Research Themes


Resurrection Island: safeguarding biodiversity around the former Aral Sea

The Aral Sea and adjacent Ustyurt plateau is one of the world’s starkest examples of human activities leading to landscape-scale environmental destruction, dramatic biodiversity loss, and economic collapse – with disastrous ramifications for human health and wellbeing. A final hold-out for nature in the region is so-called ‘Resurrection Island’ in the middle of the former Aral Sea; now a peninsula, it harbours unique, undisturbed biodiversity, but having been newly opened up it is currently threatened by looting and poaching.

We are working with partners across the region to develop an integrated approach towards the recovery of the social-ecological system around the former Aral Sea, using Resurrection Island as our flagship. Our work will involve a combination of primary research (field surveys and remote observation to track wildlife and ecological restoration trajectories, landscape-scale mapping of land use change and restoration opportunities, structured surveys to explore the preferences of actors in the social-ecological system) and capacity building, working with scientists, businesses, and public sector organisations.

Arriving at a field site on the bank of the Aral Sea, Uzbekistan (credit: J W Bull)

Accurate large-scale prediction of biodiversity impacts

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 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 seeking to explore this topic, combining: (i) newly collated global datasets on impact mitigation actions; (ii) analysis of remotely-sensed (satellite) data; (iii) machine learning algorithms designed to extract available online biodiversity data; and, (iv) direct ecological surveys in the field.

Natural gas exploration site, Central Asia (credit; J W Bull)

See also:

Benchmark for Nature | Machine learning for automated evaluation of the biodiversity risk associated with different corporations, as the basis for financial investment decisions.

SUPERB | Systemic solutions for upscaling of urgent ecosystem restoration for forest-related biodiversity and ecosystem services. Major forthcoming project (2022 – ) working with partners across Europe, developing the technical basis for delivering widespread forest restoration and then putting it into practice.

The Conservation Hierarchy | Development of a technical framework for mapping and monitoring progress towards nature conservation targets, for a range of actors, across multiple spatial scales.


Net outcomes

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)
From Bull et al. (2019) Nature Sustainability

System dynamics

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
From Bull & Milner-Gulland (2020) Journal of Applied Ecology

Spatial analyses

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
From Bull et al (2015) Land Use Policy

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’.

From Addison, Bull & Milner-Gulland (2019) Conservation Biology

Field ecology

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
  • Ground-truthing

Note: The copyright for all photos on this website belong to J. W. Bull unless otherwise stated