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Protection of natural or semi-natural ecosystems is an important part of societal strategies for maintaining biodiversity, ecosystem services, and achieving overall sustainable development. The assessment of multiple emerging land use trade-offs is complicated by the fact that land use changes occur and have consequences at local, regional, and even global scale. Outcomes also depend on the underlying socio-economic trends. We apply a coupled, multi-scale modelling system to assess an increase in nature protection areas as a key policy option in the European Union (EU). The main goal of the analysis is to understand the interactions between policy-induced land use changes across different scales and sectors under two contrasting future socio-economic pathways. We demonstrate how complementary insights into land system change can be gained by coupling land use models for agriculture, forestry, and urban areas for Europe, in connection with other world regions. The simulated policy case of nature protection shows how the allocation of a certain share of total available land to newly protected areas, with specific management restrictions imposed, may have a range of impacts on different land-based sectors until the year 2040. Agricultural land in Europe is slightly reduced, which is partly compensated for by higher management intensity. As a consequence of higher costs, total calorie supply per capita is reduced within the EU. While wood harvest is projected to decrease, carbon sequestration rates increase in European forests. At the same time, imports of industrial roundwood from other world regions are expected to increase. Some of the aggregate effects of nature protection have very different implications at the local to regional scale in different parts of Europe. Due to nature protection measures, agricultural production is shifted from more productive land in Europe to on average less productive land in other parts of the world. This increases, at the global level, the allocation of land resources for agriculture, leading to a decrease in tropical forest areas, reduced carbon stocks, and higher greenhouse gas emissions outside of Europe. The integrated modelling framework provides a method to assess the land use effects of a single policy option while accounting for the trade-offs between locations, and between regional, European, and global scales.
Several thousands of moraine-dammed and supraglacial lakes spread over the Hindu Kush Himalayan (HKH) region, and some have grown rapidly in past decades due to glacier retreat. The sudden emptying of these lakes releases large volumes of water and sediment in destructive glacial lake outburst floods (GLOFs), one of the most publicised natural hazards to the rapidly growing Himalayan population. Despite the growing number and size of glacial lakes, the frequency of documented GLOFs is remarkably constant. We explore this possible reporting bias and offer a new processing chain for establishing a more complete Himalayan GLOF inventory. We make use of the full seasonal archive of Landsat images between 1988 and 2016, and track automatically where GLOFs left shrinking water bodies, and tails of sediment at high elevations. We trained a Random Forest classifier to generate fuzzy land cover maps for 2491 images, achieving overall accuracies of 91%. We developed a likelihood-based change point technique to estimate the timing of GLOFs at the pixel scale. Our method objectively detected ten out of eleven documented GLOFs, and another ten lakes that gave rise to previously unreported GLOFs. We thus nearly doubled the existing GLOF record for a study area covering similar to 10% of the HKH region. Remaining challenges for automatically detecting GLOFs include image insufficiently accurate co-registration, misclassifications in the land cover maps and image noise from clouds, shadows or ice. Yet our processing chain is robust and has the potential for being applied on the greater HKH and mountain ranges elsewhere, opening the door for objectively expanding the knowledge base on GLOF activity over the past three decades.
Glacial lakes in the Hindu Kush–Karakoram–Himalayas–Nyainqentanglha (HKKHN) region have grown rapidly in number and area in past decades, and some dozens have drained in catastrophic glacial lake outburst floods (GLOFs). Estimating regional susceptibility of glacial lakes has largely relied on qualitative assessments by experts, thus motivating a more systematic and quantitative appraisal. Before the backdrop of current climate-change projections and the potential of elevation-dependent warming, an objective and regionally consistent assessment is urgently needed. We use an inventory of 3390 moraine-dammed lakes and their documented outburst history in the past four decades to test whether elevation, lake area and its rate of change, glacier-mass balance, and monsoonality are useful inputs to a probabilistic classification model. We implement these candidate predictors in four Bayesian multi-level logistic regression models to estimate the posterior susceptibility to GLOFs. We find that mostly larger lakes have been more prone to GLOFs in the past four decades regardless of the elevation band in which they occurred. We also find that including the regional average glacier-mass balance improves the model classification. In contrast, changes in lake area and monsoonality play ambiguous roles. Our study provides first quantitative evidence that GLOF susceptibility in the HKKHN scales with lake area, though less so with its dynamics. Our probabilistic prognoses offer improvement compared to a random classification based on average GLOF frequency. Yet they also reveal some major uncertainties that have remained largely unquantified previously and that challenge the applicability of single models. Ensembles of multiple models could be a viable alternative for more accurately classifying the susceptibility of moraine-dammed lakes to GLOFs.
