2 Climate variability - change in average, variation, and/or extreme values

New Reality Seastedt et al. 2008, Frontiers in Ecology, Novel ecosystems will be increasingly common

Time Ecosystem characteristics C Management objective A Complexity management objective B Silvicultural interventions Modified from Puettmann et al. Management objective “Complexity” management approach

This can be achieved by viewing and managing ecosystems as complex adaptive systems

The most important ideas about ecosystems come from Complex Systems Science: Much of the order/pattern we see in the world comes, not from top down control, but from local-level (bottom-up) interactions among system components. (self-organization) Examples: Examples: grass roots social movements, viral YouTube, ant colonies, microbial networks

 A system with many parts  The parts interact (inter- dependent, feedbacks)  Emergence or synergy  The whole is greater than the sum of the parts (interactions give rise to emergent properties).  Bottom-up self-organization  Adaptive, Evolving  System memory  Fuzzy, open boundaries

Feedbacks are the key to self-organization of terrestrial ecosystems Ehrenfeld et al. (2005)

 Unpredictable: because interactions non-linear  Contagion: easy spread due to interconnection  Modularity: some parts more intra-connected than inter-connected (e.g., above- and belowground foodwebs)  Redundancy  Resilient

Forest ecosystems: cross- scale interactions and emergence of self- organization Forest structure is emergent property

Neural networks underpin the brain as a complex adaptive system  Feedback loops, cross scales  Non-linear, sometimes chaotic  Indeterminate, unpredictable  Self-organization  Emergent properties  System memory  Non-equilibrium, open to outside  Fuzzy boundaries  Adaptive “use it or lose it” “mindful practice” “neurons that wire together, fire together”

EQUILIBRIUM PERSPECTIVE  The future is the basically the same as the past  Most systems return to a stable state  Time is reversible COMPLEXITY PERSPECTIVE  The future is never the same as the past  Systems continue to evolve  Time is like an arrow -not reversible

Climate essentially stable at time scales relevant to ecosystem management After disturbance, ecosystems follow a predictable trajectory back to a climax state Zonal soils and zonal plant communities best reflect the regional climate Climate variable over short and long time scales relevant to ecosystem management Disturbance and recovery are ongoing processes; Both ecosystems and soils change over time Equilibrium vs. Non-Equilibrium Perspective of System Dynamics Equilibrium PerspectiveComplexity Perspective

Essentially one pathway to stability Disturbance seen as an aberration Time succession disturbance