My project focuses on integrating multiple abiotic and biotic factors to predict spatial patterns of wild bee biodiversity in agricultural landscapes. The purpose of this research is to 1) address fundamental knowledge gaps about drivers of wild bee diversity, specifically how the quantity and diversity of floral resources, proximity to water, and soil conditions interact to dictate wild bee diversity at local and landscape scales, and 2) formulate practical guidelines for farmers in implementing pollinator conservation plantings.
Biodiversity conservation is a fundamental tenet of sustainable and organic agriculture, both for its intrinsic value and the ecosystem services provided by a diverse flora and fauna. More than 90% of flowering plants and nearly 75% of major crops benefit from animal pollination. For many important pollinator-dependent crops in the Northeast, such as apple, pumpkin, watermelon, and blueberry, wild bees are more efficient pollinators than managed honey bees and are responsible for a majority of pollination services for these crops. Globally, higher wild bee diversity translates to higher fruit set of many pollinator-dependent crops, regardless of honey bee abundance.
In agricultural landscapes, adjacent natural and semi-natural habitats host a majority of the available plant species and provide crucial food resources (nectar and pollen), water, and nesting sites, as well as shelter from pesticides for pollinators. Loss of semi-natural habitat reduces floral and nesting resources available for bees, and loss of high quality nutritional resources decreases bees’ resilience to other stressors like pathogens or pesticides. The potentially synergistic effects of habitat loss/degradation and pesticide use means that agricultural landscapes can be high-risk environments for bees.
In response to these challenges, many farmers, landowners, and conservation practitioners are increasingly interested in how farmland can be designed and managed for wild bees. Indeed, farmers can receive government conservation payments for managing surrounding wildlife habitat and planting field borders, hedgerows, shelterbelts or wildflower meadows for pollinators. While there is some evidence that the recommended plant mixes can attract diverse bee communities, supplementing with specific plant species or mixes does not reliably improve pollinator outcomes.
Landscape context appears to be critical for determining if these plantings are successful: for example, the amount and arrangement of habitat in the landscape (heterogeneity and connectivity) is crucial for pollinator movement and access to resources, and is positively correlated with higher bee abundance and diversity worldwide. Studies in Europe found that ignoring the context surrounding pollinator plantings can decrease the benefits of these plantings so that there is no detectable difference between conservation and control sites.
Environmental context for pollinator conservation practices has typically been defined in terms of local plant diversity, landscape heterogeneity, and connectivity, but abiotic site conditions (such as soil quality) can also influence plant nutritional quality and pollinator visitation, and local water features provide important resources for bees. Thus, it is critical that conservation practices for pollinators take into account both biotic and abiotic context. However, accessible guidelines are very sparse for growers on how and where to implement pollinator practices in terms of abiotic and biotic factors at multiple scales. In my proposed research, I will identify the relationships among local abiotic factors, landscape context, and plant and pollinator communities to help create predictive models that can be used by land managers to optimize placement of new pollinator habitat.
To develop clear guidelines that farmers can use to design optimal pollinator habitat, we will select 30 sites in the greater Ithaca region, New York* across forest, agricultural, wetland, successional, and developed habitat typical of Northeast US agricultural landscapes. Within each of these sites, we will complete Objectives 1-3.
- Assess plant species abundance and richness (to be completed with existing data from collaborators)
- Document bee species abundance and richness.
- Measure soil moisture, fertility, and organic matter content.
Using the data from these objectives, we will complete the following analytical objectives:
- Determine relationships among local abiotic factors, including soil moisture, fertility, and proximity to water, and plant and wild bee abundance and richness. Expected Outcome: Plant and wild bee communities will be more diverse at sites close to water features, and sites with more spatially variable soil moisture, and lower soil fertility (as these sites are less likely to be dominated by a few very competitive plant species).
- Determine the relative contribution and interactions among local abiotic factors, plant diversity, landscape heterogeneity, and connectivity in explaining wild bee diversity and abundance. Expected Outcome: Local abiotic factors will interact with landscape heterogeneity and connectivity, so that there is a minimum amount of habitat necessary to support wild bees, but plant diversity and abiotic factors will significantly influence bee community diversity above this threshold.
