Cheadle Center for Biodiversity and Ecological Restoration

Las abejas son fundamentales para nuestra seguridad alimentaria y la polinización de las plantas silvestres y cultivadas. Sin embargo, algunas poblaciones y especies están en riesgo de desaparecer. Nuestro conocimiento de los factores que causan estas disminuciones es limitado, en parte porque carecemos de datos suficientes sobre la distribución de las especies que nos sirvan para predecir cambios en su rango geográfico bajo escenarios de cambio climático. Además, carecemos de datos adecuados sobre las características morfológicas y comportamentales que podrían influir en la vulnerabilidad de las abejas a los cambios ambientales inducidos por el hombre, como la pérdida de hábitat y el cambio climático. Afortunadamente, se puede extraer una gran cantidad de información a partir de los especímenes depositados en colecciones entomológicas. Acá presentamos este proyecto, el cual incluye 13 instituciones y es financiado por la Fundación Nacional de Ciencias de los EE. UU. (NSF, por sus siglas en Ingles). En el transcurso de tres años, crearemos más de un millón de imágenes (2D y 3D) de alta resolución de especímenes de abejas que representan alrededor de 1⁄4 de la diversidad mundial. También desarrollaremos herramientas para medir los rasgos de las abejas a partir de las imágenes. La información generada estará disponible a través de un portal de datos abierto Symbiota-Light llamado Bee Library. Además, los datos de interacción biótica y asociación de especies se compartirán a través de Global Biotic Interactions. Presented by Victor Hugo Gonzalez at the XII Congreso Mesoamericano de Abejas Nativas, Centro de Investigaciones Apícolas Tropicales (CINAT), Universidad Nacional, Costa Rica, Nov. 20-21, 2021

The macroalgae collection of the UC Santa Barbara (UCSB) Herbarium has been utilized as a resource by students and researchers at UCSB. In order to increase the scientific value of the collection, we have initiated a digitization project to add to a growing data set being assembled by a consortium of seaweed herbaria. Collectively, these data can be used to address questions of changing climate, ocean currents, invasive species, and biodiversity along the Pacific Coast of North America. Our IMLS-funded digitization project is focused on digitizing ca. 10,000 specimens in our Pacific Coast of North America collection. Our digital data are currently available on two Symbiota-based web portals: The Consortium of California Herbaria 2 and the Macroalgal Herbarium Portal. Our data are also aggregated and shared worldwide through the Global Biodiversity Information Facility (GBIF). Our digitization project is not only creating high-quality public data, but also is providing ample opportunities for learning about algae and the activities associated with curation in a natural history museum. USCB students, interns, and volunteers gain hands-on experience with our collections, seaweed identification, and phycological special events. The history and scientific insight that herbaria can tell argue for the importance of their preservation and for the continued need for new field collections. Reimagining these collections to present them to a wider audience increases the kinds of voices in science and the types of questions that can be asked about our changing world. This poster was presented at the annual meeting for the Western Society of Naturalists, which in 2021 was held virtually.

Wing venation can be used to accurately identify bees (Hymenoptera: Anthophila) to species. Wing venation patterns alone, captured by geometric morphometrics, may also be sufficient to classify variation between populations of the same species. An application of this method is presented here with bees in the genus Halictus (Hymenoptera: Halictidae). Specimens were collected from Santa Cruz Island and Santa Barbara, California. The Pacific Ocean provides a physical barrier between mainland and island populations. To analyze wing venation patterns, forewings were removed, slide mounted, imaged, and annotated with digital landmarks using TPS morphometric software for approximately 360 specimens and 9 landmarks. Data collection for this project was conducted remotely during the COVID-19 pandemic with inexpensive equipment. Results show 100% accurate discrimination of three Halictus species and less accurate discrimination of two populations of one species, H. tripartitus, collected either from mainland or island locations.

While bees are critical to sustaining a large proportion of global food production, as well as pollinating both wild and cultivated plants, they are decreasing in both numbers and diversity. Our understanding of the factors driving these declines is limited, in part, because we lack sufficient data on the distribution of bee species to predict changes in their geographic range under climate change scenarios. Additionally lacking is adequate data on the behavioral and anatomical traits that may make bees either vulnerable or resilient to human-induced environmental changes, such as habitat loss and climate change. Fortunately, a wealth of associated attributes can be extracted from the specimens deposited in natural history collections for over 100 years.

