ABSTRACT
Ruminant meat provides valuable protein to humans, but livestock production has many negative environmental impacts, especially in terms of deforestation, greenhouse gas emissions, water use and eutrophication1. In addition to a dietary shift towards plant-based diets2, imitation products, including plant-based meat, cultured meat and fermentation-derived microbial protein (MP), have been proposed as means to reduce the externalities of livestock production3-7. Life cycle assessment (LCA) studies have estimated substantial environmental benefits of MP, produced in bioreactors using sugar as feedstock, especially compared to ruminant meat3,7. Here we present an analysis of MP as substitute for ruminant meat in forward-looking global land-use scenarios towards 2050. Our study complements LCA studies by estimating the environmental benefits of MP within a future socio-economic pathway. Our model projections show that substituting 20% of per-capita ruminant meat consumption with MP globally by 2050 (on a protein basis) offsets future increases in global pasture area, cutting annual deforestation and related CO2 emissions roughly in half, while also lowering methane emissions. However, further upscaling of MP, under the assumption of given consumer acceptance, results in a non-linear saturation effect on reduced deforestation and related CO2 emissions-an effect that cannot be captured with the method of static LCA.
Subject(s)
Carbon Dioxide , Greenhouse Gases , Animals , Cattle , Diet , Greenhouse Effect , Humans , Livestock , Meat , RuminantsABSTRACT
The Paris Agreement calls for a cooperative response with the aim of limiting global warming to well below two degrees Celsius above pre-industrial levels while reaffirming the principles of equity and common, but differentiated responsibilities and capabilities1. Although the goal is clear, the approach required to achieve it is not. Cap-and-trade policies using uniform carbon prices could produce cost-effective reductions of global carbon emissions, but tend to impose relatively high mitigation costs on developing and emerging economies. Huge international financial transfers are required to complement cap-and-trade to achieve equal sharing of effort, defined as an equal distribution of mitigation costs as a share of income2,3, and therefore the cap-and-trade policy is often perceived as infringing on national sovereignty2-7. Here we show that a strategy of international financial transfers guided by moderate deviations from uniform carbon pricing could achieve the goal without straining either the economies or sovereignty of nations. We use the integrated assessment model REMIND-MAgPIE to analyse alternative policies: financial transfers in uniform carbon pricing systems, differentiated carbon pricing in the absence of financial transfers, or a hybrid combining financial transfers and differentiated carbon prices. Under uniform carbon prices, a present value of international financial transfers of 4.4 trillion US dollars over the next 80 years to 2100 would be required to equalize effort. By contrast, achieving equal effort without financial transfers requires carbon prices in advanced countries to exceed those in developing countries by a factor of more than 100, leading to efficiency losses of 2.6 trillion US dollars. Hybrid solutions reveal a strongly nonlinear trade-off between cost efficiency and sovereignty: moderate deviations from uniform carbon prices strongly reduce financial transfers at relatively small efficiency losses and moderate financial transfers substantially reduce inefficiencies by narrowing the carbon price spread. We also identify risks and adverse consequences of carbon price differentiation due to market distortions that can undermine environmental sustainability targets8,9. Quantifying the advantages and risks of carbon price differentiation provides insight into climate and sector-specific policy mixes.
Subject(s)
Commerce/economics , Commerce/legislation & jurisprudence , Environmental Policy/economics , Environmental Policy/legislation & jurisprudence , Global Warming/legislation & jurisprudence , Global Warming/prevention & control , International Cooperation/legislation & jurisprudence , Global Warming/economics , Paris , Social Justice , Socioeconomic FactorsABSTRACT
Increased efforts are required to prevent further losses to terrestrial biodiversity and the ecosystem services that it provides1,2. Ambitious targets have been proposed, such as reversing the declining trends in biodiversity3; however, just feeding the growing human population will make this a challenge4. Here we use an ensemble of land-use and biodiversity models to assess whether-and how-humanity can reverse the declines in terrestrial biodiversity caused by habitat conversion, which is a major threat to biodiversity5. We show that immediate efforts, consistent with the broader sustainability agenda but of unprecedented ambition and coordination, could enable the provision of food for the growing human population while reversing the global terrestrial biodiversity trends caused by habitat conversion. If we decide to increase the extent of land under conservation management, restore degraded land and generalize landscape-level conservation planning, biodiversity trends from habitat conversion could become positive by the mid-twenty-first century on average across models (confidence interval, 2042-2061), but this was not the case for all models. Food prices could increase and, on average across models, almost half (confidence interval, 34-50%) of the future biodiversity losses could not be avoided. However, additionally tackling the drivers of land-use change could avoid conflict with affordable food provision and reduces the environmental effects of the food-provision system. Through further sustainable intensification and trade, reduced food waste and more plant-based human diets, more than two thirds of future biodiversity losses are avoided and the biodiversity trends from habitat conversion are reversed by 2050 for almost all of the models. Although limiting further loss will remain challenging in several biodiversity-rich regions, and other threats-such as climate change-must be addressed to truly reverse the declines in biodiversity, our results show that ambitious conservation efforts and food system transformation are central to an effective post-2020 biodiversity strategy.
