Climate Change, Agriculture, and Water Quality in the Chesapeake Bay Region

Research on climate change and agriculture has largely focused on production, food prices, and producer incomes. However, societal interest in agriculture is much broader than these issues. The objective of this paper is to analyze the potential impacts of climate change on an important negative externality from agriculture, water quality. We construct a simulation model of maize production in twelve watersheds within the U.S. Chesapeake Bay Region that has economic and watershed components linking climate to productivity, production decisions by maize farmers, and nitrogen loadings delivered to the Chesapeake Bay. Maize is an important crop to study because of its importance to the region's agriculture and because it is a major source of nutrient pollution. The model is run under alternative scenarios regarding the future climate, future baseline (without any climate change), whether farmers respond to climate change, whether there are carbon dioxide (CO₂) enrichment effects on maize production, and whether agricultural prices facing the region change due to climate change impacts on global agricultural commodity markets. The simulation results differ from one scenario to another on the magnitude and direction of change in nitrogen deliveries to the Chesapeake Bay. The results are highly sensitive to the choice of future baseline scenario and to whether there are CO₂ enrichment effects. The results are also highly sensitive to assumptions about the impact of climate change on commodity prices facing farmers in the Chesapeake Bay region. The results indicate that economic responses by farmers to climate change definitely matter. Assuming that farmers do not respond to changes in temperature, precipitation, and atmosphericCO₂ levels could lead to mistaken conclusions about the magnitude and direction of environmental impacts.     

内蒙古典型草原区近40年气候变化及其对土壤水分的影响

分析气候变化对草原区土壤水分的影响对了解草原退化原因、恢复草原生态环境有重要的指导意义。根据近40年气象资料和近20年的土壤水分观测资料,利用线性趋势等数理统计方法,分析了内蒙古典型草原区气候变化趋势和对土壤水分变化的影响,得出内蒙古典型草原区近40年气候变化趋势与全球气候变化规律相似;影响土壤湿度的气象因子主要是降水和蒸发,温度通过影响蒸发而间接影响土壤湿度,蒸降差是分析气候变化对土壤水分影响的直观指标。气候变暖导致蒸发加剧,在降水增加不明显的条件下,加速了土壤干旱化程度。     

全球气候变化对中国森林生态系统的影响

人类活动所引起的温室效应及由此造成的全球气候变化和对全球生态环境的影响正引起人们越来越多的重视.作为全球陆地生态系统一个重要组分,中国的森林生态系统对未来全球气候变化的响应更是人们关注的重点.作者系统地总结了全球气候变化对中国森林生态系统分布、生态系统生产力、森林树种以及森林土壤的影响,指出了现阶段该领域研究中存在的一些问题,并对今后需要加强的一些核心问题与研究重点作了展望.     

Nutrient cycling and biomass growth at a North American hardwood site in relation to climate change: ForSVA assessments

The biomass growth and nutrient cycling model ForSVA (forest-soil-vegetation-atmosphere model) is used to analyze potential changes in nutrient cycling (Ca, Mg, K, N, S) and forest biomass production in response to four climate-change scenarios. The analysis is done for an old-growth hardwood stand within the Turkey Lakes watershed north of Lake Superior, Ontario. With ForSVA, any effects due to species interactions, competition, and resulting species shifts are not addressed explicitly. Instead, the calculations are based on functional relationships that primarily respond to soil and climate conditions in general, and to structural changes within the forest itself. The simulations cover a period of about 200 years, and suggest that a principal change in annual pattern of soil moisture is to be expected for the UKMO climate scenario, and that this scenario will likely induce a major change of vegetation covertype resulting from major changes in seasonal soil moisture conditions and a general lack of snow during winter. In contrast, the OSU, GISS and GFDL scenarios should not cause a principal change in forest type, but the soil will be somewhat drier than what is currently the case. However, increased precipitation rates and/or air temperatures during summer and spring should, in combination, increase actual evapotranspiration rates, and such increases should increase net primary production. For example, calculations with GFDL suggest that cumulative wood biomass at the Turkey Lakes site can be expected to increase by 25%. Foliage biomass and fine root production can be expected to increase by 70% from current conditions. It is assumed that within-tree allocation of photosynthate is not affected by climate.     

