Elkinton, Joseph

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Professor of Entomology, Department of Plant, Soil & Insect Sciences
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Plant Sciences
Dynamics of Insect Outbreaks
Forest Entomology
Gypsy Moth Population Dynamics
Insect Conservation
Insect Population Ecology
Insect/Pathogen Interactions
Invasive Species
Lepidopteran Biology
Joe Elkinton is a professor of entomology in the Dept. of Plant, Soil and Insect Sciences at the University of Massachusetts in Amherst. His laboratory conducts research on population dynamics and biological control of invasive forest insects. His early work focused on gypsy moth and the impact of small mammal predators and viral and fungal pathogens on that system. More recent projects focus on the population dynamics of browntail moth, hemlock woolly adelgid, and winter moth. He is currently involved with efforts to introduce predatory beetles to control hemlock woolly adelgid and a tachinid parasitoid to control winter moth.

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  • Publication
    Validating Morphometrics with DNA Barcoding to Reliably Separate Three Cryptic Species of Bombus Cresson (Hymenoptera: Apidae)
    (2020-01-01) Milam, Joan; Johnson, Dennis E.; Andersen, Jeremy C.; Fassler, Aliza B.; Narango, Desiree L.; Elkinton, Joseph S.
    Despite their large size and striking markings, the identification of bumble bees (Bombus spp.) is surprisingly difficult. This is particularly true for three North American sympatric species in the subgenus Pyrobombus that are often misidentified: B. sandersoni Franklin, B. vagans Smith B. perplexus Cresson. Traditionally, the identification of these cryptic species was based on observations of differences in hair coloration and pattern and qualitative comparisons of morphological characters including malar length. Unfortunately, these characteristics do not reliably separate these species. We present quantitative morphometric methods to separate these species based on the malar length to width ratio (MRL) and the ratios of the malar length to flagellar segments 1 (MR1) and 3 (MR3) for queens and workers, and validated our determinations based on DNA barcoding. All three measurements discriminated queens of B. sandersoni and B. vagans with 100% accuracy. For workers, we achieved 99% accuracy by combining both MR1 and MR3 measurements, and 100% accuracy differentiating workers using MRL. Moreover, measurements were highly repeatable within and among both experienced and inexperienced observers. Our results, validated by genetic evidence, demonstrate that malar measurements provide accurate identifications of B. vagans and B. sandersoni. There was considerable overlap in the measurements between B. perplexus and B. sandersoni. However, these species can usually be reliably separated by combining malar ratio measurements with other morphological features like hair color. The ability to identify bumble bees is key to monitoring the status and trends of their populations, and the methods we present here advance these efforts.