Impacts of climate change on growth, migration and recruitment success of Japanese sardine (Sardinops melanostictus) in the western North Pacific

We developed a multi-trophic level ecosystem model by coupling physical, biogeochemical-plankton and fish models. An oceanic general circulation model was coupled with a lower trophic level ecosystem model and a Japanese sardine migration model, and applied to the western North Pacific. To investigate the impact of global warming on the pelagic fish ecosystem, such as Japanese sardine, we conducted numerical experiments of growth and migration of Japanese sardine using physical fields for the present day and future with a global warming scenario simulated by a high-resolution climate model. The model results demonstrated possible impacts of global warming on the growth and migration pattern of Japanese sardine. The growths of fish in the current main spawning region under the global warming scenario were significantly slower than those under the present climate scenario. Fish in this region will be at disadvantage for their recruitment under the global warming condition. Prey conditions in the spawning region were projected not to markedly change under global warming condition while water temperature increased. As a result sardine spawning ground was projected to shift towards more north areas. During the feeding migration period in summer, geographical distribution of juveniles fish was projected to shift northwards by one to two degrees latitude under the global warming condition following the change in the distribution of optimal temperature region for feeding. However, this northwards shift of the optimal temperature for feeding was minimized adjacent to the western North Pacific by the cooler water supply by the intensification of the Oyashio.     

Bayesian multi-model projection of climate: bias assumptions and interannual variability

Current climate change projections are based on comprehensive multi-model ensembles of global and regional climate simulations. Application of this information to impact studies requires a combined probabilistic estimate taking into account the different models and their performance under current climatic conditions. Here we present a Bayesian statistical model for the distribution of seasonal mean surface temperatures for control and scenario periods. The model combines observational data for the control period with the output of regional climate models (RCMs) driven by different global climate models (GCMs). The proposed Bayesian methodology addresses seasonal mean temperatures and considers both changes in mean temperature and interannual variability. In addition, unlike previous studies, our methodology explicitly considers model biases that are allowed to be time-dependent (i.e. change between control and scenario period). More specifically, the model considers additive and multiplicative model biases for each RCM and introduces two plausible assumptions (“constant bias” and “constant relationship”) about extrapolating the biases from the control to the scenario period. The resulting identifiability problem is resolved by using informative priors for the bias changes. A sensitivity analysis illustrates the role of the informative prior. As an example, we present results for Alpine winter and summer temperatures for control (1961–1990) and scenario periods (2071–2100) under the SRES A2 greenhouse gas scenario. For winter, both bias assumptions yield a comparable mean warming of 3.5–3.6°C. For summer, the two different assumptions have a strong influence on the probabilistic prediction of mean warming, which amounts to 5.4°C and 3.4°C for the “constant bias” and “constant relation” assumptions, respectively. Analysis shows that the underlying reason for this large uncertainty is due to the overestimation of summer interannual variability in all models considered. Our results show the necessity to consider potential bias changes when projecting climate under an emission scenario. Further work is needed to determine how bias information can be exploited for this task.     

The use of scenarios as the basis for combined assessment of climate change mitigation and adaptation

Scenarios are used to explore the consequences of different adaptation and mitigation strategies under uncertainty. In this paper, two scenarios are used to explore developments with (1) no mitigation leading to an increase of global mean temperature of 4 °C by 2100 and (2) an ambitious mitigation strategy leading to 2 °C increase by 2100. For the second scenario, uncertainties in the climate system imply that a global mean temperature increase of 3 °C or more cannot be ruled out. Our analysis shows that, in many cases, adaptation and mitigation are not trade-offs but supplements. For example, the number of people exposed to increased water resource stress due to climate change can be substantially reduced in the mitigation scenario, but adaptation will still be required for the remaining large numbers of people exposed to increased stress. Another example is sea level rise, for which, from a global and purely monetary perspective, adaptation (up to 2100) seems more effective than mitigation. From the perspective of poorer and small island countries, however, stringent mitigation is necessary to keep risks at manageable levels. For agriculture, only a scenario based on a combination of adaptation and mitigation is able to avoid serious climate change impacts.     

