998 resultados para 0501 Ecological Applications


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Effects of agricultural intensification (AI) on biodiversity are often assessed on the plot scale, although processes determining diversity also operate on larger spatial scales. Here, we analyzed the diversity of vascular plants, carabid beetles, and birds in agricultural landscapes in cereal crop fields at the field (n = 1350), farm (n = 270), and European-region (n = 9) scale. We partitioned diversity into its additive components alpha, beta, and gamma, and assessed the relative contribution of beta diversity to total species richness at each spatial scale. AI was determined using pesticide and fertilizer inputs, as well as tillage operations and categorized into low, medium, and high levels. As AI was not significantly related to landscape complexity, we could disentangle potential AI effects on local vs. landscape community homogenization. AI negatively affected the species richness of plants and birds, but not carabid beetles, at all spatial scales. Hence, local AI was closely correlated to beta diversity on larger scales up to the farm and region level, and thereby was an indicator of farm-and region-wide biodiversity losses. At the scale of farms (12.83-20.52%) and regions (68.34-80.18%), beta diversity accounted for the major part of the total species richness for all three taxa, indicating great dissimilarity in environmental conditions on larger spatial scales. For plants, relative importance of alpha diversity decreased with AI, while relative importance of beta diversity on the farm scale increased with AI for carabids and birds. Hence, and in contrast to our expectations, AI does not necessarily homogenize local communities, presumably due to the heterogeneity of farming practices. In conclusion, a more detailed understanding of AI effects on diversity patterns of various taxa and at multiple spatial scales would contribute to more efficient agri-environmental schemes in agroecosystems.

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Beta diversity describes how local communities within an area or region differ in species composition/abundance. There have been attempts to use changes in beta diversity as a biotic indicator of disturbance, but lack of theory and methodological caveats have hampered progress. We here propose that the neutral theory of biodiversity plus the definition of beta diversity as the total variance of a community matrix provide a suitable, novel, starting point for ecological applications. Observed levels of beta diversity (BD) can be compared to neutral predictions with three possible outcomes: Observed BD equals neutral prediction or is larger (divergence) or smaller (convergence) than the neutral prediction. Disturbance might lead to either divergence or convergence, depending on type and strength. We here apply these ideas to datasets collected on oribatid mites (a key, very diverse soil taxon) under several regimes of disturbances. When disturbance is expected to increase the heterogeneity of soil spatial properties or the sampling strategy encompassed a range of diverging environmental conditions, we observed diverging assemblages. On the contrary, we observed patterns consistent with neutrality when disturbance could determine homogenization of soil properties in space or the sampling strategy encompassed fairly homogeneous areas. With our method, spatial and temporal changes in beta diversity can be directly and easily monitored to detect significant changes in community dynamics, although the method itself cannot inform on underlying mechanisms. However, human-driven disturbances and the spatial scales at which they operate are usually known. In this case, our approach allows the formulation of testable predictions in terms of expected changes in beta diversity, thereby offering a promising monitoring tool.

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High resolution descriptions of plant distribution have utility for many ecological applications but are especially useful for predictive modelling of gene flow from transgenic crops. Difficulty lies in the extrapolation errors that occur when limited ground survey data are scaled up to the landscape or national level. This problem is epitomized by the wide confidence limits generated in a previous attempt to describe the national abundance of riverside Brassica rapa (a wild relative of cultivated rapeseed) across the United Kingdom. Here, we assess the value of airborne remote sensing to locate B. rapa over large areas and so reduce the need for extrapolation. We describe results from flights over the river Nene in England acquired using Airborne Thematic Mapper (ATM) and Compact Airborne Spectrographic Imager (CASI) imagery, together with ground truth data. It proved possible to detect 97% of flowering B. rapa on the basis of spectral profiles. This included all stands of plants that occupied >2m square (>5 plants), which were detected using single-pixel classification. It also included very small populations (<5 flowering plants, 1-2m square) that generated mixed pixels, which were detected using spectral unmixing. The high detection accuracy for flowering B. rapa was coupled with a rather large false positive rate (43%). The latter could be reduced by using the image detections to target fieldwork to confirm species identity, or by acquiring additional remote sensing data such as laser altimetry or multitemporal imagery.

