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Forest health is an attractive concept in forestry research, which environmental, social, and political interests have shaped. Assessing forest health is crucial, but finding a single definition of the concept is complex. It is determined by the aim of the forest study, different areas of knowledge, scales of work, technology, methodologies, the historical moment, or the source of funding, among others. With almost a century of scientific evidence, the aim is to identify and contextualise temporal changes in the relevance of this key concept. Trends are analysed through the construction of three main descriptors (state variables, drivers, and methods) and the main conceptual subdomains (themes). This review reveals the significant geographical bias driven by diverse needs and interests. Methodologies have evolved from traditional inventories to the use of advanced tools such as remote sensing or ecophysiology, improving forest characterisation at both global and individual scales. Research has evolved from unicausality towards holistic and multidisciplinary approaches, influencing research to date and future scenarios. We identified key knowledge gaps in the scientific literature, particularly the concepts of ecosystem services, Essential Biodiversity Variables (EBVs) and the concept of "one health". These findings highlight the need for a research assessment, future directions, and scenarios for forest health research. [ABSTRACT FROM AUTHOR]

Future dynamics of biological invasions are highly uncertain because they depend on multiple social–ecological drivers. We used a scenario‐based approach to explore potential management options for invasive species in Europe. During two workshops involving a multidisciplinary team of experts, we developed a management strategy arranged into 19 goals relating to policy, research, public awareness, and biosecurity. We conceived solutions for achieving these goals under different plausible future scenarios, and identified four interrelated recommendations around which any long‐term strategy for managing invasive species can be structured: (1) a European biosecurity regime, (2) a dedicated communication strategy, (3) data standardization and management tools, and (4) a monitoring and assessment system. Finally, we assessed the feasibility of the management strategy and found substantial differences among scenarios. Collectively, our results indicate that it is time for a new strategy for managing biological invasions in Europe, one that is based on a more integrative approach across socioeconomic sectors and countries. [ABSTRACT FROM AUTHOR]

AbstractGlobally, the coffee berry borer (CBB) Hypothenemus hampei (Ferreri) is the most severe pest of the commercial coffee species arabica coffee (Coffea arabica). Heterogenous landscapes characterize many coffee-growing areas. We studied the phenology of coffee and the abundance, and development of infestation by CBB within the context an altitudinal gradient in the coffee-growing region of Caldas, Colombia. This was between 1200 m and 1800 m (a.s.l.) from September 2019 to July 2020 covering two seasons of coffee flowering. Coffee berry phenology did not differ over the altitudinal gradient studied, but CBB abundance and berry infestation differed in quantity and timings, with lower altitudes having higher abundances and proportions of infestation than higher altitudes. In the context of CBB management, October through to December is vital for coffee farms <1500 m as CBB abundance and infestation both spike, and March to June is key for farms between 1500-1700 m for the same reasons. In conclusion, coffee farmers in highly heterogeneous landscapes will have to adjust their CBB management according to the altitude gradients of their farm. [ABSTRACT FROM AUTHOR]

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Introduction: Accurate and timely detection of plant stress is essential for yield protection, allowing better-targeted intervention strategies. Recent advances in remote sensing and deep learning have shown great potential for rapid noninvasive detection of plant stress in a fully automated and reproducible manner. However, the existing models always face several challenges: 1) computational inefficiency and the misclassifications between the different stresses with similar symptoms; and 2) the poor interpretability of the host-stress interaction. Methods: In this work, we propose a novel fast Fourier Convolutional Neural Network (FFDNN) for accurate and explainable detection of two plant stresses with similar symptoms (i.e. Wheat Yellow Rust And Nitrogen Deficiency). Specifically, unlike the existing CNN models, the main components of the proposed model include: 1) a fast Fourier convolutional block, a newly fast Fourier transformation kernel as the basic perception unit, to substitute the traditional convolutional kernel to capture both local and global responses to plant stress in various time-scale and improve computing efficiency with reduced learning parameters in Fourier domain; 2) Capsule Feature Encoder to encapsulate the extracted features into a series of vector features to represent part-to-whole relationship with the hierarchical structure of the host-stress interactions of the specific stress. In addition, in order to alleviate over-fitting, a photochemical vegetation indices-based filter is placed as pre-processing operator to remove the non-photochemical noises from the input Sentinel-2 time series. Results and discussion: The proposed model has been evaluated with ground truth data under both controlled and natural conditions. The results demonstrate that the high-level vector features interpret the influence of the host-stress interaction/response and the proposed model achieves competitive advantages in the detection and discrimination of yellow rust and nitrogen deficiency on Sentinel-2 time series in terms of classification accuracy, robustness, and generalization. [ABSTRACT FROM AUTHOR]

Aims: Several cases of ertapenem‐related neurotoxicity have been published in the current literature. However, studies evaluating the ertapenem blood concentration (EBC) as a risk of these adverse events are scarce. We aimed to evaluate the relationship between the trough EBC and the risk of neurological toxicity. Methods: This was a retrospective study, including patients who underwent ertapenem treatment between October 2019 and February 2021. We excluded patients in the critical care unit and those whose blood samples were not properly taken in order to analyse ertapenem trough concentration. We also excluded patients whose clinical follow‐up was not properly realized for the entire period of ertapenem treatment. The main outcome was the presence of any suspicious neurological side effect owing to ertapenem administration and its relationship with the plasma concentration. Secondary outcomes were to identify clinical and analytical data contributing to a higher risk of neurotoxicity. Results: The initial cohort comprised 158 individuals. For the final analysis we evaluated 102 patients, reporting a neurological alteration in 13/102 (12.7%). Mean trough EBC was significantly higher in patients showing neurotoxicity in comparison with those who did not (37.8 mcg mL−1, standard deviation [SD] ± 35.7 vs. 14.6 mcg mL−1, SD ± 15.2; P =.002). In multivariable logistic regression analysis, EBC (odds ratio [OR] = 1.07; P =.006), a moderate renal insufficiency (OR = 9.2; P =.02) and a history of previous neurologic disease (OR = 9.9; P =.02) were identified as risk factors of neurological alteration during ertapenem treatment. Conclusions: In patients at risk, determining the ertapenem plasma concentration may help to minimize the risk of neurotoxicity. [ABSTRACT FROM AUTHOR]