A presentation by L. German, D. Merrey and N. Johnson at the Workshop on Dealing with Drivers of Rapid Change in Africa: Integration of Lessons from Long-term Research on INRM, ILRI, Nairobi, June 12-13, 2008.

1. Resilience:Concepts & Implications for CG-Wide Research Collaboration Presented by L. German, D. Merrey and N. Johnson at the Workshop on Dealing with Drivers of Rapid Change in Africa: Integration of Lessons from Long-term Research on INRM, ILRI, Nairobi, June 12-13, 2008

2. I. CONCEPTS Ecological Scales Global Biome Landscape Ecosystem Plot/Herd Plant/Animal Genetic Socio-Political Scales International Regional National Municipal Village Family Individual

3. I. CONCEPTS “Birth, growth, death & renewal transform hierarchies from fixed static structures to dynamic adaptive entities” (Gunderson & Lowell) HIERARCHY  PANARCHY

4. I. CONCEPTS “Brittle” state at the end of growth cycle (tightly coupled system susceptible to triggers) Weakly connected state susceptible to change

5. I. CONCEPTS “Brittle” state at the end of growth cycle (tightly coupled system susceptible to triggers) Weakly connected state susceptible to change Susceptibility of the large / slow variables to change in the small / fast variables

6. I. CONCEPTS “Command & Control” Management: Avoid Release / Reorganization (…decreased resilience)

7. I. CONCEPTS “Command & Control” Management: Avoid Release / Reorganization (…decreased resilience) ‘Managers are often successful at rapidly achieving a set of narrowly defined goals, encouraging dependence on continuation while eroding the ecological support that it requires. Ecological change becomes thus increasingly undesirable and simultaneously more difficult to avoid’ (Gunderson and Lowell)

8. Properties Engineering Resilience Ecological Resilience Definition Speed of return to steady state following a perturbation (Pimm, O’Neill, Tilman, Downing) Magnitude of a disturbance that can be absorbed before the system is restructured with different controlling variables and processes (Walker, Holling) Discipline Engineering; economics Evolutionary biology Management aims Controlling unwanted variation (constancy, predictability) to achieve singular goal Persistence despite change & unpredictability (Gunderson & Pritchard) …or shift to more desirable steady state? Focus of study System behavior near known stable state Properties of boundaries between alternative states Management paradigms Command and control (Holling and Meffe 1996); avoidance of alternative states Adaptive management (Holling 1978; Walters 1986); maintenance of ecosystem function despite disturbance Time frame Short-term Historical, evolutionary Assumptions Knowledge is complete; predictability; ability to “control away” disturbance & surprise; ability to harness nature for narrowly defined goals Knowledge is incomplete; unpredictability; inevitability / constructive role of disturbance & adjustment (diversity, persistence); ecological systems pose limits to human knowledge and control Source: Gunderson and Pritchard 2002; Holling and Meffe 1996 I. CONCEPTS

9. Properties Engineering Resilience (Socio-)Ecological Resilience Definition Speed of return to steady state following a perturbation (Pimm, O’Neill, Tilman, Downing) Magnitude of a disturbance that can be absorbed before the system is restructured with different controlling variables and processes (Walker, Holling) Disciplines Engineering; economics Evolutionary biology; historical ecology Management aims Controlling unwanted variation (constancy, predictability) to achieve singular goal Persistence despite change & unpredictability (Gunderson & Pritchard) …or shift to more desirable steady state? Focus of study System behavior near known stable state Properties of boundaries between alternative states Management paradigms Command and control (Holling and Meffe 1996); avoidance of alternative states Adaptive management (Holling 1978; Walters 1986); maintenance of ecosystem function despite disturbance Time frame Short-term Historical, evolutionary Assumptions Knowledge is complete; predictability; ability to “control away” disturbance & surprise; ability to harness nature for narrowly defined goals Knowledge is incomplete; unpredictability; inevitability / constructive role of disturbance & adjustment (diversity, persistence); ecological systems pose limits to human knowledge and control Source: Gunderson and Pritchard 2002; Holling and Meffe 1996 I. CONCEPTS

