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We present a thorough analysis of the scientific production in climate change and adaptation in Brazil. We conducted a bibliometric and bibliographic review to reveal and discuss how climate change research has been carried out. We compared a broader climate change research dataset with a more specific climate adaptation research dataset, to understand the main differences and convergence points, and how science conducted from a mitigation and adaptation perspective demonstrates potential to confront the climate change challenges and drivers in Brazil. Four main clusters of investigation within climate change were detected: (1) impacts on forest and plant development, (2) land use and ecology, (3) adaptation/governance, and (4) climate/atmospheric studies. Only about 5% of the total studies on climate change address adaptation, for which three main clusters of research were identified: (1) adaptation actions and policies; (2) urban environment, vulnerability, and health and (3) food and coastal impacts. Although there are strong research trends in climate change for the Amazon Forest, there was less evidence of studies concerning climate adaptation for this and other Brazilian biomes, smaller cities, rural and traditional communities, and poorer regions. Our results shed a light on the more commonly chosen research topics, their strongest points and potential gaps and trends. This can contribute to the scientific communication and implementation of climate actions in Brazil, and a better understanding of the climate science knowledge from the perspective of a middle-income country. [ABSTRACT FROM AUTHOR]

Researchers have long hypothesized linkages between climate change, food security, and migration in low- and middle-income countries (LMICs). One such hypothesis is the “agricultural pathway,” which postulates that negative climate change impacts on food production harm livelihoods, which triggers rural out-migration, internally or abroad. Migration is thus an adaptation to cope with the impacts of climate change and bolster livelihoods. Recent evidence suggests that the agriculture pathway is a plausible mechanism to explain climate-related migration. But direct causal connections from climate impacts on food production to livelihood loss to rural out-migration have yet to be fully established. To guide future research on the climate-food-migration nexus, we present a conceptual framework that outlines the components and linkages underpinning the agricultural pathway in LMICs. We build on established environmental-migration conceptual frameworks that have informed empirical research and deepened our understanding of complex human-environmental systems. First, we provide an overview of the conceptual framework and its connection to the agricultural pathway hypothesis in the climate mobility literature. We then outline the primary components and linkages of the conceptual framework as they pertain to LMIC contexts, highlighting current research gaps and challenges relating to the agricultural pathway. Last, we discuss possible future research directions for the climate-food-migration nexus. By highlighting the complex, multiscale, interconnected linkages that underpin the agricultural pathway, our framework unpacks the multiple causal connections that currently lie hidden in the agricultural pathway hypothesis. [ABSTRACT FROM AUTHOR]

The frequency of hot days in much of the world is increasing. What is the impact of high temperatures on productivity? Can technology-based adaptation mitigate such effects of climate change? We provide some answers to these questions by examining how high outdoor temperatures affect a high-technology, precision manufacturing setting. Exploiting individual-level data on the quantity and quality of work done across 35,190 worker-shifts in a leading NYSE-listed silicon wafer maker in China, we evidence a negative effect of outdoor heat on productivity. The effects are large: in our preferred linear specification, an increase in wet bulb temperature of 10 ∘ C causes a reduction in output of 8.3%. Temperature effects exist even though the manufacturer's work-spaces are indoors and protected by high-quality climate control systems. Results are not driven by extreme weather events and are robust to alternative modelling approaches. They illustrate the potential future adverse economic effects of climate change in most of the industrialised world. [ABSTRACT FROM AUTHOR]

The impacts of climate change on agricultural systems in West Africa have been analyzed extensively. However, few studies have focused on livestock systems. Using export data for the period 1996–2017 and climate data for two major cattle suppliers (Mali and Burkina Faso) and one net importer (Côte d’Ivoire) in West Africa, we estimated a gravity model of temperature and cattle trade. Our study provides findings on the impacts of climate change on cattle supply. Indeed, we found that climate shocks in some major Sahel cattle-exporting countries, i.e., Mali and Burkina Faso, can affect the supply of a coastal import country, such as Côte d’Ivoire. Specifically, the study supports findings that a temperature increase in the Sudanian region of the Sahel induces a significant decrease in cattle trade flows. We found, as an example, that a 0.3 °C global increase in temperature could decrease cattle trade flow by 25%, which could happen to exports in 10 years from 2020 in the moderate climate change scenario (RCP 4.5), and in 06 years in the pessimistic scenario (RCP 8.5) at horizon 2050. There is a 67% and 80% chance, respectively, that this will happen, based on the climate change scenario. Our results are of great interest to cattle systems because they partly demonstrate the result of inaction in the face of climate change in that economic sector. In fact, if nothing is set up, significant disruption to cattle trade flow from Sahelian countries, which is projected to occur in the near future, could weaken regional economic integration in addition to raising the risk of food insecurity. [ABSTRACT FROM AUTHOR]

Because there are limited locations where atmospheric mercury (Hg) measurements are made, a method is needed for characterizing air concentrations locally, regionally and globally. Research has shown growth rings of some tree species may be used as archives that record concentrations of gaseous elemental Hg. However, there are still questions regarding the most appropriate sampling method(s), which tree species to use, and the physiological factors that influence atmospheric Hg uptake and translocation to the rings. To address these questions, tree cores were collected from different tree species at two locations on the eastern side of the Sierra Nevada, California, USA. An assessment was made as to whether there was correlation of ring concentrations between co-located deciduous and coniferous trees, as well as between concentrations measured on the east versus west sides of individual trees, and whether tree ring Hg concentrations correlated with local climate, tree ring width, and total tree ring mass. Broadleaved and coniferous tree ring Hg concentrations were not correlated. Based on results obtained in this and other studies, Pinus species of relatively the same age are recommended for tree ring monitoring in the Western United States; however, the potential for radial translocation still needs to be assessed. Data collected from the two sites focused on were aligned with the overall regional trends in Hg concentrations established from previous studies. Climatic factors, including dew point, temperature, and relative humidity, were negatively correlated with ring Hg concentrations. Tree tissues are active samplers of atmospheric Hg, and are affected by climate and local growing conditions. [ABSTRACT FROM AUTHOR]

We parallelize the extended path method for solving rational expectations models, and apply it to compute perfect foresight competitive equilibrium for the global economy with multiple goods, regions, industries, and households. At each iteration, first intertemporal variables are updated, then equations for intra-temporal variables are solved in parallel. We compare serial, and parallel, versions of the extended path method in high-performance computing environments based on scenarios with long time horizons that include future populations, economic growth, energy use, and carbon dioxide emissions. Relative to the serial version, the speedup factor for the parallel extended path method grows almost linearly up to about 30 times with 18 cores, and computing times reduced from over 10 h for the serial version down to about 20 min for the parallel version. [ABSTRACT FROM AUTHOR]

