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    This dataset contains global dryland literature abstracts from over the last 75 years (8218 articles) to identify areas in arid ecology that are well studied and topics that are emerging.

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    The record contains information on the number of aphids and chemical footprints of two aphid species. The data was collected in field and laboratory trials, we first examined how plant microsites alter fitness by measuring the fecundity of each species. Next, we tested whether intra- and interspecific pre-inhabitation modify habitat selection in two aphid species. Then we conducted laboratory trials showed that <i>R. maidis</i> displaced <i>R. padi</i>. Through gas chromatography-mass spectrometry analysis and bioassays testing the effects of aphid density and footprint extracts, we found a density-dependent response, with <i>R. padi</i> avoiding locations previously inhabited by <i>R. maidis</i>. Chemical analysis of footprint crude extracts showed a highly abundant compound, 1-hexacosanol, and when presented as the synthetic form also elicited <i>R. padi</i> displacement.

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    The dataset includes three csv files: [1] effects of pre-inhabitation and viruses on the feeding behavior of <i>Rhopalosiphum padi</i> and <i>R. maidis</i> (min). [2] effects of pre-inhabitation and viruses on the fecundity of<i> R. padi</i> and <i>R. maidis</i> (total offspring in laboratory and field). [3] effect of pre-inhabitation and viruses on the host plant nutrient content (amino acids, total sterols, and simple sugars-mg/g). These data might be used by researchers studying positive interactions, effects of viruses on host plants and vectors, phytochemistry of the wheat plant, and feeding behavior of phloem-feeders.

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    This dataset consists of counts for multiple plant species obtained from the Ethabuka Station and Carlo Reserve in the Simpson Desert, Australia, from 2004-2013 by the Desert Ecology Research Group (DERG) in conjunction with LTERN. It also consists rainfall data obtained from 2004-2012. These datasets were used to perform a Dynamic Factor Analyses for the manuscript, "Life form explains consistent temporal trends across species: the application of dynamic factor analysis". For more information see: DERG; https://www.desertecology.edu.au.

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    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.

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    This dataset consists of counts of plants and seeds for the ephemeral desert herb <i>Trachymene glaucifolia</i> obtained from the Ethabuka and Carlo Reserves in the Simpson Desert, Australia, from 2004-2011 by the Desert Ecology Research Group (DERG) in conjunction with LTERN. It also consists of monthly rainfall data obtained from 1995-2012. Collectively, the dataset was used to construct Multivariate Auto-regressive State-Space (MARSS) models for the manuscript "Reducing common sources of uncertainty in time series population data using MARSS models". For more information see: DERG : https://www.desertecology.edu.au

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    The dataset contains distribution data for the Yellow Crazy Ant (<i>Anoplolepis gracilipes</i>) and scale insects (eg <i>Parasaissetia nigra</i>, ,i>Dysmicoccus finitimus</i>), collected during the Waypoint Survey component of the Pulu Keeling National Park Island-wide Survey (IWS). The aim of the Waypoint Survey is to monitor densities of the invasive Yellow Crazy Ant (<i>Anoplolepis gracilipes</i>) and to detect establishment of any new scale insect species. The other components of the IWS (Transit Survey and Ink Card and Nocturnal Survey) are recorded in separate submissions.

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    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).

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    The dataset contains biological data collected 2005, 2012 as part of the Tanami Regional Biodiversity Monitoring (Tanami RBM) program. The Tanami RBM program uses 89 sites across the Tanami region, central-west Northern Territory. At these sites, flora and fauna are surveyed during the late-dry (usually November-December) or late-wet (usually February-March) seasons. Each site comprises a 200 m x 300 m survey plot from which the data are recorded using various survey methods: site descriptions, vegetation transects, bird surveys, small vertebrate trapping, and tracking surveys. This dataset contains the data from eight surveys undertaken between 2005 and 2012: six in the late-dry and two in the late-wet seasons. The precision of site locations has been reduced to 0.1 decimal degree, which is approximately 10 km at the study region. This denaturing is because some sites contain threatened and/or sensitive species that might be at risk from collection or disturbance. The dataset contains species information from vegetation surveys and fauna species captures and observations. The data can be used to: [1] Review the outcomes of the survey methodologies [2] Presence data of the species recorded [3] Impacts of mining on the region's flora and fauna e.g. what is the spatial and temporal impact of mining activities on biota? [4] Conservation and biodiversity e.g. what are the spatial and temporal trends in the occurrence of key/threatened species? How do land units/systems change over time?

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    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.