Category: New Research Page 1 of 66

Limited Morphological Differences of Brown Anoles (Anolis sagrei) between Their Native Cuban and Invasive Florida Range

On July 29, 2024

Jars containing museum specimens are on a cart next to the shelf.

The ubiquity of Brown Anoles (Anolis sagrei) in Florida means that they are constantly on my mind. Given the proposition that rapid evolution may be important to invasive species success, I was curious to determine if invasive Brown Anoles in the southeastern United States, centered in Florida, have any morphological differences from Brown Anoles in their native range in Cuba. To address this question, I measured museum specimens to compare Brown Anole morphology between their invasive and native range and “go back in time” to see if Brown Anole morphology has changed since their invasion.

As reported in our recent paper, Brown Anoles have broadly similar morphology between their native Cuban and invasive Florida ranges. Additionally, we found no clear evidence of the measured morphological traits changing over time. These results suggest that rapid morphological evolution may not be essential to the success of invasive Brown Anoles.

Abstract:

Understanding why some species and not others are successful global invaders is an important question in ecology and evolutionary biology. There is much debate on the role that rapid post-invasion adaptation plays in the success of invasive species. Here, we investigated signals of rapid and broad-scale morphological evolution in Anolis sagrei (Brown Anole) between their invasive and native distributions. Although we found significant differences in a few morphological characters between invasive and native Brown Anoles, the morphological variation present in the species broadly overlapped between both populations and has not significantly changed over the last century. These results suggest the invasive success of Brown Anoles in Florida may not be due to major evolutionary change from their Cuban ancestors.

Mapping Anole Operative Temperature with Unoccupied Aerial Vehicles (UAVs)

By Emma Higgins

On May 12, 2024

In All Posts, New Research

Left: Emma setting up the 3D Anolis replicas (excuse the yoga clothes–it was hot!), Right: 3D replica in-situ.

A lot of us have been there…. setting up what seems like endless 3D anole replicas, often in the tropical heat, messing around with countless iButtons (which are a nightmare to get out of the replicas), to measure operative temperature (T_e)–the temperature of the animal at equilibrium with its environment….

As frustrating as this can sometimes be, it is an integral part of measuring thermal habitat quality and availability, which as we all know, is important for such things as ectotherm energetics, abundance and predicting species responses to climate and land cover change.

However, using these 3D replicas, we only get point-based measures of T_e at randomly selected points within the survey area. These points are sampling only a very small extent of thermal habitat, and therefore may not represent the conditions mere metres away. This method therefore does not allow us to measure T_eacross the whole of the survey area at spatial resolutions relevant to the individual animal. This method is also, costly in terms of both time and money. Therefore, is there another way?

Well, we do have microclimate–biophysical modelling, which generally relies on mechanistic models that downscale broad scale (usually monthly) macro-climate (≥ 1km grid) data to estimate microclimate in specific habitats, e.g. NicheMapR, Microclima and Microclimc (Kearney and Porter, 2017; Maclean et al., 2018; Maclean and Klinges, 2021). These estimates of microclimate must then be combined with biophysical heat exchange models to estimate animal operative temperature (T_e), e.g. the ectotherm model in NicheMapR (Kearney and Porter, 2020).

These models have revolutionized our ability to model thermal environments across broad spatial extents, especially for species distribution modelling, and new developments have the potential to model much finer variation (e.g. Microclimc), but applications at scales of individual organismal movement (e.g. cms to m) are still rare.

These limitations of existing methods are particularly pertinent given the established importance of spatial heterogeneity of thermal environment for species, particularly ectotherms, and by extension our beloved anoles (Huey, 1974; Sears and Angiletta, 2015; Sears et al., 2016).

Luckily, we as a team had already pondered, if the canopy is key for regulating ectotherm operative temperatures (T_e), then, can we predict T_e using biophysical equations relating to canopy characteristics?

Part of the field team, helping process what is certainly not an anole, whilst setting up survey plots (photo credit Adam Algar).

This was the basis of this paper, “Unoccupied Aerial Vehicles as a Tool to Map Lizard Operative Temperature in Tropical Environments.”

So, to test this, we first needed to collect canopy data – which, for anyone who has done this type of work will agree, is not so easy! This is where Unoccupied Aerial Vehicles (UAVs) come in.

Dewlap Displays Supersede Headbobs, Yet Again

By Terry Ord

On March 11, 2023

In All Posts, New Research

The dewlap is probably the most noticeable thing about anoles. For me, the best way to spot an anole is by the flash of color from the dewlap as a lizard displays. Without that, many anoles would remain cryptic amongst the vegetation. This seems to be the case for the lizards themselves as well. The burst of color and movement as the dewlap is rapidly extended is a wonderful device for attracting the attention of rivals and mates. It’s possible that the dewlap originally evolved as an attention-grabbing flag to augment an existing sequence of elaborate headbob movements in forested environments. These days, the dewlap is a complex signal component in its own right, often with a dizzying array of colours and displayed using a variety of movements.

