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In a previous paper, we used simulations and empirical data to show that BAMM (Bayesian Analysis of Macroevolutionary Mixtures) can give misleading estimates of rates and rate shifts. In simulations, BAMM underestimated rate shifts across every tree analyzed, and assigned incorrect rates to most clades in most trees. In empirical analyses, BAMM behaved as expected from simulations, and assigned different rates to clades when clades were analyzed alone versus across the tree (i.e., with rate heterogeneity). Rabosky recently criticized our paper, focusing primarily on the idea that our comparison of BAMM to another approach (methodof-moments estimators of Magallón and Sanderson, or MS estimators) was unfair to BAMM. Here, we provide further evidence that BAMM gives misleading rate estimates in empirical studies. We then describe how Rabosky’s rown method comparisons were either acknowledged as being problematic or were described inaccurately (to favor BAMM). Finally, we show that the MS estimators can perform well when rates vary over time, despite untested assertions that they require constant rates to be accurate. Many other methods are available for analyzing diversification rates: we argue that BAMM should be avoided for estimating both diversification rates and rate shifts.

The software program BAMM has been widely used to study rates of speciation, extinction, and phenotypic evolution on phylogenetic trees. The program implements a model-based clustering algorithm to identify clades that share common macroevolutionary rate dynamics and to estimate parameters. A recent simulation study by Meyer and Wiens (M & W) argued that (1) a simple inference framework (MS) performs much better than BAMM, and (2) evolutionary rates inferred with BAMM are poorly correlated with true rates. I address two statistical concerns with their assessment that affect the generality of their conclusions. These considerations are not specific to BAMM and apply to other methods for estimating parameters from empirical data where the true grouping structure of the data is unknown. M & W constrain roughly half of the parameters in their MS analyses to their true values, but BAMM is given no such information and must estimate all parameters from the data. This information disparity results in a substantial degrees of freedom advantage for the MS estimators. When both methods are given equivalent information, BAMM outperforms the MS estimators.

Our 2020 Educational Researcher article, \"The Imperative of Social Foundations to (Urban) Education Research and Practice,\" emphasizes three particular social foundations of education (SFE) subdisciplines (sociology of education, history of education, and philosophy of education) to demonstrate the strength and necessity of SFE as a multi-perspectival approach to resolving persistent education justice dilemmas. In their technical comment, Aydarova et al. (2022) insist that our article potentially facilitates \"erasure of SFE's complexity and interdisciplinarity\" (p. 289). They, like us, care deeply that SFE be understood as indispensable to advancing racial justice in and beyond education research, policy, and practice. These scholars foreground the invaluable contributions of anthropology of education to oppose racism and accentuate justice-oriented education alternatives. This essay responds to the technical comment by clarifying what we find to be a fundamental misinterpretation of our argument and, ultimately, its scholarly purpose. Not only do we contend with our colleagues' concern that our work is reductionist, we demonstrate how Aydarova et al.'s urgent call to foreground SFE's interdisciplinary nature further underscores the central argument made in our 2020 paper.

Males and females have different optimal values for some traits, such as body size. When the same genes control these traits in both sexes, selection pushes in opposite directions in males and females. Alleles at autosomal loci spend equal amounts of time in males and females, suggesting that the sexually antagonistic selective forces may approximately balance between the opposing optima. Frank and Crespi noted that alleles on the X chromosome spend twice as much time in diploid females as in haploid males. That distinction between the sexes may tend to favor X-linked genes that push more strongly toward the female optimum than the male optimum. The female bias of X-linked genes opposes the intermediate optimum of autosomal genes, potentially creating a difference between the direction of selection on traits favored by X chromosomes and autosomes. Patten has recently argued that explicit genetic assumptions about dominance and the relative magnitude of allelic effects may lead X-linked genes to favor the male rather than the female optimum, contradicting Frank and Crespi. This article combines the insights of those prior analyses into a new, more general theory. We find some parameter combinations for X-linked loci that favor a female bias and other parameter combinations that favor a male bias. We conclude that the X likely contains a mosaic pattern of loci that differ with autosomes over sexually antagonistic traits. The overall tendency for a female or male bias on the X depends on prior assumptions about the distribution of key parameters across X-linked loci. Those parameters include the dominance coefficient and the way in which ploidy influences the magnitude of allelic effects.

