Modelling the impact of climate change on Pacific skipjack tuna population and fisheries

IPCC-type climate models have produced simulations of the oceanic environment that can be used to drive models of upper trophic levels to explore the impact of climate change on marine resources. We use the Spatial Ecosystem And Population Dynamics Model (SEAPODYM) to investigate the potential impact of Climate change under IPCC A2 scenario on Pacific skipjack tuna (Katsuwonus pelamis). IPCC-type models are still coarse in resolution and can produce significant anomalies, e.g., in water temperature. These limitations have direct and strong effects when modeling the dynamics of marine species. Therefore, parameter estimation experiments based on assimilation of historical fishing data are necessary to calibrate the model to these conditions before exploring the future scenarios. A new simulation based on corrected temperature fields of the A2 simulation from one climate model (IPSL-CM4) is presented. The corrected fields led to a new parameterization close to the one achieved with more realistic environment from an ocean reanalysis and satellite-derived primary production. Projected changes in skipjack population under simple fishing effort scenarios are presented. The skipjack catch and biomass is predicted to slightly increase in the Western Central Pacific Ocean until 2050 then the biomass stabilizes and starts to decrease after 2060 while the catch reaches a plateau. Both feeding and spawning habitat become progressively more favourable in the eastern Pacific Ocean and also extend to higher latitudes, while the western equatorial warm pool is predicted to become less favorable for skipjack spawning.     

Simulation of leaf blast infection in tropical rice agro-ecology under climate change scenario

Assessing disease risk has become an important component in the development of climate change adaptation strategies. Here, the infection ability of leaf blast (Magnaporthe oryzae) was modeled based on the epidemiological parameters of minimum (T _min), optimum (T _opt), and maximum (T _max) temperatures for sporulation and lesion development. An infection ability response curve was used to assess the impact of rising temperature on the disease. The simulated spatial pattern of the infection ability index (IAI) corresponded with observed leaf blast occurrence in Indo-Gangetic plains (IGP). The IAI for leaf blast is projected to increase during the winter season (December–March) in 2020 (2010–2039) and 2050 (2040–2069) climate scenarios due to temperature rise, particularly in lower latitudes. However, during monsoon season (July–October), the IAI is projected to remain unchanged or even reduce across the IGP. The results show that the response curve may be successfully used to assess the impact of climate change on leaf blast in rice. The model could be further extended with a crop model to assess yield loss.     

An assessment of the potential impact of climate change on rice farmers and markets in Bangladesh

Bangladesh, the sixth largest rice producer in the world, has been identified as high risk from the effects of climate change. Many of the adverse impacts of climate change such as land inundation and changes in weather patterns and CO₂ levels will impact the agricultural sector. This study develops a partial-equilibrium multi-regional farm household model of Bangladesh rice and non-rice agricultural markets to quantify the impacts of climate change on consumption, production, prices, and farmers’ welfare. The model is calibrated to the Bangladesh rice market using Household Income and Expenditure Survey data. The model is simulated to analyze the impact of land reduction and productivity decline resulting from climate change. The results show that the decline in production in the coastal and northern regions offsets the production increase in the central and eastern regions, and the simulation predicts that total rice production for Bangladesh falls by about 2%. As total rice consumption falls and imports rise, the net effect leads to a rise in the rice price by 5.71% and a decline in farmers’ welfare. Sensitivity analysis shows that more- (less-) effective abatement technology could play a key role in mitigating (exacerbating) the price and welfare effects. The model predicts that many farmers in regions directly impacted by climate change could leave farming in search of off-farm work. Thus, the government can ease this transition by promoting urban development to provide more job options and technical training for farmers.     

河南省稻麦类作物对气候变化的响应

小麦和水稻是世界最重要的粮食作物。利用河南省小麦和水稻的历史观测资料,结合DSSAT-CERES 小麦和ORYZA2000水稻模拟模型,分析和模拟河南省稻麦类作物在历史气候变化条件下发育期和产量的变化。结果表明：冬小麦全育期长度呈缩短趋势,但播种-越冬天数平均每10年增加1.7天,开花到乳熟天数平均每10年增加2-4天,返青后各发育期均表现出不同程度的提前;水稻各发育期均有不同程度的提前,尤其是拔节期以前,分蘖前的发育期间隔天数以缩短为主,拔节后以延长为主。雨养小麦模拟产量和水氮增产潜力均呈减少趋势;随着播种期的提前,水稻减产趋势逐渐减弱。     

A co-evolutionary approach to climate change impact assessment: Part I. Integrating socio-economic and climate change scenarios

