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Application of the forsol model to the spruce site at Solling, Germany
E(OLOGI(IIL mODELLInG ELSEVIER
Ecological Modelling 83 (1995) 197-205
Application of the FORSOL model to the spruce site at Soiling, Germany Jelle G. Van Minnen *, Rob Meijers, Leon C. Braat National Institute of Public Health and Environmental Protection, P.O. Box 1, 3729 BA Bilthoven, Netherlands
Accepted 7 February 1995
Abstract
In this paper we present and discuss the results of an application of the regional forest simulation model FORSOL for the Norway spruce site in Soiling (Germany). The objective of the application to the Solling site was stated as assessment of the performance of FORSOL at the site level. The application of FORSOL has taken place in the context of a comparative study of forest models. The study indicates that FORSOL, originally developed as a model for production of annually and regionally averaged simulation data, is well capable to simulate average values of relevant site behaviour indicators. It is however not equipped to simulate year to year fluctuations in site-specific forest behaviour. This conclusion is based on the fair agreement between simulated and observed data with respect to DBH, stem biomass, the nutrient contents for most nutrients and the nutrient fluxes and the results of the evaluation of the impact of growth reduction factors. To evaluate the relative impact of the different stress factors, additional simulation runs were done with FORSOL for the period 1976-1989. The simulations indicate that the shortage of base cations causes the largest growth reduction. The additional impact of soil acidification is relatively small. The negative effects of sulphur dioxide and ozone on potential growth are even smaller. The impact of drought stress varied over the years. The evaluation of two deposition scenarios indicated that a strong reduction of especially the N deposition may reduce the growth and biomass of forests after some years, when the nitrogen available in the soil is incorporated in the trees. However, base cation concentrations in the leaf compartment recover. Keywords: Acidification; Drought; Forest ecosystems; FORSOL; Stress
1. I n t r o d u c t i o n
In this p a p e r we p r e s e n t a n d discuss t h e results o f an a p p l i c a t i o n o f the r e g i o n a l forest simu-
* Corresponding author. Present address: International Institute for Applied System Analysis, A-2361 Laxenburg, Austria. Fax: (+43) 2236 71313; email: [email protected]
l a t i o n m o d e l FORSOL (version 1.0) for t h e N o r w a y s p r u c e (Picea abies) site in Soiling ( G e r m a n y ) . FORSOL has b e e n d e v e l o p e d as p a r t o f a r a p i d r e s p o n s e i n t e g r a t e d e n v i r o n m e n t a l m o d e l (EXPECr; see B r a a t et al., 1991; B a k e m a et al., 1994). T h e role within the EXPECt m o d e l is to s i m u l a t e t h e effects o f m u l t i p l e e n v i r o n m e n t a l stress factors o n t r e e growth a n d forest soils.
0304-3800/95/$09.50 © 1995 Elsevier Science B.V. All rights reserved SSDI 0304-3800(95)00098-4
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J. G. Van Minnen et al. / Ecological Modelling 83 (1995) 197-205
The objective of the application to the Soiling site was stated as assessment of the performance of FORSOL at the site level. The application of FORSOL has taken place in the context of a comparative study of forest models (see Van Heerden and Yanai, 1995). For this purpose all participating models were required to use a particular data set for the Soiling site (Bredemeier et al., 1995). The application regards the 1976-1989 period. For this period an historical simulation has been executed and compared with field data to assess performance and to analyze the relative contribution of a number of environmental stress factors to net growth reduction at the Soiling site. In addition, the impacts of two environmental policy scenarios for the 1970-2070 period have been evaluated. In the last few decades, a number of forest ecosystem models have been developed which address the impacts of environmental stress factors on forest development. These factors include soil acidification (e.g. Kercher and Axelbrod, 1984; Mohren, 1987; Berdowski et al., 1991), nutrient deficiency (e.g. ,&gren and Bosatta, 1988), lack of soil moisture (e.g. Pastor and Post, 1985; Hunt, 1990) and climatic change (e.g. McGuire et al., 1992; Klein Goldewijk et al., 1994). None of the models considered fits the requirements of the EXPECTmodel, which include a maximum run time of a few minutes for geographically explicit, 50-year simulations and handling multiple stress factors simultaneously. The trade off made explicitly in the EXPECT project is that output data are annual, regional averages rather than sitespecific values. A number of patch dynamics and succession models (e.g. Botkin et al., 1972; Leemans, 1989) can produce results in a short time. These models, however, deal with the relevant stress factors in too simplified a fashion. To satisfy the EXPECT model requirements, FORSOLhas been developed. The development philosophy has been to integrate the useful parts of the available models. 2. Structure of the model
In this section an overview of the structure of FORSOL is given. A full mathematical and quanti-
tative description of FORSOL 1.0 is available in Van Minnen and Meijers (1994). FORSOL 1.0 simulates the annual growth of homogeneous forest stands, annual nutrient and water fluxes in these stands and the soil chemistry of a multi-layer soil below, with regionally averaged stress input values. The model combines concepts used in statistical yield tables with principles of process simulation models. The driving force in FORSOL is an age-dependent annual reference-increment of the diameter at breast height (DBH). With this increment the potential growth of all tree compartments (leaves, wood and fine roots) is subsequently computed. We define reference-increment as the increment under optimum conditions, assuming constant climatic conditions. The growth function is based on the function used by Leemans (1989,1991) and subsequently parameterized with data from LaBastide and Faber (1972) and Mohren et al. (1991). The model may then be used to evaluate the combined impacts of the following environmental stress factors: acidification, drought and nutrient shortage. Acidification includes direct influence of atmospheric sulphur dioxide (SO 2) and ozone (O 3) and indirect effects through soil acidification which influences the availability of nutrients. Finally, maintenance respiration fluxes are calculated to evaluate their contribution to the reduction of the potential growth. The maintenance respiration is computed with a method described by Mohren (1987), who relates the respiration flux to the total amount of nutrients in a tree. Fig. 1 presents an overview of the processes represented in FORSOL1.0. Inputs include deposition fluxes of sulphate (SOx), nitrogen oxides (NOy), reduced nitrogen compounds (NHz), calcium (Ca), magnesium (Mg), potassium (K), sodium (Na) and chlorides (Cl), the ambient air concentrations of sulphur dioxide (SOz), ozone (O 3) and ammonia (NH3), and the number of drought days (see below). Within FORSOL three compartments can be distinguished: the tree compartment, the rooted soil compartment and the soil compartment without roots. The tree compartment and the rooted soil compartment interact via throughfall, turnover of leaves, stem and roots and by the root
J.G. Van Minnen et aL / Ecological Modelling 83 (1995) 197-205
uptake of N, Mg, Ca and K. Throughfall is the result of the deposition fluxes, modified in the canopy by leaf uptake and leaf exudation. The turnover of leaves, stem and fine roots is computed in FORSOL at the end of each one year time step as a fraction of the biomass. This fraction is adjusted in case of high stress levels. The turnover of fine roots is simulated with an iterative procedure, because the yearly turnover is larger than the fine root biomass. Root uptake depends on transpiration, an age-specific nutrient uptake factor, and the nutrient availability in the soil solution. It is negatively affected by reduction of fine root biomass, low pH values and a high A1 concentration in the soil solution (Scott Russel, 1977; Berdowski et al., 1991; see also below). The nutrient availability in the rooted soil compartment is determined by throughfall, mineralization, nitrification, denitrification, and weathering. Each of the two soil compartments of FORSOL consists of two soil layers. The equations for the processes in each layer (Fig. 1) have been derived from De Vries et al. (1988). Mineralization, nitrification, denitrification and weathering are the processes in the rooted soil layers that are modelled. Together with the deposition and net root uptake flux they determine the concentration of plant nutrients and other compounds (e.g. AI, H ÷) in the soil solution. Denitrification and
Soil p r o c e s s e s
Tree p r o c e s s e s
rooted layers :min e ~ I-iza-tio-.--: : nitrification : Idenitrification i
j ............ : leaf uptake
weathering leaching
,denitdfication weathering leaching
Stress factors
-~ ] i
~1~
, leaf exudation
-.i-;q-~al~ty---i
through fall
i nuuientavail. ': i drought ',
DBH increment, allocation total growth respiration transpiration root uptake turnover
ELog,_t,_o?~___. ',atmospheric ', ', deposition I : concentr. [ Idrought days I
Fig. 1. A n overview of the processes modelled in FORSOL.
