All posts by Buzz Holling

Big Back Loop, Reflections

From Ecosystems and Economics to Social Systems: Reflections Pt 6

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panarchyMy personal discovery that economists could be synthetic and insightful provided the spark for another series of studies that finally led to an effort to collaborate with economists, ecologists, social scientists and mathematicians to develop an integrative theory and examples of systems change and evolution. The rationale was that the theories developed in each of those disciplines were not wrong, just incomplete in different ways.

The integration of the results of the Resilience Project was presented in the book Panarchy: Understanding transformations in Human and Natural Systems (Gunderson and Holling 2002). In it I tried to summarize my present understanding of complex adaptive systems in the first three chapters, and in the conclusions in Chapter 15. Perhaps those chapters, and the book, will eventually have the citations and influence of the three papers that were highlighted by the student’s discovery of key Ecosystem references.

Writing the third, key chapter of theoretical synthesis, (Holling et al. 2002) was like a “mind dump”! I was happy with the content I wrote, but the style is very condensed, very dense. Some sentences could have been expanded to a few pages, some short paragraphs to a full chapter. But space was limiting.

As modest help, I also wrote an essential condensation of the book in Holling, 2001. And a more lightly written summary that expanded the work to its possible relevance to the big social and political changes that were set in motion after the terrorist attacks on September 11, 2001 (Holling 2004). I suggested it was the time for small scale abundant experiments in living, and working. It is a time when individuals have the greatest chances for influence, as resisting institutions weaken and fail. Do not develop an overall plan for those experiments, but set a tactical goal, which, in this case is novelty, safety and low cost. The invention of the internet offers explosive opportunity. Some fail, some succeed and that can provide seeds for subsequent healthy re-creation. That is a way for the trap, now global, to be transformed into something more positive for the future of people. There are ways out!

But maybe that alone is too naïve and hopeful. Consider the present moment.

I wrote the above paper one and a half years after 9/11. As I write these reflections it has been five years. What has been unrolling is the same pathology as described earlier for the resource management pathologies. So far, the responses to terrorism have been largely quick and expensive military fixes and security checks, followed by quick successes. But the result has led political leaders to ignore the slowly enrolling causes, and long-term failure.

Therefore, in addition to a plethora of experiments, now it is clear we also need to attend the slow variables as well. We need responses to the slow, deep changes that have caused the explosion. It is not just evil loose in the world. There is humiliation, inequality and ignorance, combined with an exaggerated fixation on a particular extreme identity found in the fundamentalism of the religions of Abraham- of Christians, Muslims and Jews. That is a slow process to create; a slow process to redress. And all is made more rigid by the dependence of developed countries and of powerful ones on the oil of the Middle East. People seem locked into their personal, fear-ridden regimes that are self re-enforcing, creating differences between them, not bridging them: a deep, deep trap. Panarchy perhaps helps in providing a theory and contexts.

References
Holling, C.S. 2001. Understanding the complexity of economic, social and ecological systems. Ecosystems 4: 390-405.

Holling, C. S. 2004. From complex regions to complex worlds. Ecology and Society 9(1): 11. [online] URL: http://www.ecologyandsociety.org/vol9/iss1/art11

Holling, C. S., L.H. Gunderson and G.D. Peterson. 2002. Sustainability and Panarchies. In. Gunderson, L.H and Holling, C.S (eds) Panarchy: Understanding transformations in Human and Natural Systems . Island Press, Washington and London, Chapter 3, 63-102.

Ecological Management, Reflections

Ecosystem Reality – Modelling: Reflections Pt 5

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The second advance produced by our series of studies of large scale ecosystems was a set of deep case studies with modeling efforts that could be used in a comparative analysis of ecosystems behavior and ecosystems management. Those examples included some 20-30 examples of crisis-ridden histories of forests, fisheries, agriculture, human diseases and water resource development.

One theoretical study suddenly helped significantly, when my eyes were opened to the essential way to understand and display the (relatively simple) causes of complex behavior (Ludwig, Jones and Holling, 1978). It was Don Ludwig and Dixon Jones who taught me the way, using the essence of qualitative differential equation theory.

