Farmers’ climate change beliefs and adaptation strategies for a water scarce future in Australia

Climate change is likely to require irrigators in Australia's Murray-Darling Basin to cope with less water, which will require ongoing farm adjustment. Possible incremental adjustment strategies include expansive and accommodating responses, such as irrigators buying land and water, increasing their irrigated area, changing crop mix and adopting efficient infrastructure. Contractive strategies include selling land and water, and decreasing their irrigated area. Using historical surveys we provide a comparison of irrigators’ planned and actual strategies over the past fifteen years, thereby offering a strong foundation to support analysing future adaptation strategies. We explore influences associated with farm adjustment strategies, and in particular the role that climate change beliefs play. Farmers convinced that climate change is occurring are more likely to plan accommodating, but not expansive, strategies. The relationship between climate change belief and adopting various adaptive strategies was found to be often endogenous, especially for accommodating strategies. Such results suggest the need for irrigation farming policies to be targeted at improving irrigators’ adaptability to manage water variability, and its link with farm future viability.     

Assessing the impact of climate changes on the potential yields of maize and paddy rice in Northeast China by 2050

Northeast China is the main crop production region in China, and future climate change will directly impact crop potential yields, so exploring crop potential yields under future climate scenarios in Northeast China is extremely critical for ensuring future food security. Here, this study projected the climate changes using 12 general circulation models (GCMs) under two moderate Representative Concentration Pathway (RCP) scenarios (RCP 4.5 and 6.0) from 2015 to 2050. Then, based on the Global Agro-ecological Zones (GAEZ) model, we explored the effect of climate change on the potential yields of maize and paddy rice in Northeast China during 2015–2050. The annual relative humidity increased almost throughout the Northeast China under two RCPs. The annual precipitation increased more than 400 mm in some west, east, and south areas under RCP 4.5, but decreased slightly in some areas under RCP 6.0. The annual wind speed increased over 2 m/s in the west region. The annual net solar radiation changes varied significantly with latitude, but the changes of annual maximum temperature and minimum temperature were closely related to the terrain. Under RCP 4.5, the average maize potential yield increased by 34.31% under the influence of climate changes from 2015 to 2050. The average rice potential yield increased by 16.82% from 2015 to 2050. Under RCP 6.0, the average maize and rice potential yields increased by 25.65% and 6.34% respectively. The changes of maize potential yields were positively correlated with the changes of precipitation, wind speed, and net solar radiation (the correlation coefficients were > 0.2), and negatively correlated with the changes of relative humidity, minimum and maximum temperature under two RCPs. The changes of rice potential yields were positively correlated with the changes of precipitation (correlation coefficient = 0.15) under RCP 4.5. Under RCP 6.0, it had a slight positive correlation with net solar radiation, relative humidity, and wind speed.     

2021—2050年河南省夏玉米净灌溉需水量对气候变化的响应

基于河南省17个气象站点观测资料和25个CMIP5模式预估数据,采用BCC/RCG-WG 3.0天气发生器构建区域气候变化情景,集合评估了RCP4.5情景下2021—2050年夏玉米净灌溉需水量较1961—2000年的变化及其空间分布。结果表明：全生育期内气温升高1.8℃,降水增加3.6%,引起作物需水量和有效降水量分别增加5.1%和1.5%,净灌溉需水量增加5.6%。受气温升高和降水减少的双重影响,播种－拔节期净灌溉需水量增幅较大,达到21.3%;拔节－乳熟期尽管有效降水量增加3.0%,但这并不足以抵消气温升高引起的作物需水量增加5.1%的影响,净灌溉需水量仍然增加3.4%;乳熟－成熟期,由于有效降水量增加8.2%,超过了作物需水量增加7.4%的影响,净灌溉需水量减少1.4%。豫西三门峡、孟津和豫西南栾川、西峡等4站在各生育期内净灌溉需水量均有不同程度的增加。     

