One size does not fit all: variation in thermal eco-physiology among Pacific salmonids

Reviews in Fish Biology and Fisheries - Pacific salmonids, cold-water fishes native to the northern hemisphere, span a massive geographic range (~?33° latitude) and are exposed to a wide...     

One size does not fit all: no evidence for an optimal body size on islands

Aim Optimal body size theories predict that large clades have a single, optimal, body size that serves as an evolutionary attractor, with the full body size spectrum of a clade resulting from interspecific competition. Because interspecific competition is believed to be reduced on islands, such theories predict that insular animals should be closer to the optimal size than mainland animals. We test the resulting prediction that insular clade members should therefore have narrower body size ranges than their mainland relatives. Location World‐wide. Methods We used body sizes and a phylogenetic tree of 4004 mammal species, including more than 200 species that went extinct since the last ice age. We tested, in a phylogenetically explicit framework, whether insular taxa converge on an optimal size and whether insular clades have narrow size ranges. Results We found no support for any of the predictions of the optimal size theory. No specific size serves as an evolutionary attractor. We did find consistent evidence that large (> 10 kg) mammals grow smaller on islands. Smaller species, however, show no consistent tendency to either dwarf or grow larger on islands. Size ranges of insular taxa are not narrower than expected by chance given the number of species in their clades, nor are they narrower than the size ranges of their mainland sister clades – despite insular clade members showing strong phylogenetic clustering. Main conclusions The concept of a single optimal body size is not supported by the data that were thought most likely to show it. We reject the notion that inclusive clades evolve towards a body‐plan‐specific optimum.     

One size does not fit all: Customizing MCMC methods for hierarchical models using NIMBLE

Improved efficiency of Markov chain Monte Carlo facilitates all aspects of statistical analysis with Bayesian hierarchical models. Identifying strategies to improve MCMC performance is becoming increasingly crucial as the complexity of models, and the run times to fit them, increases. We evaluate different strategies for improving MCMC efficiency using the open‐source software NIMBLE (R package nimble) using common ecological models of species occurrence and abundance as examples. We ask how MCMC efficiency depends on model formulation, model size, data, and sampling strategy. For multiseason and/or multispecies occupancy models and for N‐mixture models, we compare the efficiency of sampling discrete latent states vs. integrating over them, including more vs. fewer hierarchical model components, and univariate vs. block‐sampling methods. We include the common MCMC tool JAGS in comparisons. For simple models, there is little practical difference between computational approaches. As model complexity increases, there are strong interactions between model formulation and sampling strategy on MCMC efficiency. There is no one‐size‐fits‐all best strategy, but rather problem‐specific best strategies related to model structure and type. In all but the simplest cases, NIMBLE's default or customized performance achieves much higher efficiency than JAGS. In the two most complex examples, NIMBLE was 10–12 times more efficient than JAGS. We find NIMBLE is a valuable tool for many ecologists utilizing Bayesian inference, particularly for complex models where JAGS is prohibitively slow. Our results highlight the need for more guidelines and customizable approaches to fit hierarchical models to ensure practitioners can make the most of occupancy and other hierarchical models. By implementing model‐generic MCMC procedures in open‐source software, including the NIMBLE extensions for integrating over latent states (implemented in the R package nimbleEcology), we have made progress toward this aim.     

Metabolic equivalent: one size does not fit all.

