Browsing by Author "Leal, Manuel"

Changing environmental conditions may present substantial challenges to organisms experiencing them. In animals, the fastest way to respond to these changes is often by altering behavior. This ability, called behavioral flexibility, varies among species and can be studied on several levels. First, the extent of behavioral flexibility exhibited by a species can be determined by observation of that species' behavior, either in nature or in experimental settings. Second, because the central nervous system is the substrate determining behavior, neuroanatomy can be studied as the proximate cause of behavioral flexibility. Finally, the ultimate causation can be examined by studying ecological factors that favor the evolution of behavioral flexibility. In this dissertation, I investigate behavioral flexibility across all three levels by examining the relationship between habitat structure, the size of different structures within the brain and total brain size, and behavioral flexibility in six closely-related species of Puerto Rican Anolis lizards. Anolis lizards provide an excellent taxon for this study as certain species, including those used here, are classified as belonging to different ecomorphs and are morphologically and behaviorally specialized to distinct structural habitat types.

In order to determine the presence of behavioral flexibility in Anolis, I first presented Anolis evermanni with a series of tasks requiring motor learning and a single instance of reversal learning. Anolis evermanni demonstrated high levels of behavioral flexibility in both tasks.

To address the pattern of brain evolution in the Anolis brain, I used a histological approach to measure the volume of the whole brain, telencephalon, dorsal cortex, dorsomedial cortex, medial cortex, dorsal ventricular ridge, cerebellum, and medulla in six closely-related species of Puerto Rican Anolis lizards belonging to three ecomorphs. These data were analyzed to determine the relative contribution of concerted and mosaic brain evolution to Anolis brain evolution. The cerebellum showed a trend toward mosaic evolution while the remaining brain structures matched the predictions of concerted brain evolution.

I then examined the relationship between the complexity of structural habitat occupied by each species and brain size in order to determine if complex habitats are associated with relatively large brains. I measured brain volume using histological methods and directly measured habitat complexity in all six species. Using Principal Component Analysis, I condensed the measures of habitat structure to a single variable and corrected it for the scale of each lizard species' movement, calling the resulting measurement relevant habitat complexity. I tested the relationship between relative volume of the telencephalon, dorsal cortex, dorsomedial cortex, and whole brain against both relative habitat complexity and ecomorph classification. There was no relationship between the relative volume of any brain structure examined and either relevant habitat complexity or ecomorph. However, relevant habitat complexities for each species did not completely match their ecomorph classifications.

Finally, I tested the levels of behavioral flexibility of three species of Anolis, A. evermanni, A. pulchellus, and A. cristatellus, belonging to three distinct ecomorphs, by presenting them with tasks requiring motor and reversal learning. Anolis evermanni performed well in both tasks, while A. pulchellus required more trials to learn the motor task. Only a single Anolis cristatellus was able to perform either task. Anolis evermanni displayed lower levels of neophobia than the other species, which may be related to its superior performance.

In combination, this research suggests that Anolis of different ecomorphs display different levels of behavioral flexibility. At the proximate level, this difference in behavioral flexibility cannot be explained by changes in the relative size of the total brain or brain structures associated with cognitive abilities in other taxa. At the ultimate level, the size of the brain and several constituent structures cannot be predicted by habitat complexity. However, behavioral flexibility in certain tasks may be favored by utilization of complex habitats. Flexibility in different tasks is not correlated, rendering broad comparisons to a habitat complexity problematic.

The evolution of animal signals is driven largely by characteristics of the signaling environment and properties of receiver sensory systems. Selection favors signal traits that increase the probability that a signal will stimulate the sensory systems of intended receivers, but not potential predators, under average environmental conditions. However, environmental conditions often fluctuate, which means that a given signal property may not be equally effective at all times. One potential mechanism that an organism might employ to overcome this challenge is to modulate its signal properties as environmental conditions change in order to maintain stimulation of the receiver sensory system. In this dissertation, I explore the possible role of signal modulation using the motion detection and communication systems of tropical Anolis lizards.

