This dataset includes upper and lower thermal limits, voluntary exposure to extreme cold and warm temperatures, ATP levels, and longevity of <i>Acyrtociphom pisum</i> and <i>Hippodamia convergens</i>. Pathogens can modify many aspects of host behavior or physiology, with cascading impacts across trophic levels in terrestrial food webs. These changes include thermal tolerance of hosts, however, the effects of fungal infections on thermal tolerances and behavioral responses to extreme temperatures of prey (<i>Acyrtociphon pisum</i>) and predator (<i>Hippodamia convergens</i>) insect species have rarely been studied. We measured the impacts of fungal infection (at two levels: low and high spore load) on thermal tolerance (critical thermal maximum and minimum), voluntary exposure, energetic cost, and survival of both insect species. Fungal infection reduced thermal tolerance to heat in both insect species, but only reduced tolerance to cold of the predator. Voluntary exposure to extreme temperatures was modified by the infection, energetic cost increased with infection and thermal conditions, and survival was significantly reduced in both insect species.

Schools Weather and Air Quality (SWAQ) is a citizen science project funded by the Department of Industry, Innovation and Science as part of its Inspiring Australia - Citizen Engagement Program. SWAQ is equipping public schools across Sydney with research-grade meteorology and air quality sensors, enabling students to collect and analyse research quality data through curriculum-aligned classroom activities. The network includes twelve automatic weather stations and seven automatic air quality stations, stretched from -33.5995° to -34.0421° latitude and from 150.6913° to 151.2708° longitude. The average spacing is 10.2 km and the average installation height is 2.5 m above ground level. Optimum site allocation was determined by undertaking a multi-criteria weighted overlay analysis to ensure data representativeness and quality. Six meteorological parameters (dry-bulb temperature, relative humidity, barometric pressure, rain, wind speed, and wind direction) and six air pollutants (SO2, NO2, CO, O3, PM2.5, and PM10) are recorded. Observations and metadata are available from September 2019 for WXT536 + AQT420 stations and from October 2019 for WXT536 stations (refer to Table 1 of the Dataset Guide), thus encompassing the Black Summer bushfire and the COVID-19 lockdown period. Data routinely undergo quality control, quality assurance and publication.

NSW Office of Environment and Heritage Macarthur Forest Fire Danger index. Modelled fire frequency projections at ~10km resolution for 2060-2079 period using MIROC3.2 and R2 ensemble member using the WRF 3.3 model. This product will provide policy makers, land managers and researchers access to accurate and temporally fine scaled information with which to make hazard reduction and management strategies.

This vegetation survey data package comprises standardised vegetation condition measurements, which were first conducted in 2004 and then repeated in 2006, 2007, 2009, 2012, and 2017 using vegetation structure plots (1 m x 1 m, 20 m x 20 m) nested within 1 ha sites. Within the 100 m x 100 m 1 ha survey site, two 20 m x 20 m plots are located along a central transect at the 20–40 m and 60–80 m points. Within each of the 20 m x 20 m plots are four 1 m x 1 m subplots. Plot data are measured in two 20 m x 20 m plots at each site. Ground cover is measured in four 1 m x 1 m subplots located within each 20 m x 20 m plot. Landscape context variables are measured in polygons of 200 m and 500 m radii around each field site. Much of Booderee National Park was burned by wildfire in December 2003. The Jervis Bay Booderee National Park Plot Network was established in 2002 in Booderee National Park in the Jervis Bay Territory, south-eastern Australia. The study location is a floristically diverse area in which fire history has been well-documented over several decades. The plot network’s objectives involve quantifying the inter-relationships between natural disturbance and/or management intervention (including weed and feral animal control and prescribed burning) and the reciprocal changes in vegetation condition and biodiversity response. This particular study forms part of the collection of data packages from the Jervis Bay Booderee National Park Plot Network. A synopsis of related data packages which have been collected as part of the Jervis Bay Plot Network’s full program is provided at https://www.ltern.org.au/index.php/ltern-plot-networks/jervis-bay-booderee-national-park.

Modelled top-layer soil moisture (0-10 cm) using the Australian Water Resources Assessment model via assimilation of satellite soil moisture products: 97.5th percentile of the ensemble of model estimates. Note that the data represents the mean of an ensemble of 100 modelled estimates for each data derived via perturbed meteorological forcing. Resolution of the output data is 0.05-degree for the whole country. The unit of measure is relative wetness (0-1, indicating 0 and 100% degree of saturation).

Modelled top-layer soil moisture (0-10 cm) using the Australian Water Resources Assessment model via assimilation of satellite soil moisture products: 2.5th percentile of the ensemble of model estimates. Note that the data represents the mean of an ensemble of 100 modelled estimates for each data derived via perturbed meteorological forcing. Resolution of the output data is 0.05-degree for the whole country. The unit of measure is relative wetness (0-1, indicating 0 and 100% degree of saturation).

<br>This release consists of flux tower measurements of the exchange of energy and mass between the surface and the atmospheric boundary-layer using eddy covariance techniques. Data were processed using PyFluxPro (v3.4.7) as described by Isaac et al. (2017). PyFluxPro produces a final, gap-filled product with Net Ecosystem Exchange (NEE) partitioned into Gross Primary Productivity (GPP) and Ecosystem Respiration (ER). <br /> <br /> Located in a 5 km² block of relatively uniform open-forest savanna, the site is representative of high rainfall, frequently burnt tropical savanna. <br /><br /> Tropical savanna in Australia occupies 1.9 million km² across the north and given the extent of this biome, understanding biogeochemical cycles, impacts of fire on sequestration, vegetation and fauna is a national priority. In the NT, savanna ecosystems are largely intact in terms of tree cover, with only modest levels of land use change. Despite this, there is evidence of a loss of biodiversity, most likely due to shifts in fire regimes and a loss of patchiness in the landscape. Approximately 40 % of the savanna burn every year and understanding fire impacts on fauna and flora is essential for effective land management. <br /><br />

Modelled root-layer soil moisture (0-100 cm) using the Australian Water Resources Assessment model via assimilation of satellite soil moisture products: 2.5th percentile of the ensemble of model estimates. Note that the data represents the mean of an ensemble of 100 modelled estimates for each data derived via perturbed meteorological forcing. Resolution of the output data is 0.05-degree for the whole country. The unit of measure is relative wetness (0-1, indicating 0 and 100% degree of saturation).

Annual lowest period radiation for each 0.01 degree grid cell of the Australian continent. Modelled using eMAST-R-Package 2.0.

NSW Office of Environment and Heritage Macarthur Forest Fire Danger index. Modelled fire frequency projections at ~50km resolution for 1990-2009 period using CCCMA3.1 and R1 ensemble member using the WRF 3.3 model. This product will provide policy makers, land managers and researchers access to accurate and temporally fine scaled information with which to make hazard reduction and management strategies.