Leena Finér. (1989). Biomass and nutrient cycle in fertilized and unfertilized pine, mixed birch and pine and spruce stands on a drained mire. Acta Forestalia Fennica no. 208 article id 7655. https://doi.org/10.14214/aff.7655

Keywords: fertilization; Picea abies; Betula pubescens; peatland; biomass allocation; nutrient cycle; stand modelling

Abstract | View details | Full text in PDF | Author Info

At the beginning of the investigation period the total biomass of the Scots pine (Pinus sylvestris L.) stands on the ordinary sedge pine mire was 48 t/ha. The biomass of the mixed stands of Scots pine and birch (Betula pubescens Erhr.) on the herbrich sedge pine mire was 91 t/ha, out of which 60% was from pine. The biomass of the Norway spruce (Picea abies (L.) H. Karst.) on the Vaccinium-Myrtillus spruce mire was 148 t/ha. The average annual net increment of the stand biomass was 5.8 t/ha in the unfertilized pine stand and 6.7 t/ha in the NPK and micronutrient fertilized one during the six-year investigation period. The corresponding figures in the mixed stand were 7.2 t/ha and 7.6 t/ha. The net increment of the biomass in the unfertilized spruce stand was 6.9 t/ha and in the fertilized 8.4 t/ha. A considerable proportion of the net increment was lost to the ground as litter in all stands.

The nitrogen, phosphorus, potassium, magnesium, iron, manganese, zinc, copper and boron cycles were investigated. The annual nitrogen uptake from the soil was 26–42 kg/ha, that of phosphorus 2.5–3.4 kg/ha, potassium 4.5–12 kg/ha, calcium 12–29 kg/ha, magnesium 2–4 kg/ha, iron 1.4–6.6 kg/ha, manganese less than 2 kg/ha and the other nutrients only some grams. Only part of the fertilized nutrients was fixed in the stand.

The PDF includes a summary in Finnish.

Finér, E-mail: lf@mm.unknown

Category : Research article

article id 201, category Research article

Rui Qi, Véronique Letort, Mengzhen Kang, Paul-Henry Cournède, Philippe de Reffye, Thierry Fourcaud. (2009). Application of the GreenLab model to simulate and optimize wood production and tree stability: a theoretical study. Silva Fennica vol. 43 no. 3 article id 201. https://doi.org/10.14214/sf.201

Keywords: wood quality; optimization; biomechanics; FSPM; Particle Swarm Optimization; source-sink dynamics; biomass allocation

Abstract | View details | Full text in PDF | Author Info

The GreenLab model was used to study the interaction between source-sink dynamics at the whole tree level, wood production and distribution within the stem, and tree mechanical stability through simulation and optimization. In this first promising numerical attempt, two GreenLab parameters were considered in order to maximize wood production: the sink strength for cambial growth and a coefficient that determines the way the biomass assigned to cambial growth is allocated to each metamer, through optimization and simulation respectively. The optimization procedure that has been used is based on a heuristic optimization algorithm called Particle Swarm Optimization (PSO). In the first part of the paper, wood production was maximized without considering the effect of wood distribution on tree mechanical stability. Contrary to common idea that increasing sink strength for cambial growth leads to increasing wood production, an optimal value can be found. The optimization results implied that an optimal source and sink balance should be considered to optimize wood production. In a further step, the mechanical stability of trees submitted to their self weight was taken into account based on simplified mechanical assumptions. Simulation results revealed that the allocation of wood at the stem base strongly influenced its global deformation. Such basic mechanical criterion can be an indicator of wood quality if we consider further the active biomechanical processes involved in tree gravitropic responses, e.g. formation of reaction wood.

Qi, Ecole Centrale Paris, Laboratory of Applied Mathematics, Grande Voie des Vignes, 92295 Chatenay-Malabry, France; Institute of Automation, Chinese Academy of Sciences, LIAMA/NLPR, P.O.Box 2728, Beijing, China E-mail: qiruitree@gmail.com
Letort, Ecole Centrale Paris, Laboratory of Applied Mathematics, Grande Voie des Vignes, 92295 Chatenay-Malabry, France E-mail: vl@nn.fr
Kang, Institute of Automation, Chinese Academy of Sciences, LIAMA/NLPR, P.O.Box 2728, Beijing, China E-mail: mk@nn.cn
Cournède, Ecole Centrale Paris, Laboratory of Applied Mathematics, Grande Voie des Vignes, 92295 Chatenay-Malabry, France; INRIA saclay Ile-de-France, EPI Digiplant, Parc Orsay Université, 91893 Orsay cedex, France E-mail: phc@nn.fr
Reffye, INRIA saclay Ile-de-France, EPI Digiplant, Parc Orsay Université, 91893 Orsay cedex, France; CIRAD, UMR AMAP, Montpellier, F-34000 France E-mail: pdr@nn.fr
Fourcaud, CIRAD, UMR AMAP, Montpellier, F-34000 France E-mail: tf@nn.fr

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