Anoles aren’t the only ones with a moveable dewlap. The Southeast Asian Draco lizards have a dewlap, and again to back up the headbob movements that make up their main channel of social communication. There are many other parallels between Draco and Anolis lizards, but the similarities in how they communicate is something that particularly fascinates me.

Early on in my fieldwork with Draco, I started discovering species that didn’t seem to use headbobs as part of their social display. It seemed these species had lost the headbob entirely and instead concentrated all of their communication through the dewlap display. These species are a minority, but not by much. It was a puzzle. These Draco had lost a central and complex element of their communication in favour of something that was seemingly more basic. Communication biologists are often fixated on trying to explain how animal communication becomes more elaborate over evolutionary time, but less attentive to why complexity subsequently becomes lost. These Draco lizards were an excellent case study.

Draco melanopogon (photo above) only communicates using the dewlap, whereas Draco sumatranus (opening banner photo) relies on both headbobs and the dewlap, just like anoles.

After nearly a decade of fieldwork on numerous species of Draco throughout Malaysia, Borneo and the Philippines, my trips stalled in 2020, as did the rest of the world. Celebrities had nothing better to do than write biographies, but my lockdown project was to focus on using the data I already had at hand to finally solve the curious case of the missing headbob.

It felt like an endless series of stay-at-home orders in Australia, and well into 2021 too. While the celebrities had gone on to finish their books and were now doing the zoom promotion circuit, my progress was hurdled by home-schooling two young children. We survived home-schooling in the end, and my attempt at figuring out why some Draco have lost the headbob has finally been published.

The evolutionary history of visual displays in agamid lizards

The first discovery is the headbob display is very ancient, evolving something like 130 million years ago or more. That’s before the evolution of Draco, and before the evolution of the anoles, in an evolutionary ancestor to both the iguanid (new world) and agamid (old world) lizard families. This was back in the age of the dinosaurs. Today, virtually all iguanid and agamid lizards use a headbob display or some variant of it in social communication. Which means the absence of the headbob in a handful of Draco species is very unusual.

The loss of the headbob from the social display of Draco is effectively a loss of complexity. A loss of complexity means a loss of “information potential.” Try writing a biography with half the alphabet. You might manage the following or something a little longer: “I was born. I paid taxes.” Thirteen unique letters in total. Obviously not the rich backstory you might hope for. Not because you hadn’t lived a fulfilling existence; rather you don’t have the language complexity to convey it in detail.

There are various reasons animals might lose complexity in their social signals. Perhaps the original need for a complex signal is no longer present. Perhaps the invasion of a new environment puts a brake on the level of complexity that can be accurately perceived. Or perhaps natural selection on other things, like body size, has made performing a complex signal too costly.

The beauty of having spent so much time in the field is the accumulation of a large library of data. By leveraging this information, I was able to test each of the above scenarios. The short of it is, Draco that have lost the headbob are unusually large species. Physically moving the head and body in a headbob display is more energetically expensive than pumping the dewlap in and out. It seems, then, that the physiological cost of performing the headbob became too great for these large species and they shifted to relying only on the dewlap for communication. This implies the communication system of these species is compromised, unless they have made up the loss of information potential somewhere else.

Draco without the headbob have more complex dewlap colour patterns. Each dot is a different species.

In fact, the dewlap itself tends to be more complex in Draco that have lost the headbob. Stealing a method for measuring complexity of anole displays, the dewlap of these Draco are more elaborately coloured than the average Draco. Unfortunately, this is unlikely to have been enough to fully cover the loss of the headbob. This means Draco that no longer use the headbob are relying on a constrained communication system.

The idea that the headbob is likely to be more energetically expensive than the dewlap was originally proposed for the anoles. It was used to explain the physiological basis for why Jamaican anoles might have evolved an innovation that allowed them to move away from a headbob-centred display in favour of one focussed on the dewlap. To be clear, the Jamaican anoles do still rely on headbobs in their social displays. But a rapid series of dewlap pumps features more prominently in their displays compared to the typical anole, like those on Puerto Rico for example.

It seems the dewlap has begun to supersede the headbob in anoles as well.

If you’d rather not slog through the paper itself, you can view a 12 minute video summary instead. If you would like to slog through the paper and can’t access it behind the paywall, drop me an email and I’ll forward you a free copy (t.ord@unsw.edu.au).

