Historically, human uses of land have transformed and fragmented ecosystems
, degraded biodiversity
, disrupted carbon and nitrogen cycles
and added prodigious quantities of greenhouse gases (GHGs) ...to the atmosphere
. However, in contrast to fossil-fuel carbon dioxide (CO
) emissions, trends and drivers of GHG emissions from land management and land-use change (together referred to as 'land-use emissions') have not been as comprehensively and systematically assessed. Here we present country-, process-, GHG- and product-specific inventories of global land-use emissions from 1961 to 2017, we decompose key demographic, economic and technical drivers of emissions and we assess the uncertainties and the sensitivity of results to different accounting assumptions. Despite steady increases in population (+144 per cent) and agricultural production per capita (+58 per cent), as well as smaller increases in emissions per land area used (+8 per cent), decreases in land required per unit of agricultural production (-70 per cent) kept global annual land-use emissions relatively constant at about 11 gigatonnes CO
-equivalent until 2001. After 2001, driven by rising emissions per land area, emissions increased by 2.4 gigatonnes CO
-equivalent per decade to 14.6 gigatonnes CO
-equivalent in 2017 (about 25 per cent of total anthropogenic GHG emissions). Although emissions intensity decreased in all regions, large differences across regions persist over time. The three highest-emitting regions (Latin America, Southeast Asia and sub-Saharan Africa) dominate global emissions growth from 1961 to 2017, driven by rapid and extensive growth of agricultural production and related land-use change. In addition, disproportionate emissions are related to certain products: beef and a few other red meats supply only 1 per cent of calories worldwide, but account for 25 per cent of all land-use emissions. Even where land-use change emissions are negligible or negative, total per capita CO
-equivalent land-use emissions remain near 0.5 tonnes per capita, suggesting the current frontier of mitigation efforts. Our results are consistent with existing knowledge-for example, on the role of population and economic growth and dietary choice-but provide additional insight into regional and sectoral trends.
The atmospheric concentration of carbon dioxide strongly influences global temperatures, and changes in this concentration result from variations in carbon sinks (in the ocean and the land biosphere) ...and sources (fossil-fuel burning and the transformation of natural ecosystems, such as forests, to managed land). Nutrients can be replaced by soil microbes as they decompose organic material, by plants that fix nitrogen from the air, by the addition of fertilizers or by the deposition from the atmosphere of nitrogen-containing compounds produced by industrial processes (one of the few beneficial side effects of air pollution).
Deforestation influences surface temperature locally (“local effects”), but also at neighboring or remote regions (“nonlocal effects”). Observations indicate that local effects induce a warming in ...most locations, while many climate models show a global mean cooling when simulating global deforestation. We show that a nonlocal cooling in models, which is excluded from observations, may strongly contribute to these conflicting results. For the MPI‐ESM, the globally averaged nonlocal cooling exceeds the globally averaged local warming by a factor of three, for global deforestation but also for realistic areal extents and spatial distributions of deforestation. Furthermore, the globally averaged nonlocal effects dominate the local effects in realistic scenarios across a range of climate models. We conclude that observations alone are not sufficient to capture the full biogeophysical effects, and climate models are needed to better understand and quantify the full effects of deforestation before they are considered in strategies for climate mitigation.
Plain Language Summary
Deforestation influences surface temperature at the location of deforestation (local effects) and elsewhere (nonlocal effects). Only the local effects are included in observation‐based data sets, but in reality surface temperature may in addition be substantially influenced by the nonlocal effects. Using simulations in a climate model, we show that deforestation‐induced changes in the brightness of the surface influence surface temperature mainly nonlocally and thus may be largely overlooked in observation‐based data sets. The simulations show that the nonlocal effects have a larger impact on global average surface temperature than the local effects, independent of how much area is deforested and at which latitude the deforestation takes place. A better understanding of the nonlocal effects is essential before the full climate effects of deforestation can be included into international climate policies that aim at mitigating global climate warming.
Key Points
Deforestation influences surface temperature also in locations that are not deforested
Globally averaged, this temperature change may be stronger than the temperature change at deforested locations
The surface cooling from changing surface albedo may mainly be nonlocal and thus underestimated in observation‐based estimates
Rainfall‐intense summer monsoon seasons on the Indian subcontinent that are exceeding long‐term averages cause widespread floods and landslides. Here we show that the latest generation of coupled ...climate models robustly project an intensification of very rainfall‐intense seasons (June–September). Under the shared socioeconomic pathway SSP5‐8.5, very wet monsoon seasons as observed in only 5 years in the period 1965–2015 are projected to occur 8 times more often in 2050–2100 in the multi‐model average. Under SSP2‐4.5, these seasons become only a factor of 6 times more frequent, showing that even modest efforts to mitigate climate change can have a strong impact on the frequency of very strong rainfall seasons. Besides, we find that the increasing risk of extreme seasonal rainfall is accompanied by a shift from days with light rainfall to days with moderate or heavy rainfall. Additionally, the number of wet days is projected to increase.
