ORYZA2000 : modeling lowland rice
Bouman, B.A.M. ; Kropff, M.J. ; Tuong, T.P. ; Wopereis, M.C.S. ; Berge, H.F.M. ten; Laar, H.H. van - \ 2001
Los Baños : IRRI - ISBN 9789712201714 - 235
rijst - oryza sativa - simulatiemodellen - computersimulatie - groeimodellen - computer software - rice - oryza sativa - simulation models - computer simulation - growth models - computer software
Radar modelling of coniferous forest using a tree growth model
Woodhouse, I.H. ; Hoekman, D.H. - \ 2000
International Journal of Remote Sensing 21 (2000)8. - ISSN 0143-1161 - p. 1725 - 1737.
remote sensing - microgolfstraling - groeimodellen - naaldbossen - remote sensing - microwave radiation - growth models - coniferous forests
Modeling solid-to-solid biocatalysis
Michielsen, M.J.F. - \ 1999
Agricultural University. Promotor(en): J. Tramper; H.H. Beeftink; R.H. Wijffels. - S.l. : S.n. - ISBN 9789058080806 - 190
biochemie - pseudomonas - modellen - kinetica - kristallen - groeimodellen - biochemistry - pseudomonas - models - kinetics - crystals - growth models
In this thesis, a kinetic model is described for the conversion of solid Ca-maleate to solid Ca-D-malate. The reaction is catalysed by maleate hydratase in permeabilized Pseudomonas pseudoalcaligenes and is executed in a batch reactor seeded with Ca-D-malate (product) crystals. To this end, separate kinetic models were first developed for each of the constituent steps, i.e. substrate crystal dissolution, bioconversion (with biocatalyst inactivation superimposed), and product crystal growth.
According to both the crystal dissolution and the crystal growth model, the rate is controlled by the rate of crystal surface processes, by the rate of solute transport from or to the crystal surface (in case of dissolution or growth, respectively), or by both. Tools are developed to determine the rate-controlling process(es). Dissolution of Ca-maleate crystals and growth of Ca-D-malate crystals were both found to be surface-controlled, obeying linear and exponential rate laws, respectively. The kinetic parameters were determined by fitting data sets of concentration versus time.
The biokinetic model featured substrate inhibition, competitive product inhibition, and simultaneous first-order biocatalyst inactivation. The kinetic parameters were determined by fitting the complete kinetic model simultaneously through three data sets of maleate (substrate) concentration versus time. Furthermore, the biokinetic model was used to determine under which conditions the total costs of substrate and biocatalyst were minimal in a continuous system with biocatalyst replenishment and recycling.
The individual kinetic models of the constituent processes were then integrated into one overall process model. The model gave a very good quantitative prediction of the solid-to-solid bioconversion in a batch reactor seeded with Ca-D-malate crystals.
Finally, two potentially attractive modes for operation of a reactor for solid-to-solid bioconversions, batch operation at very high concentrations of undissolved substrate and continuous operation, are evaluated with respect to their feasibility and overall costs per kg of product.
Plant morphology, environment, and leaf area growth in wheat and maize
Bos, H.J. - \ 1999
Agricultural University. Promotor(en): P.C. Struik; J. Vos. - S.l. : Bos - ISBN 9789058080035 - 149
tarwe - maïs - plantenmorfologie - bladoppervlakte - temperatuur - lichtrelaties - plantdichtheid - groeimodellen - wheat - maize - plant morphology - leaf area - temperature - light relations - plant density - growth models
Leaf area expansion of wheat (Triticum aestivum L.) and maize (Zea mays L.) plants, as contrasting representatives of the Gramineae family, was analysed. Seven variables were identified that together completely determine leaf area expansion of the plant: leaf appearance rate per tiller, specific site usage (fraction of buds that ultimately develop into a visible tiller at a specific site), Haun Stagedelay (indicating the timing of tiller appearance relative to the parent tiller), leaf elongation rate, leaf elongation duration, maximum leaf width and a leaf shape variable.
