Why publish in high-priced, for-profit journals?

February 28, 2007 Allyson Quinlan 1 Comment

An article titled The Economics of Ecology Journals by Bergstrom & Bergstrom (Front Ecol Environ 2006; 4(9):488-495) was recently brought to my attention. The authors analyzed price data and citations from 92 regularly published primary research ecology journals and, in a nutshell, determined that for-profit journals are approximately five times as expensive as their non-profit counterparts. Even when page charges, common with both non-profit and jointly published journals, are factored in, total revenue is approximately three times higher for the for-profit journals. This price difference exists despite the fact that the higher-priced journals do not have corresponding higher quality, as measured by citation rates.

Bergstrom & Bergstrom go on to note the trends of increasing library expenditures on serials (doubling since 1986) as well as the increased proportion of expensive for-profit publications. This trend is especially puzzling given the relatively recent transition to online access, which has come at a generally low cost to publishers. The authors next ask why these price differences persist and then present their answer in game theory terms. Basically, scientists will publish where other top-scientists publish and a shift to lower-cost, non-profit journals (with greater distribution and higher citation rates!) will require a coordinated shift within the scholarly community. They conclude:

Finally, from the broader community perspective, the scientific community as a whole would benefit if over-priced journals were displaced by journals priced at or near average cost. The fraction of library budgets that is currently going to the shareholders of large commercial publishers could instead by used to provide services of genuine value to the academic community. Professional societies and university presses could help by expanding their existing journals or starting new ones. Individual scholars could advance this process in many ways: by contributing their time and efforts to the expansion of these non-profit journals, by refusing to do unpaid referee work for overpriced commercial publications, by self-archiving their papers in preprint archives or institutional repositories, and by favoring reasonably priced journals with their submissions.

As a side, it is interesting to note that only three of the 107 ecology journals listed in the 2005 Journal Citation Reports were open-access journals, with all of their content freely available on the web. This category of course, includes Ecology & Society (www.ecologyandsociety) which was highlighted in another article recently by Kueffer et al. (Towards a Publication Culture in Transdisciplinary Research, GAIA 16/1 (2007):22-26) for its contribution to transdisciplinary research publishing.

Ecosystem services, Greenlash

A surprising decline of pollination services in USA

February 28, 2007 Garry Peterson 9 Comments

The Feb 27 the New York Times article Honeybees Vanish, Leaving Crops and Keepers in Peril describes the recent poorly understood decline in US honeybee populations. While the causes of this decline are not understood, such a decline has been expected by scientists. For example, last year’s US National Research Council report on the Status of Pollinators in North America warned about the many threats facing pollinators and bees in particular.

The introduced European honeybees are the major source of pollination for many crops (See graph). These bees have displaced populations of native bees, reducing the diversity of pollinators.

The honeybee decline seems to match Holling’s pathology of natural resource management. Pollination services are increasingly provided by a single highly managed population. In the US many beekeepers make more money by providing pollination services than making honey. This population has become increasingly vulnerable to disturbance, while the intensive monocultures of industrial agriculture has become dependent on artificial pollination. The NYTimes article describes the situation:

Once the domain of hobbyists with a handful of backyard hives, beekeeping has become increasingly commercial and consolidated. Over the last two decades, the number of beehives, now estimated by the Agriculture Department to be 2.4 million, has dropped by a quarter and the number of beekeepers by half.

Pressure has been building on the bee industry. The costs to maintain hives, also known as colonies, are rising along with the strain on bees of being bred to pollinate rather than just make honey. And beekeepers are losing out to suburban sprawl in their quest for spots where bees can forage for nectar to stay healthy and strong during the pollination season.

“There are less beekeepers, less bees, yet more crops to pollinate,” Mr. Browning said. “While this sounds sweet for the bee business, with so much added loss and expense due to disease, pests and higher equipment costs, profitability is actually falling.”

…

A Cornell University study has estimated that honeybees annually pollinate more than $14 billion worth of seeds and crops in the United States, mostly fruits, vegetables and nuts. “Every third bite we consume in our diet is dependent on a honeybee to pollinate that food,” said Zac Browning, vice president of the American Beekeeping Federation.