Climate change policies currently pay disproportionately greater attention to the mitigation of climate change through emission reductions strategies than to adaptation measures. Realising that the world is already committed to some global warming, policy makers are beginning to turn their attention to the challenge of preparing society to adapt to the unfolding impacts at the local level. This two-part article presents an integrated, or `co-evolutionary', approach to using scenarios in adaptation and vulnerability assessment. Part I explains how climate and social scenarios can be integrated to better understand the inter-relationships between a changing climate and the dynamic evolution of social, economic and political systems. The integrated scenarios are then calibrated so that they can be applied `bottom up’ to local stakeholders in vulnerable sectors of the economy. Part I concludes that a co-evolutionary approach (1) produces a more sophisticated and dynamic account of the potential feedbacks between natural and human systems; (2) suggests that sustainability indicators are both a potentially valuable input to and an output of integrated scenario formulation and application. Part II describes how a broadly representative sample of public, private and voluntary organisations in the East Anglian region of the UK responded to the scenarios, and identifies future research priorities.     

An assessment of regional vulnerability of rice to climate change in India

A simulation analysis was carried out using the InfoCrop-rice model to quantify impacts and adaptation gains, as well as to identify vulnerable regions for irrigated and rain fed rice cultivation in future climates in India. Climates in A1b, A2, B1 and B2 emission scenarios as per a global climate model (MIROC3.2.HI) and a regional climate model (PRECIS) were considered for the study. On an aggregated scale, the mean of all emission scenarios indicate that climate change is likely to reduce irrigated rice yields by ~4 % in 2020 (2010–2039), ~7 % in 2050 (2040–2069), and by ~10 % in 2080 (2070–2099) climate scenarios. On the other hand, rainfed rice yields in India are likely to be reduced by ~6 % in the 2020 scenario, but in the 2050 and 2080 scenarios they are projected to decrease only marginally (<2.5 %). However, spatial variations exist for the magnitude of the impact, with some regions likely to be affected more than others. Adaptation strategies comprising agronomical management can offset negative impacts in the near future—particularly in rainfed conditions—but in the longer run, developing suitable varieties coupled with improved and efficient crop husbandry will become essential. For irrigated rice crop, genotypic and agronomic improvements will become crucial; while for rainfed conditions, improved management and additional fertilizers will be needed. Basically climate change is likely to exhibit three types of impacts on rice crop: i) regions that are adversely affected by climate change can gain in net productivity with adaptation; ii) regions that are adversely affected will still remain vulnerable despite adaptation gains; and iii) rainfed regions (with currently low rainfall) that are likely to gain due to increase in rainfall can further benefit by adaptation. Regions falling in the vulnerable category even after suggested adaptation to climate change will require more intensive, specific and innovative adaptation options. The present analysis indicates the possibility of substantial improvement in yields with efficient utilization of inputs and adoption of improved varieties.     

The impact of perturbations to ocean-model parameters on climate and climate change in a coupled model

Assessments of the impacts of uncertainties in parameters on mean climate and climate change in complex climate models have, to date, largely focussed on perturbations to parameters in the atmosphere component of the model. Here we expand on a previously published study which found the global impacts of perturbed ocean parameters on the rate of transient climate change to be small compared to perturbed atmosphere parameters. By separating the climate-change-induced ocean vertical heat transport in each perturbed member into components associated with the resolved flow and each parameterisation scheme, we show that variations in global mean heat uptake in different perturbed versions are an order of magnitude smaller than the average heat uptake. The lack of impact of the perturbations is attributed to (1) the relatively small impact of the perturbation on the direct vertical heat transport associated with the perturbed process and (2) a compensation between those direct changes and indirect changes in heat transport from other processes. Interactions between processes and changes appear to combine in complex ways to limit ensemble spread and uncertainty in the rate of warming. We also investigate regional impacts of the perturbations that may be important for climate change predictions. We find variations across the ensemble that are significant when measured against natural variability. In terms of the experimental set-up used here (models without flux adjustments) we conclude that perturbed physics ensembles with ocean parameter perturbations are an important component of any probabilistic estimate of future climate change, despite the low spread in global mean quantities. Hence, careful consideration should be given to assessing uncertainty in ocean processes in future probabilistic assessments of regional climate change.     

