Effective Climate Change Adaptation Strategies Research Articles

Statistical downscaling of CMIP5 outputs for projecting future changes in rainfall in the Onkaparinga catchment

A generalized linear model was fitted to stochastically downscaled multi-site daily rainfall projections from CMIP5 General Circulation Models (GCMs) for the Onkaparinga catchment in South Australia to assess future changes to hydrologically relevant metrics. For this purpose three GCMs, two multi-model ensembles (one by averaging the predictors of GCMs and the other by regressing the predictors of GCMs against reanalysis datasets) and two scenarios (RCP4.5 and RCP8.5) were considered. The downscaling model was able to reasonably reproduce the observed historical rainfall statistics when the model was driven by NCEP reanalysis datasets. Significant bias was observed in the rainfall when downscaled from historical outputs of GCMs. Bias was corrected using the Frequency Adapted Quantile Mapping technique. Future changes in rainfall were computed from the bias corrected downscaled rainfall forced by GCM outputs for the period 2041–2060 and these were then compared to the base period 1961–2000. The results show that annual and seasonal rainfalls are likely to significantly decrease for all models and scenarios in the future. The number of dry days and maximum consecutive dry days will increase whereas the number of wet days and maximum consecutive wet days will decrease. Future changes of daily rainfall occurrence sequences combined with a reduction in rainfall amounts will lead to a drier catchment, thereby reducing the runoff potential. Because this is a catchment that is a significant source of Adelaide's water supply, irrigation water and water for maintaining environmental flows, an effective climate change adaptation strategy is needed in order to face future potential water shortages.

Effective climate change adaptation strategies for biodiversity conservation

Effective Climate Change (CC) adaptation strategies for biodiversity conservation have been heavily discussed recently. Currently, there are ∼650 CC adaptation recommendations such as managing healthy vegetation on slopes (Veech, 2003), terrestrial and inland water systems (Settele et al., 2014), landscape restoration efforts (Pradhan and Shrestha, 2007), creation and protection of climate refuges (Lindenmayer et al., 2010), wildlife conservation (Mawdsley et al., 2009) among several others (Grabherr, 2009; Khattak et al., 2010). However, they are vague, lack specific solutions with limited analysis of significant benefits, advantages and disadvantages. Over the last few years, I have been developing a database which critically evaluates a variety of CC adaptation strategies, for several biodiversity conservation scenarios. After performing extensive analysis of the existing recommendations, and comparing them against the database that I have been populating, I have critically identified and analyzed 13 effective adaptation strategies for biodiversity conservation that confer significant ecological benefits, and therefore, I discuss them here as most effective. They are segmented under [1] identification and analysis of existing stressors, [2] initiation of strategic zoning of land uses, [3] better preparation for major disturbances, [4] identification and designation of reserves, and [5] increased communication of knowledge to stakeholders. Intended benefits of such adaptation strategies include [a] improved capacity of decision makers to adapt to CC; [b] ability to adapt CC with specific reference to the interactions between ecosystems, communities and populations; [c] ability to device most appropriate adaptation strategies for different CC scenarios; [d] increased flow of communication; [e] ability to device proactive adaptive strategies for different habitat; [f] establish cross-national collaboration among the organizations; [g]ability to develop guidelines for adapting to CC that is specific for regions prone to extremities of stress, and [h] quantify environmental susceptibility against adaptive capacity, for effective biodiversity conservation (see Table 1).

P-graph approach for GDP-optimal allocation of resources, commodities and capital in economic systems under climate change-induced crisis conditions