High impact weather events such as extreme temperatures or rainfall can cause significant disruption across the UK affecting sectors such as health, transport, agriculture and energy. In this study we draw on the latest set of UK climate projections, UKCP, to examine metrics relating to high-impact weather over the UK and how these change with different levels of future global warming from 1.5 °C to 4 °C above pre-industrial. The changes to these hazards show increases in the frequency of extremely hot days and nights, with a UK average increase in hot days of between 5 and 39 days per year between 1.5 °C and 4 °C of global warming. Projections indicate an increase in cooling degree days of 134–627% and an increase in growing degree days of 19–60% between 1.5 °C and 4 °C of global warming. Extremely hot nights, which are currently rare, are emerging as more common occurrences. The frequency of high daily temperatures and rainfall increase systematically, while the frequency of very cold conditions (based on days where temperatures fall below 0 °C) is shown to decrease by 10 to 49 days per year. A reduction in heating degree days, of 11–32% between 1.5 °C and 4 °C of warming, is projected. Levels of daily rainfall, which currently relate to increased risk of river flooding, are shown to increase across the country, with increases of days with high impact levels of rainfall occurring by 1 to 8 days per year between 1.5 °C and 4 °C of warming. Average drought severity is projected to increase for 3-, 6-, 12- and 36-month-long droughts. The largest changes in the severity of the 12-month drought are between −3 and +19% between 1.5 °C and 4 °C of warming and for 36-month drought between −2 and +54% between 1.5 °C and 4 °C of warming. The projected future changes in high impact weather from this study will enable the characterization of climate risks and ultimately be able to better inform adaptation planning in different sectors to support the increase in resilience of the UK to future climate variability and change. [ABSTRACT FROM AUTHOR]

There is increasing concern among financial regulators that changes in the distribution and frequency of extreme weather events induced by climate change could pose a threat to global financial stability. We assess this risk, for the case of floods, by developing a simple model of the propagation of climate-induced shocks through financial networks. We show that the magnitude of global risks is determined by the interplay between the exposure of countries to climate-related natural hazards and their financial leverage. Climate change induces a shift in the distribution of impacts towards high-income countries and thus larger amplification of impacts as the financial sectors of high-income countries are more leveraged. Conversely, high-income countries are more exposed to financial shocks. In high-end climate scenarios, this could lead to the emergence of systemic risk as total impacts become commensurate with the capital of the banking sectors of countries that are hubs of the global financial network. Adaptation policy, or the lack thereof, appears to be one of the key risk drivers as it determines the future exposure of high-income countries. This implies in particular that the avoided costs in terms of financial stability should be weighted in as benefits of adaptation policy. [ABSTRACT FROM AUTHOR]

Printed and hybrid integrated electronics produced from recycled and renewable materials can reduce the depletion of limited material resources while obtaining energy savings in small electronic applications and their energy storage. In this work, bio-based poly(lactic acid) (PLA) and recycled polyethylene terephthalate (rPET) were fabricated in film extrusion process and utilized as a substrate in ultra-thin organic photovoltaics (OPV). In the device structure, metals and metal oxides were replaced by printing PEDOT:PSS, carbon and amino acid/heterocycles. Scalable, energy-efficient fabrication of solar cells resulted in efficiencies up to 6.9% under indoor light. Furthermore, virgin-PET was replaced with PLA and rPET in printed and hybrid integrated electronics where surface-mount devices (SMD) were die-bonded onto silver-printed PLA and virgin-PET films to prepare LED foils followed by an overmoulding process using the rPET and PLA. As a result, higher relative adhesion of PLA-PLA interface was obtained in comparison with rPET-PET interface. The obtained results are encouraging from the point of utilization of scalable manufacturing technologies and natural/recycled materials in printed and hybrid integrated electronics. Assessment showed a considerable decrease in carbon footprint, about 10–85%, mainly achieved through replacing of silver, virgin-PET and modifying solar cell structure. In outdoor light, the materials with low carbon footprint can decrease energy payback times (EPBT) from ca. 250 days to under 10 days. In indoor energy harvesting, it is possible to achieve EPBT of less than 1 year. The structures produced and studied herein have a high potential of providing sustainable energy solutions for example in IoT-related technologies. [ABSTRACT FROM AUTHOR]

Climate change is a serious threat to agriculture and food security. The development of adaptation measures is one of the key strategies to offset the climate change impacts on rice crop. A study was planned to develop adaptation strategies for future rice crop through simulation model. This study was consisted of six transplanting dates and three seedling densities which were tested to develop adaptations at three locations, i.e., Faisalabad, Hafizabad, and Gujranwala during the years 2015 and 2016. Climate change scenarios were developed for selected locations through statistical downscaling by selecting five general circulation models under representative concentration pathways (RCPs 8.5) for mid-century (2039–2069). The APSIM-ORYZA model was calibrated well with experimental data which showed an error of 2.35% between observed and simulated grain yield. The impact of climate change was studied by calculating the difference of baseline (1980–2010) and future yield. Model simulated results indicated that the rise in temperature will reduce the rice yield by 7.3%. To overcome this decrease in rice yield, suitable adaptation strategies were tested for mid-century. The developed adaptations, i.e., increased in plant population, nitrogen amount, and early transplanting, improved the rice yield by 8.7% under RCPs 8.5 for mid-century scenarios. Overall, this study provide better understanding of the adaptation processes for sustainable rice yield under anticipated future climate change. [ABSTRACT FROM AUTHOR]

British pre-industrial economic growth has traditionally been analysed from the Malthusian point of view and other more optimistic approaches, but in many cases, ignoring environmental factors. This article explores the inclusion of the climate in this general debate, focusing on one of the colder periods of the last 500 years, known as the Maunder Minimum. The provisional results suggest that climate change and the resulting adaptations may have influenced the start of the English Agricultural Revolution, the Energy Transition and the European Divergence. However, from an econometric point of view these results are not fully conclusive, making it necessary to continue working with better primary sources and other alternative methodologies. [ABSTRACT FROM AUTHOR]

Berry-producing plants are a key subsistence resource in Indigenous Alaskan communities. Coastal, high-latitude regions are particularly impacted by global climate change because their location at the land-sea ecotone subjects them to both terrestrial stressors and shifting ocean dynamics. Although changes in near-shore vegetation communities have been previously documented for the sub-Arctic coastal region of Alaska, we know little about vegetation dynamics in the permafrost-underlain portions of the landscape that support berry communities. To fill this gap, surveys were administered in four communities within the Yukon-Kuskokwim Delta to identify observations of changes in berry resources and integrate Indigenous Knowledge of drivers of changes with climate projections. We found that while many participants identified changes in berry phenology, abundance, and habitat related to climate drivers, important differences in responses were identified at the community level. Regional consensus can be used in combination with climate projections to forecast potential future impacts to berry resources, while distinctions at the community level can help to account for impacts of local scale disturbances and importance of social context. [ABSTRACT FROM AUTHOR]