199
Growth reductionfactor (-)
1.0 0.8
0.6 S02
0.4 i
0.2 Q.O
0
f0 20 30 number ol drought days
40
100 concentration (ug.m-3)
200
Uptake reduction factor (-)
1.0 c 0.8 0.6 0.4 0.2 0.0
, 5
.
r 4 pH {-)
, 3
y
d
2 4 6 8 10 AI concentration (molc.m-3)
Fig. 2. Overview of growth reduction factors, implemented in the FORSOL model (note that in (a) and (b) potential growth is affected and in (c) and (d) the root uptake capacity is affected).
weathering are the processes in the soil compartment without roots that are included in the model. For each soil compartment, the model computes concentrations and leaching fluxes based on soil and tree processes and the net water flux, which in turn is determined by net precipitation and evapotranspiration. The A1 weathering flux is based on weathering of primary silicates and on the weathering of gibbsite (Van Minnen and Meijers, 1994). The pH results from the mass balance in each layer. The computed AI concentrations and pH values are averaged over the soil compartments to generate the controlling parameters for the pH and A1 root uptake reduction. Fig. 2 gives an overview of the environmental stress factors which, in the model, influence the potential growth of a forest stand, i.e. drought
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stress, atmospheric S O 2 and 0 3 and nutrient shortage. In addition, a large maintenance respiration flux also reduces potential growth in FORSOL. This reduction factor is computed by comparing the actual respiration flux with the reference flux. Drought stress is simulated with the exogenous variable drought days (Fig. 2a) which is defined as the number of days on which the soil water content is below wilting point (Pastor and Post, 1985). The multiplicative function representing the relationship between atmospheric O 3 and SO 2 and the potential growth is taken from Berdowski et al. (1991) who follow Jeffree (1981) and Linzon et al. (1984). These authors suggest that both compounds affect tree growth in a more or less similar way. The third variable in FORSOL which may act as a stress factor which affects the potential growth function in FORSOL is the net availability in the trees of N, Mg, C and K. The net availability of these nutrients is calculated as the result of root uptake (affected by the fine root biomass, the p H value and Al concentration in the soil solution, see Fig. 2c + d), leaf uptake and leaf exudation. The net nutrient availability is compared with the required amount of nutrients, a value based on total potential growth ( = sum of the potential growth of leaves, stem and fine roots) and a preset nutrient-and compartmentspecific minimum content. If a shortage of one or several nutrients occurs, the nutrient in greatest demand determines the actual growth reduction factor. The reduction factor representing nutrient shortage is computed after the potential growth has been modified for drought stress, SO z and O 3, and respiration. The multiplicative relationship between potential growth and the separate reduction factors used in FORSOL is based on Berdowski et al. (1991).
3. Derivation of input data for the Soiling study Initialization of FORSOL variables and quantification of parameters for the application of the model to the Soiling spruce site was started with the data set of Bredemeier et al. (1995). The atmospheric deposition data as well as the SO2,
and N H 3 concentration data have been taken directly from this set. The compound-specific filtering factors for dry deposition have been set to 1, because the data in Bredemeier et al. (1995) represent deposition as measured below the spruce canopy. Tree age (96 year), the actual D B H (33.4 cm) and the biomass of the leaf, fine roots and wood compartment (18100, 3500 and 80000 kg ha -1 respectively) for the initial year 1976 have been taken directly from this data set. Allocation fractions of carbon and nutrients in FORSOL have been calibrated to the Bredemeier et al. (1995) growth data and nutrient contents, while the turnover fractions of the leaves, stem and fine roots have been derived from their biomass data and turnover fluxes. Leaf uptake and exudation fractions have been calculated from the deposition and throughfall fluxes. Nutrient-specific selectivity factors for root uptake have been calibrated to the same growth data and nutrient contents, using calculated leaf exudation, leaf uptake and reallocation fluxes. The initial nutrient contents in the tree have been set for each nutrient to the mean value of the observed data over the period 1968-1975. Thinning fractions have been set to Soiling site tree densities to obtain the correct number of trees per hectare. Thinning has not occurred at the Soiling site during the calibration period, but a reduction of the number of trees caused by storms has thus been simulated with FORSOL. We have also derived most of the required soil data from the Bredemeier et al. (1995) data set, e.g. the initial litter biomass and the initial concentrations of all compounds in the soil layers. The initial pH values in both rooted soil layers have been set to 3.8, equal to the mean of the measured values. Furthermore we have calibrated the acid neutralization capacity (ANC) in the rooted soil layers (respectively 0.1 and 0.2 molc kg-1), which is necessary for the simulation of H + and Al concentrations. We also had to set the values of the compound-specific silicate weathering rates to the observed values, because FORSOL is not able to simulate such high weathering fluxes. The values have been set to 125, 75, 25 and 25 tool e yr -1 for magnesium, potassium, 0 3
J.G. Van Minnen et al. / Ecological Modelling 83 (1995) 197-205
calcium and sodium rates respectively (Bredemeier et al., 1995). The remaining data have been derived from literature and other models. The initial reference DBH (52.6 cm) has been taken from yield tables (LaBastide and Faber, 1972). We have calibrated the number of drought days for each year. FORSOL requires the number of drought days as a single numerical value per year. The calibration of this value is based on (1) an annual ratio based on daily actual and potential evapotranspiration data, and computed by Groenenberg et al. (1995), (2) the relationship between this annual ratio and annual potential growth (see McGuire et al., 1992; Klein Goldewijk et al., 1994) and (3) the relationship between growth reduction and the number of drought days (Pastor and Post, 1985). The maximum number of drought days was derived from Pastor and Post (1985) and set to 30 days per year. For those parameters for which spruce data were not available, Douglas fir (Pseudotsuga mensiezii) data have been used. This approach has also been followed in other studies which simulate forest stress at the Solling site (e.g. Van Heerden et al., 1995).
4. Statistical analysis To compare the simulation results with measured data, three statistical indicators were selected from a set described by Janssen and Heuberger (1995): index of agreement (IoA), normalized root mean square error (NRMSE) and normalized mean absolute error (NMAE). These three performance measures have been selected because they allow comparison of simulation results with a relatively small set of field data. Furthermore, the normalized values (instead of RMSE and MAIE) were selected, because they show the relative error instead of the absolute error. IoA expresses the agreement between observations and predictions in a straightforward manner. It varies between 0 (no agreement) and 1 (perfect agreement). N R M S E and N M A E express the deviation from a 1:1 relationship between model predictions and observations. These
201
two indicators become 0 in case of a perfect agreement. The major difference between the two indicators is that N M A E is less sensitive to outliers, because it compensates for positive and negative discrepancies in the same way.
