Simulating wood quality in forest management models

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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

Extensions of the matrix Gelfand-Dickey hierarchy from generalized Drinfeld-Sokolov reduction

The $p\times p$ matrix version of the $r$-KdV hierarchy has been recently treated as the reduced system arising in a Drinfeld-Sokolov type Hamiltonian symmetry reduction applied to a Poisson submanifold in the dual of the Lie algebra $\widehat{gl}_{pr}\otimes {\Complex}[\lambda, \lambda^{-1}]$. Here a series of extensions of this matrix Gelfand-Dickey system is derived by means of a generalized Drinfeld-Sokolov reduction defined for the Lie algebra $\widehat{gl}_{pr+s}\otimes {\Complex}[\lambda,\lambda^{-1}]$ using the natural embedding $gl_{pr}\subset gl_{pr+s}$ for $s$ any positive integer. The hierarchies obtained admit a description in terms of a $p\times p$ matrix pseudo-differential operator comprising an $r$-KdV type positive part and a non-trivial negative part. This system has been investigated previously in the $p=1$ case as a constrained KP system. In this paper the previous results are considerably extended and a systematic study is presented on the basis of the Drinfeld-Sokolov approach that has the advantage that it leads to local Poisson brackets and makes clear the conformal ($\cal W$-algebra) structures related to the KdV type hierarchies. Discrete reductions and modified versions of the extended $r$-KdV hierarchies are also discussed.Comment: 60 pages, plain TE

KEYLINK: Towards a more integrative soil representation for inclusion in ecosystem scale models - II: Model description, implementation and testing

New knowledge on soil structure highlights its importance for hydrology and soil organic matter (SOM) stabilization, which however remains neglected in many wide used models. We present here a new model, KEYLINK, in which soil structure is integrated with the existing concepts on SOM pools, and elements from food web models, that is, those from direct trophic interactions among soil organisms. KEYLINK is, therefore, an attempt to integrate soil functional diversity and food webs in predictions of soil carbon (C) and soil water balances. We present a selection of equations that can be used for most models as well as basic parameter intervals, for example, key pools, functional groups' biomasses and growth rates. Parameter distributions can be determined with Bayesian calibration, and here an example is presented for food web growth rate parameters for a pine forest in Belgium. We show how these added equations can improve the functioning of the model in describing known phenomena. For this, five test cases are given as simulation examples: changing the input litter quality (recalcitrance and carbon to nitrogen ratio), excluding predators, increasing pH and changing initial soil porosity. These results overall show how KEYLINK is able to simulate the known effects of these parameters and can simulate the linked effects of biopore formation, hydrology and aggregation on soil functioning. Furthermore, the results show an important trophic cascade effect of predation on the complete C cycle with repercussions on the soil structure as ecosystem engineers are predated, and on SOM turnover when predation on fungivore and bacterivore populations are reduced. In summary, KEYLINK shows how soil functional diversity and trophic organization and their role in C and water cycling in soils should be considered in order to improve our predictions on C sequestration and C emissions from soils. © 2021 PeerJ Inc.. All rights reserved.The following grant information was disclosed by the authors: COST (European Cooperation in Science and Technology): FP1305 (BioLink) and ES1406 (KEYSOM). Short Term Scientific Mission (STSM) programs. Spanish Ministry of Science, Innovation and Universities. Spanish Ministry of Economy and Competitiveness (MINECO): IBERYCA (CGL2017-84723-P). BC3 María de Maeztu Excellence Accreditation: MDM-2017-0714. Basque Government: BERC 2018-2021. This article is based upon work from COST Actions FP1305 (BioLink) and ES1406 (KEYSOM), supported by COST (European Cooperation in Science and Technology), and their Short Term Scientific Mission (STSM) programs. Omar Flores’ work was funded by FPU PhD grant program of the Spanish Ministry of Science, Innovation and Universities. Jorge Curiel Yuste received funding from the Spanish Ministry of Economy and Competitiveness (MINECO) under projects IBERYCA (CGL2017-84723-P) and the BC3 María de Maeztu excellence accreditation (MDM-2017-0714). Jorge Curiel Yuste also received funding from the Basque Government through the BERC 2018-2021 program. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

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