Individual-tree growth and mortality models for Scots pine (Pinus sylvestris L.) in north-east Spain
Summary (3 min read)
1. INTRODUCTION
- It is very important to Spanish forestry because of its economic, ecological and social roles.
- In the case of Spain, these predictions have been traditionally taken from yield tables -tabular records showing the expected volume of wood per hectare by combinations of measurable characteristics of the forest stand (age, site quality and stand density).
- In view of the importance of P. sylvestris in Spain, there is a need for a reliable system of growth and yield predictions that, with appropriate economic parameters and ecological models, would support decision making in the management of Scots pine forests.
- Distance-dependent tree-level models, on the other hand, include a competition measure.
2.1. Data
- Agrarias (INIA) to represent most Scots pine sites in north-east Spain.
- The site index for each site was determined using the site index model of Palahí et al. [19] .
- The plots were measured at 5-year-intervals, except for the last measurement where the interval varied from 10 to 16 years.
- Dead trees were recorded at each measurement.
2.2. Diameter increment
- A diameter growth model was prepared using tree-level (diameter and basal area of larger trees) and stand-level (site, basal area and age) characteristics and their transformations as predictors.
- The last growth observation (10 to 16 years growth) was converted into five-year growth by dividing the diameter increment by the time interval between the two measurements and multiplying the result by 5.
- Therefore, it was not possible to model the logarithmic transformation of the predicted variable.
- All predictors had to be significant at the 0.05 level without any systematic errors in the residuals.
- The linear models were estimated using the maximum likelihood procedure of the computer software PROC MIXED [27] .
2.3. Height model
- Since the height sample trees in each measurement were different, the observations in the estimation data (table I ) did not allow for the estimation of a height growth model.
- For this purpose, two candidate models were evaluated; a non-linear height model used by e.g., Hynynen [12] and Mabvurira and Miina [15] and a linear height model proposed by Eerikäinen [7] .
- Both model types were estimated with and without random parameters, which can take into account the random between-plot and between-measurement factors.
- The loss function was defined as the sum of squared residuals (observed minus predicted values).
- This model enables the estimation of tree heights when only stand age, tree diameters and stand dominant height are measured (as is the normal case in forest inventory).
2.4. Mortality
- To account for mortality, two types of models -a model of the self-thinning limit and a model for the probability of a tree to survive the coming growth period -were developed.
- The self-thinning model was developed from data obtained from 10 plots (table I ).
- Individual tree survival models predict the probability of survival for each tree involved in the growth projection [5] .
- Monserud [16] demonstrated that growth was an important explanatory variable in mortality determination.
2.5.1. Fitting statistics
- The models were evaluated quantitatively by examining the magnitude and distribution of residuals for all possible combinations of variables.
- The aim was to detect any obvious dependencies or patterns that indicate systematic discrepancies.
- To determine the accuracy of model predictions, bias and precision of the models were tested [8, 19, 30, 33] .
- Absolute and relative biases and root mean square error (RMSE) were calculated as follows: (6) (7) (8) (9) where n is the number of observations; and y i and are observed and predicted values, respectively.
2.5.2. Simulations
- In addition, the models were further evaluated by graphical comparisons between measured and simulated stand development.
- Multiply the frequency of each tree (number of trees per hectare that a tree represents) by the 5-year survival probability.
- Calculate stand dominant height from the site index and incremented stand age using the Hossfeld equation of Palahí et al. [19] , and calculate the dominant diameter from incremented tree diameters.
- In addition all growth intervals of all plots were simulated and the simulated 5-year change in stand characteristics was compared to the measured change.
3.1. Diameter growth and height models
- All parameter estimates of the diameter growth model are logical and significant at the 0.001 level (table II ).
- The absolute and relative biases in the diameter growth model were 0.0124 cm per 5-year-period and 1.2%, respectively (table III ).
- The residuals of the fixed model part are correlated within each.
- Furthermore, when the age of the stand increases the height differences between dominant trees and the other trees in the stand are less pronounced.
3.2. Mortality models
- The self-thinning model describes the relationship between the square mean diameter and number of trees per hectare in a stand (Eq. ( 3)).
- According to the model, the better the site the higher the stocking level of the stand with differences between sites being more pronounced in young stands .
- The relative bias and RMSE value for the self-thinning model were 0.23 and 17%, respectively.
- The greater is the past diameter growth (average growth or past 5 years growth), the greater is the probability of a tree surviving.
- With continuous variables, the probability ratio describes the change of probability per one unit change of covariate.
3.3. Simulation results
- Figure 4 shows examples of actual and simulated stand development for four stands with site indices 26, 19, 14 and 15 m at 100 years, respectively.
- The four selected plots cover the range of variation in site index and stand age among the plots used to develop the growth and mortality models.
- Figure 4 shows that the model set developed in this study enables a very accurate long-term simulation of stand development for the four selected stands.
- Figure 5 shows the measured and predicted changes of different stand variables for all plots in all the measurements.
- This is mainly due to the fact that the diameter growth model explains only part of the variation in diameter increment.
4. DISCUSSION
- In fitting the models, both measured dominant height and site index were used as predictors.
- To predict mortality below the self-thinning limit, the logistic survival functions may be used.
- Height growth models could not be developed because there were not enough sample tree heights per plot measured more than once.
- Simulation results were presented for four stands, which represent the range in site index (from 14 to 26 m at 100 years) of the data set.
- This study is the first, known by the authors, on individualtree growth models for Scots pine in Spain.
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Citations
61 citations
Cites background from "Individual-tree growth and mortalit..."
...In order to address this problem, several researchers have recently developed growth and yield models based on an individual-tree approach (e.g. Palahí, 2002 ; Palahí and Grau Corbí, 2003 ; Palahí et al. , 2003 ; Trasobares, 2003 ; Trasobares and Pukkala, 2004 ; Trasobares et al. , 2004a , b )....
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59 citations
Cites background from "Individual-tree growth and mortalit..."
..., 2006), the application of alternative management regimes, which increase the small-scale spatial variation, would make more detailed spatio–temporal single-tree analyses desirable (Palahı́ et al., 2003)....
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...…structure justifies the use of stand-level growth models in this case (Dieguez-Aranda et al., 2006), the application of alternative management regimes, which increase the small-scale spatial variation, would make more detailed spatio–temporal single-tree analyses desirable (Palahı́ et al., 2003)....
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59 citations
55 citations
46 citations
Cites background from "Individual-tree growth and mortalit..."
...These variables are commonly included as predictors in single tree diameter growth models (West, 1981; Wykoff, 1990; Palahi et al., 2003, Soares and Tomé, 2003)....
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References
981 citations
"Individual-tree growth and mortalit..." refers methods in this paper
...To determine the accuracy of model predictions, bias and precision of the models were tested [8, 19, 30, 33]....
[...]
970 citations
871 citations
751 citations
"Individual-tree growth and mortalit..." refers methods in this paper
...According to Reineke’s expression [23] and the –3/2 power rule of self-thinning [34], a loglog plot of the average tree size and stem density will give a straight self-thinning line of a constant slope....
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