Shrinking glaciers in the Hindu Kush-Karakoram-Himalaya-Nyainqentanglha (HKKHN) region have formed several thousand moraine-dammed glacial lakes(1-3), some of these having grown rapidly in past decades(3,4). This growth may promote more frequent and potentially destructive glacial lake outburst floods (GLOFs)(5-7). Testing this hypothesis, however, is confounded by incomplete databases of the few reliable, though selective, case studies. Here we present a consistent Himalayan GLOF inventory derived automatically from all available Landsat imagery since the late 1980s. We more than double the known GLOF count and identify the southern Himalayas as a hotspot region, compared to the more rarely affected Hindu Kush-Karakoram ranges. Nevertheless, the average annual frequency of 1.3 GLOFs has no credible posterior trend despite reported increases in glacial lake areas in most of the HKKHN3,8, so that GLOF activity per unit lake area has decreased since the late 1980s. We conclude that learning more about the frequency and magnitude of outburst triggers, rather than focusing solely on rapidly growing glacial lakes, might improve the appraisal of GLOF hazards.
Niche-based species distribution models (SDMs) have become an essential tool in conservation and restoration planning. Given the current threats to freshwater biodiversity, it is of fundamental importance to address scale effects on the performance of niche-based SDMs of freshwater species’ distributions. The scale effects are addressed here in the context of hierarchical catchment ordering, considered as counterpart to coarsening grain-size by increasing grid-cell size. We combine fish occurrence data from the Danube River Basin, the hierarchical catchment ordering and multiple environmental factors representing topographic, climatic and anthropogenic effects to model fish occurrence probability across multiple scales. We focus on 1st to 5th order catchments. The spatial scale (hierarchical catchment order) only marginally influences the mean performance of SDMs, however the uncertainty of the estimates increases with scale. Key predictors and their relative importance are scale and species dependent. Our findings have useful implications for choosing proper species dependent spatial scales for river rehabilitation measures, and for conservation planning in areas where fine grain species data are unavailable.
Sociocultural valuation (SCV) of ecosystem services (ES) discloses the principles, importance or preferences expressed by people towards nature. Although ES research has increasingly addressed sociocultural values in past years, little effort has been made to systematically review the components of sociocultural valuation applications for different decision contexts (i.e. awareness raising, accounting, priority setting, litigation and instrument design). In this analysis, we investigate the characteristics of 48 different sociocultural valuation applications—characterised by unique combinations of decision context, methods, data collection formats and participants—across ten European case studies. Our findings show that raising awareness for the sociocultural value of ES by capturing people’s perspective and establishing the status quo, was found the most frequent decision context in case studies, followed by priority setting and instrument development. Accounting and litigation issues were not addressed in any of the applications. We reveal that applications for particular decision contexts are methodologically similar, and that decision contexts determine the choice of methods, data collection formats and participants involved. Therefore, we conclude that understanding the decision context is a critical first step to designing and carrying out fit-for-purpose sociocultural valuation of ES in operational ecosystem management.
Testing socio-cultural valuation methods of ecosystem services to explain land use preferences
(2017)
Socio-cultural valuation still emerges as a methodological field in ecosystem service (ES) research and until now lacks consistent formalisation and balanced application in ES assessments. In this study, we examine the explanatory value of ES values for land use preferences. We use 563 responses to a survey about the Pentland Hills regional park in Scotland. Specifically, we aim to (1) identify clusters of land use preferences by using a novel visualisation tool, (2) test if socio-cultural values of ESs or (3) user characteristics are linked with land use preferences, and (4) determine whether both socio-cultural values of ESs and user characteristics can predict land use preferences. Our results suggest that there are five groups of people with different land use preferences, ranging from forest and nature enthusiasts to traditionalists, multi-functionalists and recreation seekers. Rating and weighting of ESs and user characteristics were associated with different clusters. Neither socio-cultural values nor user characteristics were suitable predictors for land use preferences. While several studies have explored land use preferences by identifying socio-cultural values in the past, our findings imply that in this case study ES values inform about general perceptions but do not replace the assessment of land use preferences. (C) 2017 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license.
