ALBERT

Description: Numerous studies have concluded that deforestation of mid to high latitudes result in a global cooling. This is mainly because of the increased albedo of deforested land which dominates over other biogeophysical and biogeochemical mechanisms in the energy balance. This dominance however may be due to an underestimation of the biogeochemical response, as carbon emissions are typically at or below the lower end of estimates. Here, we use the dynamic global vegetation model LPJmL for a better estimate of the carbon cycle under such large-scale deforestation. These studies are purely academic to understand the role of vegetation in the energy balance and the earth system. They must not be mistaken as possible mitigation options, because of the devastating effects on pristine ecosystems. We show that even optimistic assumptions on the manageability of these areas and its utilization for bioenergy crops could not make up for the strong carbon losses in connection with the losses of vegetation carbon and the long-term decline of soil carbon stocks. We find that the global biophysical bioenergy potential is 78.9 ± 7.9 EJ yr−1 of primary energy at the end of the 21st century for the most plausible scenario. Due to avoided usage of fossil fuels over the time frame of this experiment, the cooling due to the biogeophysical feedback could be supplemented by an avoided warming of approximately 0.1 to 0.3 °C. However, the extensive deforestation simulated in this study causes an immediate emission of 182.3 ± 0.7 GtC followed by long term emissions. In the most plausible scenario, this carbon debt is not neutralized even if bioenergy production is assumed to be carbon-neutral other than for the land use emissions so that global temperatures would increase by ~0.2 to 0.6 °C by the end of the 21st century. The carbon dynamics in the high latitudes, especially with respect to permafrost dynamics and long-term carbon losses, require additional attention in the role for the Earth's carbon and energy budget.

Description: Numerous studies have concluded that deforestation of the high latitudes result in a global cooling. This is mainly because of the increased albedo of deforested land which dominates over other biogeophysical and biogeochemical mechanisms in the energy balance. This dominance, however, may be due to an underestimation of the biogeochemical response, as carbon emissions are typically at or below the lower end of estimates. Here, we use the dynamic global vegetation model LPJmL for a better estimate of the carbon cycle under such large-scale deforestation. These studies are purely theoretical in order to understand the role of vegetation in the energy balance and the earth system. They must not be mistaken as possible mitigation options, because of the devastating effects on pristine ecosystems. For realistic assumptions of land suitability, the total emissions computed in this study are higher than that of previous studies assessing the effects of boreal deforestation. The warming due to biogeochemical effects ranges from 0.12 to 0.32 °C, depending on the climate sensitivity. Using LPJmL to assess the mitigation potential of bioenergy plantations in the suitable areas of the deforested region, we find that the global biophysical bioenergy potential is 68.1 ± 5.6 EJ yr−1 of primary energy at the end of the 21st century in the most plausible scenario. The avoided combustion of fossil fuels over the time frame of this experiment would lead to further cooling. However, since the carbon debt caused by the cumulative emissions is not repaid by the end of the 21st century, the global temperatures would increase by 0.04 to 0.11 °C. The carbon dynamics in the high latitudes especially with respect to permafrost dynamics and long-term carbon losses, require additional attention in the role for the Earth's carbon and energy budget.

Description: Terrestrial ecosystems of northern Eurasia are greening, yet few studies have provided definitive attribution for the changes. While prior studies point to increasing temperatures as the principle environmental control, influences from moisture and other factors are less clear. We assess how changes in temperature, precipitation, cloudiness and forest fires contribute to the trend in Gross Primary Productivity (GPP) derived from satellite data across northern Eurasia. For the period 1982–2008 we find that GPP, estimated using ensemble satellite NDVI (Normalized Difference Vegetation Index) observations from GIMMS3g and VIP datasets, is most sensitive to temperature, precipitation and cloudiness during summer, the peak of the growing season. For regional median GPP, summer temperature explains 33.3 % of the variation in GPP, while the other environmental variables explain from 2.2 to 11.8 %. Warming over the period analyzed, even without a sustained increase in precipitation, led to a significant GPP increase over 67.3 % of the region. A significant decrease in GPP was found over 6.2 % of the region, primarily the dryer grasslands in the south-western. For this area, precipitation positively correlates with GPP, as does cloudiness. This shows that the south-western part of northern Eurasia is relatively more vulnerable to drought than other areas. Our results further advance the notion that air temperature is the dominant environmental control for the recent GPP increases across northern Eurasia.