10. Properties Engineering Resilience (Socio-)Ecological Resilience Definition Speed of return to steady state following a perturbation (Pimm, O’Neill, Tilman, Downing) Magnitude of a disturbance that can be absorbed before the system is restructured with different controlling variables and processes (Walker, Holling) Disciplines Engineering; economics Evolutionary biology; historical ecology Management aims Controlling unwanted variation (constancy, predictability) to achieve singular goal Persistence despite change & unpredictability (Gunderson & Pritchard) …or shift to more desirable steady state? Focus of study System behavior near known stable state Properties of boundaries between alternative states Management paradigms Command and control (Holling and Meffe 1996); avoidance of alternative states Adaptive management (Holling 1978; Walters 1986); maintenance of ecosystem function despite disturbance Time frame Short-term Historical, evolutionary Assumptions Knowledge is complete; predictability; ability to “control away” disturbance & surprise; ability to harness nature for narrowly defined goals Knowledge is incomplete; unpredictability; inevitability / constructive role of disturbance & adjustment (diversity, persistence); ecological systems pose limits to human knowledge and control Source: Gunderson and Pritchard 2002; Holling and Meffe 1996 I. CONCEPTS

11. Properties Engineering Resilience (Socio-)Ecological Resilience Definition Speed of return to steady state following a perturbation (Pimm, O’Neill, Tilman, Downing) Magnitude of a disturbance that can be absorbed before the system is restructured with different controlling variables and processes (Walker, Holling) Discipline Engineering; economics Evolutionary biology; historical ecology Management aims Controlling unwanted variation (constancy, predictability) to achieve singular goal Persistence despite change & unpredictability (Gunderson & Pritchard) …or shift to more desirable steady state? Focus of study System behavior near known stable state Properties of boundaries between alternative states Management paradigms Command and control (Holling and Meffe 1996); avoidance of disturbance / alternative states Adaptive management (Holling 1978; Walters 1986); maintenance of ecosystem & social functions despite disturbance Time frame Short-term Historical, evolutionary Assumptions Knowledge is complete; predictability; ability to “control away” disturbance & surprise; ability to harness nature for narrowly defined goals Knowledge is incomplete; unpredictability; inevitability / constructive role of disturbance & adjustment (diversity, persistence); ecological systems pose limits to human knowledge and control Source: Gunderson and Pritchard 2002; Holling and Meffe 1996 I. CONCEPTS

12. Properties Engineering Resilience (Socio-)Ecological Resilience Definition Speed of return to steady state following a perturbation (Pimm, O’Neill, Tilman, Downing) Magnitude of a disturbance that can be absorbed before the system is restructured with different controlling variables and processes (Walker, Holling) Discipline Engineering; economics Evolutionary biology; historical ecology Management aims Controlling unwanted variation (constancy, predictability) to achieve singular goal Persistence despite change & unpredictability (Gunderson & Pritchard) …or shift to more desirable steady state? Focus of study System behavior near known stable state Properties of boundaries between alternative states Management paradigms Command and control (Holling and Meffe 1996); avoidance of disturbance / alternative states Adaptive management (Holling 1978; Walters 1986); maintenance of ecosystem & social functions despite disturbance Time frame Short-term Historical, evolutionary Assumptions Knowledge is complete; predictability; ability to “control away” disturbance & surprise; ability to harness nature for narrowly defined goals Knowledge is incomplete; unpredictability; inevitability / constructive role of disturbance & adjustment (diversity, persistence); ecological systems pose limits to human knowledge and control Source: Gunderson and Pritchard 2002; Holling and Meffe 1996 I. CONCEPTS

13. I. CONCEPTS What if the current state is undesirable? Is resilience an undesirable quality? Resilience  resisting change Resilient systems are those that retain essential (ecological, social) functions despite disturbance

14. I. CONCEPTS What if the current state is undesirable? Is resilience an undesirable quality? Resilience  resisting change Resilient systems are those that retain essential (ecological, social) functions despite shocks / disturbance

15. I. CONCEPTS What if the current state is undesirable? Is resilience an undesirable quality? Resilience  resisting change Resilient systems are those that retain essential (ecological, social) functions despite shocks / disturbance ?

