Ecosystem carbon dioxide fluxes after disturbance in forests of North America
University of Manitoba1, Environment Canada2, University of British Columbia3, University of Florida4, University of Toledo5, United States Forest Service6, Pennsylvania State University7, University of Wisconsin-Madison8, Northern Arizona University9, University of California, Berkeley10, University of California, Irvine11, Canadian Forest Service12, Oregon State University13, Laval University14, Queen's University15, North Carolina State University16, University of Alabama17, University of New Hampshire18
TL;DR: In this article, the authors summarize more than 180 site years of eddy covariance measurements of carbon dioxide flux made at forest chronosequences in North America and show that carbon loss from all ecosystems following a stand-replacing disturbance, becoming a carbon sink by 20 years for all ecosystems and by 10 years for most.
Abstract: Disturbances are important for renewal of North American forests. Here we summarize more than 180 site years of eddy covariance measurements of carbon dioxide flux made at forest chronosequences in North America. The disturbances included stand-replacing fire (Alaska, Arizona, Manitoba, and Saskatchewan) and harvest (British Columbia, Florida, New Brunswick, Oregon, Quebec, Saskatchewan, and Wisconsin) events, insect infestations (gypsy moth, forest tent caterpillar, and mountain pine beetle), Hurricane Wilma, and silvicultural thinning (Arizona, California, and New Brunswick). Net ecosystem production (NEP) showed a carbon loss from all ecosystems following a stand-replacing disturbance, becoming a carbon sink by 20 years for all ecosystems and by 10 years for most. Maximum carbon losses following disturbance (g C m−2y−1) ranged from 1270 in Florida to 200 in boreal ecosystems. Similarly, for forests less than 100 years old, maximum uptake (g C m−2y−1) was 1180 in Florida mangroves and 210 in boreal ecosystems. More temperate forests had intermediate fluxes. Boreal ecosystems were relatively time invariant after 20 years, whereas western ecosystems tended to increase in carbon gain over time. This was driven mostly by gross photosynthetic production (GPP) because total ecosystem respiration (ER) and heterotrophic respiration were relatively invariant with age. GPP/ER was as low as 0.2 immediately following stand-replacing disturbance reaching a constant value of 1.2 after 20 years. NEP following insect defoliations and silvicultural thinning showed lesser changes than stand-replacing events, with decreases in the year of disturbance followed by rapid recovery. NEP decreased in a mangrove ecosystem following Hurricane Wilma because of a decrease in GPP and an increase in ER.
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TL;DR: In this article, the societal and ecological consequences of forest die-off are considered. But the authors do not consider the impact of forest mortality on terrestrial ecosystems, climate-ecosystem interactions, and carbon-cycle feedbacks.
Abstract: The multitude of forest die-off events within the last decade strongly suggests that forest mortality is an emerging global phenomenon, constituting a major uncertainty in projections of climate impacts on terrestrial ecosystems, climate-ecosystem interactions, and carbon-cycle feedbacks. This Review considers the societal and ecological consequences of dying forests.
969 citations
01 Dec 2012
Abstract: We upscaled FLUXNET observations of carbon dioxide, water, and energy fluxes to the global scale using the machine learning technique, model tree ensembles (MTE). We trained MTE to predict site-level gross primary productivity (GPP), terrestrial ecosystem respiration (TER), net ecosystem exchange (NEE), latent energy (LE), and sensible heat (H) based on remote sensing indices, climate and meteorological data, and information on land use. We applied the trained MTEs to generate global flux fields at a 0.5 degrees x 0.5 degrees spatial resolution and a monthly temporal resolution from 1982 to 2008. Cross-validation analyses revealed good performance of MTE in predicting among-site flux variability with modeling efficiencies (MEf) between 0.64 and 0.84, except for NEE (MEf = 0.32). Performance was also good for predicting seasonal patterns (MEf between 0.84 and 0.89, except for NEE (0.64)). By comparison, predictions of monthly anomalies were not as strong (MEf between 0.29 and 0.52). Improved accounting of disturbance and lagged environmental effects, along with improved characterization of errors in the training data set, would contribute most to further reducing uncertainties. Our global estimates of LE (158 +/- 7 J x 10(18) yr(-1)), H (164 +/- 15 J x 10(18) yr(-1)), and GPP (119 +/- 6 Pg C yr(-1)) were similar to independent estimates. Our global TER estimate (96 +/- 6 Pg C yr(-1)) was likely underestimated by 5-10%. Hot spot regions of interannual variability in carbon fluxes occurred in semiarid to semihumid regions and were controlled by moisture supply. Overall, GPP was more important to interannual variability in NEE than TER. Our empirically derived fluxes may be used for calibration and evaluation of land surface process models and for exploratory and diagnostic assessments of the biosphere.
