Equilibrium responses of global net primary production and carbon storage to doubled atmospheric carbon dioxide: sensitivity to changes in vegetation nitrogen concentration

We ran the terrestrial ecosystem model (TEM) for the globe at 0.5° resolution for atmospheric CO2 concentrations of 340 and 680 parts per million by volume (ppmv) to evaluate global and regional responses of net primary production (NPP) and carbon storage to elevated CO2 for their sensitivity to changes in vegetation nitrogen concentration. At 340 ppmv, TEM estimated global NPP of 49.0 1015 g (Pg) C yr−1 and global total carbon storage of 1701.8 Pg C; the estimate of total carbon storage does not include the carbon content of inert soil organic matter. For the reference simulation in which doubled atmospheric CO2 was accompanied with no change in vegetation nitrogen concentration, global NPP increased 4.1 Pg C yr−1 (8.3%), and global total carbon storage increased 114.2 Pg C. To examine sensitivity in the global responses of NPP and carbon storage to decreases in the nitrogen concentration of vegetation, we compared doubled CO2 responses of the reference TEM to simulations in which the vegetation nitrogen concentration was reduced without influencing decomposition dynamics (“lower N” simulations) and to simulations in which reductions in vegetation nitrogen concentration influence decomposition dynamics (“lower N+D” simulations). We conducted three lower N simulations and three lower N+D simulations in which we reduced the nitrogen concentration of vegetation by 7.5, 15.0, and 22.5%. In the lower N simulations, the response of global NPP to doubled atmospheric CO2 increased approximately 2 Pg C yr−1 for each incremental 7.5% reduction in vegetation nitrogen concentration, and vegetation carbon increased approximately an additional 40 Pg C, and soil carbon increased an additional 30 Pg C, for a total carbon storage increase of approximately 70 Pg C. In the lower N+D simulations, the responses of NPP and vegetation carbon storage were relatively insensitive to differences in the reduction of nitrogen concentration, but soil carbon storage showed a large change. The insensitivity of NPP in the N+D simulations occurred because potential enhancements in NPP associated with reduced vegetation nitrogen concentration were approximately offset by lower nitrogen availability associated with the decomposition dynamics of reduced litter nitrogen concentration. For each 7.5% reduction in vegetation nitrogen concentration, soil carbon increased approximately an additional 60 Pg C, while vegetation carbon storage increased by only approximately 5 Pg C. As the reduction in vegetation nitrogen concentration gets greater in the lower N+D simulations, more of the additional carbon storage tends to become concentrated in the north temperate-boreal region in comparison to the tropics. Other studies with TEM show that elevated CO2 more than offsets the effects of climate change to cause increased carbon storage. The results of this study indicate that carbon storage would be enhanced by the influence of changes in plant nitrogen concentration on carbon assimilation and decomposition rates. Thus changes in vegetation nitrogen concentration may have important implications for the ability of the terrestrial biosphere to mitigate increases in the atmospheric concentration of CO2 and climate changes associated with the increases

Impacts of extreme winter warming events on litter decomposition in a sub-Arctic heathland

Arctic climate change is expected to lead to a greater frequency of extreme winter warming events. During these events, temperatures rapidly increase to well above 0 degrees C for a number of days, which can lead to snow melt at the landscape scale, loss of insulating snow cover and warming of soils. However, upon return of cold ambient temperatures, soils can freeze deeper and may experience more freeze-thaw cycles due to the absence of a buffering snow layer. Such loss of snow cover and changes in soil temperatures may be critical for litter decomposition since a stable soil microclimate during winter (facilitated by snow cover) allows activity of soil organisms. Indeed, a substantial part of fresh litter decomposition may occur in winter. However, the impacts of extreme winter warming events on soil processes such as decomposition have never before been investigated. With this study we quantify the impacts of winter warming events on fresh litter decomposition using field simulations and lab studies. Winter warming events were simulated in sub-Arctic heathland using infrared heating lamps and soil warming cables during March (typically the period of maximum snow depth) in three consecutive years of 2007, 2008, and 2009. During the winters of 2008 and 2009, simulations were also run in January (typically a period of shallow snow cover) on separate plots. The lab study included soil cores with and without fresh litter subjected to winter-warming simulations in climate chambers. Litter decomposition of common plant species was unaffected by winter warming events simulated either in the lab (litter of Betula pubescens ssp. czerepanovii), or field (litter of Vaccinium vitis-idaea, and B. pubescens ssp. czerepanovii) with the exception of Vaccinium myrtillus (a common deciduous dwarf shrub) that showed less mass loss in response to winter warming events. Soil CO2 efflux measured in the lab study was (as expected) highly responsive to winter warming events but surprisingly fresh litter decomposition was not. Most fresh litter mass loss in the lab occurred during the first 3-4 weeks (simulating the period after litter fall). In contrast to past understanding, this suggests that winter decomposition of fresh litter is almost nonexistent and observations of substantial mass loss across the cold season seen here and in other studies may result from leaching in autumn, prior to the onset of "true" winter. Further, our findings surprisingly suggest that extreme winter warming events do not affect fresh litter decomposition. Crown Copyright (c) 2009 Published by Elsevier Ltd. All rights reserved

