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1. Performance Surface Analysis Identifies Consistent Functional Patterns across 10 Morphologically Divergent Terrestrial Turtle Lineages

   https://doi.org/10.1093/icb/icz072  

   Stayton, C. Tristan (June 2019, Integrative and Comparative Biology)

   Abstract Newly-developed methods for utilizing performance surfaces—multivariate representations of the relationship between phenotype and functional performance—allow researchers to test hypotheses about adaptive landscapes and evolutionary diversification with explicit attention to functional factors. Here, information from performance surfaces of three turtle shell functions—shell strength, hydrodynamics, and self-righting—is used to test the hypothesis that turtle lineages transitioning from aquatic to terrestrial habitats show patterns of shell shape evolution consistent with decreased importance of hydrodynamic performance. Turtle shells are excellent model systems for evolutionary functional analysis. The evolution of terrestriality is an interesting test case for the efficacy of these methods because terrestrial turtles do not show a straightforward pattern of morphological convergence in shell shape: many terrestrial lineages show increased shell height, typically assumed to decrease hydrodynamic performance, but there are also several lineages where the evolution of terrestriality was accompanied by shell flattening. Performance surface analyses allow exploration of these complex patterns and explicit quantitative analysis of the functional implications of changes in shell shape. Ten lineages were examined. Nearly all terrestrial lineages, including those which experienced decreased shell height, are associated with morphological changes consistent with a decrease in the importance of shell hydrodynamics. This implies a common selective pattern across lineages showing divergent morphological patterns. Performance studies such as these hold great potential for integrating adaptive and performance data in macroevolutionary studies. 

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2. Macroevolutionary bursts and constraints generate a rainbow in a clade of tropical birds

   https://doi.org/10.1186/s12862-020-1577-y  

   Merwin, Jon T.; Seeholzer, Glenn F.; Smith, Brian Tilston (December 2020, BMC Evolutionary Biology)

   null (Ed.)

   Abstract Background Bird plumage exhibits a diversity of colors that serve functional roles ranging from signaling to camouflage and thermoregulation. However, birds must maintain a balance between evolving colorful signals to attract mates, minimizing conspicuousness to predators, and optimizing adaptation to climate conditions. Examining plumage color macroevolution provides a framework for understanding this dynamic interplay over phylogenetic scales. Plumage evolution due to a single overarching process, such as selection, may generate the same macroevolutionary pattern of color variation across all body regions. In contrast, independent processes may partition plumage and produce region-specific patterns. To test these alternative scenarios, we collected color data from museum specimens of an ornate clade of birds, the Australasian lorikeets, using visible-light and UV-light photography, and comparative methods. We predicted that the diversification of homologous feather regions, i.e., patches, known to be involved in sexual signaling (e.g., face) would be less constrained than patches on the back and wings, where new color states may come at the cost of crypsis. Because environmental adaptation may drive evolution towards or away from color states, we tested whether climate more strongly covaried with plumage regions under greater or weaker macroevolutionary constraint. Results We found that alternative macroevolutionary models and varying rates best describe color evolution, a pattern consistent with our prediction that different plumage regions evolved in response to independent processes. Modeling plumage regions independently, in functional groups, and all together showed that patches with similar macroevolutionary models clustered together into distinct regions (e.g., head, wing, belly), which suggests that plumage does not evolve as a single trait in this group. Wing patches, which were conserved on a macroevolutionary scale, covaried with climate more strongly than plumage regions (e.g., head), which diversified in a burst. Conclusions Overall, our results support the hypothesis that the extraordinary color diversity in the lorikeets was generated by a mosaic of evolutionary processes acting on plumage region subsets. Partitioning of plumage regions in different parts of the body provides a mechanism that allows birds to evolve bright colors for signaling and remain hidden from predators or adapt to local climatic conditions. 