The metabolic equivalent (MET) is a widely used physiological concept that represents a simple procedure for expressing energy cost of physical activities as multiples of resting metabolic rate (RMR). The value equating 1 MET (3.5 ml O2 x kg(-1) x min(-1) or 1 kcal x kg(-1) x h(-1)) was first derived from the resting O2 consumption (VO2) of one person, a 70-kg, 40-yr-old man. Given the extensive use of MET levels to quantify physical activity level or work output, we investigated the adequacy of this scientific convention. Subjects consisted of 642 women and 127 men, 18-74 yr of age, 35-186 kg in weight, who were weight stable and healthy, albeit obese in some cases. RMR was measured by indirect calorimetry using a ventilated hood system, and the energy cost of walking on a treadmill at 5.6 km/h was measured in a subsample of 49 men and 49 women (26-45 kg/m2; 29-47 yr). Average VO2 and energy cost corresponding with rest (2.6 +/- 0.4 ml O2 x kg(-1) x min(-1) and 0.84 +/- 0.16 kcal x kg(-1) x h(-1), respectively) were significantly lower than the commonly accepted 1-MET values of 3.5 ml O2 x kg(-1) x min(-1) and 1 kcal x kg(-1) x h(-1), respectively. Body composition (fat mass and fat-free mass) accounted for 62% of the variance in resting VO2 compared with age, which accounted for only 14%. For a large heterogeneous sample, the 1-MET value of 3.5 ml O2 x kg(-1) x min(-1) overestimates the actual resting VO2 value on average by 35%, and the 1-MET of 1 kcal/h overestimates resting energy expenditure by 20%. Using measured or predicted RMR (ml O2 x kg(-1) x min(-1) or kcal x kg(-1) x h(-1)) as a correction factor can appropriately adjust for individual differences when estimating the energy cost of moderate intensity walking (5.6 km/h).     

One size does not fit all: flexible models are required to understand animal movement across scales

1. Large data sets containing precise movement data from free-roaming animals are now becoming commonplace. One means of analysing individual movement data is through discrete, random walk-based models. 2. Random walk models are easily modified to incorporate common features of animal movement, and the ways that these modifications affect the scaling of net displacement are well studied. Recently, ecologists have begun to explore more complex statistical models with multiple latent states, each of which are characterized by a distribution of step lengths and have their own unimodal distribution of turning angles centred on one type of turn (e.g. reversals). 3. Here, we introduce the compound wrapped Cauchy distribution, which allows for multimodal distributions of turning angles within a single state. When used as a single state model, the parameters provide a straightforward summary of the relative contributions of different turn types. The compound wrapped Cauchy distribution can also be used to build multiple state models. 4. We hypothesize that a multiple state model with unimodal distributions of turning angles will best describe movement at finer resolutions, while a multiple state model using our multimodal distribution will better describe movement at intermediate temporal resolutions. At coarser temporal resolutions, a single state model using our multimodal distribution should be sufficient. We parameterize and compare the performance of these models at four different temporal resolutions (1, 4, 12 and 24 h) using data from eight individuals of Loxodonta cyclotis and find support for our hypotheses. 5. We assess the efficacy of the different models in extrapolating to coarser temporal resolution by comparing properties of data simulated from the different models to the properties of the observed data. At coarser resolutions, simulated data sets recreate many aspects of the observed data; however, only one of the models accurately predicts step length, and all models underestimate the frequency of reversals. 6. The single state model we introduce may be adequate to describe movement data at many resolutions and can be interpreted easily. Multiscalar analyses of movement such as the ones presented here are a useful means of identifying inconsistencies in our understanding of movement.     

Targeting mTOR with rapamycin: One dose does not fit all

A puzzling aspect of rapamycin-based therapeutic strategies is the wide disparity in the doses needed to suppress mTOR under different circumstances. A recent study revealing mechanistically how rapamycin suppresses mTOR provides two explanations for the differential sensitivities to rapamycin. First, mTOR exists as two functionally distinct complexes (mTORC1 and mTORC2), and while rapamycin suppresses both, it does so at very different concentrations. Whereas mTORC1 is suppressed by concentrations of rapamycin in the low nM range, mTORC2 generally requires low μM concentrations. Second, the efficacy of rapamycin is dependent on the level of phosphatidic acid (PA), which is required for the assembly of both mTORC1 and mTORC2 complexes. Rapamycin interacts with mTOR in a manner that is competitive with PA. Therefore, elevated levels of PA, which is common in cancer cells, increases the level of rapamycin needed to suppress both mTORC1 and mTORC2. A practical outcome of the recent study is that if PA levels are suppressed, mTORC2 becomes sensitive to concentrations of rapamycin that can be achieved clinically. Since mTORC2 is likely more critical for survival signals in cancer cells, the recent findings suggest new strategies for enhancing the efficacy of rapamycin-based therapeutic approaches in cancer cells.     

