Israel Del Toro

Background. Urban spaces can be re-imagined to encourage greater plant and insect biodiversity. Here, we share refined results from the first iteration of No Mow May in 2020, in Appleton, Wisconsin, which aimed to rapidly assess bee richness and abundance, plant richness and percent cover of lawns or greenspaces, and cultivate an engaged community of citizen scientists. We also present the subsequent 2021 No Mow May study, and demonstrate the process of open-access science. We integrated reviewer feedback to refine the methods used to assess the impacts of not mowing through the month of May. Methods. The 2020 study compared bee richness and abundance and plant richness and percent cover in lawns that were not mowed through the month of May with urban parks with regular mowing, using a sweep netting sand a largely no-kill approach to bee collection and identification. The 2021 study compared paired lawns that were in the No Mow treatment relative to neighboring lawns that were regularly mowed, and assessed flowering plant counts and percent cover as well as Hymenoptera genera abundance and richness using yellow pan traps and preserving bees in ethanol for subsequent identification in the lab. Results. We found a threefold increase in bee abundance and twofold increase in bee genera richness in 2020 in No Mow treatments compared with regularly mowed greenspaces. In 2020, mowed areas had 36% fewer plant species and 34% lower flower density than No Mow areas. In 2021, Hymenoptera richness mean values were 1.99 the No Mow vs. 0.18 the Mowed treatment, and the mean number of flowering plants hovered around 10 in No Mow vs. 2 across the Mowed treatments. This study highlights the importance of reproducibility in science as we show 2020 trends are consistent in 2021. We discuss the iterative nature of research studies and the benefits of the continued refinement in research questions and communication in science. We close by inviting folks to experiment with ways to advocate for small scale changes to improve pollinator forage and habitat resources, promote environmentally friendly urban spaces, increase water conservation efforts, and garden with native flowers and plants.

As cities become more populated and the density of urban development increases, local biodiversity is threatened. Urban greenspaces have the capacity to preserve pollinator biodiversity, but the quality of support they provide depends on greenspace landscape attributes, including the availability of pollinator habitat and foraging resources. Wild native bees provide important pollination services to urban ecosystems, yet relatively little is known about how urban landscape management influences pollinator community composition and diversity. Our study explores how wild bee communities are affected by greenspace and landscape-level features like pollinator management practices, in urban greenspaces in and around Appleton Wisconsin: a mid-sized urban community spanning more than 100 sq. km. We sampled and identified native bees periodically between late-May 2017 and mid-September of 2018 using standardized arrays of pan traps at 15 sites around the city. We classified greenspaces based on their level of development (urban or suburban) and whether they were managed or unmanaged for increasing wild pollinator diversity. We quantified floral species diversity, floral color diversity, tree species diversity, and proximity of sites to open water for each site and used remotely sensed satellite data from both the USGS National Land Cover Database (NLCD) and the Normalized Difference Vegetation Index (NDVI). All variables were tested as potential correlates of wild bee abundance and species richness. Active pollinator management sites supported higher levels of bee abundance and richness. Notably, active greenspace management (e.g. planting native wildflowers) was a stronger correlate of bee abundance and richness than greenspace size and other landscape-level attributes. Within-greenspace attributes such as floral diversity, tree diversity, and proximity to open water contributed positively to both bee abundance and richness. Based on these findings, we suggest that urban greenspaces may be managed more efficiently and cost-effectively by focusing resources on active management by planting wildflowers, removing invasive species, creating nesting habitat, and providing water resources, rather than simply expanding in area.

Increasingly, students training in the biological sciences depend on a proper grounding in biological statistics, data science and experimental design. As biological datasets increase in size and complexity, transparent data management and analytical methods are essential skills for undergraduate biologists. We propose that using the software R and RStudio are effective tools to train first- and second-year undergraduate students in data visualization and foundational statistical analyses. Here, we present the redesigned laboratory curriculum for our Experimental Design and Statistics course, a required course for all first- or second-year biology majors at Lawrence University, a small liberal arts institution in northeast Wisconsin. We include an example 10-week syllabus and eight laboratory exercises (as supplementary materials) for undergraduate institutions that aim to introduce and guide students through acquiring a basic understanding of biostatistical analyses and skills using R and RStudio. We also provide a flexible framework and examples that are easily modifiable and cover the essential biostatistics and data science skills needed for biology undergraduates. Finally, we discuss the potential pitfalls and obstacles as well as the intrinsic benefits and expected outcomes of our laboratories.

No Mow May is a community science initiative popularized in recent years that encourages property owners to limit their lawn mowing practices during the month of May. The goal of No Mow May is to provide early season foraging resources for pollinators that emerge in the spring, especially in urban landscapes when few floral resources are available. We worked with the city council of Appleton, Wisconsin, USA. to allow No Mow May to take place in May 2020. Four hundred and thirty-five property owners registered for No Mow May in Appleton. We measured floral and bee richness and abundance in the yards of a subset of homes (N = 20) located near regularly mowed urban parks (N = 15) at the end of the month. We found that homes that participated in No Mow May had more diverse and abundant flora than regularly mowed green spaces throughout the city. No Mow May homes had three times higher bee richness and five times higher bee abundances than frequently mowed greenspaces. Using generalized linear models, we found that the best predictor of bee richness was the size of the designated unmowed area, and the best predictors of bee abundances were the size of the unmowed area as well as floral richness. While our findings cannot conclusively attribute increases in bee abundances and richness to the No Mow May efforts, our data does show that bee pollinators make use of no mow spaces as key floral resources during early spring in the upper midwestern United States. A post-No Mow May survey revealed that the participants were keen to increase native floral resources in their yards, increase native bee nesting habitat, reduce mowing intensities, and limit herbicide, pesticide, and fertilizer applications to their lawns. The No Mow May initiative educated an engaged community on best practices to improve the conservation of urban pollinators in future years.

