Systems Paleoecology – Allee Effects I

Tags

Allee effect, extinction, paleoecology, stochastic extinction

WHAT IS ECOLOGICAL STABILITY? In 2019 I posed this question informally to colleagues, using Twitter, a professional workshop that I lead, and a conference. Respondents on Twitter consisted mostly of ecological scientists, but the workshop included paleontologists, biologists, physicists, applied mathematicians, and an array of social scientists, including sociologists, anthropologists, economists, archaeologists, political scientists, historians and others. And this happened…

Previous posts in this series

1. Welcome Back Video
2. Introduction
3. Malthusian Populations
4. Logistic Populations
5. Logistic Populations II
6. Deviations from Equilibrium
7. r, R, and Bifurcations
8. Quasiperiodicity and Chaos
9. Chaotic Stability

10. Environmental Variation: Expectations and Averages
11. Nonlinearity and Inequality
12. States, Transitions and Extinction
13. Regime Shifts I
14. Regime Shifts II

In the previous post, we discussed the dramatic decline of the Atlantic cod (Gadus morhua) off Newfoundland over the past 60 years. I left us with the question of why, given the very limited catch sizes since the 1990’s, there was little evidence of population recovery (at least up until 2005). An Allee effect is a likely explanation for the failure of the population to recover during that extended period of reduced fishing pressure.

Beginning around 1994, the population may have become limited by an Allee phenomenon, or more appropriately mechanism, where a population’s size is limited far below the presumed carrying capacity, or observed maximum population size, because of reduced population size itself. Analogous to carrying capacity, where an upper limit is set on population growth rate by the effects of a relatively large population size, an Allee effect is an upper limit set by relatively small population size. Intuitive examples are easy to find, e.g. (1) species that require sufficient numbers for successful defense against predators will be increasingly limited by predation at low population size; (2) species for which habitat engineering by a sufficient number of individuals is necessary for offspring success; (3) species that depend on a minimum number of participants for the formation of successful mating assemblages. G. morhua, in which individual fecundity increases with age and body size (to a limit) (Fudge and Rose, 2008), is known to form, or have formed, large pelagic assemblages during spawning. Allee effects, therefore, describe situations where individual fitness depends on the presence of conspecifics, and is positively correlated with population size.

One vulnerability of populations subject to Allee effects is that small population size becomes an inescapable trap, with the likelihood of extinction increasing as population size declines. The reasons for this are twofold. First, if growth rates decline to zero or even become negative below an Allee threshold, then the state of zero population size becomes a stable state and extinction is assured. If you recall, our earlier models of population growth considered X= 0 (extinction) to be an unstable steady state; unstable because the addition of reproducing individuals to the population would result in divergence away from the zero state —population growth. Second, even if growth rate never becomes negative below the Allee threshold, a sufficiently large or sustained decline of population size increases the probability of extinction due to random events, a phenomenon termed stochastic extinction. Stochastic extinction, the probability of which could increase with deteriorating environmental conditions, is of interest to anyone studying extinction, including paleontologists, and will be discussed in a later section. Here, however, we will first explore several simple models of Allee effects.

Models of Allee effects

In the logistic model (Eq. 1 here), mortality rate increases as population size, X, approaches carrying capacity K, and population growth rate subsequently declines. The logistic model has two alternative steady states, X=K and X= 0, the latter of which is unstable as discussed above. The extinct state is a stable attractor, however, in the presence of an Allee effect. There are several simple models that demonstrate the effect, but to appreciate them, and the Allee effect itself, let us first examine the relationship between population size and growth rate under the logistic model. If we plot growth rate (dX/dt) against population size in the logistic model (Fig. 1), we see that the rate increases steadily at small population size, reaches a maximum when population size is half of the carrying capacity —X(t) =K/2— and declines steadily thereafter, reaching zero at carrying capacity. This value can be arrived at analytically because what we are visualizing is the rate of change of growth rate itself, technically the second derivative of the logistic growth equation. If we expand the logistic growth rate equation


and take the derivative, we derive the acceleration (or deceleration) of the rate of change of population size as a function of population size itself.

Setting d²X/dt equal to zero —the point at which growth rate is neither accelerating nor decelerating— we get the maximum that is illustrated in Fig. 1.


The important thing to note here is that growth rate is always positive when 0<X(t)<K, that is, when population size lies between zero and the carrying capacity.

Fig. 1: The relationship between population growth rate and population size under a logistic model. In this example carrying capacity K=100.