Parallel Urban Adaptation from Phenotype to Genotype in Anolis Lizards

By Kristin Winchell

On January 20, 2023

In New Research

Anoles are models for studying evolution in the wild. Not only do anoles have a history of repeatedly diversifying to specialize in the same types of microhabitats in the same ways across the Greater Antilles, these lizards also have a tendency to adapt on rapid timescales to environmental change — be it the addition or subtraction of a predator or competitor, a polar vortex, a change to the structural environment, or a hurricane.

Anoles are also models for urban evolution. Why? Anoles are found abundantly across the Caribbean in urban and forest environments where they specialize in divergent microenvironments characterized by shifts in climate and physical structure. Urban habitats tend to be warmer, drier, more open, and dominated by buildings and impervious surfaces instead of vegetation — providing the perfect opportunity for repeated adaptation to a novel combination of environmental conditions. In other words, Caribbean cities provide a replicated natural laboratory to study adaptation as it happens when these lizards colonize and thrive in urbanizing areas. And there is no shortage of urban-tolerant and urbanophilic anole species to choose from!

Species of Anolis lizards are found in urban environments across the Caribbean (photos CC-BY K. Winchell; Earth at night by NASA).

Island Colonization, Drought, and Competition in Panama

By Dan Nicholson

On December 14, 2022

In Introduced Anoles, New Research

You open your eyes, blinking away water, you’re on a beach you don’t recognise, and never set out to visit. You look up and along the coast, it’s an island, the flora is alien to you, the climate hotter, and you’re already sweating. An eldritch cry emanates from the forest near you, new wildlife, things you have never seen before skulk around beyond the vines that lay before you.

Lifting yourself up, you decide to escape the blazing sun. You leave the beach and push through the wall of vegetation that veils the forest from the beach. You expect it to be cooler, but it isn’t. The forest is completely new to you, as you move through the undergrowth, unfamiliar insects dart away, flying past plants you’ve never seen before. As you press on through the undergrowth you wonder how long you will have to spend here? How much more time do you have here?

Dewlap Size Is Not What We Thought

By Terry Ord

On October 14, 2022

In All Posts, New Research

The large, colourful dewlap is an obvious defining characteristic of the anole. Understandably, then, there has been a lot of investigation (and speculation) on what the dewlap is used for. Without doubt it’s for social communication, but to communicate what. Historically, the dewlap was thought to be used for species recognition, which remains a reasonable explanation today. But a typical assumption made by many anole researchers and evolutionary ecologists alike is the dewlap, and specifically its size, is effectively an ornament used to attract mates or advertise potential fighting ability among territorial rivals. In other words, the evolution of the dewlap is the product of sexual selection.

If that’s the case, then dewlap size should be linked to some aspect of an individual’s ‘quality’ or physical condition, especially in males who seem to be the ones courting females (not vice versa) or defending territories. This is because a male’s quality or condition can be hard to assess by general appearance alone, unless there is a key feature that provides an honest indicator of that quality. In anoles, this is assumed to be a large dewlap that’s physiologically costly to produce.

One easy way that has been proposed to test for sexual selection in the origin of a morphological structure like the dewlap, is to look how it scales with body size. Structures that are honest indicators of condition will be costly to develop and maintain. Large males are often in better condition than small males because of the underlying factors that result in bigger bodies (e.g., a history of successful foraging, superior growth rate, having ‘good’ genes). This means larger males can invest more in exaggerating the size of the dewlap than smaller males. There would be a clear evolutionary incentive to do so as well, because having a larger dewlap would attract more mates and appear more threatening to male rivals. The outcome of this should be disproportionately larger dewlaps in larger males. This is called positive allometry or hyper-allometry. If dewlap size has a hyper-allometric scaling relationship with body size, then it probably resulted from sexual selection. Or at least that’s the idea. And you can find this out by just measuring a bunch a males.

The dewlap of anoles featured heavily in the original formulation of this idea, with the conclusion being that dewlap size was hyper-allometric and assumed to be the product of sexual selection. Anoles have therefore become a classic example of how sexual selection drives hyper-allometric scaling in ornament size.

Tom Summers

Tom Summers was a graduate student who thought about hyper-allometric scaling a lot. He looked at the scaling relationship of ornaments that he had confirmed experimentally to be the target of sexual selection in fish, and found they were hyper-allometric…sometimes. Tom found natural selection on ornament size can often work in the opposite direction to sexual selection. This is because large ornaments can interfere with locomotion and often be conspicuous targets for predators. When these pressures are high, species tend not to show hyper-allometry in ornaments. Those ornaments were still the product of sexual selection, but their allometric scaling was dampened by opposing natural selection.

Tom turned this attention to the anoles, and found overwhelmingly that dewlap size was not hyper-allometric but hypo-allometric. That is, larger males have disproportionately smaller dewlaps than smaller males. He even looked at another group of lizards that have independently evolved a dewlap, the southeast Asian Draco, and found the same pattern. His results have just been published in the Journal of Evolutionary Biology.

