Regional impact analysis of climate change on natural and managed forests in the Federal State of Brandenburg, Germany

A methodology for regional application of forest simulation models has been developed as part of an assessment of possible climate change impacts in the Federal state of Brandenburg (Germany). Here we report on the application of a forest gap model to analyse the impacts of climate change on species composition and productivity of natural and managed forests in Brandenburg using a statistical method for the development of climate scenarios. The forest model was linked to a GIS that includes soil and groundwater table maps, as well as gridded climate data with a resolution of 10 × 10 km and simulated a steady-state species composition which was classified into forest types based on the biomass distribution between species. Different climate scenarios were used to assess the sensitivity of species composition to climate change. The simulated forest distribution patterns for current climate were compared with a map of Potential Natural Vegetation (PNV) of Brandenburg.In order to analyse the possible consequences of climate change on forest management, we used forest inventory data to initialize the model with representative forest stands. Simulation experiments with two different management strategies indicated how forest management could respond to the projected impacts of climate change. The combination of regional analysis of natural forest dynamics under climate change with simulation experiments for managed forests outlines possible trends for the forest resources. The implications of the results are discussed, emphasizing the regional differences in environmental risks and the adaptation potentials of forestry in Brandenburg.     

Coupling climate and economic models in a cost-benefit framework: A convex optimisation approach

In this paper, we present a general method, based on a convex optimisation technique, that facilitates the coupling of climate and economic models in a cost-benefit framework. As a demonstration of the method, we couple an economic growth model à la Ramsey adapted from DICE-99 with an efficient intermediate complexity climate model, C-GOLDSTEIN, which has highly simplified physics, but fully 3-D ocean dynamics. As in DICE-99, we assume that an economic cost is associated with global temperature change: this change is obtained from the climate model, which is driven by the GHG concentrations computed from the economic growth path. The work extends a previous paper in which these models were coupled in cost-effectiveness mode. Here we consider the more intricate cost-benefit coupling in which the climate impact is not fixed a priori. We implement the coupled model using an oracle-based optimisation technique. Each model is contained in an oracle, which supplies model output and information on its sensitivity to a master program. The algorithm Proximal-ACCPM guarantees the convergence of the procedure under sufficient convexity assumptions. Our results demonstrate the possibility of a consistent, cost-benefit, climate-damage optimisation analysis with a 3-D climate model.     

Sustainability of winter tourism in a changing climate over Kashmir Himalaya

Mountain areas are sensitive to climate change. Implications of climate change can be seen in less snow, receding glaciers, increasing temperatures, and decreasing precipitation. Climate change is also a severe threat to snow-related winter sports such as skiing, snowboarding, and cross-country skiing. The change in climate will put further pressure on the sensitive environment of high mountains. Therefore, in this study, an attempt has been made to know the impact of climate change on the snow precipitation, water resources, and winter tourism in the two famous tourist resorts of the Kashmir Valley. Our findings show that winters are getting prolonged with little snow falls on account of climate change. The average minimum and maximum temperatures are showing statistically significant increasing trends for winter months. The precipitation is showing decreasing trends in both the regions. A considerable area in these regions remains under the snow and glacier cover throughout the year especially during the winter and spring seasons. However, time series analysis of LandSat MODIS images using Normalized Difference Snow Index shows a decreasing trend in snow cover in both the regions from past few years. Similarly, the stream discharge, comprising predominantly of snow- and glacier-melt, is showing a statistically significant declining trend despite the melting of these glaciers. The predicted futuristic trends of temperature from Predicting Regional Climates for Impact Studies regional climate model are showing an increase which may enhance snow-melting in the near future posing a serious threat to the sustainability of winter tourism in the region. Hence, it becomes essential to monitor the changes in temperature and snow cover depletion in these basins in order to evaluate their effect on the winter tourism and water resources in the region.     