There are several ways in which an Allee effect can be modelled in a logistically growing population. For example, if the Allee threshold is represented as a specific population size A, then the effect can be incorporated into the logistic formula as

(Lewis and Kareiva, 1993; Boukal and Berec, 2002). The first term on the RHS of the equation is the logistic function, where growth declines to zero as X approaches K. The second term introduces the threshold, A, with growth rate declining if X < A, and increasing when X > A. Here, the effect is treated as the difference between population size and the threshold, taken as a fraction of carrying capacity, or maximum population size. Note that if A=0 —there is no Allee effect— the model reduces to the logistic growth model. A more nuanced model, where A must be greater than zero —an Allee effect always exists— treats the Allee threshold as equivalent yet opposite to K, representing a lower bound on growth rate (Courchamp et al., 1999).

If A=1 —in which a population comprising a single individual is compromised under all circumstances— then the strength of the Allee effect depends on the size of the population. In both models, growth rate becomes negative below the threshold A, effectively dooming the population to extinction (Fig. 2). This condition is often termed a “strong” Allee effect.

Negative growth rates, a feature that is common to many models of the Allee effect, can be somewhat problematic from a conceptual viewpoint because of their determinism. We’ll pick this point up in the next post, and also discuss why paleontologists might care about both Allee effects, and model determinism.

Fig. 2: Two models of strong Allee effects illustrates as plots of population growth rate vs. population size. K=100. Red shows the first model where growth rate is relative to the Allee threshold A as a function of K. Blue shows the second model where growth rate is relative to the threshold A itself.

Vocabulary
Allee effect — A positive correlation between individual fitness, or population growth rate, and population size. This means that fitness and/or growth rates decrease with declining population size.
Second derivative — The derivative of a function’s derivative (the first derivative), thus the acceleration (deceleration) of a rate. E.g. the first derivative of a body in motion, described by position and time, is velocity or speed. The second derivative is acceleration, or the rate at which the speed is changing.
Stochastic extinction — A relationship between the probability of a population’s extinction, and population size and/or environmental variability. In general, the risk of extinction increases due to random fluctuations of either factor.
Strong Allee effect — Population growth rate becomes negative below some threshold of population size.

References
Boukal, D. S. and Berec, L. (2002). Single-species models of the Allee effect: extinction boundaries, sex ratios and mate encounters. Journal of Theoretical Biology, 218(3):375–394.
Courchamp, F., Clutton-Brock, T., and Grenfell, B. (1999). Inverse density dependence and the Allee effect. Trends in Ecology & Evolution, 14(10):405–410
Fudge, S. B. and Rose, G. A. (2008). Changes in fecundity in a stressed population: Northern cod (Gadus morhua) off Newfoundland. Resiliency of gadid stocks to fishing and climate change. Alaska Sea Grant, University of Alaska Fairbanks.
Lewis, M. and Kareiva, P. (1993). Allee dynamics and the spread of invading organisms.Theoretical Population Biology, 43(2):141–158

A Welcome Back Video!

Tags

COVID-19, extinction, food webs, mathematical model, Network theory, Permian-Triassic extinction, social distancing, virtual teaching

Well, it certainly has been a very long time since my last post. Like many of you, however, I find myself impacted by the COVID-19 pandemic. My short story is that I stopped my commute to work at the California Academy of Sciences more than two weeks ago because, let’s just say that I would probably not fare too well if I became infected. Then on Thursday March 12th the decision was made to close the Academy to the public, we closed to most staff at 8 am on Monday, March 16th, and by that afternoon counties in the San Francisco Bay Area had announced shelter-in-place orders.

As countries across the globe move toward the circumstances in which China found itself by early January, and take more or less appropriate and necessary actions, the disruption to our lives and societies is unprecedented for many (NOW, however, is a great time to reflect on the hardships that have been inflicted globally in recent years on refugees and immigrants). Myself and many of my colleagues have spent hours (online) this week brainstorming ideas of how to help. We are scientists, and although some of us work on crises of various sorts, we are not all biomedical researchers or epidemiologists. Nevertheless, there has been a veritable explosion of virtual offerings intended to help the teachers, professors, kids and parents who are struggling to cope with cancelled classes, closed schools, and prematurely terminated school years. I think that I can contribute here in a small way. Over the next few weeks I will use this blog to roll out a primer that I’ve been working on. It is the basis for a book, but right now I would rather just give it away. I will discuss it in more detail in an upcoming post. In the meanwhile, however, here is a new video from the Academy highlighting some of our ongoing work. I hope that you enjoy it. And please everyone, be safe, be civic, be thankful for all the amazing health care workers around the world, and be anti-social.