吉林省春秋季林火气象指数的建立及其变化特征

以吉林省为例,利用该省1952—2010年森林火灾(简称林火,下同)次数资料和全省气象站资料,分析该省林火次数时间变化特征及其与气象条件的关系,利用水分平衡法和统计回归方法建立林火次数气候影响评价模型并对其进行比较;在此基础上,利用水分平衡模型建立林火指数时间变化序列。结果表明,林火次数与降水、相对湿度、气温、风速等气象因子关系密切,水分平衡模型的气候影响评价效果优于统计回归模型;近62 a来吉林省林火指数和次数均呈增加趋势,表明气候变化有利于林火发生;2000年之后进入春、秋季林火多发期。     

Modeling the eco-hydrologic response of a Mediterranean type ecosystem to the combined impacts of projected climate change and altered fire frequencies

Global Climate Models (GCMs) project moderate warming along with increases in atmospheric CO₂ for California Mediterranean type ecosystems (MTEs). In water-limited ecosystems, vegetation acts as an important control on streamflow and responds to soil moisture availability. Fires are also key disturbances in semi-arid environments, and few studies have explored the potential interactions among changes in climate, vegetation dynamics, hydrology, elevated atmospheric CO2 concentrations and fire. We model ecosystem productivity, evapotranspiration, and summer streamflow under a range of temperature and precipitation scenarios using RHESSys, a spatially distributed model of carbon–water interactions. We examine the direct impacts of temperature and precipitation on vegetation productivity and impacts associated with higher water-use efficiency under elevated atmospheric CO2. Results suggest that for most climate scenarios, biomass in chaparral-dominated systems is likely to increase, leading to reductions in summer streamflow. However, within the range of GCM predictions, there are some scenarios in which vegetation may decrease, leading to higher summer streamflows. Changes due to increases in fire frequency will also impact summer streamflow but these will be small relative to changes due to vegetation productivity. Results suggest that monitoring vegetation responses to a changing climate should be a focus of climate change assessment for California MTEs.     

Potential climate change impacts on the probability of wind damage in a south Swedish forest

We estimated how the possible changes in wind climate and state of the forest due to climate change may affect the probability of exceeding critical wind speeds expected to cause wind damage within a forest management unit located in Southern Sweden. The topography of the management unit was relatively gentle and the forests were dominated by Norway spruce (Picea abies (L.) Karst.). We incorporated a model relating the site index (SI) to the site productivity into the forest projection model FTM. Using estimated changes in the net primary production (NPP) due to climate change and assuming a relative change in NPP equal to a relative change in the site productivity, we simulated possible future states of the forest under gradual adjustment of SI in response to climate change. We estimated changes in NPP by combining the boreal-adapted BIOMASS model with four regional climate change scenarios calculated using the RCAO model for the period 2071–2100 and two control period scenarios for the period 1961–1990. The modified WINDA model was used to calculate the probability of wind damage for individual forest stands in simulated future states of the forest. The climate change scenarios used represent non-extreme projections on a 100-year time scale in terms of global mean warming. A 15–40% increase in NPP was estimated to result from climate change until the period 2071–2100. Increasing sensitivity of the forest to wind was indicated when the management rules of today were applied. A greater proportion of the calculated change in probability of wind damage was due to changes in wind climate than to changes in the sensitivity of the forest to wind. While regional climate scenarios based on the HadAM3H general circulation model (GCM) indicated no change (SRES A2 emission scenario) or a slightly reduced (SRES B2 emission scenario) probability of wind damage, scenarios based on the ECHAM4/OPYC3 GCM indicated increased probability of wind damage. The assessment should, however, be reviewed as the simulation of forest growth under climate change as well as climate change scenarios are refined.     

Climate change influences on agricultural research productivity

This paper investigates the impacts of climate change on US returns to research investments on agricultural productivity. We examine this using a historical data set in a panel time-series econometric model of state agricultural productivity. The fitted model allows derivation of the rate of return to research investments and the effects of climate change thereon. We find climate change is altering the rate of return to public agricultural research in a spatially heterogeneous manner. Increases in precipitation raise returns to research, while the impact of higher temperatures varies by region, are negative in Southern areas, particularly the Southern Plains, and positive in northern areas. We simulate the impact of projected climate change and find cases where agricultural productivity is reduced, for example in the Southern Plains. Finally, we consider the amount of research investment that is needed to adapt to overcome the impacts of climate change on agricultural productivity. Under the 2100 scenario, a 7–17 % increase in total US research investment is needed to adapt, but effects by region differ greatly—some requiring little changes and the Southern Plain requiring an increase as high as 57 %.     

