Analysis of climate variability in the Manas River Valley,North-Western China (1956–2006)

This paper examines the short-run climate variability (change in the levels of temperature and precipitation) with a focus on the Manas River Valley, North-Western China, over the past 50 years (1956 to 2006) using data collected from four meteorological stations. The results show that the annual mean temperature had a positive trend, with temperature increasing at 0.4 °C per decade. Application of the Mann-Kendall test revealed that the overall positive trend became statistically significant at the p?=?0.95 level only after 1988. The increase in temperature was most marked in winter and spring (0.8 and 0.7 °C per decade, respectively), absent in summer and very small in autumn (0.1 °C per decade). Concerning precipitation, our results indicate a negative but not significant trend for the period between 1956 and 1982, while annual total precipitation tended to increase thereafter and the increase was mainly during the crop growing-season. Concerning variability in temperature and precipitation, the characteristic time scales were identified by application of wavelet analysis. For temperature the quasi-decadal variations were found on time scales between approximately 5 and 15 years, with a peak in wavelet variance on a time scale of 9 years. For precipitation, the most striking features were a precipitation increase (6.7 mm per decade) during the crop growing season. Irregularities and abrupt changes in both temperature and precipitation were more common at scales less than 10 years, indicating the complexity and uncertainty in the short-period climate variability. Possible causes of climate variability in the Manas River Valley may include anthropogenic factors such as intensive human activity and the expansion of both farmland and irrigation. Global climate variability might also have some impacts on the local climate variability; analyses of local and regional climate trends can better inform local adaptation actions for global impacts.     

Vulnerability of Indian mustard (<Emphasis Type="Italic">Brassica juncea</Emphasis> (L.) Czernj. Cosson) to climate variability and future adaptation strategies

A simulation study has been carried out using the InfoCrop mustard model to assess the impact of climate change and adaptation gains and to delineate the vulnerable regions for mustard (Brassica juncea (L.) Czernj. Cosson) production in India. On an all India basis, climate change is projected to reduce mustard grain yield by ～2 % in 2020 (2010–2039), ～7.9 % in 2050 (2040–2069) and ～15 % in 2080 (2070–2099) climate scenarios of MIROC3.2.HI (a global climate model) and Providing Regional Climates for Impact Studies (PRECIS, a regional climate model) models, if no adaptation is followed. However, spatiotemporal variations exist for the magnitude of impacts. Yield is projected to reduce in regions with current mean seasonal temperature regimes above 25/10 °C during crop growth. Adapting to climate change through a combination of improved input efficiency, additional fertilizers and adjusting the sowing time of current varieties can increase yield by ～17 %. With improved varieties, yield can be enhanced by ～25 % in 2020 climate scenario. But, projected benefits may reduce thereafter. Development of short-duration varieties and improved crop husbandry becomes essential for sustaining mustard yield in future climates. As climatically suitable period for mustard cultivation may reduce in future, short-duration (<130 days) cultivars with 63 % pod filling period will become more adaptable. There is a need to look beyond the suggested adaptation strategy to minimize the yield reduction in net vulnerable regions.     

Impacts of climate change on water resources in the Yellow River basin and identification of global adaptation strategies

Climate change is a global environmental issue, which is challenging water resources management and practices. This study investigates the impact of climate change on water resources of the Yellow River basin, a major grain-producing area in China, and provides recommendations on strategies to increase adaptive capacity and resilience in the basin region. Results show that the recorded stream flows of the Yellow River declined from 1951 to 2010 and have decreased significantly in the middle and lower reaches. The variable infiltration capacity (VIC) model performs well as a tool to simulate monthly discharge of both the tributary catchments and the whole Yellow River basin. Temperature across the Yellow River basin over 2021–2050 is expected to continue to rise with an average rates of approximately 0.039–0.056 °C/annum. The average annual precipitation in the basin is projected to increase by 1.28–3.29 % compared with the 1991–2010 baseline. Runoff during 2021–2050 is projected to decrease by 0.53–9.67 % relative to 1991–2010 with high decadal and spatial variability. This is likely due to the model’s projections of a significant rise in temperature and changes in precipitation patterns. Climate change will likely aggravate the severity and frequency of both water shortages and flooding in the basin region. It is therefore essential to devote sufficient attention on structural and non-structural measures for the Yellow River basin to cope with climate change. At the global level, strategies to increase adaptive capacity and build resilience to climate change focus on public education to improve awareness of climate risks, implementing the integrated water resources management and planning based on impact assessments.     