5. Results and discussion Fig. 3 shows the simulated and measured DBH values, stem volumes (both in Fig. 3a) and leaf nutrient contents (Fig. 3c), as well as the simulated leaf and fine root biomass (Fig. 3b) for the period 1978-1989. The measured and simulated DBH start in 1976 with 33.1 and 33.7 cm, respectively, and increase both to 37.1 cm in 1989, which produces a good statistical agreement (see Table 1). Stem biomass field data show an increase from 558 to 651 m 3 ha -l, while VORSOL simulates an increase from 561 to 630 m 3 h a - t , which leads to a good statistical agreement (see Table 1). The discrepancy at the end of the simulation period is readily explained by: (1) the VORSOL thinning fraction, meant for homogenous forest stands and now used in the application to simulate storm damage at the Soiling site, overestimates the actual biomass reduction, as the damage is for the greater part constituted by small trees; (2) the growth function in VORSOL has been parameterized for Dutch forests where old stands are rare. Consequently VORSOL u n d e r e s t i m a t e s stem growth at the relatively old Soiling site. Because field data for leaf biomass are not available beyond 1977, simulated leaf biomass data (fluctuating between 18-19 ton ha -1 ) have been compared to the statistical mean value for field data for the period 1967-1977 (17.8 ton ha-J). In this particular comparison, the IoA produces a relatively low score (see Table 1). This is the consequence of the raising to a square of the relatively large accumulated difference between observed and simulated data. With regard to nutrient contents in the leaf biomass, the simulation data have been compared with the lines between the only available observed data sets (1976 and 1983). Most simulated nutrient contents follow these lines closely. The
J.G. Van Minnen et al. // Ecological Modelling 83 (1995) 197-205
202
simulated N contents in leaves (Fig. 3c) remain at 11.1 g kg -1 dry matter and the measured contents vary between 11 and 11.7 g kg -1. The simulated N contents in litter (not shown in the figure) remain at 20 g kg-1 dry matter and the measured contents vary between 18.5 and 21.1 g kg -~. The simulated Mg, K and Ca contents in the leaf compartment show a decreasing trend
Table 1 Statistical comparison between simulation results and observed data (note that IoA becomes 1 in case of a prefect agreement, while N R M S E and N M A E are then 0)
NRMSE IoA NMAE
DBH
Leaf biomass a
Stem biomass
0.012 0.96 0.009
0.024 0.46 0.02
0.023 0.96 0.02
a Because field data were not available after 1977, the average value of the period 1967-1977 was used in the comparison. - ----
(<-) (->)
• ¢
(<-) D B H (->) S t e r n m a s s
800
40
700 35
-r rn t3
11~ I~ f
11/
600
~f/
30 1975
- -
11~i I
1980
leaf
- - - fine root (<5ram)
1985
500 1990
1985
1990
'
E
]
20000
~-15000
~
'10000
5000.
0 1975
- - -
1980.
•
K
12
E (D "E
oo
-w.
~---7-7--7---7-~'--7"--, 0 1980 1975
. . . . . . .
1985
1990
years
Fig. 3. Comparison between simulated and m e a s u r e d biomasses and nutrient contents in Solling for the period 1976 to 1989. (Lines represent model results and markers are observations).
(Fig. 3c). These trends are in agreement with published data about severe shortage of base cations in many forests in the northern hemisphere (e.g. Kimmins et al., 1985; Van den Burg, 1986; Tomlinsson, 1991). The simulated Ca content decreases from 4.9 in 1976 to 3.1 g kg -1 in 1983, while field data are 5.0 g kg-1 (1976) and 3.4 g kg -1 (1983). The simulated Mg content decreases in the same period from 0.36 to 0.24 g kg- 1 with field data of 0.4 g kg- 1 (1976) and 0.27 g kg -1 (1983). For the K content in the leaf biomass FORSOL simulates a decrease from 5.1 g kg -~ in 1976 to 4.1 g kg -1 in 1983 and 4.0 g kg -~ in 1989. The observed content is about the same in 1976 as in 1983 (5.1 g kg-1). The leaf exudation flux of K presented by Bredemeier et al. (1995) is relatively large. The field data about nutrient content suggest that this loss was compensated for. Such a compensation is not realized with FORSOL. The exudation flux is adequately simulated by FORSOL, but re-uptake by the roots of exudated nutrients is limited. To evaluate the relative impact of the different stress factors, seven additional simulation runs were done with FORSOL for the period 1976-1989 (Table 2). The results of the simulation run with the calibrated model, with all stress factors active, have been used as a reference set (run I). The results of all runs have been averaged over the 1976-1989 period. The simulations indicate that the shortage of base cations causes the largest growth reduction (Table 2: run I-IV). If nutrient shortage is eliminated, growth rates increase by 30-40% (Table 2: run V-VIII). Additional availability of nutrients strongly raises the leaf content of the base cations and increases the respiration
J.G. Van Minnen et al. / Ecological Modelling 83 (1995) 197-205 Table 2 Evaluation of the effects of growth reduction factors on actual stem volume, stem growth, leaf biomass, respiration flux and N and Mg contents in the leaf biomass, averaged over the period 1976-1989 (the results of the reference run are set to
6O
40
100%) Volume Stemgrowth Leaf mass Respiration c{N/lf c{Mg}lf
203
20
I
II
III
IV
V
100 100 100 100 100 100
101 105 103 100 97 100
100 100 100 100 100 100
101 105 103 100 97 100
104 133 142 131 103 290
VI 105 138 145 131 101 279
VII
VIII
105 140 146 131 100 275
105 145 150 131 98 266
30000 Leaf (linE}
......
25000
Root (IrnE)
Root (BAU)
20000
......-\ . . .,..,.~..........,..,...... ......................... ..................
15000
I: Reference = all stress factors active; II: Drought + nutrient stress; III: Nutrient and acidification stress; IV: Nutrient stress only; V: Drought and acidification stress; VI: Drought stress only; VII: Acidification stress only; VIII: No stress factors active.
. . . .
Leaf (BAU)
o
10000
5000
1000
. . . . ~:~ I% ] flux. The nutrient shortage can only be partly explained by soil acidification. If soil acidification stress is set to background conditions and ambient air concentrations of SO 2 and 0 3 are eliminated (Table 2: run II, IV, VI and VIII), growth increases only slightly. Furthermore the nitrogen content decreases, because the availability of N remains constant and is used in more biomass. In the application of FORSOL to the Solling site, soil acidification affects tree growth only when nutrients in the soil are scarce, because the uptake capacity of a tree is affected by low pH and high AI concentration. In the reference run the root uptake of most nutrients is reduced with a maximum of 35%. If H + and A1 concentrations are set to background values, the root uptake reductions are 25-30%. The additional impact of soil acidification is thus relatively small (5% growth reduction). The negative effects of SO 2 and 0 3 on potential growth are even smaller. In the application of FORSOL for Solling, the years 1976, 1982, 1988 and 1989 are years with a relatively large drought stress (10-12%). The drought impact averaged over the period 19761989 was negligible (Table 2 run 1II, IV, VII and VIII), especially in a period without nutrient limitation. In the model, drought is directly linked to potential growth and does not affect the root uptake of nutrients. Therefore, total drought ira-
// ~J
20 N (linE) Mg (linE)
.... ....
