Fire-induced Carbon Emissions and Regrowth Uptake in Western U.S. Forests: Documenting Variation Across Forest Types, Fire Severity, and Climate Regions

The forest area in the western United States that burns annually is increasing with warmer temperatures, more frequent droughts, and higher fuel densities. Studies that examine fire effects for regional carbon balances have tended to either focus on individual fires as examples or adopt generalizations without considering how forest type, fire severity, and regional climate influence carbon legacies. This study provides a more detailed characterization of fire effects and quantifies the full carbon impacts in relation to direct emissions, slow release of fire-killed biomass, and net carbon uptake from forest regrowth. We find important variations in fire-induced mortality and combustion across carbon pools (leaf, live wood, dead wood, litter, and duff) and across low- to high-severity classes. This corresponds to fire-induced direct emissions from 1984 to 2008 averaging 4 TgC/yr and biomass killed averaging 10.5 TgC/yr, with average burn area of 2723 sq km/yr across the western United States. These direct emission and biomass killed rates were 1.4 and 3.7 times higher, respectively, for high-severity fires than those for low-severity fires. The results show that forest regrowth varies greatly by forest type and with severity and that these factors impose a sustained carbon uptake legacy. The western U.S. fires between 1984 and 2008 imposed a net source of 12.3 TgC/yr in 2008, accounting for both direct fire emissions (9.5 TgC/yr) and heterotrophic decomposition of fire-killed biomass (6.1 TgC yr1) as well as contemporary regrowth sinks (3.3 TgC/yr). A sizeable trend exists toward increasing emissions as a larger area burns annually

Carbon Consequences of Forest Disturbance and Recovery Across the Conterminous United States

Forests of North America are thought to constitute a significant long term sink for atmospheric carbon. The United States Forest Service Forest Inventory and Analysis (FIA) program has developed a large data base of stock changes derived from consecutive estimates of growing stock volume in the US. These data reveal a large and relatively stable increase in forest carbon stocks over the last two decades or more. The mechanisms underlying this national increase in forest stocks may include recovery of forests from past disturbances, net increases in forest area, and growth enhancement driven by climate or fertilization by CO2 and Nitrogen. Here we estimate the forest recovery component of the observed stock changes using FIA data on the age structure of US forests and carbon stocks as a function of age. The latter are used to parameterize forest disturbance and recovery processes in a carbon cycle model. We then apply resulting disturbance/recovery dynamics to landscapes and regions based on the forest age distributions. The analysis centers on 28 representative climate settings spread about forested regions of the conterminous US. We estimate carbon fluxes for each region and propagate uncertainties in calibration data through to the predicted fluxes. The largest recovery-driven carbon sinks are found in the South central, Pacific Northwest, and Pacific Southwest regions, with spatially averaged net ecosystem productivity (NEP) of about 100 g C / square m / a driven by forest age structure. Carbon sinks from recovery in the Northeast and Northern Lake States remain moderate to large owing to the legacy of historical clearing and relatively low modern disturbance rates from harvest and fire. At the continental scale, we find a conterminous U.S. forest NEP of only 0.16 Pg C/a from age structure in 2005, or only 0.047 Pg C/a of forest stock change after accounting for fire emissions and harvest transfers. Recent estimates of NEP derived from inventory stock change, harvest, and fire data show twice the NEP sink we derive from forest age distributions. We discuss possible reasons for the discrepancies including modeling errors and the possibility of climate and/or fertilization (CO2 or N) growth enhancements

Impacts of disturbance history on forest carbon stocks and fluxes: Merging satellite disturbance mapping with forest inventory data in a carbon cycle model framework

