Effects of climate-induced changes in isoprene emissions after the eruption of Mount Pinatubo

In the 1990s the rates of increase of greenhouse gas concentrations, most notably of methane, were observed to change, for reasons that have yet to be fully determined. This period included the eruption of Mt. Pinatubo and an El Nino warm event, both of which affect biogeochemical processes, by changes in temperature, precipitation and radiation. We examine the impact of these changes in climate on global isoprene emissions and the effect these climate dependent emissions have on the hydroxy radical, OH, the dominant sink for methane. We model a reduction of isoprene emissions in the early 1990s, with a maximum decrease of 40 Tg(C)/yr in late 1992 and early 1993, a change of 9%. This reduction is caused by the cooler, drier conditions following the eruption of Mt. Pinatubo. Isoprene emissions are reduced both directly, by changes in temperature and a soil moisture dependent suppression factor, and indirectly, through reductions in the total biomass. The reduction in isoprene emissions causes increases of tropospheric OH which lead to an increased sink for methane of up to 5 Tg(CH4)/year, comparable to estimated source changes over the time period studied. There remain many uncertainties in the emission and oxidation of isoprene which may affect the exact size of this effect, but its magnitude is large enough that it should remain important

Evaluating the spatial uncertainty of future land abandonment in a mountain valley (Vicdessos, Pyrenees-France) : insights form model parameterization and experiments

International audienceEuropean mountains are particularly sensitive to climatic disruptions and land use changes. The latter leads to high rates of natural reforestation over the last 50 years. Faced with the challenge of predicting possible impacts on ecosystem services, LUCC models offer new opportunities for land managers to adapt or mitigate their strategies. Assessing the spatial uncertainty of future LUCC is crucial for the defintion of sustainable land use strategies. However, the sources of uncertainty may differ, including the input parameters, the model itself, and the wide range of possible futures. The aim of this paper is to propose a method to assess the probability of occurrence of future LUCC that combines the inherent uncertainty of model parameterization and the ensemble uncertainty of the future based scenarios. For this purpose, we used the Land Change Modeler tool to simulate future LUCC on a study site located in the Pyrenees Mountains (France) and 2 scenarios illustratins 2 land use strategies. The model was parameterized with the same driving factors used for its calibration. The defintion of static vs. dynamic and quantitative vs. qualitative (discretized) driving factors, and their combination resulted in 4 parameterizations. The combination of model outcomes produced maps of spatial uncertainty of future LUCC. This work involves literature to future-based LUCC studies. It goes beyond the uncertainty of simulation models by integrating the unceertainty of the future to provide maps to help decision makers and land managers

Drivers of plant diversity in Bulgarian dry grasslands vary across spatial scales and functional-taxonomic groups

Questions: Studying dry grasslands in a previously unexplored region, we asked: (a) which environmental factors drive the diversity patterns in vegetation; (b) are taxonomic groups (vascular plants, bryophytes, lichens) and functional vascular plant groups differently affected; and (c) how is fine-grain beta diversity affected by environmental drivers? Location: Northwestern and Central Bulgaria. Methods: We sampled environmental data and vascular plant, terricolous bryophyte and lichen species in 97 10-m2 plots and 15 nested-plot series with seven grain sizes (0.0001–100 m2) of ten grassland sites within the two regions. We used species richness as measure of alpha-diversity and the z-value of the power-law species–area relationship as measure of beta-diversity. We analysed effects of landscape, topographic, soil and land-use variables on the species richness of the different taxonomic and functional groups. We applied generalised linear models (GLMs) or, in the presence of spatial autocorrelation, generalised linear mixed-effect models (GLMMs) in a multi-model inference framework. Results: The main factors affecting total and vascular plant species richness in 10-m2 plots were soil pH (unimodal) and inclination (negative). Species richness of bryophytes was positively affected by rock cover, sand proportion and negatively by inclination. Inclination and litter cover were also negative predictors of lichen species richness. Elevation negatively affected phanerophyte and therophyte richness, but positively that of cryptophytes. A major part of unexplained variance in species richness was associated with the grassland site. The z-values for total richness showed a positive relationship with elevation and inclination. Conclusions: Environmental factors shaping richness patterns strongly differed among taxonomic groups, functional vascular plant groups and spatial scales. The disparities between our and previous findings suggest that many drivers of biodiversity cannot be generalised but rather depend on the regional context. The large unexplained variance at the site level calls for considering more site-related factors such as land-use history