Climate change response in Europe: what’s the reality? Analysis of adaptation and mitigation plans from 200 urban areas in 11 countries

Urban areas are pivotal to global adaptation and mitigation efforts. But how do cities actually perform in terms of climate change response? This study sheds light on the state of urban climate change adaptation and mitigation planning across Europe. Europe is an excellent test case given its advanced environmental policies and high urbanization. We performed a detailed analysis of 200 large and medium-sized cities across 11 European countries and analysed the cities’ climate change adaptation and mitigation plans. We investigate the regional distribution of plans, adaptation and mitigation foci and the extent to which planned greenhouse gas (GHG) reductions contribute to national and international climate objectives. To our knowledge, it is the first study of its kind as it does not rely on self-assessment (questionnaires or social surveys). Our results show that 35 % of European cities studied have no dedicated mitigation plan and 72 % have no adaptation plan. No city has an adaptation plan without a mitigation plan. One quarter of the cities have both an adaptation and a mitigation plan and set quantitative GHG reduction targets, but those vary extensively in scope and ambition. Furthermore, we show that if the planned actions within cities are nationally representative the 11 countries investigated would achieve a 37 % reduction in GHG emissions by 2050, translating into a 27 % reduction in GHG emissions for the EU as a whole. However, the actions would often be insufficient to reach national targets and fall short of the 80 % reduction in GHG emissions recommended to avoid global mean temperature rising by 2 °C above pre-industrial levels.     

Shifts in African crop climates by 2050, and the implications for crop improvement and genetic resources conservation

Increased understanding of the substantial threat climate change poses to agriculture has not been met with a similarly improved understanding of how best to respond. Here we examine likely shifts in crop climates in Sub-Saharan Africa under climate change to 2050, and explore the implications for agricultural adaptation, with particular focus on identifying priorities in crop breeding and the conservation of crop genetic resources. We find that for three of Africa's primary cereal crops – maize, millet, and sorghum – expected changes in growing season temperature are considerable and dwarf changes projected for precipitation, with the warmest recent temperatures on average cooler than almost 9 out of 10 expected observations by 2050. For the “novel” crop climates currently unrepresented in each country but likely extant there in 2050, we identify current analogs across the continent. The majority of African countries will have novel climates over at least half of their current crop area by 2050. Of these countries, 75% will have novel climates with analogs in the current climate of at least five other countries, suggesting that international movement of germplasm will be necessary for adaptation. A more troubling set of countries – largely the hotter Sahelian countries – will have climates with few analogs for any crop. Finally, we identify countries, such as Sudan, Cameroon, and Nigeria, whose current crop areas are analogs to many future climates but that are poorly represented in major genebanks – promising locations in which to focus future genetic resource conservation efforts.     

企业管理人员气候变化意识及影响因素分析

基于对企业管理人员进行气候变化意识的问卷调查,对被调查者关于气候变化的认知指数、行为指数和意识指数3个指标进行评价,对被调查者的背景对其气候变化意识的影响作出分析。分析结果表明,产业类型、企业类型、企业规模和工作部门对被调查者认知指数的影响显著,企业规模对被调查者行为指数的影响显著,年龄、学历、企业类型、企业规模和工作部门对被调查者意识指数的影响显著。26～35岁年龄段的企业管理人员的气候变化意识水平高于其他年龄段,研究生及以上学历的企业管理人员的气候变化意识水平要高于本科及以下的企业管理人员,国有企业的管理人员的气候变化意识水平要高于私营企业的管理人员,企业规模越大,其管理人员的气候变化意识水平越高,各部门管理人员中技术类管理人员的气候变化意识水平最高。     

Probabilistic evaluation of climate change impacts on paddy rice productivity in Japan