Adaptation to changing water resources in the Ganges basin, northern India

An ensemble of regional climate model (RCM) runs from the EU HighNoon project are used to project future air temperatures and precipitation on a 25 km grid for the Ganges basin in northern India, with a view to assessing impact of climate change on water resources and determining what multi-sector adaptation measures and policies might be adopted at different spatial scales.The RCM results suggest an increase in mean annual temperature, averaged over the Ganges basin, in the range 1–4 °C over the period from 2000 to 2050, using the SRES A1B forcing scenario. Projections of precipitation indicate that natural variability dominates the climate change signal and there is considerable uncertainty concerning change in regional annual mean precipitation by 2050. The RCMs do suggest an increase in annual mean precipitation in this region to 2050, but lack significant trend. Glaciers in headwater tributary basins of the Ganges appear to be continuing to decline but it is not clear whether meltwater runoff continues to increase. The predicted changes in precipitation and temperature will probably not lead to significant increase in water availability to 2050, but the timing of runoff from snowmelt will likely occur earlier in spring and summer. Water availability is subject to decadal variability, with much uncertainty in the contribution from climate change.Although global social-economic scenarios show trends to urbanization, locally these trends are less evident and in some districts rural population is increasing. Falling groundwater levels in the Ganges plain may prevent expansion of irrigated areas for food supply. Changes in socio-economic development in combination with projected changes in timing of runoff outside the monsoon period will make difficult choices for water managers.Because of the uncertainty in future water availability trends, decreasing vulnerability by augmenting resilience is the preferred way to adapt to climate change. Adaptive policies are required to increase society's capacity to adapt to both anticipated and unanticipated conditions. Integrated solutions are needed, consistent at various spatial scales, to assure robust and sustainable future use of resources. For water resources this is at the river basin scale. At present adaptation measures in India are planned at national and state level, not taking into account the physical boundaries of water systems. To increase resilience adaptation plans should be made locally specific. However, as it is expected that the partitioning of water over the different sectors and regions will be the biggest constraint, a consistent water use plan at catchment and river basin scale may be the best solution. A policy enabling such river basin planning is essential.     

Assessing high-impact spots of climate change: spatial yield simulations with Decision Support System for Agrotechnology Transfer (DSSAT) model

Drybeans (Phaseolus vulgaris L.) are an important subsistence crop in Central America. Future climate change may threaten drybean production and jeopardize smallholder farmers’ food security. We estimated yield changes in drybeans due to changing climate in these countries using downscaled data from global circulation models (GCMs) in El Salvador, Guatemala, Honduras, and Nicaragua. We generated daily weather data, which we used in the Decision Support System for Agrotechnology Transfer (DSSAT) drybean submodel. We compared different cultivars, soils, and fertilizer options in three planting seasons. We analyzed the simulated yields to spatially classify high-impact spots of climate change across the four countries. The results show a corridor of reduced yields from Lake Nicaragua to central Honduras (10–38 % decrease). Yields increased in the Guatemalan highlands, towards the Atlantic coast, and in southern Nicaragua (10–41 % increase). Some farmers will be able to adapt to climate change, but others will have to change crops, which will require external support. Research institutions will need to devise technologies that allow farmers to adapt and provide policy makers with feasible strategies to implement them.     

气候变化对澜沧江-湄公河上中游径流的影响研究

将区域气候模式RegCM3与水循环模拟模型WACM进行单向耦合,对澜沧江-湄公河流域未来气候变化和流域上中游主要控制水文站径流响应进行了模拟和分析。区域气候预估表明,相对于现状(1980—2009年),A1B情景下未来(2010—2039年)流域年平均温度和降水均有增加趋势,分别增加了0.65 ℃和1.87%,但降水增加不明显;流域北部温度增幅比南部明显,而降水区域差异较大,变化较为复杂。径流模拟结果表明,未来气候变化情景下,清盛和琅勃拉邦站多年平均径流量与天然情景相比均有减少趋势,分别减少了1.23%和3.69%,但变化不明显;未来径流年际变化呈不显著的减少趋势,而温度变化对径流影响作用要强于降水;未来春季和夏季(3—6月)径流增减相对明显,局部区域有洪涝和水文干旱的风险,而其它月份径流变化不显著。     

Adaptation to climate change: changes in farmland use and stocking rate in the U.S.