Potential overwintering boundary and voltinism changes in the brown planthopper, <Emphasis Type="Italic">Nilaparvata lugens</Emphasis>, in China in response to global warming

The brown planthopper Nilaparvata lugens (Stål) is a major rice insect pest in China and other Asian countries. This study assessed a potential northward shift in the overwintering boundaries and changes in the overwintering areas and voltinism of this planthopper species in China in response to global warming. Temperature data generated by 15 Global Circulation Models (GCMs) from 2010 to 2099 were employed to analyze the planthopper’s overwintering boundaries and overwintering areas in conjunction with three Special Report on Emissions Scenarios (SRES). Planthopper voltinism from 1961 to 2050 was analyzed in scenario A2 using degree-day models with projections from the regional circulation model (RCM) Providing Regional Climates for Impacts Studies (PRECIS). In both analyses, 1961–1990 served as the baseline period. Both the intermittent and constant overwintering boundaries were projected to shift northward; these shifts were more pronounced during later time periods and in scenarios A2 and A1B. The intermittent overwintering area was modeled to increase by 11, 24 and 44 %, and the constant overwintering area, by 66, 206 and 477 %, during the 2020s, 2050s and 2080s, respectively. Planthopper voltinism will increase by <0.5, 0.5–1.0 and 1.0–1.4 generations in northern, central and southern China, respectively, in 2021–2050. Our results suggest that the brown planthopper will overwinter in a much larger region and will produce more generations under future climate warming scenarios. As a result, the planthopper will exert an even greater threat to China’s rice production in the future.     

Statistical downscaling of daily climate variables for climate change impact assessment over New South Wales, Australia

This paper outlines a new statistical downscaling method based on a stochastic weather generator. The monthly climate projections from global climate models (GCMs) are first downscaled to specific sites using an inverse distance-weighted interpolation method. A bias correction procedure is then applied to the monthly GCM values of each site. Daily climate projections for the site are generated by using a stochastic weather generator, WGEN. For downscaling WGEN parameters, historical climate data from 1889 to 2008 are sorted, in an ascending order, into 6 climate groups. The WGEN parameters are downscaled based on the linear and non-linear relationships derived from the 6 groups of historical climates and future GCM projections. The overall averaged confidence intervals for these significant linear relationships between parameters and climate variables are 0.08 and 0.11 (the range of these parameters are up to a value of 1.0) at the observed mean and maximum values of climate variables, revealing a high confidence in extrapolating parameters for downscaling future climate. An evaluation procedure is set up to ensure that the downscaled daily sequences are consistent with monthly GCM output in terms of monthly means or totals. The performance of this model is evaluated through the comparison between the distributions of measured and downscaled climate data. Kruskall-Wallis rank (K-W) and Siegel-Tukey rank sum dispersion (S-T) tests are used. The results show that the method can reproduce the climate statistics at annual, monthly and daily time scales for both training and validation periods. The method is applied to 1062 sites across New South Wales (NSW) for 9 GCMs and three IPCC SRES emission scenarios, B1, A1B and A2, for the period of 1900–2099. Projected climate changes by 7 GCMs are also analyzed for the A2 emission scenario based on the downscaling results.     

A method to evaluate the usability of interactive climate change impact decision aids

Reducing the impacts from climate change requires people to make decisions that may prompt substantial changes in their lives. One possible way to help them is with personalized decision aids. Here we describe a method for evaluating such aids, in terms of how they affect users’ understanding of their situation, defined in terms of their (a) knowledge, (b) consistency of preferences, and (c) active mastery of the material. Our method provides a simple way to evaluate the usability of climate-change decision aids, and to address concerns that the choice of display could bias users’ attitudes. We demonstrate it with the Surging Seas Risk Finder, a decision aid focused on coastal flooding (http://sealevel.climatecentral.org/).     

企业气候变化意识及应对措施调查研究

基于2012—2015年在华北、珠三角和湖南湖北地区对企业管理人员进行的气候变化意识的问卷调查,构建了气候变化意识和企业应对气候变化措施两个一级指数。通过对调查结果交叉列联表分析,得出以下结论：企业管理人员的气候变化意识指数处于一般水平,并且受年龄、产业类型、企业类型的影响显著;企业应对气候变化措施指数也处于一般水平且不同企业水平差距较大,企业管理人员气候变化意识水平、未来预期和自主知识产权拥有量对其影响显著。     

Determining the impact of climate change on land suitability for rice paddy cultivation using GIS and RS on FAO maximum limitation approach

Theoretical and Applied Climatology - In the present study, we aimed to understand the current condition of land suitability and how climate change will affect its suitability for rice paddy...     

