Modeling of Ecological Footprint and Climate Change Impacts on Food Security of the Hill Tracts of Chittagong in Bangladesh

This paper presents an integrated and dynamic model for the management of the uplands of the Hill Tracts of Chittagong to predict food security and environmental loading for gradual transition of shifting agriculture land into horticulture crops and teak plantation, and crop land into tobacco cultivation. Food security status for gradual transmission of shifting agriculture land into horticulture crops and teak plantation, and crop land into tobacco cultivation is the best option for food security, but this causes the highest environmental loading resulting from tobacco cultivation. Considering both food security and environmental degradation in terms of ecological footprint, the best option is gradual transition of shifting agriculture land into horticulture crops which provides moderate increase in the food security with a relatively lower environmental degradation in terms of ecological footprint. Crop growth model InfoCrop was used to predict the climate change impacts on rice and maize production in the uplands of the Hill Tracts of Chittagong. Climate change impacts on the yields of rice and maize of three treatments of temperature, carbon dioxide and rainfall change (+0 °C, +0 ppm and +0 % rainfall), (+2 °C, +50 ppm and 20 % rainfall) and (+2 °C, +100 ppm and 30 % rainfall) were assessed. The yield of rice decreases for treatment 2, but it increases for treatment 3. The yield of maize increases for treatments 2 and 3 since maize is a C₄ plant. There is almost no change in food security at upazila (sub-district) level for the historical climate change scenario, but there is small change in the food security at upazila levels for IPCC climate change scenario.     

global climate change: processes and products – an overview

Our knowledge of global climate change has many uncertainties.Whether global air temperature will increase, by how much, and when,are subject to debate, but there is little doubt that troposphericconcentrations of several trace gases are increasing. While possibleincreases in the average air temperature is a product of these changes,the increases in the trace gases alone will have an effect on agriculture.Increases in the ambient concentrations of carbon dioxide are expectedto have a positive net effect on crop production. In contrast, anyincreases in the penetration of surface-level ultraviolet-B (280–320 nm)radiation, and known increases in surface ozone concentrations, areconsidered to have adverse effects on certain crops. Our presentknowledge of the joint effects on crops of elevated levels of carbondioxide, ultraviolet-B radiation and ozone, and possible alterations in airtemperature and precipitation patterns, is virtually zero. Therefore, anypredictions of the effects of global climate change on agriculture aresubject to significant uncertainties. In contrast, coupling of climatechange (only temperature and precipitation) models to crop productionhas led to a number of future scenarios. In spite of theirpresent limitations, results from these efforts can be useful in planningfor future agriculture.     

Risk of Hunger Under Climate Change, Social Disparity, and Agroproductivity Scenarios

Considering the projected population growth in the twenty-first century, some studies have indicated that global warming may have negative impacts on the risk of hunger. These conclusions were derived based on assumptions related to social and technological scenarios that involve substantial and influential uncertainties. In this paper, focusing on agrotechnology and food access disparity, we analyzed food availability and risk of hunger under the combined scenarios of food demands and agroproductivity with and without climate change by 2100 for the B2 scenario in the Special Report on Emissions Scenarios. The results of this study suggest that (1) future food demand can be satisfied globally under all assumed combined scenarios, and (2) a reduction of food access disparity and increased progress in productivity are just as important as climate change mitigation for reducing the risk of hunger.     

Constructing “not Implausible” Climate and Economic Scenarios for Egypt

A space of “not-implausible” scenarios for Egypt's future under climate change is defined along two dimensions. One depicts representative climate change and climate variability scenarios that span the realm of possibility. Some would not be very threatening. Others portend dramatic reductions in average flows into Lake Nassar and associated increases in the likelihood of year to year shortfalls below critical coping thresholds; these would be extremely troublesome, especially if they were cast in the context of increased political instability across the entire Nile Basin. Still others depict futures along which relatively routine and relatively inexpensive adaptation might be anticipated. The ability to adapt to change and to cope with more severe extremes would, however, be linked inexorably to the second set of social–political–economic scenarios. The second dimension, defined as “anthropogenic” social/economic/political scenarios describe the holistic environment within which the determinants of adaptive capacity for water management, agriculture, and coastal zone management must be assessed. This revised version was published online in July 2006 with corrections to the Cover Date.     