This paper examines possible adaptations to climate change in terms of pasture and crop land use and stocking rate in the United States (U.S.). Using Agricultural Census and climate data in a statistical model, we find that as temperature and precipitation increases agricultural commodity producers respond by reducing crop land and increasing pasture land. In addition, cattle stocking rate decreases as the summer Temperature-humidity Index (THI) increases and summer precipitation decreases. Using the statistical model with climate data from four General Circulation Models (GCMs), we project that land use shifts from cropping to grazing and the stocking rate declines, and these adaptations are more pronounced in the central and the southeast regions of the U.S. Controlling for other farm production variables, crop land decreases by 6 % and pasture land increases by 33 % from the baseline. Correspondingly, the associated economic impact due to adaptation is around ?14 and 29 million dollars to crop producers and pasture producers by the end of this century, respectively. The national and regional results have implications for farm programs and subsidy policies.     

Adaptation strategies for maize cultivation under climate change in Iran: irrigation and planting date management

Climate change is affecting the productivity of crops and their regional distribution. Strategies to enhance local adaptation capacity are needed to mitigate climate change impacts and to maintain regional stability of food production. The objectives of this study were to simulate the climate change effects on phenological stages, Leaf Area Index (LAI), biomass and grain yield of maize (Zea mays L.) in the future and to explore the possibilities of employing irrigation water and planting dates as adaptation strategies to decrease the climate change impacts on maize production in Khorasan Razavi province, Iran. For this purpose, we employed two types of General Circulation Models ((United Kingdom Met. Office Hadley Center: HadCM3) and (Institute Pierre Simon Laplace: IPCM4)) and three scenarios (A1B, A2 and B1). Long Ashton Research Station-Weather Generator (LARS-WG) was used to produce daily climatic parameters as one stochastic growing season for each projection period. Also, crop growth under projected climate conditions was simulated based on the Cropping System Model (CSM)-CERES-Maize. The results of model evaluation showed that LARS-WG had appropriate prediction for climatic parameters. Time period from cultivation until anthesis and maturity were reduced in majority of scenarios as affected by climate change. The results indicated that the grain yield of maize may be reduced (11 % to 38 %) as affected by climate change based on common planting date in baseline and changed (?61 % to 48 %) in response to different irrigation regimes in the future climate change, under all scenarios and times. In general, earlier planting date (1 May) and decreasing irrigation intervals in the anthesis stage (11 applications) caused higher yield compared with other planting dates due to adaption to high temperature. Based on our findings, it seems that management of irrigation water and planting dates can be beneficial for adaptation of maize to climate change in this region.     

全球变暖背景下中亚兴都库什、喀喇昆仑及天山气候变化研究进展

中亚兴都库什、喀喇昆仑及天山山脉（HKT）是气候变化敏感区,其在全球变暖背景下的气候变化对区域生态和经济系统的稳定性及可持续发展有重要意义。目前对中亚高海拔地区的研究多集中于局部区域,有关HKT地区气候变化的综合对比分析较为缺乏。本文对HKT地区现代气候变化的相关研究成果进行简单梳理和回顾,重点总结了HKT地区气候变化特征、影响机制及其与全球变暖的联系。结果表明：（1）近60 a,HKT地区不同区域气候的时空特征存在差异,从时间上看,天山的年均温及年降水量均呈上升趋势,而兴都库什-喀喇昆仑山的年均温呈不显著增加趋势,其年降水量变化趋势不稳定;从空间上看,HKT地区山脉南坡气温高于北坡,但北坡降水量高于南坡,且天山南北坡年降水均呈上升趋势。（2）HKT地区的气候变化除了受西风环流、南亚印度季风及局地条件等影响外,还受到北大西洋涛动和厄尔尼诺-南方涛动等大尺度气候模态的调制,如兴都库什-喀喇昆仑山脉在NAO正（负）位相和ENSO暖（冷）位相降水趋于增加（减少）。     

Impacts of climate change on savannah woodland biomass carbon density and water-use: a modelling study of the Sudanese gum belt region

