Massive increase in visual range preceded the origin of terrestrial vertebrates

Large Eyes Appeared Before Terrestriality

Fig. 1 shows the sequence of steps of our study across its parent disciplines. We start with the assembly of a time-calibrated phylogeny of 59 tetrapodomorph taxa that bracket the water–land transition and have measurable skull and eye socket lengths (Materials and Methods). We generated a set of 1,000 evolutionary trees to account for uncertainties in phylogeny. Using this tree distribution, we then apply a phylogenetic comparative approach to estimate whether there were changes in the selective regime governing the evolution of relative eye socket length (socket length corrected for size of animal inferred from skull length by a regression). A statistical approach incorporating phylogenetic information is needed, because the evolutionary relationships of the animals in our sample result in our observations of their eye socket sizes losing statistical independence (1, 2), disqualifying conventional significance tests that depend on this property. Specifically, we follow an approach guided by the Ornstein–Uhlenbeck (OU) process as a model of trait evolution (3, 4). We use a Bayesian variant of this method (5) to study the adaptive landscape of the relative eye socket sizes of early tetrapods (Materials and Methods).

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Fig. 1.

The sequence of steps within early tetrapod paleontology as well as computational visual ecology used for generating the results of this study.

Analysis of the selective regime shifts within the tree distribution reveals a surprising finding: a change favoring larger eye sockets is most likely to have happened before the origin of the vertebrates with complete limbs including fingers and toes (hereafter “digited tetrapods”), in animals understood to be primarily aquatic (Fig. 2). This major shift in eye socket evolution occurred in a phase of fundamental reorganization of the tetrapod body plan. The transitional phase begins with the lineage leading to the last ancestor of the elpistostegalians (the finned transitional group in Fig. 2) and ends with the lineage connecting to the last ancestor of the very first digited tetrapods, Ventastega (inferred to have digits) and Acanthostega. During this phase of evolution, tetrapods entered a new adaptive zone that selected relative eye socket sizes that were a factor of 1.42–1.53 larger than the ancestral adaptive peak for fish, such as Eusthenopteron (Fig. 2). Fig. 3 shows the absolute and relative socket sizes for our dataset grouped according to the adaptive zones identified by the analysis of selective regime shifts. We refer to the group before the increase in eye socket size as “finned tetrapods” (6). As shown in Fig. 3, there was a near tripling in the mean absolute socket size between the finned and digited tetrapods. We will show below that the enlargement of eye sockets supports the inference that eyes also approximately tripled in size.

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Fig. 2.

Evolution and adaptive landscape of relative eye socket size in early tetrapods summarizing our phylogenetic comparative study performed over a sample of 1,000 time-calibrated trees. The circles (red for finned, yellow for finned transitional, blue for digited, and brown for digited aquatic tetrapods) represent body size-corrected relative eye socket sizes, the residuals from phylogenetically generalized least squares regression (PGLS) of log₁₀-transformed variables (Materials and Methods and SI Appendix, Scaling of Orbit and Skull Length in Early Tetrapods). The thick branches indicate positions of well-supported selective regime shifts, with associated factors signifying the change in eye socket size compared with the ancestral regime (before the green dot) after body size effects are accounted for.

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Fig. 3.

Eye socket lengths across the taxa in Fig. 2 grouped by the regime shift analysis. (A) The mean (horizontal bars) absolute eye socket length of digited tetrapods was three times larger than that of their finned relatives, with the elpistostegalians (finned-transitional) midway. The digited tetrapods that returned to life underwater (adelospondyl-colosteids, digited-aquatic) reverted to a size similar to that of their finned relatives. (B) Relative eye socket size was calculated as residuals from a phylogenetically informed regression of log₁₀-transformed variables (Materials and Methods) averaged over the full set of 1,000 trees. Positive residuals indicate eye sockets larger than expected based on skull length, whereas negative residuals indicate eye sockets smaller than expected. The Bayesian OU results in Fig. 2 show the presence of an adaptive evolutionary process and provide estimates of the adaptive peak for each group (horizontal bars). The elpistostegalians entered a new selective regime but are lagging behind, because time was insufficient to accrue enough increases in eye socket size to reach the peak.However, the digited tetrapods are centered around their adaptive peak, except for the adelospondyl-colosteids. As expected for adiverse group, not all tetrapods are at their respective peak, reflecting a normal evolutionary pattern in which trait values are dispersed around the optimal value. The Bayesian OU findings show that there must have been a selective benefit from larger eye sockets in finned transitional and digited tetrapods, but uncovering its basis requires modeling visual performance across likely environments.