Extending Anthophila Research Through Image and Trait Digitization (Big-Bee) is a newly funded US National Science Foundation Advancing Digitization of Biodiversity Collections project. Over the course of three years, we will create over one million high-resolution 2D and 3D images of bee specimens (Fig. 1), representing over 5,000 worldwide bee species, including most of the major pollinating species. We will also develop tools to measure bee traits from images and generate comprehensive bee trait and image datasets to measure changes through time. The Big-Bee network of participating institutions includes 13 US institutions (Fig. 2) and partnerships with US government agencies. We will develop novel mechanisms for sharing image datasets and datasets of bee traits that will be available through an open, Symbiota-Light (Gilbert et al. 2020) data portal called the Bee Library. In addition, biotic interaction and species association data will be shared via Global Biotic Interactions (Poelen et al. 2014). The Big-Bee project will engage the public in research through community science via crowdsourcing trait measurements and data transcription from images using Notes from Nature (Hill et al. 2012). Training and professional development for natural history collection staff, researchers, and university students in data science will be provided through the creation and implementation of workshops focusing on bee traits and species identification. We are also planning a short, artistic college radio segment called "the Buzz" to get people excited about bees, biodiversity, and the wonders of our natural world.

This poster was prepared for TDWG 2021 virtual conference.

Ecological restoration seeks to provide quality habitat and maximize native biodiversity in small reserve areas. In restoration projects that begin on largely degraded and/or barren landscapes, constructing habitat-providing features such as hibernacula, structures for small organisms to seek refuge, can aid in the site’s colonization, particularly by small vertebrate species. In 2018, at the start of the North Campus Open Space ecological restoration project in Goleta, California, 63 hibernacula were constructed across a 90-acre landscape, scraped bare for its transformation from a golf course into coastal slough and associated habitats. These simple hibernacula consist primarily of concrete slabs (salvaged from the golf course) piled into meter-deep holes, providing many variably spaced crevices. Although these hibernacula were constructed with the intent to provide habitat for small vertebrate colonizers, a systematic assessment of their species richness and use patterns had yet to be made. Thus, in February and March of 2021, we endeavored to quantify biodiversity at the hibernacula using three survey methods: visual surveys, camera trapping, and footprint tracking tunnels. During this pilot study period, we examined 35 hibernacula for five nights each to record different species’ visitation patterns.

Visual surveys and footprint tracking tunnels were not as informative as camera trapping efforts, which revealed at least 23 vertebrate species (8 mammals/12 birds/3 reptiles) visiting the hibernacula. All 35 sites were occupied with an average of 5.28 ±1.62 species visiting each site during the 5-night camera trapping period. Ground squirrels, fence lizards, rabbits, mice, and Burrowing Owls were the most common visitors and likely occupants of these structures. Less common visitors included song and shorebird species, and meso-carnivores, two of which were new sightings at the restoration site (spotted skunk and grey fox). Occupants moved in and out of crevices and tunnels in a hibernaculum, while visitors moved over or around the structure, often investigating its entrances. Ground squirrels were the most frequently observed species and may play an ecologically important role by creating tunnels underneath the hibernacula, thereby engineering habitat for other vertebrates. Close monitoring of this process following the construction of a hibernaculum would be valuable for understanding its importance. Overall, we conclude that constructed hibernacula are a simple and low-cost method for supporting small vertebrate biodiversity and colonization at an early stage of restoration. Further implementation and monitoring of constructed habitat features are needed to determine their value, effectiveness, and contribution towards supporting biodiversity on restoration sites.

This poster was presented at the Ecological Society of America meeting, 2021.

The macroalgae collection of the UC Santa Barbara (UCSB) Herbarium has been utilized as a resource by students and researchers at UCSB. In order to increase the scientific value of the collection, we have initiated a digitization project to add to a growing data set being assembled by a consortium of seaweed herbaria. Collectively, these data can be used to address questions of changing climate, ocean currents, invasive species, and biodiversity along the Pacific Coast of North America. Our IMLS-funded digitization project is focused on digitizing ca. 10,000 specimens in our Pacific Coast of North America collection. Our digital data are currently available on two Symbiota-based web portals: The Consortium of California Herbaria 2 and the Macroalgal Herbarium Portal. Our data are also aggregated and shared worldwide through the Global Biodiversity Information Facility (GBIF). Our digitization project is not only creating high-quality public data, but also is providing ample opportunities for learning about algae and the activities associated with curation in a natural history museum. USCB students, interns, and volunteers gain hands-on experience with our collections, seaweed identification, and phycological special events. The history and scientific insight that herbaria can tell argue for the importance of their preservation and for the continued need for new field collections. Reimagining these collections to present them to a wider audience increases the kinds of voices in science and the types of questions that can be asked about our changing world. This poster was presented at the 2021 annual meeting of the Phycological Society of America, which was held virtually.

Background/Question/Methods

    A single species geographically separated into island and mainland populations often exhibits differences in phenotype between those populations. Size differences, such as dwarfism and gigantism, are well-studied particularly in mammals, but island-mainland population phenotype differences are not well-studied in insects.

Bees (Hymenoptera: Anthophila) have unique wing venation and imaged bee wings can be used to accurately identify bees to species. Wing venation patterns alone may be sufficient to classify variation between populations of the same species using geometric morphometrics. In this study, we applied these methods to determine if populations of island and mainland bees are significantly different. Populations are from Santa Cruz Island and Santa Barbara, California, a coastal mainland town. Santa Cruz Island is a 35-kilometer long island about 32 kilometers off the coast of Santa Barbara in the Pacific Ocean. Thus, there is a physical barrier between mainland and island populations. One species of sweat bee, Halictus tripartitus (Hymenoptera: Halictidae), was chosen. This species is commonly collected on both the island and the mainland, and specimens were obtained from both natural history collections and new collections. 

