Supplementary Data: Biodiversity and Energy System Planning - Queensland 2025

Supplementary Data: Biodiversity and Energy System Planning - Queensland 2025<h2>Dataset Overview</h2><p dir="ltr">This dataset contains comprehensive spatial and analytical data supporting the research on balancing biodiversity conservation with renewable energy infrastructure development in Queensland, Australia. The materials include energy system modeling results, conservation priority analyses using Zonation software, species and ecological community data, and reproducible analysis scripts.</p><p dir="ltr"><b>Study Area</b>: Queensland, Australia<br><b>Temporal Scope</b>: 2030, 2040, 2050 projection years<br><b>Data Volume</b>: ~7.8 GB total<br><b>Coordinate System</b>: GDA2020 / MGA Zone 56 (EPSG:7856)</p><h2>Dataset Contents</h2><h3>Energy System Analysis Data</h3><ul><li><b>QLD_v202412_eplus_tx1.gdb.zip</b> (1.0 GB): Geodatabase containing renewable energy infrastructure scenarios under transmission development option 1. Includes solar photovoltaic, onshore wind, and offshore wind potential development areas under different biodiversity protection thresholds (0%, 10%, 30%, 50%, 70%, 90%).</li><li><b>QLD_v202412_eplus_tx2.gdb.zip</b> (2.7 GB): Geodatabase for transmission development option 2, containing the same renewable energy technologies and protection scenarios as tx1 but under alternative transmission infrastructure assumptions.</li><li><b>cost_increase_results.csv</b>: Economic analysis results showing percentage cost increases for residential and industrial energy consumers under different High Biodiversity Value Area (HBVA) exclusion scenarios.</li><li><b>eplus_Domestic_NPV_2025.xlsx</b>: Net Present Value calculations for domestic renewable energy projects across different protection thresholds and projection years (2030, 2040, 2050).</li></ul><h3>Conservation Priority Analysis</h3><ul><li><b>Zonation_output/250m_SNES_ECNES_red_zones_weighted_QLD/</b>: Complete Zonation conservation prioritization analysis results at 250m resolution, including:</li><li><ul><li><b>feature_curves.csv</b> (17.7 MB): Performance curves for 524+ conservation features showing coverage across priority ranks</li><li><b>feature_coverage_summary_with_CI.csv</b>: Summary statistics with confidence intervals for feature coverage at different protection thresholds</li><li><b>rankmap.tif</b> (47.5 MB): Spatial priority ranking map</li><li><b>MNES_2019_prioritisation_QLD.tif</b> (47.5 MB): Matters of National Environmental Significance prioritization layer</li><li>Configuration files, analysis logs, and metadata</li></ul></li></ul><h3>Biodiversity Data</h3><ul><li><b>Species_files_weights_table.xlsx</b>: Weighting schemes applied to individual species in conservation planning, including rationale for differential weighting based on threat status and endemism.</li><li><b>Table 8_The 524 species and their associated threat status.xls</b>: Comprehensive list of fauna species included in the analysis with IUCN Red List categories, national conservation status, and state-level classifications.</li><li><b>Table 9_The 22 ecological communities and their threat status.xlsx</b>: Threatened ecological communities included in conservation planning with threat classifications and distribution information.</li></ul><h3>Spatial Constraints</h3><ul><li><b>Supplementary table_other spatial exclusions.xlsx</b>: Non-biodiversity spatial exclusion layers used in energy system modeling, including urban areas, protected areas, infrastructure corridors, and other development constraints.</li></ul><h3>Analysis Scripts</h3><p dir="ltr">Complete set of R scripts for reproducing all analyses:</p><ul><li><b>percent cost increase_line plot.R</b>: Creates visualizations of energy cost impacts under different conservation scenarios</li><li><b>Zonation curves.R</b>: Generates conservation performance curves and coverage statistics</li><li><b>NPV_bar_plot.R</b>: Produces economic analysis plots with Net Present Value breakdowns</li><li><b>domestic_export_map_iterations.R</b>: Creates spatial maps of renewable energy infrastructure for domestic and export scenarios</li></ul><h2>Technical Specifications</h2><h3>Data Formats</h3><ul><li><b>Spatial