994 resultados para Common land


Relevância:

40.00% 40.00%

Publicador:

Resumo:

Well-functioning factor markets are an essential condition for the competitiveness and sustainable development of agriculture and rural areas. At the same time, the functioning of the factor markets themselves is influenced by changes in agriculture and the rural economy. Such changes can be the result of progress in technology, globalisation and European market integration, changing consumer preferences and shifts in policy. Changes in the Common Agricultural Policy (CAP) over the last decade have particularly affected the rural factor markets. This book analyses the functioning of factor markets for agriculture in the EU-27 and several candidate countries. Written by leading academics and policy analysts from various European countries, these chapters compare the different markets, their institutional framework, their impact on agricultural development and structural change, and their interaction with the CAP. As the first comparative study to cover rural factor markets in Europe, highlighting their diversity − despite the Common Agricultural Policy and an integrated single market − Land, Labour & Capital Markets in European Agriculture provides a timely and valuable source of information at a time of further CAP reform and the continuing transformation of the EU's rural areas.

Relevância:

40.00% 40.00%

Publicador:

Resumo:

Against the background of the current discussion about the EU’s common agricultural policy (CAP) after 2013, the question of the impact of government support on land prices is crucially important. Validation of the CAP’s success also hinges on a proper assessment of a choice of policy instruments. This study therefore has the objective of investigating on a theoretical basis the effects of different government support measures on land rental prices and land allocation. The different measures under consideration are the price support, area payments and decoupled single farm payments (SFPs) of the CAP. Our approach evaluates the potential impact of each measure based on a Ricardian land rent model with heterogeneous land quality and multiple land uses. We start with a simple model of one output and two inputs, where a Cobb-Douglas production technology is assumed between the two factors of land and non-land inputs. In a second step, an outside option is introduced. This outside option, as opposed to land use of the Ricardian type, is independent of land quality. The results show that area payments and SFPs become fully capitalised into land rents, whereas in a price support scheme the capitalisation depends on per-acreage productivity. Moreover, in a price support scheme and a historical model, the capitalisation is positively influenced by land quality. Both area payments and price supports influence land allocation across different uses compared with no subsidies, where the shift tends to be larger in an area payment scheme than in a price support scheme. By contrast, SFPs do not influence land allocation.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

