Sustainability of forest management practices: Evaluation through a simulation model of nutrient cycling

Transcription

1 Forest Ecology and Management 213 (2005) Sustainability of forest management practices: Evaluation through a simulation model of nutrient cycling Juan A. Blanco a, Miguel A. Zavala b, J. Bosco Imbert a, Federico J. Castillo a, * a Departamento de Ciencias del Medio Natural, Edificio los Olivos, Universidad Pública de Navarra, E Pamplona, Navarra, Spain b Departamento de Ecología, Edificio de Ciencias, Universidad de Alcalá, E Alcalá de Henares, Madrid, Spain Received 11 May 2004; received in revised form 25 January 2005; accepted 30 March 2005 Abstract Forest harvesting may interfere with long-term ecosystem structure and function and different harvesting methods will differ in their effects on soil fertility (e.g. whole-tree harvesting versus stem removal). In the case of thinning, effects of thinning intensity, rotation length and site quality must be assessed in order to formulate sustainable management practices. Assessment of the relative impact of these practices is difficult, however, given the long temporal scales involved. In this study, we implement a process-based model of nutrient cycling to evaluate temporal changes in ecosystem nutrient dynamics of managed and nonmanaged forest stands. The model was specifically designed to asses differences between two contrasting site-quality Pinus sylvestris L. stands in the western Pyrenees (Navarre, Spain) managed under two thinning intensities. The model describes the main nutrient fluxes in the stand: litterfall, decomposition, retranslocation, root uptake and management type, and it was parameterized and verified with 3 years of field data. After model verification we examined the effects of thinning intensity, thinning frequency and harvesting method (whole-tree versus stem removal) on potential nutrient losses. The results suggest that in this heterogeneous region, sustainability of forestry practices is strongly site dependent. N and P were particularly sensitive to overexploitation and in no case could whole-tree removal be recommended as it may have a strong negative effect on nutrient reserves. In relation to previous nutrient cycling models, our model offers a satisfactory compromise between simplicity, biological realism and predictability, and it proved to be a useful tool to predict short-term changes in nutrient reserves as well as to evaluate possible negative effects of applying current thinning prescriptions on long-term sustainability of managed forests in the western Pyrenees. # 2005 Elsevier B.V. All rights reserved. Keywords: Thinning; Pinus sylvestris L.; Scots pine; Navarre; Whole-tree removal; Forest harvesting; Nitrogen; Phosphorus; Mediterranean pine forests 1. Introduction * Corresponding author. Tel.: ; fax: address: federico.castillo@unavarra.es (F.J. Castillo). To achieve ecosystem and economic sustainability a forest practice must achieve three different goals: (1) to be economically profitable and to perpetuate forest /$ see front matter # 2005 Elsevier B.V. All rights reserved. doi: /j.foreco

2 210 J.A. Blanco et al. / Forest Ecology and Management 213 (2005) cover, (2) to preserve ecosystem structure (e.g. for biodiversity values) and (3) to preserve ecosystem function (e.g. nutrient cycling) (Zavala and Oria, 1995; Sverdrup and Svensson, 2002). Among other effects, thinning reduces stand biomass, nutrient contents, litterfall (Klemmedson et al., 1990; Harrington and Edwards, 1999) and can alter decomposition rates (Piene and Van Cleve, 1978; Pérez- Batallón et al., 1998). Continuous long-term studies of the effect of management practices on nutrient budgets are expensive and time consuming. As a compliment to long-term experiments, simulation models are useful tools that allow us to extrapolate observed short-term changes in nutrient dynamics to longer time scales (Landsberg, 2003). Experimental studies and modelling are complementary approaches within an adaptive management context that can identify essential mechanisms controlling short- and long-term processes that are critical for maintaining ecosystem structure and function (Kirschbaum, 1999; Grigal, 2000). Once identified, a field-monitoring program can be designed that maximizes the efficiency of sampling and laboratory analyses, which are necessary to confirm that management is sustainable. Models of nutrient cycling are of particular importance for evaluation of sustainability of forest practices. Typically these models include feedbacks among litterfall, retranslocation, tree growth, root uptake and decomposition while aboveground processes are directly related to tree growth. A number of modelling approaches have been used to describe decomposition and root uptake processes. These models differ both in structure and applicability for forest management. The first decomposition models were correlational (Andersson et al., 2000) and were based on statistical relationships among the different variables involved (Olson, 1963; Swift et al., 1979). A second generation of models explicitly considered different fractions of soil organic matter characterized by chemical composition and decomposition rates (CENTURY, Parton et al., 1987). These models are currently used for forest research and management as well as modules within biosphere carbon cycle simulators (e.g. FORSANA, Grote et al., 1998; FORECAST, Kimmins et al., 1999; CenW, Kirschbaum, 1999; EFIMOD 2, Komarov et al., 2003; ForNBM, Zhu et al., 2003). Although they provide adequate biological realism, these models tend to be very complex. This adds uncertainty to the causes underlying their final predictions and weakens their heuristic value (Andersson et al., 2000). Finally, analytical models, such as the Q model (Agren and Bosatta, 1996), provide useful theoretical insights but they often omit too much critical detail (Kimmins, 2004) or are based on parameters difficult to estimate under field conditions. Therefore, the applicability of these simpler models for forest management is often quite limited (Battaglia and Sands, 1998). From a management perspective the most adequate model can be defined as the simplest one among those that meet the users needs both in terms of resolution and precision (Battaglia and Sands, 1998; Botkin, 2001; Landsberg, 2003). Based on this idea, in this study, we have developed a relatively simple model that can be easily parameterized with field data and that allows us to quantify and compare the sustainability of different thinning regimes and harvesting methods for Pinus sylvestris L. stands of contrasting site quality. The model has been developed in response to current forest management needs in Navarre (Spain), and to our knowledge is the first biologically informed model developed in Spain resulting from the cooperation between the university system, the public administration and a forestry enterprise. Data and model validation were performed on two contrasting experimental forests located in the western Pyrenees which represent the two extremes of a site quality gradient. Aspurz is a highly productive Mediterranean forest with relatively fast decomposition rates. Garde in turn exhibits a more continental climate and has a lower production and slower decomposition rates (Blanco et al., 2003a,b). P. sylvestris L. forests have been extensively studied in northern Europe (e.g. Berg and Lousier, 2000; Agren and Knecht, 2001, among others). Results from these studies, however, may not be directly applicable to the Iberian P. sylvestris forests (the southern and western distribution limits for this species) where ecological factors and processes can be qualitatively different from those operating in northern forests. For example, thinning has been shown to reduce decomposition rates in the western Pyrenees forests (Blanco et al., 2003b), while the opposite has been found at higher latitudes (Edmonds, 1990). This, among other observations, points out the need to develop simple biologically based models of nutrient cycling specifically suited for

