Chance in the Modern Synthesis

The modern synthesis in evolutionary biology is taken to be that period in which a consensus developed among biologists about the major causes of evolution, a consensus that informed research in evolutionary biology for at least a half century. As such, it is a particularly fruitful period to consider when reflecting on the meaning and role of chance in evolutionary explanation. Biologists of this period make reference to “chance” and loose cognates of “chance,” such as: “random,” “contingent,” “accidental,” “haphazard,” or “stochastic.” Of course, what an author might mean by “chance” in any specific context varies. In the following, we first offer a historiographical note on the synthesis. Second, we introduce five ways in which synthesis authors spoke about chance. We do not take these to be an exhaustive taxonomy of all possible ways in which chance meaningfully figures in explanations in evolutionary biology. These are simply five common uses of the term by biologists at this period. They will serve to organize our summary of the collected references to chance and the analysis and discussion of the following questions: • What did synthesis authors understand by chance? • How did these authors see chance operating in evolution? • Did their appeals to chance increase or decrease over time during the synthesis? That is, was there a “hardening” of the synthesis, as Gould claimed (1983)

Archaeological Potential of the Grand Staircase-Escalante National Monument

posterExecutive proclamation 9682 reduces the size of the Grand Staircase-Escalante National Monument (GSENM), removing protections for at least 2,000 known archaeological sites and an unknown number of undiscovered cultural properties. Because only 10% of the GSENM's 1.9 million acres has been inventoried by archaeologists, fully evaluating the potential consequences of these boundary reductions in the remaining 90%, or 1.71 million acres, requires the use of predictive modeling. Here we report the major findings of a comprehensive predictive modeling program undertaken by the University of Utah Archaeological Center. Methodological and analytical details are available from the authors or in a report issued to the Bureau of Land Management

Averting biodiversity collapse in tropical forest protected areas

The rapid disruption of tropical forests probably imperils global biodiversity more than any other contemporary phenomenon¹⁻³. With deforestation advancing quickly, protected areas are increasingly becoming final refuges for threatened species and natural ecosystem processes. However, many protected areas in the tropics are themselves vulnerable to human encroachment and other environmental stresses⁴⁻⁹. As pressures mount, it is vital to know whether existing reserves can sustain their biodiversity. A critical constraint in addressing this question has been that data describing a broad array of biodiversity groups have been unavailable for a sufficiently large and representative sample of reserves. Here we present a uniquely comprehensive data set on changes over the past 20 to 30 years in 31 functional groups of species and 21 potential drivers of environmental change, for 60 protected areas stratified across the world’s major tropical regions. Our analysis reveals great variation in reserve ‘health’: about half of all reserves have been effective or performed passably, but the rest are experiencing an erosion of biodiversity that is often alarmingly widespread taxonomically and functionally. Habitat disruption, hunting and forest-product exploitation were the strongest predictors of declining reserve health. Crucially, environmental changes immediately outside reserves seemed nearly as important as those inside in determining their ecological fate, with changes inside reserves strongly mirroring those occurring around them. These findings suggest that tropical protected areas are often intimately linked ecologically to their surrounding habitats, and that a failure to stem broad-scale loss and degradation of such habitats could sharply increase the likelihood of serious biodiversity declines.Keywords: Ecology, Environmental scienc

Evaluating the efficacy of regression and machine learning models to predict prehistoric land-use patterns

PosterPredictive modeling in archaeology is critical to making informed land management decisions and answering key anthropological research questions. However, archaeological predictive modeling su#30;ers from several theoretical, empirical, and analytical problems. To address these shortcomings, we build on theory from behavioral ecology and statistical innovations from ecology. Here we apply four modeling approaches and evaluate their performance using a threshold-independent measure. Two are regression- based: generalized linear (GLM) and generalized additive (GAM) models. Two are machine-learning based: maximum entropy (MaxEnt) and random forests (RF). The results of this analysis establish a foundation for future applications of predictive models in archaeology

Addition of a carbohydrate-binding module enhances cellulase penetration into cellulose substrates

Introduction. Cellulases are of great interest for application in biomass degradation, yet the molecular details of the mode of action of glycoside hydrolases during degradation of insoluble cellulose remain elusive. To further improve these enzymes for application at industrial conditions, it is critical to gain a better understanding of not only the details of the degradation process, but also the function of accessory modules. Method. We fused a carbohydrate-binding module (CBM) from family 2a to two thermophilic endoglucanases. We then applied neutron reflectometry to determine the mechanism of the resulting enhancements. Results: Catalytic activity of the chimeric enzymes was enhanced up to three fold on insoluble cellulose substrates as compared to wild type. Importantly, we demonstrate that the wild type enzymes affect primarily the surface properties of an amorphous cellulose film, while the chimeras containing a CBM alter the bulk properties of the amorphous film. Conclusion: Our findings suggest that the CBM improves the efficiency of these cellulases by enabling digestion within the bulk of the film