<b>Pendall</b>, E., D. Bachelet, R. T. Conant, B. El Masri, L. B. Flanagan, A. K. Knapp, J. Liu, S. Liu, and S. M. Schaeffer, 2018: Chapter 10: Grasslands. In Second State of the Carbon Cycle Report (SOCCR2): A Sustained Assessment Report [Cavallaro, N., G. Shrestha, R. Birdsey, M. A. Mayes, R. G. Najjar, S. C. Reed, P. Romero-Lankao, and Z. Zhu (eds.)]. U.S. Global Change Research Program, Washington, DC, USA, pp. 399-427, https://doi.org/10.7930/SOCCR2.2018.Ch10.
Grasslands are globally important carbon sinks that are resilient to climate change and managed grazing because the mixture of native species that occur are adapted to variable climatic conditions and grazing pressure. In drier regions, such as the southwestern United States and Mexico, grasslands may lose carbon in response to droughts or overgrazing. Mesic grasslands in Florida have stored vast amounts of soil carbon, which may be vulnerable to losses from fire and flooding, and CH4 emissions from these and other poorly drained grasslands can be significant. Changes in the geographic extent of grasslands caused by land-use change, including cropping and grazing management, will affect grassland carbon cycling. The net uptake rate of carbon is higher in grasslands than in agricultural lands, but management that takes carbon storage into consideration may mitigate potential carbon losses. Invasive species also are likely to alter grassland carbon cycling: woody species such as juniper or mesquite may increase net carbon uptake while herbaceous invasive species, such as cheatgrass, may diminish net carbon uptake.
10.5.2 Knowledge Gaps
Grassland productivity and carbon cycling are linked very closely to variations in precipitation and soil moisture availability in space and time. Changes in climate that lead to altered moisture availability are likely to affect the ability of grasslands to store carbon. Therefore, one of the main sources of uncertainty in predicting grassland carbon cycling is related to predictions of future precipitation, in terms of means, extremes, and seasonal distribution. The forecasted intensification of the global hydrological cycle will manifest in many ways, including increased interannual precipitation variability, more frequent extreme precipitation years (wet and dry), and alterations in annual precipitation amount (IPCC 2013). Recent climatological trends have supported these predictions (Fischer and Knutti 2014; Min et al., 2011). In grasslands, carbon uptake processes have been shown to be quite responsive to precipitation amount and event size and timing (Cherwin and Knapp 2012; Goldstein and Suding 2014; Heisler-White et al., 2008, 2009; Knapp et al., 2008b; Kulmatiski and Beard 2013; Thomey et al., 2011), but both positive and negative effects have been documented. Resolving the effects on carbon cycling from altered precipitation regimes—including seasonality—in future grasslands will reduce uncertainty in responses (Knapp et al., 2008b). Moreover, also unknown are future effects on carbon cycling from interactions between climate change and species composition. Additional simulations with dynamic vegetation models, including management parameters such as fire suppression, will help reduce these uncertainties (Bachelet et al., 2017).
Model intercomparison projects that address large differences in future projections of carbon cycling in grasslands and other ecosystem types also will reduce uncertainties (Medlyn et al., 2015). Methodological differences in estimating regional- to continental-scale carbon stocks and fluxes have resulted in large apparent uncertainties in budgets. For inventory methods, these uncertainties appear to stem from extrapolating carbon stocks and fluxes from point measurements to regional scales based on land-use classifications. For land-surface models, uncertainties can result from different assumptions, drivers, and processes. For atmospheric inverse models, the attribution of specified land areas may not align well with other approaches. For all these methods, inconsistencies in the depth of soil carbon can lead to large differences in stocks and process rates. Reconciling these divergent results likely will lead to improved understanding of processes and narrow the range of uncertainty in carbon forecasts.
Projections of soil carbon trends in response to future climate and land-use changes remain highly uncertain, particularly in warm, dry areas of Mexico and the U.S. Southwest and at high northern latitudes where data to inform modeling are limited. One uncertainty is related to the depth of soil carbon storage, with most models considering only the top 20 cm. However, validation and calibration datasets are not readily available, so models are rarely updated (e.g., Liu et al., 2003), and there is disagreement about which drivers of soil carbon dynamics should be included in models (Wieder et al., 2015). A recent study that simulated results from several multifactor climate change experiments indicated that productivity and decomposition responded more to increased precipitation and elevated CO2 in drier sites, including grasslands, than they did in wetter sites (Luo et al., 2008). The four tested ecosystem models all demonstrated significant interactive effects of warming, elevated CO2, and altered precipitation, although results for different sites varied because model formulations differed (Luo et al., 2008). These disparate findings demonstrate that rigorously evaluating model assumptions against experimental results will improve ESM projections (Medlyn et al., 2015).
Grasslands, the most extensive land-use type in the continental United States when combined with rangelands, shrublands, and pastures (Reeves and Mitchell 2012), are expected to maintain net carbon uptake at least until the middle of this century. The most significant threats to this carbon uptake potential likely will be related to land management and land use, along with changes in the precipitation regime associated with ongoing climate change.
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