An assessment of the potential impact of climate change on flood risk in Mumbai

Managing risks from extreme events will be a crucial component of climate change adaptation. In this study, we demonstrate an approach to assess future risks and quantify the benefits of adaptation options at a city-scale, with application to flood risk in Mumbai. In 2005, Mumbai experienced unprecedented flooding, causing direct economic damages estimated at almost two billion USD and 500 fatalities. Our findings suggest that by the 2080s, in a SRES A2 scenario, an ??upper bound?? climate scenario could see the likelihood of a 2005-like event more than double. We estimate that total losses (direct plus indirect) associated with a 1-in-100 year event could triple compared with current situation (to $690?C$1,890 million USD), due to climate change alone. Continued rapid urbanisation could further increase the risk level. The analysis also demonstrates that adaptation could significantly reduce future losses; for example, estimates suggest that by improving the drainage system in Mumbai, losses associated with a 1-in-100 year flood event today could be reduced by as much as 70%.,We show that assessing the indirect costs of extreme events is an important component of an adaptation assessment, both in ensuring the analysis captures the full economic benefits of adaptation and also identifying options that can help to manage indirect risks of disasters. For example, we show that by extending insurance to 100% penetration, the indirect effects of flooding could be almost halved. We conclude that, while this study explores only the upper-bound climate scenario, the risk-assessment core demonstrated in this study could form an important quantitative tool in developing city-scale adaptation strategies. We provide a discussion of sources of uncertainty and risk-based tools could be linked with decision-making approaches to inform adaptation plans that are robust to climate change.     

未来气候变化情景下长江上游年径流量变化趋势研究

依据政府间气候变化委员会(IPCC)第五次评估报告(AR5)未来不同排放情景(RCPs)下的多模式(CMIP5)气温和降水预估结果,构建基于气温和降水的未来径流量预估模型,并以宜昌站为例分析了不同模式不同排放情景下未来80年(2020～2099年)长江上游年径流量的变化趋势。多模式集合平均预估结果表明:在99%的置信水平下,未来80年长江上游年径流量在RCP2.6排放情景下呈不显著增加趋势,在RCP4.5排放情景下呈不显著减小趋势,而在RCP8.5排放情景下则呈显著减小趋势;在RCP2.6、RCP4.5和RCP8.5排放情景下未来80年长江上游年径流量预估均值相对于1961～2000年分别减少6.42%、10.99%和13.25%;同时,未来80年长江上游年径流量变化具有一定的年代际特征,在RCP2.6和RCP4.5排放情景下21世纪初期偏多、中期偏少而后期变化并不明显,在RCP8.5排放情景下则是21世纪中期以前偏多而中期以后明显偏少。本研究方法可为未来气候变化情景预估分析提供技术参考,本研究成果可供气候变化背景下长江上游乃至长江流域水资源开发利用及对策分析提供决策依据。      

Projected Changes in Surface Air Temperature and Surface Wind in the Gulf of St. Lawrence

Abstract

The impacts of climate change on surface air temperature (SAT) and winds in the Gulf of St. Lawrence (GSL) are investigated by performing simulations from 1970 to 2099 with the Canadian Regional Climate Model (CRCM), driven by a five-member ensemble. Three members are from Canadian Global Climate Model (CGCM3) simulations following scenario A1B from the Intergovernmental Panel on Climate Change (IPCC); one member is from the Community Climate System Model, version 3 (CCSM3) simulation, also following the A1B scenario; and one member is from the CCSM4 (version 4) simulation following the Representative Concentration Pathway (RCP8.5) scenario. Compared with North America Regional Reanalysis (NARR) data, it is shown that CRCM can reproduce the observed SAT spatial patterns; for example, both CRCM simulations and NARR data show a warm SAT tongue along the eastern Gulf; CRCM simulations also capture the dominant northwesterly winds in January and the southwesterly winds in July. In terms of future climate scenarios, the spatial patterns of SAT show plausible seasonal variations. In January, the warming is 3°–3.5°C in the northern Gulf and 2.5°–3°C near Cabot Strait during 2040–2069, whereas the warming is more uniform during 2070–2099, with SAT increases of 4°–5°C. In summer, the warming gradually decreases from the western side of the GSL to the eastern side because of the different heat capacities between land and water. Moreover, the January winds increase by 0.2–0.4?m?s^?1 during 2040–2069, related to weakening stability in the atmospheric planetary boundary layer. However, during 2070–2099, the winds decrease by 0.2–0.4?m?s^?1 over the western Gulf, reflecting the northeastward shift in northwest Atlantic storm tracks. In July, enhanced baroclinicity along the east coast of North America dominates the wind changes, with increases of 0.2–0.4?m?s^?1. On average, the variance for the SAT changes is about 10% of the SAT increase, and the variance for projected wind changes is the same magnitude as the projected changes, suggesting uncertainty in the latter.     

