Biodiversity finance
Biodiversity continues to decline and the financing gap over the next ten years is estimated to be significant. Philanthropy and taxpayer funds will be insufficient in addressing the financing gap required to mitigate biodiversity loss. I aim to contribute to addressing this challenge through my work by developing insights about the role of private financing in bridging this financial gap.
I am a member of the cross-faculty working group at the Melbourne Biodiversity Institute, and Chief Investigator at the Centre for Nature-Positive Climate Transitions.
Working papers
with Robert Turnbull, Damien J. Mannion, Jessie Wells, Kabir Manandhar Shrestha, Rebecca Runting
Revise and resubmit in the Journal of Remote Sensing
Accurate land cover change prediction is vital for informed land management, and deep learning offers a flexible solution capable of capturing complex ecological patterns. This paper presents Themeda, a modeling framework using artificial neural networks that predict land cover category probability distributions based on historical data. It integrates ConvLSTM and a novel Temporal U-Net architecture, extending the U-Net with LSTM layers for multi-scale temporal processing, enabling fine-grained local and broader spatial pattern capture. Leveraging 33 years of historical data from the world's largest intact savanna, Themeda incorporates diverse spatio-temporal features like rainfall, temperature, elevation, soil types, land use, and fire scars. Themeda overcomes limitations of current spatio-temporal models by processing temporal data at multiple spatial scales, capturing local and regional ecological changes effectively. It achieves a 93.4% pixel-wise validation accuracy on FAO Level 3 classes and a KL divergence of 1.65e-03 for aggregated land cover predictions in 4000 m x 4000 m areas, surpassing baseline persistence models. The model maintains high performance on unseen test years, demonstrating robust generalizability. The probabilistic outputs and multi-scale temporal processing have significant implications for enhancing cellular automata and land use planning models and could be adapted for ecological forecasting in other regions.
Industry reports
Review of nature-related financial disclosures, materiality assessment process and outcomes (for a commercial bank), with Billy Geary, Sam Hickman, Rachel Morgain, Dale Wright, Hendri Wijaya, Brendan Wintle
Evaluating Biodiversity Impact Assessment Tools for Financial Institutions: A Comprehensive Review (for a global investment manager), with Matthew Cantele, Lakshmi Palaparambil Dinesh, Billy Geary, Sam Hickman, Brendan Wintle