Interestingly, there was a reversion to small eye sockets in a group of animals that subsequently specialized for life underwater. This group is termed the “adelospondyl-colosteids” (7) (Figs. 2 and 3). They have elongated snake-like bodies with tiny limbs (7, 8) and shrunken eye sockets similar to those of the finned tetrapods. Although there are other animals that are clearly semiaquatic within the digited tetrapods, the adelospondyl-colosteids are unique in the extent of aquatic specialization across the entire group and considered fully aquatic.

Our discovery that the evolution of larger eye sockets occurred in animals that were primarily aquatic is in line with other critical conclusions of the past several decades of early tetrapod paleontology, which has found that robust limbs evolved in primarily aquatic animals (9, 10) and that fingers and toes evolved in primarily aquatic animals (11). Notably, the increase in eye size starting in the elpistostegalians coincided with a distinct change in the placement of eyes in this group. Although placed laterally in the early phase of tetrapod evolution, similar to other fish, the eyes moved into a position on the top of the head in this group (Eusthenopteron compared with Tiktaalik in Fig. 2). They are on raised “eye brows,” low bony prominences on the top of the skull (12⇓–14).

Computational Visual Ecology

The adaptive landscape analysis in Fig. 2 shows the location and magnitude of changes in relative eye socket size but is insufficient for understanding their possible bases. Larger sockets strongly correlate with larger eyes as shown by data on fish (SI Appendix, Estimating Eye and Pupil Size in Early Tetrapods and Fig. S4), reptiles (15), birds (16), and primates (17). Evidence spanning such a broad bracket of vertebrates shows that eye socket size in our group of ancient animals reliably captures what their eye size would have been. We can, therefore, estimate that the nearly threefold increase of absolute eye socket size (Fig. 3) corresponds to an almost threefold increase in eye size. However, what are these large eyes good for? To better understand the significance of the increase in eye size, estimates of the functional consequences of these changes across environments that bracket the most likely possibilities (computational visual ecology) (Fig. 1) can be helpful.

Larger eyes are strongly correlated with larger pupils (SI Appendix, Estimating Eye and Pupil Size in Early Tetrapods and Fig. S4), a key variable in estimating visual capability. We selected four measures of visual function that we calculated as a function of pupil size: the distance at which a standard object, a 10-cm black disk, could be seen; the volume of space within which that same object could be seen given an estimate of the field of view; and the gains in both range and volume for a change in eye size (the derivatives of range and volume measures with respect to eye size). These measures were computed for the mean pupil size of the finned and digited groups ±1 SD as estimated from the absolute socket lengths for these groups (Materials and Methods and Fig. 3A).

To make estimates of visual range and volume, we adapted a model of aquatic visual capability for pelagic fish from Nilsson et al. (18), which focused on first-order optical physics, and incorporated contrast threshold into this framework. With this change, visual ranges in aquatic and above-water environments can be calculated using the same model. The visual system is modeled with two channels: one that only sees an empty background and one that only sees a given target (18) (Materials and Methods and SI Appendix, Computational Visual Sensory Ecology Estimates). For these reasons, our visual range estimates represent a best case scenario for visual detection in the absence of clutter.