Projecting the impacts of climate change includes various uncertainties from physical, biophysical, and socioeconomic processes. Providing a more comprehensive impact projection that better represents the uncertainties is a priority research issue. We used an ensemble-based projection approach that accounts for the uncertainties in climate projections associated with general circulation models (GCMs) and biophysical and empirical parameter values in a crop model. We applied the approach to address the paddy rice yield change in Japan in the 2050s (2046–2065) and 2090s (2081–2100) relative to the 1990s (1981–2000). Seventeen climate projections, nine (eight) climate projections performed by seven (six) GCMs conditional on the Special Report on Emission Scenarios (SRES) A1B (A2), were included in this projection. In addition, 50 sets of biophysical and empirical parameter values of a large-scale process-based crop model for irrigated paddy rice were included to represent the uncertainties of crop parameter values. The planting windows, cultivation practices, and crop cultivars in the future were assumed to be the same as the level in the baseline period (1990s). The resulting probability density functions conditioned on SRES A1B and A2 indicate projected median yield changes of +?17.2% and +?26.9% in Hokkaido, the northern part of Japan, in the 2050s and 2090s with 90% probability intervals of (??5.2%, +?40.3%) and (+?6.3%, +?51.2%), relative to the 1990s mean yield, respectively. The corresponding values in Aichi, on the Pacific side of Western Japan, are 2.2% and ??0.8%, with 90% probability intervals of (??15.0%, +?14.9%) and (??33.4%, +?17.9%), respectively. We also provided geographical maps of the probability that the future 20-year mean yield will decrease and that the future standard deviation of yield for 20 years will increase. Finally, we investigated the relative contributions of the climate projection and crop parameter values to the uncertainty in projecting yield change in the 2090s. The choice of GCM yielded a relatively larger spread of projected yield changes than that of the other factors. The choice of crop parameter values could be more important than that of GCM in a specific prefecture.     

Projections of uncertainties in climate change scenarios into expected winter wheat yields

Summary The crop model CERES-Wheat in combination with the stochastic weather generator were used to quantify the effect of uncertainties in selected climate change scenarios on the yields of winter wheat, which is the most important European cereal crop. Seven experimental sites with the high quality experimental data were selected in order to evaluate the crop model and to carry out the climate change impact analysis. The analysis was based on the multi-year crop model simulations run with the daily weather series prepared by the stochastic weather generator. Seven global circulation models (GCMs) were used to derive the climate change scenarios. In addition, seven GCM-based scenarios were averaged in order to derive the average scenario (AVG). The scenarios were constructed for three time periods (2025, 2050 and 2100) and two SRES emission scenarios (A2 and B1). The simulated results showed that: (1) Wheat yields tend to increase (40 out of 42 applied scenarios) in most locations in the range of 7.5–25.3% in all three time periods. In case of the CCSR scenario that predicts the most severe increase of air temperature, the yields would be reduced by 9.6% in 2050 and by 25.8% in 2100 if the A2 emission scenario would become reality. Differences between individual scenarios are large and statistically significant. Particularly for the time periods 2050 and 2100 there are doubts about the trend of the yield shifts. (2) The site effect was caused by the site-specific soil and climatic conditions. Importance of the site influence increases with increasing severity of imposed climatic changes and culminates for the emission scenario A2 and the time period 2100. The sustained tendency benefiting two warmest sites has been found as well as more positive response to the changed climatic conditions of the sites with deeper soil profiles. (3) Temperature variability proved to be an important factor and influenced both mean and standard deviation of the yields. Change of temperature variability by more than 25% leads to statistically significant changes in yield distribution. The effect of temperature variability decreases with increased values of mean temperature. (4) The study proved that the application of the AVG scenarios – despite possible objections of physical inconsistency – might be justifiable and convenient in some cases. It might bring results comparable to those derived from averaging outputs based on number of scenarios and provide more robust estimate than the application of only one selected GCM scenario.     

