Geocentric alternatives to site index for modeling tree increment in uneven-aged mixed stands

Dănescu, Adrian; Albrecht, Axel; Bauhus, Jürgen; Kohnle, Ulrich

doi:10.1016/j.foreco.2017.02.045

Cited by 28 publications

(27 citation statements)

References 53 publications

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“…This method is based on predicting the growth of a tree on an average site and setting this in relation to its observed growth [48]. The same kind of modelling has been used as a productivity index at the stand level [49] or by using modified residuals of the individual tree growth model [50]. To predict tree growth on an average site, we modelled the annual past radial increment (APRI) of a tree of a certain species as a function of species-specific competition, tree size, and climate but omitting site variables (Equation (13)).…”

Section: Site Variablesmentioning

confidence: 99%

Mixing Effects in Norway Spruce—European Beech Stands Are Modulated by Site Quality, Stand Age and Moisture Availability

Houpert

Rohner

Forrester

et al. 2018

Forests

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Abstract:Although mixing tree species is considered an efficient risk-reduction strategy in the face of climate change, the conditions where mixtures are more productive than monocultures are under ongoing debate. Generalizations have been difficult because of the variety of methods used and due to contradictory findings regarding the effects of the species investigated, mixing proportions, and many site and stand conditions. Using data from 960 plots of the Swiss National Forest Inventory data, we assessed whether Picea abies (L.) Karst-Fagus sylvatica L. mixed stands are more productive than pure stands, and whether the mixing effect depends on site-or stand-characteristics. The species proportions were estimated using species proportion by area, which depends on the maximum stand basal area of an unmanaged stand (BA max ). Four different alternatives were used to estimate BA max and to investigate the effect of these differing alternatives on the estimated mixture effect. On average, the mixture had a negative effect on the growth of Picea abies. However, this effect decreased as moisture availability increased. Fagus sylvatica grew better in mixtures and this effect increased with site quality. A significant interaction between species proportions and quadratic mean diameter, a proxy for stand age, was found for both species: the older the stand, the better the growth of Fagus sylvatica and the lower the growth of Picea abies. Overyielding was predicted for 80% of the investigated sites. The alternative to estimate BA max weakly modulated the estimated mixture effect, but it did not affect the way mixing effects changed with site characteristics.

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Section: Site Variablesmentioning

confidence: 99%

Mixing Effects in Norway Spruce—European Beech Stands Are Modulated by Site Quality, Stand Age and Moisture Availability

Houpert

Rohner

Forrester

et al. 2018

Forests

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“…CART was applied using the height of dominant trees (DH) at a reference age of 20 years as a response variable. The height of dominant trees at a reference age has been used in our study because it is the most common indicator to measure site productivity in even-aged stands and therefore is an index of forest productivity widely used in forestry [64,65]. It is recommended for studies of site classification and stand productivity [66], basically because it is less dependent on stand density and thinning [67].…”

Section: Statistical Analysesmentioning

confidence: 99%

Forest Site Classification in the Southern Andean Region of Ecuador: A Case Study of Pine Plantations to Collect a Base of Soil Attributes

Quichimbo

Jiménez

Veintimilla

et al. 2017

Forests

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Forest site classification adapted to the respective site conditions is one prerequisite for sustainable silviculture. This work aims to initiate the forest site classification for pine plantations in the southern Andean region of Ecuador. Forest productivity, estimated by the dominant height of 20-year-old trees (DH 20 ), was related to data from climate, topography, and soil using 23 plots installed in pine plantations in the province of Loja. Forest site productivity was classified as: low (class C: 13.4 m), middle (class B: 16.6 m), and high (Class A: 22.3 m). Strong determinants to differentiate the forest site classes were: the short to medium term available Ca and K stocks (organic layer + mineral soil standardized to a depth of 60 cm), soil acidity, the C:N ratio, clay and sand content, forest floor thickness, altitude, and slope. The lowest forest productivity (Class C) is mainly associated with the lowest short to medium term available K and Ca stocks. Whereas, in site classes with the highest forest productivity, pines could benefit from a more active microbial community releasing N and P, since the soil pH was about 1 unit less acidic. This is supported by the lowest forest floor thickness and the narrowest C:N ratio.