Subject(s)
Biodiversity , Conservation of Natural Resources/methods , Conservation of Natural Resources/trends , Environmental Policy/trends , Human Activities/trends , Diet , Diet, Vegetarian/trends , Food Supply , Humans , Sustainable Development/trendsABSTRACT
A multitude of actions to protect, sustainably manage and restore natural and modified ecosystems can have co-benefits for both climate mitigation and biodiversity conservation. Reducing greenhouse emissions to limit warming to less than 1.5 or 2°C above preindustrial levels, as outlined in the Paris Agreement, can yield strong co-benefits for land, freshwater and marine biodiversity and reduce amplifying climate feedbacks from ecosystem changes. Not all climate mitigation strategies are equally effective at producing biodiversity co-benefits, some in fact are counterproductive. Moreover, social implications are often overlooked within the climate-biodiversity nexus. Protecting biodiverse and carbon-rich natural environments, ecological restoration of potentially biodiverse and carbon-rich habitats, the deliberate creation of novel habitats, taking into consideration a locally adapted and meaningful (i.e. full consequences considered) mix of these measures, can result in the most robust win-win solutions. These can be further enhanced by avoidance of narrow goals, taking long-term views and minimizing further losses of intact ecosystems. In this review paper, we first discuss various climate mitigation actions that evidence demonstrates can negatively impact biodiversity, resulting in unseen and unintended negative consequences. We then examine climate mitigation actions that co-deliver biodiversity and societal benefits. We give examples of these win-win solutions, categorized as 'protect, restore, manage and create', in different regions of the world that could be expanded, upscaled and used for further innovation.
Subject(s)
Climate Change , Ecosystem , Biodiversity , Carbon , Climate , Conservation of Natural Resources/methodsABSTRACT
Land-based climate mitigation measures have gained significant attention and importance in public and private sector climate policies. Building on previous studies, we refine and update the mitigation potentials for 20 land-based measures in >200 countries and five regions, comparing "bottom-up" sectoral estimates with integrated assessment models (IAMs). We also assess implementation feasibility at the country level. Cost-effective (available up to $100/tCO2 eq) land-based mitigation is 8-13.8 GtCO2 eq yr-1 between 2020 and 2050, with the bottom end of this range representing the IAM median and the upper end representing the sectoral estimate. The cost-effective sectoral estimate is about 40% of available technical potential and is in line with achieving a 1.5°C pathway in 2050. Compared to technical potentials, cost-effective estimates represent a more realistic and actionable target for policy. The cost-effective potential is approximately 50% from forests and other ecosystems, 35% from agriculture, and 15% from demand-side measures. The potential varies sixfold across the five regions assessed (0.75-4.8 GtCO2eq yr-1 ) and the top 15 countries account for about 60% of the global potential. Protection of forests and other ecosystems and demand-side measures present particularly high mitigation efficiency, high provision of co-benefits, and relatively lower costs. The feasibility assessment suggests that governance, economic investment, and socio-cultural conditions influence the likelihood that land-based mitigation potentials are realized. A substantial portion of potential (80%) is in developing countries and LDCs, where feasibility barriers are of greatest concern. Assisting countries to overcome barriers may result in significant quantities of near-term, low-cost mitigation while locally achieving important climate adaptation and development benefits. Opportunities among countries vary widely depending on types of land-based measures available, their potential co-benefits and risks, and their feasibility. Enhanced investments and country-specific plans that accommodate this complexity are urgently needed to realize the large global potential from improved land stewardship.