Climate change is expected to exacerbate the current threats to freshwater ecosystems, yet multifaceted studies on the potential impacts of climate change on freshwater biodiversity at scales that inform management planning are lacking. The aim of this study was to fill this void through the development of a novel framework for assessing climate change vulnerability tailored to freshwater ecosystems. The three dimensions of climate change vulnerability are as follows: (i) exposure to climate change, (ii) sensitivity to altered environmental conditions and (iii) resilience potential. Our vulnerability framework includes 1685 freshwater species of plants, fishes, molluscs, odonates, amphibians, crayfish and turtles alongside key features within and between catchments, such as topography and connectivity. Several methodologies were used to combine these dimensions across a variety of future climate change models and scenarios. The resulting indices were overlaid to assess the vulnerability of European freshwater ecosystems at the catchment scale (18 783 catchments). The Balkan Lakes Ohrid and Prespa and Mediterranean islands emerge as most vulnerable to climate change. For the 2030s, we showed a consensus among the applied methods whereby up to 573 lake and river catchments are highly vulnerable to climate change. The anthropogenic disruption of hydrological habitat connectivity by dams is the major factor reducing climate change resilience. A gap analysis demonstrated that the current European protected area network covers <25% of the most vulnerable catchments. Practical steps need to be taken to ensure the persistence of freshwater biodiversity under climate change. Priority should be placed on enhancing stakeholder cooperation at the major basin scale towards preventing further degradation of freshwater ecosystems and maintaining connectivity among catchments. The catchments identified as most vulnerable to climate change provide preliminary targets for development of climate change conservation management and mitigation strategies.
Climate change increases riverine carbon outgassing, while export to the ocean remains uncertain
(2016)
Any regular interaction of land and river during flooding affects carbon pools within the terrestrial system, riverine carbon and carbon exported from the system. In the Amazon basin carbon fluxes are considerably influenced by annual flooding, during which terrigenous organic material is imported to the river. The Amazon basin therefore represents an excellent example of a tightly coupled terrestrial-riverine system. The processes of generation, conversion and transport of organic carbon in such a coupled terrigenous-riverine system strongly interact and are climate-sensitive, yet their functioning is rarely considered in Earth system models and their response to climate change is still largely unknown. To quantify regional and global carbon budgets and climate change effects on carbon pools and carbon fluxes, it is important to account for the coupling between the land, the river, the ocean and the atmosphere. We developed the RIVerine Carbon Model (RivCM), which is directly coupled to the well-established dynamic vegetation and hydrology model LPJmL, in order to account for this large-scale coupling. We evaluate RivCM with observational data and show that some of the values are reproduced quite well by the model, while we see large deviations for other variables. This is mainly caused by some simplifications we assumed. Our evaluation shows that it is possible to reproduce large-scale carbon transport across a river system but that this involves large uncertainties. Acknowledging these uncertainties, we estimate the potential changes in riverine carbon by applying RivCM for climate forcing from five climate models and three CO2 emission scenarios (Special Report on Emissions Scenarios, SRES). We find that climate change causes a doubling of riverine organic carbon in the southern and western basin while reducing it by 20% in the eastern and northern parts. In contrast, the amount of riverine inorganic carbon shows a 2- to 3-fold increase in the entire basin, independent of the SRES scenario. The export of carbon to the atmosphere increases as well, with an average of about 30 %. In contrast, changes in future export of organic carbon to the Atlantic Ocean depend on the SRES scenario and are projected to either decrease by about 8.9% (SRES A1B) or increase by about 9.1% (SRES A2). Such changes in the terrigenous-riverine system could have local and regional impacts on the carbon budget of the whole Amazon basin and parts of the Atlantic Ocean. Changes in riverine carbon could lead to a shift in the riverine nutrient supply and pH, while changes in the exported carbon to the ocean lead to changes in the supply of organic material that acts as a food source in the Atlantic. On larger scales the increased outgassing of CO2 could turn the Amazon basin from a sink of carbon to a considerable source. Therefore, we propose that the coupling of terrestrial and riverine carbon budgets should be included in subsequent analysis of the future regional carbon budget.
