Ecosystems, Epidemics, and Economies

Yesterday I gave a talk for the “Breakfast Club” series at the Academy (California Academy of Sciences). The club is a twice weekly series of online talks started by the Academy in response to the widespread shelter-in-place and shutdown orders. It’s intended to bring a bit of our science and other activities to those interested who, like so many of us, find ourselves mostly limited these days to online interaction.

My talk focused on some new work that we are doing in the lab, related to the COVID-19 pandemic, but inspired by and built partly on our paleoecological and modelling work. I hope that you find it interesting! Oh, and while you’re there, check out the other talks in the series (link above)!

A New Hypothesis

The previous post introduced the concept of long-term ecological persistence in the fossil record. Very often in the geological past, once a clade (group of organisms descended from a common ancestor) became established, it would persist for a long time. And often some of those clades would become diverse, consisting of many species, and dominant, i.e. being very abundant members of their ecological communities. E.g., think trilobites or dinosaurs. As a result, we also have had communities and ecosystems in the past that have long-lasting characteristics because of the geologically persistent clades within them. Thus, the history of life can be divided and sub-divided into a set of nested types of communities. This is a surprising observation, because that history is embedded in processes of change, notably evolution and the dynamic geology of our planet. Many explanatory hypotheses have been put forward. Most of these assert that it is some particular feature of the clades themselves that make them persistent, such as greater rates of speciation (they evolve new species faster than less persistent clades), or competitive superiority (they muscle out other clades, making them less persistent). Others have pointed to ecological interactions among the species, suggesting that the possibility for the interactions to be altered by evolutionary change is constrained by the heavy dependence of survival on the interactions themselves, a sort of “ecological locking”. We instead suggest a new hypothesis, and it goes like this.

A guild-level food web, or “metanetwork”, or a late Permian terrestrial community from the Karoo Basin, South Africa. Each node represents a group of organisms with statistically similar trophic (predator-prey) interactions. The cartoon silhouettes are representative of the types of organisms in each node or guild. (Most silhouettes from phylopic.org; see our paper for proper attribution to the artists!)

Our hypothesis centers on biotic interactions, i.e. the interactions among species, such as predation. Those interactions exist within an organizational framework above the level of species, namely the functional groups into which a community’s species can be categorized, that is, the “jobs” that species perform. These functional groups may be further resolved based on habitat (where species live), foraging habitat (where they feed), and so on, yielding guilds of species. Examples of guilds from our study system include things such as “carnivorous insects”, “very large carnivorous amphibians”, and “small amniote insectivores/carnivores”. Finally, the interactions among species can also be grouped into interactions among guilds. Our hypothesis claims that the patterns of interactions among guilds affect (1) the persistence of a species in the community, i.e. the probability that the species will not become locally extinct after a period of time, and (2) the stable coexistence of species for an indefinite period of time. The second point hinges on my opinion that one of Nature’s nasty little secrets is that, in general, species do not like each other. I think that many species would be most happy if they could get by with a stable supply of sustenance and shelter, and not have to deal with species that don’t wish to be eaten, species that want to eat you, species that compete with you for sustenance and shelter, species that sponge off you (parasites), and so on. The hypothesis further predicts that once such a pattern becomes established, the likelihood of it changing will be low, both because of the persistence of its species, and because that persistence is superior to that conferred by other patterns. There is nothing preventing either the development or establishment of inferior patterns, but we should expect them to be geologically short-lived because their species will be less persistent, and the coexistences less stable.

The hypothesis maybe summarized as follows. When groups of interacting evolutionary lineages co-evolve, the patterns of interactions that result among them:

1. Promote the persistence of species within the community, i.e. probabilities of local extinction are low.
   
2. Promote the indefinite stable co-existence of the species.
   

Once attained, the likelihood that these patterns will be altered in any significant way (evolution of dramatically novel species or ecologies) is very low. If such a pattern or community type is altered, it is likely due to extreme perturbation of the external environment, accompanied by widespread extinctions.

