957 resultados para AGRICULTURAL LAND
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Replaces the author's Land economics and simplified appraisal system.
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There has been a long dependency on credit by Indonesian farmers as a result of the lack of capital to apply proper farming practices. This paper describes the farming activities applied by agricultural credit users in Central Lombok, Indonesia. A survey was conducted during July 2001- March 2002 of 65 farmers making use of government or private credit in three villages within the Regency. Data from the farmers were collected using face-to-face, semi-structured interviews. Survey results indicated that on average, farmers had some 20 years experience of farming, were aged 40 years, but lacked of formal education. Their main asset was cropping land with average landholding of 0.69 ha. As a consequence of their capital constraints, farmers were commonly making use of credit to finance their farming activities, including both production of rice as the main crop and secondary crops. Farmers generally applied less than recommended amount of inputs in their farming practices, since the amount of credit they obtained was limited. As a result, their farms become less productive and their repayment capability of loans diminished. Of 65 farmers interviewed, 54 could earn extra income by engaging in a variety of non-farm activities, which contributed on average some 36% to family incomes of over Rp 5 million (A$ 1 thousand). The average credit repayment rate made by agricultural producers was 60%. The repayment made did not always reflect farm production capacity, being sometimes supported by other borrowings. The greater role of credit is not in increasing agricultural production or improving farmers’ income, but in helping them to sustain farm production and their living. Farmers need a bigger amount of credit to make an impact on their livelihood. This should be accompanied by extension services for farmers to enable better use of credit and to change their attitude towards it. As well, farmers require to be equipped with technical and market skills to run a business. Interdisciplinarity, holistic analysis, and an expansion of traditional ‘agricultural’ interests to embrace the span of interests included in rural livelihood, are each critical features of revision of the existing system.
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This research investigates the contribution that Geographic Information Systems (GIS) can make to the land suitability process used to determine the effects of a climate change scenario. The research is intended to redress the severe under representation of Developing countries within the literature examining the impacts of climatic change upon crop productivity. The methodology adopts some of the Intergovernmental Panel on Climate Change (IPCC) estimates for regional climate variations, based upon General Circulation Model predictions (GCMs) and applies them to a baseline climate for Bangladesh. Utilising the United Nations Food & Agricultural Organisation's Agro-ecological Zones land suitability methodology and crop yield model, the effects of the scenario upon agricultural productivity on 14 crops are determined. A Geographic Information System (IDRISI) is adopted in order to facilitate the methodology, in conjunction with a specially designed spreadsheet, used to determine the yield and suitability rating for each crop. A simple optimisation routine using the GIS is incorporated to provide an indication of the 'maximum theoretical' yield available to the country, should the most calorifically significant crops be cultivated on each land unit both before and after the climate change scenario. This routine will provide an estimate of the theoretical population supporting capacity of the country, both now and in the future, to assist with planning strategies and research. The research evaluates the utility of this alternative GIS based methodology for the land evaluation process and determines the relative changes in crop yields that may result from changes in temperature, photosynthesis and flooding hazard frequency. In summary, the combination of a GIS and a spreadsheet was successful, the yield prediction model indicates that the application of the climate change scenario will have a deleterious effect upon the yields of the study crops. Any yield reductions will have severe implications for agricultural practices. The optimisation routine suggests that the 'theoretical maximum' population supporting capacity is well in excess of current and future population figures. If this agricultural potential could be realised however, it may provide some amelioration from the effects of climate change.
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This paper investigates the environmental sustainability and competitiveness perceptions of small farmers in a region in northern Brazil. The main data collection instruments included a survey questionnaire and an analysis of the region's strategic plan. In total, ninety-nine goat and sheep breeding farmers were surveyed. Data analysis methods included descriptive statistics, cluster analysis, and chi-squared tests. The main results relate to the impact of education, land size, and location on the farmers' perceptions of competitiveness and environmental issues. Farmers with longer periods of education have higher perception scores about business competitiveness and environmental sustainability than those with less formal education. Farmers who are working larger land areas also have higher scores than those with smaller farms. Lastly, location can yield factors that impact on farmers' perceptions. In our study, farmers located in Angicos and Lajes had higher perception scores than Pedro Avelino and Afonso Bezerra, despite the geographical proximity of these municipalities. On the other hand, three other profile variables did not impact on farmers' perceptions, namely: family income, dairy production volume, and associative condition. The authors believe the results and insights can be extended to livestock farming in other developing countries and contribute generally to fostering effective sustainable development policies, mainly in the agribusiness sector. © 2013 Elsevier Ltd. All rights reserved.
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The aim of this article is to draw attention to calculations on the environmental effects of agriculture and to the definition of marginal agricultural yield. When calculating the environmental impacts of agricultural activities, the real environmental load generated by agriculture is not revealed properly through ecological footprint indicators, as the type of agricultural farming (thus the nature of the pollution it creates) is not incorporated in the calculation. It is commonly known that extensive farming uses relatively small amounts of labor and capital. It produces a lower yield per unit of land and thus requires more land than intensive farming practices to produce similar yields, so it has a larger crop and grazing footprint. However, intensive farms, to achieve higher yields, apply fertilizers, insecticides, herbicides, etc., and cultivation and harvesting are often mechanized. In this study, the focus is on highlighting the differences in the environmental impacts of extensive and intensive farming practices through a statistical analysis of the factors determining agricultural yield. A marginal function is constructed for the relation between chemical fertilizer use and yield per unit fertilizer input. Furthermore, a proposal is presented for how calculation of the yield factor could possibly be improved. The yield factor used in the calculation of biocapacity is not the marginal yield for a given area, but is calculated from the real and actual yields, and this way biocapacity and the ecological footprint for cropland are equivalent. Calculations for cropland biocapacity do not show the area needed for sustainable production, but rather the actual land area used for agricultural production. The proposal the authors present is a modification of the yield factor and also the changed biocapacity is calculated. The results of statistical analyses reveal the need for a clarification of the methodology for calculating marginal yield, which could clearly contribute to assessing the real environmental impacts of agriculture.