It all started when Don took a half page I wrote explaining the essence of the causes of forest changes mediated by spruce budworm in eastern Canada. He then turned that into a coupled, three differential equation model that expressed the interacting dynamics of budworm, foliage and trees. Meanwhile Dixon, with help from Bill Clark and I, had been developing the big simulation model of the system that emerged out of a series of workshops with the scientists and policy people in New Brunswick. As part of our philosophy of economy in modeling, I had been careful to leave out the effects of avian predation, relying on an eventual check with measured behavior of the whole system in nature to tell us what essentials we had missed. When we discovered that the behavior of the simulation model simply did not match the field behavior, we used it and our ecological knowledge to discover the “missing process”, as a kind of interactive, diagnostic procedure.

The missing piece turned out to be one with certain specific nonlinearities at low densities of budworm and low volume of foliage. The only process we could discover to fill the bill was predation by the 35 different species of insectivorous birds. That linked us back to my earlier set of predation discoveries and we added the effect using the predation equations and parameter data from the field. The effect added progressively stronger predation as budworm densities rose from low levels, and faded thereafter as budworm populations increased- that is, a domed shaped response. Since the densities of birds were essentially constant, that predation effect gradually weakened as the forest aged and the increasing volume of foliage dispersed the searching by birds. The result was periodic outbreak of the insect in older forests.

When these same bird predation effects were then added to Don’s differential equations, that too began to reflect what occurred in nature. So it was a beautiful example of the power of linking three key methodological concepts; Don’s qualitative differential equation approaches, Dixon’s scientifically infused simulation modeling and my general process analysis modeling (Ludwig et al. 1978). The advance led to a clear way to understand and compare the 20-30 examples of complex ecosystem behavior in totally different kinds of situations (Holling, 1986).

The results appeared in the second paper discovered by the students i.e. in Holling 1986. It is a chapter in the first (and maybe only) significant book that deals with sustainability in a fundamental, interdisciplinary way. That book was Bill Clark’s inspiration and creation. My chapter for the first time developed the theoretical discoveries emerging from the comparison of those ecosystem studies. Some of the key features of ecosystems popped out: e.g. there had to be at least three sets of variables, each operating at qualitatively different speeds. There was an essential interaction across scales in space and time covering at least three orders of magnitude. Non-linearities were essential. Multi-stable states were inevitable. Surprise was the consequence.

And a puzzle emerged concerning what seemed to be an inevitable pathology of resource management. In case after case, the same pattern appeared. An economic or social problem was identified as being present or looming in the near future. It was then narrowly defined and treated in a least cost manner for fast corrective response. Then, unknown to all, the system evolved.

First, the problem seemed to disappear. Budworm outbreak populations became controlled, forest fires were suppressed before spreading, water was stored and irrigation became possible for agriculture, fisheries were augmented with hatchery stocks, and so on. Second, industry expanded: pulp mills, tree harvesting, agriculture, fisheries and with that, regional economic and social development.

Third, slow, unappreciated changes occurred that meant that resilience was restricting, was declining. In most cases, the resilience declined because spatial heterogeneity shifted to a more homogeneous state. A “spark”, once initiated, could therefore spread up scale. That is, conditions for outbreaks in healthy forests spread, forest stands became more homogeneous in age and became fuel rich, salt accumulated in soil as soil water levels rose, natural fish stocks gradually went extinct leaving fisheries precariously dependent on a few enhanced stocks. All became disastrous surprises waiting to happen.

Slowly decreasing resilience faced fast increasing economic and social dependencies that made retreat and redesign extremely difficult. Working with nature was rarely conceived. Instead, the response to correct the surprises, started or continued a sequence that maintained the evolving system with more and more costs. The classic example of that is the Everglades, which, after over 80 years of four crises, now is launched into an eight billion dollar restoration, with little active adaptive design. In contrast, the Columbia River system is deeply involved in a policy that indeed does exploit natural forces in an interesting adaptive scheme.

Other examples of “command and control”, of passive and active adaptation in regional social/ecological systems have been recently described in Olsson et al 2006, leading to a set of considerations and actions we identified for successful transformation toward adaptive governance,

This universal pattern represented one of the social traps later discovered as a potential for panarchies. Subsequent avoidance of the trap can occur through learning and actions to enhance resilience by reintroducing spatial heterogeneity at appropriate scales. But often the remedial responses simply continued and extended the process, protected by gradually increasing investments of money to monitor, subsidize and control.

