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1.
Wolfgang Lucht Sibyll Schaphoff Tim Erbrecht Ursula Heyder Wolfgang Cramer 《Carbon balance and management》2006,1(1):6-7
Background
Dynamic Global Vegetation Models (DGVMs) compute the terrestrial carbon balance as well as the transient spatial distribution of vegetation. We study two scenarios of moderate and strong climate change (2.9 K and 5.3 K temperature increase over present) to investigate the spatial redistribution of major vegetation types and their carbon balance in the year 2100. 相似文献2.
Background
The amount of carbon dioxide in the atmosphere steadily increases as a consequence of anthropogenic emissions but with large interannual variability caused by the terrestrial biosphere. These variations in the CO2 growth rate are caused by large-scale climate anomalies but the relative contributions of vegetation growth and soil decomposition is uncertain. We use a biogeochemical model of the terrestrial biosphere to differentiate the effects of temperature and precipitation on net primary production (NPP) and heterotrophic respiration (Rh) during the two largest anomalies in atmospheric CO2 increase during the last 25 years. One of these, the smallest atmospheric year-to-year increase (largest land carbon uptake) in that period, was caused by global cooling in 1992/93 after the Pinatubo volcanic eruption. The other, the largest atmospheric increase on record (largest land carbon release), was caused by the strong El Niño event of 1997/98.Results
We find that the LPJ model correctly simulates the magnitude of terrestrial modulation of atmospheric carbon anomalies for these two extreme disturbances. The response of soil respiration to changes in temperature and precipitation explains most of the modelled anomalous CO2 flux.Conclusion
Observed and modelled NEE anomalies are in good agreement, therefore we suggest that the temporal variability of heterotrophic respiration produced by our model is reasonably realistic. We therefore conclude that during the last 25 years the two largest disturbances of the global carbon cycle were strongly controlled by soil processes rather then the response of vegetation to these large-scale climatic events. 相似文献3.
Background
The Himalayan zones, with dense forest vegetation, cover a fifth part of India and store a third part of the country reserves of soil organic carbon (SOC). However, the details of altitudinal distribution of these carbon stocks, which are vulnerable to forest management and climate change impacts, are not well known. 相似文献4.
Background
Unmanaged or old-growth forests are of paramount importance for carbon sequestration and thus for the mitigation of climate change among further implications, e.g. biodiversity aspects. Still, the importance of those forests for climate change mitigation compared to managed forests is under controversial debate. We evaluate the adequacy of referring to CO2 flux measurements alone and include external impacts on growth (nitrogen immissions, increasing temperatures, CO2 enrichment, changed precipitation patterns) for an evaluation of central European forests in this context.Results
We deduce that the use of CO2 flux measurements alone does not allow conclusions on a superiority of unmanaged to managed forests for mitigation goals. This is based on the critical consideration of uncertainties and the application of system boundaries. Furthermore, the consideration of wood products for material and energetic substitution obviously overrules the mitigation potential of unmanaged forests. Moreover, impacts of nitrogen immissions, CO2 enrichment of the atmosphere, increasing temperatures and changed precipitation patterns obviously lead to a meaningful increase in growth, even in forests of higher age.Conclusions
An impact of unmanaged forests on climate change mitigation cannot be valued by CO2 flux measurements alone. Further research is needed on cause and effect relationships between management practices and carbon stocks in different compartments of forest ecosystems in order to account for human-induced changes. Unexpected growth rates in old-growth forests ?C managed or not ?C can obviously be related to external impacts and additionally to management impacts. This should lead to the reconsideration of forest management strategies. 相似文献5.