Coupling biophysical and micro-economic models to assess the effect of mitigation measures on greenhouse gas emissions from agriculture

Agricultural soils are a major source of atmospheric nitrous oxide (N₂O), a potent greenhouse gas (GHG). Because N₂O emissions strongly depend on soil type, climate, and crop management, their inventory requires the combination of biophysical and economic modeling, to simulate farmers’ behavior. Here, we coupled a biophysical soil-crop model, CERES-EGC, with an economic farm type supply model, AROPAj, at the regional scale in northern France. Response curves of N₂O emissions to fertilizer nitrogen (Nf) inputs were generated with CERES-EGC, and linearized to obtain emission factors. The latter ranged from 0.001 to 0.0225 kg N₂O-N kg^???1 Nf, depending on soil and crop type, compared to the fixed 0.0125 value of the IPCC guidelines. The modeled emission factors were fed into the economic model AROPAj which relates farm-level GHG emissions to production factors. This resulted in a N₂O efflux 20% lower than with the default IPCC method. The costs of abating GHG emissions from agriculture were calculated using a first-best tax on GHG emissions, and a second-best tax on their presumed factors (livestock size and fertilizer inputs). The first-best taxation was relatively efficient, achieving an 8% reduction with a tax of 11 €/ t-CO₂-equivalent, compared to 68 €/t-CO₂ eq for the same target with the second-best scheme.     

Climate change impacts on regional rice production in China

Rice (Oryza sativa L.) production is an important contributor to China’s food security. Climate change, and its impact on rice production, presents challenges in meeting China’s future rice production requirements. In this study, we conducted a comprehensive analysis of how rice yield responds to climate change under different scenarios and assessed the associated simulation uncertainties of various regional-scale climate models. Simulation was performed based on a regional calibrated crop model (CERES-Rice) and spatially matched climatic (from 17 global climate models), soil, management, and cultivar parameters. Grain-filling periods for early rice were shortened by 2–7 days in three time slices (2030s, 2050s, and 2070s), whereas grain-filling periods for late rice were shortened by 10–19 days in three time slices. Most of the negative effects of climate change were predicted to affect single-crop rice in central China. Average yields of single-crop rice treated with CO₂ fertiliser in central China were predicted to be reduced by 10, 11, and 11% during the 2030s, 2050s, and 2070s, respectively, compared to the 2000s, if planting dates remained unchanged. If planting dates were optimised, single-crop rice yields were predicted to increase by 3, 7, and 11% during the 2030s, 2050s, and 2070s, respectively. In response to climate changes, early and single-crop rice should be planted earlier, and late rice planting should be delayed. The predicted net effect would be to prolong the grain-filling period and optimise rice yield.     

Analysis of farm performance in Europe under different climatic and management conditions to improve understanding of adaptive capacity

The aim of this paper is to improve understanding of the adaptive capacity of European agriculture to climate change. Extensive data on farm characteristics of individual farms from the Farm Accountancy Data Network (FADN) have been combined with climatic and socio-economic data to analyze the influence of climate and management on crop yields and income and to identify factors that determine adaptive capacity. A multilevel analysis was performed to account for regional differences in the studied relationships. Our results suggest that socio-economic conditions and farm characteristics should be considered when analyzing effects of climate conditions on farm yields and income. Next to climate, input intensity, economic size and the type of land use were identified as important factors influencing spatial variability in crop yields and income. Generally, crop yields and income are increasing with farm size and farm intensity. However, effects differed among crops and high crop yields were not always related to high incomes, suggesting that impacts of climate and management differ by impact variable. As farm characteristics influence climate impacts on crop yields and income, they are good indicators of adaptive capacity at farm level and should be considered in impact assessment models. Different farm types with different management strategies will adapt differently.     

