A global database of soil respiration data

Soil respiration – <i>R</i><sub>S</sub>, the flux of CO<sub>2</sub> from the soil to the atmosphere – is probably the least well constrained component of the terrestrial carbon cycle. Here we introduce the SRDB database, a near-universal compendium of published <i>R</i><sub>S</sub> data, and make it available to the scientific community both as a traditional static archive and as a dynamic community database that may be updated over time by interested users. The database encompasses all published studies that report one of the following data measured in the field (not laboratory): annual <i>R</i><sub>S</sub>, mean seasonal <i>R</i><sub>S</sub>, a seasonal or annual partitioning of <i>R</i><sub>S</sub> into its sources fluxes, <i>R</i><sub>S</sub> temperature response (Q<sub>10</sub>), or <i>R</i><sub>S</sub> at 10 °C. Its orientation is thus to seasonal and annual fluxes, not shorter-term or chamber-specific measurements. To date, data from 818 studies have been entered into the database, constituting 3379 records. The data span the measurement years 1961–2007 and are dominated by temperate, well-drained forests. We briefly examine some aspects of the SRDB data – its climate space coverage, mean annual <i>R</i><sub>S</sub> fluxes and their correlation with other carbon fluxes, <i>R</i><sub>S</sub> variability, temperature sensitivities, and the partitioning of <i>R</i><sub>S</sub> source flux – and suggest some potential lines of research that could be explored using these data. The SRDB database is available online in a permanent archive as well as via a project-hosting repository; the latter source leverages open-source software technologies to encourage wider participation in the database's future development. Ultimately, we hope that the updating of, and corrections to, the SRDB will become a shared project, managed by the users of these data in the scientific community

On linking an Earth system model to the equilibrium carbon representation of an economically optimizing land use model

Human activities are significantly altering biogeochemical cycles at the global scale, and the scope of these activities will change with both future climate and socioeconomic decisions. This poses a significant challenge for Earth system models (ESMs), which can incorporate land use change as prescribed inputs but do not actively simulate the policy or economic forces that drive land use change. One option to address this problem is to couple an ESM with an economically oriented integrated assessment model, but this is challenging because of the radically different goals and underpinnings of each type of model. This study describes the development and testing of a coupling between the terrestrial carbon cycle of an ESM (CESM) and an integrated assessment (GCAM) model, focusing on how CESM climate effects on the carbon cycle could be shared with GCAM. We examine the best proxy variables to share between the models, and we quantify how carbon flux changes driven by climate, CO₂ fertilization, and land use changes (e.g., deforestation) can be distinguished from each other by GCAM. The net primary production and heterotrophic respiration outputs of the Community Land Model (CLM), the land component of CESM, were found to be the most robust proxy variables by which to recalculate GCAM's assumptions of equilibrium ecosystem steady-state carbon. Carbon cycle effects of land use change are spatially limited relative to climate effects, and thus we were able to distinguish these effects successfully in the model coupling, passing only the latter to GCAM. This paper does not present results of a fully coupled simulation but shows, using a series of offline CLM simulations and an additional idealized Monte Carlo simulation, that our CESM–GCAM proxy variables reflect the phenomena that we intend and do not contain erroneous signals due to land use change. By allowing climate effects from a full ESM to dynamically modulate the economic and policy decisions of an integrated assessment model, this work will help link these models in a robust and flexible framework capable of examining two-way interactions between human and Earth system processes

Biospheric feedback effects in a synchronously coupled model of human and Earth systems

Fossil fuel combustion and land-use change are the two largest contributors to industrial-era increases in atmospheric CO2 concentration. Projections of these are thus fundamental inputs for coupled Earth system models (ESMs) used to estimate the physical and biological consequences of future climate system forcing. While historical data sets are available to inform past and current climate analyses, assessments of future climate change have relied on projections of energy and land use from energy-economic models, constrained by assumptions about future policy, land-use patterns and socio-economic development trajectories. Here we show that the climatic impacts on land ecosystems drive significant feedbacks in energy, agriculture, land use and carbon cycle projections for the twenty-first century. We find that exposure of human-appropriated land ecosystem productivity to biospheric change results in reductions of land area used for crops; increases in managed forest area and carbon stocks; decreases in global crop prices; and reduction in fossil fuel emissions for a low-mid-range forcing scenario. The feedbacks between climate-induced biospheric change and human system forcings to the climate system - demonstrated here - are handled inconsistently, or excluded altogether, in the one-way asynchronous coupling of energy-economic models to ESMs used to date