Mesoscale ecohydrological modelling to analyse regional effects of climate change

Hydrological processes and crop growth were simulated for the state of Brandenburg (Germany) using the hydrological/vegetation/water quality model SWIM, which can be applied for mesoscale river basins or regions. Hydrological validation was carried out for three mesoscale river basins in the area. The crop growth module was validated regionally for winter wheat, winter barley and maize. After that the analysis of climate change impacts on hydrology and crop growth was performed, using a transient 1.5 K scenario of climate change for Brandenburg and restricting the crop spectrum to the three above mentioned crops. According to the scenario, precipitation is expected to increase. The impact study was done comparing simulation results for two scenario periods 2022–2030 and 2042–2050 with those for a reference period 1981–1992. The atmospheric CO₂ concentrations for the reference period and two scenario periods were set to 346, 406 and 436 ppm, respectively. Two different methods – an empirical one and a semi-mechanistic one – were used for adjustment of net photosynthesis to altered CO₂. With warming, the model simulates an increase of evapotranspiration (+9.5%, +15.4%) and runoff (+7.0%, +17.2%). The crop yield was only slightly altered under the climate change only scenario (no CO₂ fertilization effect) for barley and maize, and it was reduced for wheat (–6.2%, –10.3%). The impact of higher atmospheric CO₂ compensated for climate-related wheat yield losses, and resulted in an increased yield both for barley and maize compared to the reference scenario. The simulated combined effect of climate change and elevated CO₂ on crop yield was about 7% higher for the C₃ crops when the CO₂ and temperature interaction was ignored. The assumption that stomatal control of transpiration is taking place at the regional scale led to further increase in crop yield, which was larger for maize than for wheat and barley. The regional water balance was practically not affected by the partial stimulation of net photosynthesis due to higher CO₂, while the introduction of stomatal control of regional transpiration reduced evapotranspiration and enlarged notably runoff and ground water recharge.     

Impact of Climate Change on Date Production in Tunisia

Around the Mediterranean basin, climate change is one of the major phenomena affecting agriculture. Therefore, the mode of production and crop management will have to change radically. Our objective in this article is to examine the long-run effects of climate change on date production in Tunisia using panel cointegration covering the period from 1980 to 2014 in 24 regions. The climate of Tunisia differs in our study because we find a Saharan climate in the south and a European climate in the north. The central regions are characterized by a Mediterranean climate. Our empirical results show that the effects of climate and weather variability on date production must be considered a serious threat in Tunisia. In addition, we estimate relatively negative and variable long-run effects of temperature increase and rainfall shortages across regions on date output over the last three decades.     

Modeling economy-wide climate change impacts on Egypt: A case for an integrated approach

This study looks at the role of biophysical sectors and world markets on an integrated economic assessment of climate change impacts on Egypt. Using the outcome from Global Circulation Models (GCMs) and a global model of world food trade (the Basic Linked System; BLS) — changes in crop yields; crop water demands; water and land resource availability; and world market prices were applied to a dynamic, computable general equilibrium model of Egypt (the Standard National Model of the BLS). Modeling results consistently showed that the net effect of climate change on the macro indicator of per capita GDP was not great — regardless of the level of integration. This outcome was only realized through autonomous economic adjustments which implied significant socio-economic and structural change. Including or excluding certain biophysical sectors and world markets influenced the development path and the nature of the autonomous adjustments. The importance of a particular biophysical sector or of world markets was also dependent upon the specific climate change scenario.     

Evaluating the Efficiency of a Uniform N-Input Tax under Different Policy Scenarios at Different Scales

Nitrate pollution from agriculture is an important environmental externality, caused by the excessive use of fertilizers. The internalization of this problem, via a tax on mineral nitrogen, could lead to a second best solution, reducing nitrate emissions. Several authors suggest that a reduction in agricultural support could produce similar results. In this paper, we examine the effects of different levels of a uniformly implemented nitrogen tax in France under two policy scenarios, corresponding to post Agenda 2000 and 2003 Luxembourg reforms of European Union’s Common Agricultural Policy, in order to reveal the synergies and conflicts between the tax and the policy scenarios in terms of nitrate emissions abatement. The analysis is performed at different geographical scales, from the national to the regional and is based on a bioeconomic approach that involves the coupling of the economic model AROPAj with the crop model STICS. Results show that the efficiency of the N-tax varies according to the geographical scale of the analysis and the type of farming. Furthermore, we prove that a uniform implementation may lead to perverse effects that should always be taken into account when introducing second-best instruments.     