This paper analyzes potential impacts of climate change on biomass carbon (C) density and water-use (actual evapotranspiration, AET) of savannah woodlands in Sudan. Climate change scenarios were developed from five General Circulation Models (GCMs; CGCM2, CSIRO2, ECHam4, HadCM3 and PCM) under two IPCC (Intergovernmental Panel on Climate Change) emission scenarios (A1FI and B1). Baseline (1961-90) climate and climate change scenarios for 2080s for eight map sheet grids (1° latitude x 1.5° longitude) were constructed. Compared to baseline values, mean annual precipitation (MAP) showed both increases (+112 to +221 mm) and decreases (?13 to ?188 mm) but mean annual temperature (MAT) only showed increases (+1.2 to +8.3 °C). Baseline biomass C densities showed an exponential relationship with MAP (y?=?6.798 e ^0.0054x, R²?=?0.70). Depending on climate change MAP, biomass C densities increased (+14 to +241 g C m^?2) or decreased (?1 to ?148 g?C m^?2). However, because of uncertainty in biomass C density estimates, the changes were only significant (P <0.05) for some of the climate change scenarios and for grids with MAP >260 mm. Under A1FI emission scenarios, only HadCM3 did not have a significant effect while under B1 emission scenarios, only CGCM2 and ECHam4 had a significant effect on biomass C density. AET also showed both increases (+100 to +145 mm for vertisols and +82 to +197 mm for arenosols) and decreases (?12 to ?178 mm for vertisols and ?12 to ?132 mm for arenosols). The largest relative changes in AET (up to 31 %) were associated with grids receiving the lowest rainfall. Thus, even if MAP increases across the study region, the increase will have little impact on biomass levels in the driest areas of the region, emphasizing the need for improved management and use of savannah woodlands.     

Adaptation strategies of climate variability impacts on alpine grassland ecosystems in Tibetan Plateau

Northern Tibet is the headstream region for the Yangtze, Salween River, Mekong River, and numerous other inflowing rivers and high mountain lakes. Sustaining the environmental conditions in the region is of vital importance for Tibet and the whole of China. The alpine grassland ecosystem in Northern Tibet is the most important ecosystem and extremely sensitive to climate change and human activity. In this study, we analyzed the characteristics of climate variability based on observed meteorological data and future climate scenarios, and reviewed the impact of climate variability and to explore adaptation strategies of alpine grassland in Northern Tibet. The result showed that the annual mean temperature has increased by 0.31 °C·10a^?1 while the annual total precipitation has increased by 14.6 mm·10a^?1 with high inter-annual and inter-seasonal fluctuations in Northern Tibet from 1961 to 2008. The rising trends of temperature and precipitation would be continued and the aridity indices showed a decreasing trend in the future, which potentially predicts that the climate in Northern Tibet becomes warmer and dryer. The climate variability results the melting of glaciers, the expansion of inland high mountain lakes and the negative impacts on alpine grassland in recent years. In order to adapt to such possible future climate changes, the alpine grassland water-saving irrigation was recommended as key adaptation measure and also rational grazing management, alpine grassland fencing and artificial grass planting were selected as adaptation measures, to lower the negative impacts of climate variability on the alpine grassland ecosystem in Northern Tibet.     

From site-level to regional adaptation planning for tropical commodities: cocoa in West Africa

The production of tropical agricultural commodities, such as cocoa (Theobroma cacao) and coffee (Coffea spp.), the countries and communities engaged in it, and the industries dependent on these commodities, are vulnerable to climate change. This is especially so where a large percentage of the global supply is grown in a single geographical region. Fortunately, there is often considerable spatial heterogeneity in the vulnerability to climate change within affected regions, implying that local production losses could be compensated through intensification and expansion of production elsewhere. However, this requires that site-level actions are integrated into a regional approach to climate change adaptation. We discuss here such a regional approach for cocoa in West Africa, where 70 % of global cocoa supply originates. On the basis of a statistical model of relative climatic suitability calibrated on West African cocoa farming areas and average climate projections for the 2030s and 2050s of, respectively, 15 and 19 Global Circulation Models, we divide the region into three adaptation zones: (i) a little affected zone permitting intensification and/or expansion of cocoa farming; (ii) a moderately affected zone requiring diversification and agronomic adjustments of farming practices; and (iii) a severely affected zone with need for progressive crop change. We argue that for tropical agricultural commodities, larger-scale adaptation planning that attempts to balance production trends across countries and regions could help reduce negative impacts of climate change on regional economies and global commodity supplies, despite the institutional challenges that this integration may pose.     

