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Abstract ThePCMBase Rpackage is a powerful computational tool that enables efficient calculations of likelihoods for a wide range of phylogenetic Gaussian models.Taking advantage of it, we redesigned theRpackagemvSLOUCH.Here, we demonstrate how the new version of the package can be used to thoroughly examine the evolution and adaptation of traits in a large dataset of 1252 vascular plants through the use of multivariate Ornstein–Uhlenbeck processes.The results of our analysis demonstrate the ability of the modelling framework to distinguish between various alternative hypotheses regarding the evolution of functional traits in angiosperms. 

Abstract Adams and Collyer argue that contemporary multivariate (Gaussian) phylogenetic comparative methods are prone to favouring more complex models of evolution and sometimes rotation invariance can be an issue. Here we dissect the concept of rotation invariance and point out that, depending on the understanding, this can be an issue with any method that relies on numerical instead of analytical estimation approaches. We relate this to the ongoing discussion concerning phylogenetic principal component analysis. Contrary to what Adams and Collyer found, we do not observe a bias against the simpler Brownian motion process in simulations when we use the new, improved, likelihood evaluation algorithm employed by mvSLOUCH, which allows for studying much larger phylogenies and more complex model setups. 

Abstract Models based on the Ornstein–Uhlenbeck process have become standard for the comparative study of adaptation. Cooper et al. (2016) have cast doubt on this practice by claiming statistical problems with fitting Ornstein–Uhlenbeck models to comparative data. Specifically, they claim that statistical tests of Brownian motion may have too high Type I error rates and that such error rates are exacerbated by measurement error. In this note, we argue that these results have little relevance to the estimation of adaptation with Ornstein–Uhlenbeck models for three reasons. First, we point out that Cooper et al. (2016) did not consider the detection of distinct optima (e.g. for different environments), and therefore did not evaluate the standard test for adaptation. Second, we show that consideration of parameter estimates, and not just statistical significance, will usually lead to correct inferences about evolutionary dynamics. Third, we show that bias due to measurement error can be corrected for by standard methods. We conclude that Cooper et al. (2016) have not identified any statistical problems specific to Ornstein–Uhlenbeck models, and that their cautions against their use in comparative analyses are unfounded and misleading. [adaptation, Ornstein–Uhlenbeck model, phylogenetic comparative method.] 

Abstract The advent of fast computational algorithms for phylogenetic comparative methods allows for considering multiple hypotheses concerning the co-adaptation of traits and also for studying if it is possible to distinguish between such models based on contemporary species measurements. Here we demonstrate how one can perform a study with multiple competing hypotheses using mvSLOUCH by analyzing two data sets, one concerning feeding styles and oral morphology in ungulates, and the other concerning fruit evolution in Ferula (Apiaceae). We also perform simulations to determine if it is possible to distinguish between various adaptive hypotheses. We find that Akaike’s information criterion corrected for small sample size has the ability to distinguish between most pairs of considered models. However, in some cases there seems to be bias towards Brownian motion or simpler Ornstein–Uhlenbeck models. We also find that measurement error and forcing the sign of the diagonal of the drift matrix for an Ornstein–Uhlenbeck process influences identifiability capabilities. It is a cliché that some models, despite being imperfect, are more useful than others. Nonetheless, having a much larger repertoire of models will surely lead to a better understanding of the natural world, as it will allow for dissecting in what ways they are wrong. [Adaptation; AICc; model selection; multivariate Ornstein–Uhlenbeck process; multivariate phylogenetic comparative methods; mvSLOUCH.] 

Background and aims – Tracheophyte leaf morphology is well studied but it is unclear if the findings generalize to poikilohydric plants. We tested combinations of hypotheses to determine if microhabitat characteristics, including light exposure, moisture availability, and substrate slope, controlled for morphological differences between upright and prostrate growth forms, affect phyllid surface area and costa length of mosses.Material and methods – We quantified mean phyllid surface-area and costa lengths for four replicates of 38 moss species from Alabama. Phylogenetic comparative methods that model adaptation were used to evaluate the relative evidence for each hypothesis using information criteria. To further explore mechanistic explanations involving substrate slope, we tested whether mosses on vertical substrates differed from those on horizontal substrates in the average amount of water-retaining, nutrient-rich litter they accumulated.Key results – Substrate slope and growth form combined were the best predictors of phyllid surface area. Mosses growing on vertical substrates exhibited smaller phyllid surface area for both growth forms. Although growth form and phyllid length best explained costa length variation, a more complex model including substrate slope performed nearly as well. Within the prostrate growth forms, species growing on vertical substrates exhibit longer relative costa than those on horizontal substrates. We also estimated rapid rates of adaptation for both traits.Conclusion – The smaller phyllid surface area of both upright and prostrate growth forms is possibly an adaptive response to reduced habitat moisture-retention or nutrient quality that vertical substrates offer. The longer costa lengths of prostrate mosses growing on vertical surfaces relative to prostrate mosses on horizontal surfaces, possibly make up for the decreased ability of smaller phyllids to rapidly reabsorb water when it is available. Further work is required to determine if it is truly substrate slope itself that matters or other variables associated with the differences in slope, and to determine how general this phenomenon is. 

Abstract Microbial diversity positively influences community resilience of the host microbiome. However, extinction risk factors such as habitat specialization, narrow environmental tolerances, and exposure to anthropogenic disturbance may homogenize host-associated microbial communities critical for stress responses including disease defense. In a dataset containing 43 threatened and 90 non-threatened amphibian species across two biodiversity hotspots (Brazil’s Atlantic Forest and Madagascar), we found that threatened host species carried lower skin bacterial diversity, after accounting for key environmental and host factors. The consistency of our findings across continents suggests the broad scale at which low bacteriome diversity may compromise pathogen defenses in species already burdened with the threat of extinction.