mitigation and adaptation. Although local crop production provides the majority supply of staple foods, mostly rainfed agricultural system in Sub-Saharan Africa is not prepared to adapt to projected future climate. Various studies predicted significant reduction in productivity of the major crops in the region under the changed climate scenario unless new technology and adaptation policy can counteract the adverse effect of climate variability (Schlenker and Lobell 2010, Knox 2012, Ahmed et al. 2015). Also in Sub- Saharan Africa, more than 80% of the agricultural growth since 1980 was attributed to crop area expansion instead of increase of productivity over already existing agricultural land (The World Bank, 2008). Considering the vulnerability of agricultural infrastructures in the region, despite the potential scope of improving yield to minimize landusechange, addition of new crop area is likely to be a prevailing strategy for agricultural growth in the near future. Therefore, comprehensive analysis of crop response to regional climate changes should be included in investigating future landuse changes, and the resulting feedback to regional climate. However, to our knowledge, no previous studies projecting regional climatechange in West Africa directly addressed the climatechangeimpact on crop yield and crop area distribution in evaluatinglanduse- climate interaction in West Africa.
produced is a function of radioactive decay in the Earth’s core. Rock properties, mantle heat flux, and crustal heat flux combine to determine GHF (Maule, Purucker, Olsen & Mosegaard, 2005). The dependence on such spatially variable factors makes GHF hard to quantify and apply to regional scale models (Llubes, Lanseau & Remy, 2006; Shapiro & Ritzwoller, 2004a). Methods of constraining such values include: seismic monitoring; satellite magnetic data; rock property analysis; and, more recently, direct measurements (Fisher, Mankoff, Tulaczyk, Tyler & Foley, 2015). GHF is a fundamental factor in the mass balance of Antarctic ice sheets and is crucial in discerning future climatic models of the globe. GHF has the potential to melt ice sheets and alter their basal properties, both of which have immediate run on effects to the global climate, including sea level rise (SLR) (Magnússon, Björnsson, Dall & Pálsson, 2005; Schroeder, Blankenship, Young & Quartini, 2014). The West Antarctic Ice Sheet, when completely melted, will contribute 5.5 m to global SLR, and the East Antarctic Ice Sheet will contribute 64.8 m to SLR (Bell, 2008). The relationship of GHF with the cryosphere can enhance understanding about this imminent threat of extreme SLR. Accurate valuation of Antarctic GHF, both theoretical and numerical, is difficult to obtain due to location and ice cover (Llubes et al., 2006). So, despite its importance, little is known about Antarctic GHF and its consequent effects on the cryosphere. Acknowledgement of the need for understanding in this field has led to the discovery of considerable sized subglacial hydrological networks which call for immediate academic attention (Seroussi, Ivins, Weins & Bondizo, 2017).
Peatlands can be found from almost all over the world, but in the tropical and subtropical region have a higher percentage. Around 88.6 Pg is stored in peat- lands worldwide, whereas 68.5 Pg soil carbon (C) (77%) presents in Southeast Asia. The reported evidence of carbon emissions is found in South Asia, USA, Canada, Australia, China, Siberia, Denmark, a Caribbean island, France, Brazil, mangrove forests, and tropical grasslands that have higher emissions rate -. However, most of the peat soils are mainly found in the USA, Western Europe, Eastern Asia, and Central America, Tibetan grassland   . Maitra et al. studied the distribution of peat soils in Bangladesh and possible economic uses as fuel . The distribution of peat soils in Bangladesh is hig- hlighting in Figure 1. There are lots of factors that control the carbon storage in the soil including temperature, slope, and elevation. Additionally, pasturing, landusechange and vegetation pattern also have considerable influences on the presence of soil organic carbon in peat soils. Land modification on peatlands re- sults in enormous carbon instabilities by deforestation and sweltering  .
Modeling of the anthropogenic climatechange anticipa- ted in the coming decades requires a thorough unders- tanding of the carbon cycle, in particular, the various sources and sinks of carbon exchangeable on short (de- cadal) time scales. Multiple studies have estimated both the reservoirs and fluxes of carbon from terrestrial and marine reservoirs . Early studies of carbon cycling re- cognized the importance of land-use changes, deforesta- tion and afforestation in particular, and attendant fluctua- tions in above-ground biomass carbon in contributing to fluctuations in the atmospheric reservoir. For example, Mellilo and others  estimated that deforestation con- tributes 23% of the anthropogenic CO 2 increase to the
‘Well, the potential impacts are positive. I think that the concept and then the reality are probably a little bit separated. I think people are being encouraged to change management practice and use the accrued carbon as a benefit to their business, and their business plan can prove their rates of return and give them a better value outcome – value return in there, as a cultural pursuit. I think the issue is that there is too much uncertainty in the process and downstream risks – and when I say downstream risks…in a forest, when you plant a crop of trees and commercially planted trees aren’t an allowable claim under the CFI process, but let’s just say if they were, you can claim the carbon accrued in that forest and notionally get a value return for that carbon. The consequence of taking that revenue, taking that cash flow, is that you then incur a liability – which could then be 100 year or 75 years, or some very long term horizon. And when you factor in that risk into the process, then it has a significant impact or it dilutes the value return that you would get in year one by selling your carbon source’.