In the next post I will explain how we went about testing the hypothesis using the Permian-Triassic mass extinction, and fossils of the Karoo Basin in South Africa.

Experimental Space

Tags

coral reef, food webs, Network theory, networks

Cayman Islands coral reef food web

Hi everyone, if any of you will be in the San Francisco Bay Area in the coming month, there is an exhibition at the Aggregate Space Art Gallery, featuring scientific visualizations. A couple of pieces there are from my food web work! So please stop by. Here is the gallery’s announcement:

“In their search for evidence of theories that better explain our physical reality, scientists often discover unexpected and beautiful phenomena. The researchers who created the images and videos included in “Experimental Space” did not have an art gallery in mind while they worked. Nevertheless, the images, figures, and data on view are aesthetically compelling and seductive. Through this exhibition, Aggregate Space Gallery and BAASICS bring scientific images and perspectives from the laboratory and the academic journal to the realm of art, where subjectivity trumps objectivity and ambiguity is more celebrated than demystification.

Featuring Evidence by: Erin Jarvis Alberstat, PhD candidate; Roger Anguera, Multimedia Engineer; Daniel J. Cohen, PhD; Sara M. Freeman, PhD; Luke Gilbert, PhD; Angela Kaczmarczyk, PhD candidate; Arnaud Martin, PhD; Brian Null, PhD, and Dr. Peter D. Roopnarine, PhD.”

Links–
http://aggregatespace.com/
http://www.baasics.com/

Coral reef food webs are out!

Tags

biodiversity, coral reef, corals, food webs, marine communities, real world networks, trophic guild

The first paper dealing with our Caribbean coral reef work is finally out. This paper is really just a detailed account of the data and webs compilation, but the data are now available to all. Enjoy!

Roopnarine, Peter D. and Rachel Hertog. 2013. Detailed Food Web Networks of Three Greater Antillean Coral Reef Systems: The Cayman Islands, Cuba, and Jamaica. Dataset Papers in Ecology, Vol. 2013, Article ID 857470, 9 pages.

Abstract: Food webs represent one of the most complex aspects of community biotic interactions. Complex food webs are represented as networks of interspecific interactions, where nodes represent species or groups of species, and links are predator-prey interactions. This paper presents reconstructions of coral reef food webs in three Greater Antillean regions of the Caribbean: the Cayman Islands, Cuba, and Jamaica. Though not taxonomically comprehensive, each food web nevertheless comprises producers and consumers, single-celled and multicellular organisms, and species foraging on reefs and adjacent seagrass beds. Species are grouped into trophic guilds if their prey and predator links are indistinguishable. The data list guilds, taxonomic composition, prey guilds/species, and predators. Primary producer and invertebrate richness are regionally uniform, but vertebrate richness varies on the basis of more detailed occurrence data. Each region comprises 169 primary producers, 513 protistan and invertebrate consumer species, and 159, 178, and 170 vertebrate species in the Cayman Islands, Cuba, and Jamaica, respectively. Caribbean coral reefs are among the world’s most endangered by anthropogenic activities. The datasets presented here will facilitate comparisons of historical and regional variation, the assessment of impacts of species loss and invasion, and the application of food webs to ecosystem analyses.

Competition in food webs and other complex networks

Tags

competition, coral reef, food webs, interaction strength, link strength, Network theory, networks, science

Competition is considered by many ecologists to be a major structuring factor in communities. It is a notoriously difficult thing to identify, classify and measure in the field and has been, in my opinion, an inspiration for some of the more elegant field studies. There is no doubt that species compete for resources in nature, but more elusive are answers to how much that competition matters to the stability of a species population, and the community as a whole, and what role competition might play on longer, evolutionary timescales. Typically, when we wish to measure competition, we require a few pieces of basic data, such as population sizes, interaction strengths and frequencies with the resource(s) being competed for, age structuring and so on. How can we go about doing this with complex food webs lacking these data? As usual, my answer is that you cannot, simply because of a lack of data. Nevertheless, I think that complex food webs do have something to say about competition, as long as one realizes that there is a trade-off between details of microscopic interspecific interactions and grabbing a macroscopic view of the community. Recently I’ve been mulling over appropriate ways to do this, and here are some ideas. I will preface them by saying that the interest stems from examining the potential impact of an invasive species as a competing consumer.