Pyron’s Puzzling Post Piece

Tags

Alexander Pyron, Conservation, ecology, environment, evolution, extinction, science

(Peter Roopnarine)

Alexander Pyron, a professor of biology at George Washington University, recently wrote an inflammatory op-ed for the Washington Post, entitled “We don’t need to save endangered species. Extinction is part of evolution.” The post outraged many, among them an awful lot of scientists. Needless to say, the piece is a seriously misguided bit of poor reasoning and inaccurate science, particularly with regards to extinction. Myself and colleague Luiz Rocha, also at the California Academy of Sciences, wrote our own response, published several days ago in bioGraphic. Regardless of your opinion on species conservation, Pyron’s article cannot be used as the basis for sound argument, because it is a collection of fundamentally flawed arguments. You can read our own reasoning here: Betting on Conservation.

The image, by the way, shows the fossilized burrows of tiny marine snails in sediments dating to about 250 million years ago. The fossils are from a geological exposure in the mountains of Hubei, China, and is some of the earliest evidence there of the biosphere struggling back from the devastating end Permian mass extinction of 251 million years ago. There are no guarantees in the History of Life.

I’ve edited this post to add a little addendum: While I disagree strongly with Pyron’s opinions, I cannot agree with or support the personal attacks which have been leveled against him by others. The core power of rationalism and modern science is open and free discourse. I think that his science in this case is wrong, and I disagree with his moral stance, but I would not place this in the same category of, for example, charlatan climate change deniers who have alternative and exploitative agendas. So let’s keep the discussion civil.

Community Stability

Tags

dynamics, extinction, food webs, Permian-Triassic extinction, stability, theoretical ecology

A community stability “landscape”. Green depressions represent regions of stability (the basins). There are two stable communities (balls) in the basin. The one on the left is disturbed, and returns smoothly to its original position. The one on the right amplifies the displacement, either returning eventually to its original position, or possibly transitioning to another basin, or alternate state.

One of the central questions of our paper was, “How stable are ecological communities during a mass extinction?” This might seem a bit of a silly question at first glance, with the obvious answer “Not stable at all!” But that is not necessarily the case. Consider yourself standing on the deck of a leaky shop which is filling gradually with water. You know that the ship is going down, but  your situation is stable as long as the deck remains level, or at least until the water begins to lap around your knees. We often tend to think of mass extinctions as chaotic dramas, perhaps being influenced by the end Cretaceous event, 66 million years ago (mya), when a 10 kilometer asteroid collided with the Earth and much hell really did break loose. There is also a lot of talk these days about collapsing ecosystems, because we continue to warm up the planet, eat all the fish we can eat, and so on. But what would a Sixth Mass Extinction really look like? Would ecosystems collapse, or wind down slowly to shadows of their former selves? Did the citizens of a Roman city in Gaul turn out the lights one night in the 5th century CE, bid the ancient world farewell and lay out their clothes for the next morning’s Middle Ages? Or did they rather one day, in corner market conversation, question how the heck all those Germans wound up in government anyway? A little bit of both I suspect.

So getting back to our question of mass extinctions at the end of the Permian, some 252 mya, were ecosystems stable before the extinction, collapsing as species extinctions spiralled out of control, or were they whittled down to a hardy core? Did they become more sensitive to smaller insults, such as storms or droughts, or were they hardy cores? Answering these questions depends surprisingly on what you mean by “stability”. The term is used in various ways in ecology, and I’ve even been accused of using it in a rather narrow sense, in contrast to others who believe that there are many kinds of stability. I am not convinced that the latter is really the case, and even if it is, I would argue that there is only one important type of stability, and that is the likelihood that the community will persist, that is, continue to exist in pretty much the same form, under non-extreme environmental conditions. The conditions that have prevailed during the history of a stable community, including seven year droughts, megastorms, the occasional disease epidemic, etc., did not cause the community to collapse or its species to become extinct. This definition encompasses many aspects of stability. Consider again our boat, this time with no leaks. Whether it is at anchor in a calm bay, sailing steadily on smooth seas, heaving rhythmically on rolling waves, or pitching about chaotically in a storm, the most important question is, are you and the boat still afloat the next day? I therefore do not believe that there are many different kinds of community stability, but instead different aspects to the likelihood of persistence, and different ways to measure it.