Plot characteristics recorded include tree cover, shrub cover and landuse. Ground cover was measured in terms of percentage of natural materials such as rock, bare soil, mulch, herbs, grass (maintained and unmaintained) and water, and urban materials including building, cement and tar. The herbaceous layer, consisting of non-woody stems, were considered as part of ground cover (i-Tree, 2010). Shrubs and saplings, defined as woody material with DBH at 1.37cm of less than 5cm, were excluded. The Delphi method was used to aggregate the values estimated by the fieldwork crew in midpoints of 5% intervals (MacMillan and Marshall, 2006).
The mechanisms of adaptation to climatechange - even less well studied than adapta- tion per se - are now being investigated. For example, Albouy et al. ( 2016 ) study location choices by U.S. households to identify their preferences over local climates. They find, in their baseline specification, that adaptation via human migration is moderately extensive: the average absolute value of the population change across public-use microdata areas is 10.3%. Despite this population change, the estimated aggregate welfare loss changes little (from 2.28% to 2.01%) when migration is included. Davis and Gertler ( 2015 ) examine the use of air conditioning for home cooling as an adaptation to higher temperatures. In their main results, adaptation is projected to generate additional carbon dioxide emissions as air conditioning (and electricity use) increase to keep pace with higher temperatures, such that a comprehensive analysis of damages with adaptation should incorporate both direct and indirect effects. In an agricultural context, changes in cropland use are suggested as an important mode of adaptation ( Mendelsohn et al. , 1994 ; Burke and Emerick , 2016 ). As the climate warms, for example, a farmer might grow winter wheat instead of corn due to wheat’s early harvest, prior to the higher summer temperatures of July and August. 2 Yet
The results of the RUSLE model survey show a negligible difference between observed and estimated sediment in the baseline period, which suggests that this model has a relatively good performance in the field outlet sediment estimation. The advantages of using RUSLE in this kind of study include the following: (1) easy assessment of the soil management strategies and erosion control programs on erosion and sediment; (2) simple and fast analyses of the effects of climate and landusechange on sediment; (3) easy integration in GIS for geographically precise analysis; (4) RUSLE has been extensively applied and tested over many years in different types of landscapes and climate and it is a well-known model. Meanwhile, the main disadvantage of RUSLE is that it does not have the ability to route sediment through channels [ 71 ]. Also, there are several sources of error in soil loss estimation using RUSLE, which include measurement error, spatial resolution of maps, slope length measurement error, and the grid size of DEM [ 72 ].
A systematic analysis of landuse/cover change is so decisive to exactly under- stand the extent of change and take essential measures to curb down the rate of changes and protect the land cover resources sustainably. This landuse/land cover change study was conducted in Agarfa district of Bale zone, Oromia Regional State, Southeastern Ethiopia. The objectives of this study were to evaluate the trends, drivers and its socio-economic and environmen- tal implication in study area. A descriptive research method was employed to achieve the intended objectives of the study. In the three years (1976, 1995, and 2014) Landsat Satellite images and socio-economic survey were the main data sources for this study. ERDAS Imagine and Arch-GIS tools were used to classify and generate landuse/land cover maps of the study area. Survey ques- tionnaires, key informant interviews, and field observation were employed to obtain information on drivers and its socio-economic and environmental im- plication in the district. The results show that the landuse/land cover of the study area had changed dramatically during the period of 38 years. A rapid loss of forest land and shrub land cover in the landscape took place between 1976 and 2014. Conversely, agriculture and grazing lands were increased by 30% and 42% respectively at the expense of the lost landuse/land cover types. Forest land is the most converted cover type during the entire study period. In the 38 years, forest lands diminished by over 65% of the original forest cover that was existed at the base year (1976). Local climatechange, declining agri- cultural productivity and livestock quantity and quality and scarcity of fuel wood and constructional materials were some of the socio-economic and live- lihood impacts of landuse and land cover change of the study area. Thus, this finding affords information to land users and policy makers on extent of the change and social forces leading to this changes and its subsequent implica- tion on local socio-economic and environmental conditions of the study area. How to cite this paper: Turi, T., Hayicho,