The scaling relationship of the dewlap in both groups varied from one species to another, but never was it hyper-allometric. In the case of the anole dewlap, this variation in dewlap size was predicted by factors important in signal detection (receiver distance and habitat light). This was consistent with the general hypo-allometry of the dewlap as well.

The effectiveness of a visual flag (like the dewlap) in attracting the attention of a receiver (another lizard) is dependent on the gross size of that flag, not how big it is relative to the signaller’s body (i.e., allometric scaling is irrelevant). Beyond a particular threshold size, which is dependent on the visual acuity of the animal in question, there are diminishing returns for detection with increasing size. Even a large increase in dewlap size beyond a certain point wouldn’t really improve signal detection, a phenomenon known as ‘Weber’s Law’. The resulting pattern when comparing dewlap size among males is hypo-allometric scaling. Larger males have generally reached the size threshold for reliable detection, so there’s little point in further elaboration.

It also fits with the extensive amount of work showing that the dewlap is likely to be most important in signal detection, rather than a cue of quality.

So why such a dramatically different finding to earlier investigations of the anole dewlap? All studies prior to Tom’s measured dewlap size by catching the lizard and manually pulling out the dewlap using forceps. Simon Lailvaux has discovered that the skin of the dewlap varies in its elasticity. Larger dewlaps are going to be more stretchy than smaller dewlaps. This means you can probably pull the dewlap out to a larger size in larger males. This would subsequently generate the artifact of hyper-allometric scaling when comparing dewlap size across males of different size.

Tom had measured dewlap size from high-definition videos of free-ranging males fully extending their dewlaps during display. There are various analyses in his paper that confirm this approach provides an accurate measure of dewlap size. His logic at the time was this view of the dewlap would be how lizards actually see and evaluate the size of the dewlap relative to body size. It also meant animals didn’t have to be caught, so the approach was less intrusive for the animal (always a plus). It just happened he avoided the potential problem of over stretching the dewlap if he had caught the animals and manually extended the dewlap by hand.

What does this mean for all that data that has been based on researchers pulling out the dewlap using forceps to measure its size? Honestly, I don’t know. Maybe nothing depending on what the data are being used for. Maybe everything if the data are being used in allometry studies.

Do Anoles Display with Greater Complexity than English?

By Terry Ord

On July 10, 2022

In Explainers, New Research

Above: the territorial display of a male Anolis stratulus on Puerto Rico

Take the time to watch the displays of an anole and you might appreciate how elaborate those signals seem to be. And by comparison to other lizard species, the anole display is arguably one of the most complex. Not only do anoles communicate with the up/down movement of head-bobs, but with the repeated extension of a large dewlap that in itself is often spectacularly colored. These displays are used to convey a variety of messages, from advertising the ownership of territories to the attraction of mates. We know the display is packed full of detail on species identity too.

But how do we go from gut impressions of what is complex to properly measuring the complexity of lizard displays, or any form of animal communication for that matter, including human language? The main way scientists have done this is by essentially counting the number of different components and using that to estimate an animal’s communication repertoire. There are various problems with this, such as deciding which components are different enough to count. It’s the most common method probably because it’s the easiest, but it is also the crudest. It offers only a basic view of signal complexity, missing the complexity inherent within components making up the repertoire.

An alternative approach is to apply some math from physics to measure the information potential of a signal. It is better than simply counting things because it measures the complexity of the entire signal, including the number of different components and the elaborations within those individual components as well. Best of all, it doesn’t require any decisions on what parts of a signal might be worth counting. It also provides a common, repeatable index of complexity that can be used to compare signals from very different animals, such as anole displays and human language.

So, how do anole displays stack up?

Want to know whether Anolis pulchellus on Puerto Rico has the most complex display? Read the paper and find out!

First, let’s consider some other lizards. The head-bob displays of sagebrush lizards (Sceloporus graciosus) are fairly representative of other species of fence lizards, and they clock in at 4.26 bits of information per display. “Bits” is a general unit for the amount of ‘information’ (think data) that can be “potentially” encoded in a signal, or its “information potential” for short. The number is largely meaningless by itself. The songs of birds would probably be the most obvious rivals of complexity in nature. Chickadees have 4.64 to 5.79 bits per song. But is that effectively the same or way more complex than sagebrush lizards? We need more benchmarking.

How about the famous waggle dance of the honeybee? The waggle dance was first uncovered by Karl von Frisch who found that it was a highly accurate signal conveying the direction and distance to an outside nectar source to worker bees inside the hive (google it, it really is super interesting). This discovery later contributed to von Frisch winning the Nobel Price alongside Konrad Lorenz and Nikko Tinbergen. von Frisch was also one of the first scientists to apply information theory to animal communication. The honeybee waggle dance comes in at 7.43 bits per dance. Bees are more complex than birds!

