Robust Conservation for a Dynamic World (Renewal)

Climate change is driving species to shift their geographic ranges, while human land uses tend to make shifts more difficult. Making decisions about modifying land use today, with enormous uncertainty about climate change and socioeconomic change, is an unprecedented challenge. It’s clear that our current land-use trajectories globally are unsustainable, and that space is needed to allow biodiversity to recover, but nature is much more complicated than greenhouse gases. Despite decades of research on conservation planning, it is better suited to planning static, fortress-style protected areas than whole, multi-use landscapes. A dynamic world with a patchwork of habitats in different states of recovery requires a new kind of flexible planning toolbox.
Now is an exciting time for biodiversity and ecosystem data. In some areas and for some variables the data is phenomenal; elsewhere there are big holes. Unfortunately, the urgency of conservation and restoration decisions means we can’t afford to wait for the holes to be filled.
My research uses statistical techniques to make our planning conclusions more reliable, despite the holes. It exploits the sources of strong data, to predict something that can be generalised. My methods have high potential to be widely used inside and outside academia, because many have the same issues with their data.
For the next three years, I will complete three studies, which build on my recent theoretical and statistical results.
First, I will develop a calculator for overall average species’ abundance in each land-use type in each biome. This exploits high quality land-use maps and fills in gaps for missing species based on their rarity. It is based on a prototype biodiversity indicator which I have just published.
Second, I will use global citizen science data to estimate dispersal distances for invertebrates. This exploits high densities of citizen science records in a few landscapes, and fills in gaps for missing species based on their morphology. It builds on a new method I have developed for finding the signal of dispersal in population data.
Third, I will enhance my planning model Condatis to ensure habitat networks offer connectivity for all the species that need them under climate change. Condatis quantifies the potential speed of range shifts across a given habitat map. It has been used for numerous conservation and restoration questions in the last 10 years, but hardly ever for specific, named species. My proposed new methods will be adaptable to situations where we only roughly know the niche of each species. The key principle is to find out how species’ needs are intercorrelated, and exploit this so that the planning problem has fewer variables.
To ensure my methods reach the users who need them most, I will work with practitioners as partners, ensure my software is user-friendly, and link the methods to open-access data sources.
Personally, I love the complexity of nature, yet I believe that conservation planning is over-complicated. Over-complicated results risk getting ignored by decisionmakers, who are predominantly not ecologists. I envision a conservation toolbox that is credible but simple, enabling a higher impact across sectors. I hope it will help nature to recover in coming decades, because biodiversity will be more fairly represented and quantified alongside all the societal and economic drivers of land use.