LOOC-B: biodiversity co-benefits calculator
Quantifying the biodiversity co-benefits of land management actions such as carbon farming- at any scale – anywhere in Australia
How can I access LOOC-B?
In May 2022, we released an early version of LOOC-B, offering stakeholders an opportunity to try the tool and provide feedback for further development and refinement. At this time, LOOC-B is not available for commercial use. We anticipate releasing LOOC-B for commercial use in the coming months.
Anyone may register for an account at looc-b.farm/. From here you can explore the tool’s functionality (best using a laptop or desktop computer). Individuals interested in the API functionality can use the API token within their account: documentation / programmatic examples at https://apidoc.looc-b.farm/.
For more information about the scientific approach, indicators, or inquire about a license, email the team at email@example.com.
What are the current challenges in biodiversity assessment and reporting?
Current approaches to reporting biodiversity primarily involve on-ground assessments. Although these provide valuable insights into biodiversity co-benefits, or consequences, they are costly and provide limited coverage over space and time.
They are insufficient to support identification of wider biodiversity patterns and don’t enable forecasting of potential future benefits.
In addition, they don’t allow co-benefits for biodiversity to be fully accounted for, realised and rewarded. In response to this challenge, we’ve created a national scale, paddock level, biodiversity co-benefit assessment and reporting tool.
Our digital solution, LOOC-B (’Look bee’), has an easy to use web interface and accessible data science component (an application programming interface, or API).
LOOC-B stands for Landscape Options and Opportunities Calculator for Biodiversity. It is intended as a rapid assessment solution, offering a consistent and standardised approach for monitoring how biodiversity has changed over time and anticipating how different management strategies influence the availability and quality of surrounding habitat.
An advanced machine learning approach generates the biodiversity information. Currently, LOOC-B offers:
- two modes of analysis: planning and monitoring of land management changes
- estimates for two biodiversity indicators: habitat condition and biodiversity persistence.
The analysis is most robust for those environments with higher natural tree cover. Additional indicators including habitat connectivity and threatened species are expected to complete the feature set. As new data becomes available, the reliability of estimates will improve.
The science underlying LOOC-B builds on the internationally recognised biodiversity assessment approaches we have already developed and applied, including indicators endorsed by the Convention on Biological Diversity.
Running parallel to the scientific approach was a human-centred design process where we’re actively engaging with state-based agencies, regional organisations and accreditation service providers to understand their needs for biodiversity related insights.
Through this combined data science and human-centred design approach, the tool is based on the best available data sources and advanced scientific modelling techniques.
The LOOC-B team
Dr Cara Stitzlein
- Cara’s background is in human factors, User Experience (UX) research techniques in industry, remote collaboration, critical care, first generation interfaces and workforce productivity. Cara leads Digiscape’s Biodiversity Co-benefits project.
Dr Karel Mokany
- Karel develops and applies modelling and assessment approaches to improve our understanding of biodiversity patterns and dynamics, helping to ensure well informed biodiversity policy, planning and management decisions.
Dr Chris Ware
- Chris applies expertise in ecological modelling, spatial data analysis, and high performance computing to research aimed at improving our understanding, of and capacity to manage, biodiversity.