To compute the amount of light in the background and the light from the target, we must model the likely visual environments of the early tetrapods. Visual range for a given object differs greatly between aquatic and aerial environments, a fact related to their dramatically different attenuation lengths. The attenuation length of a medium is defined as 1/c, where c is the sum of the absorption and scattering coefficients. After a beam of parallel light rays travels a distance equal to the attenuation length, a fraction of the light equal to the reciprocal of the base of the natural logarithm—≈1/2.71 or 37%—remains at the given wavelength. Aquatic attenuation lengths—for shorter wavelengths (bluish) that travel the farthest in clear water—vary in oceans from, at most, 24 m for the clearest deep water (19, 20) to meters for coastal oceanic water (18, 20) and vary in freshwater from less than 2 m to a 10th of a meter (21⇓–23). Shallow freshwater habitats are where the majority of early tetrapods emerged (8, 9, 24⇓–26). In dramatic contrast to the ancestral aquatic condition, the attenuation length for similar wavelengths of light in air is 25,000 m (27, 28) (extinction factor) (SI Appendix, Table S1)—between 10,000 and 100,000 times larger than the habitats similar to those of the early tetrapods. Additional details on the visual ecology calculations are in Materials and Methods and SI Appendix.

Our results (Fig. 4) show that visual performance underwent a massive increase with the shift from vision through water to vision through air. For the case of daytime viewing horizontally in water through finned tetrapod eyes vs. air through digited tetrapod eyes, the range increased by well over a factor of 100. A conservative estimate of the total volume that our standard object could be sensed within (Materials and Methods)—a more ethologically relevant measure (29, 30)—increases by just under 2 million times (Fig. 4 A1, A2, C1, and C2 and SI Appendix, row 2 in Table S4).

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Fig. 4.

Visual performance in and out of water. Aquatic vision is estimated using the Baseline River water type defined in SI Appendix, Table S3 at a depth of 8 m. The object is a black 10-cm-diameter disk. (A1 and A2) Maximum distance that the object can be seen in water and air, respectively, under various lighting conditions. Note that visual range scales proportionately to target size. For a 1-cm disk in daylight, the aerial range decreases to 139.3 m assuming mean pupil size for digited tetrapods and 54.7 m for the mean pupil size of finned tetrapods (data not shown). (B1 and B2) How much range is gained for an increase in pupil size? Note that the y-axis multiplier is 100 times larger in B2. (C1 and C2) Total volume within which the standard object is visible. Note that the y-axis multiplier is 1 million times larger in C2. (D1 and D2) How much volume is gained for an increase in pupil size? Note that the y-axis multiplier is 1 million times larger in D2. For the aerial plots, the aquatic values are shown but imperceptible. Uncertainty for the daylight condition (green fill) was calculated by using alternative values for the vision model (Materials and Methods) and is not shown for other conditions for clarity. SD is here only for showing the distribution of estimated pupil sizes; it cannot be used in this context for ascertaining significance because of shared ancestry (details are in the text). *Red horizontal bars show ±1 SD of pupil sizes from the mean (dotted vertical lines) estimated for the eye sockets of finned tetrapods. **Blue horizontal bars and vertical lines are for the digited tetrapods.

We have performed a large number of sensitivity analyses to determine how robust this conclusion is to our assumptions (Materials and Methods, Sensitivity Analyses). These analyses divide into perturbations of our baseline visual environment and perturbations to our baseline visual physiology. In terms of sensitivity to environment, we note that a large increase in our measures of visual performance occurs regardless of the diel activity patterns of the early tetrapods. Our results are consequently agnostic to whether the increase in eye size was for the gain of sensitivity that this causes for the dim light vision models (leading to larger range) or because larger eyes in full light lead to an increase in acuity (also leading to larger range) (SI Appendix, Vision Model Limitations and Sensitivity Analysis and Table S1). Our results are also unaffected by variations in water clarity. In terms of perturbations to our baseline visual physiology, changes to a host of factors, including contrast threshold, photoreceptor size, and dark noise level among others, have effects that are well outside of the range where our conclusions are affected. For the daylight vision case, these variations are shown in Fig. 4, solid green fill.