Forest carbon stocks and fluxes are highly dynamic following stand-clearing disturbances from severe fire and harvest and this presents a significant challenge for continental carbon budget assessments. In this work we use forest inventory data to parameterize a carbon cycle model to represent post-disturbance carbon trajectories of carbon pools and fluxes for specific forest types growing in high and low site productivity class settings. We then apply these trajectories to landscapes and regions based on forest age distributions derived from either the FIA data or from Landsat time series stacks (1985–2006) for 54 representative scenes throughout most of the conterminous United States.Weestimate the net carbon uptake in forests caused by post-disturbance growth and decomposition (“regrowth sink”) for forested regions across the country. At the landscape scale, the prevailing condition of positive net ecosystem productivity (NEP) is in stark contrast to local patcheswith large sources, particularly in the west where fires and clear cuts create contiguous disturbed patches. At the continental scale, regional differences in disturbance rates reflect management patterns of high disturbance rates in the Southeastern and South Central states, and lower disturbance rates in the Northeast andNorthern Lakes States. Despite low contemporary disturbance rates in the Northeast and Northern Lakes States (0.61 and 0.74% y−1), the regrowth sink there remains of moderate to large strength (88 and 57 g C m−2 y−1) owing to the continued legacy from historical clearing. Large regrowth sinks are also found in the Southeast, South Central, and Pacific Southwest regions (85, 86, and 95 g C m−2 y−1) where disturbance rates also tend to be higher (1.59, 1.38, and 0.93% y−1). Overall, the Landsat-derived disturbance rates are elevated relative to FIA-derived rates (1.19 versus 0.93% y−1) particularly for western regions. The differences only modestly adjust regional- and continental-scale carbon budgets, reducing NEP from forest regrowth by about 8%

Interannual variability of photosynthesis across Africa and its attribution

Africa is thought to be a large source of interannual variability in the global carbon cycle, only vaguely attributed to climate fluctuations. This study uses a biophysical model, Simple Biosphere, to examine in detail what specific factors, physiological (acute stress from low soil water, temperature, or low humidity) and biophysical (low vegetation radiation use), are responsible for spatiotemporal patterns of photosynthesis across the African continent during the period 1982-2003. Acute soil water stress emerges as the primary factor driving interannual variability of photosynthesis for most of Africa. Southern savannas and woodlands are a particular hot spot of interannual variability in photosynthesis, owing to high rainfall variability and photosynthetic potential but intermediate annual rainfall. Surprisingly low interannual variability of photosynthesis in much of the Sudano-Sahelian zone derives from relatively low vegetation cover, pronounced humidity stress, and somewhat lower rainfall variability, whereas perennially wet conditions diminish interannual variability in photosynthesis across much of the Congo Basin and coastal West Africa. Though not of focus here, the coefficient of variation in photosynthesis is notably high in drylands and desert margins (i.e., Sahel, Greater Horn, Namib, and Kalahari) having implications for supply of food and fiber. These findings emphasize that when considering impacts of climate change and land surface feedbacks to the atmosphere, it is important to recognize how vegetation, climate, and soil characteristics may conspire to filter or dampen ecosystem responses to hydroclimatic variability. Copyright 2008 by the American Geophysical Union

To What Extent Can Vegetation Mitigate Greenhouse Warming? A Modeling Approach

Climate models participating in the IPCC Fourth Assessment Report indicate that under a 2xCO2 environment, runoff would increase faster than precipitation overland. However, observations over large U.S watersheds indicate otherwise. This inconsistency suggests that there may be important feedbacks between climate and land surface unaccounted for in the present generation of models. We postulate that the increase in precipitation associated with the increase in CO2 is also increasing vegetation density, which may already be feeding back onto climate. Including this feedback in a climate model simulation resulted in precipitation and runoff trends consistent with observations and reduced the warming by 0.6OC overland. This unaccounted for missing water may be linked to about 10% of the missing land carbon sink. A recent compilation of outputs from 19 coupled atmosphere-ocean general circulation models used in the IPCC Fourth Assessment Report (AR4) shows projected increases in air temperature, precipitation and river discharge for 24 major rivers in the world in response to doubling CO2 by the end of the century (1). The ensemble mean from these models also indicates that, compared to their respective baselines overland, the global mean of the runoff change would increase faster (8.9% per year) than that of the precipitation (5% per year). We analyze century-scale observed annual runoff time-series (1901-2002) over 9 hydrological units covering large regions of the Eastern United States (Fig.1) compiled by the United States Geological Survey (USGS)(2). These regions were selected because they are the most forested; the least water-limited and are not under extensive irrigation. We compare these time-series to similar time-series of observed annual precipitation anomalies spanning the period 1900-1995 (3). Both time-series exhibit a positive longterm trend (Fig. 2); however, in contrast to the analysis of (I), these historic data records show that the rate of precipitation increase is 5.5 % per year, roughly double the rate of runoff increase of 3.1 % per year

Does Terrestrial Drought Explain Global CO2 Flux Anomalies Induced by El Nino?