Subject(s)
Climate Change , Ecosystem , Agriculture , Feasibility Studies , PolicyABSTRACT
OBJECTIVE: The microscopic review of hematoxylin-eosin-stained images of focal cortical dysplasia type IIb and cortical tuber of tuberous sclerosis complex remains challenging. Both entities are distinct subtypes of human malformations of cortical development that share histopathological features consisting of neuronal dyslamination with dysmorphic neurons and balloon cells. We trained a convolutional neural network (CNN) to classify both entities and visualize the results. Additionally, we propose a new Web-based deep learning application as proof of concept of how deep learning could enter the pathologic routine. METHODS: A digital processing pipeline was developed for a series of 56 cases of focal cortical dysplasia type IIb and cortical tuber of tuberous sclerosis complex to obtain 4000 regions of interest and 200 000 subsamples with different zoom and rotation angles to train a neural network. Guided gradient-weighted class activation maps (Guided Grad-CAMs) were generated to visualize morphological features used by the CNN to distinguish both entities. RESULTS: Our best-performing network achieved 91% accuracy and 0.88 area under the receiver operating characteristic curve at the tile level for an unseen test set. Novel histopathologic patterns were found through the visualized Guided Grad-CAMs. These patterns were assembled into a classification score to augment decision-making in routine histopathology workup. This score was successfully validated by 11 expert neuropathologists and 12 nonexperts, boosting nonexperts to expert level performance. SIGNIFICANCE: Our newly developed Web application combines the visualization of whole slide images with the possibility of deep learning-aided classification between focal cortical dysplasia IIb and tuberous sclerosis complex. This approach will help to introduce deep learning applications and visualization for the histopathologic diagnosis of rare and difficult-to-classify brain lesions.
Subject(s)
Cerebral Cortex/pathology , Deep Learning , Epilepsy/pathology , Malformations of Cortical Development, Group I/pathology , Neurons/pathology , Tuberous Sclerosis/pathology , Algorithms , Area Under Curve , Diagnosis, Computer-Assisted , Epilepsy/diagnosis , Humans , Internet , Malformations of Cortical Development, Group I/diagnosis , Neural Networks, Computer , Neuropathology , Proof of Concept Study , ROC Curve , Reproducibility of Results , Tuberous Sclerosis/diagnosisABSTRACT
Humanity's transformation of the nitrogen cycle has major consequences for ecosystems, climate and human health, making it one of the key environmental issues of our time. Understanding how trends could evolve over the course of the 21st century is crucial for scientists and decision-makers from local to global scales. Scenario analysis is the primary tool for doing so, and has been applied across all major environmental issues, including nitrogen pollution. However, to date most scenario efforts addressing nitrogen flows have either taken a narrow approach, focusing on a singular impact or sector, or have not been integrated within a broader scenario framework - a missed opportunity given the multiple environmental and socio-economic impacts that nitrogen pollution exacerbates. Capitalizing on our expanding knowledge of nitrogen flows, this study introduces a framework for new nitrogen-focused narratives based on the widely used Shared Socioeconomic Pathways that include all the major nitrogen-polluting sectors (agriculture, industry, transport and wastewater). These new narratives are the first to integrate the influence of climate and other environmental pollution control policies, while also incorporating explicit nitrogen-control measures. The next step is for them to be used as model inputs to evaluate the impact of different nitrogen production, consumption and loss trajectories, and thus advance understanding of how to address environmental impacts while simultaneously meeting key development goals. This effort is an important step in assessing how humanity can return to the planetary boundary of this essential element over the coming century.
ABSTRACT
Agricultural expansion is a leading driver of biodiversity loss across the world, but little is known on how future land-use change may encroach on remaining natural vegetation. This uncertainty is, in part, due to unknown levels of future agricultural intensification and international trade. Using an economic land-use model, we assessed potential future losses of natural vegetation with a focus on how these may threaten biodiversity hotspots and intact forest landscapes. We analysed agricultural expansion under proactive and reactive biodiversity protection scenarios, and for different rates of pasture intensification. We found growing food demand to lead to a significant expansion of cropland at the expense of pastures and natural vegetation. In our reference scenario, global cropland area increased by more than 400 Mha between 2015 and 2050, mostly in Africa and Latin America. Grazing intensification was a main determinant of future land-use change. In Africa, higher rates of pasture intensification resulted in smaller losses of natural vegetation, and reduced pressure on biodiversity hotspots and intact forest landscapes. Investments into raising pasture productivity in conjunction with proactive land-use planning appear essential in Africa to reduce further losses of areas with high conservation value. In Latin America, in contrast, higher pasture productivity resulted in increased livestock exports, highlighting that unchecked trade can reduce the land savings of pasture intensification. Reactive protection of sensitive areas significantly reduced the conversion of natural ecosystems in Latin America. We conclude that protection strategies need to adapt to region-specific trade positions. In regions with a high involvement in international trade, area-based conservation measures should be preferred over strategies aimed at increasing pasture productivity, which by themselves might not be sufficient to protect biodiversity effectively.
