Brief description
Disappearing ecological environments for Mammals as a function of change in long term (30 year average) climates between the present (1990 centred) and projected future (2050 centred) under the MIROC5 model (RCP 8.5) based on Generalised Dissimilarity Modelling (GDM) of compositional turnover.This metric describes the extent to which the long term average environmental conditions for each 9s grid square in the present (1990 centred) will be present in a projected 2050 centred future. Using a Generalised Dissimilarity Model of compositional turnover (the effects of changing environment on changing species), each location is compared with the continent in the future. For each cell, the metric looks out to all other cells in the continent, and records the ecological similarity of the present state of the cell to the most similar cell in the future. A value of 1 indicates that the environment is not disappearing, and perfect analogue is found somewhere in Australia. A value of 0 indicates that the most similar environment to be found in the future is ecologically so different that we would expect no species in common. Intermediate values show how ecologically similar the most similar cell is. However, no weight is given to the proximity of the most similar cell. The environment may be similar, but the cells thousands of kilometres apart.
This metric was developed along with others for use in an assessment of the efficacy of the protected area system for biodiversity under climate change at continental and global scales, presented at the IUCN World Parks Congress 2014. It is described in the AdaptNRM Guide “Implications of Climate Change for Biodiversity: a community-level modelling approach”, available online at: www.adaptnrm.org.
Data are provided in two forms:
1. Zipped ESRI float grids: Binary float grids (*.flt) with associated ESRI header files (*.hdr) and projection files (*.prj). After extracting from the zip archive, these files can be imported into most GIS software packages, and can be used as other binary file formats by substituting the appropriate header file.
2. ArcGIS layer package (*.lpk): These packages contain can be unpacked by ArcGIS as a raster with associated legend.
Additionally a short methods summary is provided in the file 9sMethodsSummary.pdf for further information.Tom HA
Layers in this 9s series use a consistent naming convention:
BIOLOGICAL GROUP _ FROM BASE_ TO SCENARIO_ ANALYSIS
e.g. A_90_CAN85_S or R_90_MIR85_L
where BIOLOGICAL GROUP is A: Mammals, M: mammals, R: reptiles and V: vascular plants
Lineage: Disappearing ecological environments were calculated using the highly parallel bespoke CSIRO Muru software running on a LINUX high-performance-computing cluster, taking GDM model transformed environmental grids as inputs. The similarity of the most similar future cell to the present environment of each cell was calculated. More detail of the calculations and methods are given in the document “9sMethodsSummary.pdf” provided with the data download.
GDM Model:
Generalised dissimilarity model of compositional turnover in mammal species for continental Australia at 9 second resolution using ALA data extracted 26 February 2014 (GDM: MAM_r2)
Climate data. Models were built and projected using:
a) 9-second gridded climatology for continental Australia 1976-2005: Summary variables with elevation and radiative adjustment
b) 9-second gridded climatology for continental Australia 2036-2065 MIROC5 RCP 8.5 (CMIP5): Summary variables with elevation and radiative adjustment
Available: 2014-12-10
Data time period: 2014-11-30 to 2014-11-30
Subjects
1990 climates |
Biological Sciences |
Climate Change Impacts and Adaptation |
Community Ecology (Excl. Invasive Species Ecology) |
Conservation and Biodiversity |
Environmental Sciences |
Ecological Impacts of Climate Change and Ecological Adaptation |
Ecology |
Environmental Management |
Global Change Biology |
Mammals |
Other Biological Sciences |
adaptnrm |
biodiversity |
generalised dissimilarity model |
historical climates, 2050 future climates |
scaled environmental variables |
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