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Abstract Species must adapt to persist in a changing world. As global temperatures rise, how species adapt and respond to thermal shifts is crucial for anticipating global patterns of biodiversity change. Land vertebrates can be divided into two major thermoregulatory strategies, endothermy and ectothermy. One might hypothesize that, given their reputation as being “cold blooded,” ectotherms are thermal generalists, capable of operating across a greater range of body temperatures than endotherms and exhibit greater plasticity and evolvability in body temperature. However, a wide variety of traits and ecologies could modulate responses of thermal physiology to environmental change. Here, we employ macroevolutionary models to estimate the rate of adaptation of thermal physiology across squamates, mammals, and birds in the context of their ecology, physiology, and changing climatic conditions and whether there are fundamental differences in how the three clades respond to their environments. We find stronger relationships between squamates’ body temperature and their environment than in birds and mammals, significant effects of diel activity (nocturnal and diurnal) on body temperature evolution in all clades, and no effect of aquatic/terrestrial habits and rumination on the evolution of body temperature in mammals. Most surprisingly, our findings suggest shared limits on the evolution of thermal physiology across ectothermic and endothermic groups that argue for universal constraints on the rate of evolution in thermal physiology while explaining disparate patterns of body temperature and niche evolution across groups. 

Phylogenetic comparative methods often rely on simplifying complex biological traits into discrete categories, potentially obscuring evolutionary patterns and generally limiting inferences. This dissertation confronts this ``map versus territory" problem by developing and evaluating methodological approaches that integrate known and unknown trait complexity into macroevolutionary analyses. To establish the statistical power of discrete methods in detecting trait complexity, I first demonstrate the utility of structured hidden Markov models (SHMMs) for identifying underlying continuous architectures, like threshold traits, within simulated and empirical discrete datasets (Chapter ref{ch:1}). Taking bird migration as an example of a hard-to-measure complex trait, I then develop new continuous metrics of bird movement from large-scale community science (eBird) data, using entropy-based measures and phylogenetically aligned component analysis (PACA) to reveal a multi-dimensional structure of evolutionarily relevant combinations of traits, representing underlying movement behavior in North American birds (Chapter ref{ch:2}). Next, I fit SHMMs informed by this structure to global and North American bird phylogenies, testing hypotheses about how migration may have evolved, while accounting for classification ambiguity (Chapter ref{ch:3}). I show that models incorporating hidden states that imitate the structure from Chapter ref{ch:2} were often preferred over generalized hidden Markov models and standard Markov models, suggesting that migration both contains hidden complexity and evolves along specific pathways. Overall, this dissertation provides a methodological framework for integrating continuous data and theoretical knowledge into discrete trait analyses, demonstrating a more holistic treatment of how to treat complex discretized traits like avian migration in phylogenetic comparative methods. 

Vertebrate life histories evolve in response to selection imposed by abiotic and biotic environmental conditions while being limited by genetic, developmental, physiological, demographic and phylogenetic processes that constrain adaptation. Despite the well-recognized shifts in selective pressures accompanying transitions among environments, the conditions driving innovation and the consequences for life-history evolution remain outstanding questions. Here we compare the traits of vertebrates that occupy aquatic or terrestrial environments as juveniles to infer shifts in evolutionary constraints that explain differences in their life-history traits and thus their fundamental demographic rates. Our results emphasize the reduced potential for life-history diversification on land, especially that of reproductive strategies, which limits the scope of viable life-history strategies. Moreover, our study reveals differences between the evolution of viviparity in aquatic and terrestrial realms. Transitions from egg laying to live birth represent a major shift across life-history space for aquatic organisms, whereas terrestrial egg-laying organisms evolve live birth without drastic changes in life-history strategy. Whilst trade-offs in the allocation of resources place fundamental constraints on the way life histories can vary, ecological setting influences the position of species within the viable phenotypic space available for adaptive evolution. 