N (BAU) Mg (BAU)
16 12
f
•
8 4
01970
. ..--
1990
2010
2030
2050
2070
years
Fig. 4. Simulated biomasses and nutrient status in the Business as Usual (BAU) and an Improved Environment (ImE) scenarios.
pact may be underestimated in the current application. voRSOL has further been run for the period 1970-2070 to evaluate the effects of two environmental policy scenarios: Business As Usual (BAU) and Improved Environment (ImE). Both scenarios are described in Bredemeier et al. (1995). The frequency of drought was set to that of the period 1976-1989. Fig. 4 presents some of the results. In the BAU scenario, FORSOL shows no nutrient shortage during the first ten years of the simula-
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tion. The nutrient pool in the soil, as modelled, turns out to be sufficient for this period. Therefore DBH and leaf biomasses increase more or less normally (Fig. 4a + b). The contents of most nutrients increase slightly in this period (Fig. 4d). After 1983 the nutrient stress increases, especially because of a Ca shortage. Low pH values (3.4) in the rooted soil layers cause large uptake reductions (> 30%), and high leaf exudation rates. Growth reduction due to drought fluctuates through the years (0-15%) and the reduction caused by SO z and 0 3 (10%) remains more or less constant. The result is that with a deposition as in the BAU scenario forest growth is base cation limited. Therefore, the nutrient contents in leaves, wood and fine roots decrease down to their specific minimum. This results in a slight decrease of leaf biomass (Fig. 4b) and a limited impact on stem growth (Fig. 4a + c). In the ImE scenario, forest growth becomes strongly N limited. Drought stress is about similar to that in the BAU scenario, while growth reduction by SO 2 and 0 3 becomes negligible. An increase in pH and a decrease in the A1 concentrations alleviate the reduction of root uptake. Furthermore, N in the soil decreases due to decreased deposition and a smaller mineralization flux, causing N limitation. After 2000 the growth reduction reaches 70%, causing decreases in leaf biomass (Fig. 4b) and DBH increment (Fig. 4a). Base cation concentrations in the leaf compartment recover, caused by increased root uptake (because of less soil acidification) and decreased growth. These larger nutrient contents may cause a reduced sensitivity to secondary damage by e.g. insects (as suggested by e.g. Alstad et al., 1982). The nitrogen content in leaves reaches its minimum content of 6 g kg-l as early as the year 2000. Compared to the BAU scenario, the ImE scenario produces considerably less biomass and smaller DBH.
6. Conclusions The application of the FORSOL model for the Soiling spruce site indicates that FORSOL, originally developed as a model for production of annually and regionally averaged simulation data,
is well capable to simulate average values of relevant site behaviour indicators. This conclusion is based on (1) the fair agreement between simulated and observed data with respect to DBH, stem biomass, the nutrient contents for most nutrients and the nutrient fluxes; (2) the results of the evaluation of the impact of growth reduction factors, which is in line, with respect to the type of stress, with results from other forest models (evaluated by Van Heerden and Yana'i, 1995). The importance of nutrient stress as simulated by FORSOL is furthermore in agreement with findings in a number of forest studies (e.g. Tomlinsson, 1991). (3) the statistical deviation with respect to specific leaf biomass data has been explained and therefore does not diminish the general applicability of FORSOL. However, a more detailed analysis of the model results and the large number of assumptions that had to be made for this application of the FORSOL model, suggest that year-to-year variation in sitespecific data can be simulated more adequately with a site model. Because FORSOL has been developed to be a regional forest model with an annual time step, a number of physiological processes have not been included. To solve this problem for dynamic site-specific applications, the model must be extended with at least a water balance model. The simulation time step of FORSOL should then be reduced to, e.g. 1 day, which would increase the computation time to response times which would not fit the EXPECt requirements. The evaluation of the two deposition scenarios indicated that a strong reduction of especially the N deposition may reduce the growth and biomass of forests after some years, when the nitrogen available in the soil is incorporated in the trees. The combination of improved soil conditions and decreased growth, however, leads to a greater base cations pool within the trees.
Acknowledgements We would like to thank Aldrik Bakema and Kees van Heerden for their critical reviews of
J.G. Van Minnen et al. /Ecological Modelling 83 (1995) 197-205
earlier drafts of the paper, and Caroline van der Salm for the transpiration data. Finally we thank all workshop participants for their contributions to the study.
References ,~gren, G.I. and Bosatta, E., 1988. Nitrogen saturation in terrestrial ecosystems. Environ. Pollut., 54: 185-197. Alstad, D.N., Edmunds Jr., G.F. and Weinstein, L.H., 1982. Effects of air pollutants on insect populations. Ann. Rev. Entomol., 27: 369-384. Bakema, A.H., De Boer, K.F., Braat, L.C., Kok, R.M., Meijers, R. and Van Minnen, J.G., 1994. EXPECT: A concise simulation system for environmental policy analysis. Ecol. Model., 75/76: 553-561. Berdowski, J.J.M., Van Heerden, C., Van Grinsven, J.J.M., Van Minnen, J.G. and De Vries, W., 1991. SOILVEG: A model to evaluate the effects of acid atmospheric deposition on soil and forest. Vol. 1: Model principles and application procedures. Report no. 114.1-02, RIVM, Bilthoven, the Netherlands. Botkin, D.B., Janak, J.F. and Wallis, J.R., 1972. Some ecological consequences of a computer model of forest growth. J. Ecol., 60: 849-872. Braat, L.C., Bakema, A.H., De Boer, K.F., Kok, R.M., Meijers, R. and Van Minnen, J.G. (Editors), 1991. EXPECT: Outline of an integrated model for environmental scenario analysis and impact assessment. RIVM rapport 259102001, Bilthoven, the Netherlands, 55 pp. Bredemeier, M., Tiktak, A. and Van Heerden, C., 1995. The Soiling spruce stand. Background information on the data set. Ecol. Model., 83: 7-15. De Vries, W., Waltmans, M.J.P.H., Van Versendaal, R. and Van Grinsven, J.J.M., 1988. Structure and preliminary process documentation of a soil acidification model, useful for a regional application. Winand Staring Centre, report. no 2014, Wageningen, the Netherlands, 132 pp. (in Dutch). Groenenberg, J.E., Kros, J., Van der Salm, C. and De Vries, W., 1995. Application of the model NUCSAM to the Soiling spruce site. Ecol. Model., 83: 97-107. Hunt, B.G., 1990. The simulation and prediction of drought. Vegetatio, 91: 89-103. Janssen, P.H.M. and Heuberger, P.S.C., 1995. Calibration of process-oriented models. Ecol. Model., 83: 55-66. Jeffree, C., 1981. Agricultural crop damage. In: The Costs and Benefits of Sulphur Dioxide Control. A Methodological Study. OECD, Paris, pp. 78-88. Kercher, J.R. and Axelbrod, M.C., 1984. Analysis of SilvaL. A model for forecasting the effects of SO z pollution and fire on western coniferous forests. Ecol. Model., 23: 165-184.