Let us begin with a (asymmetric) binary adjacency matrix, A, whose elements indicate whether species i preys on species j. The question is, what is the interaction between two consumer species, i and m. My first step is to simply count the number of prey shared between i and m, measured as the Hamming distance between the and rows; let’s designate that (). We can refine our view a bit by asking what fraction of a species’ prey is represented by that overlap, which is simply

where is the in-degree, or number of prey for species i in the food web network. You can think of this as the potential impact of species m on i. This is not quite satisfactory though, because and may be vastly different. For example, in our Caribbean coral reef food webs, many reef foraging piscivores (fish eaters) are specialists, preying mostly on maybe six other species, with those prey also being part of the repertoire of more generalist piscivores such as carcharhinid sharks who also forage on the reef and have k in the range of 70-80. It would be difficult to conceive of two such consumers as being strong competitors if the interactions of the generalist are distributed broadly over its prey. I therefore assume, in the absence of data on population densities, interaction strengths and functional responses of predators to prey, that this network measure of competitive interaction will be a function of both prey overlap (H) and consumer dietary breadth (k). There will be a trend of increasing pairwise strength of competitive interaction from generalist-generalist to generalist-specialist to specialist-specialist.

We can now extend our formulation in the following manner. First, count the number of prey shared between the consumers, . Then weight the interaction strength between m and its prey uniformly according to (ala CEG). The total interaction strength is

which is also the fraction of i’s prey that is being affected by m’s predation. The unaffected fraction, standardized to i’s dietary breadth is

yielding a standardized impact of

Note that this index is symmetric for i and m, i.e., it is the SAME for both species.

As a worked example, consider four species, A, B, C and D, with k’s of 60, 70, 2 and 2 respectively. The overlap of resources are: AB-35, AC-2, CD-1. The competitive indices are


and

I use in keeping with a conventional symbol for competitive interaction, but again point out that this is a very unparameterized measure compared to what is normally considered for use in Lotka-Volterra-type models or as measured empirically. You’ll notice that the values increase as the specialization of the interactors increases. It would be nice to scale these to a unit maximum to facilitate comparison, but I haven’t done that yet.

In a follow-up post I’ll provide some worked examples of all the above using real species from a real coral reef food web!

Number of predators per prey after extinction I: A start

Tags

extinction, food webs, link distribution, Network theory, networks

This series of posts are inspired by two questions that Jarrett Byrnes asked:

1. Given the extinction of E predators out of N, what is the probability that a prey species will still have at least one predator remaining?
2. Given E out of N, what then is the probability that all prey species will have at least one predator remaining?

As Jarrett and I have been discovering, these are actually quite difficult questions to answer in a general manner, i.e. for all topologies of a certain size!

Say we have a two trophic level food web with N predators, what is the probability that a prey species has at least one predator remaining after the extinction of E predators? The solution provided here depends on having the out-degree of prey species, and finding the probability that all predators of a prey species become extinct as a result of E. Say that the out-degree of the prey species is , then that probability is a hypergeometric solution

which reduces to

The probability then of a prey species having at least one prey is 1 minus the above

that is, the sum of the probabilities of having 1 predator, 2 predators, etc.

Example

Let the adjacency matrix of a food web be

where predators are rows and prey are columns. Our prey out-degree set is therefore {3, 2}. For E=1, both prey will have at least one predator since their out-degrees both exceed 1. For E=2, the possible resulting topologies are

For s=2

This is correct since our prey species of out-degree 2 (second column of A) has at least one predator in two of our three post-extinction topologies. The probability should be zero for s=3 (since E<s). If we add a third prey species, with s=1, making

then for E=1, the post-extinction topologies are

The probability that this third species has at least one prey is also 2/3.

