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Estimating Resilience, Thresholds and Regime Change Jan Sendzimir International Institute of Applied Systems Analysis Laxenburg, Austria

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Presentation on theme: "Estimating Resilience, Thresholds and Regime Change Jan Sendzimir International Institute of Applied Systems Analysis Laxenburg, Austria"— Presentation transcript:

1 Estimating Resilience, Thresholds and Regime Change Jan Sendzimir International Institute of Applied Systems Analysis Laxenburg, Austria sendzim@iiasa.ac.at

2 2  Review Resilience  Regime Shifts  Surrogates of Resilience –Methods to find surrogates –Examples of application  Summary Outline

3 3 Ecological Succession South-eastern North America (After E.P. Odum 1971 Fundamentals of Ecology) Premise: system tends toward stable equilibrium Vegetation characteristic of different successional stages

4 4 Response of charophyte vegetation in the shallow Lake Veluwe to increase and subsequent decrease of the phosphorus concentration. Red dots represent years of the forward switch in the late 1960s and early 1970s. Black dots show the effect of gradual reduction of the nutrient loading leading eventually to the backward switch in the 1990s. Percent Of Lake Covered By Macro- Phytes Hysteresis 1 2 3 4 26 5, 6…25 27 28

5 5 Defining Resilience Size of the Stability Domain Amount of change a system can undergo and still retain the same controls 1 on function and structure Degree to which system can: Self-organize Learn and adapt 1 – set of reinforcing relations and feedbacks

6 6 Resilience: Three Levels of Meaning  Metaphor related to sustainability  A property of dynamic models  A quantity measurable in field studies

7 7 Adaptive Cycle Graphic Metaphor for Dynamism of Resilience

8 8 Panarchy a hierarchy of adaptive systems related by cross-scale interactions.

9 9 Resilience as Metaphor Guiding how we define its aspects Panarchy -A Cross-scale Nested Set of Adaptive Cycles Crown Tree Stand Forest These aspects change depending on the temporal, social, and spatial scale at which one measures. To assess resilience in terms of a hierarchal context, measure the resilience of what to what. Resilience at one scale can be subsidized by resilience at a broader scale in space and/or time.

10 10 Stability Landscape View of Evolution Shift from one domain to the next as the relations and feedbacks change As it changes, a system modifies its own possible states. Here a smaller and smaller perturbation can shift the equilibrium from one stability domain to another. Finally the stability domain disappears and the system spontaneously changes state.

11 11  Review Resilience  Regime Shifts  Surrogates of Resilience –Methods to find surrogates –Examples of application  Summary Outline

12 12 Regime Shift Examples

13 13 Regime shifts at different speeds Lake water quality Stylized trajectories through time of the fast (---) and slow ( ) variables in lakes (thick blue lines) and rangelands (thin red lines) under high levels of phosphate inflow (lakes) and grazing (rangelands). Sediment Phosphorus Shrubs Grass

14 14 Regime Shift Database Five Classes  Class 1. No linkage, externally driven change in ecological or social systems  Class 2. No linkage, internally driven change in the ecological or social systems  Class 3: Linked social–ecological systems, with a threshold change in only one system  Class 4: Linked social–ecological systems with reciprocal influences, but a shift in only one system  Class 5: Linked social–ecological systems with reciprocal influences, shifts in both the ecological and social systems Walker, B. and J. A. Meyers. 2004. Thresholds in ecological and social–ecological systems: a developing database. Ecology and Society 9(2): 3. [online] URL: http://www.ecologyandsociety.org/vol9/iss2/art3

15 15 Regime Shifts–9 Categories Walker, B. and J. A. Meyers. 2004. Thresholds in ecological and social–ecological systems: a developing database. Ecology and Society 9(2): 3. [online] URL: http://www.ecologyandsociety.org/vol9/iss2/art3

16 16 Clear Water Regime Controlling Processes  Phosphorus inputs from basin –Agric Methods (intensity & history) Fertilizer type & application rate Field size and shape Buffer strips on field margins Equipment size & use frequency  Soil Deposition related to soil type  Rain events ( duration, frequency, intensity)