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High resolution descriptions of plant distribution have utility for many ecological applications but are especially useful for predictive modeling of gene flow from transgenic crops. Difficulty lies in the extrapolation errors that occur when limited ground survey data are scaled up to the landscape or national level. This problem is epitomized by the wide confidence limits generated in a previous attempt to describe the national abundance of riverside Brassica rapa (a wild relative of cultivated rapeseed) across the United Kingdom. Here, we assess the value of airborne remote sensing to locate B. rapa over large areas and so reduce the need for extrapolation. We describe results from flights over the river Nene in England acquired using Airborne Thematic Mapper (ATM) and Compact Airborne Spectrographic Imager (CASI) imagery, together with ground truth data. It proved possible to detect 97% of flowering B. rapa on the basis of spectral profiles. This included all stands of plants that occupied >2m square (>5 plants), which were detected using single-pixel classification. It also included very small populations (<5 flowering plants, 1-2m square) that generated mixed pixels, which were detected using spectral unmixing. The high detection accuracy for flowering B. rapa was coupled with a rather large false positive rate (43%). The latter could be reduced by using the image detections to target fieldwork to confirm species identity, or by acquiring additional remote sensing data such as laser altimetry or multitemporal imagery.

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Forecasting the effects of stressors on the dynamics of natural populations requires assessment of the joint effects of a stressor and population density on the population response. The effects can be depicted as a contour map in which the population response, here assessed by Population growth rate, varies with stress and density in the same way that the height of land above sea level varies with latitude and longitude. We present the first complete map of this type using as our model Folsomia candida exposed to five different concentrations of the widespread anthelmintic veterinary medicine ivermectin in replicated microcosm experiments lasting 49 days. The concentrations of ivermectin in yeast were 0.0, 6.8 28.83 66.4 and 210.0 mg/L wet weight. Increasing density and chemical concentration both significantly reduced the population growth rate of Folsomia candida, in part through effects on food consumption and fecundity. The interaction between density and ivermectin concentration was "less-than-additive," implying that at high density populations were able to compensate for the effects of the chemical. This result demonstrates that regulatory protocols carried out at low density (as in most past experiments) may seriously overestimate effects in the field, where densities are locally high and populations are resource limited (e.g., in feces of livestock treated with ivermectin).

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Very few studies have analyzed the dependence of population growth rate on population density, and even fewer have considered interaction effects of density and other stresses, such as exposure to toxic chemicals. Yet without such studies we cannot know whether chemicals harmful at low density have effects on carrying capacity or, conversely, whether chemicals reducing carrying capacity are also harmful at low density, impeding a population's capacity to recover from disturbance. This study examines the combined effects of population density and a toxicant (fluoranthene) on population growth rate (pgr) and carrying capacity using the deposit-feeding polychaete Capitella sp. I as a test organism. Populations were initiated with a stable age distribution, and population density and age/size distribution were followed during a period of 28 wk. Fluoranthene (FLU), population density, and their interaction influenced population growth rate. Population growth rate declined linearly with the logarithm of population biomass, but the slope of the relationship was steeper for the control populations than for populations exposed to 50 mug FLU/(g sediment dry mass). Populations exposed to 150 mug FLU/(g sediment dry mass) went extinct after 8 wk of exposure. Despite concerns that toxicant effects would be exacerbated at high density, we found the reverse to be the case, and effects of fluoranthene on population growth rate were much reduced in the region of carrying capacity. Fluoranthene did. reduce carrying capacity by 46%, and this could haven important implications for interacting species and/or sediment biogeochemical processes.

