Evolution of Static Allometry and Constraint on Evolutionary Allometry in a Fossil Stickleback

Allometric scaling describes the relationship of trait size to body size within and among taxa. The slope of the population-level regression of trait size against body size (i.e. static allometry) is typically invariant among closely related populations and species. Such invariance is commonly interpreted to reflect a combination of developmental and selective constraints that delimit a phenotypic space into which evolution could proceed most easily. Thus, understanding how allometric relationships do eventually evolve is important to understanding phenotypic diversification. In a lineage of fossil Threespine Stickleback (Gasterosteus doryssus), we investigated the evolvability of static allometric slopes for nine traits (five armour and four non-armour) that evolved significant trait differences across 10 samples over 8500 years. The armour traits showed weak static allometric relationships and a mismatch between those slopes and observed evolution. This suggests that observed evolution in these traits was not constrained by relationships with body size, perhaps because prior, repeated adaptation to freshwater habitats by Threespine Stickleback had generated strong selection to break constraint. In contrast, for non-armour traits, we found stronger allometric relationships. Those allometric slopes did evolve on short time scales. However, those changes were small and fluctuating and the slopes remained strong predictors of the evolutionary trajectory of trait means over time (i.e. evolutionary allometry), supporting the hypothesis of allometry as constraint

Does lack of evolvability constrain adaptation? If so, on what time scales?

The relevance of genetic constraints for evolutionary change beyond microevolutionary timescales is debated. The high evolvability of natural populations predicts rapid adaptation, but evolvability is often found to correlate with phenotypic divergence on longer timescales, which makes sense if evolvability constraints divergence. This chapter attempts to reconcile the observation of high evolvability of ppulations with the idea that genetig constraints may still be relevant on long timescales. We first establish that a relationship between evolvability and divergence is a common empirical phenomenon but among populations within species (microevolution) and among species (macroevolution), We then argue that a satisfactory model for the prevalence of this empirical relationship is lacking. Linking microevolutionary theory of phenotypic change on macroevolution timescales - is key to better understanding the relative importance of genetic constraints on phenotypic evolution beyond a handful generations.publishedVersio

Bryozoan genera Fenestrulina and Microporella no longer confamilial; multi-gene phylogeny supports separation

Bryozoans are a moderately diverse, mostly marine phylum with a fossil record extending to the early Ordovician. Compared to other phyla, little is known about their phylogenetic relationships at both lower and higher taxonomic levels. Hence, an effort is being made to elucidate the phylogenetic relationships among bryozoans. Here, we present newly sequenced nuclear and mitochondrial genes for 21 cheilostome bryozoans and compile these with existing orthologous molecular data. Using these data, we focus on reconstructing the phylogenetic relationships of Fenestrulina and Microporella, two species-rich genera. They are currently placed in a globally distributed family, Microporellidae, defined by having a semicircular primary orifice and a proximal ascopore, although there are indirect inferences in the morphological literature that suggest they might not be confamilial. Our six-gene phylogenetic analysis reveals that the genera Fenestrulina and Microporella are each monophyletic, with the sister clade to Microporella comprising non-microporellids. These genera thus have a polyphyletic relationship and should not be placed in the same family. Our result supports the reinstatement of the family Fenestrulinidae Jullien, 1888 for Fenestrulina and genera with comparable frontal shield and ooecial morphologies. Our well-supported phylogeny based on independent molecular data lends credit to existing phylogenetic hypotheses based on morphological observations but does not conform to the current classification of these particular bryozoans. This illustrates the general need for a rethink of bryozoan higher-level systematics, ideally based on both morphological and molecular data

Scaling of morphological characters across trait type, sex, and environment: A meta-analysis of static allometries

Biological diversity is, to a large extent, a matter of variation in size. Proportional (isometric) scaling, where large and small individuals are magnified versions of each other, is often assumed to be the most common way morphological traits scale relative to overall size within species. However, the many traits showing nonproportional (allometric) scaling have motivated some of the most discussed hypotheses on scaling relationships in biology, like the positive allometry hypothesis for secondary sexual traits and the negative allometry hypothesis for genitals. I evaluate more than 3,200 allometric parameters from the literature and find that negative allometry, not isometry, is the expected scaling relationship of morphological traits within species. Slopes of secondary sexual traits are more often steeper compared with other traits, but slopes larger than unity are also common for traits not under sexual selection. The steepness of the allometric slope is accordingly a weak predictor of past and present patterns of selection. Scaling of genitals varies across taxonomic groups, but negative allometry of genitals in insects and spiders is a consistent pattern. Finally, I find indications that terrestrial organisms may have a different scaling of morphological traits overall compared with aquatic species. © 2015 University of Chicago Pres

Testing eco‐evolutionary predictions using fossil data: Phyletic evolution following ecological opportunity.