Changes of Terrestrial Water Storage in River Basins of China Projected by RegCM4

In this study, a historic simulation covering the period from 1951 to 2000 and three projected scenario simulations covering 2001-2050 were conducted employing the regional climate model RegCM4 to detect the changes of terrestrial water storage (TWS) in major river basins of China, using the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES): A1B, A2, and B1. The historic simulation revealed that the variations of TWS, which are dominated by precipitation in the basins, rely highly on their climatic features. Compared with the historic simulation, the changes of TWS in the scenario simulations showed strong regional differences. However, for all scenarios, TWS was found to increase most in Northeast China and surrounding mountains around the Tibetan Plateau, and decrease most in eastern regions of China. Unlike the low seasonal variations of TWS in arid areas, the TWS showed strong seasonal variations in eastern monsoon areas, with the maximum changes usually occurring in summer, when TWS increases most in a year. Among the three scenario simulations, TWS increased most in Songhua River Basin of B1 scenario, and de- creased most in Pearl River Basin of A2 scenario and Hai River Basin of A1B scenario, accompanied by different annual trends and seasonal variations.     

Climate Change Impact on Snow Coverage, Evaporation and River Discharge in the Sub-Arctic Tana Basin, Northern Fennoscandia

Arctic environments are generally believed to be highly sensitive to human-induced climatic change. In this paper, we explore the impacts on the hydrological system of the sub-arctic Tana Basin in Northernmost Finland and Norway. In contrast with previous studies, attention is not only given to river discharge, but also to the spatial patterns in snow coverage and evapotranspiration. We used a distributed water balance model that was coupled to a regional climate model in order to calculate a scenario of climate change by the end of this century. Three different model experiments were performed, adopting different approaches to using the climate model output in the hydrological model runs. The results were largely consistent, indicating a much shorter snow season and, accordingly, decreased sublimation, an increase in evapotranspiration, and a shift in the annual runoff peak. As the snow-free season is extended, the amount of solar radiation that is received during this period increases significantly. The results also show important local differences in the hydrological response to climate change. For example, in the scenario runs, the snow season was more than 30 days shorter at higher elevations, but in some of the river valleys, this was up to 70 days.     

Fingerprinting of the Atlantic meridional overturning circulation in climate models to aid in the design of proxy investigations

It is desirable to design proxy investigations that target regions where properties reconstructed from calibrated parameters potentially carry high-fidelity information concerning changes in large-scale climate systems. Numerical climate models can play an important role in this task, producing simulations that can be analyzed to produce spatial “fingerprints” of the expected response of various properties under a variety of different scenarios. We will introduce a new method of fingerprinting the Atlantic meridional overturning circulation (AMOC) that not only provides information concerning the sensitivity of the response at a given location to changes in the large-scale system, but also quantifies the linearity, monotonicity and symmetry of the response. In this way, locations that show high sensitivities to changes in the AMOC, but that exhibit, for example, strongly nonlinear behavior can be avoided during proxy investigations. To demonstrate the proposed approach we will use the example of the response of seawater temperatures to changes in the strength of the AMOC. We present results from an earth-system climate model which has been perturbed with an idealized freshwater forcing scenario in order to reduce the strength of the AMOC in a systematic manner. The seawater temperature anomalies that result from the freshwater forcing are quantified in terms of their sensitivity to the AMOC strength in addition to the linearity and monotonicity of their response. A first-order reversal curve (FORC) approach is employed to investigate and quantify the irreversibility of the temperature response to a slowing and recovering AMOC. Thus, FORCs allow the identification of areas that are unsuitable for proxy reconstructions because their temperature versus AMOC relationship lacks symmetry.     

Future regional projections of extreme temperatures in Europe: a nonstationary seasonal approach

This paper analyzes changes of maximum temperatures in Europe, which are evaluated using two state-of-the-art regional climate models from the EU ENSEMBLES project. Extremes are expressed in terms of return values using a time-dependent generalized extreme value (GEV) model fitted to monthly maxima. Unlike the standard GEV method, this approach allows analyzing return periods at different time scales (monthly, seasonal, annual, etc). The study focuses on the end of the 20th century (1961?C2000), used as a calibration/validation period, and assesses the changes projected for the period 2061?C2100 considering the A1B emission scenario. The performance of the regional models is evaluated for each season of the calibration period against the high-resolution gridded E-OBS dataset, showing a similar South-North gradient with larger values over the Mediterranean basin. The inter-RCM changes in the bias pattern with respect to the E-OBS are larger than the bias resulting from a change in the boundary conditions from ERA-40 to ECHAM5 20c3m. The maximum temperature response to increased green house gases, as projected by the A1B scenario, is consistent for both RCMs. Under that scenario, results indicate that the increments for extremes (e.g. 40-year return values) will be two or three times higher than those for the mean seasonal temperatures, particularly during Spring and Summer in Southern Europe.     