The Kyoto-Protocol promotes management activ- ities to increase C stocks in ecosystems, but landuse is and will be largely driven by other socio- economic constraints. We chose a scenario-based assessment to estimate how general socio-eco- nomic trends may affect future C stock changes at a national level. To do so, we quantified changes in area of major land-use types under varying socio-economic conditions by combining scenario- based, spatial modeling with estimations of C stocks for forest biomass, forest soils, and agri- cultural open-land. These changes were subse- quently translated into potential changes of terrestrial C stocks. The scenarios of land-usechange presented here describe a broad range of potential pathways which could enhance policy discussions that aim to assess future demands and productivity across the landscape, as well as the potential of managed land to act as a C sink. The moderate business-as-usual scenario is contrasted by a more extreme liberalization and an extensi- fication scenario. The liberalization scenario would lead to a 24.3% increase in forest cover, mainly in mountainous areas after a build-up time which we estimate to be 100 years. Agri- culture in the lowlands would intensify due to favorable socio-economic, topographic and infra- structural conditions which foster agricultural management, whereas mountainous regions would become increasingly forested. Extensifica- tion would mean a 37% increase of currently extensively used open land and an 80% decrease of currently intensively used open-land.
Here we review the literature on landusechange and its impacts on emissions, deposition, and air quality. This section is broken down by key specific chemical species. The micrometeorological feedbacks of vegetation changes associated with landusechange (e.g. radiation, Bowen ratio, boundary layer heights, etc.) on air quality are beyond the scope of this review, however these factors may also play a critical role, as discussed for example by Ganzeveld et al. 50 Throughout this review we employ the terms radiative
The connectivity of materials, energy, and information flow across large spatial scales has significant implications for natural resource management (Peters et al., 2008) and is one of many factors considered in an All Lands approach. For example, long distance transport of air or water pollution means that receiving landscapes need to be managed to mitigate adverse impacts whose cause may originate from several kilometers away. Forests of the southern United States are heavily fragmented and most are privately owned. Public lands dispersed within this landscape pose a great challenge to public land management. This interaction among land ownership patterns is especially critical in the Eastern US where national forests are smaller compared to the Western US, and potentially much more influenced by changes outside the NFS boundaries.
quickly owing to the steep slope of the region. For the mid- stream, a sharp drop is observed up to a certain level during October, indicating the termination of direct runoff contri- bution to streamflow. Following this, the contribution is pre- dominantly through baseflow which in this case is observed to be higher than the baseflow before the monsoon months. The higher baseflow during post-monsoon period could be attributed to slow release of water stored by forests (dense and scrub) in the region aided by low elevation of the terrain in the region. Downstream region, though entirely a flat ter- rain, is dominated by cropland and urban areas that lack the capacity of holding the water, therefore limiting the contri- bution of baseflow to streamflow which leads to the observed sharp decline in the recession limb. Furthermore, long-term impacts of LU change are more evident in annual streamflow that is observed to increase by 12, 17 and 1 % from 1971 to 2011 for upstream, midstream and downstream regions, re- spectively.
It was the first legally binding international agreement to mandate countries to reduce greenhouse-gas emissions. Countries first agreed upon Kyoto Protocol in 1997 and it entered into force on 16 February 2005. 60 The Kyoto Protocol extends the main objective of the UNFCCC i.e., “stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference with the climate system.” 61 In addition, the Protocol places the obligation upon developed countries to reduce emissions, since; they are historically responsible for the current levels of greenhouse gases in the atmosphere. Except the United States of America, all most every country has ratified the treaty. 62 It is noteworthy that, under the treaty, developing countries, including China, India, Brazil and South Africa were not mandated to reduce emissions, given that these countries only contributed a relatively small share of the current emission of greenhouse gases. 63
over the results given by Intergovernmental Panel on ClimateChange (IPCC) in its assessment however there is general agreement over the fact that the climate of the world is changing. This climatechange has already affected the economic system of the world (IPCC, 1996) in which some economies got positive and some got 1999) over their economic activities. Even in the same economy sectoral differences are realized in response to climatechange (IPCC, 2001). Regional on has also emerged as an important aspect of the Paruelo, 1994; De Siqueira et al., 1994). But in aggregate it is acknowledged that the climatechange has brought more bad 1998) that forced the natural and social scientists to analyse the size of economic losses, the degree of vulnerability of various economies, its measurement, causes of the problems and their probable Among all sectors of the economy agriculture is termed as most sensitive to the climate. The productivity and the production of agricultural commodities are primarily determined by the climatic conditions in ceteris paribus condition because it not only provides an environment for the crops and their health but also decides the quality and texture of the soil which is the primary determinant. A change in climate is expected to bring changes in almost all spheres of agricultural practices.