Adaptive cycle

And I used the paper to present the first big theoretical synthesis. That was the place where the Adaptive Cycle was first described and presented. That is, there are four components of change in ecosystems, the traditionally known and slowly evolving exploitation and conservation phases and the newer, fast, unpredictable creative destruction and renewal phases. The first two are when capital and skills are slowly accumulated, but resilience is typically gradually lost. The last two are when unpredictability explodes, capital is freed for other roles and novelty can become implanted. Moreover, those same four components seemed to provide a general metaphor for all systems, and examples were discussed from economics, technology, institutions and psychology. In fact, I discovered that the creative destruction phase had already been posited decades earlier by an economist, Joseph Schumpeter, for international businesses. Maybe economists were not all so narrow!

References

Holling, C.S. 1986. The resilience of terrestrial ecosystems; local surprise and global change. In: W.C. Clark and R.E. Munn (eds.). Sustainable Development of the Biosphere. Cambridge University Press, Cambridge, U.K. Chap. 10: 292-317.

Holling, C.S. and A.D. Chambers. 1973. Resource science: the nurture of an infant. Bioscience 23(1): 13-20.

Ludwig, D., D.D. Jones and C.S. Holling. 1978. Qualitative analysis of insect outbreak systems: the spruce budworm and forest. J. Animal. Ecol. 44: 315-332.

Olsson, P., L. H. Gunderson, S. R. Carpenter, P. Ryan, L. Lebel, C. Folke and C. Holling 2006. Shooting the Rapids: Navigating Transitions to Adaptive Governance of Social-Ecological Systems. Ecology and Society 11 (1): 18. [online] URL: http://www.ecologyandsociety.org/vol11/iss1/art18/

Walters, C.J. 1986. Adaptive Management of Renewable Resources. MacMillan, New York.

Walters, C., and Martell, S. 2004. Fisheries Ecology and Management. Princeton Univ. Press, Princeton, NJ.

Ecological Management, Reflections

Ecosystem Reality – Workshops: Reflections Pt 4

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The second paper the students identified was: Holling, C.S. 1986. The resilience of terrestrial ecosystems; local surprise and global change. In: W.C. Clark and R.E. Munn (eds.). Sustainable Development of the Biosphere. Cambridge University Press, Cambridge, U.K. Chap. 10: 292-317.

For me, the 1973 “Resilience’ paper launched the Adaptive Management work, with Carl Walters at the University of British Columbia- a great friend and a truly brilliant, maverick scientist who walks a non-traditional path that creates new traditions. His work on adaptive management methods has been a classic contribution to the field (Walters 1986). More recently he has advanced ecosystem dynamics understanding using his creation of foraging arena theory which had its beginnings in my own predation work (Walters and Martell 2004).

The resilience research led us to mobilize a series of studies of large scale ecosystems subject to management- terrestrial, fresh water and marine. All this was done with the key scientists and, in some cases, policy people who “owned “ the systems and the data. So the process encouraged two major advances.

One advance developed a sequence of workshop techniques so that we could work with experts to develop alternative explanatory models and suggestive policies. We learned an immense amount from the first experiment. That focused on the beautiful Gulf Islands, an archipelago off the coast of Vancouver. We chose to develop a recreational land simulation of recreational property. I knew little about speculation, but we made up a marvelous scheme that used the predation equations as the foundation- the land of various classes were the “prey”, speculators were the “predators” and a highest bidder auction cleared the market each year. The equations were modifications of the general predation equations. The predictions were astonishingly effective and persisted so for at least a decade. As much as anything, it reinforced the earlier conclusion that these equations were powerful and general. But the important conclusion concerned the workshop process and the people.

The essence of those workshop methods were fun to present in a critical paper where the workshop processes were described and where key personalities were represented in delightful cartoons drawn by Roy Peterson, a cartoonist in Vancouver, and methods were expressed as a game. (Holling, C.S. and A.D. Chambers. 1973 ).

workshop characters 2

It was fun to reveal the truth about characters like Snively Whiplash, The Blunt Scot, The Utopians and The Peerless Leaders and such in this way, but a reviewer in Ecology turned it down by saying “no one wants to know about the games people in British Columbia play!” BioScience reviewers were more enlightened so I happily published there.

workshop characters

Those approaches helped shape the essential design and maintain the flexibility of the big international Resilience Project that I began about two decades later. It produces a turbulent, broad and delightful process of mutual discovery for those who chose to be part of it.

