Comprehensive ecosystem model‐data synthesis using multiple data sets at two temperate forest free‐air CO₂ enrichment experiments: Model performance at ambient CO₂ concentration

Abstract

Free-air CO 2 enrichment (FACE) experiments provide a remarkable wealth of data which can be used to evaluate and improve terrestrial ecosystem models (TEMs). In the FACE model-data synthesis project, 11 TEMs were applied to two decadelong FACE experiments in temperate forests of the southeastern U.S.-the evergreen Duke Forest and the deciduous Oak Ridge Forest. In this baseline paper, we demonstrate our approach to model-data synthesis by evaluating the models' ability to reproduce observed net primary productivity (NPP), transpiration, and leaf area index (LAI) in ambient CO 2 treatments. Model outputs were compared against observations using a range of goodness-of-fit statistics. Many models simulated annual NPP and transpiration within observed uncertainty. We demonstrate, however, that high goodness-of-fit values do not necessarily indicate a successful model, because simulation accuracy may be achieved through compensating biases in component variables. For example, transpiration accuracy was sometimes achieved with compensating biases in leaf area index and transpiration per unit leaf area. Our approach to model-data synthesis therefore goes beyond goodness-of-fit to investigate the success of alternative representations of component processes. Here we demonstrate this approach by comparing competing model hypotheses determining peak LAI. Of three alternative hypotheses-(1) optimization to maximize carbon export, (2) increasing specific leaf area with canopy depth, and (3) the pipe model-the pipe model produced peak LAI closest to the observations. This example illustrates how data sets from intensive field experiments such as FACE can be used to reduce model uncertainty despite compensating biases by evaluating individual model assumptions.

Land-use and climate change risks in the Amazon and the need of a novel sustainable development paradigm

“…In a CO 2 -enriched atmosphere, one of the few potentially resilience-increasing aspects for forests seems to be the effect known as "CO 2 fertilization" (122). The increasing concentration of this gas in the atmosphere has been recognized as being responsible for faster growth of trees, a fact that has been proven in large-scale experiments (123)(124)(125)(126). However, there are large uncertainties about the long-term response of the tropical forests to this effect (127), although modeling of this effect for the Amazon indicates that the impact of high degrees of climate change are attenuated, but not to the extent of avoiding forest loss (128).…”

Future changes of the terrestrial ecosystem based on a dynamic vegetation model driven with RCP8.5 climate projections from 19 GCMs

“…Future climate change is expected to significantly influence the terrestrial ecosystems with the potential to cause diversity and biome shifts (Williams et al 2007;Sala et al 2000) as well as dramatic changes in carbon fluxes and storages (Matthews et al 2005;Cox et al 2000;Friedlingstein et al 2001;Dufresne et al 2002). Lucht et al (2006) using LPJ-DGVM simulated widespread shifts of major vegetation types including increased coverage of deciduous trees and an northward shift of boreal forests in some areas.…”

Grand Challenges in Understanding the Interplay of Climate and Land Changes

“…Several major model intercomparison efforts have been conducted in recent years in both the land and climate modeling communities (de Noblet-Ducoudré et al 2012;Huntzinger et al 2012;Taylor et al 2012b;Walker et al 2014;Schwalm et al 2015b). For example, Zaehle et al (2014b) studied the representations of the ecosystem C-N cycle responses to elevated atmospheric CO 2 in 11 models at two temperate forest ecosystems (the Duke and Oak Ridge National Laboratory FACE experiment sites).…”