 To analyze wing venation patterns, both forewing and hindwing were removed, slide mounted, imaged, and annotated with digital landmarks using TPS morphometric software for approximately 500 specimens and 9 landmarks. In R, landmark coordinates were aligned with a generalized procrustes analysis (GPA) and simplified with a principal component analysis (PCA). The output of the PCA was plotted on biplots, and the output of the GPA was used in an analysis of similarities (ANOSIM) test.

Results/Conclusions

    Current ANOSIM results show that there is a statistically significant difference between island and mainland Halictus tripartitus populations (p-value < 0.05). Ongoing work includes adding additional specimens and running new tests, including non-metric multidimensional scaling (NMDS), and “envfit” regression (in R library vegan) to identify the strength and direction each of the 9 landmarks has on the group. This project shows that wing morphometrics can distinguish between populations of bees and may be a viable method of automated bee identification. Additionally, these found differences in bee wing morphology can lead to further work in island-mainland population variation, including evolutionary questions of gene flow between island and mainland populations.

Large, open-access biological datasets, like those hosted by Global Biotic Interactions (GloBI), have become increasingly accessible due to greater data collection, compilation, and storage. These databases serve to better inform our understanding of species occurrences, interactions, and ecosystem structure, broadly. In this work, we leverage GloBI data to better understand patterns of pollination, a biologically and economically essential biotic interaction between plants and pollinators. Specifically, we sought to develop a better understanding of bee specialization of pollen, an evolutionary trait in bees that underscores the stability and structure of pollinator interaction networks. We compared GloBI and expert-compiled data to better understand patterns in resource specialization.

Through our exploration of GloBI, we found several sources of bias, including the limitations of community data collection and scarcity of rare bees. We found a strong positive correlation between the number of sources (i.e. literature, natural history collection) citing the interactions of a bee species and the number of plant families visited by that same bee species. We also found that while the expert classification of bee specialists visit fewer plant families than other bees in the GloBI dataset, there are clusters of species that diverge from the expected trend. These findings indicate that observer bias, on a global scale, can skew our definition of resource specialization or generalization. Moreover, large, open-access datasets like GloBI can change our previous understanding of biological interactions and systems by accessing novel data sources and aggregation.

This poster was presented during the LB 40: "Vital Connections in Ecology: Breakthroughs in Understanding Species Interactions 2" Thursday, August 5, 2021, Ecological Society of America Meeting, Virtual, 2021

Bees (Hymenoptera: Anthophila) have unique wing venation, which can be used to classify variation between populations of the same species using geometric morphometrics. Here, an application of this method is presented, showing successful distinction between populations of the sweat bee Halictus tripartitus (Hymenoptera: Halictidae) from either island or mainland collections. These two locations are Santa Cruz Island, a 35-kilometer long island about 32 kilometers off the coast of Santa Barbara in the Pacific Ocean, and Santa Barbara, California, a coastal mainland town. 

To analyze wing patterns, forewings were removed, imaged, and annotated with digital landmarks using TPS morphometric software for 9 landmarks. Significant difference between populations is shown with an ANOSIM test (p<0.05), and principal component analysis results are visualized on a biplot. Ongoing work includes adding additional specimens and running new tests, including non-metric multidimensional scaling (NMDS), and “envfit” regression (in R library vegan) to identify the strength and direction each of the 9 landmarks has on the group.

What time of year are bees flying, where are they flying, and how do biogeographical factors, sex, and native status affect flight phenology? Consistent monitoring along with creating spatially and temporally explicit visualizations using large openly available data sets enhance our understanding of trends in flight time phenology and shape our understanding of bee-plant interactions, including shifts in the phenology of bee pollinators.

Species occurrence data from digitized collection networks (iNaturalist, Global Biodiversity Information Faculty (GBIF), Integrated Digitized Biocollections (iDigBio), Symbiota Collections of Arthropods Network (SCAN), and UC Santa Barbara Collection Network) are part of an effort to improve our understanding of bees in coastal Santa Barbara County, including the California Channel Islands. New inventory collections combined with historical data from over 11 natural history museums and 2 observation networks are used in an effort to examine patterns and changes in phenology of native and non-native bee species, and create updated species inventories.

Synthesizing species observation data from digitized natural history collections makes use of a wealth of existing data and multiplies the analytical power of isolated observations, but it is not without limitations and challenges. By exploring novel techniques to generate clear and accurate visualizations to communicate bee flight time, we present our key initial findings and identify geographic, temporal, and taxonomic gaps, which will lead to further focused inventory projects of coastal Santa Barbara County, improved data quality for phenological analyses, and reusable methods for visualizing insect phenology data across taxa or geography.