Experiments with spaced plants in growth chambers yielded equations in which the effects of leaf and tiller position, temperature and photosynthetic photon flux density (PPFD) were quantified for each leaf area variable. In non-tillering species maize, leaf appearance rate and leaf elongation rate were higher, and leaf elongation duration was shorter at higher temperatures. At higher PPFD values, leaf appearance rate and maximum leaf width were higher and leaf elongation rate was lower. In wheat, the effects of temperature and PPFD were qualitatively equal to those in maize, except that there was no effect of PPFD on maximum leaf width. In the tillering species wheat, specific site usage was higher at lower temperatures and higher PPI'D values. Equations were developed for the effects of leaf position on leaf elongation rate and maximum leaf width.
This knowledge was used in the analysis of effects of plant density in growth chamber and field experiments. Plant density mainly affected leaf appearance rate in maize and specific site usage in wheat. For both species, the effects of plant density on these variables seemed well related to local assimilate availability.
Based upon the morphological framework presented, a simulation model was developed for wheat using the principles of object orientation. Plant related processes were strictly simulated at organ level. The simulation results showed clear differences in leaf area expansion for leaves at different positions in the plant.
The morphological framework can be used for experimental analysis of leaf area growth, revealing mechanisms regulating leaf area growth of plants. The simulation model is flexible and can be easily extended for different environmental conditions and plant species.
Simulation of growth and competition in mixed stands of Douglas-fir and beech
Bartelink, H.H. - \ 1998
Agricultural University. Promotor(en): J. Goudriaan; A. van Maaren; G.M.J. Mohren. - S.l. : Bartelink - ISBN 9789054858348 - 222
bosbouw - gemengde bossen - groeimodellen - houtaanwas - voorspellen - plantensuccessie - periodiciteit - vegetatie - bomen - computersimulatie - simulatie - simulatiemodellen - pseudotsuga menziesii - fagus sylvatica - gemengde opstanden - forestry - mixed forests - growth models - increment - forecasting - plant succession - periodicity - vegetation - trees - computer simulation - simulation - simulation models - pseudotsuga menziesii - fagus sylvatica - mixed stands
For a long time, the emphasis in silviculture in Western Europe was solely on even-aged, monospecific stands; many empirical stand-level growth models were developed and successfully used for managing such stands. In contrast, no generally accepted growth and yield approach has emerged so far for mixed forests. Moreover, the inexhaustible number of species combinations, management regimes, and site-dependent interactions make an empirical approach less suitable.
In the present study, a mechanistic model was developed that simulates growth and yield in mixed forest stands. Douglas-fir ( Pseudotsuga menziesii (Mirb.) Franco) and beech ( Fagus sylvatica L.) were used in this research. In the model, tree growth is dependent on radiation availability. Stand development is largely driven by competition for radiation. A spatial module was developed to investigate the effects of tree and stand characteristics on radiation interception. The study showed that in heterogeneous stands a spatial approach is needed to account for competition between trees.
Growth of the trees was estimated using the radiation-use efficiency concept (RUE). Results revealed that detailed process models can be used to estimate RUE and that it is a suitable tool for (mixed) forest modelling.
To describe the distribution of the dry matter growth, a separate module was developed using functional relationships between tree components: the dry matter distribution is driven by the aim to maintain structural balances within the tree. The study showed that this approach is able to reproduce the development of an individual forest tree. The approach was thus considered very suitable for modelling the effects of between-tree competition for resources on growth and development of mixed forest stands.
The overall growth model, COMMIX, was applied to investigate the effects of stand composition on mixed stand productivity, using a replacement series. Analysis showed that the productivity of mixed forest stands is generally somewhere in between the yield levels of the monocultures of the less productive and the most productive species. It will only be possible to achieve higher yields in mixed stands if these stands have a relatively small proportion of the sub-dominant species. In the case of Douglas-fir and beech, the maintenance of a mixed stand appeared to conflict with the maximization of the wood production.