Assessment of vegetation water content is critical for monitoring vegetation condition, detecting plant water stress, assessing the risk of forest fires and evaluating water status for irrigation. The main objective of this study was to investigate the performance of various mono- and multi-variate statistical methods for estimating vegetation water content (VWC) from hyper-spectral data. Hyper-spectral data is influenced by multi-collinearity because of a large number of (independent) spectral bands being modeled by a small number of (dependent) biophysical variables. Therefore, some full spectrum methods that are known to be suitable for analyzing multi-collinear data set were chosen. Canopy spectral reflectance was obtained with a GER 3700 spectro-radiometer (400–2400 nm) in a laboratory setting and VWC was measured by calculating wet/dry weight difference per unit of ground area (g/m2) of each plant canopy (n = 95). Three multivariate statistical methods were applied to estimate VWC: (1) partial least square regression, (2) artificial neural network and (3) principal component regression. They were selected to minimize the problem related to multi-collinearity. For comparison, uni-variate techniques including narrow band ratio water index (RWI), normalized difference water index (NDWI), second soil adjusted vegetation index (SAVI2) and transferred soil adjusted vegetation index (TSAVI) were applied. For each type of vegetation index, all two-band combinations were evaluated to determine the best band combination. Validation of the methods was based on the cross validation procedure and using three statistical indicators: R2, RMSE and relative RMSE. The cross-validated results identified PLSR as the regression model providing the most accurate estimates of VWC among the various methods. The result revealed that this model is highly recommended for use with multi-collinear datasets (, RRMSECV = 0.23). Principal component regression exhibited the lowest accuracy among the multivariate models (, RRMSECV = 0.41). 相似文献
6.
Yukiko Yoshida 《Carbon balance and management》2006,1(1):12-12
Background
Architectural methods that take into account global environmental conservation generally concentrate on mitigating the heat load of buildings. Here, we evaluate the reduction of carbon dioxide (CO2) emissions that can be achieved by improving heating, ventilating, and air conditioning (HVAC) technologies. 相似文献7.
Christopher Potter Steven Klooster Robert Crabtree Shengli Huang Peggy Gross Vanessa Genovese 《Carbon balance and management》2011,6(1):1-16
Background
A simulation model based on remote sensing data for spatial vegetation properties has been used to estimate ecosystem carbon fluxes across Yellowstone National Park (YNP). The CASA (Carnegie Ames Stanford Approach) model was applied at a regional scale to estimate seasonal and annual carbon fluxes as net primary production (NPP) and soil respiration components. Predicted net ecosystem production (NEP) flux of CO2 is estimated from the model for carbon sinks and sources over multi-year periods that varied in climate and (wildfire) disturbance histories. Monthly Enhanced Vegetation Index (EVI) image coverages from the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) instrument (from 2000 to 2006) were direct inputs to the model. New map products have been added to CASA from airborne remote sensing of coarse woody debris (CWD) in areas burned by wildfires over the past two decades.Results
Model results indicated that relatively cooler and wetter summer growing seasons were the most favorable for annual plant production and net ecosystem carbon gains in representative landscapes of YNP. When summed across vegetation class areas, the predominance of evergreen forest and shrubland (sagebrush) cover was evident, with these two classes together accounting for 88% of the total annual NPP flux of 2.5 Tg C yr-1 (1 Tg = 1012 g) for the entire Yellowstone study area from 2000-2006. Most vegetation classes were estimated as net ecosystem sinks of atmospheric CO2 on annual basis, making the entire study area a moderate net sink of about +0.13 Tg C yr-1. This average sink value for forested lands nonetheless masks the contribution of areas burned during the 1988 wildfires, which were estimated as net sources of CO2 to the atmosphere, totaling to a NEP flux of -0.04 Tg C yr-1 for the entire burned area. Several areas burned in the 1988 wildfires were estimated to be among the lowest in overall yearly NPP, namely the Hellroaring Fire, Mink Fire, and Falls Fire areas.Conclusions
Rates of recovery for burned forest areas to pre-1988 biomass levels were estimated from a unique combination of remote sensing and CASA model predictions. Ecosystem production and carbon fluxes in the Greater Yellowstone Ecosystem (GYE) result from complex interactions between climate, forest age structure, and disturbance-recovery patterns of the landscape. 相似文献8.
Background
Anthropogenic CO2 uptake by the ocean decreases the pH of seawater, leading to an 'acidification' which may have potential detrimental consequences on marine organisms [1]. Ocean warming or circulation alterations induced by climate change has the potential to slowdown the rate of acidification of ocean waters by decreasing the amount of CO2 uptake by the ocean [2]. However, a recent study showed that climate change affected the decrease in pH insignificantly [3]. Here, we examine the sensitivity of future oceanic acidification to climate change feedbacks within a coupled atmosphere-ocean model and find that ocean warming dominates the climate change feedbacks. 相似文献9.
