layeranalyzer: Inferring correlative and causal connections from time series data inr

Fitting and evaluating univariate and multivariate models of within-lineage evolution

The nature of phenotypic evolution within lineages is central to many unresolved questions in paleontology and evolutionary biology. Analyses of evolutionary time-series of ancestor-descendant populations in the fossil record are likely to make important contributions to many of these debates. However, the limited number of models that have been applied to these types of data may restrict our ability to interpret phenotypic evolution in the fossil record. Using uni- and multivariate models of trait evolution that make different assumptions regarding the dynamics of the adaptive landscape, I evaluate contrasting hypotheses to explain evolution of size in the radiolarian Eucyrtidium calvertense and armor in the stickleback Gaserosteus doryssus. Body size evolution in E. calvertense is best explained by a model where the lineage evolves as a consequence of a shift in the adaptive landscape that coincides with the initiation of neosympatry with its sister lineage. Multivariate evolution of armor traits in a stickleback lineage (Gasterosteus doryssus) show evidence of adaptation towards independent optima on the adaptive landscape at the same time as traits change in a correlated fashion. The fitted models are available in a the R package evoTS, which builds on the commonly used paleoTS framework.

Causes and Consequences of Apparent Timescaling Across All Estimated Evolutionary Rates

Evolutionary rates play a central role in connecting micro- and macroevolution. All evolutionary rate estimates, including rates of molecular evolution, trait evolution, and lineage diversification, share a similar scaling pattern with time: The highest rates are those measured over the shortest time interval. This creates a disconnect between micro- and macroevolution, although the pattern is the opposite of what some might expect: Patterns of change over short timescales predict that evolution has tremendous potential to create variation and that potential is barely tapped by macroevolution. In this review, we discuss this shared scaling pattern across evolutionary rates. We break down possible explanations for scaling into two categories, estimation error and model misspecification, and discuss how both apply to each type of rate. We also discuss the consequences of this ubiquitous pattern, which can lead to unexpected results when comparing ratesover different timescales. Finally, after addressing purely statistical concerns, we explore a few possibilities for a shared unifying explanation across the three types of rates that results from a failure to fully understand and account for how biological processes scale over time.

When fossil clades 'compete': local dominance, global diversification dynamics and causation

Examining the supposition that local-scale competition drives macroevolutionary patterns has become a familiar goal in fossil biodiversity studies. However, it is an elusive goal, hampered by inadequate confirmation of ecological equivalence and interactive processes between clades, patchy sampling, few comparative analyses of local species assemblages over long geological intervals, and a dearth of appropriate statistical tools. We address these concerns by reevaluating one of the classic examples of clade displacement in the fossil record, in which cheilostome bryozoans surpass the once dominant cyclostomes. Here, we analyse a newly expanded and vetted compilation of 40 190 fossil species occurrences to estimate cheilostome and cyclostome patterns of species proportions within assemblages, global genus richness and genus origination and extinction rates while accounting for sampling. Comparison of time-series models using linear stochastic differential equations suggests that inter-clade genus origination and extinction rates are causally linked to each other in a complex feedback relationship rather than by simple correlations or unidirectional relationships, and that these rates are not causally linked to changing within-assemblage proportions of cheilostome versus cyclostome species.

Investigating Biotic Interactions in Deep Time

Recent renewed interest in using fossil data to understand how biotic interactions have shaped the evolution of life is challenging the widely held assumption that long-term climate changes are the primary drivers of biodiversity change. New approaches go beyond traditional richness and co-occurrence studies to explicitly model biotic interactions using data on fossil and modern biodiversity. Important developments in three primary areas of research include analysis of (i) macroevolutionary rates, (ii) the impacts of and recovery from extinction events, and (iii) how humans (Homo sapiens) affected interactions among non-human species. We present multiple lines of evidence for an important and measurable role of biotic interactions in shaping the evolution of communities and lineages on long timescales.