I learned that the key design was to identify large, unattainable goals that can be approached, but not achieved; ones that relate to fundamental values of free speech, freedom, equity, tolerance and education. And then to add a tough design for the first step, in a way that highlights or creates options to design, later, a second step—and then a third and so on. We found that the results were steps that rapidly covered more ground than could ever be designed at the start. At the heart, that is adaptive design, where the unknown is great, learning is continual and actions evolve.

References

Holling, C.S. 1986. The resilience of terrestrial ecosystems; local surprise and global change. In: W.C. Clark and R.E. Munn (eds.). Sustainable Development of the Biosphere. Cambridge University Press, Cambridge, U.K. Chap. 10: 292-317.

Holling, C.S. and A.D. Chambers. 1973. Resource science: the nurture of an infant. Bioscience 23(1): 13-20.

Ludwig, D., D.D. Jones and C.S. Holling. 1978. Qualitative analysis of insect outbreak systems: the spruce budworm and forest. J. Animal. Ecol. 44: 315-332.

Walters, C.J. 1986. Adaptive Management of Renewable Resources. MacMillan, New York.

Walters, C., and Martell, S. 2004. Fisheries Ecology and Management. Princeton Univ. Press, Princeton, NJ.

Reflections, Regime Shifts

Resilience: Reflections part 3

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My bridge to studying ecosystems started once I shifted to combine the functional and numerical response equations with others concerning other processes in order to make a population model, of interacting predator and prey. That is when, suddenly and unexpectedly, multi-stable states appeared. Lovely indeed. Great fun and a big surprise to me! A new landscape for exploration opened.

Non-linear forms of the functional responses (e.g. the Type 3 S-shaped response) and of reproduction responses (e.g. the Allee effect) interacted to create two stable equilibria for interacting populations, with an enclosed stability domain around one of them. It was the responses at low densities that were critical- that is where vertebrate predators have yet to learn to locate the prey easily, and where mates are too scarce to find each other easily. Once discovered, it seemed obvious that conditions for multi-stable states were inevitable. And that, being inevitable, there were huge consequences for theory and for practice.

Up to that time, a concentration on a single equilibrium and assumptions of global stability had made ecology, as well as economics, focus on near equilibrium behavior, and on fixed carrying capacity with a goal of minimizing variability. Command and control was the policy for managing fish, fowl, trees, herds, and freedom was unlimited to provide opportunity for people.

The multi-stable state reality, in contrast, opened an entirely different direction that focused on behavior far from equilibrium and on stability boundaries. High variability, not low variability, became an attribute necessary to maintain existence and learning. Surprise and inherent unpredictability was the inevitable consequence for ecological systems. Data and understanding at low densities, rare because they are all the more difficult to obtain, were more important than those at high-density. I used the word resilience to represent this latter kind of stability

Hence the useful measure of resilience was the size of stability domains, or, more meaningfully, the amount of disturbance a system can take before its controls shift to another set of variables and relationships that dominate another stability region. And the relevant focus is not on constancy but on variability. Not on statistically easy collection and analysis of data but statistically difficult and unfamiliar ones. That needs a different eye to see and a different theory to perceive consequences.

About that time, I was invited to write a 1973 review article for the Annual Review of Ecology and Systematics. I therefore decided to turn it into a review of the two different ways of perceiving stability and in so doing highlight the significance for theory and for practice. That required finding additional rare field data in the literature that demonstrated flips of populations from one level or state to another, as well as describing the recently discovered known non-linearities in the processes that caused or inhibited the phenomenon. That was a big job and I recall days when I thought it was all bunk, and days when I believed it was all real. I finished the paper on a “good” day, when all seemed pretty clear. By then I guess I was convinced. The causal, process evidence was excellent, though the field evidence concerning population flips, was only suggestive. Nevertheless the consequences for theory and management were enormous. It implied that uncertainty was inevitable. And that ecosystems, in an evolutionary time span, were momentary entities pausing in a flip to different states. As I’ll describe, it took about 30 years to confirm those conclusions for others.