Macroevolutionary biologists have classically rejected the notion that higher-level patterns of divergence arise through microevolutionary processes acting within populations. For morphology, this consensus partly derives from the inability of quantitative genetics models to correctly predict the behaviour of evolutionary processes at the scale of millions of years. Developmental studies (evo-devo) have been proposed to reconcile micro- and macroevolution. However, there has been little progress in establishing a formal framework to apply evo-devo models of phenotypic diversification. Here we reframe this issue by asking whether using evo-devo models to quantify biological variation can improve the explanatory power of comparative models, thus helping us bridge the gap between micro- and macroevolution. We test this prediction by evaluating the evolution of primate lower molars in a comprehensive dataset densely sampled across living and extinct taxa. Our results suggest that biologically informed morphospaces alongside quantitative genetics models allow a seamless transition between the micro- and macroscales, whereas biologically uninformed spaces do not. We show that the adaptive landscape for primate teeth is corridor like, with changes in morphology within the corridor being nearly neutral. Overall, our framework provides a basis for integrating evo-devo into the modern synthesis, allowing an operational way to evaluate the ultimate causes of macroevolution. 

Explaining broad molecular, phenotypic and species biodiversity patterns necessitates a unifying framework spanning multiple evolutionary scales. Here we argue that although substantial effort has been made to reconcile microevolution and macroevolution, much work remains to identify the links between biological processes at play. We highlight four major questions of evolutionary biology whose solutions require conceptual bridges between micro and macroevolution. We review potential avenues for future research to establish how mechanisms at one scale (drift, mutation, migration, selection) translate to processes at the other scale (speciation, extinction, biogeographic dispersal) and vice versa. We propose ways in which current comparative methods to infer molecular evolution, phenotypic evolution and species diversification could be improved to specifically address these questions. We conclude that researchers are in a better position than ever before to build a synthesis to understand how microevolutionary dynamics unfold over millions of years. 

A central challenge for biology is to reveal how different levels of biological variation interact and shape diversity. However, recent experimental studies have indicated that prevailing models of evolution cannot readily explain the link between micro- and macroevolution at deep timescales. Here, we suggest that this paradox could be the result of a common mechanism driving a correlated pattern of evolution. We examine the proportionality between genetic variance and patterns of trait evolution in a system whose developmental processes are well understood to gain insight into how such alignment between morphological divergence and genetic variation might be maintained over macroevolutionary time. Primate molars present a model system by which to link developmental processes to evolutionary dynamics because of the biased pattern of variation that results from the developmental architecture regulating their formation. We consider how this biased variation is expressed at the population level, and how it manifests through evolution across primates. There is a strong correspondence between the macroevolutionary rates of primate molar divergence and their genetic variation. This suggests a model of evolution in which selection is closely aligned with the direction of genetic variance, phenotypic variance, and the underlying developmental architecture of anatomical traits. 

The prevalence of stasis on macroevolution has been classically taken as evidence of the strong role of stabilizing selection in constraining morphological change. Rates of evolution calculated over longer timescales tend to fall below the expected under genetic drift, suggesting that directional selection signals are erased at longer timescales. Here, we investigated the rates of morphological evolution of the skull in a fossil lineage that underwent extreme morphological modification, the glyptodonts. Contrary to what was expected, we show here that directional selection was the primary process during the evolution of glyptodonts. Furthermore, the reconstruction of selection patterns shows that traits selected to generate a glyptodont morphology are markedly different from those operating on extant armadillos. Changes in both direction and magnitude of selection are probably tied to glyptodonts' invasion of a specialist-herbivore adaptive zone. These results suggest that directional selection might have played a more critical role in the evolution of extreme morphologies than previously imagined. 

Evolutionary rates play a central role in connecting micro- and macroevolution. All evolutionary rate estimates, including rates of molecular evolution, trait evolution, and lineage diversification, share a similar scaling pattern with time: The highest rates are those measured over the shortest time interval. This creates a disconnect between micro- and macroevolution, although the pattern is the opposite of what some might expect: Patterns of change over short timescales predict that evolution has tremendous potential to create variation and that potential is barely tapped by macroevolution. In this review, we discuss this shared scaling pattern across evolutionary rates. We break down possible explanations for scaling into two categories, estimation error and model misspecification, and discuss how both apply to each type of rate. We also discuss the consequences of this ubiquitous pattern, which can lead to unexpected results when comparing ratesover different timescales. Finally, after addressing purely statistical concerns, we explore a few possibilities for a shared unifying explanation across the three types of rates that results from a failure to fully understand and account for how biological processes scale over time.