Pan-tropical prediction of forest structure from the largest trees

Aim: Large tropical trees form the interface between ground and airborne observations, offering a unique opportunity to capture forest properties remotely and to investigate their variations on broad scales. However, despite rapid development of metrics to characterize the forest canopy from remotely sensed data, a gap remains between aerial and field inventories. To close this gap, we propose a new pan-tropical model to predict plot-level forest structure properties and biomass from only the largest trees. Location: Pan-tropical. Time period: Early 21st century. Major taxa studied: Woody plants. Methods: Using a dataset of 867 plots distributed among 118 sites across the tropics, we tested the prediction of the quadratic mean diameter, basal area, Lorey's height, community wood density and aboveground biomass (AGB) from the ith largest trees. Results: Measuring the largest trees in tropical forests enables unbiased predictions of plot- and site-level forest structure. The 20 largest trees per hectare predicted quadratic mean diameter, basal area, Lorey's height, community wood density and AGB with 12, 16, 4, 4 and 17.7% of relative error, respectively. Most of the remaining error in biomass prediction is driven by differences in the proportion of total biomass held in medium-sized trees (50–70 cm diameter at breast height), which shows some continental dependency, with American tropical forests presenting the highest proportion of total biomass in these intermediate-diameter classes relative to other continents. Main conclusions: Our approach provides new information on tropical forest structure and can be used to generate accurate field estimates of tropical forest carbon stocks to support the calibration and validation of current and forthcoming space missions. It will reduce the cost of field inventories and contribute to scientific understanding of tropical forest ecosystems and response to climate change

Infective Endocarditis After Transcatheter Versus Surgical Aortic Valve Replacement

Abstract Background Scarce data are available comparing infective endocarditis (IE) following surgical aortic valve replacement (SAVR) and transcatheter aortic valve replacement (TAVR). This study aimed to compare the clinical presentation, microbiological profile, management, and outcomes of IE after SAVR versus TAVR. Methods Data were collected from the “Infectious Endocarditis after TAVR International” (enrollment from 2005 to 2020) and the “International Collaboration on Endocarditis” (enrollment from 2000 to 2012) registries. Only patients with an IE affecting the aortic valve prosthesis were included. A 1:1 paired matching approach was used to compare patients with TAVR and SAVR. Results A total of 1688 patients were included. Of them, 602 (35.7%) had a surgical bioprosthesis (SB), 666 (39.5%) a mechanical prosthesis, 70 (4.2%) a homograft, and 350 (20.7%) a transcatheter heart valve. In the SAVR versus TAVR matched population, the rate of new moderate or severe aortic regurgitation was higher in the SB group (43.4% vs 13.5%; P < .001), and fewer vegetations were diagnosed in the SB group (62.5% vs 82%; P < .001). Patients with an SB had a higher rate of perivalvular extension (47.9% vs 27%; P < .001) and Staphylococcus aureus was less common in this group (13.4% vs 22%; P = .033). Despite a higher rate of surgery in patients with SB (44.4% vs 27.3%; P < .001), 1-year mortality was similar (SB: 46.5%; TAVR: 44.8%; log-rank P = .697). Conclusions Clinical presentation, type of causative microorganism, and treatment differed between patients with an IE located on SB compared with TAVR. Despite these differences, both groups exhibited high and similar mortality at 1-year follow-up

Alirocumab and cardiovascular outcomes after acute coronary syndrome

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Alirocumab and Cardiovascular Outcomes after Acute Coronary Syndrome

BACKGROUN