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BackgroundThe novel COVID-19 disease has negatively impacted mortality, economic conditions, and mental health. These impacts are likely to continue after the COVID-19 pandemic ends. There are no methods for characterizing the mental health burden of the COVID-19 pandemic, and differentiating this burden from that of the prepandemic era. Accurate illness detection methods are critical for facilitating pandemic-related treatment and preventing the worsening of symptoms. ObjectiveWe aimed to identify major themes and symptom clusters in the SMS text messages that patients send to therapists. We assessed patients who were seeking treatment for pandemic-related distress on Talkspace, which is a popular telemental health platform. MethodsWe used a machine learning algorithm to identify patients’ pandemic-related concerns, based on their SMS text messages in a large, digital mental health service platform (ie, Talkspace). This platform uses natural language processing methods to analyze unstructured therapy transcript data, in parallel with brief clinical assessment methods for analyzing depression and anxiety symptoms. ResultsOur results show a significant increase in the incidence of COVID-19–related intake anxiety symptoms (P

BackgroundThe novel COVID-19 disease has negatively impacted mortality, economic conditions, and mental health. These impacts are likely to continue after the COVID-19 pandemic ends. There are no methods for characterizing the mental health burden of the COVID-19 pandemic, and differentiating this burden from that of the prepandemic era. Accurate illness detection methods are critical for facilitating pandemic-related treatment and preventing the worsening of symptoms.ObjectiveWe aimed to identify major themes and symptom clusters in the SMS text messages that patients send to therapists. We assessed patients who were seeking treatment for pandemic-related distress on Talkspace, which is a popular telemental health platform.MethodsWe used a machine learning algorithm to identify patients' pandemic-related concerns, based on their SMS text messages in a large, digital mental health service platform (ie, Talkspace). This platform uses natural language processing methods to analyze unstructured therapy transcript data, in parallel with brief clinical assessment methods for analyzing depression and anxiety symptoms.ResultsOur results show a significant increase in the incidence of COVID-19-related intake anxiety symptoms (P

A significant expansion of prescribed fire activity will be necessary to mitigate growing wildfire hazard in California forests. Forest managers can facilitate this expansion by promoting forest structures that allow for more effective implementation of prescribed fire, for both initial-entry and repeat burns. We analyzed changes in surface fuel during a series of three burns in replicated mixed-conifer stands following a period of over 100 years of fire suppression and exclusion. Total fuel load, proportion of pine present, canopy cover and basal area of live trees were relevant forest-structure components that influenced plot-scale fuel consumption. The study highlighted the importance of pre-fire fuel load and the relative proportion of pine in the overstory, which both led to greater amounts of fuel consumption. The initial-entry burn dramatically reduced all fuel categories (fine fuel, coarse wood and duff). Following each burn, fuel recovered until the next burn reduced loads enough to maintain low fuel levels. We apply the results to provide an example of how to determine the timing of prescribed fires.

Live shrubs in forest understories pose a challenge for mitigating wildfire risk with prescribed fire. Factors driving shrub consumption in prescribed fires are variable and difficult to explain. This study investigated spatial patterns and drivers of Sierra Nevada mixed-conifer forest shrub consumption in prescribed fires through analysis of high-resolution imagery taken before and after prescribed fire. We applied a spatially explicit, generalized additive model to assess tree cover and coarse woody material as potential drivers of shrub consumption. Shrub cover in two experimental stands prior to burning was 38% and 59% and was 36% and 45% one-year post-burn. In both stands shrub patch density increased, while area-weighted mean patch size and largest patch index decreased. Increased local percent cover of coarse woody material was associated with increased shrub consumption. These findings provide information for prescribed fire managers to help better anticipate shrub consumption and patchiness outcomes under similar conditions. Key words: high resolution imagery, Teakettle Experimental Forest, mixed- conifer, fire hazards, fuel treatments, coarse woody debris. Les arbustes vivants dans les sous-bois constituent un defi pour l'attenuation des risques d'incendie lors d'un brulage dirige. Les facteurs responsables de la combustion des arbustes lors des brulages diriges sont varies et difficiles a cerner. Cette etude se penche sur les patrons spatiaux et les facteurs determinants de la combustion des arbustes dans la foret mixte de coniferes de la Sierra Nevada lors de brulages diriges au moyen de l'analyse d'images a haute resolution prises avant et apres un brulage dirige. Nous avons applique un modele additif generalise, spatialement explicite, pour evaluer le couvert arborescent et le materiel ligneux grossier en tant que facteurs determinants potentiels de la combustion des arbustes. Le couvert arbustif dans deux peuplements experimentaux etait de 38 et 59 % avant le brulage et de 36 et 45 % un an apres le brulage. Dans les deux peuplements, la densite des ilots d'arbustes a augmente tandis que la taille moyenne des ilots ponderee par la superficie et l'indice des plus grands ilots ont diminue. L'augmentation locale du pourcentage de couverture du materiel ligneux grossier etait associee a l'augmentation de la combustion des arbustes. Ces resultats fournissent de l'information aux gestionnaires des brulages diriges pour les aider a mieux anticiper la combustion et la repartition en ilots des arbustes dans des conditions similaires. [Traduit par la Redaction] Mots-cles: imagerie a haute resolution, foret experimentale de Teakettle, coniferes mixtes, risque d'incendie, traitements des combustibles, debris ligneux grossiers., Introduction Shrubs are an essential ecosystem component of forested environments in the western United States and are important for wildlife, nutrient cycling, and biodiversity (Hunter 1990; North et al. 2016). [...]