Cristina-Maria Iordan Xiangping Hu Anders Arvesen Pekka Kauppi Francesco Cherubini 《Carbon balance and management》2018,13(1):12
Background
Forests and forest products can significantly contribute to climate change mitigation by stabilizing and even potentially decreasing the concentration of carbon dioxide (CO2) in the atmosphere. Harvested wood products (HWP) represent a common widespread and cost-efficient opportunity for negative emissions. After harvest, a significant fraction of the wood remains stored in HWPs for a period that can vary from some months to many decades, whereas atmospheric carbon (C) is immediately sequestered by vegetation re-growth. This temporal mismatch between oxidation of HWPs and C uptake by vegetation generates a net sink that lasts over time. The role of temporary carbon storage in forest products has been analysed and debated in the scientific literature, but detailed bottom-up studies mapping the fate of harvested materials and quantifying the associated emission profiles at national scales are rare. In this work, we quantify the net CO2 emissions and the temporary carbon storage in forest products in Norway, Sweden and Finland for the period 1960–2015, and investigate their correlation. We use a Chi square probability distribution to model the oxidation rate of C over time in HWPs, taking into consideration specific half-lives of each category of products. We model the forest regrowth and estimate the time-distributed C removal. We also integrate the specific HWP flows with an emission inventory database to quantify the associated life-cycle emissions of fossil CO2, CH4 and N2O.Results
We find that assuming an instantaneous oxidation of HWPs would overestimate emissions of about 1.18 billion t CO2 (cumulative values for the three countries over the period 1960–2015).We also find that about 40 years after 1960, the starting year of our analysis, are sufficient to detect signs of negative emissions. The total amount of net CO2 emissions achieved in 2015 are about ??3.8 million t CO2, ??27.9 t CO2 and ??43.6 t CO2 in Norway, Sweden, and Finland, respectively.Conclusion
We argue for a more explicit accounting of the actual emission rates from HWPs in carbon balance studies and climate impact analysis of forestry systems and products, and a more transparent inclusion of the potential of HWP as negative emissions in perspective studies and scenarios. Simply assuming that all harvested carbon is instantaneously oxidized can lead to large biases and ultimately overlook the benefits of negative emissions of HWPs.10.
Collins O. Oduor Nancy Karanja Richard Onwong’a Stephen Mureithi David Pelster Gert Nyberg 《Carbon balance and management》2018,13(1):24
Background
Pasture enclosures play an important role in rehabilitating the degraded soils and vegetation, and may also influence the emission of key greenhouse gasses (GHGs) from the soil. However, no study in East Africa and in Kenya has conducted direct measurements of GHG fluxes following the restoration of degraded communal grazing lands through the establishment of pasture enclosures. A field experiment was conducted in northwestern Kenya to measure the emission of CO2, CH4 and N2O from soil under two pasture restoration systems; grazing dominated enclosure (GDE) and contractual grazing enclosure (CGE), and in the adjacent open grazing rangeland (OGR) as control. Herbaceous vegetation cover, biomass production, and surface (0–10 cm) soil organic carbon (SOC) were also assessed to determine their relationship with the GHG flux rate.Results
Vegetation cover was higher enclosure systems and ranged from 20.7% in OGR to 40.2% in GDE while aboveground biomass increased from 72.0 kg DM ha?1 in OGR to 483.1 and 560.4 kg DM ha?1 in CGE and GDE respectively. The SOC concentration in GDE and CGE increased by an average of 27% relative to OGR and ranged between 4.4 g kg?1 and 6.6 g kg?1. The mean emission rates across the grazing systems were 18.6 μg N m?2 h?1, 50.1 μg C m?2 h?1 and 199.7 mg C m?2 h?1 for N2O, CH4, and CO2, respectively. Soil CO2 emission was considerably higher in GDE and CGE systems than in OGR (P?<?0.001). However, non-significantly higher CH4 and N2O emissions were observed in GDE and CGE compared to OGR (P?=?0.33 and 0.53 for CH4 and N2O, respectively). Soil moisture exhibited a significant positive relationship with CO2, CH4, and N2O, implying that it is the key factor influencing the flux rate of GHGs in the area.Conclusions
The results demonstrated that the establishment of enclosures in tropical rangelands is a valuable intervention for improving pasture production and restoration of surface soil properties. However, a long-term study is required to evaluate the patterns in annual CO2, N2O, CH4 fluxes from soils and determine the ecosystem carbon balance across the pastoral landscape.11.
