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.

<p> The dataset aims at studying associations between mating system parameters and fitness in natural populations of trees. Fifty-eight open-pollinated progeny arrays were collected from trees in three populations. Progeny were planted in a reciprocal transplant trial. Fitness was measured by family establishment rates. We genotyped all trees and their progeny at eight microsatellite loci. Planting site had a strong effect on fitness, but seed provenance and seed provenance × planting site did not. Populations had comparable mating system parameters and were generally outcrossed, experienced low biparental inbreeding and high levels of multiple paternity. As predicted, seed families that had more multiple paternities also had higher fitness, and no fitness-inbreeding correlations were detected. Demonstrating that fitness was most affected by multiple paternities rather than inbreeding, we provide evidence supporting the constrained inbreeding hypothesis; i.e. that multiple paternity may impact on fitness over and above that of inbreeding, particularly for preferentially outcrossing trees at life stages beyond seed development. This dataset could potentially be reused for meta-analysis or review of effects of habitat fragmentation on plants (e.g. pollination, mating system, genetic diversity etc). Please contact owner prior to re-use. </p> <p>This is part of the authors' PhD at the University of Adelaide, supervised by Prof Andrew Lowe, Dr Mike Gardner and Dr Kym Ottewell. Main goals of the project were 1. Examine and quantify the impact of fragmentation and tree density on mating patterns, and how this may vary with pollinators of differing mobility 2. Determine the theoretical expectations and perform empirical tests of mating pattern-fitness relationships in trees 3. Explore the plant genetic resource management implications that arise from the observations in aims 1 and 2 </p>

In 1963, the Glen Canyon Dam, in Hite Utah was completed, creating the Lake Powell reservoir along the Colorado River. The water levels of Lake Powell peaked in 1983 and have declined since, releasing over-pressure on the underlying sediment. This release in over-pressure created mud volcanoes, structures along the shoreline made of cavities that allow fluid and gases to rise to the surface and escape. Green house gases including methane are released from these structures, and to better understand how development of natural wetlands can result in unintended increased levels of greenhouse gas emissions, we asked 1) how much of each gas is generated or and whether the amount of each gas is changing through time and 2) how are these gases forming in the subsurface? We first measured the amounts of carbon dioxide (CO2), methane (CH4), and air (N) in volcano gas samples collected in 2014, 2015, and 2016. We found that from 2014 through 2016, methane levels from these volcanoes fluctuated significantly. In 2016, we looked at the amounts of carbon and hydrogen isotopes in the methane, which told us the gas is generated from microorganisms feeding on organic matter and is released during water-level fluctuations. We looked at mud volcanoes only located along the Lake Powell marina delta in Hite, Utah. The data spans geological structures restricted to one marina delta.

There are presence absence records for vegetation and matched hydrological data from 687 1 x 1 m quadrats recorded from 11 wetlands and wetland complexes (28 sampled hydrological gradients (referred to as transects) across the upper and lower southeast of South Australia. Plant data were collected in spring 2013. Hydrological monitoring data at each site consisted of continuous (6 hourly) surface water level data from a state agency monitoring network. Observed water levels at the monitoring instrument on the day of monitoring were related to the observed depth of water at each quadrat, assuming a flat, level water surface and obtain a datum for each quadrat relative to the monitoring instrument. The continuous monitoring record was then used to calculate a range of different hydrological predictors indicating the variation at each quadrat. The hydrological dataset provided are the univariate summary statistics recording different aspects of surface water dynamics for each quadrat. Hydrological predictors (sum-exceedance value, hydroperiod and maximum inundation depth) were calculated for annual and seasonal periods in the three-years prior to plant data collection. See metadata and relevant publication for additional details on calculation. Hydrological predictors for each quadrat are provided in a single matrix of sites by predictors, with relevant location details for the quadrat (xy coordinates, site, transect). Included is a single electrical conductivity class for each transect (ordinal variable - low moderate, high - see metadata). Vegetation data are provided as a single matrix (quadrats x plant functional group) showing presence absence of each functional group in each quadrat. There is also a lookup table giving the assignment of each plant species to a plant functional group.

