SignificanceDecades of research have fostered the now-prevalent assumption that noncrop habitat facilitates better pest suppression by providing shelter and food resources to the predators and parasitoids of crop pests. Based on our analysis of the largest pest-control database of its kind, noncrop habitat surrounding farm fields does affect multiple dimensions of pest control, but the actual responses of pests and enemies are highly variable across geographies and cropping systems. Because noncrop habitat often does not enhance biological control, more information about local farming contexts is needed before habitat conservation can be recommended as a viable pest-suppression strategy. Consequently, when pest control does not benefit from noncrop vegetation, farms will need to be carefully comanaged for competing conservation and production objectives.
A large body of research has examined students' conceptions of evolution and their relationships to acceptance of evolution. Proficiency in statistical and probabilistic reasoning has long been considered to be an essential feature of evolutionary reasoning, yet almost no empirical work has explored these putative connections. The RaPro instruments have recently been developed to measure statistical reasoning in the contexts of mathematics (RaProMath) and evolution (RaProEvo). Our study provides additional validation of these instruments using Rasch analysis and quantifies the contribution of statistical reasoning to both understanding and accepting evolution. We recruited a large sample (N = 564) of undergraduate students enrolled in an introductory biology course at a large public research university in the United States. Students completed a suite of published instruments that assessed statistical reasoning, evolutionary understanding, and evolutionary acceptance. Our findings indicate that validity inferences derived from RaPro scores generalized to the new sample, and that proficiency in statistical reasoning explained 28% of the variance in evolutionary knowledge and 19% of the variation in evolutionary acceptance. The inclusion of demographic variables into the model significantly increased the explained variance in acceptance. Notably, the variance in evolution acceptance explained by statistical reasoning was comparable to that of thinking dispositions or evolutionary knowledge reported in the literature. This work provides the first large-scale evidence of the role of statistical reasoning in evolutionary knowledge and acceptance and motivates future work to explore how statistical literacy should be integrated into evolution education efforts.
Two instruments—Randomness and Probability Test in the Context of Evolution (RaProEvo) and Randomness and Probability Test in the Context of Mathematics (RaProMath)—that include both multiple-choice and free-response items were developed. The results indicate that they generate reliable and valid inferences.
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