Current and emerging research
One of the most important environmental challenges of our time is to better quantify, model and predict the impacts of economic development activities on nature. Only if this is done to a greater degree of accuracy will we be able to fully avoid and mitigate those impacts.
Global levels of biodiversity are declining at an alarming rate, with severe implications for human wellbeing. Economic development activities are amongst the leading mechanisms for global biodiversity loss. Yet there is currently no solid empirical basis for quantifiably predicting the typical impacts of specific development projects. This is a problem since decision-makers require an accurate assessment of the likely biodiversity impacts of any given development project when determining whether it should proceed, and a robust basis on which to predicate impact mitigation measures.
We are exploring this topic, combining: (i) new global datasets; (ii) analysis of remotely-sensed land cover data; (iii) machine learning algorithms designed to extract available online biodiversity data; and, (iv) direct field surveys using environmental DNA (‘eDNA’) methods.
Established research themes
Our ‘net outcomes’ research explores drivers of positive and negative biodiversity change, particularly in relation to quantifying empirical outcomes of net outcome policies, the choice of appropriate metrics, and the key sources of stochasticity. Strands include:
- Biodiversity measurement
- Quantification of biodiversity outcomes
- Demonstration of ecological equivalence
- Impact mitigation (including biodiversity offsets)
Systems thinking is crucial to our work, both in terms of tracking trends and in terms of mechanistic processes underlying the ways in which ecosystems change through time. Interests include:
- Counterfactual evaluation and reference frames
- Social-ecological systems dynamics
- Agent-based modelling
Conservation science is inextricably linked to spatial analysis. We use a combination of open source and proprietary GIS software to collate and analyse spatial datasets, and to implement structured conservation planning algorithms. For example:
- Remote sensing
- Systematic conservation planning
- Spatial statistics
Business and biodiversity
Successful achievement of current global conservation objectives necessitates direct and meaningful engagement with industry. We seek to contribute towards this not only through Wild Business (link) but also through research on the topic of ‘business and biodiversity’.
Nature conservation rests upon a good understanding of how nature works, which rests partly upon experience out in the field. We base our other research themes upon direct biodiversity observation and monitoring, including:
- Biodiversity monitoring
- Impact mapping
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