Climate change is significantly affecting agriculture and food security. Variations in temperature and uncertainties in rainfall patterns negatively affect the yield of crops. Crop models have been widely used in assessing the impact of climate change on agricultural crops. The study was planned to evaluate the potential impacts of climate change on wheat yield in different agro-ecological zones of Khyber Pakhtunkhwa (KPK), Pakistan. The CERES-Wheat model was calibrated and evaluated with the experimental dataset. The survey data of 50 farms were collected from the study districts Chitral, Dera Ismail (D.I.) Khan, and Peshawar. Climate change scenarios were generated on the basis of five selected general circulation models (GCMs) under representative concentration pathways (RCPs 4.5 and 8.5) for mid-century (2040–2069). Model was calibrated well and showed a close agreement between observed and simulated values of grain yield with root mean square error (RMSE) ranging from 25 to 55 kg ha−1 for three cultivars, i.e., Faisalabad-2008, Galaxy-2013, and PirSabak-2013. Climate projections showed that there would be increases in Tmax of 2.33 °C and 2.93 °C and Tmin of 2.16 °C and 3.13 °C under RCPs 4.5 and 8.5 respectively. Climate change impacts showed that wheat yield will increase by 10% in RCP 4.5 and 14% in RCP 8.5 at Chitral, while yield will be reduced by 7.9% in RCP 4.5 and 11% in RCP 8.5 in D.I. Khan. The yield will also be reduced at Peshawar by 5.5% in RCP 4.5 and 8.4% in RCP 8.5. [ABSTRACT FROM AUTHOR]

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The extreme temperatures and uneven distribution of rainfall associated with climate change are expected to affect agricultural productivity and food security. A study was conducted to evaluate the impact of climate change on wheat in southeastern regions of Turkey. The CERES-wheat crop simulation model was calibrated and evaluated with data from eight surveyed farms. The four farms were used for calibration and four for evaluation. Climate change scenarios were developed for the middle (2036–2065) and late 21st century (2066–2095) under representative concentration pathways (RCPs 4.5 and 8.5) for study sites in Islahiye and Nurdagi. Model calibration results showed a good agreement between observed and simulated yield with only a 1 to 11% range of error. The model evaluation results showed good fit between observed and simulated values of all parameters with % error ranged from 0.51 to 13.3%. Future climate change projections showed that maximum temperature (Tmax) will increase between 1.6 °C (RCP4.5) and 2.3 °C (RCP8.5), while minimum temperature (Tmin) will increase between 1.0 °C (RCP4.5) and 1.5 °C (RCP8.5) for mid-century. At the end of the century, Tmax is projected to increase from 2 °C (RCP4.5) to 4 °C (RCP8.5) and Tmin from 1.3 °C (RCP4.5) to 3.1 °C (RCP8.5). Climate change impacts results showed that future rise in temperature will reduce wheat yield by 16.3% in mid-century and 16.8% at the end of the century at Islahiye and for Nurdagi, while 13.0% in mid and 14.4% end of the century. The use of climate and crop modeling technique provides useful information in evaluating the climate change impacts and may assist stakeholders to make decisions to overcome the negative impacts in the near and long term. [ABSTRACT FROM AUTHOR]

The South American silver croaker is a popular fish that has recently received substantial attention from scientists, mainly due to its importance as source of animal protein and as a key fisheries species. However, little is known about the conditions that explain its historical and current spatial distribution, both in its native habitat and where it is a successful invasive species. The aim of the present study was to explore the ecological information available for this species, to then critically examine ecological theories related to the conditions underpinning its success. To this end, an exhaustive literature search was conducted with the immediate aim of investigating whether the success of South American silver croaker was driven by species-climate or species-human interactions. The non-native populations were found to occupy climate niche spaces different from those observed in their native ranges. In addition, it was clear that humans played a role in facilitating the large-scale dispersion of silver croaker, and assisted as agents of impact driving the observed current and, probably, the future spatial distribution, which we can predict from our data and from the pattern of propagule pressure. Overall, the current biogeography of this species illustrates how the construction of dams, along with the introduction and stocking of non-native species, overfishing and other human activities can alter fish populations and assemblages. Such processes can reduce native species, increase the abundance and distribution of invasive species, as well as cause changes in life-history traits and genetic variability, all with long-term socioeconomic consequences. [ABSTRACT FROM AUTHOR]

A primary goal of studying climate change adaptation is to identify the adaptation options that are used to improve crop productivity or reduce the negative impacts of climate change. Many of the adjustments in farm management that farmers adopt do not necessarily represent true adaptations to climate change, an issue often ignored in existing literature and resulting in a risk that policy makers are misled to think that adaptation is easier than it actually is, and thereby underestimate the challenge that climate change presents. The overall goal of this study is to identify whether farmers’ adoptions are enhancing food production and adapting to climate change. The identification uses a plot-level panel from a survey of 619 rural households in three provinces in China and county-level weather data. With the use of plot and county-by-year fixed effects as well as instrumental variable approaches, our estimates show that the autonomous adoptions are not effective in improving crop yields. This implies that farmers’ adoptions cannot be always considered adaptations to climate change. The paper provides a possible explanation for the results and concludes with policy implications. [ABSTRACT FROM AUTHOR]

Irrigation-based agriculture constitutes an essential factor for food security as well as fresh water resources and has a distinct impact on regional and global climate. Many issues related to irrigation’s climate impact are addressed in studies that apply a wide range of models. These involve substantial uncertainties related to differences in the model’s structure and its parametrizations on the one hand and the need for simplifying assumptions for the representation of irrigation on the other hand. To address these uncertainties, we used the Max Planck Institute for Meteorology’s Earth System model into which a simple irrigation scheme was implemented. In order to estimate possible uncertainties with regard to the model’s more general structure, we compared the climate impact of irrigation between three simulations that use different schemes for the land-surface-atmosphere coupling. Here, it can be shown that the choice of coupling scheme does not only affect the magnitude of possible impacts but even their direction. For example, when using a scheme that does not explicitly resolve spatial subgrid scale heterogeneity at the surface, irrigation reduces the atmospheric water content, even in heavily irrigated regions. Contrarily, in simulations that use a coupling scheme that resolves heterogeneity at the surface or even within the lowest layers of the atmosphere, irrigation increases the average atmospheric specific humidity. A second experiment targeted possible uncertainties related to the representation of irrigation characteristics. Here, in four simulations the irrigation effectiveness (controlled by the target soil moisture and the non-vegetated fraction of the grid box that receives irrigation) and the timing of delivery were varied. The second experiment shows that uncertainties related to the modelled irrigation characteristics, especially the irrigation effectiveness, are also substantial. In general the impact of irrigation on the state of the land surface is more than three times larger when assuming a low irrigation effectiveness than when a high effectiveness is assumed. For certain variables, such as the vertically integrated water vapour, the impact is almost an order of magnitude larger. The timing of irrigation also has non-negligible effects on the simulated climate impacts and it can strongly alter their seasonality. [ABSTRACT FROM AUTHOR]

