<p>The record comprises data on rabbit warren surveys conducted within the TGB Osborn (Koonamore) Vegetation Reserve (KVR) from 1977 to 2014 as part of ongoing rabbit control efforts. The Reserve was divided into 400x400 m grid squares (with exceptions for row 5 and column 6), and warrens were identified based on the presence of at least four rabbit holes. In some years, the entire Reserve was surveyed; in others, only a subset was covered. All identified warrens or holes were fumigated and filled following detection.</p> <p>This is version 2.0 of the Koonamore Rabbit Warren Survey data release.</p>

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

This is a data set on the prescence of Salmonella and the exposure of flavivirus in the Australian White Ibis. The data is presented in an excel file that lists, band numbers, sample dates, age, sex, bill lengths, presence of Salmonella in gut samples, and evidence of exposure to flavivirus for 72 birds sampled in the years 2002, 2003 and 2015 in Sydney, Australia. Detailed results listed in our open accessible manuscript published in the Journal of Urban Ecology in 2019. <em> https://academic.oup.com/jue/article/5/1/juz006/5506280</em>.

The dataset contains a record of coastal dolphin- Australian Snubfin (<em>Orcaella heinsohni</em>) and Indo-Pacific Humpback (<em>Sousa chinensis</em>)) species sighted, total number of individuals, and group/school size in Kakadu National Park rivers between March 2007 to August 2011.

The data set contains information on Camera Trap Fauna Survey conducted in the Samford Peri-urban Site in 2017. Information on the camera trap site location, height, observation time, species identification and related field remarks have been presented in this data set.

The dataset contains records of Robber Crab (<i>Birgus latro</i>) mortality across Christmas Island, including location co-ordinates and details of sex and thoracic length. To manage the impact of road mortality on the species, this monitoring project is designed to assess spatial variation in road mortality. Basic data are collected at the site (sex, size, date, coordinates).

FosSahul is the first database compiling the ages of nonhuman vertebrate fossils from the Middle Pleistocene to the present in the Sahul region. It includes comprehensive metadata with ratings of reliability allocated to each fossil age. Because ecological and evolutionary phenomena are time-dependent, the entire range of archaeological and palaeontological research disciplines benefit from the availability of this data.

This data set contains information on the Lizard Assemblages in Karawatha Peri-Urban site, South East Queensland. Site details, sampling methods and total number of individual animals is listed for each plot location.

Data is provided from three survey types: nocturnal drive-by monitoring; ground counts; and exit counts. The nocturnal drive-by monitoring dataset provides information on species presence/absence at 124 sites across Christmas Island. The ground count dataset provides information on numbers of bats observed roosting in trees at known camp sites; while the exit count dataset records counts of bats exiting from the respective camp sites.

The lesser hairy­footed dunnart (<i>Sminthopsis youngsoni, Dasyuridae</i>) is a generalist marsupial insectivore in arid Australia, but consumes wolf spiders (<i>Lycosa spp., Lycosidae</i>) disproportionately often relative to their availability. This project tested the hypothesis that this disproportionate predation is a product of frequent encounter rates between the interactants due to high overlap in their diets and use of space and time. This data set focuses on overlap in the use of different microhabitats of wolf spiders (<i>Lycosa spp.</i>) and the lesser hairy­footed dunnart (<i>Sminthopsis youngsoni</i>) in the Simpson Desert, south­western Queensland Australia. Microhabitat use was determined by estimating the percentage cover of seven microhabitat variables and distance to nearest cover along trails left by individuals of each species­ group and a randomly orientated (control) trail for each actual trail as a measure of the availability of each microhabitat within the local environment. Trail length was also recorded and data was collected across 16 trapping grids at Main Camp during July and October (winter and Spring) in 2017. Differences in microhabitat use between trail types (actual vs control) and species (lycosids vs dunnarts) were assessed using non­metric multidimensional scaling (NMDS) and permutational analyses of variance (PERMANOVA). These analyses were performed using this data.