Data

GAL Ecological expert elicitation and receptor impact models v01

data.gov.au
Bioregional Assessment Program (Owned by)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=http://data.gov.au/data/dataset/d6a86c8f-78e5-4931-a403-7f31e3bd0c12&rft.title=GAL Ecological expert elicitation and receptor impact models v01&rft.identifier=60772948-7354-453c-bffa-37b3f2063083&rft.publisher=data.gov.au&rft.description=## **Abstract** \n\nThe dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.\n\n\n\nReceptor impact models (RIMs) use inputs from surface water and groundwater models. For a given node, there is a value for each combination of hydrological response variable, future, and replicate or run number. RIMs are developed for specific landscape classes. The hydrological response variables that a RIM within a landscape class requires are organised by the R script RIM_Prediction_CreateArray.R into an array. The formatted data is available as an R data file format called RDS and can be read directly into R. The R script IMIA_XXX_RIM_predictions.R applies the receptor model functions (RDS object as part of Data set 1: Ecological expert elicitation and receptor impact models for the XXX subregion) to the HRV array for each landscape class (or landscape group) to make predictions of receptor impact varibles (RIVs). Predictions of a receptor impact from a RIM for a landscape class are summarised at relevant AUIDs by the 5th through to the 95th percentiles (in 5% increments) for baseline and CRDP futures. These are available in the XXX_RIV_quantiles_IMIA.csv data set. RIV predictions are further summarised and compared as boxplots (using the R script boxplotsbyfutureperiod.R) and as (aggregated) spatial risk maps using GIS.\n\n## **Dataset History** \n\nReceptor impact models (RIMs) are developed for specific landscape classes. The hydrological response variables that a RIM within a landscape class requires are organised by the R script RIM_Prediction_CreateArray.R into an array. The formatted data is available as an R data file format called RDS and can be read directly into R. \n\nThe R script IMIA_XXX_RIM_predictions.R applies the receptor model functions (RDS object as part of Data set 1: Ecological expert elicitation and receptor impact models for the XXX subregion) to the HRV array for each landscape class (or landscape group) to make predictions of receptor impact varibles (RIVs). Predictions of a receptor impact from a RIM for a landscape class are summarised at relevant AUIDs by the 5th through to the 95th percentiles (in 5% increments) for baseline and CRDP futures. These are available in the XXX_RIV_quantiles_IMIA.csv data set. RIV predictions are further summarised and compared as boxplots (using the R script boxplotsbyfutureperiod.R) and as (aggregated) spatial risk maps using GIS.\n\n## **Dataset Citation** \n\nBioregional Assessment Programme (2018) GAL Ecological expert elicitation and receptor impact models v01. Bioregional Assessment Derived Dataset. Viewed 07 December 2018, http://data.bioregionalassessments.gov.au/dataset/60772948-7354-453c-bffa-37b3f2063083.\n\n## **Dataset Ancestors** \n\n* **Derived From** [Queensland wetland data version 3 - wetland areas.](https://data.gov.au/data/dataset/2a187a00-b01e-4097-9ca4-c9683e7f4786)\n\n* **Derived From** [Geofabric Surface Cartography - V2.1](https://data.gov.au/data/dataset/5342c4ba-f094-4ac5-a65d-071ff5c642bc)\n\n* **Derived From** [Landscape classification of the Galilee preliminary assessment extent](https://data.gov.au/data/dataset/53c534ba-bf4a-4d2a-a220-e74d72e27969)\n\n* **Derived From** [Geofabric Surface Cartography - V2.1.1](https://data.gov.au/data/dataset/ce5b77bf-5a02-4cf8-9cf2-be4a2cee2677)\n\n* **Derived From** [GAL Landscape Class Reclassification for impact and risk analysis 20170601](https://data.gov.au/data/dataset/316ff486-3f8a-4b3c-8b3f-81c5e529b012)\n\n* **Derived From** [GEODATA TOPO 250K Series 3, File Geodatabase format (.gdb)](https://data.gov.au/data/dataset/96ebf889-f726-4967-9964-714fb57d679b)\n\n* **Derived From** [Queensland groundwater dependent ecosystems](https://data.gov.au/data/dataset/10940dfa-d7ef-44fb-8ac2-15d75068fff8)\n\n* **Derived From** [GEODATA TOPO 250K Series 3](https://data.gov.au/data/dataset/a0650f18-518a-4b99-a553-44f82f28bb5f)\n\n* **Derived From** [Multi-resolution Valley Bottom Flatness MrVBF at three second resolution CSIRO 20000211](https://data.gov.au/data/dataset/7dfc93bb-62f3-40a1-8d39-0c0f27a83cb3)\n\n* **Derived From** [Landscape classification of the Galilee preliminary assessment extent](https://data.gov.au/data/dataset/80e7b80a-23e4-4aa1-a56c-27febe34d7db)\n\n* **Derived From** [Biodiversity status of pre-clearing and remnant regional ecosystems - South East Qld](https://data.gov.au/data/dataset/9b7bcebf-8b7f-4fb4-bc91-d39f1bd960cb)\n\n&rft.creator=Bioregional Assessment Program&rft.date=2023&rft.coverage=POLYGON ((0 0, 0 0, 0 0, 0 0))&rft_rights=Restricted access. This dataset is not available for public distribution.&rft_subject=Galilee subregion&rft_subject=environment&rft.type=dataset&rft.language=English Access the data

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Brief description

## **Abstract**

The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.



