147 resultados para Agricultural abandonment
Resumo:
From 1948 to 1994, the agricultural sector was afforded special treatment in the GATT. We analyse the extent to which this agricultural exceptionalism was curbed as a result of the GATT Uruguay Round Agreement on Agriculture, discuss why it was curbed and finally explore the implication of this for EU policy making. We argue that, in particular, two major changes in GATT institutions brought about restrictions on agricultural exceptionalism. First, the Uruguay Round was a 'single undertaking' in which progress on other dossiers was contingent upon an outcome on agriculture. The EU had keenly supported this new decision rule in the GATT. Within the EU this led to the MacSharry reforms of the Common Agricultural Policy (CAP) in 1992, paving the way for a trade agreement on agriculture within the GATT. Second, under the new quasi-judicial dispute settlement procedure, countries are expected to bring their policies into conformity with WTO rules or face retaliatory trade sanctions. This has brought about a greater willingness on the part of the EU to submit its farm policy to WTO disciplines.
Resumo:
This paper argues that the Uruguay Round Agreement on Agriculture (URAA) introduced the market liberal paradigm as the ideational underpinning of the new farm trade regime. Though the immediate consequences in terms of limitations on agricultural support and protection were very modest, the Agreement did impact on the way in which domestic farm policy evolves. It forced EU agricultural policy makers to consider the agricultural negotiations when reforming the Common Agricultural Policy (CAP). The new paradigm in global farm trade resulted in a process of institutional layering in which concerns raised in the World Trade Organization (WTO) were gradually incorporated in EU agricultural institutions. This has resulted in gradual reform of the CAP in which policy instruments have been changed in order to make the CAP more WTO compatible. The underlying paradigm, the state-assisted paradigm, has been sustained though it has been rephrased by introducing the concept of multifunctionality.
Resumo:
This article demonstrates that the design and nature of agricultural support schemes has an influence on farmers' perception of their level of dependence on agricultural support. While direct aid payments inform farmers about the extent to which they are subsidised, indirect support mechanisms veil the level of subsidisation, and therefore they are not fully aware of the extent to which they are supported. To test this hypothesis, we applied data from a survey of 4,500 farmers in three countries: the United Kingdom, Germany and Portugal. It is demonstrated that indirect support, such as that provided through artificially high consumer prices, gives an illusion of free and competitive markets among farmers. This 'visibility' hypothesis is evaluated against an alternative hypothesis that assumes farmers have complete, or at least a fairly comprehensive level of, information on agricultural support schemes. Our findings show that this alternative hypothesis can be ruled out.
Resumo:
1. Recent changes in European agricultural policy have led to measures to reverse the loss of species-rich grasslands through the creation of new areas on ex-arable land. Ex-arable soils are often characterized by high inorganic nitrogen (N) levels, which lead to the rapid establishment of annual and fast-growing perennial species during the initial phase of habitat creation. The addition of carbon (C) to the soil has been suggested as a countermeasure to reduce plant-available N and alter competitive interactions among plant species. 2. To test the effect of C addition on habitat creation on ex-arable land, an experiment was set up on two recently abandoned fields in Switzerland and on two 6-year-old restoration sites in the UK. Carbon was added as a mixture of either sugar and sawdust or wood chips and sawdust during a period of 2 years. The effects of C addition on soil parameters and vegetation composition were assessed during the period of C additions and 1 year thereafter. 3. Soil nitrate concentrations were reduced at all sites within weeks of the first C addition, and remained low until cessation of the C additions. The overall effect of C addition on vegetation was a reduction in above-ground biomass and cover. At the Swiss sites, the addition of sugar and sawdust led to a relative increase in legume and forb cover and to a decrease in grass cover. The soil N availability, composition of soil micro-organisms and vegetation characteristics continued to be affected after cessation of C additions. 4. Synthesis and applications. The results suggest that C addition in grassland restoration is a useful management method to reduce N availability on ex-arable land. Carbon addition alters the vegetation composition by creating gaps in the vegetation that facilitates the establishment of late-seral plant species, and is most effective when started immediately after the abandonment of arable fields and applied over several years.
Resumo:
Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate forecasts has employed historic analogs based on categorical ENSO indices. Other methods based on classification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within climate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate'.
Resumo:
Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate forecasts has employed historic analogs based on categorical ENSO indices. Other methods based on classification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within climate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate'.
Resumo:
This paper assesses the impact of the 'decoupling' reform of the Common Agricultural Policy on the labour allocation decisions of Irish farmers. The agricultural household decision-making model provides the conceptual and theoretical framework to examine the interaction between government subsidies and farmers' time allocation decisions. The relationship postulated is that 'decoupling' of agricultural support from production would probably result in a decline in the return to farm labour but it would also lead to an increase in household wealth. The effect of these factors on how farmers allocate their time is tested empirically using labour participation and labour supply models. The models developed are sufficiently general for application elsewhere. The main findings for the Irish situation are that the decoupling of direct payments is likely to increase the probability of farmers participating in the off-farm employment market and that the amount of time allocated to off-farm work will increase.