Cheadle Center for Biodiversity and Ecological Restoration

Aquatic invertebrates are often used as indicator species for water quality. Aquatic invertebrates were collected and identified at a protected reserve for 30+ years and at a newly restored site, previously developed as a golf course. Dissolved oxygen and salinity measurements were also taken. Results show that salinity has a stronger influence on species communities than restored state.

In 2017, UC Santa Barbara’s North Campus Open Space (NCOS) Ecological Restoration Project began major excavation on a golf course to convert it back into the upper arms of a slough and coastal mesa which historically existed in the area. Before restoration began, twenty-six coverboards were monitored between 2012 and 2014 to assess terrestrial populations of reptiles, amphibians, and invertebrates. In 2020, forty-four plywood coverboards with a uniform area (1526 in²) were deployed across various planting and restoration regimes on these 300 acres of recently restored open space. Boards are monitored weekly by a student research intern, who records vertebrate species abundance and invertebrate species presence at each site. So far, species richness and composition of herpetological inhabitants remained the same before and after restoration (six reptile and two amphibian species). However, encounter rates (our proxy for abundance), have changed for some species following restoration. Most notably, we recorded an increase in garter and gopher snakes, especially in adjacent salt marsh habitats, and a decrease of slender salamanders, which have not been found in areas of high soil movement. Our results demonstrate that the processes and outcomes of ecological restoration affect populations of reptiles and amphibians, and that these species should be considered in monitoring efforts that determine the “success” of a project. We hope to continue this monitoring for many years, both to examine the impacts of the restoration at a longer timescale and provide undergraduates with opportunities to conduct scientific research related to herpetology near their campus.

All winged insects have wing veins that form unique patterns. A strong correlation between wing size and body size has been established in the insect order Hymenoptera, including bees. Vein pattern in bees is also an important trait for identification at the genus level. However, how this pattern relates to the density of veins observed in the wing has not previously been studied and the overall relationship between wing vein number and body size has not been evaluated in bees in the absence of other hymenopteran taxa. Bee forewing vein density as it relates to body size and taxonomic group was investigated. Using dorsal and slide-plated wing images, wing vein density and intertegular span were measured for bee species within different genera and families. The study found that both taxonomic level and body size influence wing vein density, of which the taxonomic level of genus has the most significant effect, regardless of body size. This poster was presented at the UC Santa Barbara Undergraduate Research and Creative Activities Poster Colloquium on May 3rd, 2022. Github link: https://github.com/LeoEisner/Body-Size-and-Taxonomic-Influence-on-Bee-Wing-Vein-Density

Bees are important pollinators. However, their numbers and diversity are in decline which poses a serious threat to plant pollination and affects food production. The Big-Bee project (http://big-bee.net) launched in 2021 to research bee ecology and taxonomy through the digitalization of bee specimens. Bees’ ocelli are important navigational organs that receive and evaluate light intensities. The project aims at exploring the impact of bees’ sociality on potential variation in ocelli morphology. By measuring median ocellar width between sexes, I firstly tested whether sexual size dimorphism occurs in ocelli between sexes in the same bee species. Then, I evaluated whether the sexual size dimorphism exists based on social versus solitary bees. The results indicated the existence of a different median ocellar size between males and females within one species. However, such existence does not occur in males and females based on sociality categorization, indicating the sociality might not be a driver in causing the dimorphism. This poster was presented at UC Santa Barbara Undergraduate Research and Creative Activities Poster Colloquim on May 3rd, 2022.

The Cheadle Center for Biodiversity and Ecological Restoration (CCBER) is working with the UCSB Data Science capstone team to continue the research and understanding of bee ecology through image and trait digitalization.

In efforts to help researchers involved in the Big-Bee project, we want to automate the process it takes to handle and process the digital images of bees. Given images of bees with a QR/Datamatrix code, we sought to develop scripts that can rename the image files based on the decoded box and extract EXIF metadata. In the latter half of our project, we shift our focus toward the hairy characteristics of bees. Given data of high definition lateral bee images, we want to create models that can quantify how hairy a bee is. 

Results

Two scripts, the QR Code Scanner & MetaData Extractors, are published on GitHub and are currently used by two academic institutions. More trial testing is required to discover bugs and further improvements for the scripts. Using density as our metric, our U-net and transfer learning method yields an accuracy of 97.68% for bee masking and 87.2% for hair masking. Using entropy as our metric, we were able to compare the average entropy values for different bees binned in the following manner: low, middle, and high hairiness. The box-plot distribution of the bins and t-tests show that there was a positive correlation between bee hairiness and average entropy value. Furthermore, we discover that entropy analysis works best for specimens that have low reflectivity and minimal skin texture. 

QR Scanner: https://github.com/booleank/Bee-ScannerMetadata

Extractor: https://github.com/harperklauke/Metadata-Extractor

The distribution of bees can be estimated, in part, by enviromental variables associated with geography. Using bee occurrence records, we quantified the estimated species richness of the EPA level 3 defined ecoregions using coverage-based rarefaction. Our study reveals that bee species richness is highest in ecoregions with warm dry summers. Furthermore, increased species richness was found to be correlated with maximum mean temperature.

Presented at the iDigBio 6th Annual Digital Data in Biodiversity Research Conference on 05/24/2022 and the University of California Santa Barbara EEMB Undergraduate Research Symposium on 04/23/2022

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.