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Society is confronted by interconnected threats to ecological sustainability. Among these is the devastation of forests by destructive non-native pathogens and insects introduced through global trade, leading to the loss of critical ecosystem services and a global forest health crisis. We argue that the forest health crisis is a public-good social dilemma and propose a response framework that incorporates principles of collective action. This framework enables scientists to better engage policymakers and empowers the public to advocate for proactive biosecurity and forest health management. Collective action in forest health features broadly inclusive stakeholder engagement to build trust and set goals; accountability for destructive pest introductions; pooled support for weakest-link partners; and inclusion of intrinsic and nonmarket values of forest ecosystems in risk assessment. We provide short-term and longer-term measures that incorporate the above principles to shift the societal and ecological forest health paradigm to a more resilient state. Expected final online publication date for the Annual Review of Phytopathology, Volume 61 is September 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates. 

The ability to detect diseased trees before symptoms emerge is key in forest health management because it allows for more timely and targeted intervention. The objective of this study was to develop an in-field approach for early and rapid detection of beech leaf disease (BLD), an emerging disease of American beech trees, based on supervised classification models of leaf near-infrared (NIR) spectral profiles. To validate the effectiveness of the method we also utilized a qPCR-based protocol for the quantification of the newly identified foliar nematode identified as the putative causal agent of BLD, Litylenchus crenatae ssp. mccannii (LCM). NIR spectra were collected in May, July, and September of 2021 and analyzed using support vector machine and random forest algorithms. For the May and July datasets, the models accurately predicted pre-symptomatic leaves (highest testing accuracy = 100%), but also accurately discriminated the spectra based on geographic location (highest testing accuracy = 90%). Therefore, we could not conclude that spectral differences were due to pathogen presence alone. However, the September dataset removed location as a factor and the models accurately discriminated pre-symptomatic from naïve samples (highest testing accuracy = 95.9%). Five spectral bands (2,220, 2,400, 2,346, 1,750, and 1,424 nm), selected using variable selection models, were shared across all models, indicating consistency with respect to phytochemical induction by LCM infection of pre-symptomatic leaves. Our results demonstrate that this technique holds high promise as an in-field diagnostic tool for BLD. 

Climate change (CC) conditions projected for many temperate areas of the world, expressed by way of excessive temperatures and low water availability, will impact forest health directly by means of abiotic stress but also by predisposing trees to pathogenic attack. However, we do not yet know how such environmental conditions alter the physiology and metabolism of trees to render them more susceptible to pathogens. To explore these mechanisms, we conditioned 3-year-old Austrian pine saplings to a simulated CC environment (combined drought and elevated temperatures), followed by pathogenic inoculation with two sister fungal species characterized by contrasting aggressiveness, Diplodia sapinea (aggressive) and D. scrobiculata (less aggressive). Lesion lengths resulting from infection were measured after 3 weeks to determine phenotypes, while dual transcriptomics analysis was conducted on tissues collected from the margins of developing lesions on separate branches 72 h post inoculation. As expected, climate change conditions enhanced host susceptibility to the less aggressive pathogen, D. scrobiculata , to a level that was not statistically different from the more aggressive D. sapinea . Under controlled climate conditions, D. sapinea induced suppression of critical pathways associated with host nitrogen and carbon metabolism, while enhancing its own carbon assimilation. This was accompanied by suppression of host defense-associated pathways. In contrast, D. scrobiculata infection induced host nitrogen and fatty acid metabolism as well as host defense response. The CC treatment, on the other hand, was associated with suppression of critical host carbon and nitrogen metabolic pathways, alongside defense associated pathways, in response to either pathogen. We propose a new working model integrating concurrent host and pathogen responses, connecting the weakened host phenotype under CC treatment with specific metabolic compartments. Our results contribute to a richer understanding of the mechanisms underlying the oft-observed increased susceptibility to fungal infection in trees under conditions of low water availability and open new areas of investigation to further integrate our knowledge in this critical aspect of tree physiology and ecology.