Future production of rainfed wheat in Iran (Khorasan province): climate change scenario analysis

Projecting staple crop production including wheat under future climate plays a fundamental role in planning the required adaptation and mitigation strategies for climate change effects especially in developing countries. The main aim of this study was to investigate the direction and magnitude of climate change impacts on grain yield of rainfed wheat (Triticum aestivum L.) production and precipitation within growing season. This study was performed for various regions in Khorasan province which is located in northeast of Iran. Climate projections of two General Circulation Models (GCM) for four locations under three climate change scenarios were employed in this study for different future time periods. A stochastic weather generator (LARS-WG5) was used for downscaling to generate daily climate parameters from GCMs output. The Decision Support System for Agrotechnology Transfer (DSSAT) Version 4.5 was employed to evaluate rainfed wheat performance under future climate. Grain yield of rainfed wheat and precipitation during growth period considerably decreased under different scenarios in various time periods in contrast to baseline. Highest grain yield and precipitation during growth period was obtained under B1 scenario but A1B and A2 scenarios resulted in sharp decrease (by ?57 %) of grain yield. Climate change did not have marked effects on evapotranspiration during the rainfed wheat growth. A significant correlation was detected between grain yield, precipitation and evapotranspiration under climate change for both GCMs and under all study scenarios. It was concluded, that rainfed wheat production may decline during the next 80 years especially under A2 scenario. Therefore, planning the comprehensive adaptation and mitigation program is necessary for avoiding climate change negative impact on rainfed wheat production.     

Dengue epidemics in the Caribbean-temperature indices to gauge the potential for onset of dengue

The seasonality, patterns and the climate associations of the reported cases of dengue in the Caribbean were studied by analyzing the annual and monthly variability of reported cases as well as those of climate parameters (temperature and precipitation). More attention was given to Trinidad and Tobago, Barbados, and Jamaica, as those countries contributed mostly to the reported cases. The data were for the period 1980–2003. Results showed that the incidence of dengue in the Caribbean were higher in the last decade (1990s) compared to that in the previous decade (1980s). The yearly patterns of dengue exhibited a well-defined seasonality. The epidemics appeared to occur in the later half of the year following onset of rainfall and increasing temperature. Analysis revealed that the association of the epidemics with temperature was stronger, especially in relation to the onset of dengue, and the probability of epidemics was high during El Niño periods. In years with early warmer periods epidemics appeared to occur early, which was a scenario more probable in the year after an El Niño (an El Niño + 1 year). Indices linked to temperatures that are useful for gauging the potential for onset of dengue were examined. An index based on a moving average temperature (MAT) appeared to be effective in gauging such potential and its average (AMAT) signals a threshold effect. MAT index has potential use in adaptation and mitigation strategies.     

Climate change impact, mitigation and adaptation strategies for agricultural and water resources, in Ganga Plain (India)

Agriculture consumes more than two-thirds of global fresh water out of which 90 % is used by developing countries. Freshwater consumption worldwide is expected to rise another 25 %by 2030 due to increase in population from 6.6 billion currently to about 8 billion by 2030 and over 9 billion by 2050. Worldwide climate change and variability are affecting water resources and agricultural production and in India Ganga Plain region is one of them. Hydroclimatic changes are very prominent in all the regions of Ganga Plain. Climate change and variability impacts are further drying the semi-arid areas and may cause serious problem of water and food scarcity for about 250 million people of the area. About 80 million ha out of total 141 million ha net cultivated area of India is rainfed, which contributes approximately 44 % of total food production has been severely affected by climate change. Further changing climatic conditions are causing prominent hydrological variations like change in drainage density, river morphology (tectonic control) & geometry, water quality and precipitation. Majority of the river channels seen today in the Ganga Plain has migrated from their historic positions. Large scale changes in land use and land cover pattern, cropping pattern, drainage pattern and over exploitation of water resources are modifying the hydrological cycle in Ganga basin. The frequency of floods and drought and its intensity has increased manifold. Ganga Plain rivers has changed their course with time and the regional hydrological conditions shows full control over the rates and processes by which environments geomorphically evolve. Approximately 47 % of total irrigated area of the country is located in Ganga Plain, which is severely affected by changing climatic conditions. In long run climate change will affect the quantity and quality of the crops and the crop yield is going to be down. This will increase the already high food inflation in the country. The warmer atmospheric temperatures and drought conditions will increase soil salinization, desertification and drying-up of aquifer, while flooding conditions will escalate soil erosion, soil degradation and sedimentation. The aim of this study is to understand the impact of different hydrological changes due to climatic conditions and come up with easily and economically feasible solutions effective in addressing the problem of water and food scarcity in future.     