Effects of climate and landcover change on stream discharge in the Ozark Highlands,USA

Stream discharge of a watershed is affected and altered by climate and landcover changes. These effects vary depending on the magnitude and interaction of the changes, and need to be understood so that local water resource availability can be evaluated and socioeconomic development within a watershed be pursued and managed in a way sustainable with the local water resources. In this study, the landcover and climate change effects on stream discharge from the Jacks Fork River basin in the Ozark Highlands of the south-central United States were examined in three phases: site observation and data collection, model calibration and simulation, and model experiment and analysis. Major results of the study show that climate fluctuations between wet and dry extremes resulted in the same change of the basin discharge regardless of the landcover condition in the basin. On the other hand, under a specified climate condition landcover change from a grassland basin to a fully forested basin only resulted in about one half of the discharge change caused by the climate variation. Furthermore, when landcover change occurred simultaneously with climate variation, the basin discharge change amplified significantly and became larger than the combined discharge changes caused by the climate and landcover change alone, a result indicating a synergistic effect of landcover and climate change on basin discharge variability. Agricultural Research Division, University of Nebraska-Lincoln, Contribution Number 13437.Qi Hu: Corresponding author: Dr. Qi Hu, Climate and Bio-Atmospheric Sciences Group, School of Natural Resource Sciences, 237 L.W. Chase Hall, University of Nebraska-Lincoln, Lincoln, NE 68583-0728, USA. E-mail: qhu2@unl.edu.     

The potential effects of climate change on the distribution and productivity of Cunninghamia lanceolata in China

Climate changes may have immediate implications for forest productivity and may produce dramatic shifts in tree species distributions in the future. Quantifying these implications is significant for both scientists and managers. Cunninghamia lanceolata is an important coniferous timber species due to its fast growth and wide distribution in China. This paper proposes a methodology aiming at enhancing the distribution and productivity of C. lanceolata against a background of climate change. First, we simulated the potential distributions and establishment probabilities of C. lanceolata based on a species distribution model. Second, a process-based model, the PnET-II model, was calibrated and its parameterization of water balance improved. Finally, the improved PnET-II model was used to simulate the net primary productivity (NPP) of C. lanceolata. The simulated NPP and potential distribution were combined to produce an integrated indicator, the estimated total NPP, which serves to comprehensively characterize the productivity of the forest under climate change. The results of the analysis showed that (1) the distribution of C. lanceolata will increase in central China, but the mean probability of establishment will decrease in the 2050s; (2) the PnET-II model was improved, calibrated, and successfully validated for the simulation of the NPP of C. lanceolata in China; and (3) all scenarios predicted a reduction in total NPP in the 2050s, with a markedly lower reduction under the a2 scenario than under the b2 scenario. The changes in NPP suggested that forest productivity will show a large decrease in southern China and a mild increase in central China. All of these findings could improve our understanding of the impact of climate change on forest ecosystem structure and function and could provide a basis for policy-makers to apply adaptive measures and overcome the unfavorable influences of climate change.     

Spatiotemporal analysis of the effect of climate change on vegetation health in the Drakensberg Mountain Region of South Africa

The impact of climate change on mountain ecosystems has been in the spotlight for the past three decades. Climate change is generally considered to be a threat to ecosystem health in mountain regions. Vegetation indices can be used to detect shifts in ecosystem phenology and climate change in mountain regions while satellite imagery can play an important role in this process. However, what has remained problematic is determining the extent to which ecosystem phenology is affected by climate change under increasingly warming conditions. In this paper, we use climate and vegetation indices that were derived from satellite data to investigate the link between ecosystem phenology and climate change in the Namahadi Catchment Area of the Drakensberg Mountain Region of South Africa. The time series for climate indices as well as those for gridded precipitation and temperature data were analyzed in order to determine climate shifts, and concomitant changes in vegetation health were assessed in the resultant epochs using vegetation indices. The results indicate that vegetation indices should only be used to assess trends in climate change under relatively pristine conditions, where human influence is limited. This knowledge is important for designing climate change monitoring strategies that are based on ecosystem phenology and vegetation health.     