If we apply the same method of measuring complexity to written English, we find it has about 8.12 bits per word. Now let’s recap: sagebrush lizards are 4.26 bits per headbob display, chickadees are 4.64-5.79 bits per song, the honeybee waggle dance (my personal favourite) is 7.43 bits per dance, and written English is about 8.12 bits per word. Those comparisons in themselves are very interesting, but what about anole displays?

We’ve comprehensively measured the male territorial displays of eight different species of Puerto Rican anole and published our findings in Behavioral Ecology. When I say comprehensive, I mean just that: we measured dewlap colour pattern, the way in which the dewlap is repeatedly extended and retracted during the display, the pattern of movement of both push-ups and head-bobs, and a variety of other behaviors often seen accompanying territorial displays (e.g., tail curls and flicks).

The least complex part of the display is the dewlap colour pattern. At best, it encodes 1.02 bits per dewlap pattern. That’s for a dewlap with at least four different colours. The movement of the dewlap during the display—the timing of the in/out movement, how much the dewlap is extended—has far more information potential with as much as 3.87 bits per display. The sequence of head-bobs is the most complex aspect of the anole display and can be as high as 5.11 bits per display. Considering the entire display, the complexity of the territorial display ranges from 6.54 bits per display in Anolis poncensis to a whopping 15.40 bits per display in Anolis pulchellus.

15.40 bits per display! Does this mean anole displays are more complex than written English? Yes! And no. The estimate for written English—8.12 bits per word—was for single words, not a sentence, a paragraph or an encyclopedia. But the fact that anole displays are as complex as they are and might outclass songbirds is truly amazing.

It is contentious as well. During peer-review of our paper, some scientific referees found the reported values hard to digest. All of them thought our numbers for anoles were correct, but couldn’t accept that signals of mere lizards might be more complex than those of songbirds. The comparison to written English drew so much heat that we had to remove comparison to it from the paper entirely. The referees had various reasonable points. One referee highlighted that the value for written English was for single words, not whole texts (fair enough). Another referee suggested our application of information theory was more comprehensive than how it has been previously applied. The implication being other studies have tended to focus on measuring the easiest things and not the full breadth of a song (hmm…).

If you want to find out which Puerto Rican anole species varied most in display complexity and the adaptive explanations of why, or what might have driven the evolution of such complex signals in anoles to begin with, you’ll have to read our paper. Email me and I’ll send you a free copy.

Anoles outclass songbirds? Why not, I say. Perhaps in communicative complexity, but certainly on many other scales.

Inferring Where Anole Ranges Tend to Spread or Split

By Michael Landis

On April 29, 2022

In All Posts, New Research

When I mentioned to Jonathan Losos that I had applied a new biogeographic model to anoles, he gave me a copy of Lizards in an Evolutionary Tree. What could I do but take it as both a generous gift and gentle suggestion? This is all to say that I’m no herpetologist. I know this, and so should you. I write humbly to the AA readers as a twig anole standing on the shoulders of crown-giants.

With that said, several close colleagues (Ignacio Quintero, Martha Muñoz, Felipe Zapata, Michael Donoghue) and I recently had a paper published that introduces a new modeling framework that allows regional features of geography to inform phylogenetic rates of dispersal, extinction, and speciation – called FIG (Feature-Informed GeoSSE). We then applied FIG to the phylogenetic and biogeographic Anolis dataset published by Steven Poe and co-authors. This piece summarizes that work and subjects its readers to a few lame jokes.

Cartoon of FIG model behavior.

The first aim of our project was to propose a new framework for modeling historical biogeography using GeoSSE, a diversification model introduced by Goldberg et al. (2011). Under GeoSSE models, all species occupy different sets of regions in a shared geographical arena. As time advances, species stochastically disperse, go extinct, and speciate. Speciation itself might occur within a region or between regions (e.g., in a manner consistent with allopatric speciation).

Thinking realistically, when and where these events happen should somehow depend on the set of regions each species occupies and the geographical features of the relevant regions. Unless instructed otherwise, however, GeoSSE estimates every possible event rate from phylogenetic and biogeographic data alone. Regional features of geography aren’t used. This leaves historical biogeographers with at least one technical problem and one missed opportunity.

First, concerning the technical problem, the number of event rates explodes with the number of regions. A geographical system with two regions (A and B) requires seven rate parameters: two within-region speciation rates for regions A and B, two extinction rates for A and B, two dispersal rates for A into B and B into A, and one between-region speciation rate for splitting the widespread ancestral species with range A+B into two daughter lineages with ranges A against B. Three regions requires 18 rates, four regions requires 45 rates, and so on. Between-region (“allopatric”) speciation rates and, to a lesser degree, the dispersal rates fuel this explosion in rate parameters. Somehow the number of rates must be reduced if we hope to estimate any of them at all.

