970 resultados para Degraded pasture


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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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In Brazil the intensive agriculture use, mainly pasture, is the main cause of the presence of extensive areas of degraded lands. This study aimed to assess the impact of different soil management practices in a pasture degraded area used as garbage disposal. The experiment was performed at the Faculdade de Engenharia Agrícola, Universidade Estadual de Campinas - UNICAMP, in Campinas, state of São Paulo, Brazil, from 1990 to 1996. This area has undergone a process of recovery through removal of trash deposited on the surface, in 1985, levelling of soil, followed by application of limestone, subsoiling, planting of legumes (Crotalaria juncea) and crop rotation (soybean and maize). Since 1990 only popcorn maize was grown and established plots managed with different soil tillage systems, including harrow, chisel plow, moldboard plow, no tillage, disk plow and revolving hoe. One plot was planted exclusively with guinea grass (Panicum maximum) to serve as a reference for minimum loss of soil and another grown on a downhill direction to correspond to the expected maximum erosion. There were differences in sediment loss, nutrient loss and productivity of the popcorn maize in the period analyzed. The chisel plow and no tillage treatments caused the slightest loss of soil and nutrients, compared to other tillage systems. The results show that the soil management systems influenced the physical and chemical characteristics of soil, allowing an economical and environmental recovery of the area, providing the conditions for grain agricultural production.

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Greenhouse gas emissions from a well established, unfertilized tropical grass-legume pasture were monitored over two consecutive years using high resolution automatic sampling. Nitrous oxide emissions were highest during the summer months and were highly episodic, related more to the size and distribution of rain events than WFPS alone. Mean annual emissions were significantly higher during 2008 (5.7 ± 1.0 g N2O-N/ha/day) than 2007 (3.9 ± 0.4 and g N2O-N/ha/day) despite receiving nearly 500 mm less rain. Mean CO2 (28.2 ± 1.5 kg CO2 C/ha/day) was not significantly different (P < 0.01) between measurement years, emissions being highly dependent on temperature. A negative correlation between CO2 and WFPS at >70% indicated a threshold for soil conditions favouring denitrification. The use of automatic chambers for high resolution greenhouse gas sampling can greatly reduce emission estimation errors associated with temperature and WFPS changes.

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The effect of conversion from forest-to-pasture upon soil carbon stocks has been intensively discussed, but few studies focus on how this land-use change affects carbon (C) distribution across soil fractions in the Amazon basin. We investigated this in the 20 cm depth along a chronosequence of sites from native forest to three successively older pastures. We performed a physicochemical fractionation of bulk soil samples to better understand the mechanisms by which soil C is stabilized and evaluate the contribution of each C fraction to total soil C. Additionally, we used a two-pool model to estimate the mean residence time (MRT) for the slow and active pool C in each fraction. Soil C increased with conversion from forest-to-pasture in the particulate organic matter (> 250 mu m), microaggregate (53-250 mu m), and d-clay (< 2 mu m) fractions. The microaggregate comprised the highest soil C content after the conversion from forest-to-pasture. The C content of the d-silt fraction decreased with time since conversion to pasture. Forest-derived C remained in all fractions with the highest concentration in the finest fractions, with the largest proportion of forest-derived soil C associated with clay minerals. Results from this work indicate that microaggregate formation is sensitive to changes in management and might serve as an indicator for management-induced soil carbon changes, and the soil C changes in the fractions are dependent on soil texture.

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Since land use change can have significant impacts on regional biogeochemistry, we investigated how conversion of forest and cultivation to pasture impact soil C and N cycling. In addition to examining total soil C, we isolated soil physiochemical C fractions in order to understand the mechanisms by which soil C is sequestered or lost. Total soil C did not change significantly over time following conversion from forest, though coarse (250-2,000 mum) particulate organic matter C increased by a factor of 6 immediately after conversion. Aggregate mean weight diameter was reduced by about 50% after conversion, but values were like those under forest after 8 years under pasture. Samples collected from a long-term pasture that was converted from annual cultivation more than 50 years ago revealed that some soil physical properties negatively impacted by cultivation were very slow to recover. Finally, our results indicate that soil macroaggregates turn over more rapidly under pasture than under forest and are less efficient at stabilizing soil C, whereas microaggregates from pasture soils stabilize a larger concentration of C than forest microaggregates. Since conversion from forest to pasture has a minimal impact on total soil C content in the Piedmont region of Virginia, United States, a simple C stock accounting system could use the same base soil C stock value for either type of land use. However, since the effects of forest to pasture conversion are a function of grassland management following conversion, assessments of C sequestration rates require activity data on the extent of various grassland management practices.