Attribution assessment and projection of natural runoff change in the Yellow River Basin of China

Climate variability and human activities are two driving factors in the hydrological cycle. The analysis of river basin hydrological response to this change in the past and future is scientifically essential for the improvement of water resource and land management. Using a water balance model based on Fu’ equation, the attribution of climate variability and land-use/land-cover change (LUCC) for natural runoff decrease was quantitatively assessed in the Yellow River Basin (YRB). With five general circulation model (GCM) s’ output provided by The Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), future runoff in the context of climate change was projected. The results show that (1) compared with other distributed hydrological models, the water balance model in this study has fewer parameters and simpler calculation methods, thus having advantages in hydrological simulation and projection in large scale; (2) during the last 50 years, the annual precipitation and runoff have decreased, while the mean temperature has increased in the YRB. The decrease of natural runoff between natural period (1961 to 1985) and impacted period (1986 to 2011) could be attributed to 27.1–49.8 and 50.2–72.9% from climate variability and LUCC, respectively. As the LUCC is the major driving factor of the decrease in the upper and middle reaches of the YRB, policymakers could focus on water resources management. While climate variability makes more contribution in the middle and lower reaches of the YRB, it is essential to study the impact of future climate change on water resources under different climate change scenarios, for planning and management agencies; (3) temperature and precipitation in the YRB were predicted to increase under RCP4.5. It means that the YRB will become warmer and wetter in the future. If we assume the land-use/land-cover condition during 2011 to 2050 is the same as that during 1986 to 2011, future annual average natural runoff in the YRB will increase by 14.4 to 16.8%. However, future runoff will still be lower than the average value during 1961 to 1985. In other words, although future climate change will cause the increase of natural runoff in the YRB, the negative effect of underlying surface condition variation is stronger. It is necessary to promote the sustainable development and utilization of water resources and to enhance adaptation capacity so as to reduce the vulnerability of the water resources system to climate change and human activities.     

Influence of tree species composition,thinning intensity and climate change on carbon sequestration in Mediterranean mountain forests: a case study using the CO2Fix model

Prediction of future forest carbon (C) stocks as influenced by forest management and climate is a crucial issue in the search for strategies to mitigate and adapt to global change. It is hard to quantify the long-term effect of specific forest practices on C stocks due to the high number of processes affected by forest management. This work aims to quantify how forest management impacts C stocks in Mediterranean mountain forests based on 25 combinations of site index, tree species composition and thinning intensity in three different climate scenarios using the CO2Fix v.3.2 model Masera et al. (Ecol Modell 164:177–199, 2003). The study area is an ecotonal zone located in Central Spain, and the tree species are Scots pine (Pinus sylvestris L.) and Pyrenean oak (Quercus pyrenaica Willd.). Our results show a strong effect of tree species composition and a negligible effect of thinning intensity. Mixed stands have the highest total stand C stocks: 100 % and 15 % more than pure oak and pine stands respectively, and are here suggested as a feasible and effective mitigation option. Climate change induced a net C loss compared to control scenarios, when reduction in tree growth is taken into account. Mixed stands showed the lowest reduction in forest C stocks due to climate change, indicating that mixed stands are also a valid adaptation strategy. Thus converting from pure to mixed forests would enhance C sequestration under both current and future climate conditions.     

