The record contains information on beetle succession in decaying <i>Eucalyptus obliqua</i> logs, from 1999-2009. Data on beetle species identification, field sampling notes, and collection details from eucalyptus logs across the decade range from 1999 - 2009 are provided.

The data set contains information on the soil water content at various depths in the Samford Ecological Research Facility (SERF), Samford Peri-Urban Site. Information on soil water content is provided from two sensors, i.e., 1) Sentek Solo, for high frequency sampling and 2) Sentek Diviner, for coarser resolution sampling.

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).

This data contains vegetation cover, ground cover, tree density and stand basal area data across a multi-century time-since-fire sequence derived from growth ring-size relationships in fire-sensitive <em>Eucalyptus salubris</em> woodlands.

The record contains information on litterfall data from four 1-hectare plots from the Great Western Woodlands site collected in 2014. Data on total litter weights from fifteen litter traps in each of four 1-ha study plots and crown canopy cover percent is provided.

This data contains the visual assessment of fuel layers in fire-sensitive <em>Eucalyptus salubris</em> woodlands using Vesta methods across 24 sites in a multi-century (10 to 260+ years since fire) time-since-fire sequence derived from growth ring-size relationships.

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).

These datasets provide the data underlying the publication on <i>"Lines in the sand: quantifying the cumulative development footprint in the world’s largest remaining temperate woodland"</i> <em> https://link.springer.com/article/10.1007/s10980-017-0558-z. </em>. The datasets are: (A) data in csv format: [1] development footprint by sample area: Information on the 24, ~490 km^2 sample areas assessed in the study, including the different infrastructure types (roads, railways, mapped tracks, un-mapped tracks which have been manually digitized in the study using aerial imagery and hub infrastructure such as mine pits and waste rock dumps, also manually digitized in the study). Also contains some key co-variables assessed as potential explanatory variables for development footprint. The region-wide modelling of development footprint found strong positive effects of mining project density and pastoralism, as well as a highly significant negative interaction between the two. At low mining project densities, development footprints are more extensive in pastoral areas, but at high mining project densities, pastoral areas are relatively less developed than non-pastoral areas, on average. [2] Great Western Woodlands (GWW) 20 km grid: The datasets provides data for the 20x20 km grid placed over the whole GWW and used for the regional estimation of development footprint, linear infrastructure density, and linear infrastructure type based on the region-wide analysis. Data is for each cell in the grid and provides the total length of roads in that grid cell, MINEDEX mining projects, pastoral status, etc. This dateset was used to project the data from the 24 study areas across the whole of the Great Western Woodlands and calculate region-wide estimates of development footprint and linear infrastructure lengths. [3] disturbance by patch: This dataset provides the data for each patch for the analysis of patch-level drivers of development footprint, which was performed to gain further insights into the effects of other landscape variables that what could be gleaned from the region-wide analysis. For this analysis, we divided sample areas into polygonal patch types, each with a unique combination of the following categorical co-variables: pastoral tenure, greenstone lithology, conservation tenure, ironstone formation, schedule-1 area clearing restrictions, environmentally sensitive area designation, vegetation formation, and sample area. For each patch type (n=261), we calculated the following attributes: a) number of mining projects, b) number of dead mineral tenements, c) sum of duration of all live and dead tenements, d) type of tenements (exploration/prospecting tenement, mining and related activities tenement, none), e) primary target commodity (gold, nickel, iron-ore, other), f) distance to wheatbelt, and g) distance to the nearest town. [4] mapped versus digitized tracks: This dataset provides mapped and un-mapped track widths, measured using high-resolution aerial imagery at at least 20 randomly-generated locations within each of 24 sample areas. Pastoral tenure and mining intensity for each sample area are included for analysis purposes. [5] edge effect scenarios: Hypothetical edge effect zones were created, based on effect zones gleaned from the literature and arranged under three scenarios, to reflect potential risks of offsite impacts in areas adjacent to development footprints observed (see appendix 3 of article). The calculated proportion of the entire GWW within edge effect zones varied from ~3% under the conservative scenario to ~35% under the maximal scenario. Within the range of development footprints observed in this study, the proportion of a landscape that lies within edge effect zones increases hyperbolically with the number of mining projects, and approaches 100% in the maximal scenario, 60% in the moderate scenario, and ~20% under the conservative scenario. shapefiles: [6] Great Western Woodlands boundary, [7] sample areas (layer file shows sample areas by category).

