Jennifer Pontius

Foliar chemistry linked to infestation and susceptibility to hemlock woolly adelgid (Homoptera: Adelgidae)

Abstract Hemlock woolly adelgid (Adelges tsugae Annand) is an invasive insect pest that is causing widespread mortality of eastern hemlock. However, some stands remain living more than a decade after infestation. To date, this has been attributed to site and climatic variables. This multi-tiered study examines the role foliar chemistry may play in A. tsugae success and subsequent hemlock decline. Comparisons of resistant and susceptible hemlock species indicate higher concentrations of P and lower concentrations of N in resistant species. On experimentally colonized hemlocks, the numbers of live sistens present after two A. tsugae generations was correlated with higher K and lower P concentrations. A regional T. canadensis monitoring effort showed that concentrations of Ca, K, N, and P were most strongly correlated with A. tsugae densities, which was the driving factor in hemlock decline. From the results of this study, we hypothesize that higher N and K concentrations may enhance hemlock palatability, thereby increasing A. tsugae population levels, whereas higher concentrations of Ca and P may deter more severe infestations. Foliar chemistry alone can explain over one-half of the variability in hemlock decline witnessed at 45 monitoring plots across the northeastern United States. Combining chemistry and traditional site factors, an 11-class decline rating could be predicted with 98% 1-class tolerance accuracy on an independent validation set. These results suggest that foliar chemistry may play a role in eastern hemlock susceptibility to A. tsugae infestation and should be included in risk assessment models.

Using changes in basal area increments to map relative risk of HWA impacts on hemlock growth across the Northeastern U.S.A

Eastern hemlock (Tsuga canadensis) is a critical species in eastern North American forests, providing a multitude of ecological and societal benefits while also acting as a foundation species in many habitats. In recent decades, however, hemlock has become threatened by hemlock woolly adelgid (HWA; Adelges tsugae), an invasive sap-feeding insect from Asia. In addition to causing the more commonly assessed metrics of foliar damage, crown decline, and hemlock mortality, HWA also decreases hemlock growth and productivity. Dendrochronological methods provide a more nuanced assessment of HWA impacts on hemlock by quantifying variable rates of radial-growth decline that follow incipient infestation. This information is necessary to better understand the variable response of hemlock to HWA, and identify the characteristics of stands with the highest potential for tolerance and recovery. To quantify decline, we calculated changes in hemlock yearly radial growth using basal area increment (BAI) measurements to identify periods of growth decline from 41 hemlock stands across New England covering a range of infestation density, duration and hemlock vigor. The onset of growth decline periods were predominantly associated with either HWA infestation or drought. However, the magnitude of change in BAI values pre- and post-decline was significantly related to HWA infestation density and crown impacts, indicating that radial growth metrics can be used to identify locations where HWA infestations have incited significant reductions in hemlock health and productivity. Additional site characteristics (slope, hillshade, and January minimum temperatures), were also significantly associated with hemlock health and productivity decline rates. In order to develop a model to identify stands likely to tolerate HWA infestation, these metrics were used to build a logit model to differentiate high- and low-BAI-reduction stands with 78% accuracy. Independent validation of the model applied to 15 hemlock sites in Massachusetts classified high and low BAI reduction classes with 80% accuracy. The model was then applied to GIS layers for New England and eastern New York to produce a spatially-explicit model that predicts the likelihood of severe hemlock growth declines if/when HWA arrives. Currently 26% of the region’s hemlock stands fall into this high risk category. Under projected climate change, this could increase to 43%. This model, along with knowledge of current HWA infestation borders, can be used to direct management efforts of potentially tolerant hemlock stands in eastern North America, with the intention of minimizing HWA-induced hemlock mortality.

A new approach for forest decline assessments: maximizing detail and accuracy with multispectral imagery

Remote sensing of forest condition is typically based on broadband vegetation indices to quantify coarse categories of canopy condition. More detailed and accurate assessments have been demonstrated using narrowband sensors, although with more limited image availability. While differences in sensor capabilities are obvious, I hypothesized that multispectral imagery may be able to detect more subtle canopy stress symptoms if a new calibration approach was considered. This involves three major changes to traditional decline assessments: (1) calibration with more detailed field measurements, (2) consideration of narrowband derived indices adapted for broadband calculation, and (3) a multivariate calibration model. Testing this approach on Landsat-5 (TM) imagery in the Catskills, NY, USA, a five-term linear regression model (r2 = 0.621, RMSE 0.403) based on a unique combination of vegetation indices sensitive to canopy chlorophyll, carotenoids, green leaf area, and water content was able to quantify a broad range of forest condition across species. When rounded to a class-based system for comparison to more traditional methods, this equation predicted decline across 42 mixed-species plots with 65% accuracy (10-classes), and 100% accuracy (5-classes). This approach was a significant improvement over commonly used vegetation indices such as NDVI (r2 = 0.351, RMSE = 0.500, 10-class accuracy = 60%, and 5-class accuracy = 74%). These results suggest that relying solely on a single common vegetation index to assess forest condition may artificially limit the accuracy and detail possible with multispectral imagery. I recommend that future efforts to monitor forest decline consider this three-pronged approach to decline predictions in order to maximize the information and accuracy obtainable with broadband sensors so widely available at this time.

Proceedings of the 8th Eastern CANUSA Forest Science Conference: Understanding and Managing ECANUSA Forests in a Changing Environment

Author. 2017. Abstract Title. In: Proceedings of the 8th Eastern CANUSA Forest Science Conference: Understanding and Managing ECANUSA Forests in a Changing Environment. Pontius, J., Schaberg, P. and J. Duncan (Eds.) September 30October 1, 2016. Burlington, VT. Forest Ecosystem Monitoring Cooperative. pp XX-XX. Digital Object Identifier: doi:10.18125/D2MW2X Available online at https://www.uvm.edu/femc/ecanusa2016#proceedings This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License