Ben I McNeil 《Carbon balance and management》2006,1(1):5-4
Background
Under the United Nations convention on the law of the sea (1982), each participating country maintains exclusive economic and environmental rights within the oceanic region extending 200 nm from its coastline, known as the Exclusive Economic Zone (EEZ). Although the ocean within each EEZ has a vast capacity to absorb anthropogenic CO2 and therefore potentially be used as a carbon sink, it is not mentioned within the Kyoto Protocol most likely due to inadequate quantitative estimates. Here, I use two methods to estimate the anthropogenic CO2 storage and uptake for a typically large EEZ (Australia). 相似文献12.
Background
The repeated freeze-thaw events during cold season, freezing of soils in autumn and thawing in spring are typical for the tundra, boreal, and temperate soils. The thawing of soils during winter-summer transitions induces the release of decomposable organic carbon and acceleration of soil respiration. The winter-spring fluxes of CO2 from permanently and seasonally frozen soils are essential part of annual carbon budget varying from 5 to 50%. The mechanisms of the freeze-thaw activation are not absolutely clear and need clarifying. We investigated the effect of repeated freezing-thawing events on CO2 emission from intact arable and forest soils (Luvisols, loamy silt; Central Germany) at different moisture (65% and 100% of WHC). 相似文献13.
Background
Soil organic carbon (SOC) represents a significant pool of carbon within the biosphere. Climatic shifts in temperature and precipitation have a major influence on the decomposition and amount of SOC stored within an ecosystem and that released into the atmosphere. We have linked net primary production (NPP) algorithms, which include the impact of enhanced atmospheric CO2 on plant growth, to the SOCRATES terrestrial carbon model to estimate changes in SOC for the Australia continent between the years 1990 and 2100 in response to climate changes generated by the CSIRO Mark 2 Global Circulation Model (GCM). 相似文献14.
Background
Fires emit significant amounts of CO2 to the atmosphere. These emissions, however, are highly variable in both space and time. Additionally, CO2 emissions estimates from fires are very uncertain. The combination of high spatial and temporal variability and substantial uncertainty associated with fire CO2 emissions can be problematic to efforts to develop remote sensing, monitoring, and inverse modeling techniques to quantify carbon fluxes at the continental scale. Policy and carbon management decisions based on atmospheric sampling/modeling techniques must account for the impact of fire CO2 emissions; a task that may prove very difficult for the foreseeable future. This paper addresses the variability of CO2 emissions from fires across the US, how these emissions compare to anthropogenic emissions of CO2 and Net Primary Productivity, and the potential implications for monitoring programs and policy development. 相似文献15.