Environmental water demand assessment under climate change conditions

Measures taken to cope with the possible effects of climate change on water resources management are key for the successful adaptation to such change. This work assesses the environmental water demand of the Karkheh river in the reach comprising Karkheh dam to the Hoor-al-Azim wetland, Iran, under climate change during the period 2010–2059. The assessment of the environmental demand applies (1) representative concentration pathways (RCPs) and (2) downscaling methods. The first phase of this work projects temperature and rainfall in the period 2010–2059 under three RCPs and with two downscaling methods. Thus, six climatic scenarios are generated. The results showed that temperature and rainfall average would increase in the range of 1.7–5.2 and 1.9–9.2%, respectively. Subsequently, flows corresponding to the six different climatic scenarios are simulated with the unit hydrographs and component flows from rainfall, evaporation, and stream flow data (IHACRES) rainfall-runoff model and are input to the Karkheh reservoir. The simulation results indicated increases of 0.9–7.7% in the average flow under the six simulation scenarios during the period of analysis. The second phase of this paper’s methodology determines the monthly minimum environmental water demands of the Karkheh river associated with the six simulation scenarios using a hydrological method. The determined environmental demands are compared with historical ones. The results show that the temporal variation of monthly environmental demand would change under climate change conditions. Furthermore, some climatic scenarios project environmental water demand larger than and some of them project less than the baseline one.     

Sharing the geo-Referenced Results of Climate Change Impact Research

The Prairie Adaptation Research Collaborative (PARC) has implemented an Internet Map Server (IMS) at the PARC web site (www.parc.ca) to 1) disseminate the geo-referenced results of PARC sponsored research on climate change impacts and adaptation, and 2) address data, information and knowledge management within the PARC network of researchers and partners. PARC facilitates interdisciplinary research on adaptation to the impacts of climate change in the Canadian Prairie Provinces. The web site is intended as a platform for sharing information and encouraging discussion of climate change impacts and adaptation. The IMS enables scientists and stakeholders to apply simple climate change scenarios to geo-referenced biophysical and social data, and dynamically create maps that display the geographic distribution of potential impacts of climate change. With a limited capacity for spatial analysis, most geo-processing and the climate impact modeling is done offline within a GIS environment. The IMS will serve the output from climate impact models, such that the model results can be customized by the web site user and be most readily applied to the planning and analysis of adaptation strategies.     

Climate Impact Response Functions for Terrestrial Ecosystems

We introduce climate impact response functions as a means for summarizing and visualizing the responses of climate-sensitive sectors to changes in fundamental drivers of global climate change. In an inverse application, they allow the translation of thresholds for climate change impacts (‘impact guard-rails’) into constraints for climate and atmospheric composition parameters (‘climate windows’). It thus becomes feasible to specify long-term objectives for climate protection with respect to the impacts of climate change instead of crude proxy variables, like the change in global mean temperature. We apply the method to assess impacts on terrestrial ecosystems, using the threat to protected areas as the central impact indicator. Future climate states are characterized by geographically and seasonally explicit climate change patterns for temperature, precipitation and cloud cover, and by their atmospheric CO₂ concentration. The patterns are based on the results of coupled general circulation models. We study the sensitivity of the impact indicators and the corresponding climate windows to the spatial coverage of the analysis and to different climate change projections. This enables us to identify the most sensitive biomes and regions, and to determine those factors which significantly influence the results of the impact assessment. Based on the analysis, we conclude that climate impact response functions are a valuable means for the representation of climate change impacts across a wide range of plausible futures. They are particularly useful in integrated assessment models of climate change based on optimizing or inverse approaches where the on-line simulation of climate impacts by sophisticated impact models is infeasible due to their high computational demand. This revised version was published online in July 2006 with corrections to the Cover Date.     

Rural poverty driven soil degradation under climate change: the sensitivity of the disposition towards the Sahel Syndrome with respect to climate