In our paper we looked at one particular aspect of stability, commonly termed “local”. Let me explain why. Imagine our community is represented by a small ball, and its state is represented by its position on a landscape (Fig. 1; scientists love to imagine states as positions on an imaginary landscape). The landscape is rugged and hilly, and is shaped by the environment. If our ball is on a slope, it won’t stay there for very long, and its state will change. It is unstable. If it is located at the bottom of a basin though, then it will remain there, as long as nothing disturbs it. It is stable. If it is displaced by a small amount, remaining in the basin’s depression, then it will roll downhill and return to the bottom of the basin as soon as the displacing force is removed. Interestingly, with a little care one could also balance the ball on one of the peaks, and it will remain there, but that position is precarious and fragile. Any relatively minor force would serve to start a downhill roll. The basin is an “attractor“.

Now, there are a number of limitations to using local stability to describe the behaviours (dynamics) of which your community is capable. A perhaps obvious one is what happens as you increase the distance by which the ball is displaced. One possibility is that the community does not return to the basin of origin, but specifically what does happen to it depends on the topography of the landscape. A slightly more subtle set of questions, and the ones which we pursued, is what happens to the community between the time at which it is displaced (a little), and its return to the bottom of the basin? Is it a simple, Sisyphusean roll back down to the bottom of the basin? Does it happen quickly? What if the ball is kicked again before it’s finished rolling? These are important questions to ask when the planet is undergoing a slow, persistent environmental meltdown as it did 252 mya.

There are probably many interesting and important transient dynamics between departure and return. These can be very difficult to predict. To appreciate this, let us agree that our community really isn’t a ball at all, but is better described as a large collection of balls (species populations), many of which are connected to each other with ropes, pulleys and springs. The contraption now could even amplify a displacement, weaving about the slope, perhaps shifting to a new basin, or losing species along the way. These transient dynamics might be fairly common in real communities, and communities might in fact never really spend any time at the bottoms of basins, instead rolling about, tracing out complicated pathways in response to displacing forces, according to their system of species, ropes and springs.

So, what did our South African ecosystem do 252 mya as the planet became less and less hospitable?

Is the past a key to the future?

Tags

extinction, food webs, paleo-food web, paleontology, Permian-Triassic extinction

Time travel anyone? (BBC)

One of the main motivations for our most recent paper (available here) was to gain insight into how modern ecosystems might behave in the future as they are subjected to increasing human-driven stresses. “Global change” biology is an emerging field that seeks to understand how the biosphere will change in response to factors such as ongoing climate change, habitat loss, landscape transformation, and so forth. Much of the work in this area rightfully focuses on measuring change, working to understand how modern ecosystems work, and projecting how they might respond in the future. The effort is ongoing, and includes theoretical work, controlled experiments, and uncontrolled impacts on natural systems. A limitation of these efforts, however, is the magnitude of the changes that are available for study. For example, we can observe how species are moving in space right now in response to rising environmental temperatures, or how they are adapting (or not) to drought conditions, but we cannot observe how they will respond in the future as those stressors continue to increase in magnitude. No one realistically expects the responses to increase linearly; we fully expect nonlinear, hard-to-predict, surprises. That was the message of an earlier paper, and a focus of a lot of current work on critical ecosystem transitions. One way to address this concern, and the one that we’ve taken, is to look back into Earth’s past, to times when the planet was similarly undergoing major changes. Those were natural experiments; times when ecosystems were subjected to extreme environmental stresses. The problem there of course is that we don’t have a Tardis, and all our information has to come from evidence that has been preserved in the geological record, and our ability to interpret it. Yes, the natural experiments were performed, but as I like to say, either no one kept notes, or the notebook was chewed up by the family dog before anyone had a chance to read it.

So where does that leave us? It leaves us with an incomplete record yes, but it’s also the only record of how the biosphere has responded to truly dire circumstances. Our challenge is to take this incomplete record, and to extract from it data and ideas that are useful for forecasting how the biosphere might respond to future dire circumstances. In the case of our present study, we were able to take advantage of first-rate field paleontology, first-rate organismal paleontology, recent developments in theoretical ecology, and to combine those with our own methods for reconstructing paleo-food webs. And the main question which we were interested in was, “How would those food webs (important parts of the paleoecosystems) have responded to everyday types of disturbances, on the short-term, as the planet was busily falling apart?”