The bee losses are ranging from 30 to 60 percent on the West Coast, with some beekeepers on the East Coast and in Texas reporting losses of more than 70 percent; beekeepers consider a loss of up to 20 percent in the offseason to be normal.

…

Beekeepers now earn many times more renting their bees out to pollinate crops than in producing honey. Two years ago a lack of bees for the California almond crop caused bee rental prices to jump, drawing beekeepers from the East Coast.

This year the price for a bee colony is about $135, up from $55 in 2004, said Joe Traynor, a bee broker in Bakersfield, Calif.

A typical bee colony ranges from 15,000 to 30,000 bees. But beekeepers’ costs are also on the rise. In the past decade, fuel, equipment and even bee boxes have doubled and tripled in price.

The cost to control mites has also risen, along with the price of queen bees, which cost about $15 each, up from $10 three years ago.

To give bees energy while they are pollinating, beekeepers now feed them protein supplements and a liquid mix of sucrose and corn syrup carried in tanker-sized trucks costing $12,000 per load. Over all, Mr. Bradshaw figures, in recent years he has spent $145 a hive annually to keep his bees alive, for a profit of about $11 a hive, not including labor expenses. The last three years his net income has averaged $30,000 a year from his 4,200 bee colonies, he said.

Ecological Management, Reflections

Ecosystem Reality – Modelling: Reflections Pt 5

February 27, 2007 Buzz Holling 2 Comments

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.

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

February 26, 2007 Buzz Holling 2 Comments

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 ).

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.

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. 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.

Adaptation, General

Latour rethinks the social construction of science

February 25, 2007 Garry Peterson 3 Comments

Bruno Latour, an eminent figure in social studies of science and science policy, writes Why Has Critique Run out of Steam? From Matters of Fact to Matters of Concern in Critical Inquiry 2004 30(2).

Wars. So many wars. Wars outside and wars inside. Cultural wars, science wars, and wars against terrorists. Wars against poverty and wars against the poor. Wars against ignorance and wars out of ignorance. My question is simple: Should we be at war, too, we, the scholars, the intellectuals? Is it really our duty to add fresh ruins to fields of ruins? Is it really the task of the humanities to add deconstruction to destructions? More iconoclasm to iconoclasm? What has become of critical spirit? Has it not run out of steam?

Quite simply, my worry is that it might not be aligned to the right target. To remain in the metaphorical atmosphere of the time, military experts constantly revise their strategic doctrines, their contingency plans, the size, direction, technology of their projectiles, of their smart bombs, of their missiles: I wonder why we, we alone, would be saved from those sort of revisions. It does not seem to me that we have been as quick, in academe, to prepare ourselves for new threats, new dangers, new tasks, new targets. Are we not like those mechanical toys that endlessly continue to do the same gesture when everything else has changed around them? Would it not be rather terrible if we were still training young kids–yes, young recruits, young cadets–for wars that cannot be thought, for fighting enemies long gone, for conquering territories that no longer exist and leaving them ill-equipped in the face of threats we have not anticipated, for which we are so thoroughly disarmed? Generals have always been accused of being on the ready one war late–especially French generals, especially these days; what would be so surprising, after all, if intellectuals were also one war late, one critique late–especially French intellectuals, especially now? It has been a long time, after all, since intellectuals have stopped being in the vanguard of things to come. Indeed, it has been a long time now since the very notion of the avant-garde–the proletariat, the artistic–has passed away, has been pushed aside by other forces, moved to the rear guard, or may be lumped with the baggage train. We are still able to go through the motions of a critical avant-garde, but is not the spirit gone?

In this most depressing of times, these are some of the issues I want to press not to depress the reader but to press ahead, to redirect our meager capacities as fast as possible. To prove my point, I have not exactly facts rather tiny cues, nagging doubts, disturbing telltale signs. What has become of critique, I wonder, when the New York Times runs the following story?