In FIG, regional features (size, distance, barriers) can inform event rates. Different features are free to have different relationships with each process. For example, region size may increase within-region speciation rates while decreasing local extinction rates. Distance may decrease dispersal rates but increase between-region speciation rates. FIG also allows for barriers and distances to inform the rate and way in which a widespread range splits following between-region speciation.

Second, concerning the missed opportunity, biogeographers often hypothesize how geographical features should influence evolutionary outcomes – for example, that a single species should “split” in two more rapidly when its range is subdivided by a barrier – but GeoSSE has not really been used to test such hypotheses, in large part because of the technical issue mentioned above.

For hypothesis testing, FIG analyses estimate the probability that each geographical feature has an effect on a corresponding class of evolutionary rates. This is done with Bayesian reversible-jump Markov chain Monte Carlo to turn “on” and “off” different relationships between features and rates. For example, if FIG estimates that the effect of distance on dispersal was “on” in 97% of MCMC samples, you might make the bold claim that distance influences dispersal rates between regions. Or, if the effect of size on extinction was “on” in only 31% of samples, you might say no conclusive relationship or non-relationship was detected.

The other aim of our work was to see if FIG produced any biologically interesting inferences. If not, why bother? Anolis led the pack when selecting a clade to feature for empirical analysis. Anoles are well-known for their distribution throughout the Caribbean and the neotropical mainland, with some expectation of moderate, but not rampant, dispersal. Because anole phylogeny and biogeography has been studied in such detail over the decades, the clade is also ideal for test driving phylogenetic models.

Geographical distribution of Anolis.

We adapted the Poe et al. (2019) dataset into a nine-region biogeographical system with five continental and four insular regions of varying sizes and distances. There are ~380 anoles in this dataset, with nearly as many insular as continental species, but nearly [*] all widespread anoles are restricted to adjacent continental regions. This is exactly the type of pattern you’d expect to see if geographical distance and oceanic barriers restricted anole movement. That is, widespread fragmented ranges should be difficult to maintain and should therefore be rare.

Biogeographic rates. Left: extinction (nodes) and dispersal (edges) rates. Right: within-region speciation (nodes) and between-region speciation (edges) rates.

Reassuringly, FIG inferred that dispersal was limited by distance, especially over water. Similarly, between-region speciation rates split ranges the fastest when the inhabited regions were far apart and/or separated by water. Region size and island-status did not have a predictable effect (or non-effect) on extinction and within-region speciation rate. The network diagrams above summarize different regional rates of evolutionary change.

Dispersal rates, between-region speciation rates, and distances.

We also were interested in a critical distance that we defined – the maximum range cohesion distance – beyond which widespread species tended to split into two rather than remain as one. The idea is that if dispersal rates are low, interpopulation migration rates should be low, and therefore rates of allopatric speciation should be high. If we assume that FIG’s dispersal rates approximate the rates of pulsed migration needed to maintain gene flow between regions, we predicted the corresponding distance at which organismal movement became too slow to maintain range cohesion. So how far is too far?

Our scrappy little estimator predicted that range cohesion is almost certainly degraded beyond ~470km over land and ~160km over water. As it turns out, six pairs of continental regions had average distances closer than 470km, where we find all widespread continental anoles today. We don’t expect that these distances perfectly describe the limits of range cohesion for all anole species in all contexts, but a cursory review of the anole population genetic literature convinced us that our estimates were at least reasonable.

Extinction rates, within-region speciation rates, and sizes.

We didn’t recover an analogous relationship for the ratio of extinction and within-region speciation rates with region size. But neither does FIG reject those relationships. Still, recalling the histogram of regional species richness above, it seems unlikely that size alone dictates richness in anoles across continental and insular regions – as they’re defined here – since Amazonia has so few species relative to much smaller regions, like the island of Hispaniola. More work on this issue is needed.

In its conclusion, our paper reflects on how phylogenetic models of biogeography treat allopatric speciation. With anoles under FIG, for example, the consequence of dispersal into a new region depends on the geographical context. If dispersal is between adjacent continental regions, dispersal tends to result in range expansion. But, if dispersal is between distant regions or involves insular regions, it tends to result in cladogenesis that’s consistent with allopatric speciation. In large part, this inference was made possible because regional features inform evolutionary rates in FIG, letting us predict where anoles tend to “split or spread.” We think this historical view of allopatric speciation in a phylogenetic context will be worth exploring further.

Not to pander, but Anolis has played and continues to play such an instrumental role in the development of biologically meaningful models of ecology and evolution. Many of the statistical phylogenetic models that I’ve looked to for inspiration in my own research over the years were introduced by anolologists. Maybe this is a second meaning for model clade? Rambling aside, our project was a true collaboration among some of the most creative organismal and mathematical biologists I’ve known. Our hope is that our small contribution lives up to the high standard of modeling anole diversity.

