906 resultados para Agricultural systems modelling
Resumo:
The study of the ecology of soil microbial communities at relevant spatial scales is primordial in the wide Amazon region due to the current land use changes. In this study, the diversity of the Archaea domain (community structure) and ammonia-oxidizing Archaea (richness and community composition) were investigated using molecular biology-based techniques in different land-use systems in western Amazonia, Brazil. Soil samples were collected in two periods with high precipitation (March 2008 and January 2009) from Inceptisols under primary tropical rainforest, secondary forest (5-20 year old), agricultural systems of indigenous people and cattle pasture. Denaturing gradient gel electrophoresis of polymerase chain reaction-amplified DNA (PCR-DGGE) using the 16S rRNA gene as a biomarker showed that archaeal community structures in crops and pasture soils are different from those in primary forest soil, which is more similar to the community structure in secondary forest soil. Sequence analysis of excised DGGE bands indicated the presence of crenarchaeal and euryarchaeal organisms. Based on clone library analysis of the gene coding the subunit of the enzyme ammonia monooxygenase (amoA) of Archaea (306 sequences), the Shannon-Wiener function and Simpson's index showed a greater ammonia-oxidizing archaeal diversity in primary forest soils (H' = 2.1486; D = 0.1366), followed by a lower diversity in soils under pasture (H' = 1.9629; D = 0.1715), crops (H' = 1.4613; D = 0.3309) and secondary forest (H' = 0.8633; D = 0.5405). All cloned inserts were similar to the Crenarchaeota amoA gene clones (identity > 95 %) previously found in soils and sediments and distributed primarily in three major phylogenetic clusters. The findings indicate that agricultural systems of indigenous people and cattle pasture affect the archaeal community structure and diversity of ammonia-oxidizing Archaea in western Amazon soils.
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In agricultural systems the N-NH4+ and N-NO3- contents is significantly affected by soil management. This study investigated the dynamics of inorganic nitrogen (N; NH4+ and NO3-) in an experimental evaluation of soil management systems (SMSs) adopted in 1988 at the experimental station of the ABC Foundation in Ponta Grossa, in the Central South region of the State of Paraná. The objective of this study was to evaluate the changes in N-NH4+ and N-NO3- flux in the surface layer of a Red Latosol arising from SMSs over a 12-month period. The experiment was arranged in a completely randomized block design in split plots, in three replications. The plots consisted of the following SMSs: 1) conventional tillage (CT); 2) minimum tillage (MT); 3) no-tillage with chisel plow every three years (NT CH); and 4) continuous no-tillage (CNT). To evaluate the dynamics of inorganic N, the subplots represented samplings (11 sampling times, T1 - T11). The ammonium N (N-NH4+) and nitric N (N-NO3-) contents were higher in systems with reduced tillage (MT and NT CH) and without tillage (CNT) than in the CT system. In the period from October 2003 to February 2004, the N-NH4+ was higher than the N-NO3- soil content. Conversely, in the period from May 2004 to July 2004, the N-NO3- was higher than the N-NH4+ content. The greatest fluctuation in the N-NH4+ and N-NO3- contents occurred in the 0-2.5 cm layer, and the highest peak in the N-NH4+ and N-NO3- concentrations occurred after the surface application of N. Both N-NH4+ and N-NO3- were strongly correlated with the soil organic C content, which indicated that these properties vary together in the system.
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A simple model of diffusion of innovations in a social network with upgrading costs is introduced. Agents are characterized by a single real variable, their technological level. According to local information, agents decide whether to upgrade their level or not, balancing their possible benefit with the upgrading cost. A critical point where technological avalanches display a power-law behavior is also found. This critical point is characterized by a macroscopic observable that turns out to optimize technological growth in the stationary state. Analytical results supporting our findings are found for the globally coupled case.
