses to climate change.
Authors: Meghan L Avolio; Kevin R Wilcox; Kimberly J Komatsu; Nathan Lemoine; William D Bowman; Scott L Collins; Alan K Knapp; Sally E Koerner; Melinda D Smith; Sara G Baer; Katherine L Gross; Forest Isbell; Jennie McLaren; Peter B Reich; Katharine N Suding; K Blake Suttle; David Tilman; Zhuwen Xu; Qiang Yu Journal: Oecologia Date: 2020-11-01 Impact factor: 3.225
Authors: Zhihua Liu; Ashley P Ballantyne; Benjamin Poulter; William R L Anderegg; Wei Li; Ana Bastos; Philippe Ciais Journal: Nat Commun Date: 2018-09-05 Impact factor: 14.919