Exploring resource efficiency for energy,land and phosphorus use: Implications for resource scarcity and the global environment

In this paper, we present four model-based scenarios exploring the potential for resource efficiency for energy, land and phosphorus use, and implications for resource depletion, climate change and biodiversity. The scenarios explored include technological improvements as well as structural changes in production systems and lifestyle changes. Many of such changes have long lead times, requiring up front and timely investments in infrastructure, innovative incentive structures and education. For simulating the scenarios we applied the IMAGE modelling framework, with a time horizon until 2050.Our findings confirm a large potential for more efficient resource use: our (no new policies) baseline scenario shows a global increase, between 2010 and 2050, by 80% of primary energy use, 4% of arable land and 40% of phosphorus fertilisers. These numbers are reduced to +25% (primary energy), −9% (arable land) and +9% (phosphorus) in the global resource efficiency scenario. Baseline developments and resource efficiency opportunities vary strikingly among regions, resources and sectors. Phosphorus use, for example, is expected to increase most on croplands in developing countries, whereas the largest potential for phosphorus use efficiency lies in the livestock sector and urban sewage treatment in industrialised countries. Consequently, while resource efficiency resonates well as a general notion in policy thinking, concrete policies need to be region-specific, resource-specific and sector-specific.Efficiency efforts on one resource tend to contribute to efficient use of other resources and to benefit the environment. There are also trade-offs, however, and the synergies analysed do not make problem-specific policies redundant: in 2050, the global resource efficiency scenario presents higher phosphorus use and higher use of fossil fuels than in 2010; greenhouse gas emission targets are met by half; and biodiversity loss slows down but is not halted. Moreover, part of the efficiency gains in land and phosphorus use is sacrificed when this scenario is combined with ambitious climate policy, due to the substantial resource requirements for the deployment of bio-energy—albeit much less than in a scenario without more efficient resource use.     

Regional hydrological cycle changes in response to an ambitious mitigation scenario

Climate change impacts on the regional hydrological cycle are compared for model projections following an ambitious emissions-reduction scenario (E1) and a medium-high emissions scenario with no mitigation policy (A1B). The E1 scenario is designed to limit global annual mean warming to 2 °C or less above pre-industrial levels. A multi-model ensemble consisting of ten coupled atmosphere–ocean general circulation models is analyzed, which includes five Earth System Models containing interactive carbon cycles. The aim of the study is to assess the changes that could be mitigated under the E1 scenario and to identify regions where even small climate change may lead to strong changes in precipitation, cloud cover and evapotranspiration. In these regions the hydrological cycle is considered particularly vulnerable to climate change, highlighting the need for adaptation measures even if strong mitigation of climate change would be achieved. In the A1B projections, there are significant drying trends in sub-tropical regions, precipitation increases in high latitudes and some monsoon regions, as well as changes in cloudiness and evapotranspiration. These signals are reduced in E1 scenario projections. However, even under the E1 scenario, significant precipitation decrease in the subtropics and increase in high latitudes are projected. Particularly the Amazon region shows strong drying tendencies in some models, most probably related to vegetation interaction. Where climate change is relatively small, the E1 scenario tends to keep the average magnitude of potential changes at a level comparable to current intra-seasonal to inter-annual variability at that location. Such regions are mainly located in the mid-latitudes.     

Integrated global change scenarios: surveying user needs in Finland

A questionnaire was sent to almost 600 people representing different target groups in Finland, to investigate their interest in obtaining global change scenarios. There was a 30% response rate to the questionnaire, of which 93% indicated that they could or might make use of scenarios. Priorities for scenarios differed between researchers and non-researchers. The research community required information over a wide spectrum of spatial and temporal resolutions and for time horizons ranging from 10 to 100 years. Non-researchers attached most importance to projections at low spatial and temporal resolution extending over time horizons up to 2025. Three of the five scenario types surveyed were regarded as of above-average importance by both researchers and non-researchers: atmospheric composition, acidification and eutrophication, and climate. Socio-economic scenarios were also of interest to non-researchers but less so to researchers, while both groups expressed below-average interest in sea level scenarios. Overall, the questionnaire provided a valuable initial contact with potential scenario users as well as useful preliminary information about their likely scenario needs.     