This paper began to influence fields outside population/community ecology a bit – anthropology, political science, systems science first, then, later, ecosystem science. It became the theoretical foundation for active adaptive ecosystem management. But it was largely ignored or opposed by practitioners in the central body of ecology. What followed was the typical and necessary skepticism released by new ideas, that I’ll describe briefly here because it is such a common foundation for developing science.

One early ecological response to the paper was by Sousa and Connell (1985). They asked the good question “was there empirical evidence for multi-stable states?”. They attempted to answer by analyzing published data on time series of population changes of organisms to see if the variance suggested multi-stable behavior. They found no such evidence. This so reinforced the dominant population ecology single equilibrium paradigm, that the resilience concept was stopped dead, in that area of science.

It seemed to be an example of evidence that refuted this new theory. But their evidence was inappropriate and the theory was not! In fact, their evidence, as is often the case, was really a model, incomplete because the collators unconsciously used an inappropriate model for choosing data that were incomplete.

There are two problems with their analysis:

  1. They did not ask any process question (are there common non-linear mechanisms that can produce the behavior?). That is where the good new hard evidence that I had discovered lay.
  2. They rightly saw the need for long time series data on populations that had high resolution. As population/community ecologists of tradition, however, their view of time was a human view- decades were seen as being long. That view is reinforced by a “quadrat” mentality. Not only small in time, but small in spatial scale; and a theory limited to linear interactions between individuals in single species populations or between two species populations, all functioning at the same speed (e.g. predator/prey, competitors). It represents the dangers caused by inferring that “microcosm” thought and experiments have anything to contribute to the multiscale functioning of ecosystems. Steve Carpenter has a perceptive critique of that tendency (Carpenter, 1996).

The multi-stable behavior can only be interpreted within the context of at least three but, as suggested in the Panarchy paper/chapter, probably not more than five variables. These variables need to differ qualitatively in speed from each other. It is therefore inherently ecosystemic. It is the slow variables that determine how many years of data are needed for their kind of test. None of their examples had anywhere near the duration of temporal data needed.

As an example: The available 45 years of budworm population changes they analyzed seemed long to Sousa and Connell and to all those conditioned by single variable behavior and linear thinking of the times. But the relevant time scale for the multi-equilibrium behavior of budworm is set by their hosts, the trees or the slow variable. What is needed for their tests was yearly budworm data (the fast variable) over several generations of trees (the slow variable), i.e. perhaps one and a half centuries – not 45 years. The normal boom and bust cycle is 40-60 years

It has since taken 25 years of study of different ecosystems to develop data for appropriate tests. Examples include those using paleo-ecological data covering centuries at high resolution, the deep and shallow lake studies and experiments of Carpenter (Carpenter 2000) in the United States and of Marten Scheffer, in Europe (Scheffer et al. 1993), the experimental manipulations of mammalian predator and prey systems in Australia and Africa by Tony Sinclair (Sinclair et al. 1990), and a variety of studies of specific ecosystems- sea urchin, coral reef etc. Terry Hughes and his colleagues’ works on coral reefs stand out as examples. Carpenter’s important summary paper makes the point (Carpenter, 2000). Multi-stable states are real and of great importance, although they are difficult to demonstrate. Surprise, uncertainty and unpredictability are the inevitable result. Command and control management temporarily hides the costs, but the ultimate cost of surprises produced by managing systems that ignore multi-stable properties is too great. Active adaptive management is the only alternative management response possible. Steve Carpenter and Buz (W.A.) Brock – a great ecosystems scientist together with a wonderful ”non-linear” economist- show why in a classic paper where a minimal model of a watershed, farming styles, of regional monitoring and regional decision regarding phosphate control, encounter the surprises created as a consequence of a multi-stable state (Carpenter, Brock, and Hanson, 1999).

References:

Carpenter, Stephen R. 1996. Microcosm experiments have limited relevance for community and ecosystem ecology. Ecology 77 (3) : 677-690.

Carpenter, S.R. 2000. Alternate states of ecosystems. Evidence and its implications for environmental decisions. In, M.C.Press, N.Huntley and S. Levin. (eds). Ecology: Achievement and Challenge, Blackwell, London.

