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The dataset consists of results from two stream mesocosm experiments that were conducted in the summer-autumn of 1996 and 1997 to distinguish the influence of fine sediment loads and nutrient concentrations on benthic macro-invertebrate and algal communities. 11 biological variables were extracted from the results of this experiment and were standardized for the purpose of training neural networks that could be used to diagnose nutrient and fine sediment impacts in field surveys. The 11 variables were selected according to how well they correlated with the experimental treatment levels (high and low values of both nutrients and fine sediments). The 11 variables were: chlorophyll a (mg/m2), macro-invertebrate familial richness, total abundance, and the abundance of <em>Oligochaeta, Leptoperla varia (Gripopterygidae), Nousia spp. (Leptophlebiidae), Austrophlebioides spp. (Leptophlebiidae), Orthocladiinae, Tanypodinae, Tipulidae</em> and larval <em>Scirtidae</em>. These taxa were abundant within and among the stream mesocosm communities and are common in a wide range of Tasmanian rivers. Values for each of 11 biological response variables were standardized by dividing by their average value observed in the experimental controls mesocosm samples from that year. See Magierowski RH, Read SM, Carter SJB, Warfe DM, Cook LS, Lefroy EC, et al. (2015) <i>Inferring Landscape-Scale Land-Use Impacts on Rivers Using Data from Mesocosm Experiments and Artificial Neural Networks.</i> PLoS ONE 10(3): e0120901. https://doi.org/10.1371/journal.pone.0120901 https://doi.org/10.1371/journal.pone.0120901. This data was collected for the purpose of training artificial neural networks that could diagnose nutrient and sediment impacts in Tasmanian rivers. Each of the 11 variables were standardized by their average value observed in the experimental control samples from that year and some experimental treatment effects (Light) were ignored to simplify the neural network training process. Therefore, these data should not be used to make conclusions about the impacts of fine sediments and nutrients in Tasmanian rivers.
The dataset describes the occurrence of bird species at sites within a burnt woodland. These sites comprise the following design: 5 replicate block. each with 2 large patch sites, 2 small patch sites and 2 matrix sites. One site of each pair was relatively more isolated than the other (surrounded by a higher proportion of unburnt vegetation). In addition, there are also 6 sites located beyond the extent of the fire. The data-set also lists vegetation attributes at each of these sites.
The dataset contains distribution data for the Yellow Crazy Ant (<i>Anoplolepis gracilipes</i>) and scale insects (eg <i>Parasaissetia nigra</i>, ,i>Dysmicoccus finitimus</i>), collected during the Waypoint Survey component of the Pulu Keeling National Park Island-wide Survey (IWS). The aim of the Waypoint Survey is to monitor densities of the invasive Yellow Crazy Ant (<i>Anoplolepis gracilipes</i>) and to detect establishment of any new scale insect species. The other components of the IWS (Transit Survey and Ink Card and Nocturnal Survey) are recorded in separate submissions.
The QBEIS survey database (formerly CORVEG) contains ecosystem physical and vegetation characteristics, including structural and floristic attributes as well as descriptions of landscape, soil and geologic features, collected at study locations across Queensland since 1982. The resulting survey database provides a comprehensive record of areas ground-truthed during the regional ecosystems mapping process and a basis for future updating of mapping or other relevant work such as species modelling.<br /><br /> Only validated survey data is made publicly available and all records of confidential taxa have been masked from the dataset. Data is accessible from the TERN Data Infrastructure, which provides the ability to extract subsets of vegetation, soil and landscape data across multiple data collections and bioregions for more than 100 variables including basal area, crown cover, growth form, stem density and vegetation height.