Hank A. Margolis

Terrestrial Gross Carbon Dioxide Uptake: Global Distribution and Covariation with Climate

Carbon Cycle and Climate Change As climate change accelerates, it is important to know the likely impact of climate change on the carbon cycle (see the Perspective by Reich). Gross primary production (GPP) is a measure of the amount of CO2 removed from the atmosphere every year to fuel photosynthesis. Beer et al. (p. 834, published online 5 July) used a combination of observation and calculation to estimate that the total GPP by terrestrial plants is around 122 billion tons per year; in comparison, burning fossil fuels emits about 7 billion tons annually. Thirty-two percent of this uptake occurs in tropical forests, and precipitation controls carbon uptake in more than 40% of vegetated land. The temperature sensitivity (Q10) of ecosystem respiratory processes is a key determinant of the interaction between climate and the carbon cycle. Mahecha et al. (p. 838, published online 5 July) now show that the Q10 of ecosystem respiration is invariant with respect to mean annual temperature, independent of the analyzed ecosystem type, with a global mean value for Q10 of 1.6. This level of temperature sensitivity suggests a less-pronounced climate sensitivity of the carbon cycle than assumed by recent climate models. A combination of data and models provides an estimate of how much photosynthesis by all the world’s plants occurs each year. Terrestrial gross primary production (GPP) is the largest global CO2 flux driving several ecosystem functions. We provide an observation-based estimate of this flux at 123 ± 8 petagrams of carbon per year (Pg C year−1) using eddy covariance flux data and various diagnostic models. Tropical forests and savannahs account for 60%. GPP over 40% of the vegetated land is associated with precipitation. State-of-the-art process-oriented biosphere models used for climate predictions exhibit a large between-model variation of GPP’s latitudinal patterns and show higher spatial correlations between GPP and precipitation, suggesting the existence of missing processes or feedback mechanisms which attenuate the vegetation response to climate. Our estimates of spatially distributed GPP and its covariation with climate can help improve coupled climate–carbon cycle process models.

Net carbon dioxide losses of northern ecosystems in response to autumn warming

The carbon balance of terrestrial ecosystems is particularly sensitive to climatic changes in autumn and spring, with spring and autumn temperatures over northern latitudes having risen by about 1.1 °C and 0.8 °C, respectively, over the past two decades. A simultaneous greening trend has also been observed, characterized by a longer growing season and greater photosynthetic activity. These observations have led to speculation that spring and autumn warming could enhance carbon sequestration and extend the period of net carbon uptake in the future. Here we analyse interannual variations in atmospheric carbon dioxide concentration data and ecosystem carbon dioxide fluxes. We find that atmospheric records from the past 20 years show a trend towards an earlier autumn-to-winter carbon dioxide build-up, suggesting a shorter net carbon uptake period. This trend cannot be explained by changes in atmospheric transport alone and, together with the ecosystem flux data, suggest increasing carbon losses in autumn. We use a process-based terrestrial biosphere model and satellite vegetation greenness index observations to investigate further the observed seasonal response of northern ecosystems to autumnal warming. We find that both photosynthesis and respiration increase during autumn warming, but the increase in respiration is greater. In contrast, warming increases photosynthesis more than respiration in spring. Our simulations and observations indicate that northern terrestrial ecosystems may currently lose carbon dioxide in response to autumn warming, with a sensitivity of about 0.2 PgC °C-1, offsetting 90% of the increased carbon dioxide uptake during spring. If future autumn warming occurs at a faster rate than in spring, the ability of northern ecosystems to sequester carbon may be diminished earlier than previously suggested.

Global patterns of land‐atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations

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.

The Boreal Ecosystem–Atmosphere Study (BOREAS): An Overview and Early Results from the 1994 Field Year

Abstract The Boreal Ecosystem Atmosphere Study (BOREAS) is large-scale international field experiment that has the goal of improving our understanding of the exchanges of radiative energy, heat water, CO2, and trace gases between the boreal forest and the lower atmosphere. An important objective of BORES is collect the data needed to improve computer simulation models of the processes controlling these exchanges so that scientists can anticipate the effects of global change. From August 1993 through September 1994, a continuous set of monitoring measurements—meteorology, hydrology, and satellite remote sensing—were gathered over the 1000 × 1000 km BOREAS study region that covers most of Saskatchewan and Manitoba, Canada. This monitoring program was punctuated by six campaigns that saw the deployment of some 300 scientists and aircrew into the field, supported by 11 research aircraft. The participants were drawn primarily from U.S. and Canadian agencies and universities, although there were also important ...

Ecosystem carbon dioxide fluxes after disturbance in forests of North America

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.

BOREAS in 1997: Experiment overview, scientific results, and future directions

The goal of the Boreal Ecosystem-Atmosphere Study (BOREAS) is to improve our understanding of the interactions between the boreal forest biome and the atmosphere in order to clarify their roles in global change. This overview paper describes the science background and motivations for BOREAS and the experimental design and operations of the BOREAS 1994 and BOREAS 1996 field years. The findings of the 83 papers in this journal special issue are reviewed. In section 7, important scientific results of the project to date are summarized and future research directions are identified.

