Ecosystem Stability, Adaptive Cycles and Panarchy

Temporal, spatial and structural features of complex system Amand et al. (2010)

Tweets (social interactions) in Japan in response to the 2011 Tsunami have a scale-free pattern When an earthquake hits, it makes more than just seismic waves. Extreme events such as earthquakes, tsunamis, and terrorist attacks also produce waves of immediate online social interactions, in the form of Tweets, that offer insights into the event itself and to broader questions of how communities of people respond to disaster. In an article for Scientific Reports (an online open-access journal by the Nature Publishing Group), SFI Postdoctoral Fellow Christa Brelsford and co-author Xin Lu analyze interactions by communities of Twitter users preceding and following the 2011 earthquake and tsunami in Japan. The authors find that among Japanese-speaking Twitter users, the disaster created more new connections and more changes in online communities than it did globally and (not surprisingly) it produced world-wide increases in earthquake-related tweets. In addition to their findings, the authors describe a novel framework for investigating the dynamics of communities in social networks that can be used to study any kind of social change. “Although we would never wish living through a natural disaster on anyone, when disasters do occur, we can learn a lot about how social systems adapt and change during stressful periods by looking at how people's interaction patterns change," Brelsford says. "Communication on Twitter can be accessed from both before and after an unexpected event, providing an accurate and detailed record of how interaction patterns change and how that influences whole communities.” Brelsford has firsthand experience with the aftermath of an earthquake. She was in Haiti in January 2010 helping her brother with a literacy project, working in a building just three kilometers from the epicenter of the earthquake, near Léogâne. The roof collapsed and a falling stairwell crushed her right leg.  "My experiences in the earthquake really were the driving thought behind this research project," Brelsford says. "When in Haiti, I had what might have been the best possible purely observational position you could have after the earthquake: I was awake, conscious, and really in the thick of things, but couldn’t actually do anything, and that was totally obvious to everyone who saw me. So, I saw a lot about how people were acting, cooperating, and treating each other that I probably wouldn’t have seen as an outsider in less dire circumstances. What I saw was really impressive coordination of people and resources to get things done -- quickly. So, I thought it would be interesting to think about how coordination and cooperation changed in communities in the aftermath of an extreme event." Read the article in Scientific Reports (October 3, 2014)

Ecosystem Stability Concepts Ecosystem stability: as the ability of an ecosystem to maintain its structure and function over long periods of time and despite disturbances. Resistance: ecosystem keeps its structure and continues normal functions even when environmental conditions change. Resilience: ecosystem eventually regains its normal structure and function after a disturbance.

Ball-and-cup model of system stability Ball=Current state of system Cup = Current stability domain Stability, the speed at which the ball returns to homeostasis; correlated with productivity Resilience, the amount of energy that the system can absorb without leaving the cup for an alternative stability domain.

Tundra: low stability, low resilience ICH: high stability, high resilience CWH: high stability, low resilience IDF: low stability, high resilience

Managing ecosystems within the range of natural variability (RONV) RONV= resilience=range of possible locations of the ball within the cup Resilience: “the capacity of a system to absorb disturbance and reorganise while undergoing change so as to still retain essentially the same function, structure, identity, and feedbacks”. Management goal: make sure you stay in the cup and that it remains as wide and deep as possible

Ecosystem stability or response to disturbance depends on: Resistance: Ability of system to absorb small disturbances and prevent amplification Resilience: Ability of system to return to its original state Robustness: amount of disturbance system can absorb without flipping to alternative state Response: Magnitude of change Recovery: Extent of return to original state

Three types of change Non-reversible Tree cover % Precipitation dry wet % Forest Cover Dry Wet Dry Wet Dry Wet

Maintaining stability Species diversity is often the key to both ecosystem resistance and resilience. An ecosystem rich in biodiversity will likely be more stable than one whose biodiversity is low. Populations respond in ways that reflect the success or failure of members of the population to survive and reproduce. Species respond to environmental change in ways that enable them to maintain homeostasis. Communities respond to environmental change in ways that reflect the responses of the species and populations in the community. Changing environmental conditions can cause the decline of local biodiversity. If this happens, an ecosystem’s resistance and/or resilience may decline. The end result is that the ecosystem loses stability. Ecosystems that are less stable may not be able to respond to a normal environmental disturbance, which may damage ecosystem structure, ecosystem function, or both.