Subject(s)
Agriculture/methods , Conservation of Natural Resources/methods , Ecosystem , Africa , Agriculture/trends , Biodiversity , Forests , Latin America , Models, TheoreticalABSTRACT
Most climate mitigation scenarios involve negative emissions, especially those that aim to limit global temperature increase to 2°C or less. However, the carbon uptake potential in land-based climate change mitigation efforts is highly uncertain. Here, we address this uncertainty by using two land-based mitigation scenarios from two land-use models (IMAGE and MAgPIE) as input to four dynamic global vegetation models (DGVMs; LPJ-GUESS, ORCHIDEE, JULES, LPJmL). Each of the four combinations of land-use models and mitigation scenarios aimed for a cumulative carbon uptake of ~130 GtC by the end of the century, achieved either via the cultivation of bioenergy crops combined with carbon capture and storage (BECCS) or avoided deforestation and afforestation (ADAFF). Results suggest large uncertainty in simulated future land demand and carbon uptake rates, depending on the assumptions related to land use and land management in the models. Total cumulative carbon uptake in the DGVMs is highly variable across mitigation scenarios, ranging between 19 and 130 GtC by year 2099. Only one out of the 16 combinations of mitigation scenarios and DGVMs achieves an equivalent or higher carbon uptake than achieved in the land-use models. The large differences in carbon uptake between the DGVMs and their discrepancy against the carbon uptake in IMAGE and MAgPIE are mainly due to different model assumptions regarding bioenergy crop yields and due to the simulation of soil carbon response to land-use change. Differences between land-use models and DGVMs regarding forest biomass and the rate of forest regrowth also have an impact, albeit smaller, on the results. Given the low confidence in simulated carbon uptake for a given land-based mitigation scenario, and that negative emissions simulated by the DGVMs are typically lower than assumed in scenarios consistent with the 2°C target, relying on negative emissions to mitigate climate change is a highly uncertain strategy.
Subject(s)
Carbon/metabolism , Climate Change , Biomass , Carbon Cycle , Carbon Dioxide/analysis , Carbon Sequestration , Conservation of Natural Resources , Crops, Agricultural , Forests , Soil , UncertaintyABSTRACT
One of the main challenges for the 21st century is to balance the increasing demand for high-quality proteins while mitigating environmental impacts. In particular, cropland-based production of protein-rich animal feed for livestock rearing results in large-scale agricultural land-expansion, nitrogen pollution, and greenhouse gas emissions. Here we propose and analyze the long-term potential of alternative animal feed supply routes based on industrial production of microbial proteins (MP). Our analysis reveals that by 2050, MP can replace, depending on socio-economic development and MP production pathways, between 10-19% of conventional crop-based animal feed protein demand. As a result, global cropland area, global nitrogen losses from croplands and agricultural greenhouse gas emissions can be decreased by 6% (0-13%), 8% (-3-8%), and 7% (-6-9%), respectively. Interestingly, the technology to industrially produce MP at competitive costs is directly accessible for implementation and has the potential to cause a major structural change in the agro-food system.
Subject(s)
Greenhouse Gases , Livestock , Agriculture , Animal Feed , Animals , IndustryABSTRACT
We explore the feasibility of limiting global warming to 1.5°C without overshoot and without the deployment of carbon dioxide removal (CDR) technologies. For this purpose, we perform a sensitivity analysis of four generic emissions reduction measures to identify a lower bound on future CO2 emissions from fossil fuel combustion and industrial processes. Final energy demand reductions and electrification of energy end uses as well as decarbonization of electricity and non-electric energy supply are all considered. We find the lower bound of cumulative fossil fuel and industry CO2 emissions to be 570 GtCO2 for the period 2016-2100, around 250 GtCO2 lower than the lower end of available 1.5°C mitigation pathways generated with integrated assessment models. Estimates of 1.5°C-consistent CO2 budgets are highly uncertain and range between 100 and 900 GtCO2 from 2016 onwards. Based on our sensitivity analysis, limiting warming to 1.5°C will require CDR or terrestrial net carbon uptake if 1.5°C-consistent budgets are smaller than 650 GtCO2 The earlier CDR is deployed, the more it neutralizes post-2020 emissions rather than producing net negative emissions. Nevertheless, if the 1.5°C budget is smaller than 550 GtCO2, temporary overshoot of the 1.5°C limit becomes unavoidable if CDR cannot be ramped up faster than to 4 GtCO2 in 2040 and 10 GtCO2 in 2050.This article is part of the theme issue 'The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels'.