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This paper presents results of the AQL2004 project, which has been develope within the GOFC-GOLD Latin American network of remote sensing and forest fires (RedLatif). The project intended to obtain monthly burned-land maps of the entire region, from Mexico to Patagonia, using MODIS (moderate-resolution imaging spectroradiometer) reflectance data. The project has been organized in three different phases: acquisition and preprocessing of satellite data; discrimination of burned pixels; and validation of results. In the first phase, input data consisting of 32-day composites of MODIS 500-m reflectance data generated by the Global Land Cover Facility (GLCF) of the University of Maryland (College Park, Maryland, U.S.A.) were collected and processed. The discrimination of burned areas was addressed in two steps: searching for "burned core" pixels using postfire spectral indices and multitemporal change detection and mapping of burned scars using contextual techniques. The validation phase was based on visual analysis of Landsat and CBERS (China-Brazil Earth Resources Satellite) images. Validation of the burned-land category showed an agreement ranging from 30% to 60%, depending on the ecosystem and vegetation species present. The total burned area for the entire year was estimated to be 153 215 km2. The most affected countries in relation to their territory were Cuba, Colombia, Bolivia, and Venezuela. Burned areas were found in most land covers; herbaceous vegetation (savannas and grasslands) presented the highest proportions of burned area, while perennial forest had the lowest proportions. The importance of croplands in the total burned area should be taken with reserve, since this cover presented the highest commission errors. The importance of generating systematic products of burned land areas for different ecological processes is emphasized.

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Individual-based models (IBMs) can simulate the actions of individual animals as they interact with one another and the landscape in which they live. When used in spatially-explicit landscapes IBMs can show how populations change over time in response to management actions. For instance, IBMs are being used to design strategies of conservation and of the exploitation of fisheries, and for assessing the effects on populations of major construction projects and of novel agricultural chemicals. In such real world contexts, it becomes especially important to build IBMs in a principled fashion, and to approach calibration and evaluation systematically. We argue that insights from physiological and behavioural ecology offer a recipe for building realistic models, and that Approximate Bayesian Computation (ABC) is a promising technique for the calibration and evaluation of IBMs. IBMs are constructed primarily from knowledge about individuals. In ecological applications the relevant knowledge is found in physiological and behavioural ecology, and we approach these from an evolutionary perspective by taking into account how physiological and behavioural processes contribute to life histories, and how those life histories evolve. Evolutionary life history theory shows that, other things being equal, organisms should grow to sexual maturity as fast as possible, and then reproduce as fast as possible, while minimising per capita death rate. Physiological and behavioural ecology are largely built on these principles together with the laws of conservation of matter and energy. To complete construction of an IBM information is also needed on the effects of competitors, conspecifics and food scarcity; the maximum rates of ingestion, growth and reproduction, and life-history parameters. Using this knowledge about physiological and behavioural processes provides a principled way to build IBMs, but model parameters vary between species and are often difficult to measure. A common solution is to manually compare model outputs with observations from real landscapes and so to obtain parameters which produce acceptable fits of model to data. However, this procedure can be convoluted and lead to over-calibrated and thus inflexible models. Many formal statistical techniques are unsuitable for use with IBMs, but we argue that ABC offers a potential way forward. It can be used to calibrate and compare complex stochastic models and to assess the uncertainty in their predictions. We describe methods used to implement ABC in an accessible way and illustrate them with examples and discussion of recent studies. Although much progress has been made, theoretical issues remain, and some of these are outlined and discussed.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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We developed a small version of the Caltech active strand cloud water collector (CASCC) for biogeochemical investigations in ecological applications. The device is battery powered and thus allows operation at locations where mains power is not available. The collector is designed for sampling periods of up to one week, depending on fog frequency. Our new device is equipped with standard sensors for air temperature, relative humidity, wind, and horizontal visibility for fog detection with a low-cost optical sensor. In mountain areas and during times when clouds are thin the installation of the visibility sensor became a key issue, which limits the potential to estimate liquid water content of the sampled fog. Field tests with 5 devices at three different sites in the Swiss Alps (Niesen) and the Jura Mountains (Lägeren, Switzerland) during two extended summer seasons in 2006 and 2007 showed that in almost all cases it was possible to obtain sample volumes which were large enough for the examination of basic inorganic chemistry of the collected cloud water. Collection rates varied typically from 12 to 30 mL h− 1. The fog droplet cutoff diameter is ≈ 6 μm, which is low enough to include all droplet sizes that are relevant for the liquid water content of typical fog types in the collected samples. From theoretical assumptions of the collection efficiency and theoretical droplet spectra it is possible to estimate the liquid water content of the sampled fog or cloud. Our new fog collector can be constructed and operated at relatively low costs. In combination with chemical and isotopic analyses of the sampled water, this allows to quantify nutrient and pollutant fluxes as is typically needed in ecosystem biogeochemistry studies.