Climate change impacts may manifest via multiple pathways, often leading to a shortage of resources, reduction in production capacities, or reduction in available labor inputs that are vital for economic activities. Effective climate change adaptation strategies are needed to determine the optimal allocation of scarce resources, commodities or capital under crisis conditions to minimize the economic consequences. In such cases, it is necessary to account for structural properties of economic systems to ensure that rational distribution policies are implemented. Input–output models are used to illustrate interdependencies among economic sectors and to assess both direct and indirect effects of disruptive events. Alternatively, these interdependencies may be exploited for developing effective recovery efforts to minimize the ripple effects of a crisis. In this paper, a process graph representation of the input–output model is developed to generate a rational procedure for the allocation of scarce resources, commodities or capital during crisis conditions. The process graph model is a graph-theoretic approach originally developed for chemical process design applications. The analogous problem structure allows it to be used for the input–output system. The method is demonstrated through several case studies to identify allocation policies geared towards reducing the impact of disruptions attributed to critical resources, commodities, or capital. Results show that depending on the economic structure, the optimal allocation of scarce resources, commodities or capital will satisfy the final demands of some economic sectors and reduce the production capacity of others in order to minimize the reduction of total gross domestic product. Though similar results can be obtained through traditional mathematical programming models, the process graph platform has the advantage to visually present the distribution of scarce resources, commodities or capital within the system. This work is a first attempt to implement the process graph approach in the fields of economics and climate change adaptation. In conclusion, the process graph based approach developed in this work can be used to provide policymakers with insights in developing appropriate risk mitigation plans associated with climate change-induced crisis conditions. Potential applications include both the development of disaster preparedness measures for anticipated disruptions, as well as the implementation of real-time emergency response in the midst of a crisis.

Changing How Earth System Modeling is Done to Provide More Useful Information for Decision Making, Science, and Society

New details about natural and anthropogenic processes are continually added to models of the Earth system, anticipating that the increased realism will increase the accuracy of their predictions. However, perspectives differ about whether this approach will improve the value of the information the models provide to decision makers, scientists, and societies. The present bias toward increasing realism leads to a range of updated projections, but at the expense of uncertainty quantification and model tractability. This bias makes it difficult to quantify the uncertainty associated with the projections from any one model or to the distribution of projections from different models. This in turn limits the utility of climate model outputs for deriving useful information such as in the design of effective climate change mitigation and adaptation strategies or identifying and prioritizing sources of uncertainty for reduction. Here we argue that a new approach to model development is needed, focused on the delivery of information to support specific policy decisions or science questions. The central tenet of this approach is the assessment and justification of the overall balance of model detail that reflects the question posed, current knowledge, available data, and sources of uncertainty. This differs from contemporary practices by explicitly seeking to quantify both the benefits and costs of details at a systemic level, taking into account the precision and accuracy with which predictions are made when compared to existing empirical evidence. We specify changes to contemporary model development practices that would help in achieving this goal.

Assessment of Patterns of Climate Variables and Malaria Cases in Two Ecological Zones of Ghana

Climate change is projected to impact human health, particularly incidence of water related and vector borne diseases, such as malaria. A better understanding of the relationship between rainfall patterns and malaria cases is thus required for effective climate change adaptation strategies involving planning and implementation of appropriate disease control interventions. We analyzed climatic data and reported cases of malaria spanning a period of eight years (2001 to 2008) from two ecological zones in Ghana (Ejura and Winneba in the transition and coastal savannah zones respectively) to determine the association between malaria cases, and temperature and rainfall patterns and the potential effects of climate change on malaria epidemiological trends. Monthly peaks of malaria caseloads lagged behind monthly rainfall peaks. Correlation between malaria caseloads and rainfall intensity, and minimum temperature were generally weak at both sites. Lag correlations of up to four months yielded better agreement between the variables, especially at Ejura where a two-month lag between malaria caseloads and rainfall was significantly high but negatively correlated (r = -0.72; p value < 0.05). Mean monthly maximum temperature and monthly malaria caseloads at Ejura showed a strong negative correlation at zero month lag (r = -0.70, p value < 0.05), with a similar, but weaker relationship at Winneba, (r = -0.51). On the other hand, a positive significant correlation (r = 0.68, p value < 0.05) between malaria caseloads and maximum temperature was observed for Ejura at a four-month lag, while Winneba showed a strong correlation (r = 0.70; p value < 0.05) between the parameters at a two-month lag. The results suggest maximum temperature as a better predictor of malaria trends than minimum temperature or precipitation, particularly in the transition zone. Climate change effects on malaria caseloads seem multi-factorial. For effective malaria control, interventions could be synchronized with the most important climatic predictors of the disease for greater impact.