3 J.A. Blanco et al. / Forest Ecology and Management 213 (2005) Mediterranean forests that can assist us in the evaluation of sustainability of current forest management practices (e.g. Harmon, 2001; Verbug and Johnson, 2001). Our modelling approach is based on the simplification strategy proposed by Tiktak and Van Grinsven (1995). These authors propose to minimize the dynamic feedback between geochemical processes and stand growth using independent submodels, to omit or aggregate short time scale processes (daily and seasonal) and to pool compartments, simplifying and aggregating process descriptions. The main objectives of our work are: (1) to assess whether site quality influences sustainability of thinning practices in western Pyrenees forests, (2) to forecast long-term changes of nutrient pools in two contrasting site-quality stands as a function of harvesting method (whole-tree versus log removal), thinning intensity and rotation length (3) and to evaluate how predicted nutrient losses for different management scenarios, including those currently recommended in P. sylvestris forests in Spain, influence stand nutrient balance and therefore, longterm sustainability of thinning practices. 2. Materials and methods 2.1. Study sites The model was tailored to describe nutrient cycling of P. sylvestris stands in the western Pyrenees (Spain). The model was parameterized with data from two contrasting experimental sites, representing the two extremes of a site quality gradient throughout this region. The lower elevation site (Aspurz, N, W) is one of the most productive P. sylvestris forests in Spain. The stand has developed on a Dystric Cambisol, with mean A horizon organic C of 7.0%. Site mean altitude is 642 m asl with mean annual precipitation and mean annual temperature 912 mm year 1 and 12 8C, respectively. The site is an even-aged P. sylvestris stand resulting from striplike clear-cutting carried out in the mid-1960s. Mean stand age is 37 years and stand density is 3555 trees ha 1, with a dominant height of 14 m and a mean dbh of 24.9 cm. The higher elevation site (Garde, N, W) is an example of a low-production P. sylvestris forest in Spain. The stand is located on a Haplic Alisol, with mean A horizon organic C of 6.3% at a mean altitude of 1335 m asl. Mean annual precipitation is 1268 mm year 1, and mean annual temperature is 8.2 8C. Stand structure is even-aged resulting from clear-cutting during the early sixties. Mean stand age is 32 years, with a density of 3500 trees ha 1, a dominant height of 15.2 m and a mean dbh of 25.0 cm. Fagus sylvatica L. saplings are relatively important on a percentage cover basis in Aspurz but not in Garde. Bedrock for both sites consists of flysch of sandstone and limestones Experimental design Data were gathered across nine rectangular (30 m 40 m) plots per location. Silvicultural treatments were implemented by the Departamento del Medio Ambiente, Gobierno de Navarra according to the guidelines of the International Union of Forestry Research Organizations (IUFRO). The experimental design consisted of three treatments with three replicates per location: treatment 1 (P0) control with no thinning; treatment 2 (P20) moderate low-thinning (20% of basal area removed according to future tree selection method; felled trees were mainly canopy suppressed but included dominant or codominant trees with malformed stems); treatment 3 (P30) heavy lowthinning (30% of basal area removed using the future tree selection method as in P20). To avoid edge effects, the silvicultural treatments were applied within a 5 10 m strip adjacent to each plot Model structure, parameterization and data gathering Our main objective was to estimate changes in N, P, K, Ca and Mg contents in the major nutrient pools. The model was designed to reach a satisfactory compromise between mathematical complexity and biological realism (e.g. Landsberg, 2003) and the number of parameters were kept as low as possible. Fig. 1 shows the main fluxes and pools considered in the model and Fig. 2 shows model inputs and outputs. Tree to soil feedbacks are integrated into the empirical growth function (Tiktak and Van Grinsven, 1995; Agren and Knecht, 2001). Summer drought in these two locations is only moderate and hydrological processes were not

