Abstract
Models of evolution commonly decompose change into deterministic and stochastic components. Different models, however, produce different concepts of signal and noise. Excursion tests correct for two distinct types of noise, sampling error and phenotypic drift, resulting in two distinct types of signal or trend. A minimal trend is a signal of historical change after correcting for sampling error; a directed trend is a model dependent measure of confidence that selection has occurred (correcting for both sampling error and drift). The history of random walks and excursion tests in paleobiology highlights the conceptual middle ground between historical pattern and underlying processes. In paleobiology, both minimal and directed trends reflect a causally agnostic, trait-level product of evolutionary and environmental processes. Directed trends provide evidence for directional causes, but the identity and relative strength of those causes requires a deeper understanding. Thus, the magnitude of minimal and directed trends should not be interpreted as the strength of selection for a specified trait. They can be a useful stepping stone in that direction when paired with a map of the middle ground and agreement about how genetic, macroevolutionary, and environmental processes contribute to evolutionary change.
Highlights
There has been great confusion about the meaning of “trend” in biology
Biologists regularly contrast “trends” as natural selection with “random” change based on a null model
This paper looks at two types of trends
Summary
There has been great confusion about the meaning of “trend” in biology. Empirical questions come deeply entwined with methodological and philosophical issues that can affect how we move between observed patterns, modeled patterns, and inferences about natural selection (McShea 2000; Sheets and Mitchell 2001; Gregory 2008; Turner 2009, 2015). The deterministic factor, often called a trend, describes directional change in a phenotype over time as selection acts to increase or decrease the frequency of a specified trait. These models are “causally agnostic” because they work in the absence of details about specific processes and their relative contributions. A closer look at the MBL model and excursion tests helps to reveal a middle ground between the historical pattern and causal factors. Biologists often seek to map historical patterns of biodiversity (i.e., the sum of stochastic and deterministic factors when describing changes in phenotypic variation through time) onto specific causes via microevolutionary, macroevolutionary, and environmental processes.
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