Resumo:
Rough turning is an important form of manufacturing cylinder-symmetric parts. Thus far, increasing the level of automation in rough turning has included process monitoring methods or adaptive turning control methods that aim to keep the process conditions constant. However, in order to improve process safety, quality and efficiency, an adaptive turning control should be transformed into an intelligent machining system optimizing cutting values to match process conditions or to actively seek to improve process conditions. In this study, primary and secondary chatter and chip formation are studied to understand how to measure the effect of these phenomena to the process conditions and how to avoid undesired cutting conditions. The concept of cutting state is used to address the combination of these phenomena and the current use of the power capacity of the lathe. The measures to the phenomena are not developed based on physical measures, but instead, the severity of the measures is modelled against expert opinion. Based on the concept of cutting state, an expert system style fuzzy control system capable of optimizing the cutting process was created. Important aspects of the system include the capability to adapt to several cutting phenomena appearing at once, even if the said phenomena would potentially require conflicting control action.
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The main objective of this paper aims at developing a methodology that takes into account the human factor extracted from the data base used by the recommender systems, and which allow to resolve the specific problems of prediction and recommendation. In this work, we propose to extract the user's human values scale from the data base of the users, to improve their suitability in open environments, such as the recommender systems. For this purpose, the methodology is applied with the data of the user after interacting with the system. The methodology is exemplified with a case study
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The JModel suite consists of a number of models of aspects of the Earth System. The Java programmes model in detail aspects of the cycles of some major biogeochemical elements that exemplify the range of geochemical processes in marine environments.
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This presentation introduces Soft Systems Modelling as a technique to support investigating the behaviour of dynamic systems in the real world. It combines techniques from General Systems Theory, Soft Systems Methodolgy and Critical Systems Heuristics. Personas and Scenarios are used as a technique for exploring the motivations of stakeholders in the systems.
Resumo:
Soils represent a large carbon pool, approximately 1500 Gt, which is equivalent to almost three times the quantity stored in terrestrial biomass and twice the amount stored in the atmosphere. Any modification of land use or land management can induce variations in soil carbon stocks, even in agricultural systems that are perceived to be in a steady state. Tillage practices often induce soil aerobic conditions that are favourable to microbial activity and may lead to a degradation of soil structure. As a result, mineralisation of soil organic matter increases in the long term. The adoption of no-tillage systems and the maintenance of a permanent vegetation cover using Direct seeding Mulch-based Cropping system or DMC, may increase carbon levels in the topsoil. In Brazil, no-tillage practices (mainly DMC), were introduced approximately 30 years ago in the south in the Parana state, primarily as a means of reducing erosion. Subsequently, research has begun to study the management of the crop waste products and their effects on soil fertility, either in terms of phosphorus management, as a means of controlling soil acidity, or determining how manures can be applied in a more localised manner. The spread of no-till in Brazil has involved a large amount of extension work. The area under no-tillage is still increasing in the centre and north of the country and currently occupies ca. 20 million hectares, covering a diversity of environmental conditions, cropping systems and management practices. Most studies of Brazilian soils give rates of carbon storage in the top 40 cm of the soil of 0.4 to 1.7 t C ha(-1) per year, with the highest rates in the Cerrado region. However, caution must be taken when analysing DMC systems in terms of carbon sequestration. Comparisons should include changes in trace gas fluxes and should not be limited to a consideration of carbon storage in the soil alone if the full implications for global warming are to be assessed.