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The aim of this article is to draw attention to calculations on the environmental effects of agriculture and to the definition of marginal agricultural yield. When calculating the environmental impacts of agricultural activities, the real environmental load generated by agriculture is not revealed properly through ecological footprint indicators, as the type of agricultural farming (thus the nature of the pollution it creates) is not incorporated in the calculation. It is commonly known that extensive farming uses relatively small amounts of labor and capital. It produces a lower yield per unit of land and thus requires more land than intensive farming practices to produce similar yields, so it has a larger crop and grazing footprint. However, intensive farms, to achieve higher yields, apply fertilizers, insecticides, herbicides, etc., and cultivation and harvesting are often mechanized. In this study, the focus is on highlighting the differences in the environmental impacts of extensive and intensive farming practices through a statistical analysis of the factors determining agricultural yield. A marginal function is constructed for the relation between chemical fertilizer use and yield per unit fertilizer input. Furthermore, a proposal is presented for how calculation of the yield factor could possibly be improved. The yield factor used in the calculation of biocapacity is not the marginal yield for a given area, but is calculated from the real and actual yields, and this way biocapacity and the ecological footprint for cropland are equivalent. Calculations for cropland biocapacity do not show the area needed for sustainable production, but rather the actual land area used for agricultural production. The proposal the authors present is a modification of the yield factor and also the changed biocapacity is calculated. The results of statistical analyses reveal the need for a clarification of the methodology for calculating marginal yield, which could clearly contribute to assessing the real environmental impacts of agriculture.
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Insect biodiversity is unevenly distributed on local, regional, and global scales. Elevation is a key factor in the uneven distribution of insect diversity, serving as a proxy for a host of environmental variables. My study examines the relationship of Heteroptera (true bugs) species diversity, abundance, and morphology to elevational gradients and land-use regimes on Mt. Kilimanjaro, Tanzania, East Africa. Heteroptera specimens were collected from 60 research sites covering an elevational range of 3684m (866-4550m above sea level). Thirty of the sites were classified as natural, while the remaining 30 were classified as disturbed (e.g., agricultural use or converted to grasslands). I measured aspects of the body size of adult specimens and recorded their location of origin. I used regression models to analyze the relationships of Heteroptera species richness, abundance, and body measurements to elevation and land-use regime. Richness and abundance declined with greater elevation, controlling for land use. The declines were linear or logarithmic in form, depending on the model. Richness and abundance were greater in natural than disturbed sites, controlling for elevation. According to an interaction, richness decreased more in natural than disturbed sites with rising elevation. Body length increased as a quadratic function of elevation, adjusting for land use. Body width X length decreased as a logarithmic function of elevation, while leg length/body length decreased as a quadratic function. Leg length/body length was greater in disturbed than natural sites. Interactions indicated that body length and body width X length were greater in natural than disturbed sites as elevation rose, although the general trend was downward. Future research should examine the relative importance of land area, temperature, and resource constraints for Heteroptera diversity and morphology on Mt. Kilimanjaro.
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This article is protected by copyright. All rights reserved. Acknowledgements We thank Tamara Ben-Ari and Jean-Francois Soussana, from INRA in France, for their valuable contributions to the early development stage of this project. We also owe great acknowledge to Prof. Ib Skovgaard, University of Copenhagen, for giving essential assistance in developing the methods for decomposing emission changes. We also thank the Centre for Regional Change in the Earth System (CRES, www.cres-centre.dk) and the Department of Plant- and Environmental Sciences, University of Copenhagen, for funding the work.
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Acknowledgements: We thank Dr. Tamara Ben-Ari and Dr. Jean-Francois Soussana, from INRA in France, for their valuable contributions to the early development stage of this project. We also owe great thanks to Prof. Ib Skovgaard, University of Copenhagen, for giving essential assistance in developing the methods for decomposing emission changes. We also thank the Centre for Regional Change in the Earth System (CRES, www.cres-centre.dk), and the University of Copenhagen for funding the work.
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South Florida continues to become increasingly developed and urbanized. My exploratory study examines connections between land use and water quality. The main objectives of the project were to develop an understanding of how land use has affected water quality in Miami-Dade canals, and an economic optimization model to estimate the costs of best management practices necessary to improve water quality. Results indicate Miami-Dade County land use and water quality are correlated. Through statistical factor and cluster analysis, it is apparent that agricultural areas are associated with higher concentrations of nitrogen, while urban areas commonly have higher levels of phosphorous than agricultural areas. The economic optimization model shows that urban areas can improve water quality by lowering fertilizer inputs. Agricultural areas can also implement methods to improve water quality although it may be more expensive than urban areas. It is important to keep solutions in mind when looking towards future water quality improvements in South Florida.