Simulating wood quality in forest management models

Peer reviewe

Atmospheric drivers of storage water use in Scots pine

International audienceIn this study we determined the microclimatic drivers of storage water use in Scots pine (Pinus sylvestris L.) growing in a temperate climate. The storage water use was modeled using the ANAFORE model, integrating a dynamic water flow and ? storage model with a process-based transpiration model. The model was calibrated and validated with sap flow measurements for the growing season of 2000 (26 May?18 October). Because there was no severe soil drought during the study period, we were able to study atmospheric effects. Incoming radiation was the main driver of storage water use. The general trends of sap flow and storage water use are similar, and follow more or less the pattern of incoming radiation. Nevertheless, considerable differences in the day-to-day pattern of sap flow and storage water use were observed, mainly driven by vapour pressure deficit (VPD). During dry atmospheric conditions (high VPD) storage water use was reduced. This reduction was disproportionally higher than the reduction in measured sap flow. Our results suggest that the trees did not rely more on storage water during periods of atmospheric drought, without severe soil drought. A third important factor was the tree water deficit. When storage compartments were depleted beyond a threshold, storage water use was limited due to the low water potential in the storage compartments. The maximum relative contribution of storage water to daily transpiration was also constrained by an increasing tree water deficit

Bayesian calibration, comparison and averaging of six forest models, using data from Scots pine stands across Europe

Forest management requires prediction of forest growth, but there is no general agreement about which models best predict growth, how to quantify model parameters, and how to assess the uncertainty of model predictions. In this paper, we show how Bayesian calibration (BC), Bayesian model comparison (BMC) and Bayesian model averaging (BMA) can help address these issues. We used six models, ranging from simple parameter-sparse models to complex process-based models: 3PG, 4C, ANAFORE, BASFOR, BRIDGING and FORMIND. For each model, the initial degree of uncertainty about parameter values was expressed in a prior probability distribution. Inventory data for Scots pine on tree height and diameter, with estimates of measurement uncertainty, were assembled for twelve sites, from four countries: Austria, Belgium, Estonia and Finland. From each country, we used data from two sites of the National Forest Inventories (NFIs), and one Permanent Sample Plot (PSP). The models were calibrated using the NFI-data and tested against the PSP-data. Calibration was done both per country and for all countries simultaneously, thus yielding country-specific and generic parameter distributions. We assessed model performance by sampling from prior and posterior distributions and comparing the growth predictions of these samples to the observations at the PSPs. We found that BC reduced uncertainties strongly in all but the most complex model. Surprisingly, country-specific BC did not lead to clearly better within-country predictions than generic BC. BMC identified the BRIDGING model, which is of intermediate complexity, as the most plausible model before calibration, with 4C taking its place after calibration. In this BMC, model plausibility was quantified as the relative probability of a model being correct given the information in the PSP-data. We discuss how the method of model initialisation affects model performance. Finally, we show how BMA affords a robust way of predicting forest growth that accounts for both parametric and model structural uncertainty

Applicability and precautions of use of liver injury biomarker FibroTest. A reappraisal at 7 years of age

<p>Abstract</p> <p>Background</p> <p>FibroTest (FT) is a validated biomarker of fibrosis. To assess the applicability rate and to reduce the risk of false positives/negatives (RFPN), security algorithms were developed. The aims were to estimate the prevalence of RFPN and of proven failures, and to identify factors associated with their occurrences.</p> <p>Methods</p> <p>Four populations were studied: 954 blood donors (P1), 7,494 healthy volunteers (P2), 345,695 consecutive worldwide sera (P3), including 24,872 sera analyzed in a tertiary care centre (GHPS) (P4). Analytical procedures of laboratories with RFPN > 5% and charts of P4 patients in with RFPN were reviewed.</p> <p>Results</p> <p>The prevalence of RFPN was 0.52% (5/954; 95%CI 0.17-1.22) in P1, 0.51% (38/7494; 0.36-0.70) in P2, and 0.97% (3349/345695; 0.94-1.00) in P3. Three a priori high-risk populations were confirmed: 1.97% in P4, 1.77% in HIV centre and 2.61% in Sub-Saharan origin subjects. RFPN was mostly associated with low haptoglobin (0.46%), and high apolipoproteinA1 (0.21%). A traceability study of a P3 laboratory with RFPFN > 5% permitted to correct analytical procedures.</p> <p>Conclusion</p> <p>The mean applicability rate of Fibrotest was 99.03%. Independent factors associated with the high risk of false positives/negatives were HIV center, subSaharan origin, and a tertiary care reference centre, although the applicability rate remained above 97%.</p