948 citations
Max Planck Society1, Laval University2, Harvard University3, McMaster University4, Lund University5, Karlsruhe Institute of Technology6, Dresden University of Technology7, Institut national de la recherche agronomique8, University of Toledo9, University College Cork10, Oregon State University11, ETH Zurich12, United States Forest Service13, Free University of Bozen-Bolzano14, Wageningen University and Research Centre15, National Research Council16, Clark University17
TL;DR: In this paper, the authors upscaled FLUXNET observations of carbon dioxide, water, and energy fluxes to the global scale using the machine learning technique, model tree ensembles (MTE), to predict site-level gross primary productivity (GPP), terrestrial ecosystem respiration (TER), net ecosystem exchange (NEE), latent energy (LE), and sensible heat (H) based on remote sensing indices, climate and meteorological data, and information on land use.
Abstract: We upscaled FLUXNET observations of carbon dioxide, water, and energy fluxes to the global scale using the machine learning technique, model tree ensembles (MTE). We trained MTE to predict site-level gross primary productivity (GPP), terrestrial ecosystem respiration (TER), net ecosystem exchange (NEE), latent energy (LE), and sensible heat (H) based on remote sensing indices, climate and meteorological data, and information on land use. We applied the trained MTEs to generate global flux fields at a 0.5 degrees x 0.5 degrees spatial resolution and a monthly temporal resolution from 1982 to 2008. Cross-validation analyses revealed good performance of MTE in predicting among-site flux variability with modeling efficiencies (MEf) between 0.64 and 0.84, except for NEE (MEf = 0.32). Performance was also good for predicting seasonal patterns (MEf between 0.84 and 0.89, except for NEE (0.64)). By comparison, predictions of monthly anomalies were not as strong (MEf between 0.29 and 0.52). Improved accounting of disturbance and lagged environmental effects, along with improved characterization of errors in the training data set, would contribute most to further reducing uncertainties. Our global estimates of LE (158 +/- 7 J x 10(18) yr(-1)), H (164 +/- 15 J x 10(18) yr(-1)), and GPP (119 +/- 6 Pg C yr(-1)) were similar to independent estimates. Our global TER estimate (96 +/- 6 Pg C yr(-1)) was likely underestimated by 5-10%. Hot spot regions of interannual variability in carbon fluxes occurred in semiarid to semihumid regions and were controlled by moisture supply. Overall, GPP was more important to interannual variability in NEE than TER. Our empirically derived fluxes may be used for calibration and evaluation of land surface process models and for exploratory and diagnostic assessments of the biosphere.
927 citations
TL;DR: These estimates expand the evaluation of the global health burden associated with outdoor air pollution, highlighted by increased concentrations in East, South, and Southeast Asia and decreases in North America and Europe.
Abstract: Ambient air pollution is associated with numerous adverse health impacts. Previous assessments of global attributable disease burden have been limited to urban areas or by coarse spatial resolution of concentration estimates. Recent developments in remote sensing, global chemical-transport models, and improvements in coverage of surface measurements facilitate virtually complete spatially resolved global air pollutant concentration estimates. We combined these data to generate global estimates of long-term average ambient concentrations of fine particles (PM2.5) and ozone at 0.1° × 0.1° spatial resolution for 1990 and 2005. In 2005, 89% of the world’s population lived in areas where the World Health Organization Air Quality Guideline of 10 μg/m3 PM2.5 (annual average) was exceeded. Globally, 32% of the population lived in areas exceeding the WHO Level 1 Interim Target of 35 μg/m3, driven by high proportions in East (76%) and South (26%) Asia. The highest seasonal ozone levels were found in North and Latin...
668 citations
TL;DR: The SL2013sv model as discussed by the authors is constrained by an unprecedentedly large set of waveform fits (∼3/4 of a million broad-band seismograms), computed in seismogram-dependent frequency bands, up to a maximum period range of 11-450 s. The model is parametrized on a triangular grid with a ∼280 km spacing.