Climate change, ambient ozone, and health in 50 US cities

We investigated how climate change could affect ambient ozone concentrations and the subsequent human health impacts. Hourly concentrations were estimated for 50 eastern US cities for five representative summers each in the 1990s and 2050s, reflecting current and projected future climates, respectively. Estimates of future concentrations were based on the IPCC A2 scenario using global climate, regional climate, and regional air quality models. This work does not explore the effects of future changes in anthropogenic emissions, but isolates the impact of altered climate on ozone and health. The cities’ ozone levels are estimated to increase under predicted future climatic conditions, with the largest increases in cities with present-day high pollution. On average across the 50 cities, the summertime daily 1-h maximum increased 4.8 ppb, with the largest increase at 9.6 ppb. The average number of days/summer exceeding the 8-h regulatory standard increased 68%. Elevated ozone levels correspond to approximately a 0.11% to 0.27% increase in daily total mortality. While actual future ozone concentrations depend on climate and other influences such as changes in emissions of anthropogenic precursors, the results presented here indicate that with other factors constant, climate change could detrimentally affect air quality and thereby harm human health.     

Postponing emission reductions from 2020 to 2030 increases climate risks and long-term costs

Substantially postponing the emission reductions, compared to the ranges indicated in IPCC’s recent assessment for 2020 as required for meeting the longterm 2°C target, increases the risk of exceeding this target. The costs of a delay strategy are lower in the short term, but leads to higher costs in the longer term. The analysis shows if the emission reductions are postponed to 2030 it is not likely that higher emissions from the earlier years can be fully compensated in future decades in a so-called ‘delayed action scenario’. A full compensation would require emission reduction rates in the coming decades that are much higher than those found in the scenario literature. Without compensation, the risk of exceeding the global temperature rise target of 2°C will increase. This confirms that it is not only the reduction commitments for 2050 that determine the risk of exceeding the 2°C target, but also the path between now and 2050. To meet this 2°C target, more ambitious 2020 reduction targets are needed for the developed and developing countries than those that have been pledged so far.     

South African crop farming and climate change: An economic assessment of impacts

This paper assesses the economic impact of the expected adverse changes in the climate on crop farming in South Africa using a revised Ricardian model and data from farm household surveys, long-term climate data, major soils and runoffs. Mean annual estimates indicate that a 1% increase in temperature will lead to about US$ 80.00 increase in net crop revenue while a 1 mm/month fall in precipitation leads to US$ 2.00 fall, but with significant seasonal differences in impacts. There are also significant spatial differences and across the different farming systems. Using selected climate scenarios, the study predicts that crop net revenues are expected to fall by as much as 90% by 2100 with small-scale farmers been most affected. Policies therefore need to be fine-tuned and more focused to take advantage of the relative benefits across seasons, farming systems and spatially, and by so doing climate change may be beneficial rather than harmful.     

Testing GISS-MM5 physics configurations for use in regional impacts studies

The Mesoscale Modeling System Version 5 (MM5) was one-way nested to the Goddard Institute for Space Studies global climate model (GISS GCM), which provided the boundary conditions for present (1990s) and future (IPCC SRES A2 scenario, 2050s) five-summer “time-slice” simulations over the continental and eastern United States. Five configurations for planetary boundary layer, cumulus parameterization, and radiation scheme were tested, and one set was selected for use in the New York City Climate and Health Project—a multi-disciplinary study investigating the effects of climate change and land-use change on human health in the New York metropolitan region. Although hourly and daily data were used in the health project, in this paper we focus on long-term current and projected mean climate change. The GISS-MM5 was very sensitive to the choice of cumulus parameterization and planetary boundary layer scheme, leading to significantly different temperature and precipitation outcomes for the 1990s. These differences can be linked to precipitation type (convective vs. non-convective), to their effect on solar radiation received at the ground, and ultimately to surface temperature. The projected changes in climate (2050s minus 1990s) were not as sensitive to choice of model physics combination. The range of the projected surface temperature changes at a given grid point among the model versions was much less than the mean change for all five model configurations, indicating relative consensus for simulating surface temperature changes among the different model projections. The MM5 versions, however, offer less consensus regarding 1990s to 2050s changes in precipitation amounts. All of the projected 2050s temperature changes were found to be significant at the 95th percent confidence interval, while the majority of the precipitation changes were not.     