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Kimmins, J.P., Binkey, D., Chahatarpaul, L. and De Catanzaro, J., 1985. Biogeochemistry of temperate forest ecosystems: Literature on inventories and dynamics of biomass and nutrients. Canadian Forest Service, Information report. Klein Goldewijk, K., Van Minnen, J.G., Kreileman, G.J.J., Vloedbeld, M. and Leemans, R., 1994. Simulation the carbon flux between the terrestrial environment and the atmosphere. Water Air Soil Pollut., 76: 199-230. LaBastide, J.G.A. and Faber, P.J., 1972. Revised yield tables for six tree species in the Netherlands. De Dorschkamp, report no. 11-1, Wageningen, the Netherlands. Leemans, R., 1989. Description and simulation of stand structure and dynamics in some Swedish forest. Ph.D. thesis, Uppsala University, Sweden. Leemans, R., 1991. Canopy gaps and establishment patterns of spruce (Picea abies) in two old-growth coniferous forest in Central-Sweden. Vegetatio, 93: 157-165. Linzon, S.M., Pearson, R.G., Donnan, J.A, and Durham, F.M., 1984. Ozone effects on crops in Ontario and related monetary values. Ontario Ministry of the Environment, ARB-13-84-phyto. McGuire, A.D., Melillo, J.M., Joyce, L.A., Kicklighter, D.W., Grace, A.L., Moore III, B. and VSrSsmarty, C.J., 1992. Interaction between carbon and nitrogen dynamics in estimating net primary productivity for potential vegetation in North America. Global Biogeochem. Cycl., 6: 101-124. Mohren, G.M.J., 1987. Simulation of forest growth to Douglas fir stands in the Netherlands. Ph.D. thesis, Agricultural University of Wageningen, the Netherlands. Mohren, G.M.J., Van Hees, A.F.M. and Bartelink, H.H., 1991. Succession models as an aid for forest management in mixed stands in the Netherlands. For. Ecol. Manage., 42: 111-127. Pastor, J. and Post, W.M., 1985. Development of a linked forest productivity-soil process model. Oak Ridge National Laboratory, Oak Ridge, TN, ORN/TM-9519. Scott Russel, R., 1977. Plant root systems: Their function and interaction with soil. McGraw-Hill, Maidenhead. Tomlinsson, G.H., 1991. Nutrient disturbances in forest trees and the nature of forest decline in Quebec and Germany. Water Air Soil Pollut., 54: 61-74. Van den Burg, J., 1986. Verslag van een onderzoek naar de naaldsamenstelling van vier grovedennenopstanden in de boswachterij Kootwijk. RIBL De Dorschkamp, Wageningen, the Netherlands (in Dutch). Van Heerden, C. and Yana'i, R., 1995. Effects of stress on forest growth in models applied to the Soiling spruce site. Ecol. Model., 83: 273-282. Van Heerden, C., Van Grinsven, J.J.M. and Tiktak, A., 1995. Simulation of forest stress for the Soiling spruce site with SOILVEG. Ecol. Model., 83: 185-195. Van Minnen, J.G. and Meijers, R., 1994. FORSOL: The EXPECT forest-soil module. RIVM, Bilthoven, the Netherlands, report no. 259102010, 55 pp.
Ecological Modelling 83 (1995) 197-205
Application of the FORSOL model to the spruce site at Soiling, Germany Jelle G. Van Minnen *, Rob Meijers, Leon C. Braat National Institute of Public Health and Environmental Protection, P.O. Box 1, 3729 BA Bilthoven, Netherlands
Accepted 7 February 1995
Abstract
In this paper we present and discuss the results of an application of the regional forest simulation model FORSOL for the Norway spruce site in Soiling (Germany). The objective of the application to the Solling site was stated as assessment of the performance of FORSOL at the site level. The application of FORSOL has taken place in the context of a comparative study of forest models. The study indicates that FORSOL, originally developed as a model for production of annually and regionally averaged simulation data, is well capable to simulate average values of relevant site behaviour indicators. It is however not equipped to simulate year to year fluctuations in site-specific forest behaviour. This conclusion is based on the fair agreement between simulated and observed data with respect to DBH, stem biomass, the nutrient contents for most nutrients and the nutrient fluxes and the results of the evaluation of the impact of growth reduction factors. To evaluate the relative impact of the different stress factors, additional simulation runs were done with FORSOL for the period 1976-1989. The simulations indicate that the shortage of base cations causes the largest growth reduction. The additional impact of soil acidification is relatively small. The negative effects of sulphur dioxide and ozone on potential growth are even smaller. The impact of drought stress varied over the years. The evaluation of two deposition scenarios indicated that a strong reduction of especially the N deposition may reduce the growth and biomass of forests after some years, when the nitrogen available in the soil is incorporated in the trees. However, base cation concentrations in the leaf compartment recover. Keywords: Acidification; Drought; Forest ecosystems; FORSOL; Stress
1. I n t r o d u c t i o n
In this p a p e r we p r e s e n t a n d discuss t h e results o f an a p p l i c a t i o n o f the r e g i o n a l forest simu-
* Corresponding author. Present address: International Institute for Applied System Analysis, A-2361 Laxenburg, Austria. Fax: (+43) 2236 71313; email: [email protected]
l a t i o n m o d e l FORSOL (version 1.0) for t h e N o r w a y s p r u c e (Picea abies) site in Soiling ( G e r m a n y ) . FORSOL has b e e n d e v e l o p e d as p a r t o f a r a p i d r e s p o n s e i n t e g r a t e d e n v i r o n m e n t a l m o d e l (EXPECr; see B r a a t et al., 1991; B a k e m a et al., 1994). T h e role within the EXPECt m o d e l is to s i m u l a t e t h e effects o f m u l t i p l e e n v i r o n m e n t a l stress factors o n t r e e growth a n d forest soils.