The features of changes and variability for cold temperature extremes over Russia are analyzed using observational data for the period from the middle of the 20th century. The impact is assessed that observed changes in thermal regime make on the characteristics of rare extremes which are used as standard parameters for designing infrastructure facilities. The results are interpreted in terms of the power system operation reliability. The risk assessment for critical temperature impacts indicates the important regional features of climate change effect on extreme energy loads and requirements for power capacities during the cold season. [ABSTRACT FROM AUTHOR]

El Niño Modoki events can be further classified into El Niño Modoki I and II in terms of their opposite impacts on southern China rainfall (Wang and Wang, J Clim 26:1322-1338, 2013) and the Indian Ocean dipole mode (Wang and Wang, Clim Dyn 42:991-1005, 2014). The present paper develops an index to identify the types of El Niño events. The El Niño Modoki II (MII) index is defined as the leading principle component of multivariate empirical orthogonal function analysis of the normalized El Niño Modoki index, Niño4 index and 850 hPa relative vorticity anomalies averaged near the Philippine Sea during autumn. The MII index exhibits dominant variations on interannual (2-3 and 4-5 years) and decadal (10-20 years) timescales. El Niño Modoki II events can be well identified by using the MII index value being larger than 1 standard deviation. Further analyses and numerical model experiments confirm that the MII index can portray the major oceanic and atmospheric features of El Niño Modoki II events. The constructed MII index along with previous ENSO indices can be used for classifying and identifying all types of El Niño events. Because of distinct impacts induced by different types of El Niño events, the implication of the present study is that climate prediction and future climate projection under global warming can be improved by using the MII index and other indices to identify the types of El Niño events. [ABSTRACT FROM AUTHOR]

Strategies to manage the risks posed by future sea-level rise hinge on a sound characterization of the inherent uncertainties. One of the major uncertainties is the possible rapid disintegration of large fractions of the Antarctic ice sheet in response to rising global temperatures. This could potentially lead to several meters of sea-level rise during the next few centuries. Previous studies have typically been silent on two coupled questions: (i) What are probabilistic estimates of this 'fast dynamic' contribution to sea-level rise? (ii) What are the implications for strategies to manage coastal flooding risks? Here, we present probabilistic hindcasts and projections of sea-level rise to 2100. The fast dynamic mechanism is approximated by a simple parameterization, designed to allow for a careful quantification of the uncertainty in its contribution to sea-level rise. We estimate that global temperature increases ranging from 1.9 to 3.1 °C coincide with fast Antarctic disintegration, and these contributions account for sea-level rise of 21-74 cm this century (5-95% range, Representative Concentration Pathway 8.5). We use a simple cost-benefit analysis of coastal defense to demonstrate in a didactic exercise how neglecting this mechanism and associated uncertainty can (i) lead to strategies which fall sizably short of protection targets and (ii) increase the expected net costs. [ABSTRACT FROM AUTHOR]

This paper reviews the current knowledge of climatic risks and impacts in South Asia associated with anthropogenic warming levels of 1.5-4 °C above pre-industrial values in the twenty-first century. It is based on the World Bank Report 'Turn Down the Heat, Climate Extremes, Regional Impacts and the Case for Resilience' (2013b) . Many of the climate change impacts in the region, which appear quite severe even with relatively modest warming of 1.5-2 °C, pose significant hazards to development. For example, increased monsoon variability and loss or glacial meltwater will likely confront populations with ongoing and multiple challenges. The result is a significant risk to stable and reliable water resources for the region, with increases in peak flows potentially causing floods and dry season flow reductions threatening agriculture. Irrespective of the anticipated economic development and growth, climate projections indicate that large parts of South Asia's growing population and especially the poor are likely to remain highly vulnerable to climate change. [ABSTRACT FROM AUTHOR]

We present the Representative Temperature and Precipitation (T&P) GCM Subsetting Approach developed within the Agricultural Model Intercomparison and Improvement Project (AgMIP) to select a practical subset of global climate models (GCMs) for regional integrated assessment of climate impacts when resource limitations do not permit the full ensemble of GCMs to be evaluated given the need to also focus on impacts sector and economics models. Subsetting inherently leads to a loss of information but can free up resources to explore important uncertainties in the integrated assessment that would otherwise be prohibitive. The Representative T&P GCM Subsetting Approach identifies five individual GCMs that capture a profile of the full ensemble of temperature and precipitation change within the growing season while maintaining information about the probability that basic classes of climate changes (relatively cool/wet, cool/dry, middle, hot/wet, and hot/dry) are projected in the full GCM ensemble. We demonstrate the selection methodology for maize impacts in Ames, Iowa, and discuss limitations and situations when additional information may be required to select representative GCMs. We then classify 29 GCMs over all land areas to identify regions and seasons with characteristic diagonal skewness related to surface moisture as well as extreme skewness connected to snow-albedo feedbacks and GCM uncertainty. Finally, we employ this basic approach to recognize that GCM projections demonstrate coherence across space, time, and greenhouse gas concentration pathway. The Representative T&P GCM Subsetting Approach provides a quantitative basis for the determination of useful GCM subsets, provides a practical and coherent approach where previous assessments selected solely on availability of scenarios, and may be extended for application to a range of scales and sectoral impacts. [ABSTRACT FROM AUTHOR]

This paper offers a Foucauldian critique of climate change research in Zimbabwe. Indeed, climate change is arguably one of the most pressing challenges confronting this developing nation. As such, it has received considerable attention from a wide array of scholars. Certainly, very significant contributions have come from scholars who have deployed various models to establish trends in climate change as well as assess and predict its impacts particularly on agriculture. However, questions on how climate change is framed, how impacts are derived using various quantitative methods and models and even the language used in such studies have not been sufficiently debated. These questions emerge especially because of the numerous problematic dimensions that have been perpetuated in literature. Noticeable is that the conceptualisation of climate change is science driven and predominantly climate change is projected on a national scale and as a national and quantifiable phenomenon in mainstream academic and policy discourses. Similarly, understanding local level impacts using farmers' perspectives is still not widely appreciated in the country. As such, there is no unified body of knowledge that considers discourses of local farmers in rural Zimbabwe to understand climate change and its impacts. This can be a fundamentally flawed trajectory that can perpetuate a seemingly universal and hegemonic discourse on climate change. This is neither desirable nor productive for the development of climate change knowledge as well as sustainable and inclusive adaptation policies and pathways in the country. [ABSTRACT FROM AUTHOR]