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Recent changes in sanitary policies within the European Union (EU) concerning disposal of carcasses of domestic animals and the increase of non-natural mortality factors, such as illegal poisoning, are threatening European vultures. However, the effects of anthropogenic activities on demographic parameters are poorly studied. Using a long-term study (1994–2011) of the threatened Pyrenean Bearded Vulture Gypaetus barbatus population, we assess the variation in the proportion of breeding pairs, egg-laying dates, clutch size, breeding success, and survival following a sharp reduction in food availability in 2005 due to the application of restrictive sanitary policies decreasing livestock carcass availability. We found a delay in laying dates and a regressive trend in clutch size, breeding success, and survival following policy change. The maintenance of specific supplementary feeding stations for Bearded Vultures probably reduced the negative effects of illegal poisoning and food shortages, which mainly affected subadult survival. A drop in food availability may have produced changes in demographic parameters and an increase in mortality due to an increased exposure to contaminated food. As a result, supplementary feeding as a precautionary measure can be a useful tool to reduce illegal poisoning and declines in demographic parameters until previous food availability scenarios are achieved. This study shows how anthropogenic activities through human health regulations that affect habitat quality can suddenly modify demographic parameters in long-lived species, including those, such as survival, with high sensitivity to population growth rate.

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Facilitation is a major force shaping the structure and diversity of plant communities in terrestrial ecosystems. Detecting positive plant–plant interactions relies on the combination of field experimentation and the demonstration of spatial association between neighboring plants. This has often restricted the study of facilitation to particular sites, limiting the development of systematic assessments of facilitation over regional and global scales. Here we explore whether the frequency of plant spatial associations detected from high-resolution remotely sensed images can be used to infer plant facilitation at the community level in drylands around the globe. We correlated the information from remotely sensed images freely available through Google Earth with detailed field assessments, and used a simple individual-based model to generate patch-size distributions using different assumptions about the type and strength of plant–plant interactions. Most of the patterns found from the remotely sensed images were more right skewed than the patterns from the null model simulating a random distribution. This suggests that the plants in the studied drylands show stronger spatial clustering than expected by chance. We found that positive plant co-occurrence, as measured in the field, was significantly related to the skewness of vegetation patch-size distribution measured using Google Earth images. Our findings suggest that the relative frequency of facilitation may be inferred from spatial pattern signals measured from remotely sensed images, since facilitation often determines positive co-occurrence among neighboring plants. They pave the road for a systematic global assessment of the role of facilitation in terrestrial ecosystems. Read More: http://www.esajournals.org/doi/10.1890/14-2358.1

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Globalization has resulted in unprecedented movements of people, goods, and alien species across the planet. Although the impacts of biological invasions are widely appreciated, a bias exists in research effort to post-dispersal processes because of the difficulties of measuring propagule pressure. The Antarctic provides an ideal model system in which to investigate propagule movements because of the region's isolation and small number of entry routes. Here we investigated the logistics operations of the South African National Antarctic Programme (SANAP) and quantified the initial dispersal of alien species into the region. we found that over 1400 seeds from 99 taxa are transported into the Antarctic each field season in association with SANAP passenger luggage and cargo. The first ever assessment of propagule drop-off indicated that 30-50% of these propagules will enter the recipient environment. Many of the taxa include cosmopolitan weeds and known aliens in the Antarctic, indicating that logistics operations form part of a globally self-perpetuating cycle moving alien species between areas of human disturbance. in addition, propagules of some taxa native to the Antarctic region were also found, suggesting that human movements may be facilitating intra-regional homogenization. Several relatively simple changes in biosecurity policy that could significantly reduce the threat of introduction of nonnative species are suggested.