0304-3800/95/$09.50 © 1995 Elsevier Science B.V. All rights reserved SSDI 0304-3800(95)00098-4
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The objective of the application to the Soiling site was stated as assessment of the performance of FORSOL at the site level. The application of FORSOL has taken place in the context of a comparative study of forest models (see Van Heerden and Yanai, 1995). For this purpose all participating models were required to use a particular data set for the Soiling site (Bredemeier et al., 1995). The application regards the 1976-1989 period. For this period an historical simulation has been executed and compared with field data to assess performance and to analyze the relative contribution of a number of environmental stress factors to net growth reduction at the Soiling site. In addition, the impacts of two environmental policy scenarios for the 1970-2070 period have been evaluated. In the last few decades, a number of forest ecosystem models have been developed which address the impacts of environmental stress factors on forest development. These factors include soil acidification (e.g. Kercher and Axelbrod, 1984; Mohren, 1987; Berdowski et al., 1991), nutrient deficiency (e.g. ,&gren and Bosatta, 1988), lack of soil moisture (e.g. Pastor and Post, 1985; Hunt, 1990) and climatic change (e.g. McGuire et al., 1992; Klein Goldewijk et al., 1994). None of the models considered fits the requirements of the EXPECTmodel, which include a maximum run time of a few minutes for geographically explicit, 50-year simulations and handling multiple stress factors simultaneously. The trade off made explicitly in the EXPECT project is that output data are annual, regional averages rather than sitespecific values. A number of patch dynamics and succession models (e.g. Botkin et al., 1972; Leemans, 1989) can produce results in a short time. These models, however, deal with the relevant stress factors in too simplified a fashion. To satisfy the EXPECT model requirements, FORSOLhas been developed. The development philosophy has been to integrate the useful parts of the available models. 2. Structure of the model
In this section an overview of the structure of FORSOL is given. A full mathematical and quanti-
tative description of FORSOL 1.0 is available in Van Minnen and Meijers (1994). FORSOL 1.0 simulates the annual growth of homogeneous forest stands, annual nutrient and water fluxes in these stands and the soil chemistry of a multi-layer soil below, with regionally averaged stress input values. The model combines concepts used in statistical yield tables with principles of process simulation models. The driving force in FORSOL is an age-dependent annual reference-increment of the diameter at breast height (DBH). With this increment the potential growth of all tree compartments (leaves, wood and fine roots) is subsequently computed. We define reference-increment as the increment under optimum conditions, assuming constant climatic conditions. The growth function is based on the function used by Leemans (1989,1991) and subsequently parameterized with data from LaBastide and Faber (1972) and Mohren et al. (1991). The model may then be used to evaluate the combined impacts of the following environmental stress factors: acidification, drought and nutrient shortage. Acidification includes direct influence of atmospheric sulphur dioxide (SO 2) and ozone (O 3) and indirect effects through soil acidification which influences the availability of nutrients. Finally, maintenance respiration fluxes are calculated to evaluate their contribution to the reduction of the potential growth. The maintenance respiration is computed with a method described by Mohren (1987), who relates the respiration flux to the total amount of nutrients in a tree. Fig. 1 presents an overview of the processes represented in FORSOL1.0. Inputs include deposition fluxes of sulphate (SOx), nitrogen oxides (NOy), reduced nitrogen compounds (NHz), calcium (Ca), magnesium (Mg), potassium (K), sodium (Na) and chlorides (Cl), the ambient air concentrations of sulphur dioxide (SOz), ozone (O 3) and ammonia (NH3), and the number of drought days (see below). Within FORSOL three compartments can be distinguished: the tree compartment, the rooted soil compartment and the soil compartment without roots. The tree compartment and the rooted soil compartment interact via throughfall, turnover of leaves, stem and roots and by the root
J.G. Van Minnen et aL / Ecological Modelling 83 (1995) 197-205
uptake of N, Mg, Ca and K. Throughfall is the result of the deposition fluxes, modified in the canopy by leaf uptake and leaf exudation. The turnover of leaves, stem and fine roots is computed in FORSOL at the end of each one year time step as a fraction of the biomass. This fraction is adjusted in case of high stress levels. The turnover of fine roots is simulated with an iterative procedure, because the yearly turnover is larger than the fine root biomass. Root uptake depends on transpiration, an age-specific nutrient uptake factor, and the nutrient availability in the soil solution. It is negatively affected by reduction of fine root biomass, low pH values and a high A1 concentration in the soil solution (Scott Russel, 1977; Berdowski et al., 1991; see also below). The nutrient availability in the rooted soil compartment is determined by throughfall, mineralization, nitrification, denitrification, and weathering. Each of the two soil compartments of FORSOL consists of two soil layers. The equations for the processes in each layer (Fig. 1) have been derived from De Vries et al. (1988). Mineralization, nitrification, denitrification and weathering are the processes in the rooted soil layers that are modelled. Together with the deposition and net root uptake flux they determine the concentration of plant nutrients and other compounds (e.g. AI, H ÷) in the soil solution. Denitrification and
Soil p r o c e s s e s
Tree p r o c e s s e s
rooted layers :min e ~ I-iza-tio-.--: : nitrification : Idenitrification i
j ............ : leaf uptake
weathering leaching
,denitdfication weathering leaching
Stress factors
-~ ] i
~1~
, leaf exudation
-.i-;q-~al~ty---i
through fall
i nuuientavail. ': i drought ',
DBH increment, allocation total growth respiration transpiration root uptake turnover
ELog,_t,_o?~___. ',atmospheric ', ', deposition I : concentr. [ Idrought days I
Fig. 1. A n overview of the processes modelled in FORSOL.
199
Growth reductionfactor (-)
1.0 0.8
0.6 S02
0.4 i
0.2 Q.O
0
f0 20 30 number ol drought days
40
100 concentration (ug.m-3)
200
Uptake reduction factor (-)
1.0 c 0.8 0.6 0.4 0.2 0.0
, 5
.
r 4 pH {-)
, 3
y
d
2 4 6 8 10 AI concentration (molc.m-3)
Fig. 2. Overview of growth reduction factors, implemented in the FORSOL model (note that in (a) and (b) potential growth is affected and in (c) and (d) the root uptake capacity is affected).
weathering are the processes in the soil compartment without roots that are included in the model. For each soil compartment, the model computes concentrations and leaching fluxes based on soil and tree processes and the net water flux, which in turn is determined by net precipitation and evapotranspiration. The A1 weathering flux is based on weathering of primary silicates and on the weathering of gibbsite (Van Minnen and Meijers, 1994). The pH results from the mass balance in each layer. The computed AI concentrations and pH values are averaged over the soil compartments to generate the controlling parameters for the pH and A1 root uptake reduction. Fig. 2 gives an overview of the environmental stress factors which, in the model, influence the potential growth of a forest stand, i.e. drought
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stress, atmospheric S O 2 and 0 3 and nutrient shortage. In addition, a large maintenance respiration flux also reduces potential growth in FORSOL. This reduction factor is computed by comparing the actual respiration flux with the reference flux. Drought stress is simulated with the exogenous variable drought days (Fig. 2a) which is defined as the number of days on which the soil water content is below wilting point (Pastor and Post, 1985). The multiplicative function representing the relationship between atmospheric O 3 and SO 2 and the potential growth is taken from Berdowski et al. (1991) who follow Jeffree (1981) and Linzon et al. (1984). These authors suggest that both compounds affect tree growth in a more or less similar way. The third variable in FORSOL which may act as a stress factor which affects the potential growth function in FORSOL is the net availability in the trees of N, Mg, C and K. The net availability of these nutrients is calculated as the result of root uptake (affected by the fine root biomass, the p H value and Al concentration in the soil solution, see Fig. 2c + d), leaf uptake and leaf exudation. The net nutrient availability is compared with the required amount of nutrients, a value based on total potential growth ( = sum of the potential growth of leaves, stem and fine roots) and a preset nutrient-and compartmentspecific minimum content. If a shortage of one or several nutrients occurs, the nutrient in greatest demand determines the actual growth reduction factor. The reduction factor representing nutrient shortage is computed after the potential growth has been modified for drought stress, SO z and O 3, and respiration. The multiplicative relationship between potential growth and the separate reduction factors used in FORSOL is based on Berdowski et al. (1991).