Receptor impact models (RIMs) use inputs from surface water and groundwater models. For a given node, there is a value for each combination of hydrological response variable, future, and replicate or run number. RIMs are developed for specific landscape classes. The hydrological response variables that a RIM within a landscape class requires are organised by the R script RIM_Prediction_CreateArray.R into an array. The formatted data is available as an R data file format called RDS and can be read directly into R. The R script IMIA_XXX_RIM_predictions.R applies the receptor model functions (RDS object as part of Data set 1: Ecological expert elicitation and receptor impact models for the XXX subregion) to the HRV array for each landscape class (or landscape group) to make predictions of receptor impact varibles (RIVs). Predictions of a receptor impact from a RIM for a landscape class are summarised at relevant AUIDs by the 5th through to the 95th percentiles (in 5% increments) for baseline and CRDP futures. These are available in the XXX_RIV_quantiles_IMIA.csv data set. RIV predictions are further summarised and compared as boxplots (using the R script boxplotsbyfutureperiod.R) and as (aggregated) spatial risk maps using GIS.

## **Dataset History**

Receptor impact models (RIMs) are developed for specific landscape classes. The hydrological response variables that a RIM within a landscape class requires are organised by the R script RIM_Prediction_CreateArray.R into an array. The formatted data is available as an R data file format called RDS and can be read directly into R.

The R script IMIA_XXX_RIM_predictions.R applies the receptor model functions (RDS object as part of Data set 1: Ecological expert elicitation and receptor impact models for the XXX subregion) to the HRV array for each landscape class (or landscape group) to make predictions of receptor impact varibles (RIVs). Predictions of a receptor impact from a RIM for a landscape class are summarised at relevant AUIDs by the 5th through to the 95th percentiles (in 5% increments) for baseline and CRDP futures. These are available in the XXX_RIV_quantiles_IMIA.csv data set. RIV predictions are further summarised and compared as boxplots (using the R script boxplotsbyfutureperiod.R) and as (aggregated) spatial risk maps using GIS.

## **Dataset Citation**

Bioregional Assessment Programme (2018) GAL Ecological expert elicitation and receptor impact models v01. Bioregional Assessment Derived Dataset. Viewed 07 December 2018, http://data.bioregionalassessments.gov.au/dataset/60772948-7354-453c-bffa-37b3f2063083.

## **Dataset Ancestors**

* **Derived From** [Queensland wetland data version 3 - wetland areas.](https://data.gov.au/data/dataset/2a187a00-b01e-4097-9ca4-c9683e7f4786)

* **Derived From** [Geofabric Surface Cartography - V2.1](https://data.gov.au/data/dataset/5342c4ba-f094-4ac5-a65d-071ff5c642bc)

* **Derived From** [Landscape classification of the Galilee preliminary assessment extent](https://data.gov.au/data/dataset/53c534ba-bf4a-4d2a-a220-e74d72e27969)

* **Derived From** [Geofabric Surface Cartography - V2.1.1](https://data.gov.au/data/dataset/ce5b77bf-5a02-4cf8-9cf2-be4a2cee2677)

* **Derived From** [GAL Landscape Class Reclassification for impact and risk analysis 20170601](https://data.gov.au/data/dataset/316ff486-3f8a-4b3c-8b3f-81c5e529b012)

* **Derived From** [GEODATA TOPO 250K Series 3, File Geodatabase format (.gdb)](https://data.gov.au/data/dataset/96ebf889-f726-4967-9964-714fb57d679b)

* **Derived From** [Queensland groundwater dependent ecosystems](https://data.gov.au/data/dataset/10940dfa-d7ef-44fb-8ac2-15d75068fff8)

* **Derived From** [GEODATA TOPO 250K Series 3](https://data.gov.au/data/dataset/a0650f18-518a-4b99-a553-44f82f28bb5f)

* **Derived From** [Multi-resolution Valley Bottom Flatness MrVBF at three second resolution CSIRO 20000211](https://data.gov.au/data/dataset/7dfc93bb-62f3-40a1-8d39-0c0f27a83cb3)

* **Derived From** [Landscape classification of the Galilee preliminary assessment extent](https://data.gov.au/data/dataset/80e7b80a-23e4-4aa1-a56c-27febe34d7db)

* **Derived From** [Biodiversity status of pre-clearing and remnant regional ecosystems - South East Qld](https://data.gov.au/data/dataset/9b7bcebf-8b7f-4fb4-bc91-d39f1bd960cb)

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Spatial Coverage And Location

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