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“…Knowing the site productivity of a forest species in a specific area of interest is essential to attain sustainable forest management (Mitsuda, 2007;Cruz et al, 2008;Ribeiro et al, 2016;Yue et al, 2016;Dãnescu et al, 2017). Therefore, the practical need for forest productivity assessment has encouraged the development of several quantitative methodologies.…”

Section: Introductionmentioning

confidence: 99%

“…However, site index does not represent the true site quality as it does not fully integrate the site factors. Therefore, more recently prediction models for site index evaluation using regression techniques have included environmental factors such as climatic, topographic or soil related attributes to improve forest productivity assessment (Fontes et al, 2004;Aersten et al, 2010;Salas, 2010;Nunes et al, 2011;Dãnescu et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Developing an Index for Forest Productivity Mapping - A Case Study for Maritime Pine Production Regulation in Portugal

et al. 2018

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-Productivity is very dependent on the environmental and biotic factors present at the site where the forest species of interest is present. Forest site productivity is usually assessed using empirical models applied to inventory data providing discrete predictions. While the use of GIS-based models enables building a site productivity distribution map. Therefore, the aim of this study was to derive a productivity index using multivariate statistics and coupled GIS-geostatistics to obtain a forest productivity map. To that end, a study area vastly covered by naturally regenerated forests of maritime pine in central Portugal was used. First, a productivity index (PI) was built based on Factorial Correspondence Analysis (FCA) by incorporating a classical site index for the species and region (Sh25 -height index model) and GIS-derived environmental variables (slope and aspect). After, the PI map was obtained by multi-Gaussian kriging and used as a GIS layer to evaluate maritime pine areas by productivity class (e.g., low, intermediate and high). In the end, the area control method was applied to assess the size and the number of compartments to establish by productivity class. The management compartments of equal productivity were digitized as GIS layer and organized in a temporal progression of stands' age regularly available for cutting each year during a 50-year schedule. The methodological approach developed in this study proved that can be used to build forest productivity maps which are crucial tools to support forest production regulation.Keywords: Site Productivity Classes; Area Control Method; Forest Management Compartments. DESENVOLVIMENTO DE UM ÍNDICE PARA O MAPEAMENTO DA PRODUTIVIDADE FLORESTAL -UM ESTUDO DE CASO PARA A REGULAÇÃO DA PRODUÇÃO DO PINHEIRO BRAVORESUMO -A produtividade florestal depende dos fatores ambientais e bióticos da estação onde a espécie florestal se encontra. A produtividade da estação florestal é geralmente avaliada com modelos empíricos aplicados a dados de inventário fornecendo previsões discretas. Enquanto o uso de modelos num SIG permite a construção de mapas de distribuição de produtividade da estação. Assim, o objetivo deste estudo foi desenvolver um índice de produtividade utilizando estatística multivariada e geoestatística acopladas ao SIG para obter um mapa de produtividade florestal. Para o efeito, selecionou-se uma área de estudo com floresta de regeneração natural de pinheiro bravo no centro de Portugal. Primeiramente, o índice de produtividade (PI) foi construído usando a Análise Fatorial das Correspondências (FCA) com um índice de qualidade de estação para a espécie e região (Sh25-modelo de índice de altura) e variáveis ambientais (declive e exposição). Depois, o mapa PI foi obtido por Krigagem multi-Gaussiana e usado como camada SIG para avaliar as áreas da espécie por classe de produtividade (p.e., baixa, intermedia e alta). No final, o método de controle da área foi aplicado para determinar o tamanho e o número de parcelas a serem estabelecidas por class...

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Geocentric alternatives to site index for modeling tree increment in uneven-aged mixed stands

Cited by 28 publications

References 53 publications

Mixing Effects in Norway Spruce—European Beech Stands Are Modulated by Site Quality, Stand Age and Moisture Availability

Mixing Effects in Norway Spruce—European Beech Stands Are Modulated by Site Quality, Stand Age and Moisture Availability

Forest Site Classification in the Southern Andean Region of Ecuador: A Case Study of Pine Plantations to Collect a Base of Soil Attributes

Developing an Index for Forest Productivity Mapping - A Case Study for Maritime Pine Production Regulation in Portugal

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