Insufficient data are available on mixed stands to directly support decision taking in forest management. New research tools capable of providing forest managers with information on possible management scenarios and on the consequences of certain management regimes are therefore urgently required. The present modelling approach is part of an ongoing development of models for mixed stands. The infinite variety of possible species mixtures coupled with the range of environmental conditions under which mixtures might be grown, necessitates a mechanistic approach and emphasises the potential use of such models.
Improving wheat simulation capabilities in Australia from a cropping systems perspective
Meinke, H. - \ 1996
Agricultural University. Promotor(en): R. Rabbinge; H. van Keulen; G.L. Hammer. - S.l. : Meinke - ISBN 9789054855118 - 270
triticum aestivum - tarwe - groeimodellen - teeltsystemen - simulatie - australië - triticum aestivum - wheat - growth models - cropping systems - simulation - australia
A methodology to objectively compare model components within a cropping systems model is introduced. It allows effective and efficient comparisons of modelling approaches with the help of a versatile cropping systems shell. This highly modular simulation environment allows inclusion of desired modules at the click of a button. The methodology is applied to some key wheat models currently in use for systems analysis and decision support in Australia. Thus, comprehensive data sets for model testing were required. One such data set, comprising various levels of applied nitrogen and water, is analysed using a crop physiological framework that provides all necessary parameter values for inclusion into a predictive wheat model of intermediate complexity. Further, detailed measurements of light interception during early growth showed that leaf sheaths and stems intercept a substantial amount of light during this phase. If this effect is not accounted for in a model, it can lead to a significant underestimate of anthesis dry matter when a maximum leaf area index of 2 is not exceeded. Data sets from Northern and Southern Australia, New Zealand and the USA were then used to evaluate performance of four wheat and one barley model currently used in Australia. In particular, resource utilization (water and nitrogen) was tested since the condition of the soil at the end of one cropping cycle determines the starting conditions of the next. Based on the strong and weak points highlighted during testing, the Integrated Wheat Model (I-WHEAT) was developed. Its main objective is to provide better predictive wheat modelling capabilities for inclusion in a cropping systems model. I-WHEAT combines well performing approaches from the tested models with some newly developed components. The number of input parameters needed is kept to a minimum and all coefficients can be easily derived from experimental data. It avoids the necessity of having to simulate green leaf dry matter as a means to predict leaf area. This avoids sensitive feedbacks that can generate significant error. I-WHEAT performed better than any of the tested models for resource utilization, leaf area and grain nitrogen content. Amongst others, it will be applied in Australia to investigate options for manipulating either the crop or the cropping system as an aid to pursuing improved sustainable farming practices.
Tussentijdse evaluatie van de opnamemethode van het SILVI-STAR monitoringsysteem
Os, L.J. van - \ 1994
Wageningen : IBN (IBN - rapport 064) - 13
bosbouw - plantenecologie - bomen - autecologie - habitus - levensvorm - plantenontwikkeling - groeimodellen - houtaanwas - voorspellen - synecologie - meting - experimenten - statistiek - simulatie - modellen - onderzoek - opstandsstructuur - opstandsontwikkeling - forestry - plant ecology - trees - autecology - habit - life form - plant development - growth models - increment - forecasting - synecology - measurement - experiments - statistics - simulation - models - research - stand structure - stand development
Simulatie van de potentiele groei van Populus Robusta
Salm, C. van der - \ 1993
Wageningen : DLO-Staring Centrum (Rapport / DLO - Staring Centrum 242) - 55
voorspellen - bosbouw - groeimodellen - houtaanwas - bomen - populus canadensis - forecasting - forestry - growth models - increment - trees - populus canadensis
Pinogram : a pine growth area model
Leersnijder, R.P. - \ 1992
Agricultural University. Promotor(en): R.A.A. Oldeman. - S.l. : s.n. - 164
bosbouw - bomen - computersimulatie - simulatie - simulatiemodellen - groeimodellen - houtaanwas - voorspellen - opstandsontwikkeling - opstandsstructuur - biomassa - pinus sylvestris - forestry - trees - computer simulation - simulation - simulation models - growth models - increment - forecasting - stand development - stand structure - biomass - pinus sylvestris - cum laude
Ideas about forest and forestry in the Netherlands have changed in recent years, partly because nature and recreation are in greater demand, partly because of growing environmental problems (air pollution, global warming) and partly because of the decrease in forest area worldwide. This has led to a change in the government's forest policy (Anonymus 1985, 1986, 1990). Ile current aim is to achieve a more natural-looking forest (uneven aged, mixed, native species) and to have forest management linked to natural processes and which, while cheaper, has more benefits.
