Methods - Agriculture and species of concern
Hotspot biodiversity maps made up of species of conservation concern (i.e. critically endangered/endangered, vulnerable, and near threatened as listed by Federal and Northern Territory governments) were used with maps showing land suitability for various crops in the Agriculture and species of concern case study. These hotspot maps were created for functional groups, or groups of species with similar conservation listings and indicate which areas may be in particular need of certain sets of conservation actions, how adequate current protected areas are for the conservation of certain groups, and/or how the distribution of threatened taxa corresponds to general distributions of biodiversity. Critical weight range (CWR) mammals is one such functional group and is used as an example here. Hotspot maps were created by summing all unique species within each pre-defined group predicted to be present in each grid cell (according to 250 m resolution vetted-occupied vetted-threshold model versions) from the National Environmental Science Program (NESP) 3.3 Project1. Those pixels with a high number of species of concern were termed hotspots. Outputs were clipped to the Darwin study area (Agriculture and species of concern case study) and intersected with land suitability maps for a range of crops from the Northern Australia Water Resource Assessment (NAWRA) data sets2.
A data layer was produced to mask or exclude those areas that were not currently available, or not likely to be available, for cropping in the study area (Agriculture and species of concern case study) This included land use categories such as urban areas, Defence land, protected areas5 and buffer zones around the significant vegetation communities called monsoon vine thickets6. This data layer, or mask, was derived from a range of input data sets but principally the Northern Territory Land Use Mapping for Biosecurity 20167 (2016 NT LUMP data).
The examples provided in this case study (Agriculture and species of concern case study) do not seek to replace formal government land use and conservation planning processes. They are designed to show how government can maximise its use of data assets from multiple sources, integrating them in ways which can provide policy insights. Formal land use planning and conservation planning is a complex process involving substantial stakeholder consultation and input, defined objectives for conservation and other purposes, articulation of biodiversity values and trade-offs and the need to consider not only where biodiversity can be currently found but where it may be found in the future due to landscape, ecological, climate and other changes.
Note that the NESP data used are a research output and may not align with the Australian Government distribution models which underpin the Environment and Protection Biosecurity Conservation Act 1999. Both development referrals and Commonwealth investment for biodiversity outcomes use the Australian Government species distribution models as a default, with further specific ecological reporting required from proponents for decision making.
Data sets used in this study (Agriculture and species of concern case study) included “Biodiversity Hotspot Maps of Terrestrial and Freshwater Taxa of Conservation Concern in Northern Australia” from NESP project 3.31 which show concentrations, or richness, of critically endangered/endangered, vulnerable, and near threatened species within 11 different taxonomic and functional groups. The resultant maps showed areas of high habitat suitability and those areas which were rich in taxa of conservation concern. These maps were then intersected with land suitability maps from the NAWRA for a number of different crops2. Here, dry-season soybean, grown with spray irrigation is presented as an example, where the land suitability was in classes 1, 2, or 3 on a five-point suitability scale. The two biodiversity examples were: all species of conservation concern from the 11 taxonomic and functional groups; and those mammal species in the CWR.