Description: A warming climate is altering land–atmosphere exchanges of carbon, with a potential for increased vegetation productivity as well as the mobilization of permafrost soil carbon stores. Here we investigate land–atmosphere carbon dioxide (CO2) dynamics through analysis of net ecosystem productivity (NEP) and its component fluxes of gross primary productivity (GPP) and ecosystem respiration (ER) and soil carbon residence time, simulated by a set of land surface models (LSMs) over a region spanning the drainage basin of northern Eurasia. The retrospective simulations were conducted over the 1960–2009 record and at 0.5° resolution, which is a scale common among many global carbon and climate model simulations. Model performance benchmarks were drawn from comparisons against both observed CO2 fluxes derived from site-based eddy covariance measurements as well as regional-scale GPP estimates based on satellite remote sensing data. The site-based comparisons show the timing of peak GPP to be well simulated. Modest overestimates in model GPP and ER are also found, which are relatively higher for two boreal forest validation sites than the two tundra sites. Across the suite of model simulations, NEP increases by as little as 0.01 to as much as 0.79 g C m−2 yr−2, equivalent to 3 to 340% of the respective model means, over the analysis period. For the multimodel average the increase is 135% of the mean from the first to last ten years of record (1960–1969 vs 2000–2009), with a weakening CO2 sink over the latter decades. Vegetation net primary productivity increased by 8 to 30% from the first to last ten years, contributing to soil carbon storage gains, while model mean residence time for soil organic carbon decreased by 10% (−5 to −16%). This suggests that inputs to the soil carbon pool exceeded losses, resulting in a net gain amid a decrease in residence time. Our analysis points to improvements in model elements controlling vegetation productivity and soil respiration as being needed for reducing uncertainty in land–atmosphere CO2 exchange. These advances require collection of new field data on vegetation and soil dynamics, the development of benchmarking datasets from measurements and remote sensing observations, and investments in future model development and intercomparison studies. Resulting improvements in parameterizations and processes driving productivity and soil respiration rates will increase confidence in model estimates of net CO2 exchange, component carbon fluxes, and underlying drivers of change across the northern high latitudes.

Description: Terrestrial ecosystems of northern Eurasia are demonstrating an increasing gross primary productivity (GPP), yet few studies have provided definitive attribution for the changes. While prior studies point to increasing temperatures as the principle environmental control, influences from moisture and other factors are less clear. We assess how changes in temperature, precipitation, cloudiness, and forest fires individually contribute to changes in GPP derived from satellite data across northern Eurasia using a light-use- efficiency-based model, for the period 1982–2010. We find that annual satellite-derived GPP is most sensitive to the temperature, precipitation and cloudiness of summer, which is the peak of the growing season and also the period of the year when the GPP trend is maximum. Considering the regional median, the summer temperature explains as much as 37.7 % of the variation in annual GPP, while precipitation and cloudiness explain 20.7 and 19.3 %. Warming over the period analysed, even without a sustained increase in precipitation, led to a significant positive impact on GPP for 61.7 % of the region. However, a significant negative impact on GPP was also found, for 2.4 % of the region, primarily the dryer grasslands in the south-west of the study area. For this region, precipitation positively correlates with GPP, as does cloudiness. This shows that the south-western part of northern Eurasia is relatively more vulnerable to drought than other areas. While our results further advance the notion that air temperature is the dominant environmental control for recent GPP increases across northern Eurasia, the role of precipitation and cloudiness can not be ignored.

Description: A warming climate is altering land-atmosphere exchanges of carbon, with a potential for increased vegetation productivity as well as the mobilization of permafrost soil carbon stores. Here we investigate land-atmosphere carbon dioxide (CO2) cycling through analysis of net ecosystem productivity (NEP) and its component fluxes of gross primary productivity (GPP) and ecosystem respiration (ER) and soil carbon residence time, simulated by a set of land surface models (LSMs) over a region spanning the drainage basin of Northern Eurasia. The retrospective simulations cover the period 1960–2009 at 0.5° resolution, which is a scale common among many global carbon and climate model simulations. Model performance benchmarks were drawn from comparisons against both observed CO2 fluxes derived from site-based eddy covariance measurements as well as regional-scale GPP estimates based on satellite remote-sensing data. The site-based comparisons depict a tendency for overestimates in GPP and ER for several of the models, particularly at the two sites to the south. For several models the spatial pattern in GPP explains less than half the variance in the MODIS MOD17 GPP product. Across the models NEP increases by as little as 0.01 to as much as 0.79 g C m−2 yr−2, equivalent to 3 to 340 % of the respective model means, over the analysis period. For the multimodel average the increase is 135 % of the mean from the first to last 10 years of record (1960–1969 vs. 2000–2009), with a weakening CO2 sink over the latter decades. Vegetation net primary productivity increased by 8 to 30 % from the first to last 10 years, contributing to soil carbon storage gains. The range in regional mean NEP among the group is twice the multimodel mean, indicative of the uncertainty in CO2 sink strength. The models simulate that inputs to the soil carbon pool exceeded losses, resulting in a net soil carbon gain amid a decrease in residence time. Our analysis points to improvements in model elements controlling vegetation productivity and soil respiration as being needed for reducing uncertainty in land-atmosphere CO2 exchange. These advances will require collection of new field data on vegetation and soil dynamics, the development of benchmarking data sets from measurements and remote-sensing observations, and investments in future model development and intercomparison studies.