Reptiles comprise nearly 11,800 species worldwide, and are the most species-rich land-vertebrate group. After 18 years of laborious work by many experts globally, early in 2022, the first extinction risk assessment of this group was completed (the Global Reptile Assessment). This important endeavor will enable adding reptiles to global conservation policy and management initiatives as one of the major groups assessed. Nevertheless, this assessment still leaves over 3000 reptile species that have either not been assessed or were assigned a data deficient category that prevents their prioritization for conservation. In an effort to fill-in this gap a new publication in the journal PLOS Biology, we presents estimates of extinction risk for those species currently neglected by the Global Reptile Assessment, using novel machine learning modelling. importantly we found that unassessed and data deficient reptile species are more likely to threatened than assessed species.
Gabriel Caetano, lead author of the paper explained “The IUCN threat assessment procedure is highly important, yet very lengthy, data intensive, subject to human decision biases, and relies on in-person meetings of experts. However, we can use information on already assessed species to better understand the risks to those not yet assessed. Species may share physiological, geographic, and ecological attributes (often via shared evolutionary history) that make them more threatened, and experience similar sources of threat when they occur at similar locations. In our work we tried to emulate the IUCN process using predominantly remotely sensed data and advanced machine learning methods. We used species that have been assessed to teach our models what makes a species threatened and then predict the threat categories of unassessed species”. He added “our new methods are important for highlighting reptile species at risk and can be used on other groups as an initial shortcut for threat categorization”.
Shai Meiri added “Importantly, the additional reptile species identified as threatened by our models are not distributed randomly across the globe or the reptilian evolutionary tree. Our added information highlights that there are more reptile species in peril – especially in Australia, Madagascar, and the Amazon basin – all of which have a high diversity of reptiles and should be targeted for extra conservation effort. Moreover, species rich groups, such as geckos and elapids (cobras, mambas, coral snakes, and others), are probably more threatened than the Global Reptile Assessment currently highlights, these groups should also be the focus of more conservation attention”
Uri Roll mentioned “Our work could be very important in helping the global efforts to prioritize the conservation of species at risk – for example using the IUCN red-list mechanism. Our world is facing a biodiversity crisis, and severe man-made changes to ecosystems and species, yet funds allocated for conservation are very limited. Consequently, it is key that we use these limited funds where they could provide the greatest benefits. Advanced tools- such as those we have employed here, together with accumulating data, could greatly cut the time and cost needed to assess extinction risk, and thus pave the way for more informed conservation decision making”.

We tend to think of ways to categorize animals either by shape (4 legs? 2 legs? no legs?, thin? Fat? big headed? small headed?) or phylogenetic affinities (reptiles? lesser animals? Snakes? Skinks?). But what about ecology?
The many aspects of a species ecological niche are generally quantified singly, or we refer to some abstract “multidimensional niche”, meaning we give up trying to characterize it before we even started. In a paper published recently in the Journal of Biogeography GARDians, led by Enav Vidan and Jonathan Belmaker, tried to define, and numerate, the main types of lizards out there – as reflected in their ecology.

We have selected four traits that we felt define much of the fundamental axes of ecological variation seen in lizards: 1. use of space / microhabitat preference, that defines where in the environment a lizard is active (on the ground? In trees or rocks? Under ground? In water?); 2. Activity times: species active in the same place, or even on the same branch or piece of ground, can segregate their use of the environment by dividing the temporal niche. Furthermore, being diurnal or nocturnal (or being cathemeral and enjoy both ‘worlds’) has strong implication on thermal biology and hence on metabolism and rates in which lizards take up resources and exchange them with the environment; 3. Diet: is a species insectivorous/carnivorous, as most lizards are? Or do they predominantly feed on plant matter (these guys seem to even take more leaves and plant parts with lower energy content)? Or do they in fact use both plants and animals (and then probably energy richer plant parts such as berries or sap)? This is directly related to the way a lizard affects its environment and may also influence its position across the sit and wait-active foraging continuum (no use waiting for plants); 4. Body size – while not an ecological trait per se size nonetheless strongly influences a host of ecological processes, from the degrees of metabolism and energy flow, to the types of available foods – and potential predators.
These four traits obviously interact, and some combinations may be more or less common than others: small, diurnal, terrestrial insectivore is after all the first picture to pop to mind when the term ‘lizard’ is introduced (except for the diehard gecko lovers among us, and well, there are a few of us with this infatuation). But are there tiny nocturnal herbivores? Or huge nocturnal lizards? How common is a marine iguana  (large, herbivorous, swimming diurnal beast) type lizard – do we remember it simply because it is exotic?