As a result of this shift in policy, forestry is expected to change significantly. In the first place, silvicultural practices in Dutch forests will be aimed at achieving a more continuous forest. Clear-cutting and large plantations will be replaced by silvicultural systems in which the cutting and regeneration processes are extended over several decades and in which mixing of species plays an important role. The management of such uneven-aged and mixed forests will have to be based much more on knowledge of the behaviour of the individual tree and its *interaction with the biotic and abiotic environment than is currently the case in even-aged and pure forests.
To be able to achieve the desired changes in composition, functions and management of the Dutch forests successfully, it will be necessary to make use of the natural dynamics and developmental processes of forests. However, our current knowledge of these is certainly not complete, or is not appropriate to the Dutch *situations or has not yet been translated in silvicultural strategy. There is a clear need to find out more about forest dynamics under specific Dutch circumstances.
Forest dynamics may be studied with the help of the *autoecology and *synecology of the different forest components. Because trees are the main components establishing forest architecture, it seems rational to start by investigating the autoecology and synecology of trees. The research presented here was directed at the Scots pine ( Pinus sylvestris L.), the most common tree species in the Netherlands. It aimed at developing silvicultural information diagrams for Scots pine for different sites, provenances and treatment (tree and stand history). Silvicultural information diagrams should give information on characteristics such as *tree architecture, crown form and -dimensions, stem form, stem diameter and stem volume, and the likelihood of flowering and fructification, disease and damage and their consequences.
In principle an infinite number of silvicultural information diagrams is possible; therefore, it is necessary to determine the influence of age, site, provenance and treatment on the *phenotype of a tree to fulfil the above aim. If these relations are known, the above aim can be achieved by developing an interactive model, in which the user can input age, site, provenance and treatment. Because the model should be dependent upon tree history and age, it was decided to develop a *growth model.
Growth models may be classified according to the hierarchical levels of their output; for instance the levels "organ", "organism", "*eco-unit" and silvatic-mosaic as defined by Oldeman (1990). Growth models rarely involve more than two levels. Growth may be understood as a process which is steered by growth factors inherent in a certain starting *situation and driving it towards a new situation over time. The starting situation may be understood as a *system of a certain hierarchical level, built up from subsystems of a lower hierarchical level. Growth models on a level between "organ" and "organism" have been developed by Aono and Kunii (1984), De Reffye et al. (1989) and others. Models such as those in the "JABOWA-family" (Botkin in West et al. 1981) mainly involve the levels "eco-unit" and "silvatic-mosaic". "Spatial models" (Hara 1988) are usually at the "organism" and "eco-unit" level.
As well as being classified according to the hierarchical levels mentioned, growth models may also be classified as physiological models, architectural models and mathematical models. This classification roughly indicates the method used to describe or declare the *situations or processes the model is dealing with. Physiological models are based on physiological processes; a process is described as the result of interacting underlying processes (see De Wit 1965, Borman and Likens 1979, Hari et al. 1985, Mohren 1987). Architectural models are based on the structural appearance of a *system, in which the appearance of a system (e.g. *silvatic-mosaic, *eco-unit, organism) is defined by the pattern and appearance of the subsystems (respectively eco-units, organisms, organs). Examples of these are the models developed by Aono and Kunii (1984), De Reffye et al. (1989), Koop (1989) and others. Mathematical growth models describe the changes in the appearance of a system over time and in relation to factors that probably influence these changes. Generally, correlations and not causal relations are used to find growth equations. The "spatial" and "nonspatial" models (see Hara 1988) can be classified as mathematical models.
