Biology subjects

Glaum, P.

Publications and source records attributed to Glaum, P..

4 recordsLinked to original sources

bioRxiv2023

A century of sampling at an ecological preserve reveals declining diversity of wild bees

We analyzed the wild bee community from 1921 to 2018 at a nature preserve in southern Michigan, USA using museum records and found significant shifts in the bee community. Across the near century of records, species richness peaked in the 1970s and 1980s. There was an intensive bee survey completed by F.C. Evans in 1972 and 1973. We attempted to replicate his effort in 2017 and 2018, and again found a significant decline in species richness and evenness. There was also evidence of declining abundance in many of the more common species. We also conducted traits analyses using neural networks, revealing that oligolectic ground-nesting bees and cleptoparasitic bees were more likely to be extirpated whereas polylectic cavity-nesting bees were more likely to have persisted. Additionally, larger body size was associated with increased probability of local extirpation for polylectic cavity-nesting species. Larger phenological range was associated with increased chances of persistence for polylectic species, while it was associated with extirpation for oligolectic ground-nesting species. Species in the contemporary samples also had a more southerly overall distribution compared to the historic one. Open Research StatementData used for analyses in this manuscript, including Evans original dataset from 1972/1973 with updated species nomenclature, will be permanently archived at the USDA Ag Data Commons after the acceptance of this manuscript and will be citable and accessible here: https://data.nal.usda.gov/dataset/century-sampling-ecological-preserve-reveals-declining-diversity-wild-bees. Complete instructions on how to access all data referenced in this manuscript can be found in Appendix S1.

ecology↗

bioRxiv2022

Through the Random Forest: Ontogeny as a study system to connect prediction to explanation

As modeling tools and approaches become more advanced, ecological models are becoming more complex and must be investigated with novel methods of analysis. Machine learning approaches are a powerful toolset for exploring such complexity. While these approaches are powerful, results may suffer from well-known trade-offs between predictive and explanatory power. We employ an empirically rooted ontogenetically stage-structured consumer-resource model to investigate how machine learning can be used as a tool to root model analysis in mechanistic ecological principles. Applying random forest models to model output using simulation parameters as feature inputs, we extended established feature analysis into a simple graphical analysis. We used this graphical analysis to reduce model behavior to a linear function of three ecologically based mechanisms. From this model, we find that stability depends on the interaction between internal plant demographics that control the distribution of plant density across ontogenetic stages and the distribution of consumer pressure across ontogenetic stages. Predicted outcomes from these linear models rival accuracy achieved by our random forests, while explaining results as a function of ecological interactions.

ecology↗

bioRxiv2020

Phenology and flowering overlap drive specialization in pollinator networks

Variation in diet breadth and specialization stems from fundamental interactions species have with their environment1-3. Consequently, understanding the drivers of this variation is key to understanding ecological and evolutionary processes, and will facilitate the development of predictive tools as ecological networks respond to environmental change4,5. Diet breadth in wild bees has been an area of focus due to both their close mutualistic dependence on plants, and because both groups are under threat from global biodiversity loss6. Though many of the principles governing specialization for pollinators have been identified7,8, they remain largely unvalidated. Using mechanistic models of adaptive foraging in pollinators9,10, we show that while temporal resource overlap has little impact on specialization in pollinators with extended flight periods, reduced overlap increases specialization as pollinator flight periods decrease. These results are corroborated empirically using pollen load data taken from bees with shorter (genus Andrena) and longer (genus Lasioglossum) flight periods across environments with both high and low temporal resource overlap. This approach reveals how interacting phenologies structure plant-pollinator networks and drive pollinator diet breadth via the temporal overlap of floral resources.

ecology↗

bioRxiv2019

Integrating Economic dynamics into Ecological Networks: The case of fishery sustainability

Summary/AbstractUnderstanding and sustainably managing anthropogenic impact on ecosystems requires studying the integrated economic -ecological dynamics driving coupled human-natural systems. Here, we expand ecological network theory to study fishery sustainability by incorporating economic drivers into food-web models to evaluate the dynamics of thousands of single-species fisheries across hundreds of generated food-webs and two management strategies. Analysis reveals harvesting high population biomass species can initially support fishery persistence, but threatens long term economic and ecological sustainability by indirectly inducing extinction cascades in non-harvested species. This dynamic is exacerbated in open access fisheries where profit driven growth in fishing effort increases perturbation strength. Results demonstrate the unique insight into both ecological dynamics and sustainability garnered from considering economically dynamic fishing effort in the network. One Sentence SummaryIntegrating economic drivers into ecological networks reveal non-linear drivers of sustainability in fisheries.

ecology↗