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C.S. Holling (1930–2019)

Holling changed what “resilience” means in ecology — and in doing so gave complex adaptive systems research one of its most productive frameworks. His central move: stability and resilience are different things. A stable system returns to its equilibrium after perturbation. A resilient system absorbs perturbation while maintaining its function — and it may never return to the same state. Ecosystems, Holling argued, are resilient rather than stable, and their resilience depends on the very variability that equilibrium-based management tries to eliminate.

Life

Born Crawford Stanley Holling, 6 January 1930 in Ontario, Canada. BSc and MSc in ecology from the University of Toronto; PhD in ecology from the University of British Columbia (1957). Research scientist at the Canadian Department of Forestry, then faculty at the University of British Columbia, where he spent most of his career. Founded the Resilience Alliance in 1999 — a network of research institutions studying social-ecological resilience. Fellow of the Royal Society of Canada. Volvo Environment Prize (1998). Died 16 August 2019.

Resilience and stability

“Resilience and Stability of Ecological Systems” (Annual Review of Ecology and Systematics, 1973) is the foundational paper. Holling distinguished two concepts that ecology had been conflating:

Engineering resilience: the speed at which a system returns to equilibrium after perturbation. A ball in a bowl — the deeper the bowl, the faster the return. This is the concept most management frameworks use: how quickly does the system bounce back?

Ecological resilience: the magnitude of perturbation a system can absorb before it shifts to a qualitatively different regime — a different basin of attraction. A ball on a landscape with multiple bowls — resilience is about which bowl you’re in and how much it takes to knock you into a different one. Once you’ve crossed the threshold, “bouncing back” means returning to a different regime, not the original one.

The distinction matters for management. Engineering resilience says: reduce variability, maintain the current state, optimise for stability. Ecological resilience says: variability is what maintains the system’s capacity to absorb shocks; suppress it and you make the system brittle. The managed forest that never burns accumulates fuel until the fire that does come is catastrophic. The regulated river that never floods loses the floodplain dynamics that sustain its ecology.

The adaptive cycle

Holling’s most widely adopted framework. Ecosystems — and, he later argued, social and economic systems — move through four phases:

Exploitation (r). Rapid growth. Resources are abundant; colonising species or strategies spread fast. The system is accumulating structure.

Conservation (K). Consolidation. Resources are locked up in established structures; the system becomes increasingly interconnected, efficient, and rigid. Resilience declines as the system optimises for the current regime.

Release (Ω). Collapse. The accumulated rigidity makes the system vulnerable to perturbation. A fire, a market crash, a disease outbreak — the trigger can be small relative to the cascade it produces. Stored resources are released; established structures break apart.

Reorganisation (α). Renewal. The released resources become available for new combinations. Innovation, experimentation, and novelty are highest here. The system is open to reconfiguration before a new exploitation phase begins.

The cycle is not a fixed sequence — it can be interrupted, reversed, or short-circuited. The key insight is that collapse is not a failure of the system but a phase of its dynamics. Conservation builds toward release; release enables reorganisation; reorganisation enables the next exploitation. The system’s long-run resilience depends on all four phases, including the destructive one.

Panarchy

Panarchy: Understanding Transformations in Human and Natural Systems (edited with Lance Gunderson, Island Press, 2002) extends the adaptive cycle across scales. Panarchy is the name for the nested hierarchy of adaptive cycles operating at different spatial and temporal scales — a leaf, a tree, a forest, a biome, each with its own cycle, coupled across levels.

The cross-scale interactions matter. A release event at a small, fast scale (a single tree falling) may be absorbed by the conservation phase at a larger, slower scale (the forest). But if the larger scale is itself in late conservation — rigid, over-connected — the small disturbance can cascade upward and trigger release at the larger scale. The framework provides a vocabulary for how local disturbances become systemic crises and how renewal at one scale can restructure the scales above and below.

Social-ecological systems

Holling and his collaborators (particularly Brian Walker and Carl Folke) extended resilience thinking from ecology to coupled social-ecological systems — the recognition that human and natural systems are not separate but intertwined, and that the resilience of either depends on the other. The Resilience Alliance and the journal Ecology and Society (which Holling co-founded) became the institutional home for this programme.

The policy implication: manage for resilience rather than for optimality. Accept variability rather than suppressing it. Maintain the system’s capacity to reorganise rather than locking in the current regime. The framing has been taken up in natural resource management, urban planning, development studies, and climate adaptation.

Where Holling stops

Holling’s framework describes the dynamics of systems across scales — how they grow, consolidate, collapse, and renew. What it does not develop is the agent level. The adaptive cycle operates at the system level; the agents within the system (organisms, firms, individuals) are not modeled as adaptive units with internal structure. The step from system-level cycles to agent-level adaptation is where Holling’s resilience framework meets CAS — and where Holland’s agent-based approach picks up what the adaptive cycle describes from above.

Key works

See also: Kauffman · Complex Adaptive Systems