The Brazilian Amazon is one of the most rapidly developing agricultural frontiers in the world. The authors assess changes in cropland area and the intensification of cropping in the Brazilian agricultural frontier state of Mato Grosso using remote sensing and develop a greenhouse gas emissions budget. The most common type of intensification in this region is a shift from single-to double-cropping patterns and associated changes in management, including increased fertilization. Using the enhanced vegetation index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor, the authors created a green-leaf phenology for 2001-06 that was temporally smoothed with a wavelet filter. The wavelet-smoothed green-leaf phenology was analyzed to detect cropland areas and their cropping patterns. The authors document cropland extensification and double-cropping intensification validated with field data with 85% accuracy for detecting croplands and 64% and 89% accuracy for detecting single-and double-cropping patterns, respectively. The results show that croplands more than doubled from 2001 to 2006 to cover about 100 000 km(2) and that new double-cropping intensification occurred on over 20% of croplands. Variations are seen in the annual rates of extensification and double-cropping intensification. Greenhouse gas emissions are estimated for the period 2001-06 due to conversion of natural vegetation and pastures to row-crop agriculture in Mato Grosso averaged 179 Tg CO(2)-e yr(-1),over half the typical fossil fuel emissions for the country in recent years.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Biogeochemistry is hosting this special thematic issue devoted to studies of land-water interactions, as part of the Large-scale Biosphere-Atmosphere Experiment in Amaznia (LBA). This compilation of papers covers a broad range of topics with a common theme of coupling land and water processes, across pristine and impacted systems. Findings highlighted that hydrologic flowpaths are clearly important across basin size and structure in determining how water and solutes reach streams. Land-use changes have pronounced impacts on flowpaths, and subsequently, on stream chemistry, from small streams to large rivers. Carbon is produced and transformed across a broad array of fluvial environments and wetlands. Surface waters are not only driven by, but provide feedback to, the atmosphere.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Soil compaction that follows the clearing of tropical forest for cattle pasture is associated with lower soil hydraulic conductivity and increased frequency and volume of overland flow. We investigated the frequency of perched water tables, overland flow and stormflow in an Amazon forest and in an adjacent 25-year-old pasture cleared from the same forest. We compared the results with the frequencies of these phenomena estimated from comparisons of rainfall intensity and soil hydraulic conductivity. The frequency of perched water tables based on rainfall intensity and soil hydraulic conductivity was expected to double in pasture compared with forest. This corresponded closely with an approximate doubling of the frequency of stormflow and overland flow in pasture. In contrast, the stormflow volume in pasture increased 17-fold. This disproportional increase of stormflow resulted from overland flow generation over large areas of pasture, while overland flow generation in the forest was spatially limited and was observed only very near the stream channel. In both catchments, stormflow was generated by saturation excess because of perched water tables and near-surface groundwater levels. Stormflow was occasionally generated in the forest by rapid return flow from macropores, while slow return flow from a continuous perched water table was more common in the pasture. These results suggest that deforestation for pasture alters fundamental mechanisms of stormflow generation and may increase runoff volumes over wide regions of Amazonia. (C) 2009 Elsevier B.V. All rights reserved.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Comparative phylogeography has proved useful for investigating biological responses to past climate change and is strongest when combined with extrinsic hypotheses derived from the fossil record or geology. However, the rarity of species with sufficient, spatially explicit fossil evidence restricts the application of this method. Here, we develop an alternative approach in which spatial models of predicted species distributions under serial paleoclimates are compared with a molecular phylogeography, in this case for a snail endemic to the rainforests of North Queensland, Australia. We also compare the phylogeography of the snail to those from several endemic vertebrates and use consilience across all of these approaches to enhance biogeographical inference for this rainforest fauna. The snail mtDNA phylogeography is consistent with predictions from paleoclimate modeling in relation to the location and size of climatic refugia through the late Pleistocene-Holocene and broad patterns of extinction and recolonization. There is general agreement between quantitative estimates of population expansion from sequence data (using likelihood and coalescent methods) vs. distributional modeling. The snail phylogeography represents a composite of both common and idiosyncratic patterns seen among vertebrates, reflecting the geographically finer scale of persistence and subdivision in the snail. In general, this multifaceted approach, combining spatially explicit paleoclimatological models and comparative phylogeography, provides a powerful approach to locating historical refugia and understanding species' responses to them.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Mathematical models and statistical analysis are key instruments in soil science scientific research as they can describe and/or predict the current state of a soil system. These tools allow us to explore the behavior of soil related processes and properties as well as to generate new hypotheses for future experimentation. A good model and analysis of soil properties variations, that permit us to extract suitable conclusions and estimating spatially correlated variables at unsampled locations, is clearly dependent on the amount and quality of data and of the robustness techniques and estimators. On the other hand, the quality of data is obviously dependent from a competent data collection procedure and from a capable laboratory analytical work. Following the standard soil sampling protocols available, soil samples should be collected according to key points such as a convenient spatial scale, landscape homogeneity (or non-homogeneity), land color, soil texture, land slope, land solar exposition. Obtaining good quality data from forest soils is predictably expensive as it is labor intensive and demands many manpower and equipment both in field work and in laboratory analysis. Also, the sampling collection scheme that should be used on a data collection procedure in forest field is not simple to design as the sampling strategies chosen are strongly dependent on soil taxonomy. In fact, a sampling grid will not be able to be followed if rocks at the predicted collecting depth are found, or no soil at all is found, or large trees bar the soil collection. Considering this, a proficient design of a soil data sampling campaign in forest field is not always a simple process and sometimes represents a truly huge challenge. In this work, we present some difficulties that have occurred during two experiments on forest soil that were conducted in order to study the spatial variation of some soil physical-chemical properties. Two different sampling protocols were considered for monitoring two types of forest soils located in NW Portugal: umbric regosol and lithosol. Two different equipments for sampling collection were also used: a manual auger and a shovel. Both scenarios were analyzed and the results achieved have allowed us to consider that monitoring forest soil in order to do some mathematical and statistical investigations needs a sampling procedure to data collection compatible to established protocols but a pre-defined grid assumption often fail when the variability of the soil property is not uniform in space. In this case, sampling grid should be conveniently adapted from one part of the landscape to another and this fact should be taken into consideration of a mathematical procedure.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Within only two decades olive oil developed from a niche product which could hardly be found in food stores outside the producing regions towards an integrated component in the diets of industrial countries. This paper discusses the impacts of the promotion of the “healthy Mediterranean diet” on land use and agro-ecosystems in the producing countries. It examines the dynamics of olive oil production, trade and consumption in the EU15 in the period 1972 to 2003 and the links between dietary patterns, trade and land use. It analyses the underlying socio-economic driving forces behind the increasing spatial disconnect between production and consumption of olive oil in the EU15 and in particular in Spain, the world largest producer during the last three decades. In the observed period olive oil consumption increased 16 fold in the non-producing EU15 countries. In the geographically limited producing regions like Spain, the 5 fold increase in export production was associated with the rapid industrialization of olive production, the conversion of vast Mediterranean landscapes to olive monocultures and a range of environmental pressures. High amounts of subsidies of the European Common Agricultural Policy and feedback loops within production and consumption systems were driving the transformation of the olive oil system. Our analysis indicates the process of change was not immediately driven by increases in demand for olive oil in non-producing countries, but rather by the institutional setting of the European Union and by concerted political interventions.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Understanding Iowa’s geology and hydrology provides the critical information needed to ensure that our natural resources are properly utilized and protected. Gaining this knowledge and helping Iowans apply it is the core function of your Iowa Geological Survey (IGS).

