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Below‐ground process responses to elevated CO 2 and temperature: a discussion of observations, measurement methods, and models
Author(s) -
Pendall Elise,
Bridgham Scott,
Hanson Paul J.,
Hungate Bruce,
Kicklighter David W.,
Johnson Dale W.,
Law Beverly E.,
Luo Yiqi,
Megonigal J. Patrick,
Olsrud Maria,
Ryan Michael G.,
Wan Shiqiang
Publication year - 2004
Publication title -
new phytologist
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.742
H-Index - 244
eISSN - 1469-8137
pISSN - 0028-646X
DOI - 10.1111/j.1469-8137.2004.01053.x
Subject(s) - environmental science , ecosystem , carbon cycle , nutrient cycle , cycling , climate change , atmospheric sciences , soil carbon , global warming , ecology , soil science , soil water , biology , geology , archaeology , history
Summary Rising atmospheric CO 2 and temperatures are probably altering ecosystem carbon cycling, causing both positive and negative feedbacks to climate. Below‐ground processes play a key role in the global carbon (C) cycle because they regulate storage of large quantities of C, and are potentially very sensitive to direct and indirect effects of elevated CO 2 and temperature. Soil organic matter pools, roots and associated rhizosphere organisms all have distinct responses to environmental change drivers, although availability of C substrates will regulate all the responses. Elevated CO 2 increases C supply below‐ground, whereas warming is likely to increase respiration and decomposition rates, leading to speculation that these effects will moderate one another. However, indirect effects on soil moisture availability and nutrient supply may alter processes in unexpected directions. Detailed, mechanistic understanding and modelling of below‐ground flux components, pool sizes and turnover rates is needed to adequately predict long‐term, net C storage in ecosystems. In this synthesis, we discuss the current status of below‐ground responses to elevated CO 2 and temperature and potential feedback effects, methodological challenges, and approaches to integrating models and measurements.