Because a silvicultural information diagram should demonstrate the temporal changes of the *phenotype of a tree, the model should involve both the levels between "organism" and "eco-unit" The phenotype of a tree depends upon its "*normal growth" and also upon favourable and stress factors. "Normal growth" is defined by the genetic characteristics of a tree, by a more or less constant site quality and climate during its lifetime and by *competition for light, water and nutrients. Stress factors may be diseases and plagues, environmental pollution and damage by, for example, temporary climate extremes. Favourable factors may be fertilization, changing soil water supply, immigration of mycorrhiza, etc.
The model presented here has been restricted to "normal growth". Competition is understood as competition for qualified space and constraints are not defined (e.g. available light, water or nutrients). One of the most important ways of influencing tree growth is to provide more space by cutting neighbouring trees. The model does indeed show large similarities with "spatial" models.
The models present in the current literature are either related to another hierarchical level, or do not deal with crown growth or with the *growing space of individual trees and the architecture of the "*eco-unit" Therefore none of them are really appropriate for creating a silvicultural information diagram for the different circumstances required. This is why a new model is needed.
Using information from the literature and data from an old provenance trial in Kootwijk (Province of Gelderland, the Netherlands), the influence of genetic traits, site, growing space, age and phenotype on the growth of trees was studied. It was found that the height growth of trees is mainly defined by *genotype, site characteristics and climate and that *radial growth is mainly defined by height growth and growing space. It still seems impossible to precisely predict the height growth of an individual tree during its life time. But it is probably possible to forecast the mean height growth and standard deviation for a tree of a certain provenance and on certain site.
In order to calculate the influence of the *growing space on the radial growth of trees a field study was done, in which diameter, crown length, crown width, tree height, volume, age and *normal growth area of 158 trees divided over 13 stands were measured once. The normal growth area is defined as the area in which a tree has more competitive power than its neighbours. It is calculated with the help of the distances from the *sample tree to its neighbouring trees, the distances between the consecutive neighbours and the heights of all these trees. Non-linear regression was used to correlate crown length, mean crown width and stem diameter with tree height, age and mean *growth area vector. The resulting correlations were sufficiently good to enable growth equations to be derived.
A good non-linear correlation, based on 38 felled trees, was also found between form factor on the one side and tree length, crown length and diameter on the other side. In the resulting regression equation the crown length defines the form factor better than tree length does. A reasonably good non-linear correlation was also found between mean branch diameter in the lower part of the crown and tree length, crown length and mean crown width.
The derived growth equations were used to develop a growth simulation program, called "PINOGRAM". This program, written in "Microsoft C, visualizes the growth of individual trees in relation to the *competition they experience.
In the PINOGRAM program growth is simulated in a *transect of 50 * 20 metres. The user first enters the planting distance within a row and between rows. He must also enter a minimum and maximum *S value. These values are defined as respectively the minimum and maximum heights that a tree of a certain provenance on a certain site can reach at infinite age. In *homogeneous stands the minimum and maximum S value do not differ greatly, in contrast with *heterogeneous stands. The program then assigns to each tree an S value S tree according to a normal distribution and a confidence interval of 95% between minimum and maximum S values. Finally, the user must enter the age at which he wants to see the transect.
The program calculates the height of each tree (called: sample tree) at the given age according to the Chapman-Richards function. Using the heights of a sample tree and its neighbours and the distances between these trees, the *normal growth area vectors between the sample tree and its neighbours are calculated first. Next the extent to which the trees can use these normal growth area vectors is calculated. This depends upon the possible crown length increment in the direction of the neighbour within the given time interval and without *competition (= *potential growth area vector). The normal growth area vectors and the potential growth area vectors of the sample tree and its neighbours are used to calculate the *maximum growth area that the sample tree can occupy (= maximum growth area vector). The perpendiculars of the maximum growth area vectors include the maximum growth area. Within this maximum growth area, new *maximum growth area vectors are calculated in sixteen compass points (N, NNE, NE, ENE, E, etc.). In order to find the growth area actually occupied (= * actual growth area), the potential growth area vectors in these sixteen directions are also calculated. The *actual growth area vectors are derived from the minimum of the maximum growth area vectors and the potential growth area vectors.