16. I. CONCEPTS “First-order resource” = a natural resource that is becoming scarcer relevant to population over time (or “First-Order Ecological Condition” ... ecological condition becoming increasingly undesirable). “Second-order resource” = set of potential 'adaptive behaviors' (rules, values, information, social capital) that enable a society to generate and implement solutions to difficult problems. (adapted from Turton and Ohlsson)

18. Patchiness of productivity

19. Species composition (W, A, P, PU) controlled by extreme years (decline in W); grazing (species, intensity – P:PU)

21. Patchiness of productivity

22. Species composition(W, A, P, PU)controlled by extreme years(decline in W); grazing(species, intensity – P:PU)

24. Patchiness of productivity

25. Species composition(W, A, P, PU)controlled by extreme years(decline in W); grazing(species, intensity – P:PU)

26. Key ecosystem processes: competition; fuel accumulation; and their interaction with drivers (rainfall, fire, grazing)

27. Resilience = f (rainfall, grazing intensity, patchiness) + “2nd Order” variables (social resilience)“A resilient landscape for pastoralism is one that can retain or recover sufficient function to support fodder production, despite disturbance” (Abel & Langston, 2001)

33. II. CASE STUDIES A. Rangeland Management (Abel and Langston, 2001) Australia / NSW: = Sheep # 1860 Time 2000

35. II. CASE STUDIES A. Rangeland Management (Abel and Langston, 2001) Australia / NSW: = Sheep # Korean War (wool $$) = Political-economic drivers & responses Global Price support ends Rural political dominance Urban dominance, “Closer Settlement” Scale of Drivers & Responses Strong economy Publicly funded water supplies / stock routes Local 1860 Time 2000

37. Policy of “closer settlement”; new settlers subsidized- Lease extension - Debt forgiveness - Rabbit fence, dingo control Aim - Unknown - Political (urban demand) -  borrowing capability for “drought-proofing” -  economic hardship - Reduce predation on sheep Outcome - Pressure on rangeland -  vulnerability; reduced economy of scale; move into marginal land - Debt decreased financial viability of ranches -  value of leases   in collateral   debt - Loss of kangaroo predator   pressure on range

39. Policy of “closer settlement”; new settlers subsidized- Lease extension - Debt forgiveness - Rabbit fence, dingo control Aim - Unknown - Political (urban demand) -  borrowing capability for “drought-proofing” -  economic hardship - Reduce predation on sheep Outcome - Pressure on rangeland -  vulnerability; reduced economy of scale; move into marginal land - Debt decreased financial viability of ranches -  value of leases   in collateral   debt - Loss of kangaroo predator   pressure on range

41. Policy of “closer settlement”; new settlers subsidized- Lease extension - Debt forgiveness - Rabbit fence, dingo control Aim - Unknown - Political (urban demand) -  borrowing capability for “drought-proofing” -  economic hardship - Reduce predation on sheep Outcome - Pressure on rangeland -  vulnerability; reduced economy of scale; move into marginal land - Debt decreased financial viability of ranches -  value of leases   in collateral   debt - Loss of kangaroo predator   pressure on range

43. Policy of “closer settlement”; new settlers subsidized- Lease extension - Debt forgiveness - Rabbit fence, dingo control Aim - Unknown - Political (urban demand) -  borrowing capability for “drought-proofing” -  economic hardship - Reduce predation on sheep Outcome - Pressure on rangeland -  vulnerability; reduced economy of scale; move into marginal land - Debt decreased financial viability of ranches -  value of leases in collateral  debt - Loss of kangaroo predator   pressure on range