And the planet really was in trouble at the end of the Permian 252 million years ago. Siberia had opened up in one of the most magnificent episodes of volcanism in the last half billion years. Recent dating suggests the volcanism started about 300,000 years before the marine extinctions, and may have continued intermittently for another 500,000 years after. The knock-on effects probably included greenhouse warming, sulphurous atmosphere, ocean acidification and reductions of oceanic oxygen concentrations. In southern Africa, the location of the terrestrial ecosystem which we studied, the stage was set for a catastrophe of global proportions.

A new paper on the Permian-Triassic mass extinction

Tags

biodiversity, extinction, food webs, modeling, paleo-food web, paleontology, Permian-Triassic extinction, Scientific models

Dicynodon, an ancient relative of mammals, at the end of the Permian. (Marlene Hill Donnelly).

Yesterday, Ken Angielczyk and I published our most recent paper on the Permian-Triassic mass extinction (PTME) in the journal Science. In a nutshell, we examined a series of paleocommunities spanning the extinction, from the Late Permian to the Middle Triassic, and modelled the stability of their food webs. We compared the models to hypothetical alternatives, where we varied parameters such as how species are divided among guilds, or ecological “jobs”, and the numbers of interactions that species have. One of our very interesting discoveries is that the real food webs were always the most stable, or amongst the most stable of the models, even during the height of the extinction! That’s remarkable, given the devastating loss of species at the end of the Permian. Our other discovery is that the ability to remain highly stable during the extinction stemmed from the more rapid extinction of small, terrestrial vertebrate species. That’s not something we would predict given our experience with modern and ongoing extinctions, where larger vertebrate species are considered to be at greater risk. And finally, our last interesting observation is that the early recovery, the immediate aftermath during the Early Triassic, was an exception to the above. That community was not particularly stable, which seems to have been the result of the rapid evolutionary diversification of the extinction survivors, and the arrival of immigrants from neighbouring regions.

Some aspects of the paper are quite technical, and take advantage of fantastic new paleontological data and recent developments in theoretical ecology. Therefore, over the next few posts I’ll go through what we did, and how we did it, using a more “plain language” approach. In the meanwhile, the paper was covered by a number of news outlets, and here’s my favourite!

“5 things we learned from the mass extinction study that’s “the first of its kind”“, The Irish Examiner.

Upcoming lecture

Tags

extinction, food webs, modeling, paleo-food web, paleontology, Scientific models

I will be giving a lecture on Tuesday, April 28th, at Swarthmore College in the Department of Mathematics and Statistics. If you’re in the area, please stop by!

RESILIENCE AND STABILITY OF PERMO-TRIASSIC KAROO BASIN COMMUNITIES

Tags

biodiversity, extinction, food webs, modeling, paleo-food web, paleontology, simulations, trophic guild

Late Permian community dynamics

This is the second presentation that I made at the Annual Conference of the Geological Society of America in Vancouver last month. The presentation was part of a special session, “Extreme Environmental Conditions and Biotic Responses during the Permian-Triassic Boundary Crisis and Early Triassic Recovery”, co-organized my myself, Tom Algeo, Hugo Bucher and Arne Winguth. The session, spanning two days, was excellent, outstanding, and a lot of fun! I came away with the firm conviction that we are beginning to really understand the massive Permo-Triassic mass extinction, from its causes to consequences to recovery. It truly was a watershed “moment” in the history of the biosphere. The full program for both days can be found here and here. And, here is the abstract. An online copy of the presentation is available here.

RESILIENCE AND STABILITY OF PERMO-TRIASSIC KAROO BASIN COMMUNITIES: THE IMPORTANCE OF SPECIES RICHNESS AND FUNCTIONAL DIVERSITY TO ECOLOGICAL STABILITY AND ECOSYSTEM RECOVERY

ROOPNARINE, Peter, Invertebrate Zoology and Geology, California Academy of Sciences, 55 Music Concourse Dr, Golden Gate Park, San Francisco, CA 94118, proopnarine@calacademy.org and ANGIELCZYK, Kenneth D., Department of Geology, The Field Museum, 1400 South Lake Shore Drive, Chicago, IL 60605

A central question of the P/Tr extinction is the manner in which Permian ecological communities collapsed and E. Triassic ones were built. The end Permian Dicynodon Assemblage Zone (DAZ) has recently been resolved into 3 phases of the extinction spanning ~120ky, followed by the E. Triassic (Induan) Lystrosaurus Assemblage Zone (LAZ), offering an opportunity to examine the ecological dynamics of extinction and recovery in enhanced detail. We do this with 2 modelling approaches.