This study focuses on the climatic impacts of the Atlantic Multidecadal Oscillation (AMO) as a mode of internal variability. Given the difficulties involved in excluding the effects of external forcing from internal variation, i.e., owing to the short record length of instrumental observations and historical simulations, we assess and compare the AMO and its related climatic impacts both in observations and in the 'Pre-industrial' experiments of models participating in CMIP5. First, we evaluate the skill of the 25 CMIP5 models' 'Historical' simulations in simulating the observational AMO, and find there is generally a considerable range of skill among them in this regard. Six of the models with higher skill relative to the other models are selected to investigate the AMO-related climate impacts, and it is found that their 'Pre-industrial' simulations capture the essential features of the AMO. A positive AMO favors warmer surface temperature around the North Atlantic, and the Atlantic ITCZ shifts northward leading to more rainfall in the Sahel and less rainfall in Brazil. Furthermore, the results confirm the existence of a teleconnection between the AMO and East Asian surface temperature, as well as the late withdrawal of the Indian summer monsoon, during positive AMO phases. These connections could be mainly caused by internal climate variability. Opposite patterns are true for the negative phase of the AMO. [ABSTRACT FROM AUTHOR]

The Zambezi River Basin in southern Africa is relatively undeveloped from both a hydropower and irrigated agriculture perspective, despite the existence of the large Kariba and Cahora Bassa dams. Accelerating economic growth increases the potential for competition for water between hydropower and irrigated agriculture, and climate change will add additional stresses to this system. The objective of this study was to assess the vulnerability of major existing and planned new hydropower plants to changes in climate and upstream irrigation demand. Our results show that Kariba is highly vulnerable to a drying climate, potentially reducing average electricity generation by 12 %. Furthermore, the expansion of Kariba generating capacity is unlikely to deliver the expected increases in production even under a favourable climate. The planned Batoka Gorge plant may also not be able to reach the anticipated production levels from the original feasibility study. Cahora Bassa's expansion is viable under a wetting climate, but its potential is less likely to be realised under a drying climate. The planned Mphanda Nkuwa plant can reach expected production levels under both climates if hydropower is given water allocation priority, but not if irrigation is prioritised, which is likely. For both Cahora Bassa and Mphanda Nkuwa, prioritising irrigation demand over hydropower could severely compromise these plants' output. Therefore, while climate change is the most important overall driver of variation in hydropower potential, increased irrigation demand will also have a major negative impact on downstream plants in Mozambique. This implies that climate change and upstream development must be explicitly incorporated into both project and system expansion planning. [ABSTRACT FROM AUTHOR]

This paper investigates historical growth and climate records among the oak sites representing the northern edge of species range in northernmost Europe (Finland). This is to characterize plant-climate interactions for a multitude of sites where oak decline has recently been observed and understand this most recent decline in the context of the past decline studies elsewhere. Further, our paper demonstrates the procedures the tree-ring data can be used in isolating those factors significantly contributing to decline. Our findings point towards complex tree mortality dynamics. Compared to oaks that remain healthy, the declining and dead oaks represent the trees clearly having suffered from competition and edaphic position within their site. This was indicated by their reduced growth rates and more drastic growth disturbance, with indications of reduced resilience. Growth of these trees was also deteriorated by cold soil temperatures during the dormancy in addition to summer droughts. By contrast, the growth of healthy oaks has been notably ameliorated by springtime soil warming over the past decades. The results demonstrate the climatic determinants for observed decline in the northern oak sites, which may become increasingly vulnerable to higher background tree mortality rates and die-off in response to future warming and drought, although their habitats are not normally considered water-limited. [ABSTRACT FROM AUTHOR]

Statistical downscaling (SD) methods have become a popular, low-cost and accessible means of bridging the gap between the coarse spatial resolution at which climate models output climate scenarios and the finer spatial scale at which impact modellers require these scenarios, with various different SD techniques used for a wide range of applications across the world. This paper compares the Generator for Point Climate Change (GPCC) model and the Statistical DownScaling Model (SDSM)-two contrasting SD methods-in terms of their ability to generate precipitation series under non-stationary conditions across ten contrasting global climates. The mean, maximum and a selection of distribution statistics as well as the cumulative frequencies of dry and wet spells for four different temporal resolutions were compared between the models and the observed series for a validation period. Results indicate that both methods can generate daily precipitation series that generally closely mirror observed series for a wide range of non-stationary climates. However, GPCC tends to overestimate higher precipitation amounts, whilst SDSM tends to underestimate these. This infers that GPCC is more likely to overestimate the effects of precipitation on a given impact sector, whilst SDSM is likely to underestimate the effects. GPCC performs better than SDSM in reproducing wet and dry day frequency, which is a key advantage for many impact sectors. Overall, the mixed performance of the two methods illustrates the importance of users performing a thorough validation in order to determine the influence of simulated precipitation on their chosen impact sector. [ABSTRACT FROM AUTHOR]

The eastern United States is vulnerable to flooding from tropical cyclone rainfall. Understanding how both the frequency and intensity of this rainfall will change in the future climate is a major challenge. One promising approach is the dynamical downscaling of relatively coarse general circulation model results using higher-resolution regional climate models (RCMs). In this paper, we examine the frequency of landfalling tropical cyclones and associated rainfall properties over the eastern United States using Zetac, an 18-km resolution RCM designed for modeling Atlantic tropical cyclone activity. Simulations of 1980-2006 tropical cyclone frequency and rainfall intensity for the months of August-October are compared against results from previous studies and observation-based datasets. The 1980-2006 control simulations are then compared against results from three future climate scenarios: CMIP3/A1B (late twenty-first century) and CMIP5/RCP4.5 (early and late twenty-first century). In CMIP5 early and late twenty-first century projections, the frequency of occurrence of post-landfall tropical cyclones shows little net change over much of the eastern U.S. despite a decrease in frequency over the ocean. This reflects a greater landfalling fraction in CMIP5 projections, which is not seen in CMIP3-based projections. Average tropical cyclone rain rates over land within 500 km of the storm center increase by 8-17 % in the future climate projections relative to control. This is at least as much as expected from the Clausius-Clapeyron relation, which links a warmer atmosphere to greater atmospheric water vapor content. Over land, the percent enhancement of area-averaged rain rates from a given tropical cyclone in the warmer climate is greater for larger averaging radius (300-500 km) than near the storm, particularly for the CMIP3 projections. Although this study does not focus on attribution, the findings are broadly consistent with historical tropical cyclone rainfall changes documented in a recent observational study. The results may have important implications for future flood risks from tropical cyclones. [ABSTRACT FROM AUTHOR]