Fossil sequences provide observations of phenotypes within a lineage over time and represent essential data for increasing our understanding of phyletic evolution beyond microevolutionary timescales. I investigate if fossil time series of the diatom Stephanodiscus niagarae/yellowstonensis follow evolutionary dynamics compatible with hypotheses for how the adaptive landscape changes when a population enters a new environment. The lineage—which has a remarkably detailed stratigraphic record—invaded Yellowstone Lake immediately after recession of ice from the basin 14,000 years ago. Several phyletic models portraying different types of evolutionary dynamics—both compatible and not compatible with changes in the adaptive landscape following ecological opportunity—were fitted to the fossil times‐series of S. niagarae/yellowstonensis. Different models best describe the three analyzed traits. Two of the models (a new model of decelerated evolution and an Ornstein–Uhlenbeck model) capture trait dynamics compatible with an event of ecological opportunity, whereas the third model (random walk) does not. Entering a new environment may accordingly affect trait dynamics for thousands of years, but the effects can vary across phenotypes. However, tests of model adequacy reveal shortcomings in all three models explaining the trait dynamics, suggesting model development is needed to more fully understand the phyletic evolution in S. niagarae/yellowstonensis

Assessing adequacy of models of phyletic evolution in the fossil record

1. Comparing relative fit of different models of evolutionary dynamics to time series of phyletic change is a common tool when interpreting the fossil record. However, a measure of relative fit is no guarantee the preferred model describes the data well. Selecting a good model is essential for robust inferences, but we are currently lacking tools to investigate if a model of phyletic evolution represents an adequate description of trait dynamics in fossil data. 2. This study develops a general statistical framework implemented in R for assessing the adequacy of the three most commonly used models of evolution in the fossil record; stasis, directional change and random walk. The statistical framework is applied to 300 fossil time series in order to assess how often the three models represent adequate descriptions of evolutionary dynamics in the fossil record. 3. The model that showed the best relative fit to a particular fossil time series (using AICc) passed all adequacy tests in 219 out of 300 cases (73%, directional trend = 76%, stasis = 64%, random walk = 81%). It is therefore not uncommon that the best model according to AICc does not adequately describe the trait dynamics in a fossil time series. 4. Statistical tests of model adequacy ease evaluation of whether a particular model is a good descriptor of phyletic evolution and can assist in making meaningful inferences of model parameters (e.g., as rates of evolution) and interpretations of evolution in the fossil record

An interspecific assessment of Bergmann’s rule in 22 mammalian families

Background Bergmann’s rule proposes that animals in cold habitats will be larger than those in warm habitats. This prediction has been tested thoroughly at the intraspecific level, but few studies have investigated the hypothesis with interspecific data using phylogenetic comparative approaches. Many clades of mammals have representatives in numerous distinct biomes, making this order highly suitable for a large-scale interspecific assessment of Bergmann’s rule. Here, we evaluate Bergmann’s rule within 22 mammalian families—with a dataset that include ~35 % of all described species—using a phylogenetic comparative approach. The method is based on an Ornstein-Uhlenbeck model of evolution that allows for joint estimation of adaptation and constraints (phylogenetic inertia) in the evolution of a trait. We use this comparative method to investigate whether body mass evolves towards phenotypic optima that are functions of median latitude, maximum latitude or temperature. We also assess the closely related Allen’s rule in five families, by testing if relative forelimb length evolves as a function of temperature or latitude. Results Among 22 mammalian families, there was weak support for Bergmann’s rule in one family: A decrease in temperature predicted increased body mass in Canidae (canids). We also found latitude and temperature to significantly predict body mass in Geomyidae (pocket gophers); however, the association went in the opposite direction of Bergmann’s predictions. Allen’s rule was supported in one of the five examined families (Pteropodidae; megabats), but only when forelimb length evolves towards an optimum that is a function of maximum latitude, not median latitude or temperature. Conclusions Based on this exhaustive assessment of Bergmann’s rule, we conclude that factors other than latitude and temperature are the major drivers of body mass evolution at the family level in mammals

ML‐morph: A fast, accurate and general approach for automated detection and landmarking of biological structures in images.

1. Morphometrics has become an indispensable component of the statistical analysis of size and shape variation in biological structures. Morphometric data have traditionally been gathered through low‐throughput manual landmark annotation, which represents a significant bottleneck for morphometric‐based phenomics. Here we propose a machine‐learning‐based high‐throughput pipeline to collect high‐dimensional morphometric data in two‐dimensional images of semi‐rigid biological structures. 2. The proposed framework has four main strengths. First, it allows for dense phenotyping with minimal impact on specimens. Second, it presents landmarking accuracy comparable to manual annotators, when applied to standardized datasets. Third, it performs data collection at speeds several orders of magnitude higher than manual annotators. And finally, it is of general applicability (i.e. not tied to a specific study system). 3. State‐of‐the‐art validation procedures show that the method achieves low error levels when applied to three morphometric datasets of increasing complexity, with error varying from 0.57% to 2.2% of the structure's length in the automated placement of landmarks. As a benchmark for the speed of the entire automated landmarking pipeline, our framework places 23 landmarks on 13,686 objects (zooids) detected in 1,684 pictures of fossil bryozoans in 3.12 min using a personal computer. 4. The proposed machine‐learning‐based phenotyping pipeline can greatly increase the scale, reproducibility and speed of data collection within biological research. To aid the use of the framework, we have developed a file conversion algorithm that can be used to leverage current morphometric datasets for automation, allowing the entire procedure, from model training all the way to prediction, to be performed in a matter of hours