Disconnect between science and end-users as a barrier to climate change adaptation

CR Climate Research Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials CR 58:29-41 (2013) - DOI: https://doi.org/10.3354/cr01181 Disconnect between science and end-users as a barrier to climate change adaptation Anthony S. Kiem*, Emma K. Austin Environmental and Climate Change Research Group, School of Environmental and Life Sciences, Faculty of Science and Information Technology, University of Newcastle, Callaghan, NSW 2308, Australia *Email: anthony.kiem@newcastle.edu.au ABSTRACT: Much research into climate change impacts and adaptation has been, and continues to be, conducted. However, the well documented themes and recommendations continue to emerge with little evidence of effective climate change adaptation strategies being implemented. This is because while climate change adaptation strategies are not hard to develop, it is difficult to evaluate their effectiveness or, in some cases, even define effectiveness. Compounding this is the fact that implementing strategies that in theory, or in pilot studies, are potentially effective is complicated due to political, economic, legislative and science constraints and the difficulties associated with decision making under uncertainty. Here we focus on Australian rural communities and have found that a major barrier to implementation of effective adaptation strategies is the disconnect between the information that end-users need (or think they need) and the existing outcomes of climate change impacts and adaptation research. While previous research, and anecdotal evidence, qualitatively establishes that a ‘gap’ does exist, this study represents a preliminary attempt at quantifying the causes and magnitude of the disconnect: a necessary first step in addressing the challenge posed by this barrier to adaptation. The findings are relevant beyond Australia, beyond the agriculture sector, and beyond climate change science, and highlight the need for urgent work aimed at bridging the gap between scientists and decision makers (and other end-users). KEY WORDS: Interdisciplinary studies · Adaptation · Decision making · Agriculture · Terminology Full text in pdf format Supplementary material PreviousNextCite this article as: Kiem AS, Austin EK (2013) Disconnect between science and end-users as a barrier to climate change adaptation. Clim Res 58:29-41. https://doi.org/10.3354/cr01181 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in CR Vol. 58, No. 1. Online publication date: November 19, 2013 Print ISSN: 0936-577X; Online ISSN: 1616-1572 Copyright © 2013 Inter-Research.

Climate Change Adaptation Through Urban Heat Management in Atlanta, Georgia

This study explores the potential effectiveness of metropolitan land cover change as a climate change adaptation strategy for managing rising temperatures in a large and rapidly warming metropolitan region of the United States. Through the integration of a mesoscale meteorological model with estimated land cover data for the Atlanta, Georgia region in 2010, this study quantifies the influence of extensive land cover change at the periphery of a large metropolitan region on temperature within the city center. The first study to directly model a metropolitan scale heat transfer mechanism, we find both enhanced tree canopy and impervious cover in the suburban zones of the Atlanta region to produce statistically significant cooling and warming effects in the urban core. Based on these findings, we conclude that urban heat island management both within and beyond the central developed core of large cities may provide an effective climate change adaptation strategy for large metropolitan regions.

Farmers’ Perceptions and Adaptations to Climate Change in Sub-Sahara Africa: A Synthesis of Empirical Studies and Implications for Public Policy in African Agriculture

The problem of climate change in Africa has the potential of undermining sustainable development efforts if steps are not taken to respond to its adverse consequences. This study reviews existing and available literature on farmers’ perceptions and adaptations to climate change in sub-Sahara Africa. It is evident that the majority of farmers in sub-Sahara Africa are aware of warmer temperatures and changes in precipitation patterns. To respond to these changes, farmers have adopted crop diversification, planting different crop varieties, changing planting and harvesting dates to correspond to the changing pattern of precipitation, irrigation, planting tree crops,water and soil conservation techniques, and switching to non-farm income activities. Years of farming experience, household size, years of education, access to credit facilities, access to extension services and off-farm income are among the signicant determinants of adopting climate change adaptation measures. To enable sub-Sahara African farmers to develop more effective climate change adaptationstrategies,there is the need for African governments to support farmers by providing the necessary resources such as credit, information and extension workers to train farmers on climate change adaptation strategies and technologies, and investing in climate resilient projects like, improving on existing or building new water infrastructure and building climate change monitoring and reporting stations.