In order to assess the possible role of signal modulation in the communication behavior of anoles, it was necessary to determine the properties of their motion detection systems. In Chapter 2, I tested whether motion detection properties are conserved across species of anole. I adapted a behavioral assay to quantify the spatial parameters of the motion detectors of three species of Puerto Rican Anolis lizards, with each preferring a distinct structural habitat type. I then compared the results to data previously collected for anoles from Cuba, Puerto Rico, and Central America. Results indicated that all species share a minimum amplitude threshold for detecting moving objects and exhibit multiple peaks in relative response to various motion amplitudes. Fine-scale interspecific differences in the number and values of response peaks were not correlated with structural niche. Overall, the study suggests that the motion detection systems of Anolis lizards are relatively conserved, which may help explain shared features of movement-based signals in anoles.

For mobile organisms, the spatial relationships of signaling individuals and intended receivers can be fluid. Such fluctuation in the distance between signalers and receivers can greatly impact signal efficacy, but it is unclear exactly how animals cope with this problem. In Chapter 3, I investigated whether signal modulation can serve as an effective strategy to cope with variation in the spacing of receivers in the environment by tuning a signal to maintain stimulation of the receiver sensory system. I evaluated this hypothesis by testing the use of modulation in the tropical lizard Anolis gundlachi in Puerto Rico. I first characterized the motion detection properties of the sensory system of A. gundlachi in the laboratory. I then measured the physical properties of movement-based headbob displays given during staged social encounters under natural conditions. I found a significant positive association between the maximum amplitude of headbob displays and the physical distance to intended receivers. Modulation occurred in response to small-scale changes in signaler-receiver distance, and signalers gave displays that fell within a range of amplitudes predicted to optimally stimulate the visual system of A. gundlachi. These findings strongly suggest that modulation of the physical properties of motion-based signals can be an effective mechanism to tune signals to both characteristics of receiver sensory systems and receiver distance, and can serve as a behavioral strategy to cope with relatively frequent changes in the spacing of individuals.

Although signaling individuals must effectively capture and hold the attention of intended conspecific receivers, they must also limit eavesdropping by potential parasites or predators. However, predation pressure can vary over the course of an individual's lifetime, or over the course of a day, thereby altering signal efficacy. In Chapter 4, I tested the hypothesis that prey can modulate the physical properties of their signals or their display behavior in order to decrease conspicuousness and potentially limit predation risk. To do so, I conducted a manipulative experiment in nature to determine the effect of predation pressure on the properties of movement-based signals and the display rate of the semiarboreal lizard Anolis sagrei. I found that male anoles reduced the maximum amplitude of headbob displays but not the proportion of time spent signaling on islands onto which predators were introduced, in comparison to males from control islands lacking the predator. Characteristics of the motion detection system and social behavior of A. sagrei show that this reduction in amplitude also decreases signal active space, which might alter the reproductive success of signaling individuals. I suggest that future studies of predator-prey interactions consider the risk effects generated by changes in signals or signaling behavior to fully determine the influence of predation pressure on the dynamics of prey populations.

Human activity has resulted in significant increases in air temperature over the last century, and air temperatures are expected to continue rising at an accelerating rate over the next 100 years (IPCC 2007). The warming that has already occurred has had significant impacts on the worlds biota: species ranges are shifting north (or upslope), seasonal phenological events are occurring earlier, disease dynamics are changing, and populations are going extinct (Walther et al. 2002; Parmesan & Yohe 2003; Parmesan 2006; Walther 2010; Pau et al. 2011). Understanding the temperature-dependent biological mechanisms that lead to such changes is a major priority: only with such understanding can we hope to make a concerted effort to mitigate the effects of continuing climatic change.

There are three general biological mechanisms by which organisms can respond to, and potentially buffer themselves from, the direct effects of climate change: 1) physiological plasticity, 2) behavior, and 3) evolution. Here, I refer to physiological plasticity as changes in thermal reaction norms, which include sensitivity to thermal change and tolerance for thermal extremes (Huey & Stevenson 1979). These plastic responses can be reversible (acclimation) or be fixed by developmental or cross-generational non-genetic processes (West-Eberhard 2003; Ghalambor et al. 2007; Angilletta 2009). There appear to be global patterns of plasticity in thermal physiology, as temperate ectotherms tend to be more plastic than tropical ectotherms (Feder 1978; Tsuji 1988; Ghalambor et al. 2006). This difference is hypothesized to result from differences in seasonality: temperate ectotherms can experience a much wider range of thermal conditions than tropical ectotherms, and thus temperate environment might select for plasticity to track changing conditions. If physiological plasticity can buffer organisms from warming (Stillman 2003; Somero 2010), then tropical ectotherms may be at a disadvantage in the face of climate change (Huey et al. 2009).

