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.
Covariates, Fauna & Flora survey records used to create the models are included.
More detailed information regarding each model, its processes and outputs are included in the dataset.
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:
https://portal.spatial.nsw.gov.au/portal/home/item.html?id=78e6ae3d34aa45d2b8118fd0308d6459
Credit
We at TERN acknowledge the Traditional Owners and Custodians throughout Australia, New Zealand and all nations. We honour their profound connections to land, water, biodiversity and culture and pay our respects to their Elders past, present and emerging.
This project was created as part of the NSW Government, Natural Resource Commission, Forest Monitoring and Improvement Program.
Purpose
The dataset was created as part fulfillment for the NRC project ‘NSW Forest Monitoring and Improvement Program'
Data Processing
Model outputs are provided in a Raster, GeoTiff format to be used in Geographic Information Systems. SOM analysis is based on the RPresence analysis software developed by Darryl Makenzie (https://www.mbr-pwrc.usgs.gov/software/presence.html and references therein). Maxent analysis is based on software developed by Steven Phillips (https://biodiversityinformatics.amnh.org/open_source/maxent/ and references therein).
Supplemental Information
SOM: Pixel values represent a probability of species occupation in an area between 0 and 1. Maxent: Pixel values represent a probability of species habitat suitability in an area between 0 and 1.
Lineage
Maxent: Species occurrence data from systematic fauna surveys conducted between 1991 and 1998 was sourced from NSW DPIE (e.g. NPWS 1994 Fauna of north-east NSW forests, NSW National Parks and Wildlife Service), as well as unpublished data held by the NSW DPI Forest Science unit. Additional occurrence data over the same period and spatial extent was extracted from the Atlas of Living Australia. Covariate data was sourced in the main from the State Vegetation Type Map (SVTM) Modelling Grid Collection (https://datasets.seed.nsw.gov.au/dataset/svtm-modelling-grid-collection) with additional data as described in ‘NSW Forest Monitoring and Improvement Program: Final Report. Project 2: Baselines, drivers and trends for species occupancy and distribution.’ Model outputs (statistical analyses and predictive surfaces) were generated using the Maxent kernel from the R Project https://cran.r-project.org/
NARCliM Projections: Species occurrence data was sourced from Bionet, based on systematic NPWS surveys conducted ~1989-2000 [cf. NPWS (1994). Fauna of north-east NSW forests. (NSW National Parks and Wildlife Service)]. Additional occurrence data from 1991-1998 and equivalent spatial extent was extracted from the Atlas of Living Australia. NARCliM variables (GCM MIROC3.1; RCM R1 provided by the Science, Economics and Insights Division of DPIE NSW) along with relevant topographic layers from the State Vegetation Type Map (SVTM) Modelling Grid Collection (https://datasets.seed.nsw.gov.au/dataset/svtm-modelling-grid-collection) as described in the NRC publication ‘NSW Forest Monitoring and Improvement Program: Final Report. Project 2: Baselines, drivers and trends for species occupancy and distribution. Model outputs (statistical analyses and predictive surfaces) were generated using the software developed by Steven Phillips (https://biodiversityinformatics.amnh.org/open_source/maxent/)
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