Advanced energy consumption system for smart farm based on reactive energy utilization technologies

Over the decades, both agriculture and energy grids have encountered significant challenges, such as the lack of power supply to agricultural farms and the difficulties of renewable energy use in the electricity sector. To overcome and address these issues, this paper presents an idea of merging smart farm and renewable energy, using surplus renewable energy for the agriculture sector using the smart farm for renewable energy supplies. First, demonstrate the framework to connect a smart farm energy system and analyze its feasibility and advantages. In this paper, Reactive Energy Utilization Technology (REUT) has been used as an efficient energy consumption system for the smart farm. It is used to predict the optimum wind power scenario in the smart farm by monitoring continuous control variables, with the lowest voltage reached in each scenario, and minimized actual total power losses. A combined system consisting of smart farming production, as well as renewable energy consumption, has been evaluated in experimental results. Experimental results and discussion shows that the proposed method has better renewable energy consumption, accuracy(96.7%), and efficiency(95.6%) for smart farming.     

Study of the Climate Change Impacts on Water Quality in the Upstream Portion of the Cau River Basin,Vietnam

This paper presents simulations of climate change impacts on water quality in the upstream portion of the Cau River Basin in the North of Vietnam. The integrated modeling system GIBSI was used to simulate hydrological processes, pollutant and sediment wash-off in the river basin, and pollutant transport and transformation in the river network. Three projections for climate change based on emission scenarios B1, B2, and A2 of IPCC Special Report on Emission Scenarios (SRES) were considered. By assuming that the input pollution sources and watershed configuration were constant, based on 2008 data, water quality in the river network was simulated up to the terminal year 2050. For each climate change scenario, patterns of precipitation in wet and dry year were considered. The change in annual and monthly trends for dissolved oxygen (DO), biochemical oxygen demand (BOD), and ammonium ions (NH4+) load and concentration for different portions of the watershed have been analyzed. The results of these simulations show that climate change has more impact on changing the seasonal water quality parameters than on altering the average annual load of the pollutants. The percent change and change pattern in water quality parameters are different for wet and dry year, and the changes in wet year are smaller than those in dry year.     

Meat,Dairy and Climate Change: Assessing the Long-Term Mitigation Potential of Alternative Agri-Food Consumption Patterns in Canada

We use a newly developed model of the entire Canadian energy system (TIMES-Canada) to assess the climate change mitigation potential of different agri-food consumption patterns in Canada. For this, our model has been extended by disaggregating the agricultural demand sector into individual agri-food demands to allow for a more in-depth analysis. Besides a business-as-usual (baseline) scenario, we have constructed four different agri-food scenarios to assess the viability of reducing Canadian meat and dairy consumption in order to diminish Canada’s agricultural sector energy consumption and greenhouse gas (GHG) emissions. Our policy scenarios progressively restrict the consumption of different meat and dairy agricultural products until the year 2030. Our results suggest that the implementation of a meat and dairy consumption reduction policy would lead to a 10 to 40 % reduction in agricultural GHG emissions, depending on the severity of the scenario. This translates to a 1 to 3 % decrease in total Canadian GHG emissions by the year 2030. Besides these environmental benefits, health benefits associated with a reduction in meat and dairy consumption (as inferred from other studies) are presented as an additional source of motivation for implementing such a policy in Canada.     

Assessing alpine plant vulnerability to climate change: a modeling perspective

The potential ecological impact of ongoing climate change has been much discussed. High mountain ecosystems were identified early on as potentially very sensitive areas. Scenarios of upward species movement and vegetation shift are commonly discussed in the literature. Mountains being characteristically conic in shape, impact scenarios usually assume that a smaller surface area will be available as species move up. However, as the frequency distribution of additional physiographic factors (e.g., slope angle) changes with increasing elevation (e.g., with few gentle slopes available at higher elevation), species migrating upslope may encounter increasingly unsuitable conditions. As a result, many species could suffer severe reduction of their habitat surface, which could in turn affect patterns of biodiversity. In this paper, results from static plant distribution modeling are used to derive climate change impact scenarios in a high mountain environment. Models are adjusted with presence/absence of species. Environmental predictors used are: annual mean air temperature, slope, indices of topographic position, geology, rock cover, modeled permafrost and several indices of solar radiation and snow cover duration. Potential Habitat Distribution maps were drawn for 62 higher plant species, from which three separate climate change impact scenarios were derived. These scenarios show a great range of response, depending on the species and the degree of warming. Alpine species would be at greatest risk of local extinction, whereas species with a large elevation range would run the lowest risk. Limitations of the models and scenarios are further discussed. This revised version was published online in July 2006 with corrections to the Cover Date.     