In general, behavioral responses to thermal challenges can be thought of as occurring on either local or regional scales. At the local scale ectotherms can engage in behavioral thermoregulation, seeking out thermally suitable microhabitats within their home ranges (Bogert 1949; Huey et al. 2003; Kearney et al. 2009). At the regional scale, organisms may shift their ranges by migrating along elevation or latitudinal thermal gradients (usually up or north, respectively) to escape warming (Buckley et al. 2013). The degree to which local- and regional-scale behavioral responses can buffer populations from warming depends on numerous factors. For example, behavioral thermoregulation requires fine-scale thermal variation within the environment. However, habitats such as heavily shaded tropical forests have little thermal heterogeneity, precluding behavioral thermoregulation as an effective buffering mechanism (Huey et al. 2009). On the other hand, range shifts can be hindered by factors such as inherent mobility and natural and man-made barriers (Forero‐Medina et al. 2011). Both behavioral thermoregulation and migration can be hindered by the presence of competitors or antagonistic species such as predators or parasites in thermally favorable locations (Araújo & Luoto 2007).

Most work on the evolution of thermal physiology focuses on the evolution of thermal tolerance limits (i.e., the lower and upper lethal temperature thresholds) (Stillman & Somero 2000; Angilletta et al. 2007; Barrett et al. 2011). Broad-scale comparative analyses have demonstrated that upper thermal limits vary less than lower thermal limits, suggesting that upper thermal limits may be evolutionarily constrained (Kellermann et al. 2012; Araújo et al. 2013; Grigg & Buckley 2013). This pattern is particularly strong looking over terrestrial latitudinal gradients; cold tolerance increases with latitude, but heat tolerance does not change appreciably (Sunday et al. 2012). Artificial selection experiments have demonstrated that the upper thermal tolerances of animals can evolve, but there may be limits to how much they can change (Huey et al. 1991; Loeschcke & Krebs 1996).

Physiology, behavior, and evolution are of course not mutually exclusive mechanisms. As noted above, physiological traits such as tolerance to extreme temperature can evolve, as can behavioral mechanisms. In addition, behavior may promote or inhibit the evolution of physiology. For example, behavioral thermoregulation can potentially inhibit the evolution of thermal physiology because it allows organisms to buffer themselves from thermal change (Huey et al. 2003). Furthermore, the physiological state of an organism can dictate how it behaviorally responds to a given stimulus (Atkins-Regan 2005). For example, lizards that are dehydrated seek out cooler microclimates (Crowley 1987).

My dissertation focuses on the physiological, behavioral, and evolutionary axes of organismal response to climatic challenges, and their interactions, using the arboreal Caribbean lizard Anolis cristatellus as a model system. The general approach that I take throughout each chapter is to consider climatic data and organismal responses to climate at a fine-scale. A recent review and meta-analysis of climate change studies found that, on average, researchers consider climatic data at a scale 10,000X larger then the animals they study (Potter et al. 2013). In other words, we frequently consider the climatic environment very coarsely relative to our focal organisms. Such an approach can yield broad patterns of warming vulnerability over large geographic scales. Nonetheless, much of the climatic variation important to organisms occurs at the scale of meters rather than kilometers (Helmuth et al. 2010). Similarly, broad-scale studies must typically make assumptions about how organisms respond to climatic variation, rather than actually measuring responses. Throughout, I highlight the benefits of working at the scale of the organism.

Chapter 1 is the only chapter that does not deal directly with thermal biology. In it, I investigate whether or not A. cristatellus from mesic and xeric habitats differ in their water loss rates, and ask whether the differences that I observe can be explained by plasticity (Gunderson et al. 2011). In the second chapter, I explore the vulnerability of A. cristatellus to climate warming by integrating behavior and physiology with fine-scale measurements of the thermal environment (Gunderson & Leal 2012). In the third chapter, I investigate the ability of thermal tolerance limits to evolve rapidly in response to climatic change using the recent introduction of A. cristatellus to Miami from Puerto Rico (Leal & Gunderson 2012). In the final chapter, I focus solely on behavior and use A. cristatellus to ask how well current models of thermal constraint on activity predict observed patterns at a fine scale in the field (Gunderson and Leal, in review).