Adapting agriculture to climate change: a review

The agricultural sector is highly vulnerable to future climate changes and climate variability, including increases in the incidence of extreme climate events. Changes in temperature and precipitation will result in changes in land and water regimes that will subsequently affect agricultural productivity. Given the gradual change of climate in the past, historically, farmers have adapted in an autonomous manner. However, with large and discrete climate change anticipated by the end of this century, planned and transformational changes will be needed. In light of these, the focus of this review is on farm-level and farmers responses to the challenges of climate change both spatially and over time. In this review of adapting agriculture to climate change, the nature, extent, and causes of climate change are analyzed and assessed. These provide the context for adapting agriculture to climate change. The review identifies the binding constraints to adaptation at the farm level. Four major priority areas are identified to relax these constraints, where new initiatives would be required, i.e., information generation and dissemination to enhance farm-level awareness, research and development (R&D) in agricultural technology, policy formulation that facilitates appropriate adaptation at the farm level, and strengthening partnerships among the relevant stakeholders. Forging partnerships among R&D providers, policy makers, extension agencies, and farmers would be at the heart of transformational adaptation to climate change at the farm level. In effecting this transformational change, sustained efforts would be needed for the attendant requirements of climate and weather forecasting and innovation, farmer’s training, and further research to improve the quality of information, invention, and application in agriculture. The investment required for these would be highly significant. The review suggests a sequenced approach through grouping research initiatives into short-term, medium-term, and long-term initiatives, with each initiative in one stage contributing to initiatives in a subsequent stage. The learning by doing inherent in such a process-oriented approach is a requirement owing to the many uncertainties associated with climate change.     

Effect of topography on farm-scale spatial variation in extreme temperatures in the Southern Mallee of Victoria, Australia

Extreme temperatures around flowering of wheat have the potential to reduce grain yield and at farm scale their impact can be spatially variable depending on topography. Twenty-five data loggers were installed at 0.8-m height across a 164-ha farm in the southern Mallee of Victoria, Australia to spatially record the daily course of temperatures around the average date of flowering of wheat in the region. The experiment was conducted during 2-years period. In 1 year, the farm had no crop cover and in another year the farm had a wheat crop. Multiple linear regression analysis techniques were used to fit models relating daily extreme temperatures to the farm topographic features of elevation, aspect and slope, and the average maximum and minimum temperatures of each day at the farm in order to identify areas of high risk of extreme temperatures around the time of the flowering of wheat. The fitted regression models explained 90% and 97% of the variability in maximum and minimum temperatures, respectively, when the farm had no crop cover and 80% and 94% of the variability in maximum and minimum temperatures, respectively, when the farm had a wheat crop cover. When the farm had no crop, only minimum temperature was partially explained by the topography however, both maximum and minimum temperatures were partially explained by the topography when the farm had a wheat crop. From this study it was concluded that, (1) high temperature variations were found across the farm (2) temperature variations were only partially explained from the developed model presumably due to the flatter topography of the farm and (3) the relationships obtained from this study could be used in a crop model which can explain variation in grain yield based on the topography of a field.     