We used Archetypal Analysis to assign lizards to types – or archetypes. Archetypal Analysis is an unsupervised machine learning technique that seeks to find the number of clusters that create the smallest convex hull in an n-dimensional trait space, by using the extreme values rather than the centroid of the clusters. AA assigns, for each species, a vector of affinities to each archetype. Most species are probabilistically assigned to several archetypes, with the partial probabilities summing to one.
We found that the most common functional trait combinations are (1) diurnal, terrestrial, carnivores (20% of the species); (2) diurnal, scansorial, carnivores (16%); and (3) nocturnal, scansorial, carnivores (13%).
Lizards could be robustly classified into seven ecological “Archetypes”:

1. terrestrial (obviously, usually small, carnivorous, diurnal thing that are, well, active on the ground), think Ablepharus skinks, for example
2. Scansorial – small diurnal, carnivorous, scansorial species, such as Pristurus rupestris.
3. Nocturnal – small terrestrial, scansorial and carnivorous species that are, at least partially, active at night (i.e. they are either nocturnal or cathemeral). Like most geckos of course – say Hemidactylus
4. Herbivorous - relatively large, diurnal, terrestrial and scansorial species whose diet includes substantial amounts of plant matter (either as omnivores or herbivores). Saharo-Arabian Uromastyx for example fit the bill very nicely
5. Fossorial – lizards living at least partially underground, mainly small, carnivorous, with varied activity times. Many skinks, such as Ophiomorus represent this strategy
6. Large - very big (all species >200 g), mainly diurnal, terrestrial or scansorial species. You know, Varanus komodoensis and Komodo-dragon wannabes.
7. Semi-aquatic - dwelling in aquatic habitats, relatively large, and generally both carnivorous and diurnal, things like Uranoscodon superciliosus

We then partitioned the global spatial patterns of lizard richness into these seven archetypes, and found that each shows pretty distinct patterns. Turns out Australia is the main hotspot for the herbivorous, nocturnal, fossorial, and terrestrial strategies – and for lizards in general. The Amazon basin is the main hotspot for the semi-aquatic, and scansorial strategies, whereas the large strategy has pan-tropical hotspots, especially in both the Amazon Basin and Northern Australia, but also in Africa, SE Asia and Mexico.
Surprisingly, we found that functional diversity peaks in areas with medium species richness and slowly decreases toward the speciose areas. This unexpected richness-functional diversity unimodal association is also revealed within the scansorial, large, and semi-aquatic strategies. The richness patterns of terrestrial, nocturnal, herbivorous, and fossorial strategies increase with species richness, but globally functional richness peaks in areas with medium species richness.
Thus increases in richness do not necessarily stem from increased functional diversity. Species diversification within specific strategies often dominates richness patterns.  Our findings support the contention that it is important to consider different functional and ecological subgroups when studying richness patterns.

Author: Shai Meiri

Throughout the years, scientists have formulated various ecological "rules" describing how body size evolves as an adaptation to various climatic factors – the first and most famous of these being Bergmann's Rule which posits animals increase in size in cold habitats as an adaptation to minimize heat loss.
In our recent paper published in Global Ecology and Biogeography, we examined trends in body size of squamates, utilizing GARD's massive dataset of distributions and body sizes. We examined these trends both at the assemblage level (how median size of squamate assemblages changes from one area to the next, and how it's correlated with climatic conditions in those areas) and at the species level (how body size changes from one species to the next, and how it's correlated with the climatic conditions experienced by each species).

​​What we found is, for lack of a better term, a huge mess - the spatial patterns for squamates differ from the spatial patterns for lizards and snakes separately, and from continent to continent, and between different families. For each of the climatic variables we examined, we found positive relationships with size in roughly a third of the cases, negative relationships in roughly a third of the cases, and no relationships in about a third of the cases.

Author & photographer: Alex Slavenko

In a recent publication in Global Ecology and Biogeograpy, I present a vast dataset of over 20 body size, ecological, thermal biology, geographic, phylogenetic and life history traits for global lizards.

I hope these data will facilitate more study into the biology of these most fascinating of creatures, and that the database publication will encourage others to add yet more data and to correct errors I surely have made when assembling them.

Author: Shai Meiri