Biophysical and socioeconomic characterization of a water-stressed area and simulating agri-production estimates and land use planning under normal and extreme climatic events: a case study

This study aims in linking the biophysical and socioeconomic data base layers with the technical coefficients or simulation models for agri-production estimates and land use planning under normal and extreme climatic events, and exploring the resource and inputs management options in village Shikohpur, Gurgaon district located in the northwest part of India. The socioeconomic profile of Shikohpur is highly skewed with mostly small and marginal farmers. Though the areas under wheat in Shikohpur are increasing, the productivity is declining or remaining stagnant over the years. Most of the area during kharif season (June-September) remains fallow. Pearl millet based cropping systems (pearl millet-mustard and pearl millet-wheat) are predominant. Soils are mostly loamy sand to sandy loam with average of 70-80% sand content. Organic C content in soil is less than 0.3%, due to high prevailing temperature with little rainfall and also intensive agriculture followed in this region. Though the annual average seasonal rainfall in Gurgaon did not have much variation over the years, occurrence of extreme climate events has increased in the last two decades. The crop intensity is low and the water table is declining. Water and nitrogen production functions were developed for the important crops of the region, for their subsequent use in scheduling of the inputs. InfoCrop, WTGROWS and technical coefficients were used for crop planning and resource management under climate change and its variability, extreme events, limited resource availability and crop intensification. These will help in disseminating necessary agro-advisories to the farmers so that they will be able to manipulate the inputs and agronomic management practices for sustained agricultural production under normal as well as extreme climatic conditions.     

Adaptation to Climatic Variability and Change: Asian Perspectives on Agriculture and Food Security

The impacts of climate change on potential rice production in Asia are reviewed in the light of the adaptation to climatic variability and change. Collaborative studies carried out by IRRI and US-EPA reported that using process-based crop simulation models increasing temperature may decrease rice potential yield up to 7.4% per degree increment of temperature. When climate scenarios predicted by GCMs were applied it was demonstrated that rice production in Asia may decline by 3.8% under the climates of the next century. Moreover, changes in rainfall pattern and distribution were also found suggesting the possible shift of agricultural lands in the region. The studies however have not taken the impacts of climatic variability into account, which often produce extreme events like that caused by monsoons and El Niño. Shifts in rice-growing areas are likely to be constrained by land-use changes occurring for other developmental reasons, which may force greater cultivation of marginal lands and further deforestation. This should be taken into account and lead to more integrated assessment, especially in developing countries where land-use change is more a top-down policy rather than farmers' decision. A key question is: To what extent will improving the ability of societies to cope with current climatic variability through changing design of agricultural systems and practices help the same societies cope with the likely changes in climate?     

Regional impact analysis of climate change on natural and managed forests in the Federal State of Brandenburg, Germany

A methodology for regional application of forest simulation models has been developed as part of an assessment of possible climate change impacts in the Federal state of Brandenburg (Germany). Here we report on the application of a forest gap model to analyse the impacts of climate change on species composition and productivity of natural and managed forests in Brandenburg using a statistical method for the development of climate scenarios. The forest model was linked to a GIS that includes soil and groundwater table maps, as well as gridded climate data with a resolution of 10 × 10 km and simulated a steady-state species composition which was classified into forest types based on the biomass distribution between species. Different climate scenarios were used to assess the sensitivity of species composition to climate change. The simulated forest distribution patterns for current climate were compared with a map of Potential Natural Vegetation (PNV) of Brandenburg.In order to analyse the possible consequences of climate change on forest management, we used forest inventory data to initialize the model with representative forest stands. Simulation experiments with two different management strategies indicated how forest management could respond to the projected impacts of climate change. The combination of regional analysis of natural forest dynamics under climate change with simulation experiments for managed forests outlines possible trends for the forest resources. The implications of the results are discussed, emphasizing the regional differences in environmental risks and the adaptation potentials of forestry in Brandenburg.     