“Most scientists believe that [global] warming is caused largely by manmade pollutants that require strict regulation. Mr. Luntz [a lobbyist for the Republicans] seems to acknowledge as much when he says that “the scientific debate is closing against us.” His advice, however, is to emphasize that the evidence is not complete. “Should the public come to believe that the scientific issues are settled,” he writes, “their views about global warming will change accordingly. Therefore, you need to continue to make the lack of scientific certainty a primary issue.”

Fancy that? An artificially maintained scientific controversy to favor a “brown backlash” as Paul Ehrlich would say. Do you see why I am worried? I myself have spent sometimes in the past trying to show the “lack of scientific certainty” inherent in the construction of facts. I too made it a “primary issue.” But I did not exactly aim at fooling the public by obscuring the certainty of a closed argument–or did I? After all, I have been accused of just that sin. Still, I’d like to believe that, on the contrary, I intended to emancipate the public from a prematurely naturalized objectified fact. Was I foolishly mistaken? Have things changed so fast?

In which case the danger would no longer be coming from an excessive confidence in ideological arguments posturing as matters of fact–as we have learned to combat so efficiently in the past–but from an excessive distrust of good matters of fact disguised as bad ideological biases! While we spent years trying to detect the real prejudices hidden behind the appearance of objective statements, do we have now to reveal the real objective and incontrovertible facts hidden behind the illusion of prejudices? And yet entire Ph.D programs are still running to make sure that good American kids are learning the hard way that facts are made up, that there is no such thing as natural, unmediated, unbiased access to truth, that we are always the prisoner of language, that we always speak from one standpoint, and so on, while dangerous extremists are using the very same argument of social construction to destroy hard-won evidence that could save our lives. Was I wrong to participate in the invention of this field known as science studies? Is it enough to say that we did not really mean what we meant? Why does it burn my tongue to say that global warming is a fact whether you like it or not? Why can’t I simply say that the argument is closed for good?

…

Reflections, Regime Shifts

Resilience: Reflections part 3

February 24, 2007 Buzz Holling 2 Comments

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:

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.
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.

Ideas, Networks

Building Interdisciplinarity

February 23, 2007 Garry Peterson Leave a comment

An article in Harvard Magazine (January-February 2007) describes The Janelia Experiment, an new biomedical research facility designed to foster great inter-discplinary research. Fostering interdisciplinary research is topic the Stockholm Resilience Center is grapling with as it organizes itself (but without the problems a $16 billion endowment brings).

Great scientific research organizations, of the rare variety that produce multiple Nobel Prize-caliber breakthroughs, share common traits that can be imitated. This is the precept behind the creation of Janelia Farm, the new biological-research campus of the Howard Hughes Medical Institute (HHMI). In November, scientists from the Harvard Stem Cell Institute visited the new campus, where everything from architecture to organization to social culture has been planned to nurture an optimal environment for scientific discovery. What the visitors saw may offer ideas for Harvard, which is planning an ambitious science-research campus in Allston and working to ensure that the organizational structure of the sciences, as well as the architecture of new buildings, will promote a culture of interdisciplinary collaboration.
…
Such places did exist in the past. Both Bell Labs and the Medical Research Council Laboratory of Molecular Biology (LMB) in Cambridge, England, took a long-term approach to problem-solving, one in the physical sciences, the other in biology. Both produced results that were “offscale,” Rubin says, “even compared to the best private institutions.” Both were used as models for Janelia Farm.

Common to Bell Labs and the LMB were small research groups, leaders who were active bench scientists, internal funding for research, outstanding shared support and infrastructure, limited tenure, and a culture that rewarded collegiality and cooperation.