ABSTRACT
This article investigates projected changes in temperature and water cycle extremes at 1.5°C of global warming, and highlights the role of land processes and land-use changes (LUCs) for these projections. We provide new comparisons of changes in climate at 1.5°C versus 2°C based on empirical sampling analyses of transient simulations versus simulations from the 'Half a degree Additional warming, Prognosis and Projected Impacts' (HAPPI) multi-model experiment. The two approaches yield similar overall results regarding changes in climate extremes on land, and reveal a substantial difference in the occurrence of regional extremes at 1.5°C versus 2°C. Land processes mediated through soil moisture feedbacks and land-use forcing play a major role for projected changes in extremes at 1.5°C in most mid-latitude regions, including densely populated areas in North America, Europe and Asia. This has important implications for low-emissions scenarios derived from integrated assessment models (IAMs), which include major LUCs in ambitious mitigation pathways (e.g. associated with increased bioenergy use), but are also shown to differ in the simulated LUC patterns. Biogeophysical effects from LUCs are not considered in the development of IAM scenarios, but play an important role for projected regional changes in climate extremes, and are thus of high relevance for sustainable development pathways.This article is part of the theme issue 'The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels'.
ABSTRACT
Understanding uncertainties in land cover projections is critical to investigating land-based climate mitigation policies, assessing the potential of climate adaptation strategies and quantifying the impacts of land cover change on the climate system. Here, we identify and quantify uncertainties in global and European land cover projections over a diverse range of model types and scenarios, extending the analysis beyond the agro-economic models included in previous comparisons. The results from 75 simulations over 18 models are analysed and show a large range in land cover area projections, with the highest variability occurring in future cropland areas. We demonstrate systematic differences in land cover areas associated with the characteristics of the modelling approach, which is at least as great as the differences attributed to the scenario variations. The results lead us to conclude that a higher degree of uncertainty exists in land use projections than currently included in climate or earth system projections. To account for land use uncertainty, it is recommended to use a diverse set of models and approaches when assessing the potential impacts of land cover change on future climate. Additionally, further work is needed to better understand the assumptions driving land use model results and reveal the causes of uncertainty in more depth, to help reduce model uncertainty and improve the projections of land cover.
Subject(s)
Climate Change , Uncertainty , Climate , Earth, Planet , Forecasting , PlantsABSTRACT
The Haber Bosch process is among the greatest inventions of the 20th century. It provided agriculture with reactive nitrogen and ultimately mankind with nourishment for a population of 7 billion people. However, the present agricultural practice of growing crops for animal production and human food constitutes a major threat to the sustainability of the planet in terms of reactive nitrogen pollution. In view of the shortage of directly feasible and cost-effective measures to avoid these planetary nitrogen burdens and the necessity to remediate this problem, we foresee the absolute need for and expect a revolution in the use of microbes as a source of protein. Bypassing land-based agriculture through direct use of Haber Bosch produced nitrogen for reactor-based production of microbial protein can be an inspiring concept for the production of high quality animal feed and even straightforward supply of proteinaceous products for human food, without significant nitrogen losses to the environment and without the need for genetic engineering to safeguard feed and food supply for the generations to come.
Subject(s)
Agriculture , Bacteria , Bioreactors , Food Supply , Nitrogen , Animal Feed , Animals , Crops, Agricultural , Environmental Pollution , HumansABSTRACT
The land use sector of agriculture, forestry, and other land use (AFOLU) plays a central role in ambitious climate change mitigation efforts. Yet, mitigation policies in agriculture may be in conflict with food security related targets. Using a global agro-economic model, we analyze the impacts on food prices under mitigation policies targeting either incentives for producers (e.g., through taxes) or consumer preferences (e.g., through education programs). Despite having a similar reduction potential of 43-44% in 2100, the two types of policy instruments result in opposite outcomes for food prices. Incentive-based mitigation, such as protecting carbon-rich forests or adopting low-emission production techniques, increase land scarcity and production costs and thereby food prices. Preference-based mitigation, such as reduced household waste or lower consumption of animal-based products, decreases land scarcity, prevents emissions leakage, and concentrates production on the most productive sites and consequently lowers food prices. Whereas agricultural emissions are further abated in the combination of these mitigation measures, the synergy of strategies fails to substantially lower food prices. Additionally, we demonstrate that the efficiency of agricultural emission abatement is stable across a range of greenhouse-gas (GHG) tax levels, while resulting food prices exhibit a disproportionally larger spread.