Observed increase in local cooling effect of deforestation at higher latitudes

Deforestation in mid- to high latitudes is hypothesized to have the potential to cool the Earth’s surface by altering biophysical processes. In climate models of continental-scale land clearing, the cooling is triggered by increases in surface albedo and is reinforced by a land albedo–sea ice feedback. This feedback is crucial in the model predictions; without it other biophysical processes may overwhelm the albedo effect to generate warming instead. Ongoing land-use activities, such as land management for climate mitigation, are occurring at local scales (hectares) presumably too small to generate the feedback, and it is not known whether the intrinsic biophysical mechanism on its own can change the surface temperature in a consistent manner. Nor has the effect of deforestation on climate been demonstrated over large areas from direct observations. Here we show that surface air temperature is lower in open land than in nearby forested land. The effect is 0.85 ± 0.44 K (mean ± one standard deviation) northwards of 45° N and 0.21 ± 0.53 K southwards. Below 35° N there is weak evidence that deforestation leads to warming. Results are based on comparisons of temperature at forested eddy covariance towers in the USA and Canada and, as a proxy for small areas of cleared land, nearby surface weather stations. Night-time temperature changes unrelated to changes in surface albedo are an important contributor to the overall cooling effect. The observed latitudinal dependence is consistent with theoretical expectation of changes in energy loss from convection and radiation across latitudes in both the daytime and night-time phase of the diurnal cycle, the latter of which remains uncertain in climate models.

Ectomycorrhizal mediation of competition between coniferous tree species

To test the effect of ectomycorrhizal fungi (EMF) on interactions between host plants, Pseudotsuga menziesii (Mirb.) Franco and Pinus ponderosa Dougl. ex. Laws., seedlings were grown in replacement series in pasteurized soil with (a) no EMF added, (A) two EMF species added - Rhizopogon vinicolor Smith (specific to Douglas-fir) and R. ochraceorubens Smith (specific to pine), and (c) tour EMF species added - the two Rhizopogon species plus two host generalists, Laccaria laccata (Scop, ex Fr.) Bk. & Br, and Hebeloma crustuliniforme (Bull.) Quel. A replacement series in unpasteurized forest soil also was included. Seedlings without added EMF were colonized by the greenhouse contaminant, Thelephora terrestris. Without added EMF (but with T. terrestris), the tree species mutually inhibited one another, producing Relative Yield Totals significantly < 1; with EMF added, mutual inhibition disappeared. With four EMF species added, Pseudotsuga menziesii seedlings were significantly larger in mixture than in monoculture, with no corresponding decrease in the size of Pinus ponderoso seedlings; this was due solely to seedlings with L. laccata, which apparently enhanced nitrogen (N) and phosphorus (P) uptake by Pseudotsuga menziesii at the expense of luxury consumption by Pinus ponderosa. Graphical analysis suggested that better growth of Pseudotosuga menziesii in mixture with EMF added was related to improved P nitrogen. Both N and P nutrition of Pinus ponderosa was better in mixture with two than no EMF species added; there was no clear nutrient effect with four EMF species added. Results indicate that EMF can reduce competition between plant species and perhaps increase overall community P uptake. However, patterns were specific to both EMF and tree species and were quite different in unpasteurized soils. Hence generalizations about the effects of EMF on plant-plant interactions must be made cautiously.

Profiles of photosynthetically active radiation, nitrogen and photosynthetic capacity in the boreal forest: Implications for scaling from leaf to canopy

Profiles of photosynthetically active radiation (PAR), leaf nitrogen per unit leaf area (Narea), and photosynthetic capacity (Amax) were measured in an aspen, two jack pine, and two black spruce stands in the BOREAS northern study area. Narea decreased with decreasing %PAR in each stand, in all conifer stands combined (r=0.52) and in all stands combined (r=0.46). Understory alder had higher Narea for similar %PAR than did aspen early in the growing season. Amax decreased with decreasing Narea, except for the negative correlation between Narea and Amax during shoot flush for jack pine. For the middle and late growing season data, Narea and Amax had r values of 0.51 for all stands combined and 0.60 for all conifer stands combined. For similar Narea the aspen stand had higher Amax than did the conifer stands. Photosynthetic capacity expressed as a percentage of Amax at the top of the canopy (%Amax0) decreased with %PAR similarly in all stands, but %Amax0 decreased at a much slower rate than did %PAR. To demonstrate the implications of the vertical distribution of Amax, three different assumptions were used to scale leaf Amax to the canopy (Acan-max): (1) constant Amax with canopy depth, (2)Amax scaled proportionally to %PAR, and (3) a linear relationship between Amax and cumulative leaf area index derived from our data. The first and third methods resulted in similar Acan-max; the second was much lower. All methods resulted in linear correlations between normalized difference vegetation indices measured from a helicopter and Acan-max (r=0.97, 0.93, and 0.97, respectively), but the slope was strongly influenced by the scaling method.

Modeling and Scaling Coupled Energy, Water, and Carbon Fluxes Based on Remote Sensing: An Application to Canada's Landmass

Abstract Land surface models (LSMs) need to be coupled with atmospheric general circulation models (GCMs) to adequately simulate the exchanges of energy, water, and carbon between the atmosphere and terrestrial surfaces. The heterogeneity of the land surface and its interaction with temporally and spatially varying meteorological conditions result in nonlinear effects on fluxes of energy, water, and carbon, making it challenging to scale these fluxes accurately. The issue of up-scaling remains one of the critical unsolved problems in the parameterization of subgrid-scale fluxes in coupled LSM and GCM models. A new distributed LSM, the Ecosystem–Atmosphere Simulation Scheme (EASS) was developed and coupled with the atmospheric Global Environmental Multiscale model (GEM) to simulate energy, water, and carbon fluxes over Canada’s landmass through the use of remote sensing and ancillary data. Two approaches (lumped case and distributed case) for handling subgrid heterogeneity were used to evaluate the effect ...