The effect of global climate change, population distribution, and climate mitigation on building energy use in the U.S. and China

Climate change will affect the energy system in a number of ways, one of which is through changes in demands for heating and cooling in buildings. Understanding the potential effect of climate change on heating and cooling demands requires taking into account not only the manner in which the building sector might evolve over time, but also important uncertainty about the nature of climate change itself. In this study, we explore the uncertainty in climate change impacts on heating and cooling requirement by constructing estimates of heating and cooling degree days (HDD/CDDs) for both reference (no-policy) and 550 ppmv CO₂ concentration pathways built from three different Global Climate Models (GCMs) output and three scenarios of gridded population distribution. The implications that changing climate and population distribution might have for building energy consumption in the U.S. and China are then explored by using the results of HDD/CDDs as inputs to a detailed, building energy model, nested in the long-term global integrated assessment framework, Global Change Assessment Model (GCAM). The results across the modeled changes in climate and population distributions indicate that unabated climate change would cause building sector’s final energy consumption to decrease modestly (6 % decrease or less depending on climate models) in both the U.S. and China by the end of the century as decreased heating consumption more than offsets increased cooling using primarily electricity. However, global climate change virtually has negligible effect on total CO₂ emissions in the buildings sector in both countries. The results also indicate more substantial implications for the fuel mix with increases in electricity and decreases in other fuels, which may be consistent with climate mitigation goals. The variation in results across all scenarios due to variation of population distribution is smaller than variation due to the use of different climate models.     

Effects of climate variability and climate change on the fishing conditions for grey mullet (Mugil cephalus L.) in the Taiwan Strait

Grey mullet (Mugil cephalus L.) is one of the most important commercial species of fish in the coastal fisheries of Taiwan. In this study, we analyzed the long-term (1967–2009) records of grey mullet catch per unit effort (CPUE) in the Taiwan Strait (TS) to investigate the influences of climatic indices on the annual catch of grey mullet at multiple timescales. A wavelet analysis revealed that variations in climatic indices, namely the Pacific Decadal Oscillation (PDO), the Oceanic Niño Index, and sea surface temperatures (SSTs) might have affected the abundance and migration behavior of grey mullet in the TS in winter. The CPUE of grey mullet showed significant high correspondence with the annual PDO index (R ²?=0.82, p?<0.01). The results suggested that the PDO affects the migration of grey mullet, but that increases in SSTs are a more important influence on the decreased catches of grey mullet after 1980. Mean SSTs increased 1.01 °C at the Chang-Yuen Rise in the TS from 1984 to 2009. The 20 °C isotherms in the TS in the winter also shifted from 23–24°N in 1958–1978 to north of 25°N after 1998. The fishing grounds of grey mullet also shifted to the north following changes in the 20 °C isotherm in the TS.     

Impact assessment of climate change,carbon dioxide fertilization and constant growing season on rice yields in China

Rice is the staple food in China, and the country’s enlarging population puts increasing pressure on its rice production as well as on that of the world. In this study, we estimate the impact of climate change, CO₂ fertilization, crop adaptation and the interactions of these three factors on the rice yields of China using model simulation with four hypothetical scenarios. According to the results of the model simulation, the rice yields without CO₂ fertilization are predicted to decrease by 3.3 % in the 2040s. Considering a constant rice-growing season (GS), the rice yields are predicted to increase by 3.2 %. When the effect of CO₂ fertilization is integrated into the Agro-C model, the expected rice yields increase by 20.9 %. When constant GS and CO₂ fertilization are both integrated into the model, the predicted rice yield increases by 28.6 %. In summary, the rice yields in China are predicted to decrease in the 2040s by 0.22 t/ha due to climate change, to increase by 0.44 t/ha due to a constant GS and to increase by 1.65 t/ha due to CO₂ fertilization. The benefits of crop adaptation would completely offset the negative impact of climate change. In the future, the most of the positive effects of climate change are expected to occur in northeastern and northwestern China, and the expansion of rice cultivation in northeastern China should further enhance the stability of rice production in China.     

An exploratory study on occurrence and impact of climate change on agriculture in Tamil Nadu,India

This study has been undertaken to examine the occurrence of climate change in Tamil Nadu, the southernmost state of India and its impact on rainfall pattern which is a primary constraint for agricultural production. Among the five sample stations examined across the state, the minimum temperature has increased significantly in Coimbatore while the same has decreased significantly in Vellore whereas both minimum and maximum temperatures have increased significantly in Madurai since 1969 with climate change occurring between late 1980s and early 1990s. As a result, the south-west monsoon has been disturbed with August rainfall increasing with more dispersion while September rainfall decreasing with less dispersion. Thus, September, the peak rainfall month of south-west monsoon before climate change, has become the monsoon receding month after climate change. Though there has been no change in the trend of the north-east monsoon, the quantity of October and November rainfall has considerably increased with increased dispersion after climate change. On the whole, south-west monsoon has decreased with decreased dispersion while north-east monsoon has increased with increased dispersion. Consequently, the season window for south-west monsoon crops has shortened while the north-east monsoon crops are left to fend against flood risk during their initial stages. Further, the incoherence in warming, climate change and rainfall impact seen across the state necessitates devising different indigenous and institutional adaptation strategies for different regions to overcome the adverse impacts of climate change on agriculture.