Recruitment models for Norway spruce, Scots pine, birch and other broadleaves in young growth forests in Norway

Abstract. Models for predicting diameter increment in multi-storey spruce stands following mountain forest selective cutting (MFS) were developed. They were based on increment cores, tree ring analyses and stump registrations. The presented models rely upon time series data from 1600 trees in thirty-one Norway spruce stands in south-eastern and central parts of Norway. The selective cuttings were heavy; on average two thirds of the standing volume were cut. The increment following the interventions was highly variable, resulting in large random variability in the models with R 2 varying between 0.18-0.31 for individual tree diameter growth and 0.40-0.50 for mean tree stand diameter growth. Dummy variables referring to three first 5-year periods after cutting were found to increase the precision and significantly reduce the random error. Selected models were validated using a test material from central Norway and also compared with the mostly applied Norwegian diameter increment models. Despite a large random variation in all models, the model performances appeared logical and the general fit to the data was acceptable. Based on tests, two diameter increment models are recommended for future yield prognoses in MFS. The models should also be of interest for wider use in other parts of the Nordic and Baltic boreal zone.

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“…Fitje & Vestjordet, 1977;Bollandsås, 2007), recruitment (e.g. Lexerød & Eid, 2005) and mortality (e.g. Eid & Tuhus, 2001;Eid & Øyen, 2003).…”

Section: Discussionmentioning

confidence: 99%

“…Andreassen & Tomter, 2003), ingrowth of small trees (e.g. Lexerød & Eid, 2005) and natural mortality (e.g. Eid & Tuhus, 2001;Eid & Øyen, 2003).…”

Section: Introductionmentioning

confidence: 99%

Predicting individual tree and stand diameter increment responses of Norway spruce (Picea abies (L.) Karst.) after mountain forest selective cutting

Øyen¹,

Nilsen

Bøhler³

et al. 2011

Forestry Studies

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“…Ingrowth can be quantified as the number, basal area or volume of trees or seedlings that reach or exceed a specific measurement threshold over a certain period of time (Beers 1962;Lexerød and Eid 2005;Bravo et al 2008). It is the link between the regeneration of a tree species and the creation of a mature stand.…”

Section: Introductionmentioning

confidence: 99%

“…The establishment, growth and survival of regeneration are largely dependent on stand and site conditions, and ingrowth is the final result of these processes. For complex and/or heterogeneous stand structures or long-term predictions, ingrowth must be taken into consideration in growth simulations because of the high probability of ingrowth as a result of different regeneration processes (Lexerød and Eid 2005;Adame et al 2010). Together with other stand characteristics, ingrowth is an essential component of long-term management and yield forecasting of forest stands (Moser 1972;Shifley et al 1993;Vanclay 1994;Klopcic et al 2012).…”

Section: Introductionmentioning

confidence: 99%

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Two-stage ingrowth models for four major tree species in Alberta

Yang

Huang

2015

Eur J Forest Res

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A two-stage modelling approach was used for developing ingrowth models for four major tree species in Alberta: aspen, lodgepole pine, black spruce and white spruce. The probability of ingrowth presence was modelled first, followed by the modelling of annual amount of ingrowth conditional on ingrowth being present. To handle variable measurement intervals and plot sizes typical of repeatedly measured forestry data, two generalized logistic models were evaluated at the first stage: a traditional model with measurement interval length and plot size factor incorporated as an exponent of a standard logistic function and an alternative model with measurement interval length and plot size factor incorporated as a denominator. Two criteria were evaluated for defining optimal threshold values for plot classification: criterion 1 to maximize the summation of sensitivity and specificity and criterion 2 to maximize the overall rate of correct plot classification. It was found that criterion 1 was superior to criterion 2 for providing better plot classifications. The two ingrowth probability models behaved similarly based on model fitting and model validation results. Annual amount of ingrowth was modelled at the second stage by exponential functions.

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Ingrowth model for pyrenean oak stands in north-western Spain using continuous forest inventory data

Adame¹,

Rı́o²,

Cañellas³

2010

Eur J Forest Res

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In this paper, a two stage ingrowth model is presented for predicting periodic, 10 years ingrowth for pyrenean oak (Quercus pyrenaica Willd.) grown in medium to fully stocked coppice stands in north-western Spain. Data from the Spanish National Forest Inventory was used to develop the model, extracting the information from two inventories taken in 222 permanent plots. The first stage of the model predicts the probability of ingrowth occurrence, and in the second stage, the number of recruits is predicted using a conditional model. Both models were biologically realistic and presented logical behaviour. The ingrowth occurrence probability model was dependent on quadratic mean diameter and average height. The recruitment quantification model included stand density and average diameter as explanatory variables. Although the occurrence probability of ingrowth was predicted correctly in 71.7% of cases, the predictions of the number of recruitment are poorer, yielding a coefficient of determination of 0.358. The evaluation criteria included qualitative and quantitative examinations and a testing with independent data from another region. The proposed ingrowth model is the first to be developed for mediterranean oak species in Spain and is an essential feature in any stand growth system.

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Recruitment models for Norway spruce, Scots pine, birch and other broadleaves in young growth forests in Norway

Cited by 28 publications

References 28 publications

Predicting individual tree and stand diameter increment responses of Norway spruce (Picea abies (L.) Karst.) after mountain forest selective cutting

Predicting individual tree and stand diameter increment responses of Norway spruce (Picea abies (L.) Karst.) after mountain forest selective cutting

Two-stage ingrowth models for four major tree species in Alberta

Ingrowth model for pyrenean oak stands in north-western Spain using continuous forest inventory data

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