Variation in heteroploid reproduction and gene flow across a polyploid complex: One size does not fit all

Whole‐genome duplication is considered an important speciation mechanism in plants. However, its effect on reproductive isolation between higher cytotypes is not well understood. We used backcrosses between different ploidy levels and surveys of mixed‐ploidy contact zones to determine how reproductive barriers differed with cytotype across a polyploid complex. We backcrossed F1 hybrids derived from 2X‐4X and 4X‐6X crosses in the Campanula rotundifolia autopolyploid complex, measured backcross fitness, and estimated backcross DNA cytotype. We then sampled four natural mixed‐ploidy contact zones (two 2X‐4X and two 4X‐6X), estimated ploidy, and genotyped individuals across each contact zone. Reproductive success and capacity for gene flow was markedly lower for 2X‐4X than 4X‐6X hybrids. In fact, 3X hybrids could not backcross; all 2X‐4X backcross progeny resulted from neotetraploid F1 hybrids. Further, no 3X individuals were found in 2X‐4X contact zones, and 2X and 4X individuals were genetically distinct. By contrast, backcrosses of 5X hybrids were relatively successful, particularly when crossed to 6X individuals. In 4X‐6X contact zones, 5X individuals and aneuploids were common and all cytotypes were largely genetically similar and spatially intermixed. Taken together, these results provide strong evidence that reproduction is low between 2X and 4X cytotypes, primarily occurring via unreduced gamete production, but that reproduction and gene flow are ongoing between 4X and 6X cytotypes. Further, it suggests whole‐genome duplication can result in speciation between diploids and polyploids, but is less likely to create reproductive barriers between different polyploid cytotypes, resulting in two fundamentally different potentials for speciation across polyploid complexes.

To assess the role of ploidy in determining reproductive isolation and speciation in polyploid contact zones, we used backcrosses between different ploidy levels and surveys of mixed‐ploidy contact zones to determine how reproductive barriers differed with cytotype across a polyploid complex. Reproductive success and capacity for gene flow was markedly higher for 4X‐6X hybrids than 2X‐4X hybrids, which was also seen in natural mixed‐ploidy contact zones. Our results suggest whole‐genome duplication can result in speciation between diploids and polyploids, but is less likely to create reproductive barriers between different polyploid cytotypes, resulting in two fundamentally different potentials for speciation across polyploid complexes.     

One size does not fit all: On how Markov model order dictates performance of genomic sequence analyses

The structural simplicity and ability to capture serial correlations make Markov models a popular modeling choice in several genomic analyses, such as identification of motifs, genes and regulatory elements. A critical, yet relatively unexplored, issue is the determination of the order of the Markov model. Most biological applications use a predetermined order for all data sets indiscriminately. Here, we show the vast variation in the performance of such applications with the order. To identify the ‘optimal’ order, we investigated two model selection criteria: Akaike information criterion and Bayesian information criterion (BIC). The BIC optimal order delivers the best performance for mammalian phylogeny reconstruction and motif discovery. Importantly, this order is different from orders typically used by many tools, suggesting that a simple additional step determining this order can significantly improve results. Further, we describe a novel classification approach based on BIC optimal Markov models to predict functionality of tissue-specific promoters. Our classifier discriminates between promoters active across 12 different tissues with remarkable accuracy, yielding 3 times the precision expected by chance. Application to the metagenomics problem of identifying the taxum from a short DNA fragment yields accuracies at least as high as the more complex mainstream methodologies, while retaining conceptual and computational simplicity.     

One strategy does not fit all: determinants of urban adaptation in mammals

Urbanisation exposes wildlife to new challenging conditions and environmental pressures. Some mammalian species have adapted to these novel environments, but it remains unclear which characteristics allow them to persist. To address this question, we identified 190 mammals regularly recorded in urban settlements worldwide, and used phylogenetic path analysis to test hypotheses regarding which behavioural, ecological and life history traits favour adaptation to urban environments for different mammalian groups. Our results show that all urban mammals produce larger litters; whereas other traits such as body size, behavioural plasticity and diet diversity were important for some but not all taxonomic groups. This variation highlights the idiosyncrasies of the urban adaptation process and likely reflects the diversity of ecological niches and roles mammals can play. Our study contributes towards a better understanding of mammal association to humans, which will ultimately allow the design of wildlife‐friendly urban environments and contribute to mitigate human‐wildlife conflicts.