Starting from the basic assumption of the syndrome concept that essentially all of the present problematic civilization–nature interactions on the global scale can be subdivided into a limited number of typical patterns, the analysis of the response of these patterns (syndromes) to climate change can make a major contribution to climate impact research, surmounting the difficulties of more common sectoral ceteris paribus impact studies with respect to their systemic integration. In this paper we investigate in particular the influence of climate on the regional proneness or disposition towards one of the most important syndromes with respect to famines and malnutrition, the Sahel Syndrome. It describes the closely interlinked natural and socioeconomic aspects of rural poverty driven degradation of soil and vegetation on marginal sites. Two strategies of global climate impact assessment on a spatial 0.5°×0.5° grid were pursued: (a) As a measure for the climate sensitivity of the regional proneness, the absolute value of the gradient of the disposition with respect to the global field of 3} 12 monthy normals of temperature, irradiation and precipitation is calculated. (b) The disposition was evaluated for two different climate forecasts under doubled atmospheric CO₂ concentration. For both strategies two new quantitative global models were incorporated in a fuzzy-logic-based algorithm for determining the disposition towards the Sahel Syndrome: a neural-net-based model for plant productivity and a waterbalance model which calculates surface runoff considering vertical and lateral fluxes, both driven by the set of 36 monthly climatological normals and designed to allow very fast global numerical evaluation.Calculation (b) shows that the change in disposition towards the Sahel Syndrome crucially depends on the chosen climate forecast, indicating that the disagreement of climate forecasts is propagated to the impact assessment of the investigated socio-economic pattern. On the other hand the regions with a significant increase in disposition in at least one of the climate scenario-based model runs form a subset of the regions which are indicated by the local climate sensitivity study (a) as highly sensitive – illustrating that the gradient measure applied here provides a resonable way to calculate an upper limit or worst case of negative climate impact. This method is particularly valuable in the case of uncertain climate predictions as, e.g., for the change in precipitation patterns.     

Mind the gap in SEA: An institutional perspective on why assessment of synergies amongst climate change mitigation, adaptation and other policy areas are missing

This article takes its point of departure in two approaches to integrating climate change into Strategic Environmental Assessment (SEA): Mitigation and adaptation, and in the fact that these, as well as the synergies between them and other policy areas, are needed as part of an integrated assessment and policy response. First, the article makes a review of how positive and negative synergies between a) climate change mitigation and adaptation and b) climate change and other environmental concerns are integrated into Danish SEA practice. Then, the article discusses the implications of not addressing synergies. Finally, the article explores institutional explanations as to why synergies are not addressed in SEA practice. A document analysis of 149 Danish SEA reports shows that only one report comprises the assessment of synergies between mitigation and adaptation, whilst 9,4% of the reports assess the synergies between climate change and other environmental concerns. The consequences of separation are both the risk of trade-offs and missed opportunities for enhancing positive synergies. In order to propose explanations for the lacking integration, the institutional background is analysed and discussed, mainly based on Scott's theory of institutions. The institutional analysis highlights a regulatory element, since the assessment of climate change synergies is underpinned by legislation, but not by guidance. This means that great focus is on normative elements such as the local interpretation of legislation and of climate change mitigation and adaptation. The analysis also focuses on how the fragmentation of the organisation in which climate change and SEA are embedded has bearings on both normative and cultural-cognitive elements. This makes the assessment of synergies challenging. The evidence gathered and presented in the article points to a need for developing the SEA process and methodology in Denmark with the aim to include climate change in the assessments in a more systematic and integrated manner.     

A new model for climate system analysis: Outline of the model and application to palaeoclimate simulations

We present a new reduced-form model for climate system analysis. This model, called CLIMBER-2 (for CLIMate and BiosphERe, level 2), fills the current gap between simple, highly parameterized climate models and computationally expensive coupled models of global atmospheric and oceanic circulation. We outline the basic assumptions implicit in CLIMBER-2 and we present examples of climate system analysis including a study of atmosphere–ocean interaction during the last glacial maximum, an analysis of synergism between various components of the climate system during the mid-Holocene around 6000 years ago, and a transient simulation of climate change during the last 8000 years. These studies demonstrate the feasibility of a computationally efficient analysis of climate system dynamics which is a prerequisite for future climate impact research and, more generally, Earth system analysis, i.e., the analysis of feedbacks between our environment and human activities.     