Grazing by domestic ungulates can have substantial impacts on forests in arid and semi-arid regions, possibly including severe loss of carbon from the soil. Predicting net livestock impacts on soil organic carbon stocks remains challenging, however, due to the dependence on animal loads and on soil and environmental parameters. The objective of this study was to better understand grazing effects on soil organic carbon in seasonal tropical dry forests of north-eastern Brazil (Caatinga) by quantifying carbon stocks of the upper soil profile (0–5 cm depth) and greater soil depths (>5 cm depth down to bedrock) along a gradient of grazing intensity while accounting for other influencing factors such as soil texture, vegetation, landscape topography, and water availability. We analysed soil organic carbon, soil clay content, altitude above sea level, soil depth to bedrock, distance to the nearest permanent water body, species diversity of perennial plants and aboveground biomass on 45 study plots located in the vicinity of the Itaparica Reservoir, Pernambuco, Brazil. Livestock (mainly goats and cattle) are unevenly distributed in the studied ecosystem, thus grazing intensity was accounted for based on the weight of livestock droppings per square metre and classified as no or light, intermediate, or heavy grazing. The mean soil organic carbon in the area was 16.86 ± 1.28 Mg ha−1 C with approximately one-quarter found in the upper 5 cm of the soil profile (4.14 ± 0.43 Mg ha−1 C) and the remainder (12.57 ± 0.97 Mg ha−1 C) in greater soil depths (>5 cm). Heavy grazing led to significantly lower soil organic carbon stocks in the upper 5 cm, whereas no effect on soil organic carbon of the soil overall or in greater soil depths was detectable. The soil’s clay content and the altitude proved to be the most relevant factors influencing overall soil organic carbon stocks and those in greater soil depths (>5 cm). Our findings suggest that grazing causes substantial release of carbon from Brazilian dry forest soils, which should be addressed through improved grazing management via a legally compulsory rotation system. This would ultimately contribute to the conservation of a unique forest system and associated ecosystem services.
Ecosystem services have a significant impact on human wellbeing. While ecosystem services are frequently represented by monetary values, social values and underlying social benefits remain underexplored. The purpose of this study is to assess whether and how social benefits have been explicitly addressed within socio-economic and socio-cultural ecosystem services research, ultimately allowing a better understanding between ecosystem services and human well-being. In this paper, we reviewed 115 international primary valuation studies and tested four hypotheses associated to the identification of social benefits of ecosystem services using logistic regressions. Tested hypotheses were that (1) social benefits are mostly derived in studies that assess cultural ecosystem services as opposed to other ecosystem service types, (2) there is a pattern of social benefits and certain cultural ecosystem services assessed simultaneously, (3) monetary valuation techniques go beyond expressing monetary values and convey social benefits, and (4) directly addressing stakeholdeŕs views the consideration of social benefits in ecosystem service assessments. Our analysis revealed that (1) a variety of social benefits are valued in studies that assess either of the four ecosystem service types, (2) certain social benefits are likely to co-occur in combination with certain cultural ecosystem services, (3) of the studies that employed monetary valuation techniques, simulated market approaches overlapped most frequently with the assessment of social benefits and (4) studies that directly incorporate stakeholder's views were more likely to also assess social benefits.
Volunteered geographical information (VGI) and citizen science have become important sources data for much scientific research. In the domain of land cover, crowdsourcing can provide a high temporal resolution data to support different analyses of landscape processes. However, the scientists may have little control over what gets recorded by the crowd, providing a potential source of error and uncertainty. This study compared analyses of crowdsourced land cover data that were contributed by different groups, based on nationality (labelled Gondor and Non-Gondor) and on domain experience (labelled Expert and Non-Expert). The analyses used a geographically weighted model to generate maps of land cover and compared the maps generated by the different groups. The results highlight the differences between the maps how specific land cover classes were under-and over-estimated. As crowdsourced data and citizen science are increasingly used to replace data collected under the designed experiment, this paper highlights the importance of considering between group variations and their impacts on the results of analyses. Critically, differences in the way that landscape features are conceptualised by different groups of contributors need to be considered when using crowdsourced data in formal scientific analyses. The discussion considers the potential for variation in crowdsourced data, the relativist nature of land cover and suggests a number of areas for future research. The key finding is that the veracity of citizen science data is not the critical issue per se. Rather, it is important to consider the impacts of differences in the semantics, affordances and functions associated with landscape features held by different groups of crowdsourced data contributors.