The actual growth area vectors are used to calculate the diameter, the crown length and crown width in sixteen directions. Next, form factor, volume and mean branch diameter (in the lower part of the crown) can be computed per tree and finally also the yield data per ha and the *canopy closure are computed. Now all the necessary data for drawing a crown map, a profile diagram or a threedimensional picture of the transect are available.
After one *situation has been computed and the crown map has been drawn, a new age can be entered and the user can request some trees to be felled. He can choose between *manual thinning (the user points out which trees have to be removed) and *automatic thinning (the user indicates whether a low thinning or a *high thinning has to be carried out and how many m 3have to be removed. At high thinning the user can indicate the critical h/cl ratio, at which a neighbouring tree should be removed). Natural mortality of a tree occurs when the tree height divided by the mean crown width of a tree exceeds six (= mortality factor M). The trees selected to be thinned are removed and now the heights and *growth areas of the remaining trees are calculated at the new age, from which the new tree dimensions are then derived.
The program displays information about stem number per ha, stem distribution, crown length and crown width, crown asymmetry, canopy closure and tree height by means of a crown map, profile diagrams and three-dimensional drawings. Underneath it displays a table showing data on the tree height, stem diameter, form factor, mean branch diameter in the lower part of the crown for individual trees, plus data on stem number per ha, basal area per ha and volume per ha of the remaining stand and of thinnings. Note that growth performance according to the equations as used in the model results in a mean expected growth for an individual tree at a given thinning regime.
This growth simulating program enables the growth of individual trees within a stand to be depicted graphically. Different silvicultural systems can be applied, to study their effects on stand growth. The graphical design makes this insight very communicable and useful (for instance, for teaching). And the results can be used in further modelling (for example, in a model of stand structure and light, or of cost and benefit, or of silvicultural system and timber quality).
The growth equations used in the model cannot be used directly on real trees. The *normal growth area of a tree, as measured in the field, often differs from the *actual growth area the tree is using at that moment. The actual growth area can be calculated using the crown widths measured in sixteen directions, but generally the matching crown lengths and diameters calculated differ from the measured ones, because these tree dimensions are not 100% correlated with age, height and actual growth area.
The model has only been tested for Scots pine on the Veluwe. It does not yet give information about *tree architecture, stem form, flowering and consequences of damage, diseases, climatic changes and environmental pollution. In its present form it also cannot yet be applied to mixed and uneven-aged stands. There is scope for improvement; fruitful avenues of future research are suggested in section 5.3.
Diameterbijgroei en boomafstand bij lijnvormige beplantingen van Populier
Jansen, J.J. - \ 1990
In: Studiekring De Populier: Verslag Studiekringdag Kon. Ned. Bosbouw Ver. / Schmidt, P., - p. 231 - 235.