Alive then dead: shifting stability domains

Perry’s cup vs peak models of system stability Destabilization of ball depends on force (cup) versus type or foreignness (peak) of disturbance. Ecosystem has plenty of warning (cup) for threshold disturbances versus surprises (falls off peak) (tipping points) Ball movement in cup reversible once disturbance removed, but not once knocked off peak (domino effects common) Cup model suggests equilibrium, but ecosystems are always in disequilibrium

Adaptive cycle Potential: the number and kinds of future options available (e.g. high levels of biodiversity provide more future options than low levels) Connectedness: the degree to which a system can control its own destiny through internal controls, as distinct from being influenced by external variables Resilience: how vulnerable a system is to unexpected disturbances and surprises that can exceed or break that control. The adaptive cycle is the process that accounts for both the stability and change in complex systems. The cycle periodically generates variability and novelty, either internally such as through genetic mutations or adaptation, or by accumulating resources that change the internal dynamics of an ecosystem. These changes are the triggers for experimentation. In the reorganization stage various experiments are tested and resources are reorganized in new configurations, some of which enter a new exploitation stage to repeat the cycle.

Complex system undergoes change through ‘adaptive cycle’ Adaptive cycle of recovery (succession) after disturbance Complex system undergoes change through ‘adaptive cycle’ r K Ω α r=exploitation (disturbance, ruderale growth; stand initiation) K=conservation (carrying capacity, competition, niche specialization; stem exclusion) Ω=release (self-thinning or gap disturbance, new opportunity, understory re-initiation) α=re-organization (stratification of survivors, old-growth) Gunderson & Holling 2002

Four stages of adaptive cycle Metaphor Ecology Biological Psychological Economic 1 Exploitation Birth Development Growth 2 Conservation Maturity Sanity Consolidate 3 Release Death Madness Collapse 4 Reorganization Decay Healing Rebuild 1) Exploitation: rapid expansion, e.g., population grows. 2) Conservation: population reaches carrying capacity and stabilizes for a time. 3) Release: population declines due to a competitor, or changed conditions 4) Reorganization: certain members of the population are selected for their ability to survive despite the competitor or changed conditions that triggered the release.

Adaptive cycle: four stages K α Ω Ω r α K

Global to arctic Mann et al. Polar amplification Chapman and Walsh

not just southern margins Permafrost is thawing in many places, not just southern margins

Mineral deposit, Siberia Cryoturbated soil, thin peat, Alaska Frozen peat, Canada, Siberia Schuur et al. 2008

Melting permafrost Hudson Bay, Canada Science Daily, Sept 2, 2008

What is panarchy? “The term [panarchy] was coined as an antithesis to the word hierarchy (literally, sacred rules). Our view is that panarchy is a framework of nature's rules, hinted at by the name of the Greek god of nature, Pan.” Pan is the God of Nature, the Wild, Shepherds, Flocks, Goats, of Mountain Wilds Panarchy: A term adopted to better represent complex adaptive systems than ‘hierarchy’ Hierarchy describes “top-down rule” Panarchy refers to a specific form of governance or rule (archy) that would encompass (pan) all others Lance Gunderson and C. S. Holling, Panarchy: Understanding Transformations in Systems of Humans and Nature, Island Press, p.21, 2001.

Panarchy: all-encompassing nested system of adaptive cycles (Gunderson and Holling 2001).

Panarchy in natural ecosystems Temporal scale Spatial scale

These cycles connect with cycles ‘above’ and ‘below’ them in the hierarchy: “Revolt" – this occurs when fast, small events overwhelm large, slow ones, as when a small fire in a forest spreads to the crowns of trees, then to another patch, and eventually the entire forest “Remember" – this occurs when the potential accumulated and stored in the larger, slow levels influences the reorganization. For example, after a forest fire the processes and resources accumulated at a larger level slow the leakage of nutrients, and options for renewal draw from the seed bank, physical structures and surrounding species that form a biotic legacy. 7/10

There are ‘discontinuities’ in variables of interest Discontinuities determine dominant scales

Panarchy predicts discontinuities in adaptive cycles across scales

Summary Complex adaptive systems are inherently stable Stable systems change but are homeostatic, like a dancer Stables systems have resistance, where small disturbances are contained, and resilience, where the system returns to the same stability domain Complex systems change through adaptive cycles Adaptive cycles and panarchy are stabilizing characteristics Positive feedbacks and crossing tipping points can lead to loss of stability Climate change could cause instability Maintaining complexity will be crucial

Melting permafrost Hudson Bay, Canada Science Daily, Sept 2, 2008