3. Derivation of input data for the Soiling study Initialization of FORSOL variables and quantification of parameters for the application of the model to the Soiling spruce site was started with the data set of Bredemeier et al. (1995). The atmospheric deposition data as well as the SO2,
and N H 3 concentration data have been taken directly from this set. The compound-specific filtering factors for dry deposition have been set to 1, because the data in Bredemeier et al. (1995) represent deposition as measured below the spruce canopy. Tree age (96 year), the actual D B H (33.4 cm) and the biomass of the leaf, fine roots and wood compartment (18100, 3500 and 80000 kg ha -1 respectively) for the initial year 1976 have been taken directly from this data set. Allocation fractions of carbon and nutrients in FORSOL have been calibrated to the Bredemeier et al. (1995) growth data and nutrient contents, while the turnover fractions of the leaves, stem and fine roots have been derived from their biomass data and turnover fluxes. Leaf uptake and exudation fractions have been calculated from the deposition and throughfall fluxes. Nutrient-specific selectivity factors for root uptake have been calibrated to the same growth data and nutrient contents, using calculated leaf exudation, leaf uptake and reallocation fluxes. The initial nutrient contents in the tree have been set for each nutrient to the mean value of the observed data over the period 1968-1975. Thinning fractions have been set to Soiling site tree densities to obtain the correct number of trees per hectare. Thinning has not occurred at the Soiling site during the calibration period, but a reduction of the number of trees caused by storms has thus been simulated with FORSOL. We have also derived most of the required soil data from the Bredemeier et al. (1995) data set, e.g. the initial litter biomass and the initial concentrations of all compounds in the soil layers. The initial pH values in both rooted soil layers have been set to 3.8, equal to the mean of the measured values. Furthermore we have calibrated the acid neutralization capacity (ANC) in the rooted soil layers (respectively 0.1 and 0.2 molc kg-1), which is necessary for the simulation of H + and Al concentrations. We also had to set the values of the compound-specific silicate weathering rates to the observed values, because FORSOL is not able to simulate such high weathering fluxes. The values have been set to 125, 75, 25 and 25 tool e yr -1 for magnesium, potassium, 0 3
J.G. Van Minnen et al. / Ecological Modelling 83 (1995) 197-205
calcium and sodium rates respectively (Bredemeier et al., 1995). The remaining data have been derived from literature and other models. The initial reference DBH (52.6 cm) has been taken from yield tables (LaBastide and Faber, 1972). We have calibrated the number of drought days for each year. FORSOL requires the number of drought days as a single numerical value per year. The calibration of this value is based on (1) an annual ratio based on daily actual and potential evapotranspiration data, and computed by Groenenberg et al. (1995), (2) the relationship between this annual ratio and annual potential growth (see McGuire et al., 1992; Klein Goldewijk et al., 1994) and (3) the relationship between growth reduction and the number of drought days (Pastor and Post, 1985). The maximum number of drought days was derived from Pastor and Post (1985) and set to 30 days per year. For those parameters for which spruce data were not available, Douglas fir (Pseudotsuga mensiezii) data have been used. This approach has also been followed in other studies which simulate forest stress at the Solling site (e.g. Van Heerden et al., 1995).
4. Statistical analysis To compare the simulation results with measured data, three statistical indicators were selected from a set described by Janssen and Heuberger (1995): index of agreement (IoA), normalized root mean square error (NRMSE) and normalized mean absolute error (NMAE). These three performance measures have been selected because they allow comparison of simulation results with a relatively small set of field data. Furthermore, the normalized values (instead of RMSE and MAIE) were selected, because they show the relative error instead of the absolute error. IoA expresses the agreement between observations and predictions in a straightforward manner. It varies between 0 (no agreement) and 1 (perfect agreement). N R M S E and N M A E express the deviation from a 1:1 relationship between model predictions and observations. These
201
two indicators become 0 in case of a perfect agreement. The major difference between the two indicators is that N M A E is less sensitive to outliers, because it compensates for positive and negative discrepancies in the same way.
5. Results and discussion Fig. 3 shows the simulated and measured DBH values, stem volumes (both in Fig. 3a) and leaf nutrient contents (Fig. 3c), as well as the simulated leaf and fine root biomass (Fig. 3b) for the period 1978-1989. The measured and simulated DBH start in 1976 with 33.1 and 33.7 cm, respectively, and increase both to 37.1 cm in 1989, which produces a good statistical agreement (see Table 1). Stem biomass field data show an increase from 558 to 651 m 3 ha -l, while VORSOL simulates an increase from 561 to 630 m 3 h a - t , which leads to a good statistical agreement (see Table 1). The discrepancy at the end of the simulation period is readily explained by: (1) the VORSOL thinning fraction, meant for homogenous forest stands and now used in the application to simulate storm damage at the Soiling site, overestimates the actual biomass reduction, as the damage is for the greater part constituted by small trees; (2) the growth function in VORSOL has been parameterized for Dutch forests where old stands are rare. Consequently VORSOL u n d e r e s t i m a t e s stem growth at the relatively old Soiling site. Because field data for leaf biomass are not available beyond 1977, simulated leaf biomass data (fluctuating between 18-19 ton ha -1 ) have been compared to the statistical mean value for field data for the period 1967-1977 (17.8 ton ha-J). In this particular comparison, the IoA produces a relatively low score (see Table 1). This is the consequence of the raising to a square of the relatively large accumulated difference between observed and simulated data. With regard to nutrient contents in the leaf biomass, the simulation data have been compared with the lines between the only available observed data sets (1976 and 1983). Most simulated nutrient contents follow these lines closely. The
J.G. Van Minnen et al. // Ecological Modelling 83 (1995) 197-205
202
simulated N contents in leaves (Fig. 3c) remain at 11.1 g kg -1 dry matter and the measured contents vary between 11 and 11.7 g kg -1. The simulated N contents in litter (not shown in the figure) remain at 20 g kg-1 dry matter and the measured contents vary between 18.5 and 21.1 g kg -~. The simulated Mg, K and Ca contents in the leaf compartment show a decreasing trend
Table 1 Statistical comparison between simulation results and observed data (note that IoA becomes 1 in case of a prefect agreement, while N R M S E and N M A E are then 0)
NRMSE IoA NMAE
DBH
Leaf biomass a
Stem biomass
0.012 0.96 0.009
0.024 0.46 0.02
0.023 0.96 0.02
a Because field data were not available after 1977, the average value of the period 1967-1977 was used in the comparison. - ----
(<-) (->)
• ¢
(<-) D B H (->) S t e r n m a s s
800
40
700 35
-r rn t3
11~ I~ f
11/
600
~f/
30 1975
- -
11~i I
1980
leaf
- - - fine root (<5ram)
1985
500 1990
1985
1990
'
E
]
20000
~-15000
~
'10000
5000.
0 1975
- - -
1980.
•
K
12
E (D "E
oo
-w.
~---7-7--7---7-~'--7"--, 0 1980 1975
. . . . . . .
1985
1990
years
Fig. 3. Comparison between simulated and m e a s u r e d biomasses and nutrient contents in Solling for the period 1976 to 1989. (Lines represent model results and markers are observations).