Challenges in the Application of Existing Process-Based Models to Predict the Effect of Climate Change on C Pools in Forest Ecosystems

Process-based models used to investigate forest ecosystem response to climate change were not necessarily developed to include the effect of carbon dioxide (CO₂) and temperature increases on physiological processes. Simulation of the impacts of climate change with such models may lead to questionable predictions. It is generally believed that significant shifts in the performance of black spruce (Picea mariana [Mill] B.S.P.) will occur under climate change. This species, which accounts for 64% of Ontario's coniferous growing stock and 80% of the annual allowable cut, represents important economic activity throughout the boreal forest region. Forest management planning requires relatively accurate productivity estimates. Thus, it is imperative to ensure that process-based models realistically predict the effect of climate change. In this study, CENTURY and FOREST-BGC models were calibrated for a productive, upland black spruce stand in northwestern Ontario. Even though both models predicted similar relative outcomes after 100 years of climate change, they disagreed on the impacts of temperature in combination with an increase in CO₂. Also, absolute amounts of carbon sequestered varied with climate change scenarios. Comparison of both models indicated that the representation of critical processes in these two forest ecosystem models is incomplete. For instance, the interactive effects of CO₂ and temperature increases on physiological processes at stand and soil levels are not well documented nor are they easily identifiable in the models. Their incorporation into models is therefore problematic. Practitioners must consequently be wary of assumptions about the inclusion of critical processes in models.     

气候变化影响与适应问题的谈判进展

 从《气候变化框架公约》（以下简称《公约》）第一次缔约方会议到目前为止，几乎历次会议都涉及气候变化影响与适应的谈判内容，但谈判进展甚微。通过综述《公约》谈判进程中与适应气候变化有关的主要决定，分析了适应气候变化影响与适应问题谈判的制约因素，最后提出了我国在气候变化影响与适应问题谈判中应持的立场。     

Prediction of Changes in Soil Moisture Associated with Climatic Changes and Their Implications for Vegetation Changes: Waves Model Simulation on Taihang Mountain, China

The WAVES model was used to simulate the effect of global warming on soil moisture on the semi-arid Taihang Mountain in China. Parameters of the WAVES model were first adjusted according to soil moisture data from a field global warming experiment. Then, the reliability of WAVES in predicting soil moisture changes induced by climatic change was confirmed by comparing the simulated and observed soil moisture values under different climatic conditions and plant growth rates of another field treatment. Next, 10 climate change scenarios incorporating increases in temperature and changes in precipitation were designed. When a simulation was conducted using the leaf area index (LAI) growth pattern from a field experiment under the present climatic conditions, the results suggested that the combination of temperature increase and precipitation decrease would greatly decrease soil water content throughout the entire simulation period. On the other hand, only when precipitation increased by 20% and temperatureincreased by 2 °C, the effect of precipitation increase on soil moisture was obviously positive. Although soil moisture conditions in the T2P1 (temperature increase by 2 °C and precipitation increase by 10%) and T4P2 (temperature increase by 4 °C and precipitation increase by 20%) scenarios were slightly better during the rainy season and notmuch changed before the rainy season, the positive effect of 10%precipitation increase on soil moisture was totally offset by moisture decrease caused bya 4 °C temperature increase in the T4P1 scenario. At the same time, the trends of soil-moisture change were highly coincident with predicted changes in productivity. Finally, the predicted LAI values from other studies were combined with the climatic change scenarios and used in the simulation. The results showed that changes in LAI alleviated, at least to some extent, the effects of temperature and precipitation changes on soil moisture.     

Application of a forest succession model to a continentality gradient through Central Europe

The forest succession model FORSKA was applied to a west-east transect across Central Europe using points from a global climate data set. Climate change experiments were undertaken for two general circulation model scenarios and two different site classes. The simulated climate changes lead to reduced forest productivity and a changed species composition on most sites. Under current climate, the broad scale pattern of the climatically driven distribution of forest communities is quite realistically reproduced. However, the resolution of climate data imposes limitations on the simulation of forest dynamics in subcontinental climate, because climate variability and extreme events are not well represented.     