45. Policy of “closer settlement”; new settlers subsidized- Lease extension - Debt forgiveness - Rabbit fence, dingo control Aim - Unknown - Political (urban demand) -  borrowing capability for “drought-proofing” -  economic hardship - Reduce predation on sheep Outcome - Pressure on rangeland -  vulnerability; reduced economy of scale; move into marginal land - Debt decreased financial viability of ranches -  value of leases in collateral  debt - Loss of kangaroo predator  pressure on range

46. II. CASE STUDIES A. Rangeland Management (Abel and Langston, 2001) Australia / NSW: = Sheep # = Social drivers & responses Global Sub-regional Networking (reciprocity, knowledge exchange) Political organizing Scale of Drivers & Responses Eviction of aborigines, fire Expansion of watering points to access new rangeland; reduced stocking density Local 1860 Time 2000

47. II. CASE STUDIES A. Rangeland Management

49. II. CASE STUDIES B. Cropping Systems Industrialized agriculture “seeks to remove dependency on the natural processes normally required for plant production” (Vaughan, 1998) Does this enhance or undermine resilience?

51. cycles (weed suppression) weeds (Striga) (E)

52. - Reliance on imported nutrients - ISFM, rotation, tillage (C)

53. Germplasm - Selection for narrow set of traits; - Outbreaks (bacterial wilt,genetic simplification stem rust) (E) - Substitute genetic resilience for - “ICGM”? (C) external controls

55. cycles (weed suppression) weeds (Striga) (E)

56. - Reliance on imported nutrients - ISFM, rotation, tillage (C)

57. Germplasm - Selection for narrow set of traits; - Outbreaks (bacterial wilt,genetic simplification stem rust) (E) - Substitute genetic resilience for - “ICGM”? (C) external controls

59. cycles (weed suppression) weeds (Striga) (E)

60. - Reliance on imported nutrients - ISFM, rotation, tillage (C)

61. Germplasm - Selection for narrow set of traits; - Outbreaks (bacterial wilt,genetic simplification stem rust) (E) - Substitute genetic resilience for - “ICGM”? (C) external controls

62. II. CASE STUDIES B. Cropping Systems Case Study (Wolaita, Ethiopia): 1991 1974 Political- Economic System Feudalist - Reliance on organic nutrients; germplasm adapted to sub-optimal, variable conditions Local Adaptive Capacity

63. II. CASE STUDIES B. Cropping Systems Case Study (Wolaita, Ethiopia): Fertilizer subsidy 1991 1974 Political- Economic System Feudalist Communist (Derg) - Reliance on organic nutrients; germplasm adapted to sub-optimal, variable conditions - Production / income gains; chemical replaces organic fertilizer; gradual loss of local germplasm Local Adaptive Capacity

65. Germplasm adapted to sub-optimal conditions now in short supply

66. Food insecurity Local Adaptive Capacity

67. II. CASE STUDIES C. River Basin Management In many river basins water is increasingly over-allocated, leading to high levels of conflict over scarce water, rising inequity, environmental degradation, serious health impacts

68. II. CASE STUDIES C. River Basin Management The current dominant paradigm – “integrated water resources management” (IWRM) – as often (mis-)understood: simultaneously addressing the full range of issues. (Source: DWAF)

70. Doing everything at once (Source: DWAF)

72. Doing everything at once (Source: DWAF)

74. Doing everything at onceundermines effectiveness(Source: DWAF)

77. II. CASE STUDIES C. River Basin Management Figures 2a,b. Biophysical results of “soft skill” approach: perennial flows (Langkford et al, 2007)

78. II. CASE STUDIES C. River Basin Management Figures 2a,b. Biophysical results of “soft skill” approach: perennial flows (Langkford et al, 2007) Key Ingredients to Success: - Research (opportunities for re-allocation) - Negotiationsupport with  volume users - Social learningamong un-like actors (private sector, government, smallholders)

79. II. IMPLICATIONS FOR INRM PLATFORM? Resilience derives from functional reinforcement across scales & functional overlap within scales. Ecological resilience can only be analyzed and measured across scales (temporal, spatial or both) … and disciplines. Surprises occur when variation in broad-scale processes (e.g. extreme weather events) interact with internal changes due to human alteration. A unique property of human systems in response to uncertainty is the generation of novelty – key to dealing with surprise/crisis. Yet societies vary in their social capacity (2nd order response) to adapt to changing natural resources (1st order trigger). Most policies are really questions masquerading as answers. Management actions then become experimental treatments. Effective responses assess types / sources of uncertainty, but also identify sources of flexibility, develop actions structured for learning, and allow for generation of novelty.