How anthropogenic and climatic effects impact on species has arisen as one of the most fundamental questions in conservation biology today. We hypothesised that human land use patterns in an agricultural matrix would influence habitat selection in badgers and, further, that seasonal and climatic factors would also have an impact. Here, using both radiotelemetry and direct observations, we clearly define badger foraging ranges and show that at the landscape and home range level, our study badgers selected pasture fields and marginal habitat such as hedgerows, whilst avoiding arable land. Both sexes tended to travel over 2 km/night, with males consistently travelling further than females. We found not only considerable overlap in the foraging and even core ranges of badgers from the same sett, but also surprising foraging range overlap between males of different setts. In terms of the nightly distance travelled during foraging forays, greater arable coverage did not force badgers to travel further, and of the climatic variables examined, only rainfall had a moderate but not significant effect. Our findings suggest a high degree of social fluidity in this study population, which may have consequences for bovine tuberculosis ( Mycobacterium bovis) transmission. [ABSTRACT FROM AUTHOR]

The paper presents a model-based approach describing the impacts of climate change on the European energy system. Existing analyses only estimate a limited range of climate impacts over a limited geographical area. Using the POLES model and the results from several climate models, the present paper quantifies the main impacts of climate change on the European energy sector, country by country, thus achieving progress in this direction. As far as energy demand is concerned, our main finding is that higher temperatures will mean that air-conditioning will consume more energy, reaching about 53 Mtoe by 2100 in a scenario with no strong emissions constraints (A1B). On the other hand, less energy will be consumed for heating buildings, falling by about 65 Mtoe per year. This represents a net decrease in energy consumption of about 12 Mtoe by 2100. On the supply side, more constrained and expensive operating conditions for electric power plants will result in lower electricity generation by thermal, nuclear and hydro-power plants, with a maximum decrease of about 200 TWh in 2070 in the A1B scenario and 150 TWh in 2060 and 2080 for a low emissions scenario (E1). These effects vary a great deal across Europe and remain very dependent on the uncertainties affecting the results of the various climate models. This overall uncertainty may inhibit effective decisions. However, the study offers insights not otherwise available without the full coverage of the energy system provided by POLES and climate features provided by climate models. The study identifies the main impacts of climate change in a strategic sector and provides an 'order of magnitude' or 'central trend' for these impacts, which might be useful in an adaptive policy of act, learn and then act again. [ABSTRACT FROM AUTHOR]

There is a paucity of research that evaluates climate change adaptation actions. Academics partnered with the City of Prince George, in Northern British Columbia, Canada, for over five years to explore and address adaptation. After an adaptation strategy was created, eight initiatives oriented towards implementation were pursued. These initiatives focused on incorporating adaptation into local plans, and in-depth explorations of impacts related to forests, river flooding and effects to transportation infrastructure. This article summarizes the initiatives pursued and assesses their effectiveness through semi-structured interviews with local planners, engineers, managers, community champions and politicians. The initiatives deemed to be most successful-and most likely to continue after the project has ended-focus on topics that: are of high public concern; have clear cost implications; incorporate adaptation into policy; and/or promote tangible outcomes. Results highlight both benefits and drawbacks associated with 'mainstreaming' adaptation into existing plans and strategies, and the importance of building and maintaining internal capacity. [ABSTRACT FROM AUTHOR]

Feeding the world's population while ensuring environmental sustainability is one of the world's 'grand challenges'. While population and income will remain the most important drivers of global food production, their relative importance will be reversed by 2050, with income growth becoming the dominant force. Energy prices are a wildcard, with continued low prices dampening demand for biofuels and encouraging intensification of production. In contrast, a return to high oil prices could greatly increase pressure to expand cropland. Regional water shortages are likely to constrain irrigated agriculture in many key river basins. However, at global scale, international trade will moderate the impacts of water scarcity on food supplies and prices. The key determinant of global food prices in 2050 will be the rate of overall technological progress in agriculture. Here, there are two competing views of the world. Pessimists point to the slowing rate of yield growth in many key breadbaskets, suggesting this will be exacerbated by climate change. In contrast, optimists argue that overall productivity growth has continued to rise - fueled by record public R&D investments in China, India and Brazil, as well as by the private sector. Reduced food waste and post-harvest losses offers another potential source of food supply. However, future agricultural land use is likely to face increasing competition from environmental services, including carbon sequestration and biodiversity. Understanding these competing demands for global resources will require greater inter-disciplinary research effort, supported by improved global geospatial data and analytical frameworks. [ABSTRACT FROM AUTHOR]

The present work identifies two types of La Niña based on the spatial distribution of sea surface temperature (SST) anomaly. In contrast to the eastern Pacific (EP) La Niña event, a new type of La Niña (central Pacific, or CP La Niña) is featured by the SST cooling center over the CP. These two types of La Niña exhibit a fundamental difference in SST anomaly evolution: the EP La Niña shows a westward propagation feature while the CP La Niña exhibits a standing feature over the CP. The two types of La Niña can give rise to a significantly different teleconnection around the globe. As a response to the EP La Niña, the North Atlantic (NA)-Western European (WE) region experiences the atmospheric anomaly resembling a negative North Atlantic Oscillation (NAO) pattern accompanied by a weakening Atlantic jet. It leads to a cooler and drier than normal winter over Western Europe. However, the CP La Niña has a roughly opposing impact on the NA-WE climate. A positive NAO-like climate anomaly is observed with a strengthening Atlantic jet, and there appears a warmer and wetter than normal winter over Western Europe. Modeling experiments indicate that the above contrasting atmospheric anomalies are mainly attributed to the different SST cooling patterns for the two types of La Niña. Mixing up their signals would lead to difficulty in seasonal prediction of regional climate. Since the La Niña-related SST anomaly is clearly observed during the developing autumn, the associated winter climate anomalies over Western Europe could be predicted a season in advance. [ABSTRACT FROM AUTHOR]

Climate is a major driver of agricultural production potentials. To make the best use of these potentials, agricultural management should be adjusted to local climatic conditions. As these conditions change over time, understanding climatic limitations and their trends in time and space is essential for the planning of suitable adaptation measures. In this study, we provide a detailed spatio-temporal analysis of climatic yield potentials for grain maize and winter wheat in Switzerland. We find that current climatic suitability for grain maize is mostly limited by sub-optimal temperatures, radiation and water scarcity, while climatic suitability for winter wheat is mostly limited through excess water, insufficient radiation, as well as frost and heat stress. Over the investigated period from 1983 to 2010, few regional trends in climate suitability were identified for the two crops, indicating that grain maize has benefitted slightly from increasing growth temperatures with recent warming (0.5 °C/decade), while winter wheat suitability decreased slightly due to suboptimal radiation/temperature ratios with warming. Despite only small trends in climate suitabilities, which are restricted to particular regions, future climatic changes could lead to more pronounced shifts. The tendencies of climate limitations identified in this study are mostly consistent with findings from other studies, and it can thus be anticipated that maize may continue to benefit from increasing temperatures on the short term, but may also be increasingly limited by water scarcity as summer precipitation decreases. For winter wheat, the relevance of heat stress is likely to increase with increasing temperatures. These results may help to support short-term adaptation planning. However, more detailed analyses of climate projections will be necessary to investigate 'critical transitions' and provide more specific information to support long-term climate change adaptation planning (e.g. for irrigation and breeding programmes). [ABSTRACT FROM AUTHOR]