Assessing impacts of climate change on forests: The state of biological modeling

Models that address the impacts of climate change on forests are reviewed at four levels of biological organization: global, regional or landscape, community, and tree. The models are compared for their ability to assess changes in fluxes of biogenic greenhouse gases, land use, patterns of forest type or species composition, forest resource productivity, forest health, biodiversity, and wildlife habitat. No one model can address all of these impacts, but landscape transition models and regional vegetation and land-use models have been used to consider more impacts than the other models. The development of landscape vegetation dynamics models of functional groups is suggested as a means to integrate the theory of both landscape ecology and individual tree responses to climate change. Risk assessment methodologies can be adapted to deal with the impacts of climate change at various spatial and temporal scales. Four areas of research needing additional effort are identified: (1) linking socioeconomic and ecologic models; (2) interfacing forest models at different scales; (3) obtaining data on susceptibility of trees and forest to changes in climate and disturbance regimes; and (4) relating information from different scales.The U.S. Government right to retain a non-exclusive, royalty-free license in and to any copyright is acknowledged.Managed by Martin Marietta Energy Systems, Inc., for the U.S. Department of Energy under contract DE-AC05-84OR21400.     

对IPCC第五次评估报告中有关淡水资源相关结论的解读

IPCC第五次评估报告指出,与淡水资源相关的气候变化风险随着温室气体浓度增加而显著增加。气候变化已经导致区域降水发生显著变化;多年冻土、冰川持续萎缩,积雪不断减少;降雪区春季最大径流量逐渐提前,夏季干旱不断加剧。预估结果表明：21世纪温室气体排放将加剧淡水资源相关风险。如显著减少亚热带干旱地区的地表水和地下水资源,加剧行业之间用水竞争;极端事件（如极端降水）明显影响原水水质,威胁用水安全;气候变化同时将导致农业灌溉用水量增加、能源生产效率降低等不利影响。报告指出需采取硬性基础设施建设和软性制度措施建设相结合的适应措施,加强水资源管理,克服气候变化的负面影响,减少损失。     

Sensitivity of Runoff, Soil Moisture and Reservoir Design to Climate Change in Central Indian River Basins

Climate change due to a doubling of the carbon dioxide in the atmosphere and its possible impacts on the hydrological cycle are a matter of growing concern. Hydrologists are specifically interested in an assessment of the impacts on the occurrence and magnitude of runoff, evapotranspiration, and soil moisture and their temporal and spatial redistribution. Such impacts become all the more important as they may also affect the water availability in the storage reservoirs. This paper examines the regional effects of climate change on various components of the hydrologic cycle viz., surface runoff, soil moisture, and evapotranspiration for three drainage basins of central India. Plausible hypothetical scenarios of precipitation and temperature changes are used as input in a conceptual rainfall-runoff model. The influences of climate change on flood, drought, and agriculture are highlighted. The response of hypothetical reservoirs in these drainage basins to climate variations has also been studied. Results indicate that the basin located in a comparatively drier region is more sensitive to climatic changes. The high probability of a significant effect of climate change on reservoir storage, especially for drier scenarios, necessitates the need of a further, more critical analysis of these effects.     

Precipitation drives interannual variation in summer soil respiration in a Mediterranean-climate, mixed-conifer forest

Predictions of future climate change rely on models of how both environmental conditions and disturbance impact carbon cycling at various temporal and spatial scales. Few multi-year studies, however, have examined how carbon efflux is affected by the interaction of disturbance and interannual climate variation. We measured daytime soil respiration (R _s) over five summers (June–September) in a Sierra Nevada mixed-conifer forest on undisturbed plots and plots manipulated with thinning, burning and their combination. We compared mean summer R _s by year with seasonal precipitation. On undisturbed plots we found that winter precipitation (PPT_w) explained between 77–96% of interannual variability in summer R _s. In contrast, spring and summer precipitation had no significant effect on summer R _s. PPT_w is an important influence on summer R _s in the Sierra Nevada because over 80% of annual precipitation falls as snow between October and April, thus greatly influencing the soil water conditions during the following growing season. Thinning and burning disrupted the relationship between PPT_w and R_s, possibly because of significant increases in soil moisture and temperature as tree density and canopy cover decreased. Our findings suggest that R _s in some moisture-limited ecosystems may be significantly influenced by annual snowpack and that management practices which reduce tree densities and soil moisture stress may offset, at least temporarily, the effect of predicted decreases in Sierran snowpack on R _s.     