80. II. IMPLICATIONS FOR INRM PLATFORM? Resilience derives from functional reinforcement across scales & functional overlap within scales. Ecological resilience can only be analyzed and measured across scales (temporal, spatial or both) … and disciplines. Surprises occur when variation in broad-scale processes (e.g. extreme weather events) interact with internal changes due to human alteration. A unique property of human systems in response to uncertainty is the generation of novelty – key to dealing with surprise/crisis. Yet societies vary in their social capacity (2nd order response) to adapt to changing natural resources (1st order trigger). Most policies are really questions masquerading as answers. Management actions then become experimental treatments. Effective responses assess types / sources of uncertainty, but also identify sources of flexibility, develop actions structured for learning, and allow for generation of novelty.

81. II. IMPLICATIONS FOR INRM PLATFORM? Resilience derives from functional reinforcement across scales & functional overlap within scales. Ecological resilience can only be analyzed and measured across scales (temporal, spatial or both) … and disciplines. Surprises occur when variation in broad-scale processes (e.g. extreme weather events) interact with internal changes due to human alteration. A unique property of human systems in response to uncertainty is the generation of novelty – key to dealing with surprise/crisis. Yet societies vary in their social capacity (2nd order response) to adapt to changing natural resources (1st order trigger). Most policies are really questions masquerading as answers. Management actions then become experimental treatments. Effective responses assess types / sources of uncertainty, but also identify sources of flexibility, develop actions structured for learning, and allow for generation of novelty.

82. II. IMPLICATIONS FOR INRM PLATFORM? Resilience derives from functional reinforcement across scales & functional overlap within scales. Ecological resilience can only be analyzed and measured across scales (temporal, spatial or both) … and disciplines. Surprises occur when variation in broad-scale processes (e.g. extreme weather events) interact with internal changes due to human alteration. A unique property of human systems in response to uncertainty is the generation of novelty – key to dealing with surprise/crisis. Yet societies vary in their social capacity (2nd order response) to adapt to changing natural resources (1st order trigger). Most policies are really questions masquerading as answers. Management actions then become experimental treatments. Effective responses assess types / sources of uncertainty, but also identify sources of flexibility, develop actions structured for learning, and allow for generation of novelty.

83. II. IMPLICATIONS FOR INRM PLATFORM? Resilience derives from functional reinforcement across scales & functional overlap within scales. Ecological resilience can only be analyzed and measured across scales (temporal, spatial or both) … and disciplines. Surprises occur when variation in broad-scale processes (e.g. extreme weather events) interact with internal changes due to human alteration. A unique property of human systems in response to uncertainty is the generation of novelty – key to dealing with surprise/crisis. Yet societies vary in their social capacity (2nd order response) to adapt to changing natural resources (1st order trigger). Most policies are really questions masquerading as answers. Management actions then become experimental treatments. Effective responses assess types / sources of uncertainty, but also identify sources of flexibility, develop actions structured for learning, and allow for generation of novelty.

85. To what extent are we aware of the long-term consequences of the focus on maximizing short-term returns?

86. To what extent are we aware of the interaction of local and higher-level variables, and of social, political, technological and biophysical variables, in producing outcomes?

87. Under what conditions do “command-and-control” type interventions enhance resilience by improving incomes and capacity to ‘weather’ shocks? Under what conditions do they enhance vulnerability (e.g. deplete natural capital or sources of novelty, enhance “brittleness” / susceptibility to shocks)?