Abstract: S U M M A R Y The rapid expansion of broad-band seismic networks over the last decade has paved the way for a new generation of global tomographic models. Significantly improved resolution of global upper-mantle and crustal structure can now be achieved, provided that structural information is extracted effectively from both surface and body waves and that the effects of errors in the data are controlled and minimized. Here, we present a new global, vertically polarized shear speed model that yields considerable improvements in resolution, compared to previous ones, for a variety of features in the upper mantle and crust. The model, SL2013sv, is constrained by an unprecedentedly large set of waveform fits (∼3/4 of a million broad-band seismograms), computed in seismogram-dependent frequency bands, up to a maximum period range of 11– 450 s. Automated multimode inversion of surface and S-wave forms was used to extract a set of linear equations with uncorrelated uncertainties from each seismogram. The equations described perturbations in elastic structure within approximate sensitivity volumes between sources and receivers. Going beyond ray theory, we calculated the phase of every mode at every frequency and its derivative with respect to Sand P-velocity perturbations by integration over a sensitivity area in a 3-D reference model; the (normally small) perturbations of the 3-D model required to fit the waveforms were then linearized using these accurate derivatives. The equations yielded by the waveform inversion of all the seismograms were simultaneously inverted for a 3-D model of shear and compressional speeds and azimuthal anisotropy within the crust and upper mantle. Elaborate outlier analysis was used to control the propagation of errors in the data (source parameters, timing at the stations, etc.). The selection of only the most mutually consistent equations exploited the data redundancy provided by our data set and strongly reduced the effect of the errors, increasing the resolution of the imaging. Our new shear speed model is parametrized on a triangular grid with a ∼280 km spacing. In well-sampled continental domains, lateral resolution approaches or exceeds that of regionalscale studies. The close match of known surface expressions of deep structure with the distribution of anomalies in the model provides a useful benchmark. In oceanic regions, spreading ridges are very well resolved, with narrow anomalies in the shallow mantle closely confined near the ridge axis, and those deeper, down to 100–120 km, showing variability in their width and location with respect to the ridge. Major subduction zones worldwide are well captured, extending from shallow depths down to the transition zone. The large size of our waveform fit data set also provides a strong statistical foundation to re-examine the validity field of the JWKB approximation and surface wave ray theory. Our analysis shows that the approximations are likely to be valid within certain time–frequency portions of most seismograms with high signal-to-noise ratios, and these portions can be identified using a set of consistent criteria that we apply in the course of waveform fitting.
497 citations
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TL;DR: The principles of ecological succession bear importantly on the relationships between man and nature and needs to be examined as a basis for resolving man’s present environmental crisis.
Abstract: The principles of ecological succession bear importantly on the relationships between man and nature. The framework of successional theory needs to be examined as a basis for resolving man’s present environmental crisis. Most ideas pertaining to the development of ecological systems are based on descriptive data obtained by observing changes in biotic communities over long periods, or on highly theoretical assumptions; very few of the generally accepted hypotheses have been tested experimentally. Some of the confusion, vagueness, and lack of experimental work in this area stems from the tendency of ecologists to regard “succession” as a single straightforward idea; in actual fact, it entails an interacting complex of processes, some of which counteract one another.
4,419 citations
University of California, Berkeley1, University of Bayreuth2, Oak Ridge National Laboratory3, United States Department of Agriculture4, University of Montana5, Oregon State University6, Dresden University of Technology7, Duke University8, Yale University9, University of Edinburgh10, National Oceanic and Atmospheric Administration11, Harvard University12, San Diego State University13, Technical University of Denmark14, Indiana University15, Tuscia University16, University of Nebraska–Lincoln17, University of Helsinki18
TL;DR: The FLUXNET project as mentioned in this paper is a global network of micrometeorological flux measurement sites that measure the exchanges of carbon dioxide, water vapor, and energy between the biosphere and atmosphere.