Quantifying the effectiveness of climate change mitigation through forest plantations and carbon sequestration with an integrated land-use model

<p>Abstract</p> <p>Background</p> <p>Carbon plantations are introduced in climate change policy as an option to slow the build-up of atmospheric carbon dioxide (CO₂) concentrations. Here we present a methodology to evaluate the potential effectiveness of carbon plantations. The methodology explicitly considers future long-term land-use change around the world and all relevant carbon (C) fluxes, including all natural fluxes. Both issues have generally been ignored in earlier studies.</p> <p>Results</p> <p>Two different baseline scenarios up to 2100 indicate that uncertainties in future land-use change lead to a near 100% difference in estimates of carbon sequestration potentials. Moreover, social, economic and institutional barriers preventing carbon plantations in natural vegetation areas decrease the physical potential by 75–80% or more.</p> <p>Nevertheless, carbon plantations can still considerably contribute to slowing the increase in the atmospheric CO₂concentration but only in the long term. The most conservative set of assumptions lowers the increase of the atmospheric CO₂concentration in 2100 by a 27 ppm and compensates for 5–7% of the total energy-related CO₂emissions. The net sequestration up to 2020 is limited, given the short-term increased need for agricultural land in most regions and the long period needed to compensate for emissions through the establishment of the plantations. The potential is highest in the tropics, despite projections that most of the agricultural expansion will be in these regions. Plantations in high latitudes as Northern Europe and Northern Russia should only be established if the objective to sequester carbon is combined with other activities.</p> <p>Conclusion</p> <p>Carbon sequestration in plantations can play an important role in mitigating the build-up of atmospheric CO₂. The actual magnitude depends on natural and management factors, social barriers, and the time frame considered. In addition, there are a number of ancillary benefits for local communities and the environment. Carbon plantations are, however, particularly effective in the long term. Furthermore, plantations do not offer the ultimate solution towards stabilizing CO₂concentrations but should be part of a broader package of options with clear energy emission reduction measures.</p

Appropriation of GPIb from platelet-derived extracellular vesicles supports monocyte recruitment in systemic inflammation

Interactions between platelets, leukocytes and the vessel wall provide alternative pathological routes of thrombo-inflammatory leukocyte recruitment. We found that when platelets were activated by a range of agonists in whole blood, they shed platelet-derived extracellular vesicles which rapidly and preferentially bound to blood monocytes compared to other leukocytes. Platelet-derived extracellular vesicle binding to monocytes was initiated by P-selectin-dependent adhesion and was stabilised by binding of phosphatidylserine. These interactions resulted in the progressive transfer of the platelet adhesion receptor GPIbα to monocytes. GPIbα+-monocytes tethered and rolled on immobilised von Willebrand Factor or were recruited and activated on endothelial cells treated with TGF-β1 to induce the expression of von Willebrand Factor. In both models monocyte adhesion was ablated by a function-blocking antibody against GPIbα. Monocytes could also bind platelet-derived extracellular vesicle in mouse blood in vitro and in vivo. Intratracheal instillations of diesel nanoparticles, to model chronic pulmonary inflammation, induced accumulation of GPIbα on circulating monocytes. In intravital experiments, GPIbα+-monocytes adhered to the microcirculation of the TGF-β1-stimulated cremaster muscle, while in the ApoE−/− model of atherosclerosis, GPIbα+-monocytes adhered to the carotid arteries. In trauma patients, monocytes bore platelet markers within 1 hour of injury, the levels of which correlated with severity of trauma and resulted in monocyte clearance from the circulation. Thus, we have defined a novel thrombo-inflammatory pathway in which platelet-derived extracellular vesicles transfer a platelet adhesion receptor to monocytes, allowing their recruitment in large and small blood vessels, and which is likely to be pathogenic