grondvlak - diameter - voorspellen - bosbouw - omtrek - groene zones - groeimodellen - heggen - hoogte - houtaanwas - bepaling van groeiplaatshoedanigheden - plaatsen op afstand - dunnen - bomen - volume - oogstvoorspelling - opbrengsttabellen - bosopstanden - basal area - diameter - forecasting - forestry - girth - green belts - growth models - hedges - height - increment - site class assessment - spacing - thinning - trees - volume - yield forecasting - yield tables - forest stands
Forest dynamics, SILVI-STAR : a comprehensive monitoring system
Koop, H. - \ 1989
Agricultural University. Promotor(en): R.A.A. Oldeman. - S.l. : Koop - ISBN 9783540515777 - 229
bosbouw - plantenecologie - bomen - autecologie - habitus - levensvorm - plantenontwikkeling - groeimodellen - houtaanwas - voorspellen - synecologie - meting - experimenten - statistiek - simulatie - modellen - onderzoek - opstandsstructuur - opstandsontwikkeling - natuurlijke opstanden - forestry - plant ecology - trees - autecology - habit - life form - plant development - growth models - increment - forecasting - synecology - measurement - experiments - statistics - simulation - models - research - stand structure - stand development - natural stands - cum laude
To learn about the interactions between individual trees and between trees and other forest organisms, long-term monitoring of spontaneous forest development is necessary. A complete monitoring system has been developed including a computer package for analysis of long-term forest dynamics observations. A method of nested plot data collection on forest architecture and plant species composition has been worked out for monitoring purposes. The spatial and temporal relations between data are numerically expressed. Therefore a three-dimensional single-tree architectural model has been worked out to describe asymmetric tree shapes with a minimum of measured data points. Time series of forest development at different sites are built up on the basis of a digital descriptive model of the complex reality of forest structure and species composition.
To guarantee continuity in data storage and data query a commercially available database and a geographical information system were used in the design of the information system. A visual interpretation of data is enabled by graphical system outputs such as profiles and ground plans of tree crown projections, providing substitutes for traditional profile drawings and maps. Application programs were developed to solve specific problems, as a step towards predictive models. In an application program, for integration with remote sensing studies, an aerial view of the forest canopy is simulated on the basis of measured plot data. This view provides a ground-truth reference for the training and interpretation of remote sensing images. To explain the growth of individual trees and the distribution patterns of herbs and tree regeneration on the forest floor, another application was developed, simulating the penetration of direct and of diffuse light. For the reconstruction of forest growth with tree ring data, a technique of animation was elaborated facilitating a visual interpretation of the forest development. The system is applied to demonstrate forest development in some European forest reserves using forest architectural descriptions and vegetation releves, tree ring data and historical sources.
|De ruimtekenmerken en de sociale positie bij het vrijstellen van toekomstbomen = Indices of competition and social position in releasing crop trees
Faber, P.J. - \ 1986
Wageningen : De Dorschkamp (Rapport / Rijksinstituut voor Onderzoek in de Bos- en Landschapsbouw "De Dorschkamp" nr. 465) - 31
bosbouw - opstandsdichtheid - boomklassen - dominantie - onderdrukking - bomen - verzorgen van jonge opstanden - dunnen - groeimodellen - houtaanwas - voorspellen - opstandsontwikkeling - opstandsstructuur - biomassa - volume - bossen - meting - afmetingen - bosopstanden - forestry - stand density - tree classes - dominance - suppression - trees - tending - thinning - growth models - increment - forecasting - stand development - stand structure - biomass - volume - forests - measurement - dimensions - forest stands
|Concurrentie en groei van de bomen binnen een opstand = Competition and growth of trees within a forest stand
Faber, P.J. - \ 1983
Wageningen : Rijksinstituut voor Onderzoek in de Bos- en Landschapsbouw "De Dorschkamp" (Uitvoerig verslag / Rijksinstituut voor Onderzoek in de Bos- en Landschapsbouw "De Dorschkamp" Bd. 18, no. 1) - 116
allelopathie - biomassa - kroon - voorspellen - bosbouw - groeimodellen - houtaanwas - meting - concurrentie tussen planten - wortels - opstandsdichtheid - opstandsontwikkeling - opstandsstructuur - dunnen - bomen - pseudotsuga menziesii - bosopstanden - allelopathy - biomass - crown - forecasting - forestry - growth models - increment - measurement - plant competition - roots - stand density - stand development - stand structure - thinning - trees - pseudotsuga menziesii - forest stands
Weergave van een model voor computersimulatie van de invloed, die de faktoren standruimte, concurrentiedruk en "excentriciteit" (een gegeven waarin de situering van een boom binnen zijn groeiruimte tot uiting wordt gebracht) hebben op de groei van bomen in een houtopstand. Het model wordt toegepast op een vele jaren geregistreerd bestand van Douglas-sparren