Plain Language Summary
The South Asian monsoon affects the life of more than one billion people. In the past, summer monsoon seasons (June–September) with very intense rainfall have been associated with widespread floods and an increased number of landslides. Here, we set the focus on the question how the probability of these very wet monsoon seasons will change in the 21st century under climate change. For this purpose, we use the latest generation of climate models with improved performance regarding the Indian monsoon as well as reduced uncertainties compared to the previous model generation. Under the strongest emission scenario, very wet monsoon seasons that used to be observed in 5 out of 50 years in the period 1965–2015 are projected to occur 8 times more frequently in 2050–2100 on multi‐model average. With modest mitigation efforts, this is reduced to a factor of 6 in the future period. Besides, this increase in frequency and intensity of extreme monsoon seasons is accompanied by a shift from days with light rainfall to days with moderate or heavy rainfall. Additionally, the number of wet days is projected to increase. The particular character of the change depends on the determination of humankind to reduce carbon emissions and implement mitigation measures.
Key Points
The latest generation of coupled climate models project an increase in severity and frequency of very wet Indian summer monsoon seasons
Very wet monsoon seasons are projected to occur 8 times more often in 2050–2100 compared to 1965–2015 under unabated climate change
On the subseasonal scale, there is a shift from days with light rainfall to days with moderate or heavy rainfall
Metalloproteases with a disintegrin domain (ADAM) has already been implicated in various cellular processes such as cytokine and growth factor shedding, proliferation, migration, and degradation of ...extracellular matrix. Their role in the development and progression of atherosclerosis in carotid lesions is however unknown. The aim of the study was to analyze expression of proteolytic ADAMs (8, 9, 10, 12, 15, 17) and their inhibitors TIMP-1, -3 in patients with high-graded carotid artery stenosis. Atherosclerotic plaques were obtained from 44 patients undergoing carotid endarterectomy (CEA) and analyzed by histochemistry, immunohistochemistry, and SYBR green-based real-time PCR. All ADAMs analyzed in our study were expressed in early as well as in advanced atherosclerotic carotid lesions. The highest expression within the plaque was observed for ADAM15 followed by ADAM8. Furthermore, a significant increase was observed in the expression of ADAM10 and ADAM12 in unstable plaques compared to unstable lesions (p = 0.05 and p = 0.036, respectively). In contrast, expression of TIMP-1 was significantly reduced in the same lesions (p = 0.020). Macrophages and smooth muscle cells showed the highest staining intensity and were positive for all ADAMs and TIMPs tested, with the exception of ADAM9. Endothelial cells at the lumen side were positive for ADAM 15 and TIMP-1, neovessels were positive also for ADAM12. In conclusion, the ADAM family of proteases seems to play an important role in the maintenance of proper vessel physiology and some ADAMs such as ADAM10 and ADAM12 might also contribute to the progression of atherosclerosis.
Forest production efficiency (FPE) metric describes how efficiently the assimilated carbon is partitioned into plants organs (biomass production, BP) or-more generally-for the production of organic ...matter (net primary production, NPP). We present a global analysis of the relationship of FPE to stand-age and climate, based on a large compilation of data on gross primary production and either BP or NPP. FPE is important for both forest production and atmospheric carbon dioxide uptake. We find that FPE increases with absolute latitude, precipitation and (all else equal) with temperature. Earlier findings-FPE declining with age-are also supported by this analysis. However, the temperature effect is opposite to what would be expected based on the short-term physiological response of respiration rates to temperature, implying a top-down regulation of carbon loss, perhaps reflecting the higher carbon costs of nutrient acquisition in colder climates. Current ecosystem models do not reproduce this phenomenon. They consistently predict lower FPE in warmer climates, and are therefore likely to overestimate carbon losses in a warming climate.
Human land use activities have resulted in large changes to the biogeochemical and biophysical properties of the Earth's surface, with consequences for climate and other ecosystem services. In the ...future, land use activities are likely to expand and/or intensify further to meet growing demands for food, fiber, and energy. As part of the World Climate Research Program Coupled Model Intercomparison Project (CMIP6), the international community has developed the next generation of advanced Earth system models (ESMs) to estimate the combined effects of human activities (e.g., land use and fossil fuel emissions) on the carbon–climate system. A new set of historical data based on the History of the Global Environment database (HYDE), and multiple alternative scenarios of the future (2015–2100) from Integrated Assessment Model (IAM) teams, is required as input for these models. With most ESM simulations for CMIP6 now completed, it is important to document the land use patterns used by those simulations. Here we present results from the Land-Use Harmonization 2 (LUH2) project, which smoothly connects updated historical reconstructions of land use with eight new future projections in the format required for ESMs. The harmonization strategy estimates the fractional land use patterns, underlying land use transitions, key agricultural management information, and resulting secondary lands annually, while minimizing the differences between the end of the historical reconstruction and IAM initial conditions and preserving changes depicted by the IAMs in the future. The new approach builds on a similar effort from CMIP5 and is now provided at higher resolution (0.25°×0.25°) over a longer time domain (850–2100, with extensions to 2300) with more detail (including multiple crop and pasture types and associated management practices) using more input datasets (including Landsat remote sensing data) and updated algorithms (wood harvest and shifting cultivation); it is assessed via a new diagnostic package. The new LUH2 products contain > 50 times the information content of the datasets used in CMIP5 and are designed to enable new and improved estimates of the combined effects of land use on the global carbon–climate system.
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