Interactions between carbon and nitrogen dynamics in estimating net primary productivity for potential vegetation in North America

We use the terrestrial ecosystem model (TEM), a process-based model, to investigate how interactions between carbon (C) and nitrogen (N) dynamics affect predictions of net primary productivity (NPP) for potential vegetation in North America. Data on pool sizes and fluxes of C and N from intensively studied field sites are used to calibrate the model for each of 17 non-wetland vegetation types. We use information on climate, soils, and vegetation to make estimates for each of 11,299 non-wetland, 0.5° latitude × 0.5° longitude, grid cells in North America. The potential annual NPP and net N mineralization (NETNMIN) of North America are estimated to be 7.032 × 1015 g C yr−1 and 104.6 × 1012 g N yr−1, respectively. Both NPP and NETNMIN increase along gradients of increasing temperature and moisture in northern and temperate regions of the continent, respectively. Nitrogen limitation of productivity is weak in tropical forests, increasingly stronger in temperate and boreal forests, and very strong in tundra ecosystems. The degree to which productivity is limited by the availability of N also varies within ecosystems. Thus spatial resolution in estimating exchanges of C between the atmosphere and the terrestrial biosphere is improved by modeling the linkage between C and N dynamics. We also perform a factorial experiment with TEM on temperate mixed forest in North America to evaluate the importance of considering interactions between C and N dynamics in the response of NPP to an elevated temperature of 2°C. With the C cycle uncoupled from the N cycle, NPP decreases primarily because of higher plant respiration. However, with the C and N cycles coupled, NPP increases because productivity that is due to increased N availability more than offsets the higher costs of plant respiration. Thus, to investigate how global change will affect biosphere-atmosphere interactions, process-based models need to consider linkages between the C and N cycles

Potential net primary productivity in South America: application of a global model

We use a mechanistically based ecosystem simulation model to describe and analyze the spatial and temporal patterns of terrestrial net primary productivity (NPP) in South America. The Terrestrial Ecosystem Model (TEM) is designed to predict major carbon and nitrogen fluxes and pool sizes in terrestrial ecosystems at continental to global scales. Information from intensively studies field sites is used in combination with continental—scale information on climate, soils, and vegetation to estimate NPP in each of 5888 non—wetland, 0.5° latitude °0.5° longitude grid cells in South America, at monthly time steps. Preliminary analyses are presented for the scenario of natural vegetation throughout the continent, as a prelude to evaluating human impacts on terrestrial NPP. The potential annual NPP of South America is estimated to be 12.5 Pg/yr of carbon (26.3 Pg/yr of organic matter) in a non—wetland area of 17.0 ° 106 km2. More than 50% of this production occurs in the tropical and subtropical evergreen forest region. Six independent model runs, each based on an independently derived set of model parameters, generated mean annual NPP estimates for the tropical evergreen forest region ranging from 900 to 1510 g°m—2°yr—1 of carbon, with an overall mean of 1170 g°m—2°yr—1. Coefficients of variation in estimated annual NPP averaged 20% for any specific location in the evergreen forests, which is probably within the confidence limits of extant NPP measurements. Predicted rates of mean annual NPP in other types of vegetation ranged from 95 g°m—2°yr—1 in arid shrublands to 930 g°m@?yr—1 in savannas, and were within the ranges measured in empirical studies. The spatial distribution of predicted NPP was directly compared with estimates made using the Miami mode of Lieth (1975). Overall, TEM predictions were °10% lower than those of the Miami model, but the two models agreed closely on the spatial patterns of NPP in south America. Unlike previous models, however, TEM estimates NPP monthly, allowing for the evaluation of seasonal phenomena. This is an important step toward integration of ecosystem models with remotely sensed information, global climate models, and atmospheric transport models, all of which are evaluated at comparable spatial and temporal scales. Seasonal patterns of NPP in South America are correlated with moisture availability in most vegetation types, but are strongly influenced by seasonal differences in cloudiness in the tropical evergreen forests. On an annual basis, moisture availability was the factor that was correlated most strongly with annual NPP in South America, but differences were again observed among vegetation types. These results allow for the investigation and analysis of climatic controls over NPP at continental scales, within and among vegetation types, and within years. Further model validation is needed. Nevertheless, the ability to investigate NPP—environment interactions with a high spatial and temporal resolution at continental scales should prove useful if not essential for rigorous analysis of the potential effects of global climate changes on terrestrial ecosystems