Integrating Impacts into Adaptation Measures

A mechanism has been established to improve integration of international climate-related programmes. Known as the Climate Agenda it outlines a programme, that in a cost-effective way, responds to national obligations to respond to international agreements as well as their national needs for social and economic development. The paper briefly describes the Climate Agenda and the incorporation within it of studies of climate impact assessments and response strategies to reduce vulnerability. The need for increased emphasis on climate impact assessment and for the development of effective adaptation measures is emphasised following the elaboration of a Kyoto Protocol to the United Nations Framework Convention on Climate Change (UNFCCC). UNEP's efforts to identify national programmes contributing to the Climate Agenda are described.The response from developing countries has, however, been very disappointing, even from countries where we know work is ongoing through funding by GEF or US Country Studies Program and other bilateral programmes. Initial compilation of information available so far shows that many developed countries are putting a lot into the area of impact assessment of not just climate change, but also climate variability. There remain some research gaps, especially in the area of assessment of climate impacts on ecosystems, hydrological systems, etc. Considerable efforts are presently being directed at reduction of emissions of greenhouse gases and in the case of developing countries, most efforts are being directed towards completing national communications and providing baseline data for future studies.The paper refers to early activities by UNEP in cooperation with other international organizations to undertake integrated assessments of the impacts of climate change on important socio-economic sectors and the later incorporation of lessons learned into the IPCC Guidelines for Assessing Impacts of Climate Change.Later sections outline the development of a handbook on methods for climate change impact assessment and adaptation strategies as a practical approach to national assessments and the development of appropriate and cost-effective response to climate change.The initiation of a GEF-funded project to apply the methods contained in the handbook and improve the results based on national studies is also described for both developed and developing countries.Working in collaboration with a team of international experts under the coordination of the Institute of Environmental Studies at Vrije University (Amsterdam), the goal of this ongoing project is to develop a valuable methodological tool that Parties to the UNFCCC may apply to develop national climate change impact and adaptation assessments. Development of these guidelines was linked to a series of country studies in Antigua and Barbuda, Estonia, Cameroon and Pakistan funded under a UNEP/GEF project. The application of the first version of the UNEP Handbook by national study teams in these four countries is making valuable technical and practical contributions and will ensure that the next version of the Handbook will be a more useful tool for experts in developing countries undertaking similar studies in the future. The methods contained in the Handbook are also the basis for similar assessments funded under bilateral development programmes in other countries. These and similar studies elsewhere are coordinated with the UNEP programme and will eventually aim to create reliable and comparable assessments, a compatible set of tools for such purpose and the identification of realistic adaptation options for incorporation into national planning for adapting to climate change. The paper also addresses how climate impact assessment and response strategies are undertaken as part of national enabling activities carried out in co-operation with UNEP.     

Risk of Hunger Under Climate Change, Social Disparity, and Agroproductivity Scenarios

Considering the projected population growth in the twenty-first century, some studies have indicated that global warming may have negative impacts on the risk of hunger. These conclusions were derived based on assumptions related to social and technological scenarios that involve substantial and influential uncertainties. In this paper, focusing on agrotechnology and food access disparity, we analyzed food availability and risk of hunger under the combined scenarios of food demands and agroproductivity with and without climate change by 2100 for the B2 scenario in the Special Report on Emissions Scenarios. The results of this study suggest that (1) future food demand can be satisfied globally under all assumed combined scenarios, and (2) a reduction of food access disparity and increased progress in productivity are just as important as climate change mitigation for reducing the risk of hunger.     

Approaches for performing uncertainty analysis in large-scale energy/economic policy models

A number of key policy insights have emerged from the application of large-scale economic/energy models, such as integrated assessment models for climate change. These insights have been particularly powerful in those instances when they are shared by all or most of the existing models. On the other hand, some results and policy recommendations obtained from integrated assessment models vary widely from model to model. This can limit their usability for policy analysis. The differences between model results are mostly due to different underlying assumptions about exogenous processes, about endogenous processes and the dynamics among them, differences in value judgments, and different approaches for simplifying model structure for computational purposes. Uncertainty analyses should be performed for the dual purpose of clarifying the uncertainties inherent in model results and improving decision making under uncertainty. This paper develops a unifying framework for comparing the different types of uncertainty analyses through their objective functions, categorizes types of uncertainty analyses that can be performed on large models, and compares different approaches to uncertainty analysis by explaining underlying assumptions, suitability for different model types, and advantages and disadvantages. The appendix presents a summary of integrated assessment models for climate change that explicitly account for uncertainty.     

The Benefits of Cooperation Under Uncertainty: the Case of Climate Change

This article presents an analysis of the behaviour of countries defining their climate policies in an uncertain context. The analysis is made using the S-CWS model, a stochastic version of an integrated assessment growth model. The model includes a stochastic definition of the climate sensitivity parameter. We show that the impact of uncertainty on policy design critically depends on the shape of the damage function. We also examine the benefits of cooperation in the context of uncertainty: We highlight the existence of an additional benefit of cooperation, namely risk reduction.     

