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Drivers and phenology of native bee-flower interactions in restored ponderosa pine forests




Davies, Cora Bryn, author
Davis, Thomas Seth, advisor
Redmond, Miranda, committee member
Ode, Paul, committee member

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Many ecosystems, globally, are degraded or transformed as a result of anthropomorphic activities. Ecological restoration can manage ecosystem processes by reintroducing disturbance and returning systems to historical conditions. There is a particular need for restoration treatments in forested ecosystems, such as the conifer forests along the Colorado Front Range, as changes due to a century of fire-suppression policies and logging practices have led to overly-dense, even age forest stands that are prone to stand-replacing wildfires that are hazards to human property and ecosystem health. Most flowering plants are pollinated by animals; native bees are especially important pollinators in many terrestrial systems. However, native bees are facing challenges due to rapid land use change, which have led to population declines. While there is evidence that ecological restoration can improve native bee habitat, the effects of restoration treatments on native bee populations and bee-flower interactions are poorly understood. Additionally, the mechanisms driving interactions, especially within forested ecosystems, are understudied. To address these knowledge gaps, this thesis aims to 1) summarize current understanding of the effects of ecological restoration on native bee communities, 2) use structural equation modelling to determine the mechanisms driving differences between bee-flower interactions in thinned and non-thinned forest sites, 3) further explore potential site and floral characteristics driving these interactions in canopy gap habitats, and 4) examine phenological matching between bees and floral abundance/nutrition. Bee-flower interactions were surveyed in two separate studies located in ponderosa pine (Pinus ponderosa Dougl. Ex. Laws.) dominated forests along the Colorado Front Range treated under the Collaborative Forest Landscape Restoration Program (CFLRP), which aims to restore ecological health. In the first study, native bee assemblages and interactions were compared between thinned and non-thinned stands in relation to site characteristics such as forest structure, temperature, floral resources, and nesting habitat. In the second study, over 6,500 bee-flower interactions were observed in canopy gap habitats and analyzed to understand phenological matching and interaction drivers such as floral availability, nutritional value, and visual traits. Overall, these studies suggest that native bee communities respond positively to ecological restoration in ponderosa pine forests along the Colorado Front Range. Specifically, structural equation modeling suggests that changes to forest structure result in cascading effects altering temperature, foraging availability, and nesting resources which increase native bee abundance, species richness, diversity, and interactions. The degree of phenological mismatch was site-specific and more severe for certain functional groups, such as small-sized bees. While at a site level higher pollen protein content may increase total interactions, bees tended to select flowers based on visual signals, such as color, display area, and height. These findings have important implications for ecosystem management. Specifically, the data suggest thinning and gap creation are important management practices for restoring ecological services, such as pollination, and increasing bee and floral diversity. Our results suggest that managers should consider bee functional diversity and floral phenological diversity in planning restoration projects. Both studies also identify floral species that play key roles in maintaining ecological networks, including invasive species that are often targeted for eradication in management plans. While ecosystem restoration likely benefits native bees, additional consideration should be given to maximize these benefits to ensure continued ecosystem function under uncertain future conditions.


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