Predicting Novel Riparian Ecosystems in a Changing Climate

Rapid changes in global climate are likely to alter species assemblages and environmental characteristics resulting in novel ecosystems. The ability to predict characteristics of future ecosystems is crucial for environmental planning and the development of effective climate change adaptation strategies. This paper presents an approach for envisioning novel ecosystems in future climates. Focusing on riparian ecosystems, we use qualitative process models to predict likely abiotic and biotic changes in four case study systems: tropical coastal floodplains, temperate streams, high mountain streams and urban riparian zones. We concentrate on functional groups rather than individual species and consider dispersal constraints and the capacity for genetic adaptation. Our scenarios suggest that climatic changes will reduce indigenous diversity, facilitate non-indigenous invasion (especially C4 graminoids), increase fragmentation and result in simplified and less distinctive riparian ecosystems. Compared to models based on biota-environment correlations, process models built on mechanistic understanding (like Bayesian belief networks) are more likely to remain valid under novel climatic conditions. We posit that predictions based on species’ functional traits will facilitate regional comparisons and can highlight effects of climate change on ecosystem structure and function. Ecosystems that have experienced similar modification to that expected under climate change (for example, altered flow regimes of regulated rivers) can be used to help inform and evaluate predictions. By manipulating attributes of these system models (for example, magnitude of climatic changes or adaptation strategies used), implications of various scenarios can be assessed and optimal management strategies identified.

Strategies for Reforestation under Uncertain Future Climates: Guidelines for Alberta, Canada

BackgroundCommercial forestry programs normally use locally collected seed for reforestation under the assumption that tree populations are optimally adapted to local environments. However, in western Canada this assumption is no longer valid because of climate trends that have occurred over the last several decades. The objective of this study is to show how we can arrive at reforestation recommendations with alternative species and genotypes that are viable under a majority of climate change scenarios.Methodology/Principal FindingsIn a case study for commercially important tree species of Alberta, we use an ecosystem-based bioclimate envelope modeling approach for western North America to project habitat for locally adapted populations of tree species using multi-model climate projections for the 2020s, 2050s and 2080s. We find that genotypes of species that are adapted to drier climatic conditions will be the preferred planting stock over much of the boreal forest that is commercially managed. Interestingly, no alternative species that are currently not present in Alberta can be recommended with any confidence. Finally, we observe large uncertainties in projections of suitable habitat that make reforestation planning beyond the 2050s difficult for most species.Conclusion/SignificanceMore than 50,000 hectares of forests are commercially planted every year in Alberta. Choosing alternative planting stock, suitable for expected future climates, could therefore offer an effective climate change adaptation strategy at little additional cost. Habitat projections for locally adapted tree populations under observed climate change conform well to projections for the 2020s, which suggests that it is a safe strategy to change current reforestation practices and adapt to new climatic realities through assisted migration prescriptions.

The Role of Spatial Risk Assessment in the Context of Planning for Adaptation in UK Urban Areas

There are many challenges to developing and delivering effective climate change adaptation strategies for urban areas. Some are associated with a lack of available tools to help understand the spatial and temporal dimensions of climate related problems, while others are associated with the limitations of existing structures and frameworks through which adaptation plans can be generated and delivered. The land-use planning system offers a number of options through which climate-related risks may be better managed, especially in urban areas. However, both land-use planning and the related process of urban design can just as easily adversely affect the nature and degree of impacts, effectively enhancing the impacts of climate change. The long-term nature of urbanization processes means that just like the climate system itself, the decisions that are taking place now will determine the response of the urban system in the future, making climate-conscious planning an urgent and important goal. This paper considers how a spatial risk assessment framework can help improve adaptation planning through providing relevant information to underpin the development of adaptation strategies related to land-use and spatial planning. The paper uses an example of adaptation to heat stress in a UK urban context (Greater Manchester) and shows how socio-economic as well as climate scenarios help to shape future patterns of risk. It ends with suggestions for how heat stress risk might be effectively tackled through considering existing policies which operate over conurbation as well as local scales.