*We originally proposed field data collection in Lancaster County, PA in arable, pasture, grassland, and forest habitats where Egan and Mortensen (2012) quantified plant diversity. In the process of preparing for the start of the funded project, Dr. Grozinger and I have developed a new collaboration with some researchers at Cornell University (see ‘Outcomes’ section below). Dr. Aaron Iverson has been leading an extensive plant community survey across the Finger Lakes region surrounding Ithaca, NY. We would like to measure bee diversity at a subset of the sites where Dr. Iverson and colleagues quantified the plant community. All of the project objectives and methods for bee and soil sampling are the same as the original proposal. Please see the ‘Materials and Methods’ below for a more detailed justification for the change in study location.
Objective 1: Plant species richness, abundance, and floral area was measured by Iverson et al (in preparation) in the greater Ithaca region, New York in 2015 and 2016. Iverson et al. surveyed 144 sites across 20 habitat types (including forest edge, dry oak forest, conifer and mixed forest, row crop, hedgerow, shrub wetland, emergent wetland, roadside ditch, etc.) that span 5 macro-habitat classes (forest, agriculture, wetland, successional, and developed). The number of sites for each habitat type ranged from 3-20 based on the plant community variability, with a median of 5 sites/habitat type. Plant communities were sampled with a half scale Modified Whittaker plot sampling design. This sampling method quantifies plant abundance as percent ground cover in 10 0.5m2 quadrats and species richness in a 500m2 plots. Iverson et al. also measured floral area for all species flowering at the time of each site visit. With multiple observations of each habitat type at different times of the year, Iverson et al generated a floral area database for all major flowering plant species within each habitat. By combining the empirical flora area data with plant flowering time drawn from regional flora references, they calculated mean floral area for each site and habitat type over the growing season.
Objective 2: I will measure bee species richness and abundance using 3.25-oz. Solo polystyrene plastic soufflé cups as bee bowls according to the protocol of a long-term bee monitoring program in our region. Blue, yellow, or white bee bowls will be filled with 50:50 mix of propylene glycol and water and placed at ground level for 10 days of sampling. Bee bowls will be set out in a 40m transect in visible areas, alternating bowl color with 5 meters between each bowl, for a total of 9 bowls per site. Bee sampling will be carried out in a minimum of 6 sites/macro-habitat type selected from the Iverson et al. (in preparation) field sites based on landowner willingness to participate in our study. Bee sampling will be conducted twice per season, first in early May and next in mid-July, guided by peak floral abundance in forest, wetland, and successional habitat. After collection, bee specimens will be stored in 70% ethyl alcohol solution until pinning and sorting. Bee specimens will be identified to genus, or species, when possible, as in my previous publication , with taxonomic assistance from collaborators within the PSU Center for Pollinator Research, including Dr. David Biddinger, Dr. Margarita López-Uribe, and Dr. Harland Patch and Sam Droege at the USGS Bee Inventory and Monitoring Lab.
Objective 3: When bee samples are collected in May 2018, soil samples will be collected from each site. We will collect measure soil moisture data with a moisture probe and take 12 soil cores to a depth of 10-20cm in a z transect at each site according to PSU soil test instructions. Cores will be combined and dried to form a representative sample for each site. A standard soil fertility and organic matter test will be conducted by the Penn State Agricultural Analytics lab (funded with external support). We chose this approach to emulate the sampling method and the soil quality information readily accessible to farmers or landowners completing a PSU soil test kit.
Objective 4: Following the Kammerer et al  analytical approach, I will use statistical models to quantify the relationship between plant richness and local soil moisture, fertility, organic matter content, proximity to water features, and landscape heterogeneity and connectivity at each site. I will calculate proximity to water features using ArcMap GIS software version 10.5 and a dataset of water features from the Tompkins County GIS office. Landscape heterogeneity will be represented with two metrics, the percent of perennial habitat land cover, and diversity of land cover types in the landscape. Landscape heterogeneity and connectivity metrics will be calculated from the 2016 USDA National Crop Data Layer using FRAGSTATS landscape analysis software and geospatial tools in the R statistical computing language. All landscape metrics will be computed at 3 scales (500m, 1000m, and 1500m) centered around each plant sampling site.
For statistical analyses, I will use either general linear mixed models or generalized linear mixed models, depending on the distribution of richness data, and specify a habitat random effect to account for variance due to habitat specific variables that were not measurable. Statistical model fits will be compared using Akaike information criterion and variance explained values. All analyses will be conducted in the R statistical computing language.
Objective 5: Analyses for this objective will use the same predictor variables and statistical methods as Objective 4, except plant species richness, evenness, and floral area at each site will be included as a predictor of bee richness.