(Fig. 3c). These trends are in agreement with published data about severe shortage of base cations in many forests in the northern hemisphere (e.g. Kimmins et al., 1985; Van den Burg, 1986; Tomlinsson, 1991). The simulated Ca content decreases from 4.9 in 1976 to 3.1 g kg -1 in 1983, while field data are 5.0 g kg-1 (1976) and 3.4 g kg -1 (1983). The simulated Mg content decreases in the same period from 0.36 to 0.24 g kg- 1 with field data of 0.4 g kg- 1 (1976) and 0.27 g kg -1 (1983). For the K content in the leaf biomass FORSOL simulates a decrease from 5.1 g kg -~ in 1976 to 4.1 g kg -1 in 1983 and 4.0 g kg -~ in 1989. The observed content is about the same in 1976 as in 1983 (5.1 g kg-1). The leaf exudation flux of K presented by Bredemeier et al. (1995) is relatively large. The field data about nutrient content suggest that this loss was compensated for. Such a compensation is not realized with FORSOL. The exudation flux is adequately simulated by FORSOL, but re-uptake by the roots of exudated nutrients is limited. To evaluate the relative impact of the different stress factors, seven additional simulation runs were done with FORSOL for the period 1976-1989 (Table 2). The results of the simulation run with the calibrated model, with all stress factors active, have been used as a reference set (run I). The results of all runs have been averaged over the 1976-1989 period. The simulations indicate that the shortage of base cations causes the largest growth reduction (Table 2: run I-IV). If nutrient shortage is eliminated, growth rates increase by 30-40% (Table 2: run V-VIII). Additional availability of nutrients strongly raises the leaf content of the base cations and increases the respiration
J.G. Van Minnen et al. / Ecological Modelling 83 (1995) 197-205 Table 2 Evaluation of the effects of growth reduction factors on actual stem volume, stem growth, leaf biomass, respiration flux and N and Mg contents in the leaf biomass, averaged over the period 1976-1989 (the results of the reference run are set to
6O
40
100%) Volume Stemgrowth Leaf mass Respiration c{N/lf c{Mg}lf
203
20
I
II
III
IV
V
100 100 100 100 100 100
101 105 103 100 97 100
100 100 100 100 100 100
101 105 103 100 97 100
104 133 142 131 103 290
VI 105 138 145 131 101 279
VII
VIII
105 140 146 131 100 275
105 145 150 131 98 266
30000 Leaf (linE}
......
25000
Root (IrnE)
Root (BAU)
20000
......-\ . . .,..,.~..........,..,...... ......................... ..................
15000
I: Reference = all stress factors active; II: Drought + nutrient stress; III: Nutrient and acidification stress; IV: Nutrient stress only; V: Drought and acidification stress; VI: Drought stress only; VII: Acidification stress only; VIII: No stress factors active.
. . . .
Leaf (BAU)
o
10000
5000
1000
. . . . ~:~ I% ] flux. The nutrient shortage can only be partly explained by soil acidification. If soil acidification stress is set to background conditions and ambient air concentrations of SO 2 and 0 3 are eliminated (Table 2: run II, IV, VI and VIII), growth increases only slightly. Furthermore the nitrogen content decreases, because the availability of N remains constant and is used in more biomass. In the application of FORSOL to the Solling site, soil acidification affects tree growth only when nutrients in the soil are scarce, because the uptake capacity of a tree is affected by low pH and high AI concentration. In the reference run the root uptake of most nutrients is reduced with a maximum of 35%. If H + and A1 concentrations are set to background values, the root uptake reductions are 25-30%. The additional impact of soil acidification is thus relatively small (5% growth reduction). The negative effects of SO 2 and 0 3 on potential growth are even smaller. In the application of FORSOL for Solling, the years 1976, 1982, 1988 and 1989 are years with a relatively large drought stress (10-12%). The drought impact averaged over the period 19761989 was negligible (Table 2 run 1II, IV, VII and VIII), especially in a period without nutrient limitation. In the model, drought is directly linked to potential growth and does not affect the root uptake of nutrients. Therefore, total drought ira-
// ~J
20 N (linE) Mg (linE)
.... ....
N (BAU) Mg (BAU)
16 12
f
•
8 4
01970
. ..--
1990
2010
2030
2050
2070
years
Fig. 4. Simulated biomasses and nutrient status in the Business as Usual (BAU) and an Improved Environment (ImE) scenarios.
pact may be underestimated in the current application. voRSOL has further been run for the period 1970-2070 to evaluate the effects of two environmental policy scenarios: Business As Usual (BAU) and Improved Environment (ImE). Both scenarios are described in Bredemeier et al. (1995). The frequency of drought was set to that of the period 1976-1989. Fig. 4 presents some of the results. In the BAU scenario, FORSOL shows no nutrient shortage during the first ten years of the simula-
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tion. The nutrient pool in the soil, as modelled, turns out to be sufficient for this period. Therefore DBH and leaf biomasses increase more or less normally (Fig. 4a + b). The contents of most nutrients increase slightly in this period (Fig. 4d). After 1983 the nutrient stress increases, especially because of a Ca shortage. Low pH values (3.4) in the rooted soil layers cause large uptake reductions (> 30%), and high leaf exudation rates. Growth reduction due to drought fluctuates through the years (0-15%) and the reduction caused by SO z and 0 3 (10%) remains more or less constant. The result is that with a deposition as in the BAU scenario forest growth is base cation limited. Therefore, the nutrient contents in leaves, wood and fine roots decrease down to their specific minimum. This results in a slight decrease of leaf biomass (Fig. 4b) and a limited impact on stem growth (Fig. 4a + c). In the ImE scenario, forest growth becomes strongly N limited. Drought stress is about similar to that in the BAU scenario, while growth reduction by SO 2 and 0 3 becomes negligible. An increase in pH and a decrease in the A1 concentrations alleviate the reduction of root uptake. Furthermore, N in the soil decreases due to decreased deposition and a smaller mineralization flux, causing N limitation. After 2000 the growth reduction reaches 70%, causing decreases in leaf biomass (Fig. 4b) and DBH increment (Fig. 4a). Base cation concentrations in the leaf compartment recover, caused by increased root uptake (because of less soil acidification) and decreased growth. These larger nutrient contents may cause a reduced sensitivity to secondary damage by e.g. insects (as suggested by e.g. Alstad et al., 1982). The nitrogen content in leaves reaches its minimum content of 6 g kg-l as early as the year 2000. Compared to the BAU scenario, the ImE scenario produces considerably less biomass and smaller DBH.
6. Conclusions The application of the FORSOL model for the Soiling spruce site indicates that FORSOL, originally developed as a model for production of annually and regionally averaged simulation data,
is well capable to simulate average values of relevant site behaviour indicators. This conclusion is based on (1) the fair agreement between simulated and observed data with respect to DBH, stem biomass, the nutrient contents for most nutrients and the nutrient fluxes; (2) the results of the evaluation of the impact of growth reduction factors, which is in line, with respect to the type of stress, with results from other forest models (evaluated by Van Heerden and Yana'i, 1995). The importance of nutrient stress as simulated by FORSOL is furthermore in agreement with findings in a number of forest studies (e.g. Tomlinsson, 1991). (3) the statistical deviation with respect to specific leaf biomass data has been explained and therefore does not diminish the general applicability of FORSOL. However, a more detailed analysis of the model results and the large number of assumptions that had to be made for this application of the FORSOL model, suggest that year-to-year variation in sitespecific data can be simulated more adequately with a site model. Because FORSOL has been developed to be a regional forest model with an annual time step, a number of physiological processes have not been included. To solve this problem for dynamic site-specific applications, the model must be extended with at least a water balance model. The simulation time step of FORSOL should then be reduced to, e.g. 1 day, which would increase the computation time to response times which would not fit the EXPECt requirements. The evaluation of the two deposition scenarios indicated that a strong reduction of especially the N deposition may reduce the growth and biomass of forests after some years, when the nitrogen available in the soil is incorporated in the trees. The combination of improved soil conditions and decreased growth, however, leads to a greater base cations pool within the trees.
Acknowledgements We would like to thank Aldrik Bakema and Kees van Heerden for their critical reviews of
J.G. Van Minnen et al. /Ecological Modelling 83 (1995) 197-205
earlier drafts of the paper, and Caroline van der Salm for the transpiration data. Finally we thank all workshop participants for their contributions to the study.
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