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Iowa Department of Natural Resources fact sheet on Geographic Information Systems.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Using LiDAR to Scan Iowa from Aircraft

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Among the types of remote sensing acquisitions, optical images are certainly one of the most widely relied upon data sources for Earth observation. They provide detailed measurements of the electromagnetic radiation reflected or emitted by each pixel in the scene. Through a process termed supervised land-cover classification, this allows to automatically yet accurately distinguish objects at the surface of our planet. In this respect, when producing a land-cover map of the surveyed area, the availability of training examples representative of each thematic class is crucial for the success of the classification procedure. However, in real applications, due to several constraints on the sample collection process, labeled pixels are usually scarce. When analyzing an image for which those key samples are unavailable, a viable solution consists in resorting to the ground truth data of other previously acquired images. This option is attractive but several factors such as atmospheric, ground and acquisition conditions can cause radiometric differences between the images, hindering therefore the transfer of knowledge from one image to another. The goal of this Thesis is to supply remote sensing image analysts with suitable processing techniques to ensure a robust portability of the classification models across different images. The ultimate purpose is to map the land-cover classes over large spatial and temporal extents with minimal ground information. To overcome, or simply quantify, the observed shifts in the statistical distribution of the spectra of the materials, we study four approaches issued from the field of machine learning. First, we propose a strategy to intelligently sample the image of interest to collect the labels only in correspondence of the most useful pixels. This iterative routine is based on a constant evaluation of the pertinence to the new image of the initial training data actually belonging to a different image. Second, an approach to reduce the radiometric differences among the images by projecting the respective pixels in a common new data space is presented. We analyze a kernel-based feature extraction framework suited for such problems, showing that, after this relative normalization, the cross-image generalization abilities of a classifier are highly increased. Third, we test a new data-driven measure of distance between probability distributions to assess the distortions caused by differences in the acquisition geometry affecting series of multi-angle images. Also, we gauge the portability of classification models through the sequences. In both exercises, the efficacy of classic physically- and statistically-based normalization methods is discussed. Finally, we explore a new family of approaches based on sparse representations of the samples to reciprocally convert the data space of two images. The projection function bridging the images allows a synthesis of new pixels with more similar characteristics ultimately facilitating the land-cover mapping across images.