Steve C. Wang

To determine the distribution and causes of extinction threat across functional groups of terrestrial vertebrates, we assembled an ecological trait data set for 18,016 species of terrestrial vertebrates and utilized phylogenetic comparative methods to test which categories of habitat association, mode of locomotion, and feeding mode best predicted extinction risk. We also examined the individual categories of the International Union for Conservation of Nature Red List extinction drivers (e.g., agriculture and logging) threatening each species and determined the greatest threats for each of the four terrestrial vertebrate groups. We then quantified the sum of extinction drivers threatening each species to provide a multistressor perspective on threat. Cave dwelling amphibians ( p < 0.01), arboreal quadrupedal mammals (all of which are primates) ( p < 0.01), aerial and scavenging birds ( p < 0.01), and pedal (i.e., walking) squamates ( p < 0.01) were all disproportionately threatened with extinction in comparison with the other assessed ecological traits. Across all threatened vertebrate species in the study, the most common risk factors were agriculture, threatening 4491 species, followed by logging, threatening 3187 species, and then invasive species and disease, threatening 2053 species. Species at higher risk of extinction were simultaneously at risk from a greater number of threat types. If left unabated, the disproportionate loss of species with certain functional traits and increasing anthropogenic pressures are likely to disrupt ecosystem functions globally. A shift in focus from species‐ to trait‐centric conservation practices will allow for protection of at‐risk functional diversity from regional to global scales.

The taxonomic and ecologic composition of Earth's biota has shifted dramatically through geologic time, with some clades going extinct while others diversified. Here, we derive a metric that quantifies the change in biotic composition due to extinction or origination and show that it equals the product of extinction/origination magnitude and selectivity (variation in magnitude among groups). We also define metrics that describe the extent to which a recovery (1) reinforced or reversed the effects of extinction on biotic composition and (2) changed composition in ways uncorrelated with the extinction. To demonstrate the approach, we analyzed an updated compilation of stratigraphic ranges of marine animal genera. We show that mass extinctions were not more selective than background intervals at the phylum level; rather, they tended to drive greater taxonomic change due to their higher magnitudes. Mass extinctions did not represent a separate class of events with respect to either strength of selectivity or effect. Similar observations apply to origination during recoveries from mass extinctions, and on average, extinction and origination were similarly selective and drove similar amounts of biotic change. Elevated origination during recoveries drove bursts of compositional change that varied considerably in effect. In some cases, origination partially reversed the effects of extinction, returning the biota toward the pre-extinction composition; in others, it reinforced the effects of the extinction, magnifying biotic change. Recoveries were as important as extinction events in shaping the marine biota, and their selectivity deserves systematic study alongside that of extinction.

The zero-force evolutionary law (ZFEL) states that in evolutionary systems, in the absence of forces or constraints, diversity and complexity tend to increase. The reason is that diversity and complexity are both variance measures, and variances tend to increase spontaneously as random events accumulate. Here, we use random-walk models to quantify the ZFEL expectation, producing equations that give the probabilities of diversity or complexity increasing as a function of time, and that give the expected magnitude of the increase. We produce two sets of equations, one for the case in which variation occurs in discrete steps, the other for the case in which variation is continuous. The equations provide a way to decompose actual trajectories of diversity or complexity into two components, the portion due to the ZFEL and a remainder due to selection and constraint. Application of the equations is demonstrated using real and hypothetical data.

