Every discipline has its hazards, and for evolution scientists and educators, a major hazard consists of encounters with creationists, their rhetoric, and their attempts to insert antievolutionism into public education. Preparation for this hazard should be a standard part of the background of professional evolutionists. One important piece of this preparation involves understanding the historical origins of creationism within the wider history of western Christianity, especially evangelical Protestantism and its development in the United States. Here, I place the standard histories of “creation science” by Numbers and Larson (covering primarily the early 1900s to the 1980s) into this larger context (going back to the evangelical split over slavery before the Civil War and during), and then show how the “intelligent design” movement (from the 1980s until the present) fits squarely within the long history of primarily evangelical, biblicist opposition to evolution. The major creationist movements and slogans are identified and also placed into this historical picture. In summary, while creationism has evolved diverse labels and strategies for legal and rhetorical purposes, its fundamental essence remains unchanged. That essence is advocacy of miraculous divine intervention, i.e., special creation, in the history of life, and the claim that science must acknowledge special creation or dire consequences for society will follow.

Abstract Background DNA target enrichment by micro-array capture combined with high throughput sequencing technologies provides the possibility to obtain large amounts of sequence data (e.g. whole mitochondrial DNA genomes) from multiple individuals at relatively low costs. Previously, whole mitochondrial genome data for domestic horses (Equus caballus) were limited to only a few specimens and only short parts of the mtDNA genome (especially the hypervariable region) were investigated for larger sample sets. Results In this study we investigated whole mitochondrial genomes of 59 domestic horses from 44 breeds and a single Przewalski horse (Equus przewalski) using a recently described multiplex micro-array capture approach. We found 473 variable positions within the domestic horses, 292 of which are parsimony-informative, providing a well resolved phylogenetic tree. Our divergence time estimate suggests that the mitochondrial genomes of modern horse breeds shared a common ancestor around 93,000 years ago and no later than 38,000 years ago. A Bayesian skyline plot (BSP) reveals a significant population expansion beginning 6,000-8,000 years ago with an ongoing exponential growth until the present, similar to other domestic animal species. Our data further suggest that a large sample of wild horse diversity was incorporated into the domestic population; specifically, at least 46 of the mtDNA lineages observed in domestic horses (73%) already existed before the beginning of domestication about 5,000 years ago. Conclusions Our study provides a window into the maternal origins of extant domestic horses and confirms that modern domestic breeds present a wide sample of the mtDNA diversity found in ancestral, now extinct, wild horse populations. The data obtained allow us to detect a population expansion event coinciding with the beginning of domestication and to estimate both the minimum number of female horses incorporated into the domestic gene pool and the time depth of the domestic horse mtDNA gene pool.

The ENMTools software package was introduced in 2008 as a platform for making measurements on environmental niche models (ENMs, frequently referred to as species distribution models or SDMs), and for using those measurements in the context of newly developed Monte Carlo tests to evaluate hypotheses regarding niche evolution. Additional functionality was later added for model selection and simulation from ENMs, and the software package has been quite widely used. ENMTools was initially implemented as a Perl script, which was also compiled into an executable file for various platforms. However, the package had a number of significant limitations; it was only designed to fit models using Maxent, it relied on a specific Perl distribution to function, and its internal structure made it difficult to maintain and expand. Subsequently, the R programming language became the platform of choice for most ENM studies, making ENMTools less usable for many practitioners. Here we introduce a new R version of ENMTools that implements much of the functionality of its predecessor as well as numerous additions that simplify the construction, comparison and evaluation of niche models. These additions include new metrics for model fit, methods of measuring ENM overlap, and methods for testing evolutionary hypotheses. The new version of ENMTools is also designed to work within the expanding universe of R tools for ecological biogeography, and as such includes greatly simplified interfaces for analyses from several other R packages.

The importance of long-distance dispersal (LDD) in shaping geographical distributions has been debated since the nineteenth century. In terrestrial vertebrates, LDD events across large water bodies are considered highly improbable, but organismal traits affecting dispersal capacity are generally not taken into account. Here, we focus on a recent lizard radiation and combine a summary-coalescent species tree based on 1225 exons with a probabilistic model that links dispersal capacity to an evolving trait, to investigate whether ecological specialization has influenced the probability of trans-oceanic dispersal. Cryptoblepharus species that occur in coastal habitats have on average dispersed 13 to 14 times more frequently than non-coastal species and coastal specialization has, therefore, led to an extraordinarily widespread distribution that includes multiple continents and distant island archipelagoes. Furthermore, their presence across the Pacific substantially predates the age of human colonization and we can explicitly reject the possibility that these patterns are solely shaped by human-mediated dispersal. Overall, by combining new analytical methods with a comprehensive phylogenomic dataset, we use a quantitative framework to show how coastal specialization can influence dispersal capacity and eventually shape geographical distributions at a macroevolutionary scale.