Potential Direct and Indirect Effects of Global Cellulosic Biofuel Production on Greenhouse Gas Fluxes from Future Land-use Chage

http://globalchange.mit.edu/research/publications/2240The production of cellulosic biofuels may have a large influence on future land emissions of greenhouse gases. These effects will vary across space and time depending on land-use policies, trade, and variations in environmental conditions. We link an economic model with a terrestrial biogeochemistry model to explore how projections of cellulosic biofuels production may influence future land emissions of carbon and nitrous oxide. Tropical regions, particularly Africa and Latin America, are projected to become major producers of biofuels. Most biofuels production is projected to occur on lands that would otherwise be used to produce crops, livestock and timber. Biofuels production leads to displacement and a redistribution of global food and timber production along with a reduction in the trade of food products. Overall, biofuels production and the displacement of other managed lands increase emissions of greenhouse gases primarily as a result of carbon emissions from deforestation and nitrous oxide emissions from fertilizer applications to maximize biofuel crop production in tropical regions. With optimal application of nitrogen fertilizers, cellulosic biofuels production may enhance carbon sequestration in soils of some regions. As a result, the relative importance of carbon emissions versus nitrous oxide emissions varies among regions. Reductions in carbon sequestration by natural ecosystems caused by the expansion of biofuels have minor effects on the global greenhouse gas budget and are more than compensated by concurrent biofuel-induced reductions in nitrous oxide emissions from natural ecosystems. Land policies that avoid deforestation and fertilizer applications, particularly in tropical regions, will have the largest impact on minimizing land emissions of greenhouse gas from cellulosic biofuels production.This research was supported in part by the David and Lucile Packard Foundation to the MBL, Department of Energy, Office of Science (BER) grants DE-FG02-94ER61937, DE-FG02- 93ER61677, DE-FG02-08ER64648, EPA grant XA-83240101, NSF grant BCS-0410344, and the industrial and foundation sponsors of the MIT Joint Program on the Science and Policy of Global Change

The AMSC mobile satellite system

The American Mobile Satellite Consortium (AMSC) Mobile Satellite Service (MSS) system is described. AMSC will use three multi-beam satellites to provide L-band MSS coverage to the United States, Canada and Mexico. The AMSC MSS system will have several noteworthy features, including a priority assignment processor that will ensure preemptive access to emergency services, a flexible SCPC channel scheme that will support a wide diversity of services, enlarged system capacity through frequency and orbit reuse, and high effective satellite transmitted power. Each AMSC satellite will make use of 14 MHz (bi-directional) of L-band spectrum. The Ku-band will be used for feeder links

Emotion classification in Parkinson's disease by higher-order spectra and power spectrum features using EEG signals: A comparative study

Deficits in the ability to process emotions characterize several neuropsychiatric disorders and are traits of Parkinson's disease (PD), and there is need for a method of quantifying emotion, which is currently performed by clinical diagnosis. Electroencephalogram (EEG) signals, being an activity of central nervous system (CNS), can reflect the underlying true emotional state of a person. This study applied machine-learning algorithms to categorize EEG emotional states in PD patients that would classify six basic emotions (happiness and sadness, fear, anger, surprise and disgust) in comparison with healthy controls (HC). Emotional EEG data were recorded from 20 PD patients and 20 healthy age-, education level- and sex-matched controls using multimodal (audio-visual) stimuli. The use of nonlinear features motivated by the higher-order spectra (HOS) has been reported to be a promising approach to classify the emotional states. In this work, we made the comparative study of the performance of k-nearest neighbor (kNN) and support vector machine (SVM) classifiers using the features derived from HOS and from the power spectrum. Analysis of variance (ANOVA) showed that power spectrum and HOS based features were statistically significant among the six emotional states (p < 0.0001). Classification results shows that using the selected HOS based features instead of power spectrum based features provided comparatively better accuracy for all the six classes with an overall accuracy of 70.10% ± 2.83% and 77.29% ± 1.73% for PD patients and HC in beta (13-30 Hz) band using SVM classifier. Besides, PD patients achieved less accuracy in the processing of negative emotions (sadness, fear, anger and disgust) than in processing of positive emotions (happiness, surprise) compared with HC. These results demonstrate the effectiveness of applying machine learning techniques to the classification of emotional states in PD patients in a user independent manner using EEG signals. The accuracy of the system can be improved by investigating the other HOS based features. This study might lead to a practical system for noninvasive assessment of the emotional impairments associated with neurological disorders