*–An innocent question from an outsider: is A. sagrei really a single species? Pretty wild.

Paper:
MJ Landis, I Quintero, MM Muñoz, F Zapata, MJ Donoghue. 2022. Phylogenetic inference of where species spread or split across barriers. Proceedings of the National Academy of Sciences 119: e2116948119. doi:10.1073/pnas.2116948119

Code:
https://github.com/mlandis/fig_model

Lab site:
http://landislab.org

Body Condition and Jumping Predict Initial Survival in a Replicated Island Introduction Experiment

By Colin Donihue

On April 20, 2022

In New Research

Back in 2014, collaborators Panayiotis Pafilis, Anthony Herrel, Johannes Foufopoulos and I initiated a multi-island lizard introduction experiment, inspired by the foundational anole evolutionary ecology work of Losos, Schoener, and Spiller. Our twist: we were going to do it in Greece, with a different genus of lizard – Podarcis. Wall lizards haven’t radiated like anoles, but there is fascinating work demonstrating rapid evolution in the genus and a large descriptive literature documenting the phenotypic differences of populations living on mainland, large islands, and small islands.

We introduced 20 marked individuals from the large, predator-rich island of Naxos to each of five Podarcis-free islets, and revisited the populations annually (up until pandemic), censusing each island. Each year we gathered new morphology, performance, behavior, and diet data, and released the lizards back to the experimental islets. We’ve just published a new paper showing that the traits that best predicted initial survival were not all the ones we’d expected. Body condition – sure – lizards with a higher body condition probably have the reserves that enable them to weather the stressful introduction. Bite force? Not so much. We’d expected bite force to be an important predictor of survival because lizards with harder bites would be more competitively dominant and also have access to defended prey items like gastropods. Contrary to our expectation, bite force was not a predictor of survival (but stay tuned, bite force has become more and more important as the experiment has continued).

If you’re interested, I’ve written lots more about the experiment on my blog over the years. We also have photos and videos from the islets:

Finally, a quick call to the community: I have six years of tissue samples from the five islet populations, but don’t have the molecular chops to ask any of the fantastically interesting questions we might be able to with paired survival, phenotype, and molecular data. If you’re interested in a collaboration, let me know!

New Literature Alert:

Colin M Donihue, Anthony Herrel, Johannes Foufopoulos, Panayiotis Pafilis, Body condition and jumping predict initial survival in a replicated island introduction experiment, Biological Journal of the Linnean Society, 2022;, blab172, https://doi.org/10.1093/biolinnean/blab172

Abstract: Over-water dispersal to small islets is an important eco-evolutionary process. Most often, new arrivals on islets find the environment harsh or mate-less, making their footholds on these islets fleeting. Occasionally, introduced animals are able to survive the strong selection following their arrival, leading to subsequent propagation and, in several famous cases, adaptive radiation. What traits predict that initial survival? We established a replicated island introduction experiment to investigate this process in lizards. In 2014, we introduced 20 Podarcis erhardii lizards to each of five small islets in the Greek Cyclades Islands. We found that the lizards that survived were those with better initial body condition, longer distal portions of their limbs and a greater propensity for jumping. Contrary to our expectations, neither body size nor the strength of the lizards’ bite – two traits positively related to competitive ability, which becomes important later in the colonization process in lizards – predicted survival. This is the first selection study of its kind investigating an experimental introduction of Podarcis, and whether the traits that determined initial survival are important in driving the future evolutionary trajectories of these populations remains to be determined.

How Do Anole Species Tell Each Other Apart?

By Terry Ord

On March 26, 2022

In New Research, Research Methods

When it comes to finding a mate or defending a territory, animals need to recognise members of their own species. The reasons are intuitive: you only want to mate with your own species to ensure viable offspring, and you should only invest the effort in being territorial when confronted by rivals from your own species. There are exceptions and these are interesting—hybridization or territorial competition between species—but generally animals need a system for species recognition.

The large, often spectacularly coloured throat fan or dewlap of anoles seems like an obvious way to evaluate species identity. Taxonomists have historically thought so, too. Each species appears to display a dewlap that’s unique in colour and pattern. But there are various Anole Annals posts highlighting this is not always the case. Instead, the colour of the dewlap is often an adaptation to the light environment for enhancing the detection of territorial displays.

So what about those territorial displays? Might anoles use the complex movements of the head-bob and push-up display to figure out species identity?

Classic work by Charles Carpenter and Tom Jenssen revealed how often the head-bob movements of lizards, and anoles in particular, seemed specific to each species. Pioneering experiments using video playback by Joe Macedonia in the ’90s has also provided evidence that anoles are able to distinguish displaying rivals of their own species from those of other species. But what is it about the pattern of movements used in the head-bob and push-up display, or even how the dewlap is extended and retracted, that conveys species identity? Is there one feature that varies the most among species that anoles commonly rely on to identify species?

