Ecosystem Stability: Components and Models

Ecosystems are Complex Adaptive Systems Ecosystems are Complex Adaptive Systems *bottom-up self-organization leads to stability A system Many parts Interactions Bottom-up Self-organization Emergence Change Feedbacks Adaptive Memory Open to outside Fuzzy boundaries Non-equilibrium Non-linear Thresholds Tipping points Surprises Stability

Ecosystem Stability The vast majority of natural ecosystems experience regular environmental change, or disturbances. Most ecologists describe ecosystem stability as the ability of an ecosystem to maintain its structure and function over long periods of time and despite disturbances.

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)

Resistance and Resilience There are two main components to ecosystem stability: resistance and resilience. An ecosystem displays resistance if keeps its structure and continues normal functions even when environmental conditions change. An ecosystem displays resilience if, following a disturbance, it eventually regains its normal structure and function.

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 Garry Oak: 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

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.

How does environmental change affect ecosystem stability? 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.

Negative: stabilizes ecsosytems Positive: destabilizes ecosystems Feedbacks Negative: stabilizes ecsosytems Positive: destabilizes ecosystems Ehrenfeld et al. (2005)

Loss of biodiversity can reduce stability 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.

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

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

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 of recovery (succession) after disturbance Complex system cycle r=growth (pioneer; stand initiation) K=carrying capacity (competition, niche specialization) (seral; stem exclusion) Ω=release, new opportunities (young climax; stand re-initiation) α=re-organization and recovery (late climax; old-growth) Gunderson & Holling 2002

Complex system cycle and threshold changes K α Ω

Panarchy: all-encompassing nested system

Panarchy in natural ecosystems Time Temporal scale Spatial scale

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 system cycles and panarchy are stabilizing characteristics Positive feedbacks and crossing tipping points can lead to loss of stability