Carpenter, S.R., Brock, W.A., Hanson, P.C., 1999. Ecological and social dynamics in simple models of ecosystem management. Conservation Ecology 3(2), 4. URL: http://www.consecol.org/vol3/iss2/art4

Scheffer, M., S.H. Hopsper, M-L. Meijer, B.Moss and E. Jeppesen. 1993. Alternative equilibria in shallow lakes. Trends in Ecol. & Evol. 8 (8): 275- 279.

Sinclair, A.R.E. , P.D. Olsen, and T.D. Redhead. Can predators regulate small mammal populations? Evidence from mouse outbreaks in Australia. Oikos 59: 382-392.

Sousa, W.P. and J.H. Connell. 1985. Further comments on the evidence for multiple stable points in natural communities. American Naturalist 125, 612-615.

      Reflections

      How it began: Reflections Part 2

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      Let me start with the origins of the first paper the students discovered, that on Resilience (Holling, C.S. 1973. Resilience and stability of ecological systems. ARES 4: 1-23.). Since that paper really opened my eyes to the ecosystem scale, I’ll then spend a bit more time referring to it, and how it originated.

      That paper came from a series of earlier experimental studies and papers analyzing a particular process, predation. The goal was to see how far one could go by being precise, realistic, general and integrative. These are goals that normally are dealt with independently in at least partial isolation from each other in order to achieve useful and useable simplification. (The key, classic references are (Holling 1965 & Holling 1966).

      Those studies did well, and eventually led to a way to classify categories of predation into four types of functional response (how much they eat) and three types of numerical responses (how many there are). The categories and resulting simplified models seemed to apply to everything from bacteria foraging for food to submarines hunting ships! But none of that was ecosystem research. It was all traditionally experimental and analytical; but at least it was synthetic, non-linear and had great generality.

      The key conclusion relevant for ecosystem science, was that it was possible to develop small suites of well tested realistic models and define a small number of general classes of responses for key population processes. The marvelous dean of ecology at that time, Bob MacArthur, wrote me at the time of the publication of the first Functional Response paper, arguing the work was too detailed and complex to be very useful for theory in ecology. That is true in a narrow sense, but he did not know that the paper was a planned step in a process that finally did yield less complex equations, but ones more complex than was traditional for the theory of the time. The “somewhat more complex”, however, led to a world of differences in the behavior of systems, because of the non-linearities in the processes. And, most important, the equations representing the various classes of processes, were sufficiently realistic, something I thought then, and now know, was a central need for further development of theory for ecosystems. That was the first hint of the “Rule of Hand” – not too simple, not too complex- that was highlighted in the conclusions to the book Panarchy (Gunderson and Holling, 2002). That is, all that is needed is a handful of key variables. The classic “disc equation experiments” and paper launched the whole sequence that led, finally, to simpler mathematical representations that captured the essential reality that I thought was needed (Holling, 1959).

      Continue reading →

      Reflections

      Introduction: Reflections Part 1

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      In May 2003, three graduate students from a mid-west university in the US, discovered that three of my papers were among the 13 most cited papers/books by authors in the journal Ecosystems 1998-2000. They asked me to comment on the papers- their origin, relevance and directions the field of ecosystem ecology might be headed.

        Holling, C.S. 1973. Resilience and stability of ecological systems. Ann. Rev. of Ecol. and Syst. 4: 1-23.
        Holling, C.S. 1986. The resilience of terrestrial ecosystems; local surprise and global change. In: W.C. Clark and R.E. Munn (eds.). Sustainable Development of the Biosphere. Cambridge University Press, Cambridge, U.K. Chap. 10: 292-317.
        Holling, C.S. 1992. Cross-scale morphology, geometry and dynamics of ecosystems. Ecological Monographs. 62(4):447-502.

      Each of those papers was a synthesis paper about ecosystems and their components that was the culmination of several years of earlier work. And, in fact, there were two additional synthesis papers, one of which preceded these three, but with a focus on behavioral ecology, not ecosystems. And one of which followed them, and was the first step in integrating ecological and social systems, again not just ecosystems. Overall, the five papers represent a progression from experimental work seeking for high certainty about simple systems, to systems work of high uncertainty about complex systems. In the latter situation, the unknown is inevitable, methods need to accept that reality and the rules for simplifying are not traditional ones. In a way, the work progressed from a focus on understanding more and more about less and less, to learning less and less about more and more!

