The Central Appalachian region, USA, contains several high elevation-endemic woodland salamanders (genus Plethodon), which are thought to be particularly vulnerable to climate change due to their restricted distributions and low vagility. In West Virginia, there is a strong management focus on protection and recovery of the federally threatened Cheat Mountain salamander (Plethodon nettingi; CMS). To support this focus, there is a need for improved understanding of CMS occurrence-habitat relationships and spatially explicit projections of fine-scale contemporary and potential future habitat quality to inform management actions. In addition, there is concern among resource managers that climate change may increase habitat quality at high elevations for CMS competitors, particularly the eastern red-backed salamander (Plethodon cinereus; RBS), potentially resulting in increased competition pressure for CMS. To address these knowledge gaps, we created ecological niche models for CMS and RBS using the Random Forest classification algorithm and used the estimated occurrence-habitat relationships to assess ecological niche overlap between the species and project fine-scale contemporary and potential future habitat availability and quality. We estimated that the ecological niches of CMS and RBS were 80.5% similar, and habitat projections indicated the species would exhibit opposite responses to climate change in our region. For CMS, we estimated that amount of high-quality habitat will be reduced by mid-century and potentially lost by end-of-century, but that moderate and low-quality habitat will persist. For RBS, we estimated that amount of high-quality habitat will increase through end-of-century, and that high elevations will become more suitable for the species, indicating that competition pressure for CMS is likely to increase. This study improves understanding of important habitat characteristics for CMS and RBS, and our spatially explicit projections can assist natural resource managers with habitat protection actions, species monitoring efforts, and climate change adaptation strategies.

<p>This database contains occurrence data for vertebrates across the Australian Wet Tropics. Species occurrence point data has been collected during field intensive surveys using a variety of sampling methods as well as from the literature and institutional databases. The records are divided into two tables: Misc_records and STD_records. The first contains records collated opportunistically, as well as records collected from literature. The latter is a collection of standardized surveys conducted by Steve E. Williams (JCU). </p> <p> All occurrences were vetted for positional and taxonomic accuracy, and for sensitivity at the state and national levels. Sensitive species records are withheld or have their location generalised following sensitive species rules for processing these records. </p>

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?

The data set contains count data of amphibians from surveys of grazing properties in the Central and Southern Tablelands of NSW, Australia. Amphibians were surveyed using pitfall and funnel trapping along transects. Twelve properties were surveyed for the data set. Each property was surveyed 5 times for five trap nights on each survey between 2014 and 2015. A total of 2378 amphibians were captured from 11 different species during the surveys. All species captured were from one of three families: Limnodynastidae (three species), Myobatrachidae (four species) and Hylidae (four species).

<p>The Biological Databases of South Australia (BDBSA) is South Australia's flora and fauna database that stores and manages specimen and observation records. This record is the fauna component that contains over 2.3 million measurements collected from over 200,000 sites, across 726 species since 1976. This dataset includes occurrence data and morphometric information for invertebrates, fish, mammals, birds, reptiles and amphibians. The resulting database provides a comprehensive record of biodiversity across sites visited during a diverse range of biodiversity projects undertaken in South Australia and provides a basis for future monitoring or other relevant work such as species modelling.</p> <p>Only validated BDBSA data is made publicly available and all records of sensitive taxa have been masked from the dataset. Data is accessible from the TERN EcoPlots portal, which provides the ability to extract subsets of fauna data across multiple data collections and bioregions for more than 27 variables including animal body size, body length, head length, number of individual animals, and number of individual plants. </p>