Emergence of white pine needle damage in the northeastern United States is associated with changes in pathogen pressure in response to climate change.

The defoliation of the eastern white pine (Pinus strobus) across the northeastern United States is an escalating concern threatening the ecological health of northern forests and economic vitality of the region's lumber industry. First documented in the spring of 2010 affecting 24 328 hectares in the state of Maine, white pine needle damage (WPND) has continued to spread and is now well established in all New England states. While causal agents of WPND are known, current research is lacking in both sampling distribution and the specific environmental factor(s) that affect the development and spread of this disease complex. This study aims to construct a more detailed distribution map of the four primary causal agents within the region, as well as utilize long-term WPND monitoring plots and data collected from land-based weather stations to develop a climatic model to predict the severity of defoliation events in the proceeding year. Sampling results showed a greater distribution of WPND than previously reported. WPND was generally found in forest stands that compromised >50% eastern white pine by basal area. No single species, nor a specific combination of species had a dominating presence in particular states or regions, thus supporting the disease complex theory that WPND is neither caused by an individual species nor by a specific combination of species. In addition, regional weather data confirmed the trend of increasing temperature and precipitation observed in this region with the previous year's May, June, and July rainfall being the best predictor of defoliation events in the following year. Climatic models were developed to aid land managers in predicting disease severity and accordingly adjust their management decisions. Our results clearly demonstrate the role changing climate patterns have on the health of eastern white pine in the northeastern United States.

Assessing Cyanobacterial Harmful Algal Blooms as Risk Factors for Amyotrophic Lateral Sclerosis.

Reoccurring seasonal cyanobacterial harmful algal blooms (CHABs) persist in many waters, and recent work has shown links between CHAB and elevated risk of amyotrophic lateral sclerosis (ALS). Quantifying the exposure levels of CHAB as a potential risk factor for ALS is complicated by human mobility, potential pathways, and data availability. In this work, we develop phycocyanin concentration (i.e., CHAB exposure) maps using satellite remote sensing across northern New England to assess relationships with ALS cases using a spatial epidemiological approach. Strategic semi-analytical regression models integrated Landsat and in situ observations to map phycocyanin concentration (PC) for all lakes greater than 8 ha (n = 4117) across the region. Then, systematic versions of a Bayesian Poisson Log-linear model were fit to assess the mapped PC as a risk factor for ALS while accounting for model uncertainty and modifiable area unit problems. The satellite remote sensing of PC had strong overall ability to map conditions (adj. R2, 0.86; RMSE, 11.92) and spatial variability across the region. PC tended to be positively associated with ALS risk with the level of significance depending on fixed model components. Meta-analysis shows that when average PC exposure is 100 µg/L, an all model average odds ratio is 1.48, meaning there is about a 48% increase in average ALS risk. This research generated the first regionally comprehensive map of PC for thousands of lakes and integrated robust spatial uncertainty. The outcomes support the hypothesis that cyanotoxins increase the risk of ALS, which helps our understanding of the etiology of ALS.