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We assessed the effect of biochar incorporation into the soil on the soil-atmosphere exchange of the greenhouse gases (GHG) from an intensive subtropical pasture. For this, we measured N2O, CH4 and CO2 emissions with high temporal resolution from April to June 2009 in an existing factorial experiment where cattle feedlot biochar had been applied at 10 t ha-1 in November 2006. Over the whole measurement period, significant emissions of N2O and CO2 were observed, whereas a net uptake of CH4 was measured. N2O emissions were found to be highly episodic with one major emission pulse (up to 502 µg N2O-N m-2 h 1) following heavy rainfall. There was no significant difference in the net flux of GHGs from the biochar amended vs. the control plots. Our results demonstrate that intensively managed subtropical pastures on ferrosols in northern New South Wales of Australia can be a significant source of GHG. Our hypothesis that the application of biochar would lead to a reduction in emissions of GHG from soils was not supported in this field assessment. Additional studies with longer observation periods are needed to clarify the long term effect of biochar amendment on soil microbial processes and the emission of GHGs under field conditions.

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Vernier acuity, a form of visual hyperacuity, is amongst the most precise forms of spatial vision. Under optimal conditions Vernier thresholds are much finer than the inter-photoreceptor distance. Achievement of such high precision is based substantially on cortical computations, most likely in the primary visual cortex. Using stimuli with added positional noise, we show that Vernier processing is reduced with advancing age across a wide range of noise levels. Using an ideal observer model, we are able to characterize the mechanisms underlying age-related loss, and show that the reduction in Vernier acuity can be mainly attributed to the reduction in efficiency of sampling, with no significant change in the level of internal position noise, or spatial distortion, in the visual system.

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The conventional mechanical properties of articular cartilage, such as compressive stiffness, have been demonstrated to be limited in their capacity to distinguish intact (visually normal) from degraded cartilage samples. In this paper, we explore the correlation between a new mechanical parameter, namely the reswelling of articular cartilage following unloading from a given compressive load, and the near infrared (NIR) spectrum. The capacity to distinguish mechanically intact from proteoglycan-depleted tissue relative to the "reswelling" characteristic was first established, and the result was subsequently correlated with the NIR spectral data of the respective tissue samples. To achieve this, normal intact and enzymatically degraded samples were subjected to both NIR probing and mechanical compression based on a load-unload-reswelling protocol. The parameter δ(r), characteristic of the osmotic "reswelling" of the matrix after unloading to a constant small load in the order of the osmotic pressure of cartilage, was obtained for the different sample types. Multivariate statistics was employed to determine the degree of correlation between δ(r) and the NIR absorption spectrum of relevant specimens using Partial Least Squared (PLS) regression. The results show a strong relationship (R(2)=95.89%, p<0.0001) between the spectral data and δ(r). This correlation of δ(r) with NIR spectral data suggests the potential for determining the reswelling characteristics non-destructively. It was also observed that δ(r) values bear a significant relationship with the cartilage matrix integrity, indicated by its proteoglycan content, and can therefore differentiate between normal and artificially degraded proteoglycan-depleted cartilage samples. It is therefore argued that the reswelling of cartilage, which is both biochemical (osmotic) and mechanical (hydrostatic pressure) in origin, could be a strong candidate for characterizing the tissue, especially in regions surrounding focal cartilage defects in joints.

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Soil-based emissions of nitrous oxide (N2O), a well-known greenhouse gas, have been associated with changes in soil water-filled pore space (WFPS) and soil temperature in many previous studies. However, it is acknowledged that the environment-N2O relationship is complex and still relatively poorly unknown. In this article, we employed a Bayesian model selection approach (Reversible jump Markov chain Monte Carlo) to develop a data-informed model of the relationship between daily N2O emissions and daily WFPS and soil temperature measurements between March 2007 and February 2009 from a soil under pasture in Queensland, Australia, taking seasonal factors and time-lagged effects into account. The model indicates a very strong relationship between a hybrid seasonal structure and daily N2O emission, with the latter substantially increased in summer. Given the other variables in the model, daily soil WFPS, lagged by a week, had a negative influence on daily N2O; there was evidence of a nonlinear positive relationship between daily soil WFPS and daily N2O emission; and daily soil temperature tended to have a linear positive relationship with daily N2O emission when daily soil temperature was above a threshold of approximately 19°C. We suggest that this flexible Bayesian modeling approach could facilitate greater understanding of the shape of the covariate-N2O flux relation and detection of effect thresholds in the natural temporal variation of environmental variables on N2O emission.

