Linking remote sensing and various site factors for predicting the spatial distribution of eastern hemlock occurrence and relative basal area in Maine, USA

Introduced invasive pests are perhaps the most important and persistent catalyst for changes in forest composition. Infestation and outbreak of the hemlock woolly adelgid (Adelges tsugae; HWA) along the eastern coast of the USA, has led to widespread loss of hemlock (Tsuga canadensis (L.) Carr.), and a shift in tree species composition toward hardwood stands. Developing an understanding of the geographic distribution of individual species can inform conservation practices that seek to maintain functional capabilities of ecosystems. Modeling is necessary for understanding changes in forest composition, and subsequent changes in biodiversity, and one that can be implemented at the species level. By integrating the use of remote sensing, modeling, and Geographic Information Systems (GIS) coupled with expert knowledge in forest ecology and disturbance, we can advance the methodologies currently available in the literature on predictive modeling. This paper describes an approach to modeling the spatial distribution of the less common but foundational tree species eastern hemlock throughout the state of Maine (∼84,000 km2) at a high resolution. There are currently no published accuracy assessments on predictive models for high resolution continuous distribution of eastern hemlock relative basal area that span the geographic extent covered by our model, which is at the northern limit of the species’ range. A two stage mapping approach was used where presence/absence was predicted with an overall accuracy of 85% and the continuous distribution (percent basal area) was predicted with an accuracy of 84%. Overall, these findings are quite good despite high variability in the training dataset and the general minor component that eastern hemlock represents in the primary forest types in Maine. Eastern hemlock occurs along the southern half of the state stretching the east-west span with little to no occurrence in the northern regions. Several environmental and site characteristics, particularly average yearly maximum and minimum temperatures, were found to be positively correlated with hemlock occurrence. Eastern hemlock dominated stands appeared predominantly in the southwest corner of the state where HWA monitoring efforts can be focused. Given the importance of climate variables in predicting eastern hemlock, forecasts of future range shifts should be possible using data generated from climate scenarios

Two Maine Forest Pests: A Comparison of Approaches to Understanding Threats to Hemlock and Ash Trees in Maine

The authors describe two invasive insect forest pests; the hemlock wooly adelgid (HWA) has already arrived in Maine, and the emerald ash borer (EAB) has not yet reached Maine, but will have a devastating effect on the state’s Indian basketmakers when it does arrive. With funding through Maine’s Sustainability Solutions Initiative, teams based at the University of Maine and Unity College are bringing together faculty, students, and stakeholders to better understand the threats that infestations pose to the ecology and economy of the Maine’s forests and to longstanding cultural practices

Projected Future Distribution of Tsuga canadensis across Alternative Climate Scenarios in Maine, U.S

Climate change is having an impact on forest ecosystems around the world and is expected to alter the suitable habitat of individual tree species. Forest managers require resources about potential impacts of climate change at the regional scale to aid in climate mitigation efforts. By understanding the geographic distribution of changes in suitable habitat, migration corridors can be identified for conservation and active management. With the increased availability of climate projection data, ancillary Geographic Information Systems data, and field observations, modeling efforts at the regional scale are now possible. Here, we modeled and mapped the continuous distribution of Tsuga canadensis throughout the state of Maine at the regional scale(30 m) with high precision (89% of pixels had a coefficient of variation ≤ 4.0%). The random forest algorithm was used to create a strong prediction of suitable habitat for the years 2050 and 2100 from both high and low emission climate projections. The results clearly suggest a significant gain in suitable habitat for Tsuga canadensis range with a general northwest expansion