Accurate estimation of forest biomass is important for scientists and policymakers interested in carbon accounting, nutrient cycling, and forest resilience. Estimates often rely on the allometry of trees; however, limited datasets, uncertainty in model form, and unaccounted-for sources of variation warrant a reexamination of allometric relationships using modern statistical techniques. We asked the following questions: (i) Is there among-stand variation in allometric relationships? (ii) Is there nonlinearity in allometric relationships? (iii) Can among-stand variation or nonlinearities in allometric equations be attributed to differences in stand age? (iv) What are the implications for biomass estimation? To answer these questions, we synthesized a dataset of small trees from six different studies in the White Mountains of New Hampshire. We compared the performance of generalized additive models (GAMs) and linear models and found that GAMs consistently outperform linear models. The best-fitting model indicates that allometries vary among both stands and species and contain subtle nonlinearities that are themselves variable by species. Using a planned contrasts analysis, we were able to attribute some of the observed among-stand heterogeneity to differences in stand age. However, variability in these results points to additional sources of stand-level heterogeneity, which if identified could improve the accuracy of live tree biomass estimation. Key words: biomass estimation, tree allometry, generalized additive models, stand effects. Une estimation juste de la biomasse forestiere est importante pour les scientifiques et les decideurs politiques qui s'interessent a la comptabilisation du carbone, au recyclage des nutriments et a la resilience des forets. Les estimations reposent souvent sur l'allometrie des arbres; cependant, les jeux de donnees limites, l'incertitude concernant la forme des modeles et les sources de variation non comptabilisees justifient qu'on reexamine les relations allometriques qui utilisent des techniques statistiques modernes. Nous avons pose les questions suivantes : (i) Est-ce que les relations allometriques varient selon le peuplement? (ii) Y a-t-il de la non-linearite dans les relations allometriques? (iii) Est-ce que la variation entre les peuplements ou la non-linearite dans les equations allometriques peuvent etre attribuees aux differences d'age entre les peuplements? (iv) Quelles sont les implications pour l'estimation de la biomasse? Pour repondre a ces questions, nous avons synthetise un jeu de donnees de petits arbres provenant de six etudes differentes realisees dans les montagnes Blanches, au New Hampshire. Nous avons compare la performance des modeles additifs generalises (MAG) et celle des modeles lineaires et nous avons trouve que les MAG etaient toujours plus performants que les modeles lineaires. Le modele le mieux ajuste indiquait que les relations allometriques varient en fonction des peuplements et de l'espece, et contiennent de subtiles non-linearites qui elles-memes varient selon l'espece. A l'aide d'une analyse de contraste planifiee nous avons pu attribuer une partie de l'heterogeneite observee parmi les peuplements a des differences d'age entre les peuplements. Cependant, la variabilite de ces resultats laisse entrevoir l'existence d'autres sources d'heterogeneite a l'echelle du peuplement qui permettraient, si elles etaient identifiees, d'ameliorer l'exactitude de l'estimation de la biomasse des arbres vivants. [Traduit par la Redaction] Mots-cles: estimation de la biomasse, allometrie des arbres, modeles additifs generalises, effets dus aux peuplements., Introduction Accurate estimation of live tree biomass is essential for scientific, economic, and policy purposes. Live trees represent a large fraction of the total forest carbon pool (Pan et al. [...]