Biospheric feedback effects in a synchronously coupled model of human and Earth systems

Fossil fuel combustion and land-use change are the two largest contributors to industrial-era increases in atmospheric CO2 concentration. Projections of these are thus fundamental inputs for coupled Earth system models (ESMs) used to estimate the physical and biological consequences of future climate system forcing. While historical data sets are available to inform past and current climate analyses, assessments of future climate change have relied on projections of energy and land use from energy-economic models, constrained by assumptions about future policy, land-use patterns and socio-economic development trajectories. Here we show that the climatic impacts on land ecosystems drive significant feedbacks in energy, agriculture, land use and carbon cycle projections for the twenty-first century. We find that exposure of human-appropriated land ecosystem productivity to biospheric change results in reductions of land area used for crops; increases in managed forest area and carbon stocks; decreases in global crop prices; and reduction in fossil fuel emissions for a low-mid-range forcing scenario. The feedbacks between climate-induced biospheric change and human system forcings to the climate system - demonstrated here - are handled inconsistently, or excluded altogether, in the one-way asynchronous coupling of energy-economic models to ESMs used to date

Modeling the impacts of major forest disturbances on the Earth\u27s coupled carbon-climate system, and the capacity of forests to meet future demands for wood, fuel, and fiber

The carbon balance of forested ecosystems are fundamentally linked to cycles of disturbance and recovery. Two of the most extreme natural disturbances are tropical cyclones and Amazon forest fires. While an average of more than 80 tropical storms and hurricanes occur per year, the number, severity, and impacts of these storms varies through time and may be increasing, while the committed carbon emissions from a single large storm such as Katrina can be as large as the net annual carbon sequestration of U.S. forest trees. Forest fires are a growing concern too, particularly in the sensitive Amazon region where they potentially compound the risk of forest die-back from climate change. The overall science goal of this project is to understand how altered natural disturbance rates could affect the carbon balance of terrestrial ecosystems, and as a consequence, the development strategies designed to mitigate against future climate change. In particular, we address two major science questions: 1) How could potentially altered disturbance rates from tropical cyclones and Amazonian fires affect vegetation, carbon stocks and fluxes, and the development of climate change mitigation strategies? 2) How does remote sensing data quantity and quality constrain model projections of the effects of altered disturbance rates on vegetation, carbon stocks and fluxes, and the development of climate change mitigation strategies? These science questions are addressed through four linked objectives: 1) remote sensing and modeling forest disturbances (tropical cyclones and Amazonian fires); 2) assess the consequences of forest disturbances in integrated assessments; 3) link ecological and socio-economic models addressing forest disturbance; and 4) quantify the implications of forest disturbances for future satellite missions and Earth System models

Biospheric feedback effects in a synchronously coupled model of human and Earth systems

Fossil fuel combustion and land-use change are the two largest contributors to industrial-era increases in atmospheric CO2 concentration. Projections of these are thus fundamental inputs for coupled Earth system models (ESMs) used to estimate the physical and biological consequences of future climate system forcing. While historical data sets are available to inform past and current climate analyses, assessments of future climate change have relied on projections of energy and land use from energy-economic models, constrained by assumptions about future policy, land-use patterns and socio-economic development trajectories. Here we show that the climatic impacts on land ecosystems drive significant feedbacks in energy, agriculture, land use and carbon cycle projections for the twenty-first century. We find that exposure of human-appropriated land ecosystem productivity to biospheric change results in reductions of land area used for crops; increases in managed forest area and carbon stocks; decreases in global crop prices; and reduction in fossil fuel emissions for a low-mid-range forcing scenario. The feedbacks between climate-induced biospheric change and human system forcings to the climate system - demonstrated here - are handled inconsistently, or excluded altogether, in the one-way asynchronous coupling of energy-economic models to ESMs used to date