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Communications at congresses:
Analysing mixture effect on European beech (Fagus sylvatica L.) and Scots pine (Pinus sylvestris L.) from growth models based on NFI data
Year:2016
Research Areas
  • Forest
Information
Abstract
Introduction: National Forest Inventories (NFI) have been used frequently to study mixing effect by developing growth models. However, the use of NFI data presents advantages and disadvantages when comparing with empirical data. So, the main problem of NFI data is the difficulty to find plots in matching site conditions, i.e. to identify triplets of plots in mixtures and pure stands of studied species. This lack of control makes models developed from this data often criticized. However, in the other hand, the NFIs have one important advantage which is to consist of systematic sample plots distributed throughout the complete range of forest types in each country which cover a wide range of environmental conditions. Therefore, if models based on NFI data were really properly validated, NFI data would open great perspectives. Data: For this study data from 4 countries NFIs (Austria, France, Spain and Poland) and 2 regional inventories (Bavaria in Germany and Catalonia in Spain) were used. The data consisted of a set of sample plots located in pure stands of Scots pine or European beech as well as in mixtures of both species. For each sample plot, each country provided with stand variables (basal area, density, dominant height...) by species and total, volumes and basal area increments, and some other variables related to site (slope, aspect, annual precipitation and mean temperature). Data summary showed that plots were distributed along a wide gradient of aridity conditions according Martonne index. Methodology: Two different analyses were done using this data set. In a first step, plots located in pure stands were used to estimate maximum stand density relationships (MSDR) for Scots pine and European beech. Non linear quantile regression was applied to estimate MSDR along the Martonne gradient. The results obtained were then used to calculate relative stand density indices for the all the sample plots as well as species proportions in plots located in mixed stands. Finally, linear mixed models for basal area increment were developed for both species using pure and mixed plots. These models were analysed and their results compared with those obtained from the experimental sample plots in triplets pure and mixed stands of same species recorded in the EuMIXFOR transect study. Results: For both pine and beech species, it has been found a clear relationship between maximum densities and climate conditions, in particular with the Martonne aridity index. The more humid the site conditions the higher the maximum densities for both species, but the pattern of this variation was different. Consequently, these relationships have to be taken into account when estimating relative densities and species proportions along a wide gradient of humidity. Moreover, the analysis of growth models showed a positive effect of pine mixture in beech basal area growth, being this positive effect found along the studied humidity's gradient. On the other hand, the effect of beech in pine basal area growth was slightly negative or non significant, and this effect depended on Martonne index. In general, species mixture resulted in a total overyielding, but its degree was related with the stage of development of each species. Conclusions: National Forest Inventories represent a large data source distributed through a wide range of forest conditions being of great interest for studying mixture effects at large scales. These data, when used properly, provide similar results as those obtained from triplets.
International
Si
Congress
Integrating Scientific Knowledge in Mixed Forests
960
Place
Praga (Republica Checa)
Reviewers
Si
ISBN/ISSN
NA
http://www.vulhm.cz/en/list_of_presentations
Start Date
05/10/2016
End Date
07/10/2016
From page
0
To page
0
Participants
  • Autor: Sonia Condes Ruiz (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Inventario y Gestión de Recursos Naturales
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