One finding that is informative given the movement of the eyes from their standard fish-like location along the sides of the head to the top (compare Eusthenopteron with Tiktaalik in Fig. 2) has to do with extended range for looking up toward the water surface vs. looking horizontally within water. Because sunlight is predominantly down-welling at shallower depths (ref. 31, figure 2.20 and ref. 32), upward viewing in these environments provides a considerable increment in range—a factor of ≈1.5 in daylight conditions (Fig. 4A1) at 8-m depth. At shallower depths than 8 m, this multiplicative factor increases.

Based on our results on trait evolution and computational visual ecology, we conclude that the observed increase in eye size is the result of adaptive evolution, where the derivative of the range and volume with respect to the pupil size is a proxy for the selective benefit of mutations that increase eye size. This measure shows a very clear pattern: in the transition from underwater to aerial viewing, there is a gain of ≈5 million in how much an increase in eye size increases the volume within which our standard object can be seen (Fig. 4 D1 and D2 and SI Appendix, row 2 in Table S4). In addition, for the volume derivative, there is a switch from diminishing returns for increasing pupil size (negative slope in Fig. 4D1) for aquatic environments to increasing returns (positive slope in Fig. 4D2) for the aerial case.

Implications of Long-Range Vision for Reactive Neural Circuits and Planning

Long-range vision has large effects on animal behavior, because it allows more complex decision making over extended sensory ranges. Stimulus-evoked behavior (51) with respect to the most crucial decisions that an organism needs to make, such as an escape response to a looming predator or a lunge at prey, was the normal situation in the aquatic habitats from which land vertebrates originated, where viewing distances were on the order of a body length (SI Appendix, Reaction Time with Respect to Visual Range in Finned Tetrapods). With short-range visual stimuli arriving in a just-in-time-to-act fashion, internally driven behavior (52) with serial decision making (53) requiring time proportional to the length of the sequence of actions being deliberated (54) was challenging for actions stemming from perception of dynamic stimuli—such as mobile predators and prey (ref. 55, p. 496). This limitation changed with the evolution of the first long-range (more than 100 body lengths) imaging sensory modality: aerial vision. The only other long-range imaging system in animals is echolocation, which only emerged much later in mammals.

In quite simple instances, an increase in visual range can result in a completely different behavioral control strategy, with large savings in mechanical effort (SI Appendix, How Temporal/Spatial Range Affects Optimal Decision Making). After the emergence of vision above the water line, the total volume of space monitored by vision in daylight conditions increased 1 million-fold over that of water in full sunlight, enabling (although not necessitating) complex “deliberative mode” strategies (29, 53, 55) with respect to the most unpredictable features of our environment: other animals. Emergence onto land, with its complex environmental geometry (56) featuring multiple paths toward prey or away from predators, would have furthered the selective benefit of more complex control strategies that take more time to compute than the simplest reactive strategies.

As more behavior became regulated by long-range vision (even with nocturnality) (SI Appendix, Table S4), there would have been reduced selective benefit for that portion of the neural infrastructure of the “reactive mode” (29, 55) that aids predator evasion after detection at short range in water. In fish and amphibians, the delay between predator detection and escape is reduced by ≈6 ms (57) through recruiting a single large caliber cell called the Mauthner neuron to initiate the escape maneuver (58). Although this neural circuit enables ultrafast reactions to stimuli (≈4 ms), the limited number of neurons and synapses involved constrains the flexibility of the response (60). Mauthner command cells, activated by close-range acoustic, lateral line, tactile, and looming visual stimuli (59) in proportion to the speed of looming (61), are only present in vertebrates up through amphibians, including frogs (62, 63).

With the evolution of suitable brain circuitry, certain animals were able to consider multiple options for pursuit or evasion that are likely to enhance fitness, such as by vicarious trial and error behavior in rodents, in which future possibilities are imagined (53, 64). Vicarious trial and error, like other forms of prospective cognition or “mental time travel,” are dependent on the hippocampus. This structure has the same developmental origin in birds and mammals (65), which had their most recent common ancestor in the Late Carboniferous not long after fully terrestrial animals arose. With this affordance of long-range vision, therefore, we hypothesize that the core neuronal components of planning (53, 65)—now understood to occur in both birds (66) and mammals but less well-studied in reptiles (67)—evolved within a common ancestor (65).