The El Nino Southern Oscillation is the dominant year-to-year mode of global climate variability. El Nino effects on terrestrial carbon cycling are mediated by associated climate anomalies, primarily drought, influencing fire emissions and biotic net ecosystem exchange (NEE). Here we evaluate whether El Nino produces a consistent response from the global carbon cycle. We apply a novel bottom-up approach to estimating global NEE anomalies based on FLUXNET data using land cover maps and weather reanalysis. We analyze 13 years (1997-2009) of globally gridded observational NEE anomalies derived from eddy covariance flux data, remotely-sensed fire emissions at the monthly time step, and NEE estimated from an atmospheric transport inversion. We evaluate the overall consistency of biospheric response to El Nino and, more generally, the link between global CO2 flux anomalies and El Nino-induced drought. Our findings, which are robust relative to uncertainty in both methods and time-lags in response, indicate that each event has a different spatial signature with only limited spatial coherence in Amazonia, Australia and southern Africa. For most regions, the sign of response changed across El Nino events. Biotic NEE anomalies, across 5 El Nino events, ranged from -1.34 to +0.98 Pg Cyr(exp -1, whereas fire emissions anomalies were generally smaller in magnitude (ranging from -0.49 to +0.53 Pg C yr(exp -1). Overall drought does not appear to impose consistent terrestrial CO2 flux anomalies during El Ninos, finding large variation in globally integrated responses from 11.15 to +0.49 Pg Cyr(exp -1). Despite the significant correlation between the CO2 flux and El Nino indices, we find that El Nino events have, when globally integrated, both enhanced and weakened terrestrial sink strength, with no consistent response across event

Deciphering the components of regional net ecosystem fluxes following a bottom-up approach for the Iberian Peninsula

Quantification of ecosystem carbon pools is a fundamental requirement for estimating carbon fluxes and for addressing the dynamics and responses of the terrestrial carbon cycle to environmental drivers. The initial estimates of carbon pools in terrestrial carbon cycle models often rely on the ecosystem steady state assumption, leading to initial equilibrium conditions. In this study, we investigate how trends and inter-annual variability of net ecosystem fluxes are affected by initial non-steady state conditions. Further, we examine how modeled ecosystem responses induced exclusively by the model drivers can be separated from the initial conditions. For this, the Carnegie-Ames-Stanford Approach (CASA) model is optimized at set of European eddy covariance sites, which support the parameterization of regional simulations of ecosystem fluxes for the Iberian Peninsula, between 1982 and 2006. <br><br> The presented analysis stands on a credible model performance for a set of sites, that represent generally well the plant functional types and selected descriptors of climate and phenology present in the Iberian region – except for a limited Northwestern area. The effects of initial conditions on inter-annual variability and on trends, results mostly from the recovery of pools to equilibrium conditions; which control most of the inter-annual variability (IAV) and both the magnitude and sign of most of the trends. However, by removing the time series of pure model recovery from the time series of the overall fluxes, we are able to retrieve estimates of inter-annual variability and trends in net ecosystem fluxes that are quasi-independent from the initial conditions. This approach reduced the sensitivity of the net fluxes to initial conditions from 47% and 174% to −3% and 7%, for strong initial sink and source conditions, respectively. <br><br> With the aim to identify and improve understanding of the component fluxes that drive the observed trends, the net ecosystem production (NEP) trends are decomposed into net primary production (NPP) and heterotrophic respiration (<i>R</i><sub>H</sub>) trends. The majority (~97%) of the positive trends in NEP is observed in regions where both NPP and <i>R</i><sub>H</sub> fluxes show significant increases, although the magnitude of NPP trends is higher. Analogously, ~83% of the negative trends in NEP are also associated with negative trends in NPP. The spatial patterns of NPP trends are mainly explained by the trends in <i>f</i>APAR (<i>r</i>=0.79) and are only marginally explained by trends in temperature and water stress scalars (<i>r</i>=0.10 and <i>r</i>=0.25, respectively). Further, we observe the significant role of substrate availability (<i>r</i>=0.25) and temperature (<i>r</i>=0.23) in explaining the spatial patterns of trends in <i>R</i><sub>H</sub>. These results highlight the role of primary production in driving ecosystem fluxes. <br><br> Overall, our study illustrates an approach for removing the confounding effects of initial conditions and emphasizes the need to decompose the ecosystem fluxes into its components and drivers for more mechanistic interpretations of modeling results. We expect that our results are not only specific for the CASA model since it incorporates concepts of ecosystem functioning and modeling assumptions common to biogeochemical models. A direct implication of these results is the ability of this approach to detect climate and phenology induced trends regardless of the initial conditions