This study explored the relationships between student background and academic performance in college introductory environmental science (ES) courses at a large U.S. research university with the premise that this analysis may inform teaching practices, curricula, and efforts to increase retention. We surveyed over 700 students across eleven introductory ES courses and used multiple linear mixed-effects regressions to model the data. We found that students who grew up in rural settings or who had frequent childhood interactions with natural environments earned higher grades, on average, than students from urban settings or with fewer childhood interactions with natural environments. Our results indicate that students reporting frequent childhood interactions with forests, for example, were projected to earn grades up to 1.5 letter grades higher in these courses than students with no such interactions. In addition, students with frequent childhood interactions with nature were likelier to report that such interactions helped them in their ES course, suggesting that these students may recognize the value of these experiences. Greater interest in the subject matter also correlated with higher ES course grades, whereas amount of prior ES coursework did not. We discuss the possible implications of these correlations for ES academic performance and educational practice.

Plant reproductive trade‐offs are thought to be caused by resource limitations or other constraints, but more empirical support for these hypotheses would be welcome. Additionally, quantitative characterization of these trade‐offs, as well as consideration of whether they are linear, could yield additional insights. We expanded our flower removal research on lowbush blueberry (Vaccinium angustifolium) to explore the nature of and causes of its reproductive trade‐offs. We used fertilization, defoliation, positionally biased flower removal, and multiple flower removal levels to discern why reproductive trade‐offs occur in this taxon and to plot these trade‐offs along two continuous axes. We found evidence through defoliation that vegetative mass per stem may trade off with reproductive effort in lowbush blueberry because the two traits compete for limited carbon. Also, several traits including ripe fruit production per reproductive node and fruit titratable acidity may be “sink‐limited”—they decline with increasing reproductive effort because average reproductive structure quality declines. We found no evidence that reproductive trade‐offs were caused by nitrogen limitation. Use of reproductive nodes remaining per stem as a measure of reproductive effort indicated steeper trade‐offs than use of the proportion of nodes remaining. For five of six traits, we found evidence that the trade‐off could be concave down or up instead of strictly linear. Synthesis. To date, studies have aimed primarily at identifying plant reproductive trade‐offs. However, understanding how and why these trade‐offs occur represent the exciting and necessary next steps for this line of inquiry.

To efficiently detect aquatic invasive species early in an invasion when control may still be possible, predictions about which locations are likeliest to be occupied are needed at fine scales but are rarely available. Occupancy modeling could provide such predictions given data of sufficient quality and quantity. We assembled a data set for the macroalga starry stonewort (Nitellopsis obtusa) across Minnesota and Wisconsin, USA, where it is a new and high-priority invader. We used these data to construct a multi-season, single-species spatial occupancy model that included biotic, abiotic, and movement-related predictors. Distance to the nearest access was an important occurrence predictor, highlighting the likely role boats play in spreading starry stonewort. Fetch and water depth also predicted occupancy. We estimated an average detection probability of 63% at sites with mean non-N. obtusa plant cover, declining to ~ 38% at sites with abundant plant cover, especially that of other Characeae. We recommend that surveyors preferentially search for starry stonewort in areas of shallow depth and high fetch close to boat accesses. We also recommend searching during late summer/early fall when detection is likelier. This study illustrates the utility of fine-scale occupancy modeling for predicting the locations of nascent populations of difficult-to-detect species.