The Consequences of CO2 Stabilisation for the Impacts of Climate Change

This paper reports the main results of an assessment of the global-scale implications of the stabilisation of atmospheric CO₂ concentrations at 750 ppm (by 2250) and 550 ppm (by 2150), in relationto a scenario of unmitigated emissions. The climate change scenarios were derived from simulation experiments conducted with the HadCM2 global climate model and forced with the IPCC IS92a, S750 and S550 emissions scenarios. The simulated changes in climate were applied to an observed global baseline climatology, and applied with impacts models to estimate impacts on natural vegetation, water resources, coastal flood risk and wetland loss, crop yield and food security, and malaria. The studies used a single set of population and socio-economic scenarios about the future that are similar to those adopted in the IS92a emissions scenario.An emissions pathway which stabilises CO₂ concentrations at 750 ppmby the 2230s delays the 2050 temperature increase under unmitigated emissions by around 50 years. The loss of tropical forest and grassland which occurs by the 2050s under unmitigated emissions is delayed to the 22nd century, and the switch from carbon sink to carbon source is delayed from the 2050s to the 2170s. Coastal wetland loss is slowed. Stabilisation at 750 ppm generally has relatively little effect on the impacts of climate change on water resource stress, and populations at risk of hunger or falciparum malaria until the 2080s.A pathway which stabilises CO₂ concentrations at 550 ppm by the 2170s delays the 2050 temperature increase under unmitigated emissions by around 100 years. There is no substantial loss of tropical forest or grassland, even by the 2230s, although the terrestrial carbon store ceases to act as a net carbon sink by around 2170 (this time because the vegetation has reached a new equilibrium with the atmosphere). Coastal wetland loss is slowed considerably, and the increase in coastal flood risk is considerably lower than under unmitigated emissions. CO₂ stabilisation at 550 ppm reduces substantially water resource stress, relative to unmitigated emissions, but has relatively little impact on populations at risk of falciparum malaria, and may even cause more people to be at risk of hunger. While this study shows that mitigation avoids many impacts, particularly in the longer-term (beyond the 2080s), stabilisation at 550 ppm appears to be necessary to avoid or significantly reduce most of the projected impacts in the unmitigated case.     

Simulating Crop Net Primary Production in China from 2000 to 2050 by Linking the Crop-C model with a FGOALS＇s Model Climate Change Scenario

Net primary production （NPP） of crop represents the capacity of sequestrating atmospheric CO2 in agro-ecosystem, and it plays an important role in terrestrial carbon cycling. By linking the Crop-C model with climate change scenario projected by a coupled GCM FGOALS via geographical information system （GIS） techniques, crop NPP in China was simulated from 2000 to 2050. The national averaged surface air temperature from FGOALS is projected to increase by 1.0℃ over this period and the corresponding atmospheric CO2 concentration is 535 ppm by 2050 under the IPCC A1B scenario. With a spatial resolution of 10 ×10 km^2, model simulation indicated that an annual average increase of 0.6 Tg C yr^-1 （Tg=10^12 g） would be possible under the A1B scenario. The NPP in the late 2040s would increase by 5% （30 Tg C） within the 98×10^6 hm^2 cropland area in contrast with that in the early 2000s. A further investigation suggested that changes in the NPP would not be evenly distributed in China. A higher increase would occur in a majority of regions located in eastern and northwestern China, while a slight reduction would appear in Hebei and Tianjin in northern China. The spatial characteristics of the crop NPP change are attributed primarily to the uneven distribution of temperature change.     

Projected climate change impacts on skiing and snowmobiling: A case study of the United States

We use a physically-based water and energy balance model to simulate natural snow accumulation at 247 winter recreation locations across the continental United States. We combine this model with projections of snowmaking conditions to determine downhill skiing, cross-country skiing, and snowmobiling season lengths under baseline and future climates, using data from five climate models and two emissions scenarios. Projected season lengths are combined with baseline estimates of winter recreation activity, entrance fee information, and potential changes in population to monetize impacts to the selected winter recreation activity categories for the years 2050 and 2090. Our results identify changes in winter recreation season lengths across the United States that vary by location, recreational activity type, and climate scenario. However, virtually all locations are projected to see reductions in winter recreation season lengths, exceeding 50% by 2050 and 80% in 2090 for some downhill skiing locations. We estimate these season length changes could result in millions to tens of millions of foregone recreational visits annually by 2050, with an annual monetized impact of hundreds of millions of dollars. Comparing results from the alternative emissions scenarios shows that limiting global greenhouse gas emissions could both delay and substantially reduce adverse impacts to the winter recreation industry.