Combining qualitative and quantitative understanding for exploring cross-sectoral climate change impacts, adaptation and vulnerability in Europe

Climate change will affect all sectors of society and the environment at all scales, ranging from the continental to the national and local. Decision-makers and other interested citizens need to be able to access reliable science-based information to help them respond to the risks of climate change impacts and assess opportunities for adaptation. Participatory integrated assessment (IA) tools combine knowledge from diverse scientific disciplines, take account of the value and importance of stakeholder ‘lay insight’ and facilitate a two-way iterative process of exploration of ‘what if’s’ to enable decision-makers to test ideas and improve their understanding of the complex issues surrounding adaptation to climate change. This paper describes the conceptual design of a participatory IA tool, the CLIMSAVE IA Platform, based on a professionally facilitated stakeholder engagement process. The CLIMSAVE (climate change integrated methodology for cross-sectoral adaptation and vulnerability in Europe) Platform is a user-friendly, interactive web-based tool that allows stakeholders to assess climate change impacts and vulnerabilities for a range of sectors, including agriculture, forests, biodiversity, coasts, water resources and urban development. The linking of models for the different sectors enables stakeholders to see how their interactions could affect European landscape change. The relationship between choice, uncertainty and constraints is a key cross-cutting theme in the conduct of past participatory IA. Integrating scenario development processes with an interactive modelling platform is shown to allow the exploration of future uncertainty as a structural feature of such complex problems, encouraging stakeholders to explore adaptation choices within real-world constraints of future resource availability and environmental and institutional capacities, rather than seeking the ‘right’ answers

Enhancing the relevance of Shared Socioeconomic Pathways for climate change impacts, adaptation and vulnerability research

This paper discusses the role and relevance of the shared socioeconomic pathways (SSPs) and the new scenarios that combine SSPs with representative concentration pathways (RCPs) for climate change impacts, adaptation, and vulnerability (IAV) research. It first provides an overview of uses of social–environmental scenarios in IAV studies and identifies the main shortcomings of earlier such scenarios. Second, the paper elaborates on two aspects of the SSPs and new scenarios that would improve their usefulness for IAV studies compared to earlier scenario sets: (i) enhancing their applicability while retaining coherence across spatial scales, and (ii) adding indicators of importance for projecting vulnerability. The paper therefore presents an agenda for future research, recommending that SSPs incorporate not only the standard variables of population and gross domestic product, but also indicators such as income distribution, spatial population, human health and governance

Experiments in Globalisation, Food Security and Land Use Decision Making

The globalisation of trade affects land use, food production and environmentsaround the world. In principle, globalisation can maximise productivity andefficiency if competition prompts specialisation on the basis of productive capacity.In reality, however, such specialisation is often constrained by practical or politicalbarriers, including those intended to ensure national or regional food security.These are likely to produce globally sub-optimal distributions of land uses. Bothoutcomes are subject to the responses of individual land managers to economicand environmental stimuli, and these responses are known to be variable and often(economically) irrational. We investigate the consequences of stylised food securitypolicies and globalisation of agricultural markets on land use patterns under avariety of modelled forms of land manager behaviour, including variation inproduction levels, tenacity, land use intensity and multi-functionality. We find that asystem entirely dedicated to regional food security is inferior to an entirelyglobalised system in terms of overall production levels, but that several forms ofbehaviour limit the difference between the two, and that variations in land useintensity and functionality can substantially increase the provision of food and otherecosystem services in both cases. We also find emergent behaviour that results inthe abandonment of productive land, the slowing of rates of land use change andthe fragmentation or, conversely, concentration of land uses following changes indemand levels