Subject(s)
Climate Change , Conservation of Natural Resources , Agriculture , Animals , Food Supply , Forestry , Greenhouse EffectABSTRACT
Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change's representative concentration pathway with end-of-century radiative forcing of 8.5 W/m(2). The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change.
Subject(s)
Agriculture/economics , Climate Change , Crops, Agricultural/growth & development , Models, Economic , Carbon Dioxide/analysis , Commerce/statistics & numerical data , Computer Simulation , Forecasting , HumansABSTRACT
Model-based global projections of future land-use and land-cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms of quantity and allocation of projected changes, which can severely impact the results of environmental assessments. In this study, we identify hotspots of uncertainty, based on 43 simulations from 11 global-scale LULC change models representing a wide range of assumptions of future biophysical and socioeconomic conditions. We attribute components of uncertainty to input data, model structure, scenario storyline and a residual term, based on a regression analysis and analysis of variance. From this diverse set of models and scenarios, we find that the uncertainty varies, depending on the region and the LULC type under consideration. Hotspots of uncertainty appear mainly at the edges of globally important biomes (e.g., boreal and tropical forests). Our results indicate that an important source of uncertainty in forest and pasture areas originates from different input data applied in the models. Cropland, in contrast, is more consistent among the starting conditions, while variation in the projections gradually increases over time due to diverse scenario assumptions and different modeling approaches. Comparisons at the grid cell level indicate that disagreement is mainly related to LULC type definitions and the individual model allocation schemes. We conclude that improving the quality and consistency of observational data utilized in the modeling process and improving the allocation mechanisms of LULC change models remain important challenges. Current LULC representation in environmental assessments might miss the uncertainty arising from the diversity of LULC change modeling approaches, and many studies ignore the uncertainty in LULC projections in assessments of LULC change impacts on climate, water resources or biodiversity.
Subject(s)
Conservation of Natural Resources , Ecosystem , Models, Theoretical , Biodiversity , UncertaintyABSTRACT
Turn residues and side-chain interactions play an important role for the folding of ß-sheets. We investigated the conformational dynamics of a three-stranded ß-sheet peptide ((D) P(D) P) and a two-stranded ß-hairpin (WVYY-(D) P) by time-resolved temperature-jump (T-jump) infrared spectroscopy. Both peptide sequences contain (D) Pro-Gly residues that favor a tight ß-turn. The three-stranded ß-sheet (Ac-VFITS(D) PGKTYTEV(D) PGOKILQ-NH2 ) is stabilized by the turn sequences, whereas the ß-hairpin (SWTVE(D) PGKYTYK-NH2 ) folding is assisted by both the turn sequence and hydrophobic cross-strand interactions. Relaxation times after the T-jump were monitored as a function of temperature and occur on a sub-microsecond time scale, (D) P(D) P being faster than WVYY-(D) P. The Xxx-(D) Pro tertiary amide provides a detectable IR band, allowing us to probe the dynamics site-specifically. The relative importance of the turn versus the intrastrand stability in ß-sheet formation is discussed.
Subject(s)
Glycine/chemistry , Lasers , Peptides/chemistry , Proline/chemistry , Spectrophotometry, Infrared/methods , Hydrophobic and Hydrophilic Interactions , TemperatureABSTRACT
Climate change has impacts on agricultural yields, which could alter cropland requirements and hence deforestation rates. Thus, land-use responses to climate change might influence terrestrial carbon stocks. Moreover, climate change could alter the carbon storage capacity of the terrestrial biosphere and hence the land-based mitigation potential. We use a global spatially explicit economic land-use optimization model to (a) estimate the mitigation potential of a climate policy that provides economic incentives for carbon stock conservation and enhancement, (b) simulate land-use and carbon cycle responses to moderate climate change (RCP2.6), and (c) investigate the combined effects throughout the 21st century. The climate policy immediately stops deforestation and strongly increases afforestation, resulting in a global mitigation potential of 191 GtC in 2100. Climate change increases terrestrial carbon stocks not only directly through enhanced carbon sequestration (62 GtC by 2100) but also indirectly through less deforestation due to higher crop yields (16 GtC by 2100). However, such beneficial climate impacts increase the potential of the climate policy only marginally, as the potential is already large under static climatic conditions. In the broader picture, this study highlights the importance of land-use dynamics for modeling carbon cycle responses to climate change in integrated assessment modeling.