Tag - Mathematical ecology

Two key questions in biodiversity conservation relate to how we manage land/sea-scapes for wildlife and at what point in time we can expect to observe the consequences of our actions. Mathematically, these questions relate to (multiple) steady states and transient dynamics. I will consider two theoretical and inferential examples under each of these questions. I will first examine how the use of suburban and agroforestry ecosystems can be optimised for biodiversity gains. I will then explore frameworks for the analysis of delayed impacts in large-scale bird community data and very fine scale grazer rewilding experiments. The convergence of ideas from dynamical systems and modern statistical inference is a very exciting development in quantitative ecology. Thorny rewilding applications are one of the top areas where such theoretical advances can gain real traction and produce tangible impact.

Rewilding aims to create ecosystems and landscapes whose dynamics are driven by natural processes. This idea has been defined verbally, but its theoretical aspects remain at the early stages of development. I will discuss aspects of rewilding that could be explored by theorists, also drawing on the related topic of ecological restoration. 1) Complex systems. Rewilding has been described as an attempt to recreate complex systems, whose key features are complex trophic structures, stochastic disturbances and heightened dispersal. 2) Resilience and critical thresholds. Concepts from complex systems science that are linked to non-linearity, such as regime shifts, ecological resilience and ecological feedbacks, could be employed to help explain variation in rewilding outcomes. 3) Dispersal. Rewilding is focused on ‘natural colonization’, meaning that outcomes depend critically on dispersal abilities and the permeability of landscapes. Ultimately, development of theory on these and related concepts may help us understand the various trajectories that rewilding may take.

A key component of most rewilding projects is the translocation of plant and animal species to restore ecosystem function, however translocations are a complex process both biologically and socially. Here I will explore the reintroduction process and suggest the areas where mathematical and statistical methods could aid decision making and the understanding of complex biological systems.

There are trade-offs in practice with rewilding particularly around food and nutrition security but also around other societal dimensions as globally represented by the UN Sustainable Development Goals (SDGs). We need solutions that are synergistic.

Building on previous collaborations, we propose transdisciplinary, methodological approaches with a focus on qualitative and quantitative scenario planning to develop both aspirational and plausible solutions based on science and society.

The first seminar included an overview of rewilding, highlighting some of the areas in which we expect that the mathematical sciences could have an impact. This was followed by a response/discussion led by mathematical scientists.  There were then opportunities for informal discussion as well.  The session closed with a wrap-up in which we captured the most promising lines to follow up at the next seminar.