Sociological research, Rubin says, has shown that humans don’t have meaningful interactions with more than about 20 people. “If you want to have interactions between groups and every group is 20 people, well, it’s just not going to happen,” says Rubin. “It’s fundamental human nature.” Thus groups at Janelia Farm, with its goal of increasing interdisciplinary cooperation between labs, are limited to no more than six members.
…
Yet even if the opportunities to create an organizational structure that promotes interdisciplinary collaboration are somewhat limited within the university environment, there is no such limitation on design and architecture that promotes collaboration. In this sense, Janelia Farm is also a model that blends lessons of the past with the most contemporary thinking in lab design. There are spaces that promote interaction: a cafeteria with good, inexpensive food, and a pub that serves coffee and tea during the day and cheeseburgers and beer after work. Forcing people out of their normal environments is a good thing, says Rubin. The LMB had a canteen and the culture there, he says, was that you were free to sit down with people you didn’t know. (A 2004 study by the National Academy of Sciences asked research administrators what they would cut last in a hypothetical budget crunch. They overwhelmingly named their cafeteria.)

Reflections

How it began: Reflections Part 2

February 22, 2007 Buzz Holling 1 Comment

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).

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General, Reorganization

Water Hyacinth Re-invades Lake Victoria

February 22, 2007 Garry Peterson 18 Comments

From NASA’s Earth Observatory, images showing the speed with which the rapidly spreading S American water hyacinth has reinvaded Lake Victoria. Water hyacinth was introduced to Africa over a century ago, but it did not become a problem in Lake Victoria until the early 1990s. It covered substantial areas of the coastline, particularly in Uganda, blocking waterways, disrupting hydropower, and decreasing the profitability of fishing. Hyacinth also provided refugia for some species from the introduced Nile Perch. It largely disappeared from the Lake in the late 90s, perhaps, but not clearly, due to the introduction of a weevil used for biological control. It experienced a resurgence in the early 2000s. Now following a wet year, which increased nutrient runoff into the lake, water hyancinth has returned.

water hyacinth

These images show the Winam Gulf, in the northeast corner of Lake Victoria in Kenya. The gulf was the most severely affected region during the first hyacinth outbreak in 1998, with as much as 17,231 hectares (67 square miles) of the plant growing on its surface. By 2000, the area covered by water hyacinth was down to about 500 hectares (2 square miles), and in December 2005, when the right image was taken, the lake appeared to be clear. In November and December 2006, however, unusually heavy rains flooded the rivers that feed into the Winam Gulf. The rain and floods raised water levels on the lake and swept agricultural run-off and nutrient-rich sediment into the water. As a result, the Winam Gulf was brown when the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite took the top left photo-like image on December 18, 2006. Vegetation around the lake was dramatically greener due to the rains.

The influx of fertilizer and sediments not only turned the water brown, but it also fed a fresh outbreak of water hyacinth. Bright green plants cover much of the Winam Gulf in the top left image. Though other plants such as algae may be contributing, water hyacinth is almost certainly one component of the soupy mass. As the photo shows, water hyacinth was growing along the shoreline, particularly in Kisumu Bay and Nyakach Bay. A comparison between December 2005 and December 2006 shows that Kisumu Bay was entirely covered by water hyacinth in 2006, and the shoreline of Nyakach Bay also appeared to change shape as the plant grew out from the shore.

The photo was taken on December 17, 2006, looking north across Kisumu Bay. The photographer stands on the shoreline and should be looking out over water, but only a field of green water hyacinth can be seen. The photo illustrates the problems the plant poses to the lake. The mat of vegetation is so thick that fishermen cannot launch their boats or bring fish to market on the shore. Sunlight does not filter through the plants, so native plants in the lake don’t get the light they need. The die-off of native plants affects fish and other aquatic animals. Water hyacinth clogs irrigation canals and pipes used to draw water from the lake for cities and villages on its shore. The plants impede water flow, creating abundant habitat for disease-carrying insects like mosquitoes. Water hyacinth can also sap oxygen from the water until it creates a ”dead zone” where plants and animals can no longer survive. Typically, only aggressive measures can control the fast-growing plant.

Reflections

Introduction: Reflections Part 1

February 21, 2007 Buzz Holling 1 Comment

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.

Resilience and stability of ecological systems

Sustainable Development of the Biosphere

Cross-scale morphology, geometry and dynamics of ecosystems

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.

Resilience Science