Extreme weather events are likely to occur more often under climate change and the resulting effects on ecosystems could lead to a further acceleration of climate change. But not all extreme weather events lead to extreme ecosystem response. Here, we focus on hazardous ecosystem behaviour and identify coinciding weather conditions. We use a simple probabilistic risk assessment based on time series of ecosystem behaviour and climate conditions. Given the risk assessment terminology, vulnerability and risk for the previously defined hazard are estimated on the basis of observed hazardous ecosystem behaviour.
We apply this approach to extreme responses of terrestrial ecosystems to drought, defining the hazard as a negative net biome productivity over a 12-month period. We show an application for two selected sites using data for 1981-2010 and then apply the method to the pan-European scale for the same period, based on numerical modelling results (LPJmL for ecosystem behaviour; ERA-Interim data for climate).
Our site-specific results demonstrate the applicability of the proposed method, using the SPEI to describe the climate condition. The site in Spain provides an example of vulnerability to drought because the expected value of the SPEI is 0.4 lower for hazardous than for non-hazardous ecosystem behaviour. In northern Germany, on the contrary, the site is not vulnerable to drought because the SPEI expectation values imply wetter conditions in the hazard case than in the non-hazard case.
At the pan-European scale, ecosystem vulnerability to drought is calculated in the Mediterranean and temperate region, whereas Scandinavian ecosystems are vulnerable under conditions without water shortages. These first model- based applications indicate the conceptual advantages of the proposed method by focusing on the identification of critical weather conditions for which we observe hazardous ecosystem behaviour in the analysed data set. Application of the method to empirical time series and to future climate would be important next steps to test the approach.
Weltweit verursachen Städte etwa 70 % der Treibhausgasemissionen und sind daher wichtige Akteure im Klimaschutz bzw. eine wichtige Zielgruppe von Klimapolitiken. Gleichzeitig sind Städte besonders stark von möglichen Auswirkungen des Klimawandels betroffen: Insbesondere extreme Wetterereignisse wie Hitzewellen oder Starkregenereignisse mit Überflutungen verursachen in Städten hohe Sachschäden und wirken sich negativ auf die Gesundheit der städtischen Bevölkerung aus. Daher verfolgt das Projekt ExTrass das Ziel, die städtische Resilienz gegenüber extremen Wetterereignissen in enger Zusammenarbeit mit Stadtverwaltungen, Strukturen des Bevölkerungsschutzes und der Zivilgesellschaft zu stärken. Im Fokus stehen dabei (kreisfreie) Groß- und Mittelstädte mit 50.000 bis 500.000 Einwohnern, insbesondere die Fallstudienstädte Potsdam, Remscheid und Würzburg.
Der vorliegende Bericht beinhaltet die Ergebnisse der 14-monatigen Definitionsphase von ExTrass, in der vor allem die Abstimmung eines Arbeitsprogramms im Mittelpunkt stand, das in einem nachfolgenden dreijährigen Forschungsprojekt (F+E-Phase) gemeinsam von Wissenschaft und Praxispartnern umgesetzt werden soll. Begleitend wurde eine Bestandsaufnahme von Klimaanpassungs- und Klimaschutzstrategien/-plänen in 99 deutschen Groß- und Mittelstädten vorgenommen. Zudem wurden für Potsdam und Würzburg Pfadanalysen für die Klimapolitik durchgeführt. Darin wird insbesondere die Bedeutung von Schlüsselakteuren deutlich. Weiterhin wurden im Rahmen von Stakeholder-Workshops Anpassungsherausforderungen und aktuelle Handlungsbedarfe in den Fallstudienstädten identifiziert und Lösungsansätze erarbeitet, die in der F+E-Phase entwickelt und getestet werden sollen. Neben Maßnahmen auf gesamtstädtischer Ebene und auf Stadtteilebene wurden Maßnahmen angestrebt, die die Risikowahrnehmung, Vorsorge und Selbsthilfefähigkeit von Unternehmen und Bevölkerung stärken können. Daher wurde der Stand der Risikokommunikation in Deutschland für das Projekt aufgearbeitet und eine erste Evaluation von Risikokommunikationswerkzeugen durchgeführt. Der Bericht endet mit einer Kurzfassung des Arbeitsprogramms 2018-2021.