Jelle G van Minnen Bart J Strengers Bas Eickhout Rob J Swart Rik Leemans 《Carbon balance and management》2008,3(1):1-20
Background
Carbon plantations are introduced in climate change policy as an option to slow the build-up of atmospheric carbon dioxide (CO2) concentrations. Here we present a methodology to evaluate the potential effectiveness of carbon plantations. The methodology explicitly considers future long-term land-use change around the world and all relevant carbon (C) fluxes, including all natural fluxes. Both issues have generally been ignored in earlier studies.Results
Two different baseline scenarios up to 2100 indicate that uncertainties in future land-use change lead to a near 100% difference in estimates of carbon sequestration potentials. Moreover, social, economic and institutional barriers preventing carbon plantations in natural vegetation areas decrease the physical potential by 75–80% or more. Nevertheless, carbon plantations can still considerably contribute to slowing the increase in the atmospheric CO2 concentration but only in the long term. The most conservative set of assumptions lowers the increase of the atmospheric CO2 concentration in 2100 by a 27 ppm and compensates for 5–7% of the total energy-related CO2 emissions. The net sequestration up to 2020 is limited, given the short-term increased need for agricultural land in most regions and the long period needed to compensate for emissions through the establishment of the plantations. The potential is highest in the tropics, despite projections that most of the agricultural expansion will be in these regions. Plantations in high latitudes as Northern Europe and Northern Russia should only be established if the objective to sequester carbon is combined with other activities.Conclusion
Carbon sequestration in plantations can play an important role in mitigating the build-up of atmospheric CO2. The actual magnitude depends on natural and management factors, social barriers, and the time frame considered. In addition, there are a number of ancillary benefits for local communities and the environment. Carbon plantations are, however, particularly effective in the long term. Furthermore, plantations do not offer the ultimate solution towards stabilizing CO2 concentrations but should be part of a broader package of options with clear energy emission reduction measures. 相似文献16.
The direct estimation of nitrogen (N) in fresh vegetation is challenging due to its weak influence on leaf reflectance and the overlaps with absorption features of other compounds. Different empirical models relate in this work leaf nitrogen concentration ([N]Leaf) on Holm oak to leaf reflectance as well as derived spectral indices such as normalized difference indices (NDIs), the three bands indices (TBIs) and indices previously used to predict leaf N and chlorophyll. The models were calibrated and assessed their accuracy, robustness and the strength of relationship when other biochemicals were considered. Red edge was the spectral region most strongly correlated with [N]Leaf, whereas most of the published spectral indexes did not provide accurate estimations. NDIs and TBIs based models could achieve robust and acceptable accuracies (TBI1310,1720,730: R2 = 0.76, [0.64,0.86]; RMSE (%) = 9.36, [7.04,12.83]). These models sometimes included indices with bands close to absorption features of N bonds or nitrogenous compounds, but also of other biochemicals. Models were independently and inter-annually validated using the bootstrap method, which allowed discarding those models non-robust across different years. Partial correlation analysis revealed that spectral estimators did not strongly respond to [N]Leaf but to other leaf variables such as chlorophyll and water, even if bands close to absorption features of N bonds or compounds were present in the models. 相似文献
17.
In this study, digital images collected at a study site in the Canadian High Arctic were processed and classified to examine the spatial-temporal patterns of percent vegetation cover (PVC). To obtain the PVC of different plant functional groups (i.e., forbs, graminoids/sedges and mosses), field near infrared-green-blue (NGB) digital images were classified using an object-based image analysis (OBIA) approach. The PVC analyses comparing different vegetation types confirmed: (i) the polar semi-desert exhibited the lowest PVC with a large proportion of bare soil/rock cover; (ii) the mesic tundra cover consisted of approximately 60% mosses; and (iii) the wet sedge consisted almost exclusively of graminoids and sedges. As expected, the PVC and green normalized difference vegetation index (GNDVI; (RNIR − RGreen)/(RNIR + RGreen)), derived from field NGB digital images, increased during the summer growing season for each vegetation type: i.e., ∼5% (0.01) for polar semi-desert; ∼10% (0.04) for mesic tundra; and ∼12% (0.03) for wet sedge respectively. PVC derived from field images was found to be strongly correlated with WorldView-2 derived normalized difference spectral indices (NDSI; (Rx − Ry)/(Rx + Ry)), where Rx is the reflectance of the red edge (724.1 nm) or near infrared (832.9 nm and 949.3 nm) bands; Ry is the reflectance of the yellow (607.7 nm) or red (658.8 nm) bands with R2’s ranging from 0.74 to 0.81. NDSIs that incorporated the yellow band (607.7 nm) performed slightly better than the NDSIs without, indicating that this band may be more useful for investigating Arctic vegetation that often includes large proportions of senescent vegetation throughout the growing season. 相似文献
18.