Climatic Implications of Revised IPCC Emissions Scenarios, the Kyoto Protocol and Quantification of Uncertainties

In December 1997, the United Nations Framework Convention on Climate Change (FCCC) adopted the Kyoto Protocol. This paper describes a framework that models the climatic implications of this international agreement, using Monte Carlo simulations and the preliminary Intergovernmental Panel on Climate Change emissions scenarios (SRES). Emissions scenarios (including intervention scenarios), climate sensitivity, and terrestrial carbon sink are the key sampled model parameters. This framework gives prior probability distributions to these parameters and, using a simple climate model, posterior distributions of global temperature change are determined for the future. Our exercise showed that the Kyoto Protocol's effectiveness will be mostly dependent upon which SRES world evolves. In some worlds the Protocol decreases the warming considerably but in others it is almost irrelevant. We exemplified this approach with a current FCCC issue, namely “hot air”. This modelling framework provides a probabilistic assessment of climate policies, which can be useful for decision-makers involved in global climate change management. This revised version was published online in July 2006 with corrections to the Cover Date.     

The potential effects of climate change on the distribution and productivity of Cunninghamia lanceolata in China

Climate changes may have immediate implications for forest productivity and may produce dramatic shifts in tree species distributions in the future. Quantifying these implications is significant for both scientists and managers. Cunninghamia lanceolata is an important coniferous timber species due to its fast growth and wide distribution in China. This paper proposes a methodology aiming at enhancing the distribution and productivity of C. lanceolata against a background of climate change. First, we simulated the potential distributions and establishment probabilities of C. lanceolata based on a species distribution model. Second, a process-based model, the PnET-II model, was calibrated and its parameterization of water balance improved. Finally, the improved PnET-II model was used to simulate the net primary productivity (NPP) of C. lanceolata. The simulated NPP and potential distribution were combined to produce an integrated indicator, the estimated total NPP, which serves to comprehensively characterize the productivity of the forest under climate change. The results of the analysis showed that (1) the distribution of C. lanceolata will increase in central China, but the mean probability of establishment will decrease in the 2050s; (2) the PnET-II model was improved, calibrated, and successfully validated for the simulation of the NPP of C. lanceolata in China; and (3) all scenarios predicted a reduction in total NPP in the 2050s, with a markedly lower reduction under the a2 scenario than under the b2 scenario. The changes in NPP suggested that forest productivity will show a large decrease in southern China and a mild increase in central China. All of these findings could improve our understanding of the impact of climate change on forest ecosystem structure and function and could provide a basis for policy-makers to apply adaptive measures and overcome the unfavorable influences of climate change.     

Monte Carlo assessment of uncertainty in the simulated hydrological response to land use change

We quantified the uncertainty in hydrological response for a set of land use change scenarios by varying plant parameters within realistic uncertainty bounds in a Monte Carlo analysis. The results show that simulated hydrological fluxes significantly change after the introduction of outwintering suckler cow management, despite the presence of a significant amount of output uncertainty due to uncertainty in the plant parameterisation. The key to a proper uncertainty assessment was to consider the uncertainty in the difference between the scenarios instead of the absolute uncertainty of each single scenario. Additionally, a sensitivity analysis showed that changing soil properties in response to land use change does not result in significantly different results in the scenario analysis.     

Monitoring of flow field based on stable isotope geochemical characteristics in deep groundwater

As circumstances of operating and maintenance activities for landfilling and composting in Tehran metropolis differ from those of cities in developed countries, it was concluded to have an environmental impact comparison between the current solid waste management (MSW) strategies: (1) landfill, and (2) composting plus landfill. Life cycle assessment (LCA) was used to compare these scenarios for MSW in Tehran, Iran. The Eco-Indicator 99 is applied as an impact assessment method considering surplus energy, climate change, acidification, respiratory effect, carcinogenesis, ecotoxicity and ozone layer depletion points of aspects. One ton of municipal solid waste of Tehran was selected as the functional unit. According to the comparisons, the composting plus landfill scenario causes less damage to human health in comparison to landfill scenario. However, its damages to both mineral and fossil resources as well as ecosystem quality are higher than the landfill scenario. Thus, the composting plus landfill scenario had a higher environmental impact than landfill scenario. However, an integrated waste management will ultimately be the most efficient approach in terms of both environmental and economic benefits. In this paper, a cost evaluation shows that the unit cost per ton of waste for the scenarios is 15.28 and 26.40 US$, respectively. Results show landfill scenario as the preferable option both in environmental and economic aspects for Tehran in the current situation.