      The earliest paper was:

      Holling, C.S. 1965. The functional response of predators to prey density and its role in mimicry and population regulation. Mem. Ent. Soc. Can. 45: 1-60

      It has been heavily referenced over the 41 years since it was published.

      The other is much more recent:

      Holling, C.S., Lance H. Gunderson and Garry D. Peterson. 2002. Sustainability and Panarchies. In: Gunderson, Lance H. and C.S. Holling (eds), 2002. Panarchy: Understanding Transformations in Human and Ecological Systems. Island Press. Chapter 3, 63-102.

      This last paper presents all I think I have learned over the years about the structure, function and history of ecosystems, social systems and the way they survive, evolve and succeed or fail. I have no idea how well that paper will affect the community of science or practice, but I am very happy with its content, although not with its style of writing.

      I am writing now to give a personal view of what I believe I have discovered – my personal, explorers’ guide of intellectual journeys that truly excited me when, as it seemed to me, wondrous new lands periodically suddenly emerged that no one had seen or remarked on before. For scientists, those are the times when a tsunami wave of excitement triggers a passion for discovery.

      This series Reflections will continue over the next few weeks.

      Reflections

      A Journey of Discovery: Reflections

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      As I write this, it is mid September 2006. I am writing in a sun-drenched room at our cottage in Ontario, thinking of the unrolling events of the last few months. It is a surprising time with some light events and some very dark ones.

      For me, the light, bright events, come from the birth of twin grandsons, living on Vancouver Island. They turn my mind from the present dark colors of international and US politics and governance, and add balance in the promise youth opens for the future. And, on the same positive note, I have also met a large group of new and old friends, on two recent trips- one trip to South Africa and one to Montreal, where we met bubbling communities of people, young and old, experimenting in new options for interracial design and novel social and scientific experimentation. The collapse of apartheid in South Africa has slowly opened huge potential and hope. This is just the opposite of the public mood I see in the United States.

      It stunned me to discover that major new centers, truly international in character, have emerged for resilience studies and policies- for the world’s coral reefs in Australia, for climate change in the UK and for regional and global social and ecological systems in Sweden. And all this is apparently influenced deeply by the discoveries and experiments presented by my own work over the last decades. All that says the world is exuberantly healthy and productive. But there are other, very dark events.

      In the United States, the mood and currents of thought and politics perceived among good friends at our main home in the small fishing village of Cedar Key, on the Gulf of Mexico is depressing. They are good friends, but now deeply pessimistic ones. The political situation in the United States is quite simply ugly. It is a time when the power of the state has achieved a rigidity unseen since the triumphs of the falling of the Berlin Wall. Politicians have reacted to extreme disturbances, like the appalling terrorist attacks of 9/11, with a powerful military response, a blind view of history and cultures, and a greedy desire for narrow benefit. Global economic expansion and dependence on peaking oil supplies, particularly in the Middle East, lock geopolitics into a self-destructive state, from which transformation is extraordinarily difficult.

      It is the classically destructive phase of the mature part of an adaptive cycle. It is also potentially creative, because opportunities for innovative experiments and novel enterprises start to open at such times. It is a time of potentially creative destruction. And a recent mid term election in the United States in November 2006 at least hints at a shift into a renewal that requires deep changes nationally and internationally. Democracy is indeed a huge invention that stimulates assessment of a society and institutions whose leaders have become rigid and myopic. Democracy, at times, can trigger its renewal.

      That is what I want to end up discussing here. But I want to get to that point by musing about the personal contributions I’ve made, my colleagues have made and our colleagues in science have at times questioned, at times supported. That is the true skepticism of science unfolding. At times it is turned over by truly novel discoveries- a kind of Kuhnian revolution of thought and approach. I think that transformation has happened, and I will describe my personal journey in science that, with other such journeys, contributed to the transformation.

      These reflections will be presented in a series of posts over the next few weeks.

      Ideas

      Thoughts on Simple and Complex Causes of Lumps

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      Reply of Buzz Holling to a message from Marten Scheffer:

      I did like your models (Scheffer and van Nes) that show that lumps of species emerge naturally from competition, augmented with predation (see post on self-organization of ecosystem lumpiness). I like also that the simulated lumpy distributions you demonstrated are very evolutionarily robust. That is what has been shown in so much of the multi species community data and experimental manipulations that have been published by various authors.