The reports of IPCC give very little information on the possible wind velocity changes in Europe. The KNMI has presented more detailed scenarios for the Netherlands. In the KNMI Scientific Report WR 2006-01: ‘KNMI ClimateChange Scenarios 2006 for the Netherlands’ (Hurk et al, 2006). General Circulation Model (GCM) simulations which have become available during the preparation for the Fourth Assessment report (AR4) of IPCC have been used to derive scenarios of sea level change in the eastern North Atlantic basin and wind velocity in the North Sea area. The GCM simulations also were used to span a range of changes in seasonal mean temperature and precipitation over the Netherlands. The KNMI defines four possible scenarios for the climatechange: G, G+, W and W+ (from moderate to more extreme). For the four scenarios the effects are summarized in Table 1. The criteria for discriminating the four scenarios are the global temperature increase in 2050 and the change of atmospheric circulation over The Netherlands in the GCM model: for scenario G, a temperature increase of +1 °C is expected and a weak change of atmospheric circulation; for scenario G+, the same increase of +1°C is expected and a strong change of atmospheric circulation; for scenario W, a temperature increase of +2 °C and a weak change of atmospheric circulation and for scenario W+, +2°C and a strong change of atmospheric circulation. Specific scenario values for the global temperature change and the circulation change were chosen in such a way that they represented the underlying variability of GCM results for Western Europe well. Deliberately, the KNMI’06 climate scenarios are not associated with a certain probability of occurring, and no ‘most likely’ scenario is identified. The scenarios are designed to serve a diverse user community, and a wide range of applications.
This study was aimed at evaluating the landuse patterns and its implication for climatechange in Gamo Gofa Zone. To this purpose, correlation and time series trend analysis was used to assess how landuse patterns affect climate variables. At the local level, results suggest that crop land expansion may induce a significant reduction in fertile land. Most of the fertile land would be converted into cropland from 2005 base to 2012. In particular, it should be remarked that this conversion pattern is observed, where the resettlement programs are implemented. This means that farmers´ adaptation to climatechange may increase the deforestation pressure in the resettlement programs implemented areas and therefore it contributes to an increase in greenhouse gas emission. Thus landuse pattern and climate variables are structurally correlated and the landuse pattern change effects are implied on climate variables- average maximum temperature difference was increased 0.425 o C in two decades (1987-1999) to (2000-2011); and average minimum temperature was 0 o C, showing declining trend(Figure 6) over 1987-2011 in Gamo Gofa, southern Ethiopia.
There is a high consensus among scientists (Bruckles, 1999; Warner, 2005, Westcoat and White, 2003) that multi-stakeholder participation is the most appropriate institutional form for achieving the adaptive management and problem solving related to environmental issues and climatechange. The links between different knowledge frameworks in the policy planning, implementation, in parallel with the sustainable agricultural development are keys to solve the climatechange related problems. Therefore, the top priority in Vietnam is now to concretise the National Target Programme into an integrated practical strategy with the participation of all stakeholders. It is important to note that some of the most vulnerable people are the rural poor with limited access to information and financial and technical supports in order to adapt to the best of their abilities (Chauhdry et al., 2007). Future adaptive strategies need to learn from, and integrate, local indigenous adaptive experiences into the response measures. This requires the participation of the poor and the most vulnerable people in the planning and implementing processes of climatechange adaptation projects. The participation of these stakeholders is especially important in the project as it concerns their current and future livelihoods.
The representation of modified landcarbon sinks and sources by LULCC vary across the ESMs leading to the wide spread in carbon pool signals. The modeling groups used common land-use data sets and handled indirect effects co- herently following the LUCID protocol so that only differ- ences in simulated climate remain. However, intrinsic differ- ences across the models remain, such as the explicit simula- tion of some carbon-cycle-related processes (e.g., the repre- sentation of crops in CAN), and the neglect or parameteri- zation of other processes (e.g., crops in MPI). One example is the simulation of fire emissions that was done by MPI and IPSL (see Fig. S5 in the Supplement). Interestingly, they both show that fire emissions are reduced by increased land man- agement, which would otherwise increase much stronger in a warmer climate. Following Houghton et al. (2012), these as- pects cause uncertainties in modeling carbon emissions from LULCC in the order of ± 50 %.