Extreme weather events are likely to occur more often under climate change and the resulting effects on ecosystems could lead to a further acceleration of climate change. But not all extreme weather events lead to extreme ecosystem response. Here, we focus on hazardous ecosystem behaviour and identify coinciding weather conditions. We use a simple probabilistic risk assessment based on time series of ecosystem behaviour and climate conditions. Given the risk assessment terminology, vulnerability and risk for the previously defined hazard are estimated on the basis of observed hazardous ecosystem behaviour.
We apply this approach to extreme responses of terrestrial ecosystems to drought, defining the hazard as a negative net biome productivity over a 12-month period. We show an application for two selected sites using data for 1981-2010 and then apply the method to the pan-European scale for the same period, based on numerical modelling results (LPJmL for ecosystem behaviour; ERA-Interim data for climate).
Our site-specific results demonstrate the applicability of the proposed method, using the SPEI to describe the climate condition. The site in Spain provides an example of vulnerability to drought because the expected value of the SPEI is 0.4 lower for hazardous than for non-hazardous ecosystem behaviour. In northern Germany, on the contrary, the site is not vulnerable to drought because the SPEI expectation values imply wetter conditions in the hazard case than in the non-hazard case.
At the pan-European scale, ecosystem vulnerability to drought is calculated in the Mediterranean and temperate region, whereas Scandinavian ecosystems are vulnerable under conditions without water shortages. These first model- based applications indicate the conceptual advantages of the proposed method by focusing on the identification of critical weather conditions for which we observe hazardous ecosystem behaviour in the analysed data set. Application of the method to empirical time series and to future climate would be important next steps to test the approach.
In this study, we investigate how immersive 3D geovisualization can be used in higher education. Based on MacEachren and Kraak's geovisualization cube, we examine the usage of immersive 3D geovisualization and its usefulness in a research-based learning module on flood risk, called GEOSimulator. Results of a survey among participating students reveal benefits, such as better orientation in the study area, higher interactivity with the data, improved discourse among students and enhanced motivation through immersive 3D geovisualization. This suggests that immersive 3D visualization can effectively be used in higher education and that 3D CAVE settings enhance interactive learning between students.
Extreme droughts, heat waves, frosts, precipitation, wind storms and other climate extremes may impact the structure, composition and functioning of terrestrial ecosystems, and thus carbon cycling and its feedbacks to the climate system. Yet, the interconnected avenues through which climate extremes drive ecological and physiological processes and alter the carbon balance are poorly understood. Here, we review the literature on carbon cycle relevant responses of ecosystems to extreme climatic events. Given that impacts of climate extremes are considered disturbances, we assume the respective general disturbance-induced mechanisms and processes to also operate in an extreme context. The paucity of well-defined studies currently renders a quantitative meta-analysis impossible, but permits us to develop a deductive framework for identifying the main mechanisms (and coupling thereof) through which climate extremes may act on the carbon cycle. We find that ecosystem responses can exceed the duration of the climate impacts via lagged effects on the carbon cycle. The expected regional impacts of future climate extremes will depend on changes in the probability and severity of their occurrence, on the compound effects and timing of different climate extremes, and on the vulnerability of each land-cover type modulated by management. Although processes and sensitivities differ among biomes, based on expert opinion, we expect forests to exhibit the largest net effect of extremes due to their large carbon pools and fluxes, potentially large indirect and lagged impacts, and long recovery time to regain previous stocks. At the global scale, we presume that droughts have the strongest and most widespread effects on terrestrial carbon cycling. Comparing impacts of climate extremes identified via remote sensing vs. ground-based observational case studies reveals that many regions in the (sub-)tropics are understudied. Hence, regional investigations are needed to allow a global upscaling of the impacts of climate extremes on global carbon-climate feedbacks.
Effects of climate change are particularly strong in high-mountain regions. Most visibly, glaciers are shrinking at a rapid pace, and as a consequence, glacier lakes are forming or growing. At the same time the stability of mountain slopes is reduced by glacier retreat, permafrost thaw and other factors, resulting in an increasing landslide hazard which can potentially impact lakes and therewith trigger far-reaching and devastating outburst floods. To manage risks from existing or future lakes, strategies need to be developed to plan in time for adequate risk reduction measures at a local level. However, methods to assess risks from future lake outbursts are not available and need to be developed to evaluate both future hazard and future damage potential.
