This dataset contains a series of spatial outputs describing probabilistic species predictive occupancy (Species Occupancy Models, or SOM) & habitat suitability (Maximum Entropy, or Maxent) surfaces, the underlying data used to calculate these models & model projections predicting the impact of climate change on flora Maxent surfaces. <br> Model outputs are combination outputs dependent on known species occurrence in the landscape, the species relationship with environmental variables (covariates) such as temperature, rainfall and topography; and its predicted occurrence based on covariate analysis. Maxent models do not predict actual occupancy, but rather habitat suitability, while SOMs predict actual occupancy. confounding factors such as inter-species competition, geographical barriers and disturbance events play a significant role in species occurrence, and are not considered in Maxent or SOM. Flora Maxent climate change projections used NSW and Australian Regional Climate Modelling (NARCliM) variables to predict habitat suitability for a baseline year 2000 and projections for 2030 and 2070. <br> Covariates, Fauna & Flora survey records used to create the models are included. <br> More detailed information regarding each model, its processes and outputs are included in the dataset. <br> A web mapping application on the NSW Spatial Collaboration Portal depicts Maxent & SOM of a selected group of vulnerable Flora & Fauna from this dataset. Access the webapp through the link below: <br> https://portal.spatial.nsw.gov.au/portal/home/item.html?id=78e6ae3d34aa45d2b8118fd0308d6459

These datasets consist of soil maps generated to assess baselines, drivers and trends for soil health and stability within the NSW Regional Forest Agreement (RFA) regions. <br> The maps are organised into empirical soil maps, digital soil maps, and data cube maps. <br> Empirical soil maps consists of four products. Maps include topsoil pH, carbon, Emerson Aggregate Stability and Soil Profile Quality Confidence. Each map consists of 2,162 units. Maps were generated using the most representative soil profile for each unit available within the Soil and Land Information System (SALIS). The 2008 woody vegetation coverage was used as baseline. Maps reflect values when the sampling occurred with temporal changes not being accounted for. Locations with missing or of poor quality data are identified, providing a confidence rating map as part of the evaluation process.<br> Digital soil maps include map products of key soil condition indicators covering the Regional Forest Agreement regions of eastern NSW. Raster maps of key soil indicators, such as soil carbon, pH, bulk density, hillslope erosion and others, were created at 100 m resolution. For each key soil indicator, maps include baseline (approximately 2008) levels as well as trends of change resulting from different human and natural disturbances such as forest harvesting, uncontrolled stock grazing, climate change and bush fire. <br> Data cube maps include time series of soil organic carbon (SOC) between January 1990 and December 2020 for the Regional Forest Agreement regions of eastern NSW. Products provide estimates of SOC concentrations and associated trends through time. Modelling was carried out using a data cube platform incorporating machine learning space-time framework and geospatial technologies. Important covariates required to drive this spatio-temporal modelling were identified using the Recursive Feature Elimination algorithm (RFE). <br> A web mapping application on the NSW Spatial Collaboration Portal depicts these datasets. Access the webapp through the link below:<br> https://portal.spatial.nsw.gov.au/portal/home/item.html?id=af9c71935f024f4a8f64cb39f5eba007

This data set is a collection of Highly Important Papers in Ecology (HIPE). Three files are included: VoteArticles.final.csv : a comma-delimited text file with the vote assessments on the relative quality of the submitted papers (Top 10, Between 11-25, Between 26-100 or Not in the top "100") and an indication of how well each voter knew the paper (Read it, Know it or Don't know it) HIP.refs.txt : tab-delimited text file with all paper bibliographic information citation.csv : a comma-delimited text file with the citation data (Google Scholar, Web of Knowledge) for each paper and each journal (Impact Factor).

This dataset comprises of new, high precision radiocarbon dates for 20 mainland thylacines and 24 mainland devils. Metadata includes museum accession numbers and origin of specimens. We envision that this dataset could be used in studies of paleo-ecological reconstructions and for estimating extinction time for both devils and thylacines on mainland Australia. This dataset includes the youngest reliable fossil ages for both species on mainland Australia as per the criteria set out in Rodriguez-Rey at al (2015). <i>"Criteria for assessing the quality of Middle Pleistocene to Holocene vertebrate fossil ages."</i> Quaternary Geochronology 30 (2015): 69-79.

A total of 53 native Australian species (52x C3, 1x C4) were sampled from 22 plant families and 7 growth forms along a transect in WA spanning 9.56 degrees latitude and 6.85 degrees longitude. Samples were collected using the nationally-accepted AusPlots Rangelands methodology. Samples were stored to preserve isotopic signatures and analysed using standard techniques for mass spectroscopy, including internationally-calibrated standards. Technical replicates of 13% showed very low drift (0.07).

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.