Physiologic Plasticity, Evolution, and Impacts of a Changing Climate on Pinus Contorta

Climate response functions for 125 Pinus contorta populations were updated to assess the impact of 16 climate change scenarios on forest productivity. Productivity was defined as the volume of wood expected per hectare at age 20 and was calculated as the product of predicted individual tree volumes, an initial stocking (1600 trees ha^–1), and predicted survival. Impact was considered according to the transient effects of a changing climate governed by (1) physiological plasticity in the contemporary generation and (2) long-term evolutionary adjustments that provide adaptedness and optimize productivity in future generations. Direct short-term plastic responses were geographically complex and had repercussions throughout the species' distribution even when temperature fluctuations were small (± 1 ° C) and changes in distribution were inconsequential. Evolutionary adjustments ameliorated negative short-term impacts while enhancing the positive. Scenarios that encompassed predictions for global warming produced short-term impacts that were negative in the south and positive in the north, but subsequent evolutionary adjustments projected substantial increases in productivity. The long-term adjustments may require only 1 to 3 generations in the north but 6 to 12 generations in the south, thereby taking between 200 and 1200 years.     

An essay on the impact of climate change on US agriculture: weather fluctuations, climatic shifts, and adaptation strategies

The impact of climate change on US agriculture has been debated for more than two decades, but the estimates ranged from no damage at the lower end to 80 % losses of grain yields at the higher end. This essay aims to help understand such divergent predictions by clarifying the concepts of weather and climate. First, the widely-read panel fixed effects models capture only the impacts of weather fluctuations but not of climate normals. Random weather fluctuations and climatic shifts are two different meteorological events and they have distinct implications on farming decisions. The former is perceived as random while the latter is perceived as non-random by the farmers. Using the historical corn yield data in the US, I explain the differences between the impact of random weather and that of climate change. Second, adaptation strategies to climatic changes and increased climate risks cannot be accounted for by the panel fixed effects models. Using the farm household data collected in sub-Saharan Africa and Latin America, I discuss quantitative significance of modeling adaptation strategies in the estimates of climate damage. Distinction between random weather fluctuations and climatic shifts is critical in modeling farming decisions, as they are fundamental to climate science, but is poorly understood by the impact researchers.     

Environmental change in grasslands: Assessment using models

Modeling studies and observed data suggest that plant production, species distribution, disturbance regimes, grassland biome boundaries and secondary production (i.e., animal productivity) could be affected by potential changes in climate and by changes in land use practices. There are many studies in which computer models have been used to assess the impact of climate changes on grassland ecosystems. A global assessment of climate change impacts suggest that some grassland ecosystems will have higher plant production (humid temperate grasslands) while the production of extreme continental steppes (e.g., more arid regions of the temperate grasslands of North America and Eurasia) could be reduced substantially. All of the grassland systems studied are projected to lose soil carbon, with the greatest losses in the extreme continental grassland systems. There are large differences in the projected changes in plant production for some regions, while alterations in soil C are relatively similar over a range of climate change projections drawn from various General Circulation Models (GCM's). The potential impact of climatic change on cattle weight gains is unclear. The results of modeling studies also suggest that the direct impact of increased atmospheric CO₂ on photosynthesis and water use in grasslands must be considered since these direct impacts could be as large as those due to climatic changes. In addition to its direct effects on photosynthesis and water use, elevated CO₂ concentrations lower N content and reduce digestibility of the forage.     

Response of a Grassland Ecosystem to Climate Change in a Theoretical Model

The response of a grassland ecosystem to climate change is discussed within the context of a theoretical model.An optimization approach,a conditional nonlinear optimal perturbation related to parameter(CNOP-P) approach,was employed in this study.The CNOP-P,a perturbation of moisture index in the theoretical model,represents a nonlinear climate perturbation.Two kinds of linear climate perturbations were also used to study the response of the grassland ecosystem to different types of climate changes.The results show that the extent of grassland ecosystem variation caused by the CNOP-P-type climate change is greater than that caused by the two linear types of climate change.In addition,the grassland ecosystem affected by the CNOP-P-type climate change evolved into a desert ecosystem,and the two linear types of climate changes failed within a specific amplitude range when the moisture index recovered to its reference state.Therefore,the grassland ecosystem response to climate change was nonlinear.This study yielded similar results for a desert ecosystem seeded with both living and wilted biomass litter.The quantitative analysis performed in this study also accounted for the role of soil moisture in the root zone and the shading effect of wilted biomass on the grassland ecosystem through nonlinear interactions between soil and vegetation.The results of this study imply that the CNOP-P approach is a potentially effective tool for assessing the impact of nonlinear climate change on grassland ecosystems.