Modelling carbon dynamics from urban land conversion: fundamental model of city in relation to a local carbon cycle 总被引：2，自引：0，他引：2
Background
The main task is to estimate the qualitative and quantitative contribution of urban territories and precisely of the process of urbanization to the Global Carbon Cycle (GCC). Note that, on the contrary to many investigations that have considered direct anthropogenic emission of CO2(urbanized territories produce ca. 96–98% of it), we are interested in more subtle, and up until the present time, weaker processes associated with the conversion of the surrounding natural ecosystems and landscapes into urban lands. Such conversion inevitably takes place when cities are sprawling and additional "natural" lands are becoming "urbanized". 相似文献19.
Knowledge of sub-pixel heterogeneity, particularly at the passive microwave scale, can improve the brightness temperature (and ultimately the soil moisture) estimation. However, the impact of surface heterogeneity (in terms of soil moisture, soil temperature and vegetation water content) on brightness temperature in an agricultural setting is relatively unknown. The Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12) provided an opportunity to evaluate sub-pixel heterogeneity at the scale of a Soil Moisture Ocean Salinity (SMOS) or the Soil Moisture Active Passive (SMAP) radiometer footprint using field measured data. The first objective of this study was to determine if accounting for surface heterogeneity reduced the error between estimated brightness temperature (Tb) and Tb measured by SMOS. It was found that when accounting for variation in surface soil moisture, temperature and vegetation water content within the pixel footprint, the error between the modelled Tb and the measured Tb was less than if a homogeneous pixel were modelled. The correlation between the surface parameters and the error associated with not accounting for surface heterogeneity were investigated. It was found that there was low to moderate correlation between the error and the coefficient of variance associated with the measured soil moisture, soil temperature and vegetation volumetric water content during the field campaign. However, it was found that the correlations changed depending on the stage of vegetation growth and the amount of time following a precipitation event. At the start of the field campaign (following a precipitation event), there was strong correlation between the error and all three surface parameters (r ≥ 0.75). Following a precipitation event close to the middle of the field campaign (during which there was rapid growth in vegetation), there was strong correlation between the error and the variability in vegetation water content (r = 0.89), moderate correlation with soil moisture (r = 0.61) and low correlation with soil temperature (r = 0.26). 相似文献
20.
This study focuses on the calibration of the effective vegetation scattering albedo (ω) and surface soil roughness parameters (HR, and NRp, p = H,V) in the Soil Moisture (SM) retrieval from L-band passive microwave observations using the L-band Microwave Emission of the Biosphere (L-MEB) model. In the current Soil Moisture and Ocean Salinity (SMOS) Level 2 (L2), v620, and Level 3 (L3), v300, SM retrieval algorithms, low vegetated areas are parameterized by ω = 0 and HR = 0.1, whereas values of ω = 0.06 − 0.08 and HR = 0.3 are used for forests. Several parameterizations of the vegetation and soil roughness parameters (ω, HR and NRp, p = H,V) were tested in this study, treating SMOS SM retrievals as homogeneous over each pixel instead of retrieving SM over a representative fraction of the pixel, as implemented in the operational SMOS L2 and L3 algorithms. Globally-constant values of ω = 0.10, HR = 0.4 and NRp = −1 (p = H,V) were found to yield SM retrievals that compared best with in situ SM data measured at many sites worldwide from the International Soil Moisture Network (ISMN). The calibration was repeated for collections of in situ sites classified in different land cover categories based on the International Geosphere-Biosphere Programme (IGBP) scheme. Depending on the IGBP land cover class, values of ω and HR varied, respectively, in the range 0.08–0.12 and 0.1–0.5. A validation exercise based on in situ measurements confirmed that using either a global or an IGBP-based calibration, there was an improvement in the accuracy of the SM retrievals compared to the SMOS L3 SM product considering all statistical metrics (R = 0.61, bias = −0.019 m3 m−3, ubRMSE = 0.062 m3 m−3 for the IGBP-based calibration; against R = 0.54, bias = −0.034 m3 m−3 and ubRMSE = 0.070 m3 m−3 for the SMOS L3 SM product). This result is a key step in the calibration of the roughness and vegetation parameters in the operational SMOS retrieval algorithm. The approach presented here is the core of a new forthcoming SMOS optimized SM product. 相似文献