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Nitrous oxide (N2O) is one of the greenhouse gases that can contribute to global warming. Spatial variability of N2O can lead to large uncertainties in prediction. However, previous studies have often ignored the spatial dependency to quantify the N2O - environmental factors relationships. Few researches have examined the impacts of various spatial correlation structures (e.g. independence, distance-based and neighbourhood based) on spatial prediction of N2O emissions. This study aimed to assess the impact of three spatial correlation structures on spatial predictions and calibrate the spatial prediction using Bayesian model averaging (BMA) based on replicated, irregular point-referenced data. The data were measured in 17 chambers randomly placed across a 271 m(2) field between October 2007 and September 2008 in the southeast of Australia. We used a Bayesian geostatistical model and a Bayesian spatial conditional autoregressive (CAR) model to investigate and accommodate spatial dependency, and to estimate the effects of environmental variables on N2O emissions across the study site. We compared these with a Bayesian regression model with independent errors. The three approaches resulted in different derived maps of spatial prediction of N2O emissions. We found that incorporating spatial dependency in the model not only substantially improved predictions of N2O emission from soil, but also better quantified uncertainties of soil parameters in the study. The hybrid model structure obtained by BMA improved the accuracy of spatial prediction of N2O emissions across this study region.

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"The extended drought periods in each degradation episode have provided a test of the capacity of grazing systems (i.e. land, plants, animals, humans and social structure) to handle stress. Evidence that degradation was already occurring was identified prior to the extended drought sequences. The sequence of dry years, ranging from two to eight years, exposed and/or amplified the degradation processes. The unequivocal evidence was provided by: (a) the physical 'horror' of bare landscapes, erosion scalds and gullies and dust storms; (b) the biological devastation of woody weeds and animal suffering/deaths or forced sales, and; (c) the financial and emotional plight of graziers and their families due to reduced production in some cases leading to abandonment of properties or, sadly, deaths (e.g. McDonald 1991, Ker Conway 1989)."--Publisher website

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Exotic grasses have been introduced in countries worldwide for pasture improvement, soil stabilisation and ornamental purposes. Some of these introductions have proven successful, but many have not (Cook & Dias 2006). In Australia, the Commonwealth Plant Introduction Scheme was initiated in 1929, and over-time introduced more than 5000 species of grasses, legumes and other forage and browse plants (Cook & Dias 2006). Lonsdale (1994) suggested that, in tropical Australia, 13% of introductions have become a problem, with only 5% being considered useful for agriculture. Low (1997) suggested that 5 out of 18 of Australia's worst tropical environmental weeds were intentionally introduced as pasture grasses. The spread and dominance of invasive grass species that degrade the quality of pastures for production can impact significantly on the livelihoods of small proprietors. Although Livestock grazing contributes only a small percentage to the world's GDP (1.5%), maintaining the long-term stability of this industry is crucial because of the high social and environmental consequence of a collapse. One billion of the world's poor are dependent on livestock grazing for food and income with this industry occupying more than 25% of the world's land base (Steinfeld et al. 2006). The ling-term sustainability of livestock grazing is also crucial for the environment. A recent FAO report attributed livestock production as a major cause of five of the most serious environmental problems: global warming, land degredation, air and water pollution, and the loss of biodiversity (Steinfeld et al. 2006). For these reasons, finding more effective approaches that guide the sustainable management of pastures is urgently needed. In Australia more than 55% of land use is for livestock grazing by sheelp and/or cattle. This land use dominate in the semi-arid and arid regions where rainfall and soil conditions are marginal for production (Commonwealth of Australia 2004). Although the level of agriculture production by conglomerates is increasing, the majority of livestock grazing within Australia remains family owned and operated (Commonwealth of Australia 2004). The sustainability of production from a grazed pasture is dependent on its botanical composition (Kemp & Dowling 1991, Kemp et al. 1996). In a grazed pasture, the dominance of an invasive grass species can impact on the functional integrity of the ecosystem, including production and nutrient cycling; wwhich will in turn, affect the income of proprietors and the ability of the system to recover from disturbance and environmental change. In Australia, $0.3 billion is spent on weed control in livestock production, but despite this substantial investment $1.9 billion is still lost in yield as a result of weeds (Sinden et al. 2004). In this paper, we adaprt a framework proposed for the restoration of degraded rainforest communities (Lamb & Gilmour 2003, Lamb et al. 2005) to compare and contrast options for recovering function integrity (i.e. a diverse set of desirable plant species that maintain key ecological processes necessary for sustainable production and nutrient cycling) within pasture communities dominated by an invasive grass species. To do this, we uase a case-study of the invasion of Eragrostis curvula (Africal lovegrss; hereafter, Lovegrass), a serious concern in Australian agricultural communities (Parsons and Cuthbertson 1992). The spread and dominance of Lovegrass is a problem because its low palatability, low nutritional content and competitiveness affect the livelihood of graziers by reducing the diversity of other plant species. We conclude by suggesting modifications to this framework for pasture ecosystems to help increase the effiency of strategies to protect functional integrity and balance social/economic and biodiversity values.