This data set is a compilation of biomass sampling of 15,054 individual measurements of 274 tree and shrub species across 826 sites in the Australian mainland, reported in 94 studies between 1950 and 2015. Various methods were used across sites, but all involved destructive harvests of individual trees or shrubs and measuring the fresh weight of above-ground biomass. Sub-sampling was used to determine moisture content, after which dry weight of the above-ground biomass was calculated. See publication for details: "Keryn I. Paul, John Larmour, Alison Specht, Ayalsew Zerihun, Peter Ritson, Stephen H. Roxburgh, Stan Sochacki, Tom Lewis, Craig V.M. Barton, Jacqueline R. England, Michael Battaglia, Anthony O'Grady, Elizabeth Pinkard, Grahame Applegate, Justin Jonson, Kim Brooksbank, Rob Sudmeyer, Dan Wildy, Kelvin D. Montagu, Matt Bradford, Don Butler, Trevor Hobbs, Testing the generality of below-ground biomass allometry across plant functional types, Forest Ecology and Management. 432: 102-114. https://doi.org/10.1016/j.foreco.2018.08.043. Paul, K.I., Larmour, J., Specht, A., Zerihun, A., Ritson, P., Roxburgh, S.H., Sochacki, S., Lewis, T., Barton, C.V.M., England, J.R., Battaglia, M., O’Grady, A., Pinkard, E., Applegate, G., Jonson, J., Brooksbank, K., Sudmeyer, R., Wildy, D., Montagu, K.D., Bradford, M., Butler, D., Hobbs, T., 2019. Testing the generality of below-ground biomass allometry across plant functional types. Forest Ecology and Management 432, 102–114. https://doi.org/10.1016/j.foreco.2018.08.043

River sites were sampled during the summers of 2008/09 and 2009/10 in a survey designed to identify correlations between commonly used river condition variables and grazing land-use. Potential stream sites in northern Tasmania were screened by catchment size, northing and slope, and according to attributes aimed at minimising confounding variables, maintaining broad consistency in landscape and geomorphological context, and promoting independence among sites. A set of 27 survey sites was selected across a gradient from low to high proportion of land under grazing in their upstream catchments. Catchment sizes varied from 20-120 km2 and proportion grazing from 0-80%. Macroinvertebrates were sampled using Surber sampler. All macroinvertebrates within a 20% sub-sample identified to family and counted, with individuals from the insect orders Ephemeroptera, Plecoptera and Trichoptera identified to genus/species (by Laurie Cook, UTAS). Algal abundance was estimated at each site as the proportion of algal cover and as areal density of benthic chlorophyll a. Physical data variables collected were: water temperature, conductivity, turbidity, pH, total alkalinity, nitrate+nitrate, dissolved reactive phosphorus, total nitrogen, total phosphorus, overhead shading, the proportion of fine sediments within the sampled riffle zone, accumulated abstraction index and accumulated regulation index. For more information see: See Magierowski RH, Read SM, Carter SJB, Warfe DM, Cook LS, Lefroy EC and Davies PE. Inferring landscape-scale land-use impacts on rivers using data from mesocosm experiments and artificial neural networks. PLOS ONE.

This data set is a compilation of individual tree and shrub above-ground biomass (dry weight), stem diameter, height, and associated auxiliary information about the sites from which the trees or shrubs were sampled. The data were derived from numerous different projects over the last 5 decades. However, the project under which support was given to collate these datasets was Australia's Department of the Environments Methodology Development Program's Complex Wood System Project (MDP-CWS). The objective of the MDP-CWS project was to develop tools and information to underpin increased land manager participation in the domestic carbon market; the Emissions Reduction Fund (ERF). However, the intention is that this database will be expanded over time and have much greater use than just supporting carbon accounting methodologies. See publication for details: "Keryn I. Paul, John Larmour, Alison Specht, Ayalsew Zerihun, Peter Ritson, Stephen H. Roxburgh, Stan Sochacki, Tom Lewis, Craig V.M. Barton, Jacqueline R. England, Michael Battaglia, Anthony O'Grady, Elizabeth Pinkard, Grahame Applegate, Justin Jonson, Kim Brooksbank, Rob Sudmeyer, Dan Wildy, Kelvin D. Montagu, Matt Bradford, Don Butler, Trevor Hobbs, Testing the generality of below-ground biomass allometry across plant functional types, Forest Ecology and Management. 432: 102-114. https://doi.org/10.1016/j.foreco.2018.08.043. Paul, K.I., Larmour, J., Specht, A., Zerihun, A., Ritson, P., Roxburgh, S.H., Sochacki, S., Lewis, T., Barton, C.V.M., England, J.R., Battaglia, M., O’Grady, A., Pinkard, E., Applegate, G., Jonson, J., Brooksbank, K., Sudmeyer, R., Wildy, D., Montagu, K.D., Bradford, M., Butler, D., Hobbs, T., 2019. Testing the generality of below-ground biomass allometry across plant functional types. Forest Ecology and Management 432, 102–114. https://doi.org/10.1016/j.foreco.2018.08.043

The dataset includes two main components: (1) Tree survey - data on the species, diameter and height of individual trees, along with a count of seedlings and saplings; and (2) Coarse woody debris - data on the size and decay class of downed coarse woody debris encountered in the plots.