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This paper reports a non-native Agrilus wood-boring jewel beetle reared from a stressed and non-native European beech (Fagus sylvatica) tree growing in New York City, USA. Results of two analyses using 759 DNA barcodes of Agrilus corroborate the morphology-based interpretation that this is the first North American record of an unnamed species from the A. roscidus species-group native to the Western Palaearctic. Taxonomy of the entire species-group requires revision, therefore we postpone formal description of the new species and refer to it as Agrilus sp. 9895. This is the 12th non-native Agrilus established in North America. Prior to our study, members of the A. roscidus species-group were not known to develop in Fagus, therefore we hypothesise whether our record is a host plant shift linked to the human-mediated transatlantic dispersal, or a case of an elusive beetle escaping detection in Fagus in its unknown native range. [ABSTRACT FROM AUTHOR]

The recently emerged beech leaf disease (BLD) is causing the decline and death of American beech in North America. First observed in 2012 in northeast Ohio, U.S.A., BLD had been documented in 10 northeastern states and the Canadian province of Ontario as of July 2022. A foliar nematode has been implicated as the causal agent, along with some bacterial taxa. No effective treatments have been documented in the primary literature. Irrespective of potential treatments, prevention and prompt eradication (rapid responses) remain the most cost-effective approaches to the management of forest tree disease. For these approaches to be feasible, however, it is necessary to understand the factors that contribute to BLD spread and use them in estimation of risk. Here, we conducted an analysis of BLD risk across northern Ohio, western Pennsylvania, western New York, and northern West Virginia, U.S.A. In the absence of symptoms, an area cannot necessarily be deemed free of BLD (i.e., absence of BLD cannot be certain) due to its fast spread and the lag in symptom expression (latency) after infection. Therefore, we employed two widely used presence-only species distribution models (SDMs), one-class support vector machine (OCSVM), and maximum entropy (Maxent) to predict the spatial pattern of BLD risk based on BLD presence records and associated environmental variables. Our results show that both methods work well for BLD environmental risk modeling purposes, but Maxent outperforms OCSVM with respect to both the quantitative receiver operating characteristics (ROC) analysis and the qualitative evaluation of the spatial risk maps. Meanwhile, the Maxent model provides a quantification of variable contribution for different environmental factors, indicating that meteorological (isothermality and temperature seasonality) and land cover type (closed broadleaved deciduous forest) factors are likely key contributors to BLD distribution. Moreover, the future trajectories of BLD risk over our study area in the context of climate change were investigated by comparing the current and future risk maps obtained by Maxent. In addition to offering the ability to predict where the disease may spread next, our work contributes to the epidemiological characterization of BLD, providing new lines of investigation to improve ecological or silvicultural management. Furthermore, this study shows strong potential for extension of environmental risk mapping over the full American beech distribution range so that proactive management measures can be put in place. Similar approaches can be designed for other significant or emerging forest pest problems, contributing to overall management efficiency and efficacy., Competing Interests: The author(s) declare no conflict of interest.

Background: Beech bark disease is an insect-fungus complex that damages and often kills American beech trees and has major ecological and economic impacts on forests of the northeastern United States and southeastern Canadian forests. The disease begins when exotic beech scale insects feed on the bark of trees, and is followed by infection of damaged bark tissues by one of the Neonectria species of fungi. Proteomic analysis was conducted of beech bark proteins from diseased trees and healthy trees in areas heavily infested with beech bark disease. All of the diseased trees had signs of Neonectria infection such as cankers or fruiting bodies. In previous tests reported elsewhere, all of the diseased trees were demonstrated to be susceptible to the scale insect and all of the healthy trees were demonstrated to be resistant to the scale insect. Sixteen trees were sampled from eight geographically isolated stands, the sample consisting of 10 healthy (scale-resistant) and 6 diseased/infested (scale-susceptible) trees. Results: Proteins were extracted from each tree and analysed in triplicate by isoelectric focusing followed by denaturing gel electrophoresis. Gels were stained and protein spots identified and intensity quantified, then a statistical model was fit to identify significant differences between trees. A subset of BBD differential proteins were analysed by mass spectrometry and matched to known protein sequences for identification. Identified proteins had homology to stress, insect, and pathogen related proteins in other plant systems. Protein spots significantly different in diseased and healthy trees having no stand or disease-by-stand interaction effects were identified. Conclusions: Further study of these proteins should help to understand processes critical to resistance to beech bark disease and to develop biomarkers for use in tree breeding programs and for the selection of resistant trees prior to or in early stages of BBD development in stands. Early identification of resistant trees (prior to the full disease development in an area) will allow forest management through the removal of susceptible trees and their root-sprouts prior to the onset of disease, allowing management and mitigation of costs, economic impact, and impacts on ecological systems and services. [ABSTRACT FROM AUTHOR]

We reconstructed the late-Holocene surface-moisture history and vegetation dynamics of a raised bog in Michigan using testate amoebae, peat humification, pollen, stomata and plant macrofossils. Our primary objective was to compare bog palaeohydrology with the water-level history of Lake Michigan, and to regional and local vegetation changes. Hydrologic histories inferred from testate amoebae and humification show similar trends, and correspond with records of past water-level variability in Lake Michigan. The bog clearly shows effective-moisture increases during the Algoma highstand (~3200-2300 cal. BP) and a later unnamed highstand (~1900-1300 cal. BP). Some higher-frequency fluctuations are also similar. The good correspondence indicates that bog hydrology and the water levels of Lake Michigan have been driven by changes in large-scale atmospheric circulation patterns for at least the past 3500 years. Climate during the Algoma highstand may have been spatiotemporally complex, with increasing moisture occurring several hundred years earlier in the northern portion of the western Great Lakes basin. Locally, the expansion and contraction of Picea populations on the bog surface was probably directly related to moisture conditions. The well-documented decline in Fagus populations in the central Great Lakes region after 1000 cal. BP is contemporaneous with a major shift towards drier conditions, suggesting that relative dryness caused the decline. [ABSTRACT FROM AUTHOR]