Here a method is presented to estimate future risks related to glacier lake outbursts for a local site in southern Switzerland (Naters, Valais). To generate two hazard scenarios, glacier shrinkage and lake formation modelling was applied, combined with simple flood modelling and field work. Furthermore, a land-use model was developed to quantify and allocate land-use changes based on local-to-regional storylines and three scenarios of land-use driving forces. Results are conceptualized in a matrix of three land-use and two hazard scenarios for the year 2045, and show the distribution of risk in the community of Naters, including high and very high risk areas. The study underlines the importance of combined risk management strategies focusing on land-use planning, on vulnerability reduction, as well as on structural measures (where necessary) to effectively reduce future risks related to lake outburst floods.
Scenario analysis is a widely used approach to incorporate uncertainties in global change research. In the context of regional ecosystem service and landscape management where global IPCC climate simulations and their downscaled derivates are applied, it can be useful to work with regional sodo-economic scenarios that are coherent with the global IPCC scenarios. The consistency with the original source scenarios, transparency and reproducibility of the methods used as well as the internal consistency of the derived scenarios are important methodological prerequisites for coherently downscaling pre-existing source scenarios. In contrast to well-established systematic-qualitative scenario techniques, we employ here a formal technique of scenario construction which combines expert judgement with a quantitative, indicator-based selection algorithm in order to deduce a formally consistent set of focus scenario. In our case study, these focus scenarios reflect the potential development pathways of major national-level drivers for ecosystem service management in Swiss mountain regions. The integration of an extra impact factor ("Global Trends") directly referring to the four principle SRES scenario families, helped us to formally internalise base assumptions of IPCC SRES scenarios to regional scenarios that address a different thematic focus (ecosystem service management), spatial level (national) and time horizon (2050). Compared to the well-established systematic-qualitative approach, we find strong similarities between the two methods, including the susceptibility to personal judgement which is only partly reduced by the formal method. However, the formalised scenario approach conveys four clear advantages, (1) the better documentation of the process, (2) its reproducibility, (3) the openness in terms of the number and directions of the finally selected set of scenarios, and (4) its analytical power. (C) 2013 Elsevier Inc. All rights reserved.
Sustainable land use in Mountain Regions under global change synthesis across scales and disciplines
(2013)
Mountain regions provide essential ecosystem goods and services (EGS) for both mountain dwellers and people living outside these areas. Global change endangers the capacity of mountain ecosystems to provide key services. The Mountland project focused on three case study regions in the Swiss Alps and aimed to propose land-use practices and alternative policy solutions to ensure the provision of key EGS under climate and land-use changes. We summarized and synthesized the results of the project and provide insights into the ecological, socioeconomic, and political processes relevant for analyzing global change impacts on a European mountain region. In Mountland, an integrative approach was applied, combining methods from economics and the political and natural sciences to analyze ecosystem functioning from a holistic human-environment system perspective. In general, surveys, experiments, and model results revealed that climate and socioeconomic changes are likely to increase the vulnerability of the EGS analyzed. We regard the following key characteristics of coupled human-environment systems as central to our case study areas in mountain regions: thresholds, heterogeneity, trade-offs, and feedback. Our results suggest that the institutional framework should be strengthened in a way that better addresses these characteristics, allowing for (1) more integrative approaches, (2) a more network-oriented management and steering of political processes that integrate local stakeholders, and (3) enhanced capacity building to decrease the identified vulnerability as central elements in the policy process. Further, to maintain and support the future provision of EGS in mountain regions, policy making should also focus on project-oriented, cross-sectoral policies and spatial planning as a coordination instrument for land use in general.
The terrestrial biosphere is a key component of the global carbon cycle and its carbon balance is strongly influenced by climate. Continuing environmental changes are thought to increase global terrestrial carbon uptake. But evidence is mounting that climate extremes such as droughts or storms can lead to a decrease in regional ecosystem carbon stocks and therefore have the potential to negate an expected increase in terrestrial carbon uptake. Here we explore the mechanisms and impacts of climate extremes on the terrestrial carbon cycle, and propose a pathway to improve our understanding of present and future impacts of climate extremes on the terrestrial carbon budget.