Gaps in the capacity of modern forage crops to adapt to the changing climate in northern Europe

The within-species diversity in response to weather and the gaps in the response diversity in the modern set of forage crop cultivars were determined using an approach that assessed the adaptive capacity under global climate change. The annual dry matter (DM) yields were recorded in multi-location MTT (Maa- ja elintarviketalouden tutkimuskeskus) Agrifood Research Official Variety Trials in Finland for modern forage crop cultivars from 2000 to 2012, as a response to agroclimatic variables critical to yield based on the year-round weather data. The effect and interaction of cultivars and agroclimatic variables were analysed using mixed model. The relatively low adaptive capacity of timothy (Phleum pratense L.) and meadow fescue (Festuca pratensis Huds.) indicates that diversification of the breeding material is warranted, particularly for resistance to high temperatures during primary growth and to high temperature sum 7 days after the first cut. All red clover cultivars (Trifolium pratense L.) suffered from both low and high accumulation of warm winter temperatures. Except for the red clover cultivars, cold stress during winter and lack of warm winter temperatures consistently reduced the yields of all species and cultivars. All tall fescue (Festuca arundinacea Schreb.) cultivars suffered from low precipitation during the fall hardening period. Although the set of festulolium (Festulolium pabulare) cultivars was also sensitive to low precipitation during the fall, festulolium was a good example of enhanced capacity to adapt to climate change with high response diversity because the cultivar germplasm base was diversified. Foreign origin in a cultivar pool was apparently not sufficient or necessary to ensure added value for a diversity of responses to climate change. Similar analyses to those used in this study, applied as practical tools for breeders, farmers and public actors, are important to secure the adaptive capacity of crops worldwide under global climate change.     

Adaptation strategies to combat climate change effect on rice and mustard in Eastern India

The negative impact of climate change on crop production is alarming as the demand for food is expected to increase in coming years, at a rate of about 2 percent a year. Wet season rice (Oryza sativa) followed by mustard (Brassica juncea) is one of the prominent cropping sequences in Eastern India. Descreases in their productivity due to climate change will not only hamper the regional food security but also affect the global economy. Considering the fact, the present study aims to assess the impact of climate change on productivity of wet-season rice and mustard and to evaluate the effectiveness of agronomic adjustment as adaptation options. Crop growth simulation model (CGSM) is a very effective tool to predict the growth and yield of a crop. One CGSM, namely InfoCrop (Generic Crop Model), was calibrated and validated for the said crops for West Bengal State, Eastern India. After validation, the model was used to predict the yield under elevated thermal condition (1 and 3 °C rise over normal temperature). Moreover, the future weather situation as predicted by PRECIS (Providing Regional Climates for Impacts Studies) model was used as weather input of the CGSM and the yield was predicted for ten selected locations of West Bengal for the year 2025 and 2050. It was observed that the average yield reduction of the wet-season rice would be in the tune of about 20.0 % for 2025 and 27.8 % for 2050. The mustard yield of West Bengal may be reduced by 20.0 to 33.9 % for the year 2025 and up to 40 % for 2050. It was concluded that the negative impact of climate change on mustard grown in winter season will be more pronounced compared to wet-season rice. Adjustment of sowing time will be the simplest and effective adaptation option for both rice and mustard. Increased rate of nutrient application can sustain the rice yield under future climate. The older seedling at the time of transplanting of wet-season rice and increased seed rate of mustard were proved less effective.     

An indicator tool for assessing local vulnerability to climate change in the Mexican agricultural sector

To propose specific adaptation strategies in the agricultural sector based on vulnerability to climate variability and climate change at the local level, we built a vulnerability index using an indicator tool at a fine spatial scale. This index was applied as a case study in the municipality of Guasave, Sinaloa, Mexico, at the basic census area (BCA) level. We used a total of 37 variables organized into three groups with equal weighting: exposure (13), sensitivity (13), and adaptive capacity (11). From the 20 rural BCAs located in the study area, eight were categorized as having very low vulnerability; five had low vulnerability; two had medium vulnerability because of the lack of basic services (sewers, water, and electricity) and a high rural population density; three had high vulnerability due to a high frequency of days with temperatures below 5 °C and the lack of basic services; and two had very high vulnerability, characterized by a high percentage of production units (PUs) with losses due to climate factors, a high rural population density, and a high frequency of days with temperatures below 5 °C. Approximately 50 % of the municipal rural population lives in BCAs vulnerable to climate change. This methodology allowed us to identify the most susceptible agricultural areas at the local level and the variables that require more attention so that we can propose adaptation strategies and minimize vulnerability due to climate change.