Analysis of climatic trends in data from the agrometeorological station of Bologna-Cadriano, Italy (1952–2007)

Agriculture is highly exposed to climate change, as farming activities directly depend on climatic conditions. Knowledge of the extent of such change and of related phenomena will help to answer the questions posed by society about adaptation strategies. The global situation is well described by the Fourth IPCC assessment report (IPCC 2007), but local studies are important to understand the impact and the priorities to adopt in adaptation strategies. In this study a historical set of meteorological data, collected during the period 1952–2007 at the University of Bologna (Italy) agrometeorological station, was analysed. Several indexes, such as Frost Severity Index, number of hot days, number of rainy days, etc., were calculated, and their trends in time were analysed. The results show a scenario of increasing temperatures and evapotranspiration, a decrease in rainy days and a deepening of the watertable. The effect of these changes on agriculture will be a decrease in water availability, an increase in heat stress in plants and an increase in drought risk.     

Scenarios in Global Environmental Assessments: Key characteristics and lessons for future use

Over the last 10 years a large set of global environmental assessment studies has been published that include scenario projections. Comparison of these studies shows that there is actually a limited set of scenario families that form the basis of many scenarios used in different environmental assessments. Mapping these scenario families allow a simpler comparison across the different assessments. The fact that many assessments can be positioned within these families gives some confidence of their relevance. It is also noticeable that several recent assessments have been focusing on more focussed policy-scenarios as variant to a single baseline. This is partly a response to a different stage in the policy-making process. While there are clear advantages of both categories of scenarios (explorative scenarios and baseline/policy variants), it might be important to test the robustness of scenario outcomes of the policy-scenario approach against the different storyline scenario-families identified in this paper.     

Historical and future quantification of terrestrial carbon sequestration from a Greenhouse-Gas-Value perspective

Terrestrial ecosystems provide a range of important services to humans, including global and regional climate regulation. These services arise from natural ecosystem functioning as governed by drivers such as climate, atmospheric carbon dioxide mixing ratio, and land-use change. From the perspective of carbon sequestration, numerous studies have assessed trends and projections of the past and future terrestrial carbon cycle, but links to the ecosystem service concept have been hindered by the lack of appropriate quantitative service metrics. The recently introduced concept of the Greenhouse Gas Value (GHGV) accounts for the land-atmosphere exchanges of multiple greenhouse gases by taking into consideration the associated ecosystem pool sizes, annual exchange fluxes and probable effects of natural disturbance in a time-sensitive manner.We use here GHGV as an indicator for the carbon sequestration aspects of the climate regulation ecosystem service, and quantify it at global scale using the LPJ-GUESS dynamic global vegetation model. The response of ecosystem dynamics and ecosystem state variables to trends in climate, atmospheric carbon dioxide levels and land use simulated by LPJ-GUESS are used to calculate the contribution of carbon dioxide to GHGV. We evaluate global variations in GHGV over historical periods and for future scenarios (1850–2100) on a biome basis following a high and a low emission scenario.GHGV is found to vary substantially depending on the biogeochemical processes represented in LPJ-GUESS (e.g. carbon–nitrogen coupling, representation of land use). The consideration of disturbance events that occur as part of an ecosystem's natural dynamics is crucial for realistic GHGV assessments; their omission results in unrealistically high GHGV. By considering the biome-specific response to current climate and land use, and their projections for the future, we highlight the importance of all forest biomes for maintaining and increasing biogeochemical carbon sequestration. Under future climate and carbon dioxide levels following a high emission scenario GHGV values are projected to increase, especially so in tropical forests, but land-use change (e.g. deforestation) opposes this trend. The GHGV of ecosystems, especially when assessed over large areas, is an appropriate metric to assess the contribution of different greenhouse gases to climate and forms a basis for the monetary valuation of the climate regulation service ecosystems provide.     