Study location: Conducting the study in the greater Ithaca region, NY will allows us to build on an incredibly detailed, rich dataset of plant diversity and floral area across the region to study how bee diversity responds to plant community characteristics, soil, and local abiotic factors. There are a couple advantages of moving the study to New York instead of Lancaster County, PA as we originally proposed.
- Iverson et al. measured flowering plants’ floral area, which is not available in the plant dataset we have for Lancaster County, PA.
- The NY plant survey work was conducted more recently (2015/2016 compared with 2008), which decreases the likelihood for management or land use changes in the period between the plant and bee surveys. We expect this will decrease the number of sites that are not suitable for the bee survey due to land use change since the plant survey, and increase the strength of the relationship between plant diversity and bee diversity in our dataset.
- There are many more sites and habitat types represented in the Iverson et al. plant survey (144 sites over 20 habitats in NY vs. 80 sites over 5 habitats in Lancaster, PA).
- The Finger Lakes region has a larger area of pollinator dependent crops (primarily apples near the Iverson et al sites), which increases the audience for our farm design website and other outreach activities.
This project has not started yet, so has not generated any results.
Education & Outreach Activities and Participation Summary
This project has not started yet, so no outreach and educational activities have been completed to date. However, we plan to target farmers and landowners, NRCS and Xerces conservation staff, and pollinator researchers through several outreach activities and products, including an interactive farm design website, presentations at farmer and scientific society meetings, and peer reviewed publications.
One of the key outreach materials from this project will be an interactive ‘Designing farms for wild bees’ website, which will feature several case studies of farmers who have successfully implemented pollinator friendly practices on their farms. I will apply the predictive models we develop to the case study farm locations using publicly available land cover data and document this workflow, illustrating model predictions on real farms. This website will also provide a proof of concept for a full-fledged decision support tool to be developed by NRCS staff or pollinator researchers. On-farm pollinator conservation case studies will be developed in collaboration with our Cornell University collaborators, Xerces Society, and Penn State Center for Pollinator Research scientists. I will reach out to Kelly Gill, Xerces Society for Invertebrate Conservation Pollinator Conservation Specialist in the Mid-Atlantic and Northeast to review the website and facilitate its inclusion with Xerces’ library of pollinator conservation resources.
In the fall of 2017, I completed two graduate level courses on building interactive web maps to display spatial data. As a final project for my second class, I created a framework and beta version of the interactive farm design website that will be used to communicate NE SARE project results (view my final project mapping application at http://www.personal.psu.edu/kma218/GEOG585/final_project/). For the class project, I used a placeholder plant diversity dataset from Lancaster County, PA, but the final farm design website will present plant and bee data from our and collaborator field studies in Ithaca region, New York. Output maps from the modelling work and farmer case studies will be added to this website as they are developed through the NE SARE project.
In the next year (year 1 of the project), I will present at the Penn State Center for Pollinator Research annual symposium and national Entomology meeting in Vancouver, hopefully participating in a symposium on pollinator landscape models (pending symposium acceptance by conference organizers).
The U.S. National Strategy to Promote the Health of Honey Bees and Other Pollinators set a goal to restore or enhance 7 million acres by 2020, and federal agencies, farmers, and land owners need practical guidelines in deciding where and how to achieve this goal. The results of my research will be used to formulate best practices for farmers, conservation professionals, and researchers to design effective, site-specific conservation practices to support and restore diverse wild bee communities and pollination services in agricultural landscapes. For example, if my results support the expectation that sites close to water features have higher plant and wild bee diversity, choosing to preserve or enhance forest fragments surrounding streams would likely influence pollinator diversity more than conservation of similar forest patches without water. Effective guidelines for how to implement pollinator conservation will improve the return on investment for government conservation programs, supporting diverse wild bee communities essential for crop and wild plant pollination across the Northeast.
This project has not started yet, but in the process of preparing for the start of the funded project, Dr. Grozinger and I have developed a new collaboration with some researchers at Cornell University. Dr. Aaron Iverson, a post-doctoral fellow working with Dr. Scott McArt has been conducting an extensive plant community survey across the Finger Lakes region surrounding Ithaca, NY. We have started collaborating with Drs. Iverson and McArt and will survey bee diversity at a subset of the sites where Dr. Iverson and colleagues quantified the plant community. This allows us to leverage an incredibly detailed, rich dataset of plant diversity and floral area across the greater Ithaca region to study how bee diversity responds to plant community characteristics as well as soil and local abiotic factors.