A further example

So far so good, right? Well, Jarrett posed this example,

Notice that we now have two prey of out-degree 2. For E=1, the post-extinction topologies are

Applying the above formula yields

which is correct, since two of the three topologies maintain at least one predator for each prey. When E=2, the topologies become

Obviously, . But the formula gives

What went wrong?! The answer points to just how devilish the questions are, and how deceptive! There are two species of out-degree 2 (s=2) in the food web, hence the second term in the formula is squared (see above). BUT, the predator-prey topologies of the species are different, meaning that simple hypergeometric counting cannot work. We literally must list and examine all the post-extinction topologies, but this is prohibitively impractical for food webs and networks of even modest size (a dozen species). So there we stand. We currently have a partial solution, and I will explore the difficulty and the partial solution in the next post.

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A species’s tragedy of the commons

Tags

biodiversity, carrying capacity, cascades, competition, extinction, food webs, interaction strength, link distribution, link strength, modeling, networks, paleo-food web, paleontology, Robustness, Scientific models, simulations, Tipping point, trophic guild

My colleague Ken Angielczyk and I have a new paper out in the Royal Society‘s Biology Letters, entitled “The evolutionary palaeoecology of species and the tragedy of the commons“. If you have never read Garrett Hardin’s original paper on the tragedy of the commons, I strongly suggest that you do. It is a principle that I believe has broad application, and would well be worth a re-visit (first visit?!) by today’s leaders and economists. Our paper can be found here or here (first page only). And here is the abstract, as a little teaser!

Abstract

The fossil record presents palaeoecological pat-
terns of rise and fall on multiple scales of time
and biological organization. Here, we argue that
the rise and fall of species can result from a tragedy
of the commons, wherein the pursuit of self-inter-
ests by individual agents in a larger interactive
system is detrimental to the overall performance
or condition of the system. Species evolving
within particular communities may conform to
this situation, affecting the ecological robustness
of their communities. Results from a trophic
network model of Permian–Triassic terrestrial
communities suggest that community perform-
ance on geological timescales may in turn
constrain the evolutionary opportunities and
histories of the species within them.

Unbalanced food webs

Tags

extinction, food webs, modeling, Network theory, networks, paleo-food web, paleontology, real world networks, simulations

Perturbation simulations of three Karoo communities. 100 sims. per community.

A number of earlier posts have discussed food webs of the Permian–Triassic of the Karoo Basin in South Africa. This terrestrial ecosystem was subjected to the devastating end Permian mass extinction. The community which emerged in the aftermath of the extinction, the Lystrosaurus Assemblage Zone (LAZ), has been identified as having very unusual food web dynamics. This first figure compares the CEG dynamics of the end Permian Dicynodon Assemblage Zone (DAZ), LAZ, and the successive Cynognathus Assemblage Zone (CAZ). The implication is that there was a breakdown of perturbation dynamics during and/or right after the extinction episode. LAZ differs from the other communities (and in fact from every other community that we’ve studied so far!) in two ways:

1. Levels of secondary extinction can be extremely high at low peturbation levels, implying food webs of very low resistance.
2. Many species level networks or food webs (SLNs) of LAZ are nevertheless quite resistant, and resemble SLNs from the other communities. So the SLNs, or at least their dynamics, are highly variable in LAZ.

So what causes all this?

Distribution of log(low pert. sd) for random networks. Karoo communities are marked in green. LAZ occupies the extreme right.

The first question we asked ourselves was, is LAZ an unusually bad community or metanetwork, or are the other Karoo communities just exceptionally good? Our approach to addressing this was to generate 1,000 random metanetworks by randomly selecting observed guild richnesses from among our observed communities to fill the richness of a random community. A random community or metanetwork could therefore have guild richnesses that never occur together in any of the observed communities, but every guild richness of a random community is observed in at least one real Karoo community. We then simulated perturbation of 100 SLNs for each random community, and collected data on the first observation above, i.e., the variability of resistance at low levels of perturbation. As we see in the second figure, LAZ really stands out, even among the random communities! Why?