The dataset accompanies the paper by Zemunik et al. (2015), which used the Jurien Bay dune chronosequence to investigate the changes in the community-wide suite of plant nutrient-acquisition strategies in response to long-term soil development. The study was located in the Southwest Australian biodiversity hotspot, in an area with an extremely rich regional flora. The dataset consists of both flora and soil data that not only allow all analyses presented in the paper (Zemunik et al. 2015) to be independently investigated, but also would allow further exploration of the data not considered or presented in the study. The study used a randomised stratified design, stratifying the dune system of the chronosequence into six stages, the first three spanning the Holocene (to ~6.5 ka) and oldest spanning soil development from the Early to Middle Pleistocene (to ~2 Ma). Floristic surveys were conducted in 60 permanent 10 m × 10 m plots (10 plots in each of six chronosequence stages). Each plot was surveyed at least once between August 2011 and March 2012, and September 2012. To estimate canopy cover and number of individuals for each plant species within the 10 m × 10 m plots, seven randomly-located 2 m × 2 m subplots were surveyed within each plot. Within each subplot, all vascular plant species were identified, the corresponding number of individuals was counted and the vertically projected vegetation canopy cover was estimated. Surface (0-20 cm) soil from each of the 420 subplots was collected, air dried and analysed at the Smithsonian Tropical Research Institute in Panama, for a range of chemical and physical properties, the main ones of which were considered in this paper being total and resin soil phosphorus, total nitrogen and dissolved organic nitrogen, soil total and organic carbon, and pH (measured in H20 and CaCl2). However, other soil data are also presented in the dataset. Nutrient-acquisition strategies were determined from the literature, where known, and from mycorrhizal analyses of root samples from species with poorly known strategies. Most of the currently known nutrient-acqusition strategies were found in the species of the chronosequence. Previous studies in the Jurien Bay chronosequence have established that its soil development conforms to models of long-term soil development first presented by Walker and Syers (1976); the youngest soils are N-limiting and the oldest are P-limiting (Laliberté et al. 2012). However, filtering of the regional flora by high soil pH on the youngest soils has the strongest effect on local plant species diversity (Laliberté et al. 2014). <br></br> References: [1] Zemunik, G., Turner, B., Lambers, H. et al. Diversity of plant nutrient-acquisition strategies increases during long-term ecosystem development. Nature Plants 1, 15050 (2015). https://doi.org/10.1038/nplants.2015.50 ; [2] T.W. Walker, J.K. Syers. The fate of phosphorus during pedogenesis Geoderma, 15 (1) (1976), pp. 1-19, 10.1016/0016-7061(76)90066-5 ; [3] Laliberté, E., Turner, B.L., Costes, T., Pearse, S.J., Wyrwoll, K.H., Zemunik, G. & Lambers, H. (2012); [3] Laliberté, E., Turner, B.L., Costes, T., Pearse, S.J., Wyrwoll, K.-H., Zemunik, G. and Lambers, H. (2012), Experimental assessment of nutrient limitation along a 2-million-year dune chronosequence in the south-western Australia biodiversity hotspot. Journal of Ecology, 100: 631-642. https://doi.org/10.1111/j.1365-2745.2012.01962.; [4] Laliberté E, Zemunik G, Turner BL. Environmental filtering explains variation in plant diversity along resource gradients. Science. 2014 Sep 26;345(6204):1602-5. doi: 10.1126/science.1256330.

This dataset contains the effect of stress and herbivory on the establishment of alternate provenances of a foundation tree species. This data relates to plant fitness and could be used for more broader studies in this area. We established a common garden experiment within a 238 ha restoration site owned and managed by the South Australian Water Corporation (SA Water), near the township of Clarendon (-35.0882°S, 138.6236°E). We grew ca.1500 seedlings sourced from one local and two non-local provenances of <i>Eucalyptus leucoxylon</i> to test whether local provenancing was appropriate. The three provenances spanned an aridity gradient, with the local provenance sourced from the most mesic area and the distant provenance sourced from the most arid. We explored the effect of provenance on four fitness proxies after 15 months, including survival, above-ground height, susceptibility to insect herbivory, and pathogen related stress.