Display-Action-Pattern graphs (above) showing the complexity of movements used by Puerto Rican anoles for territorial advertisement displays

These are hard questions to answer. Anole displays are complex, using many different types of movements, so there’s a huge number of possibilities. One approach would be to isolate and manipulate each type of movement and use video or robot playbacks to ask the anoles themselves. But doing that would take an entire career. There are a seemingly infinite number of combinations to consider. In fact, it would be impossible without a way to narrow things down.

Claire Nelson is a creative (and courageous!) graduate student who had an eye for solving the challenge. She figured it was possible to leverage the large archive of footage I’d accumulated over many, many years. These videos were of free-living male lizards performing territorial advertisement displays. Her idea was to develop an objective method for identifying which movements used in the head-bob, push-up or dewlap display had the potential to convey species identity. She’s just published her solution in Animal Behaviour.

Claire (above) doing a balancing act with some non-anoles

Claire used this archive of display videos to create Display-Action-Pattern graphs, a method developed by Carpenter back in the 60s. These track the up-and-down movement of head-bobs and push-ups as well as the extensions and retractions of the dewlap during the territorial display. To keep it manageable, she limited her efforts to anole species on Puerto Rico, and graphs of about 10 territorial advertisement displays per male. But there was an important biological reason for selecting this number of displays as well. It effectively mimicked the number of displays an anole might typically see on first encountering another lizard. That is, anoles likely make judgements on species identity from only a handful of displays.

From these Display-Action-Pattern graphs, Claire took a host of measures, ranging from the duration and number of movements used, to variation in amplitude and pauses between movements. She also noticed that anoles tend to perform certain combinations of movements together in what she came to call ‘motifs.’ After many many hours of effort, Claire accumulated a huge amount of data for nearly 20 different types of display movement for eight Puerto Rican Anolis species, and in many cases, for different populations of the same species.

Claire asked me for advice on how to analyse it all. I have to admit I was completely useless on this front. I muddled something about using coefficients of variation and some other nonsense, but really I had no idea. I was still in shock over how much data she had accumulated, and the novelty (and implications) of discovering motifs in the displays. She knew what she was doing, though. Her analytical solution was vastly superior to anything I could have suggested.

Claire investigated a variety of approaches, but in the end she settled on the method of random forest tree classification. It’s a sophisticated machine learning algorithm that, in a nutshell, takes data and groups like with like. It doesn’t require any prior direction or preconceived notion on how data should be grouped. It just uses the variation in the data itself. You could view the algorithm as an anole brain using basic rules of variation to make judgements on which displays are likely to be different and which displays are likely to be the same.

The outcome was impressive. The algorithm correctly assigned the vast majority of lizards to their correct species based on just a handful of displays. Where errors occurred, it was partly because lizards were assigned to the right species, but the wrong population. This means anoles from different populations tend to share some display features because they’re still from the same species. Yet the algorithm was able to correctly assign most lizards to the right population. In other words, there was still enough variation in the displays between populations of the same species to identify them as belonging to separate populations. This is very interesting!

Random forest tree classification (above) can assign over two thirds of displaying lizards to their correct species.

The evolution of new species begins with individuals of the same species starting to segregate from each other in some way. Often it’s physical separation (on opposite sides of a mountain range), but changes in social signals can also prompt behavioral separation as well. This could be the case for some anoles on Puerto Rico. Once individuals stop recognising each other as the same species, they no longer reproduce with one another, and the door to speciation is propped open.

The other discovery Claire made was the apparent lack of any common display feature that could be used to identify species (and population identity). Instead, different features were important for different species. The duration and number of headbob movements were features that could be used to identify the territorial displays of Anolis poncensis—a species that is striking in its use of lots of extremely rapid, up and down body movements—whereas the way the dewlap was extended was influential in identifying different populations of Anolis gundlachi—a species that has an unusually long dewlap display. Other species like Anolis pulchellus and Anolis krugi were best identified by effectively considering features of the entire territorial display.

Whether or not anoles actually use the features identified by the algorithm in species recognition remains an open question. But Claire has managed to identify the potential candidate cues that could be used. It is now possible to develop a focussed research program to test whether, and how, anoles used these features to identify species. Again, the obvious way to do this would be to ask the lizards themselves using robot playbacks.

Random forest tree classification sounds awfully complicated, and it is very sophisticated, but it’s actually easy to implement. Any dummy can do it. I taught myself how and wrote a step-by-step tutorial so you can as well. We’ve published this tutorial alongside Claire’s paper in Animal Behaviour. Give it a whirl!