Well, in order to address that, we’ve used a number of regression models to examine the dependence of that variability on proportional guild richness. Proportional guild richness, in contrast to absolute, is the fraction of a community’s total consumer richness encompassed by a particular guild. Several guilds consistently stand out: very large amphibians, very small herbivorous amniotes, very small carnivorous/insectivorous amniotes, small carnivorous/insectivorous amniotes, carnivorous insects, and herbivorous insects. Multiple regression models demonstrate that the herbivorous guilds affect resistance variability negatively, i.e., they dampen the variability, while carnivorous guilds affect it positively! Now here’s the neat part. If we examine the sub-metanetworks of DAZ, LAZ and CAZ comprising these guilds only (see figure), we can immediately see how the communities differed with respect to these crucial guilds. Guilds with a dampening effect are shown in blue, those in red have the opposite effect (producer guilds are brown). And if you think of LAZ as being somehow imbalanced or out of whack, the figures should suggest to you some ways to “restore the balance”. I’ll discuss those in the next post.

Species richness and connectance

Tags

connectance, coral reef, food webs, link distribution, marine communities, Network theory, power law, Robustness

Ever since Lord Robert May challenged Robert MacArthur’s assertion that there is a positive relationship between diversity and stability, the argument has raged as to whether there really is a relationship between the proxies, species richness and connectance. May demonstrated that, at least within randomly connected food webs (more properly graphs), diversity does not beget stability, and that there is a critical connectance above which the system becomes unstable. I say that richness and connectance are proxies because diversity is more than richness, and stability is more than a critical point of connectance. Many workers, stimulated by May’s contention, have since shown that the non-random connection topologies of food webs matter; that is, functional diversity and hierarchical arrangements of species interactions allow real food webs, apparently, to be far more complex than allowed in May’s framework. Is there then no limit, or indeed no relationship between species richness and food web connectance?

I showed in an earlier post that there is a positive relationship between node richness and the number of links spanning a broad array of food web types. The same has been demonstrated before, most recently by Ings et al. Indeed, workers such as Jennifer Dunne and others have hypothesized that increased connectance confers greater robustness on food webs, hence allowing increases in richness as long as complexity also increases. I, on the other hand, doubt that this relationship actually exists for several reasons. First, the data upon which these hypotheses are based are extremely heterogeneous, and it is unclear whether connectance as measured across the array of food webs is actually the same thing from one web to the next. Second, measures of robustness typically are incapable of assessing robustness against anything other than the bottom-up perturbation of unparameterized systems; that is, no link strengths, population sizes, etc. Additionally, there should hence be no expectation of similarity of connectance values among any food webs.

In continuing our work on Greater Antillean coral reef food webs, I wanted to examine this relationship for our three food webs, namely those of the Cayman Islands, Cuba and Jamaica. The food web models differ only in vertebrate richness, and are ordered as Caymans>Jamaica>Cuba. This ordination corresponds nicely with sampling events and efforts. Yet, Jamaica has by far the greatest connectance of the three. Is this unusual or unexpected? We assessed this by stochastically drawing food webs of varying vertebrate richness, ranging from 80 to 160 species, from the regional species pool, and calculating their connectances. We did this for about 9000 food webs, and discovered this very nice, linear relationship. Connectance clearly increases, linearly in this case, with increasing richness. Why? The explanation is rather simple. Recall that the in-degree distributions of the island food webs, and hence the regional pool, is modal, yet with a significant right long tail. As one increases the number of species in a randomly drawn food web, the probability of drawing species from the long tail, those of high in-degree, also increases. Think of those species as being more “link dense”. Connectance will therefore increase, and will not be a constant value.

A wonderful surprise, however, is that the real food webs do not necessarily conform to this. The Cayman and Cuban food webs are indeed indistinguishable from the random food webs, but look at Jamaica! It’s connectance is well above random expectation. We know why, but I won’t tell you yet.