With record breaking heat waves, dryness, and floods in several parts of the world in recent years the question arises whether and to what extent the hazard of hydrometeorological extreme weather events has changed, and if changes can be attributed to specific causes. The methodology of probabilistic event attribution allows to evaluate such potential changes in the occurence probabilities of particular types of extreme events. We show that such a probabilistic assessment not only provides information on changing hazards in hydrometerological events but also permits statements about multivariate combinations of hydrometeorological variables. Hence attribution studies could be targeted specifically towards relevant impacts in particular sectors, if different suitable multivariate proxies are used. We demonstrate our methodology by using combinations of temperature, precipitation and humidity in the large ensemble of climate simulations within the weather@home project in order to derive impact-relevant quantities such as a seasonal water balance and heat stress imposed on the human body. Finally, we estimate the hazard probabilities of those events in South-East Europe, a region that has recently experienced severe summer dryness (2012) in combination with multiple heat waves. [ABSTRACT FROM AUTHOR]

There is a growing availability of climate change information, offered to scientists and policy makers through climate services. However, climate services are not well taken up by the policy-making and planning community. Climate services focus on primary impacts of climate change, e.g., the disclosure of precipitation and temperature data, and this seems insufficient in meeting their needs. In this paper, we argue that, in order to reach the spatial planning community, climate services should take on a wider perspective by translating climate data to policy-relevant indicators and by offering support in the design of adaptation strategies. We argue there should be more focus on translating consequences of climate change to land-use claims and subsequently discuss the validity, consequences and implications of these claims with stakeholders, so they can play a role in spatial planning processes where much of the climate adaptation takes place. The term Climate Adaptation Services is introduced as being a stepwise approach supporting the assessment of vulnerability in a wider perspective and include the design and appraisal of adaptation strategies in a multi-stakeholder setting. We developed the Climate Adaptation Atlas and the Climate Ateliers as tools within the Climate Adaptation Services approach to support decision-making and planning processes. In this paper, we describe the different steps of our approach and report how some of the challenges were addressed. [ABSTRACT FROM AUTHOR]

Closing the gap between the health and well-being status of Indigenous people living in remote areas of northern Australia and non-Indigenous Australians has long been a major target of federal health policy. With climate projections suggesting large increases in hot spells in desert regions and more extremes in rainfall in other areas of the north, direct and indirect impacts resulting from these changes are likely to further entrench this health and well-being disparity. This paper argues that it is time to explicitly draw on Indigenous definitions of health, which directly address the need to connect individual and community health to the health of their country, in order to develop effective climate adaptation and health strategies. We detail how current health policies overlook this 'missing' dimension of Indigenous connection to country, and why that is likely to be detrimental to the health and well-being of people living in remote communities in a climate-changed future. [ABSTRACT FROM AUTHOR]

Apple farmers in Kazuno, northern Japan, have started to grow peaches in the northernmost climatic region suitable for peach farming. Here, we investigate the process from the initial introduction of peach cultivation to its diffusion focusing on the farmers’ perceptions of climatic and non-climatic stimuli and their actions to respond to these stressors. Interviews with the farmers identified three distinct groups. Four farmers (Group 1) initiated the transition to peach production, which then spread to other farmers (Group 2) via personal connections. Later, after the provision of various means of support from the local government and the producers’ cooperative, many more apple farmers (Group 3) decided to begin peach production. Most farmers recognized the risk of damages to apple production as a result of typhoons and drought. However, only Group 1 farmers, who depend on direct sales to customers, mentioned these climate-related damages as a reason to shift toward peach cultivation in order to maintain their customers. The peach fruit was specifically chosen as a replacement for apple because it is less vulnerable to these climatic stressors. For Group 3 farmers, the financial losses associated with these climate-related events could be compensated for by insurance. Their decision to grow peach is largely due to its higher price and immunity against a specific disease which affects apples but they only shifted once institutional support was available, thereby reducing the risk in cultivating a new species. Our findings suggest that the role of institutions was not to drive the process of the adaptation itself but rather to provide relevant support to farmers to enable them to shift to new crop varieties more easily. We argue that such process-based understanding is crucial in formulating strategies to increase adaptive capacity in agriculture. [ABSTRACT FROM AUTHOR]

An intensified hydrologic cycle and a large amount of monitoring flow data in the latter half of the 20th century attracted a lot of research on the continental U.S. hydrologic change. However, most previous studies are based on HCDN (Hydro-Climate Data Network) dataset with a period of ~1950s −1988. This study analyzed hydrologic change in continental U.S. based on MOPEX (international Model Parameter Estimation Experiment) hydrology dataset with a period of ~1950s −2000 for 302 watersheds (gages) across diverse climate, vegetation and soil conditions. This dataset is more representative of the latter half of the 20th century than HCDN. In contrast with previous studies, this study shows that only 20-30 % of watersheds present increasing trends in flow (streamflow, Q; baseflow, Q; baseflow index, BFI), and most (> 65 %) watersheds presents non-significant trends. Similar to previous studies, the watersheds with increasing trends in Q and Q are concentrated in Midwest and high plain (North-Central area) of USA. Climate contributes more to Q change (61 ± 25 % vs. 39 ± 25 %) but slightly less to Q change than human activity (49 ± 26 % vs. 51 ± 26 %) and much less to BFI change than human activity (−5 ± 61 % vs. 105 ± 61 %). A step change at ~1971 in Q and Q was found for 35-45 % but not for a large proportion of watersheds (50 % or more was reported by previous studies). This study provides new insights on the latter half of the 20th century's hydrologic cycle for the continental U.S. with a more representative dataset of this period. [ABSTRACT FROM AUTHOR]