Diel activity pattern (DAP) is a key aspect of an animal's ecology, but it is difficult to infer when behavior cannot be directly observed, as in the fossil record. Various anatomical correlates have therefore been used to attempt to classify DAP. Eyeball dimensions are good predictors of DAP because they relate directly to light sensitivity of the eye. Osteological characters, such as scleral ring dimensions, are also reliable proxies, but bony orbit dimensions alone have proven less reliable because soft tissues other than the eyeball can affect orbit size and shape. However, it would be useful if bony orbit dimensions could be used to determine DAP, particularly for mammals, which have no scleral ring, and nonmammalian synapsids, which infrequently preserve scleral rings. We investigated the possibility of predicting DAP in sciurids (Mammalia: Rodentia: Sciuridae) using orbit measurements and other cranial dimensions, and a variety of quantitative methods, including phylogenetic flexible discriminant analysis, classification trees, and logistic regression. The latter two methods do not require a priori assignment of DAP and therefore reflect the situation in a fossil data set. We find that although there are some interfering phylogenetic factors, nocturnal and non‐nocturnal sciurids can be differentiated from one another with over 80% accuracy using all methods investigated here; attempts to differentiate crepuscular animals from nocturnal and diurnal species proved much less successful. Our results indicate that these analyses offer several viable options for predicting DAP in the fossil record, but such analyses should be conducted in a phylogenetic context whenever possible. Anat Rec, 301:1774–1787, 2018.

The Signor-Lipps effect states that even a sudden mass extinction will invariably appear gradual in the fossil record, due to incomplete fossil preservation. Most previous work on the Signor–Lipps effect has focused on testing whether taxa in a mass extinction went extinct simultaneously or gradually. However, many authors have proposed scenarios in which taxa went extinct in distinct pulses. Little methodology has been developed for quantifying characteristics of such pulsed extinction events. Here we introduce a method for estimating the number of pulses in a mass extinction, based on the positions of fossil occurrences in a stratigraphic section. Rather than using a hypothesis test and assuming simultaneous extinction as the default, we reframe the question by asking what number of pulses best explains the observed fossil record. Using a two-step algorithm, we are able to estimate not just the number of extinction pulses but also a confidence level or posterior probability for each possible number of pulses. In the first step, we find the maximum likelihood estimate for each possible number of pulses. In the second step, we calculate the Akaike information criterion and Bayesian information criterion weights for each possible number of pulses, and then apply a k -nearest neighbor classifier to these weights. This method gives us a vector of confidence levels for the number of extinction pulses—for instance, we might be 80% confident that there was a single extinction pulse, 15% confident that there were two pulses, and 5% confident that there were three pulses. Equivalently, we can state that we are 95% confident that the number of extinction pulses is one or two. Using simulation studies, we show that the method performs well in a variety of situations, although it has difficulty in the case of decreasing fossil recovery potential, and it is most effective for small numbers of pulses unless the sample size is large. We demonstrate the method using a data set of Late Cretaceous ammonites.

Over the past 3.8 billion years, the maximum size of life has increased by approximately 18 orders of magnitude. Much of this increase is associated with two major evolutionary innovations: the evolution of eukaryotes from prokaryotic cells approximately 1.9 billion years ago (Ga), and multicellular life diversifying from unicellular ancestors approximately 0.6 Ga. However, the quantitative relationship between organismal size and structural complexity remains poorly documented. We assessed this relationship using a comprehensive dataset that includes organismal size and level of biological complexity for 11 172 extant genera. We find that the distributions of sizes within complexity levels are unimodal, whereas the aggregate distribution is multimodal. Moreover, both the mean size and the range of size occupied increases with each additional level of complexity. Increases in size range are non-symmetric: the maximum organismal size increases more than the minimum. The majority of the observed increase in organismal size over the history of life on the Earth is accounted for by two discrete jumps in complexity rather than evolutionary trends within levels of complexity. Our results provide quantitative support for an evolutionary expansion away from a minimal size constraint and suggest a fundamental rescaling of the constraints on minimal and maximal size as biological complexity increases.

The Geozoic encompasses the 3.6 Ga interval in Earth history when life has existed. Over this time, life has diversified from exclusively tiny, single-celled organisms to include large, complex multicellular forms. Just how and why this diversification occurred has been a major area of interest for paleontologists and evolutionary biologists for centuries. Here, we compile data on organism size throughout the Geozoic fossil record for the three domains of life. We describe canonical trends in the evolution of body size, synthesize current understanding of the patterns and causal mechanisms at various hierarchical scales, and discuss the biological and geological consequences of variation in organismal size.