Estimating possible nonlinearities in the Human-Earth system with Earth system economics

The capacity for tipping points in the climate system was elucidated decades ago by numerical climate models, which showed that nonlinearities could arise from physical interactions between the ocean, sea ice, and atmospheric components, leading to rapid shifts between qualitatively different states. However, there has been comparatively little work on physical interactions with the human component of the Earth system through numerical modeling due, in part, to the rarity of inclusion of the human system directly in Earth system models. Earth System economics provides a new approach for doing so, by proposing a particular set of physical variables that can be used as a basis for simulating such changes. These variables include spatially resolved population demography, time allocation to activities, a spatially resolved technosphere, and spatial networks that capture transportation fluxes. New global compilations of time use and technosphere data are helping to enable this approach, by quantifying the dependencies of material fluxes on time use and context. This opens the possibility of simulating long-term dynamics through motivated changes to time allocation, with outcomes dependent on the evolution of the technosphere and other coupled features of the Earth system. Examples will be discussed regarding how this approach can provide holistic, physically-grounded ways to identify possible nonlinearities and tipping points, by explicitly resolving aspects of human activities and technosphere changes, constrained by the conservation of mass, energy, and time.