Abstract: FLUXNET is a global network of micrometeorological flux measurement sites that measure the exchanges of carbon dioxide, water vapor, and energy between the biosphere and atmosphere. At present over 140 sites are operating on a long-term and continuous basis. Vegetation under study includes temperate conifer and broadleaved (deciduous and evergreen) forests, tropical and boreal forests, crops, grasslands, chaparral, wetlands, and tundra. Sites exist on five continents and their latitudinal distribution ranges from 70°N to 30°S. FLUXNET has several primary functions. First, it provides infrastructure for compiling, archiving, and distributing carbon, water, and energy flux measurement, and meteorological, plant, and soil data to the science community. (Data and site information are available online at the FLUXNET Web site, http://www-eosdis.ornl.gov/FLUXNET/.) Second, the project supports calibration and flux intercomparison activities. This activity ensures that data from the regional networks are intercomparable. And third, FLUXNET supports the synthesis, discussion, and communication of ideas and data by supporting project scientists, workshops, and visiting scientists. The overarching goal is to provide information for validating computations of net primary productivity, evaporation, and energy absorption that are being generated by sensors mounted on the NASA Terra satellite. Data being compiled by FLUXNET are being used to quantify and compare magnitudes and dynamics of annual ecosystem carbon and water balances, to quantify the response of stand-scale carbon dioxide and water vapor flux densities to controlling biotic and abiotic factors, and to validate a hierarchy of soil–plant–atmosphere trace gas exchange models. Findings so far include 1) net CO 2 exchange of temperate broadleaved forests increases by about 5.7 g C m −2 day −1 for each additional day that the growing season is extended; 2) the sensitivity of net ecosystem CO 2 exchange to sunlight doubles if the sky is cloudy rather than clear; 3) the spectrum of CO 2 flux density exhibits peaks at timescales of days, weeks, and years, and a spectral gap exists at the month timescale; 4) the optimal temperature of net CO 2 exchange varies with mean summer temperature; and 5) stand age affects carbon dioxide and water vapor flux densities.
3,162 citations
TL;DR: In this paper, the effects of disturbances caused by climate change on forestshave have been studied and the authors have focused on the ability of species to tolerate tem-perature and moisture changes and to disperse.
Abstract: tudies of the effects of climate change on forestshave focused on the ability of species to tolerate tem-perature and moisture changes and to disperse,but they haveignored the effects of disturbances caused by climate change(e.g.,Ojima et al.1991).Yet modeling studies indicate the im-portance of climate effects on disturbance regimes (He et al.1999). Local, regional, and global changes in temperatureand precipitation can influence the occurrence, timing, fre-quency,duration,extent,and intensity of disturbances (Baker1995, Turner et al. 1998). Because trees can survive fromdecades to centuries and take years to become established,climate-change impacts are expressed in forests, in part,through alterations in disturbance regimes (Franklin et al.1992, Dale et al. 2000).Disturbances,both human-induced and natural,shape for-est systems by influencing their composition,structure,andfunctional processes.Indeed,the forests of the United Statesare molded by their land-use and disturbance history.Withinthe United States,natural disturbances having the greatest ef-fects on forests include fire,drought,introduced species,in-sect and pathogen outbreaks, hurricanes, windstorms, icestorms, and landslides (Figure 1). Each disturbance affectsforests differently. Some cause large-scale tree mortality,whereas others affect community structure and organizationwithout causing massive mortality (e.g., ground fires). For-est disturbances influence how much carbon is stored intrees or dead wood. All these natural disturbances interactwith human-induced effects on the environment,such as airpollution and land-use change resulting from resource ex-traction, agriculture, urban and suburban expansion, andrecreation.Some disturbances can be functions of both nat-ural and human conditions (e.g., forest fire ignition andspread) (Figure 2).
2,080 citations
TL;DR: The cumulative impact of the mountain pine beetle outbreak in the affected region during 2000–2020 will be 270 megatonnes (Mt) carbon, which converted the forest from a small net carbon sink to a large net carbon source both during and immediately after the outbreak.
Abstract: The mountain pine beetle (Dendroctonus ponderosae Hopkins, Coleoptera: Curculionidae, Scolytinae) is a native insect of the pine forests of western North America, and its populations periodically erupt into large-scale outbreaks. During outbreaks, the resulting widespread tree mortality reduces forest carbon uptake and increases future emissions from the decay of killed trees. The impacts of insects on forest carbon dynamics, however, are generally ignored in large-scale modelling analyses. The current outbreak in British Columbia, Canada, is an order of magnitude larger in area and severity than all previous recorded outbreaks. Here we estimate that the cumulative impact of the beetle outbreak in the affected region during 2000-2020 will be 270 megatonnes (Mt) carbon (or 36 g carbon m(-2) yr(-1) on average over 374,000 km2 of forest). This impact converted the forest from a small net carbon sink to a large net carbon source both during and immediately after the outbreak. In the worst year, the impacts resulting from the beetle outbreak in British Columbia were equivalent to approximately 75% of the average annual direct forest fire emissions from all of Canada during 1959-1999. The resulting reduction in net primary production was of similar magnitude to increases observed during the 1980s and 1990s as a result of global change. Climate change has contributed to the unprecedented extent and severity of this outbreak. Insect outbreaks such as this represent an important mechanism by which climate change may undermine the ability of northern forests to take up and store atmospheric carbon, and such impacts should be accounted for in large-scale modelling analyses.
1,749 citations