Resumo:
Currently we have little understanding of the impacts of land use change on soil C stocks in the Brazilian Amazon. Such information is needed to determine impacts'6n the global C cycle and the sustainability of agricultural systems that are replacing native forest. The aim of this study was to predict soil carbon stocks and changes in the Brazilian Amazon during the period between 2000 and 2030, using the GEFSOC soil carbon (C) modelling system. In order to do so, we devised current and future land use scenarios for the Brazilian Amazon, taking into account: (i) deforestation, rates from the past three decades, (ii) census data on land use from 1940 to 2000, including the expansion and intensification of agriculture in the region, (iii) available information on management practices, primarily related to well managed pasture versus degraded pasture and conventional systems versus no-tillage systems for soybean (Glycine max) and (iv) FAO predictions on agricultural land use and land use changes for the years 2015 and 2030. The land use scenarios were integrated with spatially explicit soils data (SOTER database), climate, potential natural vegetation and land management units using the recently developed GEFSOC soil C modelling system. Results are presented in map, table and graph form for the entire Brazilian Amazon for the current situation (1990 and 2000) and the future (2015 and 2030). Results include soil organic C (SOC) stocks and SOC stock change rates estimated by three methods: (i) the Century ecosystem model, (ii) the Rothamsted C model and (iii) the intergovernmental panel on climate change (IPCC) method for assessing soil C at regional scale. In addition, we show estimated values of above and belowground biomass for native vegetation, pasture and soybean. The results on regional SOC stocks compare reasonably well with those based on mapping approaches. The GEFSOC system provided a means of efficiently handling complex interactions among biotic-edapho-climatic conditions (> 363,000 combinations) in a very large area (similar to 500 Mha) such as the Brazilian Amazon. All of the methods used showed a decline in SOC stock for the period studied; Century and RothC simulated values for 2030 being about 7% lower than those in 1990. Values from Century and RothC (30,430 and 25,000 Tg for the 0-20 cm layer for the Brazilian Amazon region were higher than those obtained from the IPCC system (23,400 Tg in the 0-30 cm layer). Finally; our results can help understand the major biogeochemical cycles that influence soil fertility and help devise management strategies that enhance the sustainability of these areas and thus slow further deforestation. (C) 2007 Elsevier B.V. All rights reserved.
Resumo:
Nutrient cycles link agricultural systems to their societies and surroundings; inputs of nitrogen and phosphorus in particular are essential for high crop yields, but downstream and downwind losses of these same nutrients diminish environmental quality and human well-being. Agricultural nutrient balances differ substantially with economic development, from inputs that are inadequate to maintain soil fertility in parts of many developing countries, particularly those of sub-Saharan Africa, to excessive and environmentally damaging surpluses in many developed and rapidly growing economies. National and/or regional policies contribute to patterns of nutrient use and their environmental consequences in all of these situations. Solutions to the nutrient challenges that face global agriculture can be informed by analyses of trajectories of change within, as well as across, agricultural systems.
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In Central Brazil, the long-term sustainability of beef cattle systems is under threat over vast tracts of farming areas, as more than half of the 50 million hectares of sown pastures are suffering from degradation. Overgrazing practised to maintain high stocking rates is regarded as one of the main causes. High stocking rates are deliberate and crucial decisions taken by the farmers, which appear paradoxical, even irrational given the state of knowledge regarding the consequences of overgrazing. The phenomenon however appears inextricably linked with the objectives that farmers hold. In this research those objectives were elicited first and from their ranking two, ‘asset value of cattle (representing cattle ownership)' and ‘present value of economic returns', were chosen to develop an original bi-criteria Compromise Programming model to test various hypotheses postulated to explain the overgrazing behaviour. As part of the model a pasture productivity index is derived to estimate the pasture recovery cost. Different scenarios based on farmers' attitudes towards overgrazing, pasture costs and capital availability were analysed. The results of the model runs show that benefits from holding more cattle can outweigh the increased pasture recovery and maintenance costs. This result undermines the hypothesis that farmers practise overgrazing because they are unaware or uncaring about overgrazing costs. An appropriate approach to the problem of pasture degradation requires information on the economics, and its interplay with farmers' objectives, for a wide range of pasture recovery and maintenance methods. Seen within the context of farmers' objectives, some level of overgrazing appears rational. Advocacy of the simple ‘no overgrazing' rule is an insufficient strategy to maintain the long-term sustainability of the beef production systems in Central Brazil.