The first model assumes that populations exist in an energetic balance between consumption and predation. Communities are modelled as stochastic variants sampled from a space defined by species richness and functional diversity. Paleoenvironmental data from the DAZ indicate an increasingly seasonal, arid and drought-prone environment. The models were perturbed by simulated reductions of primary productivity. Results show that DAZ Phase 0 (Ph0) was a robust community resistant to low-moderate levels of perturbation with a well-defined collapse threshold. DAZ Ph1 and Ph2, however, exhibit highly variable responses and are significantly less resistant. LAZ similarly exhibits highly variable responses across minor variation of model configurations.

The second model assumes that communities are locally stable, i.e. minor perturbations are followed by asymptotic returns to equilibrium. During this return, however, communities can exhibit transient behavior during which perturbations can be greatly amplified. Amplification is likely to be important in unstable environments when the frequency of perturbations is shorter than the return time to equilibrium. Applying this model to DAZ and LAZ communities shows that the Karoo ecosystem became more limited in its responses to perturbation as the P/Tr boundary was approached, with Ph1 and Ph2 communities exhibiting very little transient behavior. LAZ in contrast exhibits increased transience.

The energetics and stability models are reconcilable in a history where the Karoo ecosystem became more ecologically stable as the extinction unfolded, yet more sensitive to cascading effects of species extinction and reductions of productivity. The Induan ecosystem was an unrecovered one, sensitive to both extinction and minor ecological disturbances.

Specimen collecting and cherry picking

Tags

biodiversity, california academy of sciences, endangered species, extinction, specimen collecting

In a recent opinion piece in Slate, Ben Minteer of Arizona State University continues to raise questions of the ethical legitimacy of collecting specimens for biological research. Minteer maintains that the risk to species, where population sizes might be small enough so that collecting represents a probabilistic extinction threat, outweighs the benefits to science and conservation. Unfortunately, Minteer is expressing an opinion, not the results of a carefully weighed and conducted analysis of data or facts. This is best highlighted by his example of the recent re-discovery of a species of New Guinea bat. Minteer states, “No scientist or conservationist today would deny the importance and value of describing a new species or confirming the return of one thought lost to extinction. But scientists also have a powerful ethical responsibility to minimize any and all adverse ecological impacts of their work.” Would that the world be so easily navigated. Today there are larger threats looming to biodiversity than at any time in the past 66 million years, and every one of those threats is the result of human actions. The threat of negative ecological impacts by scientists who are trying to document, explain and ultimately sustain what remains of the natural world pales hugely when compared to the threats of habitat destruction, the over-exploitation of species, and climate change. We will face very difficult decisions in the coming decades, and information is our friend, not our enemy.

Back to Minteer though. I think that his argument amounts to cherry picking and straw men. The reason for my position is best stated in a recent blog post by my colleague at the California Academy of Sciences, Dr. Jack Dumbacher. Jack explores the discovery of that very same bat picked by Minteer as an example, and he outlines very nicely the critical nature of the work. Please read his post. I’ll end here with an excerpt: “This study highlights the value of museum specimens in modern research, and the importance of taking specimens in modern field studies. Ironically, these studies were undertaken to assess the impacts of selective logging. The biggest threat to lowland forest in PNG is due to habitat loss from logging, mining, and oil palm conversion. One of the few things that might slow habitat loss is the fact that one little poorly known female bat was recently collected there.“

The legitimacy of collections for biological research

Tags

biodiversity, extinction

(copyright Python? via YouTube)

The April 18th issue of Science magazine included a piece by Ben Minteer of Arizona State University, and co-authors, “Avoiding (re)extinction“. The authors argued that the collection of specimens for biological research has, and may continue to place species at heightened risk of extinction, citing among other things stories such as the collection of the last remaining individuals of the Great Auk, as if those extinctions could be attributed to scientific collecting. The piece was very ill-conceived and poorly supported by evidence, basically constructing a straw man in the interest of argument (“But this is just contradiction.” “No it isn’t!”). Luiz Rocha, one of my colleagues here at the California Academy of Sciences, led a response which eventually involved 134 scientists hailing from 64 institutions around the world. Our response was published last week, also in Science. I cannot print any of the letters here, but I will include a link to our press summary.
SCIENTIFIC COLLECTIONS PLAY VITAL ROLE IN CONSERVATION BIOLOGY