Statistically Downscaled Summer Rainfall over the Middle-Lower Reaches of the Yangtze River

The summer rainfall over the middle-lower reaches of the Yangtze River valley (YRSR) has been estimated with a multi-linear regression model using principal atmospheric modes derived from a 500 hPa geopotential height and a 700 hPa zonal vapor flux over the domain of East Asia and the West Pacific.The model was developed using data from 1958 92 and validated with an independent prediction from 1993 2008.The independent prediction was efficient in predicting the YRSR with a correlation coefficient of 0.72 and a relative root mean square error of 18%.The downscaling model was applied to two general circulation models (GCMs) of Flexible Global Ocean-Atmosphere-Land System Model (FGOALS) and Geophysical Fluid Dynamics Laboratory coupled climate model version 2.1 (GFDL-CM2.1) to project rainfall for present and future climate under B1 and A1B emission scenarios.The downscaled results pro-vided a closer representation of the observation compared to the raw models in the present climate.In addition,compared to the inconsistent prediction directly from dif-ferent GCMs,the downscaled results provided a consistent projection for this half-century,which indicated a clear increase in the YRSR.Under the B1 emission scenario,the rainfall could increase by an average of 11.9% until 2011 25 and 17.2% until 2036 50 from the current state;under the A1B emission scenario,rainfall could increase by an average of 15.5% until 2011 25 and 25.3% until 2036 50 from the current state.Moreover,the increased rate was faster in the following decade (2011 25) than the latter of this half-century (2036 50) under both emissions.     

全球实施碳税政策对碳减排及世界经济的影响评估

该研究模拟了全球各区域2008-2050年的经济发展和碳排放状况,并将该模拟结果设定为基准情景。在基准情景中全球GDP随时间增长,而全球的碳排放同样表现出增长趋势。为了模拟碳税政策的减排效应及其对经济的影响,本文构建了其他3种碳税政策情景。情景1,将碳税收入作为一般性财政收入,此时全球升温减缓,世界碳排放下降显著,但中国、印度、俄罗斯、马来西亚和印度尼西亚等发展中国家经济发展严重受创,世界经济不均衡加剧。情景2,将各区域的碳税收入汇总之后按照比例统一分配,该情景下,世界碳减排规模较情景1略有下降,但世界各区域的经济较基准情景得到更好的发展。情景3,碳税税率随时间阶段性增长,此时,碳税政策对全球升温的控制更显著;世界各区域,尤其是发展中国家（地区）,经济增长更迅速。另外,碳税收入用来提升区域技术进步,在一定程度上促进了产业的优化升级。碳税政策与技术进步的协同减排政策,考虑了区域经济发展的不均衡性,兼顾了气候治理的公平性,是一种有效、可行的全球气候治理政策。     

Climate change and Yakama Nation tribal well-being

The Yakima River Basin (Basin) in south-central Washington is a prime example of a place where competing water uses, coupled with over-allocation of water resources, have presented water managers with the challenge of meeting current demand, anticipating future demand, and preparing for potential impacts of climate change. We took a decision analysis approach that gathered diverse stakeholders to discuss their concerns pertaining to climate change effects on the Basin and future goals that were collectively important. One main focus was centered on how climate change may influence future salmon populations. Salmon have played a prominent role in the cultures of Basin communities, especially for tribal communities that have social, cultural, spiritual, subsistence, and economic ties to them. Stakeholders identified the need for a better understanding on how the cultural, spiritual, subsistence, and economic aspects of the Confederated Tribes and Bands of the Yakama Nation could be affected by changes in salmon populations. In an attempt to understand the complexities of these potential effects, this paper proposes a conceptual model which 1) identifies cultural values and components and the interactions between those components that could influence tribal well-being, and 2) shows how federal natural resource managers could incorporate intangible tribal cultural components into decision-making processes by understanding important components of tribal well-being. Future work includes defining the parameterization of the cultural components in order for the conceptual model to be incorporated with biophysical resource models for scenario simulations.     

The potential of Fuzzy Cognitive Maps for semi-quantitative scenario development,with an example from Brazil

The main drawback of the Story-and-Simulation approach is the weak link between qualitative and quantitative scenarios. A semi-quantitative tool, Fuzzy Cognitive Mapping, is introduced as a possible improvement. An example from the Brazilian Amazon shows that by including an integrated set of factors and feedbacks, Fuzzy Cognitive Maps can capture (future) dynamics of deforestation. The example substantiates the tool's capacity to improve the consistency of narrative storylines and the diversity of quantitative models. The tool is designed, however, to be simple and therefore has important drawbacks. Future improvements should be made in the light of applications within a larger toolbox of scenario methods.