Maximising plant and animal population persistence in an increasingly stochastic world

The vast richness of plant and animal species worldwide represents also a tremendous diversity of life histories (i.e. key moments along a species’ life cycle, such as age at maturity or death).

These extant life histories have been optimised through evolutionary time by environmental filtering operating on genetic differences among individuals and species.

However, anthropogenic environmental changes (e.g. climate change, habitat degradation) may push plant and animal species out of their evolved life-history opima.

Thus, there is an urgent need to understand and predict how environmental stochasticity (increased amplitude and fluctuation) may affect life histories and their cascading effects on global biodiversity.

This is the overarching goal of MaxPersist, where I will develop new theoretical advances to thoroughly understand how life-history strategies may respond to climatic variation, and use these advancements, alongside high-resolution, global data, to forecast how natural populations of hundreds of animal and plant species may persist in the face of increasing environmental perturbations worldwide.

I have developed a network of world-leading scientists to contribute to the development of theoretic advances including assimilation of density-dependence, small noise assumptions, and adaptation of second-derivative of population growth rate to stochastic environments.

MaxPersist will offer a comprehensive and innovative tool kit to enable realistic and effective conservation plans, useful especially for endangered species (contributing to UN Sustainable Development Goal #15), the 5th Target of the EU Biodiversity Strategy, to sustainable exploitation of harvested species and to the IUCN Red list.

The deliverables of MaxPersist will be of great interest and use to the scientific community and to the public, raising the awareness of the consequences that climate change may have on natural populations and generating knowledge to protect biodiversity.