Data</b>: ESRI Geodatabase (.gdb), Shapefile (.shp), GeoTIFF (.tif)</li><li><b>Tabular Data</b>: CSV, Microsoft Excel (.xlsx, .xls)</li><li><b>Analysis Code</b>: R scripts (.R)</li></ul><h3>Software Requirements</h3><ul><li><b>R</b> (≥4.0.0) with packages: sf, dplyr, ggplot2, readr, readxl, tidyr, furrr, ozmaps, ggpattern</li><li><b>ESRI ArcGIS</b> or <b>QGIS</b> for geodatabase access and spatial analysis</li><li><b>Zonation</b> conservation planning software (for methodology understanding)</li></ul><h3>Hardware Recommendations</h3><ul><li><b>RAM</b>: 16GB minimum (32GB recommended for full spatial analysis)</li><li><b>Storage</b>: 15GB free space for data extraction and processing</li><li><b>CPU</b>: Multi-core processor recommended for parallel processing scripts</li></ul><h2>Methodology Summary</h2><h3>Energy System Modeling</h3><p dir="ltr">Energy infrastructure scenarios were developed using least-cost optimization modeling under different spatial constraints representing biodiversity protection levels. Six protection thresholds (0%, 10%, 30%, 50%, 70%, 90%) were applied to High Biodiversity Value Areas identified through systematic conservation planning.</p><h3>Conservation Planning</h3><p dir="ltr">Systematic conservation prioritization was conducted using Zonation software with 524 vertebrate species and 22 threatened ecological communities. Analysis incorporated species threat status, range size, and habitat specificity through differential weighting schemes.</p><h3>Economic Analysis</h3><p dir="ltr">Cost-benefit analysis quantified the economic implications of biodiversity protection on energy system development, including infrastructure costs, consumer price impacts, and Net Present Value calculations for different scenarios.</p><h2>Data Quality and Limitations</h2><h3>Spatial Resolution</h3><ul><li>Energy infrastructure analysis: 250m grid resolution</li><li>Conservation features: Variable resolution (10m-1km) depending on source data</li><li>Economic modeling: Aggregated to energy market regions</li></ul><h3>Temporal Scope</h3><ul><li>Biodiversity data: Current distributions (2019-2024)</li><li>Energy projections: 2030, 2040, 2050 scenarios</li><li>Economic analysis: 2025 Australian dollar values</li></ul><h3>Coverage Limitations</h3><ul><li>Study area limited to Queensland, Australia</li><li>Marine environments included for offshore wind but limited for biodiversity features</li><li>Some rare species distributions may be incomplete due to survey limitations</li></ul><h2>Usage Guidelines</h2><h3>Getting Started</h3><ol><li>Download and extract all ZIP files to a local directory</li><li>Install required R packages using provided scripts</li><li>Set working directory to the extracted data folder</li><li>Run analysis scripts in the following order:</li><li><ul><li>Cost analysis scripts first</li><li>Conservation analysis scripts</li><li>Spatial mapping scripts last (most computationally intensive)</li></ul></li></ol><h3>Reproducibility</h3><p dir="ltr">All analysis scripts use relative file paths and include comprehensive error handling. Scripts will automatically create output directories and provide progress feedback during execution.</p><h3>Citation Requirements</h3><p dir="ltr">When using this dataset, please cite:</p><ul><li>The associated research paper</li><li>Individual data sources as listed in acknowledgments</li><li>This Figshare dataset DOI</li></ul><h2>Support and Documentation</h2><p dir="ltr">Complete documentation including setup instructions, troubleshooting guides, and methodology details is provided in the README.md file.</p><p dir="ltr">For technical questions about data processing or analysis methods, contact the corresponding author.</p><h2>License and Usage Rights</h2><p dir="ltr">Users are free to download, use, and build upon this work with appropriate attribution.</p><p dir="ltr"><b>Keywords</b>: renewable energy, biodiversity conservation, spatial planning, Queensland, systematic conservation planning, energy economics, GIS analysis, Zonation, infrastructure development</p><p dir="ltr"><b>Subject Categories</b>: Environmental Sciences, Energy Systems, Conservation Biology, Spatial Analysis, Environmental Economics</p>