Land Use and Climate Change Impacts on the Hydrology of the Bago River Basin,Myanmar

Assessment of land use and climate change impacts on the hydrological cycle is important for basin scale water resources management. This study aims to investigate the potential impacts of land use and climate change on the hydrology of the Bago River Basin in Myanmar. Two scenarios from the representative concentration pathways (RCPs): RCP4.5 and RCP8.5 recommended by the Intergovernmental Panel on Climate Change, Fifth Assessment Report (IPCC AR5) were used to project the future climate of 2020s, 2050s, and 2080s. Six general circulation models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5) were selected to project the future climate in the basin. An increase of average temperature in the range of 0.7 to 1.5 °C and 0.9 to 2.7 °C was observed under RCP 4.5 and RCP 8.5, respectively, in future periods. Similarly, average annual precipitation shows a distinct increase in all three periods with the highest increase in 2050s. A well calibrated and validated Soil and Water Assessment Tool (SWAT) was used to simulate the land use and climate change impacts on future stream flows in the basin. It is observed that the impact of climate change on stream flow is higher than the land use change in the near future. The combined impacts of land use and climate change can increase the annual stream flow up to 68 % in the near future. The findings of this study would be beneficial to improve land and water management decisions and in formulating adaptation strategies to reduce the negative impacts, and harness the positive impacts of land use and climate change in the Bago River Basin.     

Expert System for Terrestrial Vegetation Distribution, Potential Impact and Mitigation Abatement Measures

The tropical rainforest of Malaysia holds one of the richest flora in the world. The favourable climate has produced flora of amazing richness and variety. Terrestrial vegetation of tropical rainforests is an important feature of the environment. Plants play a major role in the environment and conservation of a particular environment depends fundamentally on the maintenance of existing plants and their communities and hierarchies. Interference in the balance of the ecosystem may produce radical changes that lead to progressive deviations from the original situation. Therefore, the application of a computer technology in the form of an expert system (ES) will be able to help in the analysis and management of the EIA information. The ES is named VEGEVIC. Application of the system will lead to greater consistency in the application of EIA through implementation of a standard approach.     

Climate and Freshwater Resources in Northern Mexico: Sonora, a Case Study

An analysis of current trends in water availability in the Mexican border state of Sonora is presented to illustrate what may be faced under climate change conditions. Precipitation, streamflow and even dam levels data are examined to estimate what changes have been experienced in recent decades. There are indications that the more frequent occurrence of El Niño/Southern Oscillation (ENSO) events have resulted in more winter precipitation and consequently in a slight increase in water availability in northwestern Mexico. However, water demands grow much faster than such trends in water availability, mainly due to a rapid increase in population in urban areas and in socio-economic activities such as those related to agriculture, industry and power generation. Some strategies to adapt or mitigate climate change conditions are proposed.     

Potential Impact of Climate Change on Residential Energy Consumption in Dhaka City

This study aimed to assess the impacts of climate change on residential energy consumption in Dhaka city of Bangladesh. The monthly electricity consumption data for the period 2011–2014 and long-term climate variables namely monthly rainfall and temperature records (1961–2010) were used in the study. An ensemble of six global circulation models (GCMs) of coupled model intercomparison project phase 5 (CMIP5) namely, BCCCSM1-1, CanESM2, MIROC5, MIROC-ESM, MIROC-ESM-CHEM, and NorESM1-M under four representative concentration pathway (RCP) scenarios were used to project future changes in rainfall and temperature. The regression models describing the relationship between historical energy consumption and climate variables were developed to project future changes in energy consumptions. The results revealed that daily energy consumption in Dhaka city increases in the range of 6.46–11.97 and 2.37–6.25 MkWh at 95% level of confidence for every increase of temperature by 1 °C and daily average rainfall by 1 mm, respectively. This study concluded that daily total residential energy demand and peak demand in Dhaka city can increase up to 5.9–15.6 and 5.1–16.7%, respectively, by the end of this century under different climate change scenarios.