We explore the potential to improve understanding of the climate system by directly targeting climate model analyses at specific indicators of climate change impact. Using the temperature suitability of premium winegrape cultivation as a climate impacts indicator, we quantify the inter- and intra-ensemble spread in three climate model ensembles: a physically uniform multi-member ensemble consisting of the RegCM3 high-resolution climate model nested within the NCAR CCSM3 global climate model; the multi-model NARCCAP ensemble consisting of single realizations of multiple high-resolution climate models nested within multiple global climate models; and the multi-model CMIP3 ensemble consisting of realizations of multiple global climate models. We find that the temperature suitability for premium winegrape cultivation is substantially reduced throughout the high-value growing areas of California and the Columbia Valley region (eastern Oregon and Washington) in all three ensembles in response to changes in temperature projected for the mid-twenty first century period. The reductions in temperature suitability are driven primarily by projected increases in mean growing season temperature and occurrence of growing season severe hot days. The intra-ensemble spread in the simulated climate change impact is smaller in the single-model ensemble than in the multi-model ensembles, suggesting that the uncertainty arising from internal climate system variability is smaller than the uncertainty arising from climate model formulation. In addition, the intra-ensemble spread is similar in the NARCCAP nested climate model ensemble and the CMIP3 global climate model ensemble, suggesting that the uncertainty arising from the model formulation of fine-scale climate processes is not smaller than the uncertainty arising from the formulation of large-scale climate processes. Correction of climate model biases substantially reduces both the inter- and intra-ensemble spread in projected climate change impact, particularly for the multi-model ensembles, suggesting that-at least for some systems-the projected impacts of climate change could be more robust than the projected climate change. Extension of this impacts-based analysis to a larger suite of impacts indicators will deepen our understanding of future climate change uncertainty by focusing on the climate phenomena that most directly influence natural and human systems. [ABSTRACT FROM AUTHOR]

A method is presented for estimating the global warming impact of forest biomass life cycles with respect to their functionally equivalent alternatives based on fossil fuels and non-renewable material sources. In the method, absolute global warming potentials (AGWP) of both the temporary carbon (C) debt of forest biomass stock and the C credit of the biomass use cycle displacing the fossil and non-renewable alternative are estimated as a function of the time frame of climate change mitigation. Dimensionless global warming potential (GWP) factors, GWP and GWP, are derived. As numerical examples, 1) bioenergy from boreal forest harvest residues to displace fossil fuels and 2) the use of wood for material substitution are considered. The GWP-based indicator leads to longer payback times, i.e. the time frame needed for the biomass option to be superior to its fossil-based alternative, than when just the cumulative balance of biogenic and fossil C stocks is considered. The warming payback time increases substantially with the residue diameter and low displacement factor (DF) of fossil C emissions. For the 35-cm stumps, the payback time appears to be more than 100 years in the climate conditions of Southern Finland when DF is lower than 0.5 in instant use and lower than 0.6 in continuous stump use. Wood use for construction appears to be more beneficial because, in addition to displaced emissions due to by-product bioenergy and material substitution, a significant part of round wood is sequestered into wood products for a long period, and even a zero payback time would be attainable with reasonable DFs. [ABSTRACT FROM AUTHOR]

The need for transparency is taking more prominence in international climate negotiations as developed countries pledge large sums of money to foster adaptation efforts in developing countries. Tools that provide accurate and up-to-date spatial information that can be easily used and vetted by local practitioners may provide effective and affordable ways to improve transparency. The Global Adaptation Atlas is such a tool, combining vetted, publicly available climate impact data with timely maps of on the ground adaptation projects to highlight confluences of effects of climate change with actions taken to address those effects. Here, we describe the structure and general functions of the Global Adaptation Atlas and explain how it may be utilized to track short-term investments in adaptation. Over longer time scales, it may also help gauge the effectiveness of specific adaptation investments as well as reveal how different climate impacts affect long-term investment in differing regions. [ABSTRACT FROM AUTHOR]

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Few conservation projects consider climate impacts or have a process for developing adaptation strategies. To advance climate adaptation for biodiversity conservation, we tested a step-by-step approach to developing adaptation strategies with 20 projects from diverse geographies. Project teams assessed likely climate impacts using historical climate data, future climate predictions, expert input, and scientific literature. They then developed adaptation strategies that considered ecosystems and species of concern, project goals, climate impacts, and indicators of progress. Project teams identified 176 likely climate impacts and developed adaptation strategies to address 42 of these impacts. The most common impacts were to habitat quantity or quality, and to hydrologic regimes. Nearly half of expected impacts were temperature-mediated. Twelve projects indicated that the project focus, either focal ecosystems and species or project boundaries, need to change as a result of considering climate impacts. More than half of the adaptation strategies were resistance strategies aimed at preserving the status quo. The rest aimed to make ecosystems and species more resilient in the face of expected changes. All projects altered strategies in some way, either by adding new actions, or by adjusting existing actions. Habitat restoration and enactment of policies and regulations were the most frequently prescribed, though every adaptation strategy required a unique combination of actions. While the effectiveness of these adaptation strategies remains to be evaluated, the application of consistent guidance has yielded important early lessons about how, when, and how often conservation projects may need to be modified to adapt to climate change. [ABSTRACT FROM AUTHOR]

Adaptation to climate change is given increasing international attention as the confidence in climate change projections is getting higher. Developing countries have specific needs for adaptation due to high vulnerabilities, and they will in this way carry a great part of the global costs of climate change although the rising atmospheric greenhouse gas concentrations are mainly the responsibility of industrialized countries. This article provides a status of climate change adaptation in developing countries. An overview of observed and projected climate change is given, and recent literature on impacts, vulnerability, and adaptation are reviewed, including the emerging focus on mainstreaming of climate change and adaptation in development plans and programs. The article also serves as an introduction to the seven research articles of this special issue on climate change adaptation in developing countries. It is concluded that although many useful steps have been taken in the direction of ensuring adequate adaptation in developing countries, much work still remains to fully understand the drivers of past adaptation efforts, the need for future adaptation, and how to mainstream climate into general development policies. [ABSTRACT FROM AUTHOR]

In this study we develop an “inference modeling” approach to compare and analyze how different disciplines (economics, political science, and behavioral science/environmental psychology) estimate vulnerability to drought. It is thought that a better understanding of these differences can lead to a synthesis of insights from the different disciplines and eventually to more comprehensive assessments of vulnerability. The new methodology consists of (1) developing inference models whose variables and assertions incorporate qualitative knowledge about vulnerability, (2) converting qualitative model variables into quantitative indicators by using fuzzy set theory, (3) collecting data on the values of the indicators from case study regions, (4) inputting the regional data to the models and computing quantitative values for susceptibility. The methodology was applied to three case study regions (in India, Portugal and Russia) having a range of socio-economic and water stress conditions. In some cases the estimates of susceptibility were surprisingly similar, in others not, depending on the factors included in the disciplinary models and their relative weights. A new approach was also taken to testing vulnerability parameters by comparing estimated water stress against a data set of drought occurrences based on media analysis. The new methodologies developed in this paper provide a consistent basis for comparing differences between disciplinary perspectives, and for identifying the importance of the differences. [ABSTRACT FROM AUTHOR]