17 17 Turbid Water Regime Controlling Processes  Phosphorus recycling from lake bottom –Ecological components Bethos sediment type Macrophyte / algae ratio Ratio bottom feeders / predators Zooplankton that eat algae  Physical components –Storm events (intensity & frequency) –Lake shape and depth

18 18  Review Resilience  Regime Shifts  Surrogates of Resilience –Methods to find surrogates –Examples of application  Summary Outline

19 19 Factors that challenge how we assess resilience  Context (indicators vary with it) –a web of relations that can change with time, spatial pattern, and the specifics of the local ecology and/or society.  Direct observation very difficult –events are rare, evidence may be dispersed in time and space. Manipulation impossible or unethical.

20 20 Resilience “Surrogate”  Contextual complexity – mandates that multiple models and multiple estimators be used in conjunction to measure different aspects of resilience.  Indicator – too narrow a term –to reflect this more systematic approach

21 21 Estimating Resilience Surrogates Interactive balancing between observation and modeling

22 22 Assessing R Surrogates A Stepwise methodology  Step 1 – Assess and define “problem” –- What aspect of the system should be resilient and to what?  Step 2 – ID feedback processes –- What variables are changing? –- What drivers create change? –- What feedbacks reinforce or damp change? Bennett, E.M., Cumming, G.S., Peterson, G.D. (2005). "A Systems Model Approach to Determining Resilience Surrogates for Case Studies." Ecosystems 8:pp. 945–957.

23 23 Assessing R Surrogates A Stepwise methodology  Step 3 – Model the System Structure – What are the key elements and how are they connected? –- Feedback loops and related key variables.  Step 4 – Use model to identify Resilience surrogates »- What is the threshold value of the state variable and how far is it from the threshold? »How fast is the state variable moving toward or away from the threshold? Bennett, E.M., Cumming, G.S., Peterson, G.D. (2005). "A Systems Model Approach to Determining Resilience Surrogates for Case Studies." Ecosystems 8:pp. 945–957.

24 24  Review Resilience  Regime Shifts  Surrogates of Resilience –Methods to find surrogates –Examples of application  Summary Outline

25 25 Assessing Resilience: a potential qualitative approach Australian rangeland ranching Balancing the interaction between your economic initiative:debt/income ratio your ecological constraints: shrub/grass ratio

26 26 Variance – evidence of approaching regime shift? SystemVariance evident as Regime shift approached Ocean-circulationSpectra shifted to lower frequencies Shallow lakeVariance increase in Individual macrophytes Terrestrial landscape mosaic Spatial variance of patches increased near threshold to percolation Field Data from lakes Whole lake manipulation by artificial forcing with added phosphorus exhibited increases in variance in phytoplankton biomass (Cottingham et al. 2000), and measures of variance in phosphorus recycling rates foretold threshold crossings one to two years in advance (Carpenter 2003).

27 27 Rising Variance of Phosphorus – a signal of approaching regime shift Carpenter, S.R., Brock, W.A. 2006. Rising variance: a leading indicator of ecological transition. Ecology Letters 9: 311–318.

28 28 Increasing variance as threshold approached

29 29 Variance of P: Dynamic Simulation

30 30 Possible Mechanism  Fast Variable (Phosphorus in water) –relaxes to equilibrium after small shocks.  Slow variables (Phosphorus in sediments) –SV change  slow change in two attractors making regime shift more likely  Variance (SD) in Fast variable increases In some types of systems, increased variability may occur over a wide zone of conditions near a transition, while in other types of systems the zone of increased variability may be so narrow as to be useless for empirical purposes.

31 31 Resilience Surrogates already proposed by social scientists  Organizational and institutional flexibility for dealing with uncertainty and change.  Social capital (including trust and social networks)  Social memory (including experience for dealing with change) Folke, C. (2006). "Resilience: The emergence of a perspective for social-ecological systems analyses." Global Environmental Change in press

32 32 Summary Collaborating in assessing resilience  Methods –A version of Bennett et al. 2004  Resources –Database of regime changes –Review of resilience surrogates already proposed by social scientists.

33 33 Resilience Indicator Fish Population Dynamics Model Rates of Birth and Mortality (per year) Fish Population Density (number per ha.) birth

34 34


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