Lipid peroxidation products are widely used as markers of oxidative damage in the organism. To properly interpret the information provided by these markers, it is necessary to know potential sources of bias and control confounding factors. Here, we investigated the relationship between two indicators of lipid mobilization (circulating levels of triglycerides and cholesterol) and two common markers of oxidative damage (plasma levels of malondialdehyde and hydroperoxides; the latter estimated from the d-ROMs assay kit). The following five avian species were studied: red-legged partridge (Alectoris rufa), zebra finch (Taeniopygia guttata), spotless starling (Sturnus unicolor), marsh harrier (Circus aeroginosus), and Montagu’s harrier (Circus pygargus). In all cases, plasma triglyceride levels positively and significantly correlated with lipid peroxidation markers, explaining between 8% and 34% of their variability. Plasma cholesterol, in contrast, showed a significant positive relationship only among spotless starling nestlings and a marginally significant association in zebra finches. These results indicate that lipid peroxidation marker levels covary with circulating lipid levels. We discuss the potential causes and implications of this covariation and recommend that future studies that measure oxidative damage using lipid peroxidation markers report both raw and relative levels (i.e., corrected for circulating triglycerides). Whether the observed pattern also holds for other tissues and in other taxa would deserve further research.

When working with a citizen science database like eBird, there are many possible ways to filter or subsample observations. Here, we discuss the potential biases and assumptions that surround different subsampling approaches or filtering that can be done to the eBird database. Restricting observations to species that are known to frequently hybridize, a specific time of the year, or a specific location, has the potential to greatly inflate the calculated per-individual rate of hybridization. Such filtering also assumes that researchers know a birds’ capacity to hybridize with all other species in its range, which we argue is an unfounded assumption. We ultimately conclude that a limited filtering approach is ideal when using a citizen science database to attempt to address a broad question such as: what is the per individual rate of hybridization across all of the bird species in the United States?

Hybridization has important effects on the evolutionary trajectories of natural populations but estimates of this process in the wild and at the individual-level are lacking. Justyn et al. attempted to fill this gap using the citizen science database eBird but there are limitations to this approach. Here, we outline and directly test these limitations using literature searches, case studies, and a comparison between eBird and Birds of North America (BNA), a database that documents hybridization using the scientific literature. We use a hybrid zone between Lazuli and Indigo buntings to highlight the importance of considering geographic range when estimating rates of hybridization and two literature searches to show the importance of considering cryptic hybrids (those that cannot be identified using phenotypic traits) when quantifying these rates. We also use BNA and a case study of hybrid Whitefaced and Glossy Ibises to show that citizen scientists are underreporting hybrids compared with experts. Justyn et al. highlighted an important gap in the literature, but their results likely represent the lower limit of hybridization between birds and a more nuanced interpretation of their results (e.g., considering extrinsic postzygotic selection) is needed.

Genomic evidence of introgression in natural populations has reinvigorated the study of hybridization in recent years. Still, it is largely unknown how frequently individual organisms mate across species lines. Recently, Justyn et al. suggested that eBird, one of the world’s largest citizen science databases, may supply adequate data for estimating hybridization rates. Here, we compare Justyn et al.’s estimates—and their conclusions that hybridization is rare—with estimates from museum and molecular data. We also estimate hybridization using eBird observations from areas and times when hybridization is possible, namely, in contact zones during the breeding season. These estimates are all considerably higher than those reported in Justyn et al., emphasizing that inferences from multiple datasets can differ radically. Finally, we demonstrate an approach for predicting the location of hybrid zones using eBird data, which can be done with high confidence and with unprecedented resolution. We show that citizen science data, far from settling the question of how frequently bird species hybridize, instead offer a promising step toward more focused study of hybrid zones.

Researchers commonly measure body, orifice, or skin temperature (collectively referred to as body temperature [T b] herein) of endothermic animals in biomedical, physiological, evolutionary, and ecological studies. However, comparing T b among species or placing a single study in context is challenging because there is no single, standard method to describe and synthesize T b data of endotherms. A variety of metrics are available, and each has strengths and weaknesses appropriate for answering different types of questions. Importantly, choosing the wrong metric to address the question posed can lead to misinterpretations and misleading presentation of T b data. Here I review standard metrics used to describe central tendencies and variation in T b of endothermic species, focusing on important strengths and weaknesses and suggested questions to be addressed using each metric. One of the most common mistakes in analyzing T b data is mismatching the analytical metric and the question being asked, so, ultimately, individual researchers need to determine which is most appropriate for addressing their question based on the implications of using each metric.