48 resultados para Spatial variation


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Dispersal limitation and environmental conditions are crucial drivers of plant species distribution and establishment. As these factors operate at different spatial scales, we asked: Do the environmental factors known to determine community assembly at broad scales operate at fine scales (few meters)? How much do these factors account for community variation at fine scales? In which way do biotic and abiotic interactions drive changes in species composition? We surveyed the plant community within a dry grassland along a very steep gradient of soil characteristics like pH and nutrients. We used a spatially explicit sampling design, based on three replicated macroplots of 15x15, 12x12 and 12x12 meters in extent. Soil samples were taken to quantify several soil properties (carbon, nitrogen, plant available phosphorus, pH, water content and dehydrogenase activity as a proxy for overall microbial activity). We performed variance partitioning to assess the effect of these variables on plant composition and statistically controlled for spatial autocorrelation via eigenvector mapping. We also applied null model analysis to test for non-random patterns in species co-occurrence using randomization schemes that account for patterns expected under species interactions. At a fine spatial scale, environmental factors explained 18% of variation when controlling for spatial autocorrelation in the distribution of plant species, whereas purely spatial processes accounted for 14% variation. Null model analysis showed that species spatially segregated in a non-random way and these spatial patterns could be due to a combination of environmental filtering and biotic interactions. Our grassland study suggests that environmental factors found to be directly relevant in broad scale studies are present also at small scales, but are supplemented by spatial processes and more direct interactions like competition.

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Two common scenarios in Geoforensics (definition in text) are considered: the provenance, or localization of unknown samples and the question of sample variability at scenes of crime/alibi locations. Both have been discussed in forensic and soil science publications, but mostly within a theoretical or non-forensic context. These previous publications provide context for the two case study scenarios (one actual, one based on a range of criminal casework) that consider provenance and variability. A challenging scientific question in geoforensics is the provenance question: ‘where may this sample have come from?’ A question the Tellus data can assist in answering. The question of variation between samples maybe less of a challenge, yet variation between a suspect sample within a scene of crime requires detailed sampling. Variation on a larger (tens to hundreds of kilometres) scale may provide useful intelligence on where a sample came from. To summarise, databases such as Tellus and TellusBorder may be used as effective tools to assist in the search for the origin of displaced soil and sediment

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The density and composition of stream bed metal deposits are affected by physical, chemical and biological processes. In this paper we investigate the importance of these processes and their relation to algal and non-photosynthetic detrital (NPD) biomass in a set of upland streams in Northern Ireland. Deposit density and Fe, Mn, Al and P concentrations varied with stream pH across sites but not seasonally. No effects of stream bed erosion or photoreduction were detected on deposit densities. Seasonal variation in stream water metal concentrations was correlated with rainfall. NPD biomass was a significant predictor of both spatial and seasonal variation in deposit concentrations. There were strong, non-linear, relations between NPD biomass and deposit metal concentrations, with Fe and Mn becoming relatively more important and algal biomass declining above threshold deposit/NPD densities. The results suggest that NPD biomass influences deposit density and reduces the biomass of photosynthetic autotrophs above a threshold deposit density.