Elton - Costing GBF delivery in megadiverse Australia - SF1 - Cost Model

This cost model is Supplementary File 1 accompanying the peer-reviewed journal article by Elton et al., "Costing Global Biodiversity Framework delivery in megadiverse Australia" (under review). The model is the analytical tool used to generate the study's cost estimates for delivering the Kunming-Montreal Global Biodiversity Framework (GBF) in Australia. Detailed documentation of the model's methods, structure, and inputs is provided in the accompanying research methods report (Supplementary File 2). The cost model is a Microsoft Excel spreadsheet incorporating Monte Carlo uncertainty simulation via the RiskAMP add-in. It is structured around eight umbrella GBF targets — restoration (Target 2), protection (Target 3), threatened species recovery (Target 4), international assistance (Target 19), biodiversity-inclusive spatial planning (Target 1), invasive species management (Target 6), implementation and mainstreaming (Target 14), and information and knowledge (Target 21) — which together encompass the implementation costs of all 23 GBF targets. Each target is disaggregated into discrete cost items, each defined by unit costs and cost factors derived from peer-reviewed literature, grey literature, government data, and original spatial analysis. The model calculates national costs by year in real 2025 Australian dollar values over a 26-year period (2025–2050), applies a 3.5 per cent real discount rate to derive present values, converts these to equivalent annual costs, and disaggregates results by jurisdiction across all nine Australian governments. Monte Carlo simulation (n=10,000) using triangular probability distributions is used to generate a most-likely cost estimate and a 90 per cent uncertainty range. The model is fully automated and designed for use by researchers, practitioners, and policy makers. Users can modify unit costs, cost factors, discount rates, and delivery timeframes in designated input cells to generate alternative cost estimates. The RiskAMP add-in is required to re-run Monte Carlo simulations. The model was developed by Paul Elton, PhD Candidate, ANU Fenner School of Environment and Society (March 2026).
Type
collection
Title
Elton - Costing GBF delivery in megadiverse Australia - SF1 - Cost Model
Collection Type
Dataset
Access Privileges
Fenner School of Environment & Society
DOI - Digital Object Identifier
10.25911/4hn5-3p77
Metadata Language
English
Data Language
English
Brief Description
This cost model is Supplementary File 1 accompanying the peer-reviewed journal article by Elton et al., "Costing Global Biodiversity Framework delivery in megadiverse Australia" (under review). The model is the analytical tool used to generate the study's cost estimates for delivering the Kunming-Montreal Global Biodiversity Framework (GBF) in Australia.
Full Description
This cost model is Supplementary File 1 accompanying the peer-reviewed journal article by Elton et al., "Costing Global Biodiversity Framework delivery in megadiverse Australia" (under review). The model is the analytical tool used to generate the study's cost estimates for delivering the Kunming-Montreal Global Biodiversity Framework (GBF) in Australia. Detailed documentation of the model's methods, structure, and inputs is provided in the accompanying research methods report (Supplementary File 2). The cost model is a Microsoft Excel spreadsheet incorporating Monte Carlo uncertainty simulation via the RiskAMP add-in. It is structured around eight umbrella GBF targets — restoration (Target 2), protection (Target 3), threatened species recovery (Target 4), international assistance (Target 19), biodiversity-inclusive spatial planning (Target 1), invasive species management (Target 6), implementation and mainstreaming (Target 14), and information and knowledge (Target 21) — which together encompass the implementation costs of all 23 GBF targets. Each target is disaggregated into discrete cost items, each defined by unit costs and cost factors derived from peer-reviewed literature, grey literature, government data, and original spatial analysis. The model calculates national costs by year in real 2025 Australian dollar values over a 26-year period (2025–2050), applies a 3.5 per cent real discount rate to derive present values, converts these to equivalent annual costs, and disaggregates results by jurisdiction across all nine Australian governments. Monte Carlo simulation (n=10,000) using triangular probability distributions is used to generate a most-likely cost estimate and a 90 per cent uncertainty range. The model is fully automated and designed for use by researchers, practitioners, and policy makers. Users can modify unit costs, cost factors, discount rates, and delivery timeframes in designated input cells to generate alternative cost estimates. The RiskAMP add-in is required to re-run Monte Carlo simulations. The model was developed by Paul Elton, PhD Candidate, ANU Fenner School of Environment and Society (March 2026).
Contact Email
paul.elton@anu.edu.au
Contact Address
The Australian National University, Canberra
Contact Phone Number
0408213508
Principal Investigator
Paul Elton
Supervisors
Sarah Clement
Fields of Research
460105 - Applications in social sciences and education
Socio-Economic Objective
1902 - Environmental policy, legislation and standards
Keywords
environmental policy, conservation economics, 30x30 targets, ecosystem restoration, biodiversity conservation, reducing extinctions, species recovery
Type of Research Activity
Applied Research
Date Coverage
2025
2025
Geospatial Location
text
Australia
Date of data creation
2025
Year of data publication
2026
Creator(s) for Citation
Paul
Elton
Publisher for Citation
The Australian National University Data Commons
Access Rights
Open Access allowed
Access Rights Type
Open
Licence Type
CC-BY - Attribution
Retention Period
Indefinitely
Extent or Quantity
1
Data Size
35.8 MB
Data Management Plan
No

Download data files

Number of files: 1

Size: 35.8 MB

Identifier: anudc:6464

Status: Published
Published to:
  • Australian National University
  • Australian National Data Service
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