Frontiers and challenges in soil respiration research: from measurements to model-data integration

Abstract

Soil respiration, the flux of CO 2 from the soil to the atmosphere represents a major flux in the global carbon cycle. Our ability to predict this flux remains limited because of multiple controlling mechanisms that interact over different temporal and spatial scales. However, new advances in measurement and analyses present an opportunity for the scientific community to improve the understanding of the mechanisms that regulate soil respiration. In this paper, we address several recent advancements in soil respiration research from experimental measurements and data analysis to new considerations for modeldata integration. We focus on the links between the soil-plant-atmosphere continuum at short (i.e., diel) and medium (i.e., seasonal-years) temporal scales. First, we bring attention to the importance of identifying sources of soil CO 2 production and highlight the application of automated soil respiration measurements and isotope approaches. Second, we discuss the need of quality assurance and quality control for applications in time series analysis. Third, we review perspectives about emergent ideas for modeling development and model-data integration for soil respiration research. Finally, we call for stronger interactions between modelers and experimentalists as a way to improve our understanding of soil respiration and overall terrestrial carbon cycling.

Ecosystem photosynthesis regulates soil respiration on a diurnal scale with a short-term time lag in a coastal wetland

“…For instance, the immediate link of soil respiration to photosynthesis is still uncertain on the diurnal scale (Bahn et al, 2009). Therefore, current major challenges remain ahead of us for developing process-based models of soil respiration at short and medium temporal scales, including the lags and transport of carbon from photosynthesis to soil respiration (Vargas et al, 2011b).…”

Progress and opportunities for monitoring greenhouse gases fluxes in Mexican ecosystems: the MexFlux network

“…The NEE represents the total CO 2 exchanged vertically between land-surface and the atmosphere, and can be directly measured using the micrometeorological technique of EC (Aubinet et al, 2000;Baldocchi, 2003). Furthermore, Reco components include the emission of CO 2 from soils (Vargas et al, 2011a) known as total soil respiration (RS), and to a lesser extent by autotrophic respiration of leaves and stems of plants (RAp, Fig. 1).…”

“…Although we can identify the components that contribute for the ecosystem carbon balance, methodological uncertainties still exist. For example, to date there is no theoretical model to represent the biophysical mechanisms that regulate the temporal and spatial variation of RS (Bond-Lamberty and Thomson, 2010;Vargas et al, 2011a). One complication arises from the uncertainty in the estimation of RS as it varies throughout the year (Mahecha et al, 2010) due to the heterogeneity of the contributions by RAs and Rh under different soil and environmental conditions.…”

“…At the scale of experimental plots (i.e., square meters), gas exchange chambers provide information on microbial and plant ecophysiological processes that control the exchange of water vapor and CO 2 (Vargas et al, 2011a). However, the spatial sampling is limited, making it difficult to extrapolate results to larger spatial scales, and undesirable effects of confinement and manipulation may also be inherent to the methodology (Pumpanen et al, 2004).…”

“…The experimental evaluation of the interaction between weather and these cycles has made significant progress with the development of new methodologies to measure the mass (e.g., water vapor, CO 2 ) and energy exchange (e.g., sensible heat, solar radiation) at multiple spatial and temporal scales (Canadell et al, 2000). This development has required a multidisciplinary link between earth and atmospheric sciences, functional ecology, biogeochemistry, and mathematics, which has improved the application of model-data fusion (Vargas et al, 2011a). This scientific development, known as the third scientific paradigm, is complemented by the integration of knowledge from computer systems science, which is emerging as the fourth paradigm in scientific research (Hey et al, 2009 [Tropi-Dry], among others).…”