Understanding the constraints that govern the sustainability of the living environment

"For science, there are many possible worlds; but the interesting one is the world that exists and has already shown itself to be at work for a long time. Science attempts to confront the possible with the actual" 

François Jacob.

The living environment is organized into ecological systems in which populations interact with one another and with the physical and chemical environment. These interactions generate collective properties that cannot be understood from individual components alone. Ecological systems thereby sustain processes essential to life and human well-being, including biological production, soil formation, nutrient cycling, water purification, carbon sequestration, and biodiversity.

However, energetic limits, species interactions, resource availability, and other constraints determine which ecological states and functions are feasible and sustainable. Understanding how these constraints define what is possible, how disturbance alters those possibilities, and how interventions can restore or expand them is both a fundamental scientific challenge and a prerequisite for sustaining the living environment.

Our research asks which states and functions complex living systems can sustainably support, how interacting constraints shape those possibilities, how disturbance alters them, and which interventions can restore or expand the range of feasible outcomes.

We address these questions by combining systems thinking, synthesis, mathematical theory, and empirical analysis. Our work is grounded in structural stability (the capacity of a system to maintain a particular qualitative behavior despite changes in its underlying dynamics) and the geometry of ecological feasibility. From this foundation, we study how interacting constraints shape ecological organization, dynamics, and production, and how this knowledge can inform restoration and sustainable management. We draw on population dynamics, geometry, probability, statistical mechanics, information theory, metabolic scaling, matrix and network theory, causal inference, and empirical dynamic modeling.

Systems Ecology

We are also helping build a broader scientific community around the systems-level understanding of ecological phenomena through Systems Ecology, an independent diamond open-access journal.

[Visit Systems Ecology]