To effectively document insect presence and abundance a statistically based sampling plan is necessary. No such plan for the hemlock woolly adelgid is currently available in the published literature. Two interrelated sampling strategies allow a researcher to enter a site and determine with a given level of probability whether or not an HWA infestation is present and the level of infestation. A ground based sampling plan is also critical to the ‘ground truthing’ of aerial survey systems. A fully developed sampling plan requires relatively extensive datasets obtained over time, and may include the use of computer-generated data obtained through re-sampling techniques. The results obtained through the Harvard Forest Summer Research Program should provide a firm foundation for further development of an HWA sampling program. Data collection is on-going.

In the eastern USA, eastern hemlock (Tsuga canadensis) is the host plant for two invasive insect species - hemlock woolly adelgid (Adelges tsugae) and elongate hemlock scale (Fiorinia externa). We observed the density of adult hemlock woolly adelgid and elongate hemlock scale on eastern hemlock branches on five occasions over 14 years at 142 stands across a latitudinal transect encompassing 7,500 km2 in Connecticut and Massachusetts to assess whether there is a difference in the response to abiotic conditions (winter temperature, summer temperature, summer precipitation) between the two species, and whether the distribution and abundance of each insect species is dependent on biotic interactions with the co-occurring insect species.

Monitoring programs increasingly are used to document the spread of invasive species in the hope of detecting and eradicating low-density infestations before they become established. However, interobserver variation in the detection and correct identification of low-density populations of invasive species remains largely unexplored. In this study, we compare the abilities of volunteer and experienced individuals to detect low-density populations of an actively spreading invasive species and we explore how interobserver variation can bias estimates of the proportion of sites infested derived from occupancy models that allow for both false negative and false positive (misclassification) errors. We found that experienced individuals detected small infestations at sites where volunteers failed to find infestations. However, occupancy models erroneously suggested that experienced observers had a higher probability of falsely detecting the species as present than did volunteers. This unexpected finding is an artifact of the modeling framework and results from a failure of volunteers to detect low-density infestations rather than from false positive errors by experienced observers. Our findings reveal a potential issue with site occupancy models that can arise when volunteer and experienced observers are used together in surveys.