Resumo:
In Central Brazil, the long-term, sustainability of beef cattle systems is under threat over vast tracts of farming areas, as more than half of the 50 million hectares of sown pastures are suffering from. degradation. Overgrazing practised to maintain high stocking rates is regarded as one of the main causes. High stocking rates are deliberate and crucial decisions taken by the farmers, which appear paradoxical, even irrational given the state of knowledge regarding the consequences of overgrazing. The phenomenon however appears inextricably linked with the objectives that farmers hold. In this research those objectives were elicited first and from their ranking two, 'asset value of cattle (representing cattle ownership and 'present value of economic returns', were chosen to develop an original bi-criteria Compromise Programming model to test various hypotheses postulated to explain the overgrazing behaviour. As part of the model a pasture productivity index is derived to estimate the pasture recovery cost. Different scenarios based on farmers' attitudes towards overgrazing, pasture costs and capital availability were analysed. The results of the model runs show that benefits from holding more cattle can outweigh the increased pasture recovery and maintenance costs. This result undermines the hypothesis that farmers practise overgrazing because they are unaware or uncaring caring about overgrazing costs. An appropriate approach to the problem of pasture degradation requires information on the economics,and its interplay with farmers' objectives, for a wide range of pasture recovery and maintenance methods. Seen within the context of farmers' objectives, some level of overgrazing appears rational. Advocacy of the simple 'no overgrazing' rule is an insufficient strategy to maintain the long-term sustainability of the beef production systems in Central Brazil. (C) 2004 Elsevier Ltd. All rights reserved.
Resumo:
If the fundamental precepts of Farming Systems Research were to be taken literally then it would imply that for each farm 'unique' solutions should be sought. This is an unrealistic expectation, but it has led to the idea of a recommendation domain, implying creating a taxonomy of farms, in order to increase the general applicability of recommendations. Mathematical programming models are an established means of generating recommended solutions, but for such models to be effective they have to be constructed for 'truly' typical or representative situations. The multi-variate statistical techniques provide a means of creating the required typologies, particularly when an exhaustive database is available. This paper illustrates the application of this methodology in two different studies that shared the common purpose of identifying types of farming systems in their respective study areas. The issues related with the use of factor and cluster analyses for farm typification prior to building representative mathematical programming models for Chile and Pakistan are highlighted. (C) 2003 Elsevier Science Ltd. All rights reserved.
Resumo:
In the 'rice-wheat' and the 'cotton-wheat' farming systems of Pakistan's Punjab, late planting of wheat is a perennial problem due to often delayed harvesting of the previously planted and late maturing rice and cotton crops. This leaves very limited time for land preparation for 'on-time' planting of wheat. 'No-tillage' technologies that reduce the turn-round time for wheat cultivation after rice and cotton have been developed, but their uptake has not been as expected.-This paper attempts to determine the farm and farmer characteristics and other socio-economic factors that influence the adoption of 'no-tillage' technologies'. Logit models were developed for the analysis undertaken. In the 'cotton-wheat' system personal characteristics like education, tenancy status, attitude towards risk implied in the use of new technologies and contact with extension agents are the main factors that affect adoption. As regards the 'rice-wheat' system, resource endowments such as farm size, access to a 'no-tillage' drill, clayey soils and the area sown to the rice-wheat sequence along with tenancy and contact with extension agents were dominant in explaining adoption. (C) 2002 Elsevier Science Ltd. All rights reserved.
Resumo:
There have been few rigorous assessments of the effectiveness of participatory processes for natural resource management. In Bangladesh an approach known as Participatory Action Plan Development (PAPD) has been developed and applied. By combining problem identification and solution analysis by separate stakeholder groups with plenary sessions it is claimed to result in consensus and more effective community based management. Methodological issues in assessing the effectiveness of such development are discussed and good practice illustrated. Under the same project there were sites where PAPD had been used and others without its use so a comparative assessment could be made. However, for an appropriate assessment it is important to identify clear testable hypotheses regarding the expected benefits, appropriate measures, and other factors which may affect or confound the outcome. The paper illustrates how participatory assessment involving both individual opinions and focus groups can be systematically recorded, quantified and used with other data in statistical analysis. By using statistical modelling methods at an appropriate level of aggregation and controlling for other factors, benefits from PAPD were found to be significant. The systematic approaches and practices recommended from this example can be applied in similar situations to test the effectiveness of participatory processes using participatory assessments.