Ant-mediated seed dispersal, also known as myrmecochory, is a widespread and important mutualism that structures both plant and ant communities. However, the extent to which ant functional types (e.g., granivorous generalists vs. myrmecochorous ants) across environmental gradients affect seed removal rates is not fully understood. We used a replicated, standardized seed removal experiment along elevation gradients in four mountain ranges in the southwestern United States to test predictions that: (1) seed removal rates would be greater at lower elevations, and (2) seed species identity influences seed removal rates (i.e., seeds from their native elevation range would be removed at higher rates than seeds outside of their native elevation range). Both predictions were supported. Seed removal rates were ∼25% higher at lower elevation sites than at higher elevation sites. The low elevation Datura and high elevation Iris were removed at higher rates in their respective native ranges. We attribute observed differences in dispersal rates to changes in ant community composition, functional diversity, and abundance. We also suggest that temperature variation along the elevation gradient may explain these differences in seed removal rates.

We use observed patterns of species richness and composition of ant communities along a 1000 mm rainfall gradient in northern Australian savanna to assess the accuracy of species richness and turnover predictions derived from stacked species distribution models (S‐SDMs) and constrained by macroecological models (MEMs). We systematically sampled ants at 15 sites at 50 km intervals along the rainfall gradient in 2012 and 2013. Using the observed data, we created MEMs of species richness, composition and turnover. We built distribution models for 135 of the observed species using data from museum collections and online databases. We compared two approaches of stacking SDMs and three modelling algorithms to identify the most accurate way of predicting richness and composition. We then applied the same beta diversity metrics to compare the observed versus predicted patterns. Stacked SDMs consistently over‐predicted local species richness, and there was a mismatch between the observed pattern of richness estimated from the MEM, and the pattern predicted by S‐SDMs. The most accurate richness and turnover predictions occurred when the stacked models were rank‐ordered by their habitat suitability and constrained by the observed MEM richness predictions. In contrast with species richness, the predictions obtained by the MEM of community similarity, composition and turnover matched those predicted by the S‐SDMs. S‐SDMs regulated by MEMs may therefore be a useful tool in predicting compositional patterns despite being unreliable estimators of species richness. Our results highlight that the choice of species distribution model, the stacking method used, and underlying macroecological patterns all influence the accuracy of community assembly predictions derived from S‐SDMS.

Ant-mediated seed dispersal, also known as myrmecochory, is a widespread and important mutualism that structures both plant and insect communities. However the extent to which myrmecochory is driven by abiotic and biotic environmental factors remains unclear. We used a replicated standardized seed removal experiment along elevation gradients in four mountain ranges in the southwestern United States to test predictions that: (1) seed removal rates would be greater at lower elevations, and (2) seed species identity influences seed removal rates, (i.e. seeds from their native elevation range would be removed at higher rates than seeds outside of their range). Both predictions were supported. Seed removal rates were ~25% higher at lower elevation sites than at higher elevation sites. The low elevation Datura and high elevation Iris were removed at higher rates in their respective native ranges. We attribute observed differences in dispersal rates to changes in ant community composition, functional diversity, and abundance, suggesting that temperature variation along the elevation gradient.

Ecological studies often are subjected to unintentional biases, suggesting that improved research designs for hypothesis testing should be used. Double-blind ecological studies are rare but necessary to minimize sampling biases and omission errors, and improve the reliability of research. We used a double-blind design to evaluate associations between nests of red wood ants (Formica rufa, RWA) and the distribution of tectonic faults. We randomly sampled two regions in western Denmark to map the spatial distribution of RWA nests. We then calculated nest proximity to the nearest active tectonic faults. Red wood ant nests were eight times more likely to be found within 60 m of known tectonic faults than were random points in the same region but without nests. This pattern paralleled the directionality of the fault system, with NNE–SSW faults having the strongest associations with RWA nests. The nest locations were collected without knowledge of the spatial distribution of active faults thus we are confident that the results are neither biased nor artefactual. This example highlights the benefits of double-blind designs in reducing sampling biases, testing controversial hypotheses, and increasing the reliability of the conclusions of research.

Ecological studies aim to better understand the distribution and abundances of organisms. Yet ecological works often are subjected to unintentional biases thus an improved framework for hypothesis testing should be used. Double-blind ecological studies are rare but necessary to minimize sampling biases and omission errors and improve the reliability of research. We used a double-blind design to evaluate associations between nests of red wood ants (Formica rufa, RWA) and the distribution of tectonic faults. We randomly sampled two regions in western Denmark to map the spatial distribution of RWA nests. We then calculated nest proximity to the nearest active tectonic faults. Red wood ant nests were eight times more likely to be found within 60 meters of known tectonic faults than were random points in the same region but without nests. This pattern paralleled the directionality of the fault system, with NNE-SSW faults having the strongest associations with RWA nests. The nest locations were collected without knowledge of the spatial distribution of active faults thus we are confident that the results are neither biased nor artefactual. This example highlights the benefits of double-blind designs in reducing sampling biases, testing controversial hypotheses, and increasing the reliability of the conclusions of research.