Analytical Framework for Forest Gap Gradient Effects on Tropical Species Abundance
Published:
Developed the analytical framework using generalised linear models to assess abundance changes of tropical species across forest gap gradients.
Projects
Below are selected case studies (academic + applied) with a data-science focus.
Integrating Microclimate, Physiology, Biogeochemistry, and Population Models to Link Climate Change to Demographic Outcomes
Published:
Developed and implemented a holistic Bayesian framework integrating microclimate, mechanistic physiology, biogeochemical processes, and population dynamics to identify causal pathways from climate change to survival and recruitment.
Modelling Biogeochemical Pathway Cascades using Bayesian Hierarchical Models
Published:
Revealed ecosystem cascades and biogeochemical pathways in tropical systems using Bayesian hierarchical modelling to quantify direct and indirect effects in complex ecological networks.
Web-Based Tool for Deck Optimisation in Magic: The Gathering
Published:
Developed an interactive JavaScript tool using hypergeometric probability to optimise resource distribution in competitive deck building.
Detecting Climate Impacts on Rainforest Birds Using Bayesian Spatiotemporal Modelling
Published:
Applied hierarchical Bayesian models with satellite-derived predictors to identify climate-driven population changes in rainforest birds across space and time.
Forecasting Population Viability with Bayesian Hierarchical Models
Published:
Developed Bayesian hierarchical models incorporating detection probability to forecast population viability and support elevated conservation status for imperilled species.
Dynamic Community Re-shuffling Under Elevational Climate Shifts
Published:
Developed a high-throughput spatial forecasting workflow of community turnover under climate change, optimising computational performance for multi-species forecasting across elevational gradients.
Assessing Bird Population Trends to Inform Conservation Priorities
Published:
Used time-series GLMs and interactive visualisation (Shiny app) to nominate 14 bird species for elevated protection under national and international priority lists.
Predicting Species Abundance from Environmental Suitability
Published:
Applied ensemble machine learning to convert presence-only niche models into abundance predictions, combining big-data wrangling, advanced analytics, and multi-algorithm ensembles.