      But let me offer some other empirical evidence that suggest something else may ALSO be operating. Then I’ll end with some words on the philosophy of science!

      First, in one of my tests in my “lumpy paper” I asked if herbivores and carnivores had different lump patterns among the mammals in each of the communities of the boreal prairies and boreal forests (Holling, C.S. 1992. Cross-scale morphology, geometry and dynamics of ecosystems. Ecological Monographs. 62(4):447-502). In my mind, this was a crude, crude test of the role of competition and predation in forming body mass lump patterns. Herbivores and carnivores turned out to have the same lump patterns, suggesting that something more than competition must be causing the similarity.

      Second, I asked if mammals compared to birds in the same communities (boreal forests and boreal prairies) had different or similar lump patterns. It turned out that the patterns differed when compared by untransformed masses, but were very similar when the bird masses were expressed as Mass to the third power and mammal masses as untransformed mass. Birds, it was argued, therefore must see their world in three dimensions, and mammals in one dimension. Some behavioral data seems to conform to that conclusion. But note the data and tests only applied to two systems, and clearly more ecosystems need to be compared. Adding bats, mammals that fly, offers a set of additional tests that would be very valuable. Data, however, are tough to get. Such tests need data on masses of birds, non flying mammals and bats from the same ecosystem communities.

      Third , one of my colleagues, Jan Sendzimir, asked if body mass lump patterns among birds or mammals in different ecological communities around the world were more similar if they came from the same type of community. In essence, for example, are lump patterns in boreal forest communities in Europe and North America more similar to each other than to patterns among totally different communities? The answer was that they were more similar to each other, even when comparing different continents. That suggests that patterns on landscapes over a wide range of scales is central in defining lumpy patterns.

      Fourth, Craig Allen has discovered a remarkably consistent pattern that the masses of endangered and invasive species of birds and mammals, exist disproportionately on the edge of the body mass lumps. He has shown that for at least five ecosystems around the world. It is as if crisis and opportunity are shared there, where, I suppose, the resources available at those scale breaks were poor. As scales increase, points are reached where the available resources suddenly change. (Think of viewing a high resolution satellite image of a landscape at different powers of ten from meters to tens of thousands of kms). Initially you see leaves and branches , and suddenly a scale is reached where you see trees and vegetation types- and on and on. What you see, I thought, is what you can , potentially eat or , better, utilize).

      Finally, I am delighted with your emphasis on self organization. I have long felt that self organization , integrated with Darwinian evolution, has huge explanatory power, and the combination answers many of the existing puzzles of evolution.

      But I also felt that the self organizing patterns were ones that involved not just interactions among biological species of similar trophic relations (like your competitors) but also interactions across trophic categories , and even interactions among organisms and abiotic features. Maybe, I thought, that is why anoxid, pre Cambrian organisms evolved the ability to use the dreadful poison of oxygen to explosively release a new burst of evolution. I imagined oxygen breathing species evolving in water where diffusion of oxygen was slow enough that local concentrations could be built up by organisms with facultative oxygen metabolism. Suddenly anoxic metabolism there becomes a penalty and oxygen metabolism a huge benefit. From those local concentrations, a world with oxygen could bloom.

      There are two very distinct ways to suggest and test such ideas. One is via models, where very specific causes are designed and tested as a deductive excercise. That is what your paper does, in a significant expansion of that tradition. The other comes from a larger scale of testing of whole assemblies of potentially interacting variables . The conceptual ideas might come from earlier models. That was what my lump paper attempted as a test of a set of conclusions comparing earlier simulation models of ecosystems. Each of about a dozen models /studies indicated a small number of variables (less than five) at distinctly different scales explained those systems changes in variables. Hence I suggested, real data covering broad scales should show a small number of lumpy clusters. Body mass was chosen as a test because that is the data that are available. The data indeed showed the lumpy structure.

      Now what is needed is slightly expanded deductive models with up to five variables/processes, much like those that Steve Carpenter and Buz Brock have structured for economic-ecological mini systems (see papers in Ecology and Society on lakes and fishing). And much more testing is needed with large scale assemblies of variables as I attempted in my lump paper. That is what Craig Allen has been doing, with collaborators, for a number of systems- biological, ecological , economic and social,. A book is about to be published, I believe. He might have some revealing comments that we all could learn from.

      C.S.Holling