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3. When Service Times Depend on Customers’ Delays: A Relationship Between Two Models of Dependence

   https://doi.org/10.1287/opre.2021.2179  

   Wu, Chenguang; Bassamboo, Achal; Perry, Ohad (November 2022, Operations Research)

   As empirically observed in restaurants, call centers, and intensive care units, service times needed by customers are often related to the delay they experience in queue. Two forms of dependence mechanisms in service systems with customer abandonment immediately come to mind: First, the service requirement of a customer may evolve while waiting in queue, in which case the service time of each customer is endogenously determined by the system’s dynamics. Second, customers may arrive (exogenously) to the system with a service and patience time that are stochastically dependent, so that the service-time distribution of the customers that end up in service is different than that of the entire customer population. We refer to the former type of dependence as endogenous and to the latter as exogenous. Because either dependence mechanism can have significant impacts on a system’s performance, it should be identified and taken into consideration for performance-evaluation and decision-making purposes. However, identifying the source of dependence from observed data is hard because both the service times and patience times are censored due to customer abandonment. Further, even if the dependence is known to be exogenous, there remains the difficult problem of fitting a joint service-patience times distribution to the censored data. We address these two problems and provide a solution to the corresponding statistical challenges by proving that both problems can be avoided. We show that, for any exogenous dependence, there exists a corresponding endogenous dependence, such that the queuing dynamics under either dependence have the same law. We also prove that there exist endogenous dependencies for which no equivalent exogenous dependence exists. Therefore, the endogenous dependence can be considered as a generalization of the exogenous dependence. As a result, if dependence is observed in data, one can always consider the system as having an endogenous dependence, regardless of the true underlying dependence mechanism. Because estimating the structure of an endogenous dependence is substantially easier than estimating a joint service-patience distribution from censored data, our approach facilitates statistical estimations considerably. Funding: C. A. Wu received financial support from the Hong Kong Research Grant Council [Early Career Scheme, Project 26206419]. A. Bassamboo and O. Perry received partial financial support from the National Science Foundation [Grant CMMI 2006350]. 

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4. The Sins of the Parents Are to Be Laid Upon the Children: Biased Humans, Biased Data, Biased Models

   https://doi.org/10.1177/17456916231180099  

   Osborne, Merrick_R; Omrani, Ali; Dehghani, Morteza (July 2023, Perspectives on Psychological Science)

   Technological innovations have become a key driver of societal advancements. Nowhere is this more evident than in the field of machine learning (ML), which has developed algorithmic models that shape our decisions, behaviors, and outcomes. These tools have widespread use, in part, because they can synthesize massive amounts of data to make seemingly objective recommendations. Yet, in the past few years, the ML community has been drawing attention to the need for caution when interpreting and using these models. This is because these models are created by humans, from data generated by humans, whose psychology allows for various biases that impact how the models are developed, trained, tested, and interpreted. As psychologists, we thus face a fork in the road: Down the first path, we can continue to use these models without examining and addressing these critical flaws and rely on computer scientists to try to mitigate them. Down the second path, we can turn our expertise in bias toward this growing field, collaborating with computer scientists to reduce the models’ deleterious outcomes. This article serves to light the way down the second path by identifying how extant psychological research can help examine and curtail bias in ML models. 

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5. Constraints and Opportunities for the Evolution of Metamorphic Organisms in a Changing Climate

   https://doi.org/10.3389/fevo.2021.734031  

   Suzuki, Yuichiro; Toh, Lyanna (October 2021, Frontiers in Ecology and Evolution)

   null (Ed.)

   We argue that developmental hormones facilitate the evolution of novel phenotypic innovations and timing of life history events by genetic accommodation. Within an individual’s life cycle, metamorphic hormones respond readily to environmental conditions and alter adult phenotypes. Across generations, the many effects of hormones can bias and at times constrain the evolution of traits during metamorphosis; yet, hormonal systems can overcome constraints through shifts in timing of, and acquisition of tissue specific responses to, endocrine regulation. Because of these actions of hormones, metamorphic hormones can shape the evolution of metamorphic organisms. We present a model called a developmental goblet, which provides a visual representation of how metamorphic organisms might evolve. In addition, because developmental hormones often respond to environmental changes, we discuss how endocrine regulation of postembryonic development may impact how organisms evolve in response to climate change. Thus, we propose that developmental hormones may provide a mechanistic link between climate change and organismal adaptation. 

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