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Abstract Temperate understory plant species are at risk from climate change and anthropogenic threats that include increased deer herbivory, habitat loss, pollinator declines and mismatch, and nutrient pollution. Recent work suggests that spring ephemeral wildflowers may be at additional risk due to phenological mismatch with deciduous canopy trees. The study of this dynamic, commonly referred to as “phenological escape”, and its sensitivity to spring temperature is limited to eastern North America. Here, we use herbarium specimens to show that phenological sensitivity to spring temperature is remarkably conserved for understory wildflowers across North America, Europe, and Asia, but that canopy trees in North America are significantly more sensitive to spring temperature compared to in Asia and Europe. We predict that advancing tree phenology will lead to decreasing spring light windows in North America while spring light windows will be maintained or even increase in Asia and Europe in response to projected climate warming.more » « less
Free, publicly-accessible full text available July 1, 2024
Community science image libraries offer a massive, but largely untapped, source of observational data for phenological research. The iNaturalist platform offers a particularly rich archive, containing more than 49 million verifiable, georeferenced, open access images, encompassing seven continents and over 278,000 species. A critical limitation preventing scientists from taking full advantage of this rich data source is labor. Each image must be manually inspected and categorized by phenophase, which is both time-intensive and costly. Consequently, researchers may only be able to use a subset of the total number of images available in the database. While iNaturalist has the potential to yield enough data for high-resolution and spatially extensive studies, it requires more efficient tools for phenological data extraction. A promising solution is automation of the image annotation process using deep learning. Recent innovations in deep learning have made these open-source tools accessible to a general research audience. However, it is unknown whether deep learning tools can accurately and efficiently annotate phenophases in community science images. Here, we train a convolutional neural network (CNN) to annotate images of Alliaria petiolata into distinct phenophases from iNaturalist and compare the performance of the model with non-expert human annotators. We demonstrate that researchers can successfully employ deep learning techniques to extract phenological information from community science images. A CNN classified two-stage phenology (flowering and non-flowering) with 95.9% accuracy and classified four-stage phenology (vegetative, budding, flowering, and fruiting) with 86.4% accuracy. The overall accuracy of the CNN did not differ from humans ( p = 0.383), although performance varied across phenophases. We found that a primary challenge of using deep learning for image annotation was not related to the model itself, but instead in the quality of the community science images. Up to 4% of A. petiolata images in iNaturalist were taken from an improper distance, were physically manipulated, or were digitally altered, which limited both human and machine annotators in accurately classifying phenology. Thus, we provide a list of photography guidelines that could be included in community science platforms to inform community scientists in the best practices for creating images that facilitate phenological analysis.more » « less
Societal Impact Statement
The practice of writing science blogs benefits both the scientist and society alike by providing professional development opportunities and delivering information in a format that is accessible to large and diverse audiences. By designing a project that introduced upper‐level undergraduate students to science blog writing with a focus on plant biology, we piqued students' interest in science writing and the content of a popular plant science blog website. If adopted more widely, this work could broaden the scope of science education and promote the development of effective science communication skills for the next generation of scientists.
Successful scientists must communicate their research to broad audiences, including distilling key scientific concepts for the general public. Students pursuing careers in Science, Technology, Engineering, and Mathematics (STEM) fields benefit from developing public communication skills early in their careers, but opportunities are limited in traditional biology curricula.
We created the “Plant Science Blogging Project” for a Plant Biology undergraduate course at the University of Pittsburgh in Fall 2018 and 2019. Students wrote blog posts merging personal connections with plants with plant biology concepts for the popular science blogs
Plant Love Storiesand EvoBites. By weaving biology into their narratives, students learned how to share botanical knowledge with the general public.
The project had positive impacts on student learning and public engagement. In post‐assignment surveys, the majority of students reported that they enjoyed the assignment, felt it improved their understanding of plant biology, and piqued their interest in reading and writing science blogs in the future. Approximately one‐third of the student‐authored blogs were published, including two that rose to the top 10 most‐read posts on Plant Love Stories. Some dominant themes in student blogs, including medicine and culture, differed from common story themes published on the web, indicating the potential for students to diversify science blog content.
Overall, the Plant Science Blogging Project allows undergraduate students to engage with plant biology topics in a new way, sharpen their scientific communication skills in accordance with today's world of mass information sharing, and contribute to the spread of scientific knowledge for public benefit.
Plant–fungal associations strongly influence forest carbon and nitrogen cycling. The prevailing framework for understanding these relationships is through the relative abundance of arbuscular (AM) versus ectomycorrhizal (EcM) trees. Ericoid mycorrhizal (ErM) shrubs are also common in forests and interactions between co‐occurring ErM shrubs and AM and EcM trees could shift soil biogeochemical responses. Here we test hypotheses that the effects of ErM shrubs on soil carbon and nitrogen either extend or are redundant with those of EcM trees.
Using regional vegetation inventory data (>3,500 plot observations) we evaluated the frequency, richness and relative abundance of ErM plants in temperate forests in the eastern United States and examined their relationship with EcM plant cover. We then used surface soil (7 cm) data from 414 plots within a single forest to analyse relationships between ErM plant cover, relative EcM tree basal area and soil carbon and nitrogen concentrations while accounting for other biogeochemical controls, such as soil moisture.
At both scales, we found a positive relationship between ErM and EcM plants, and the majority of ErM plants were in the shrub layer. Within the forest site, ErM plants strongly modulated tree mycorrhizal dominance effects. We found negative relationships between EcM relative basal area and soil carbon and nitrogen concentrations, but these relationships were weak to negligible in the absence of ErM plants. Both EcM relative basal area and ErM plant cover were positively associated with the soil carbon‐to‐nitrogen ratio. However, this relationship was driven by relatively lower nitrogen for EcM trees and higher carbon for ErM plants. As such, the functional effects of ErM plants on soil biogeochemistry neither extended nor were redundant with those of EcM trees.
Synthesis. We found that ErM shrubs strongly influenced the relationship between tree mycorrhizal associations and soil biogeochemistry, and the effects of ErM shrubs and EcM trees on carbon and nitrogen were functionally distinct. Our findings suggest that ErM shrubs could confound interpretation of AM versus EcM tree effects in ecosystems where they co‐occur but also bolster growing calls to consider mycorrhizal functional types as variables that strongly influence forest biogeochemistry.
Field research can be an important component of the career trajectories for researchers in numerous academic fields; however, conducting research in field settings poses risks to health and safety, and researchers from marginalized groups often face greater risks than those experienced by other researchers in their fields; If these additional risks are not actively and thoughtfully mitigated, they are likely to hinder the participation of qualified investigators in field research and counteract efforts to improve and promote diversity, equity and inclusion in the field sciences.
Here we provide, from our perspectives as co‐authors of a field safety manual for the Department of Biological Sciences at the University of Pittsburgh in Pennsylvania, United States, (A) background on risks and barriers that should be considered when planning and conducting field research and (B) suggestions on how to work as a collaborative team for developing an inclusive field safety manual.
As an example of a manual this proposed process has yielded, we have included our own field safety manual written with diversity, equity and inclusion as a central focus.
We hope this publication serves as a starting point for those interested in developing a similar document for use in their laboratory group, department or institution.