Soil respiration in a northeastern US temperate forest: a 22‐year synthesis

To better understand how forest management, phenology, vegetation type, and actual and simulated climatic change affect seasonal and inter‐annual variations in soil respiration (Rs), we analyzed more than 100,000 individual measurements of soil respiration from 23 studies conducted over 22 years at the Harvard Forest in Petersham, Massachusetts, USA. We also used 24 site‐years of eddy‐covariance measurements from two Harvard Forest sites to examine the relationship between soil and ecosystem respiration (Re). Rs was highly variable at all spatial (respiration collar to forest stand) and temporal (minutes to years) scales of measurement. The response of Rs to experimental manipulations mimicking aspects of global change or aimed at partitioning Rs into component fluxes ranged from −70% to +52%. The response appears to arise from variations in substrate availability induced by changes in the size of soil C pools and of belowground C fluxes or in environmental conditions. In some cases (e.g., logging, warming), the effect of experimental manipulations on Rs was transient, but in other cases the time series were not long enough to rule out long‐term changes in respiration rates. Inter‐annual variations in weather and phenology induced variation among annual Rs estimates of a magnitude similar to that of other drivers of global change (i.e., invasive insects, forest management practices, N deposition). At both eddy‐covariance sites, aboveground respiration dominated Re early in the growing season, whereas belowground respiration dominated later. Unusual aboveground respiration patterns—high apparent rates of respiration during winter and very low rates in mid‐to‐late summer—at the Environmental Measurement Site suggest either bias in Rs and Re estimates caused by differences in the spatial scale of processes influencing fluxes, or that additional research on the hard‐to‐measure fluxes (e.g., wintertime Rs, unaccounted losses of CO2 from eddy covariance sites), daytime and nighttime canopy respiration and its impacts on estimates of Re, and independent measurements of flux partitioning (e.g., aboveground plant respiration, isotopic partitioning) may yield insight into the unusually high and low fluxes. Overall, however, this data‐rich analysis identifies important seasonal and experimental variations in Rs and Re and in the partitioning of Re above‐ vs. belowground

The effects of CO2, climate and land-use on terrestrial carbon balance, 1920-1992: An analysis with four process-based ecosystem models

The concurrent effects of increasing atmospheric CO2 concentration, climate variability, and cropland establishment and abandonment on terrestrial carbon storage between 1920 and 1992 were assessed using a standard simulation protocol with four process-based terrestrial biosphere models. Over the long-term(1920–1992), the simulations yielded a time history of terrestrial uptake that is consistent (within the uncertainty) with a long-term analysis based on ice core and atmospheric CO2 data. Up to 1958, three of four analyses indicated a net release of carbon from terrestrial ecosystems to the atmosphere caused by cropland establishment. After 1958, all analyses indicate a net uptake of carbon by terrestrial ecosystems, primarily because of the physiological effects of rapidly rising atmospheric CO2. During the 1980s the simulations indicate that terrestrial ecosystems stored between 0.3 and 1.5 Pg C yr−1, which is within the uncertainty of analysis based on CO2 and O2 budgets. Three of the four models indicated (in accordance with O2 evidence) that the tropics were approximately neutral while a net sink existed in ecosystems north of the tropics. Although all of the models agree that the long-term effect of climate on carbon storage has been small relative to the effects of increasing atmospheric CO2 and land use, the models disagree as to whether climate variability and change in the twentieth century has promoted carbon storage or release. Simulated interannual variability from 1958 generally reproduced the El Niño/Southern Oscillation (ENSO)-scale variability in the atmospheric CO2 increase, but there were substantial differences in the magnitude of interannual variability simulated by the models. The analysis of the ability of the models to simulate the changing amplitude of the seasonal cycle of atmospheric CO2 suggested that the observed trend may be a consequence of CO2 effects, climate variability, land use changes, or a combination of these effects. The next steps for improving the process-based simulation of historical terrestrial carbon include (1) the transfer of insight gained from stand-level process studies to improve the sensitivity of simulated carbon storage responses to changes in CO2 and climate, (2) improvements in the data sets used to drive the models so that they incorporate the timing, extent, and types of major disturbances, (3) the enhancement of the models so that they consider major crop types and management schemes, (4) development of data sets that identify the spatial extent of major crop types and management schemes through time, and (5) the consideration of the effects of anthropogenic nitrogen deposition. The evaluation of the performance of the models in the context of a more complete consideration of the factors influencing historical terrestrial carbon dynamics is important for reducing uncertainties in representing the role of terrestrial ecosystems in future projections of the Earth system

Mobile satellite service in the United States

Mobile satellite service (MSS) has been under development in the United States for more than two decades. The service will soon be provided on a commercial basis by a consortium of eight U.S. companies called the American Mobile Satellite Consortium (AMSC). AMSC will build a three-satellite MSS system that will offer superior performance, reliability and cost effectiveness for organizations requiring mobile communications across the U.S. The development and operation of MSS in North America is being coordinated with Telesat Canada and Mexico. AMSC expects NASA to provide launch services in exchange for capacity on the first AMSC satellite for MSAT-X activities and for government demonstrations