4 212 J.A. Blanco et al. / Forest Ecology and Management 213 (2005) Fig. 1. Model fluxes and nutrient pools. Nd: needle demand; Bd: branch demand; Sd: stem demand; Rd: root demand; Ab: root uptake; Re: retranslocation; Wl: branch litterfall; Nl: needle litterfall; Wm: branch mineralization; Nm: needle mineralization; Rm: root mineralization. explicitly simulated. Thus, model results are restricted to non-water limited forests (Verbug and Johnson, 2001). All combined processes were simulated with 1- year time-steps with program language STELLA Research (High Performance Systems Inc., 1997), which is particularly suited for modelling ecosystem level processes (Costanza and Gottlieb, 1998). Fig. 2. Information fluxes followed to evaluate sustainability of thinning practices with our model. Required inputs are shown in italics and model outputs in bold letters.

5 J.A. Blanco et al. / Forest Ecology and Management 213 (2005) Stand growth functions were simulated with SILVES (Del Río and Montero, 2001) which simulates diameter distributions and thinning of P. sylvestris stands in Spain and calculates stand growth as a function of site index, stand basal area and tree density. Original parameter values were modified based on growth and yield tables developed for this species in Navarre (Puertas, 2003) (data provided by Departamento de Medio Ambiente, Gobierno de Navarra ). Equations describing stem growth were: Mass (Mg ha 1 ) = ln (age, years) (R 2 = 0.99, P < 0.001) for Aspurz, and mass (Mg ha 1 ) = ln (age, years) (R 2 = 0.99, P < 0.001) for Garde. Stem, needle and branch mass were predicted from stem mass through the following allometric equations determined from field data: needles (kg) = stem (kg) (R 2 = 0.66, P < 0.001); branches (kg) = stem stem (kg) (R 2 = 0.74, P < 0.001). To estimate needle, branch and stem biomass before thinning, trees were classified into five dbh classes. Then, the modal tree per dbh class was felled for each plot, for a total of five trees per plot. After determining the component biomass for felled trees, total stand aboveground biomass was calculated by multiplying the biomass of each dbh class by the number of trees in that class. To determine nutrient amounts in needles, branches and stems, we multiplied tissue concentrations by the appropriate component. Root biomass was not estimated in the field, so we assumed that root nutrient content represent a constant fraction of the aboveground tree nutrients contents as did Margolis et al. (1995), and used above/belowground ratios (Table 1) reported by Malkönen (1974) and Litton et al. (2003). A similar assumption has been made in more complex forest models such as HYBRID (Friend et al., 1993) and C_CHANGE (Beets et al., 1999). Litterfall in litter traps was collected monthly from April 2000 to October 2002 in both forests (9 litter traps of 0.29 m 2 per plot 3 treatments 3 replicates 2 sites 31 months = 5022 samples). Samples were separated in the laboratory into six components (needles, branches, fruits, bark, other pine organs and other litter) dried at 72 8C and weighed. For comparison with the simulation only two litterfall fractions were used: (1) needles and (2), a combined branches, bark and fruit (referred to below as the woody litter fraction). Litterfall inputs from tree species other than P. sylvestris and from understory plant species were small, particularly in Garde, and therefore, they have not been included in the model. Leaf litterfall and wood biomass has been assumed to be a fraction of total aboveground leaf and stemwood biomass, respectively (Kimmins et al., 1999; Kirschbaum, 1999; Komarov et al., 2003). Litterfall values for our two experimental sites (Table 1) were similar to mean litterfall values of pine forests reported by Agren (1983), and to those used in models developed by Agren and Knecht (2001). Green and senescent needles were collected bimonthly from December 2001 until October Three branches per plot at 5 m above forest floor were cut every sampling date, and green needles were separated into three cohorts. A total of 972 green samples were collected during this study (3 branches per plot 3 cohorts 3 treatments 3 replicates 2 sites 6 sampling dates). Mean retranslocation efficiency for all cohorts together was calculated following Aerts et al. (1999) as: % retranslocation = 100 (mean concentration in green needles mean concentration in senescent needles)/mean concentration in green needles. Change in nutrient content of the green needles after retranslocation was calculated by multiplying retranslocation percentage by total needle nutrient content. We assumed that retranslocation from roots and woody litter fractions was negligible (Verbug and Johnson, 2001). To calculate the uptake of nutrients by the roots we assumed that the uptake equalled nutrients requirements by trees (Cole and Rapp, 1981; Waring and Running, 2001), which were provided in part by nutrient retranslocation from senescing needles. To estimate tree nutrient requirements we added up the amount of nutrients used for needle, branch, stem and root growth, plus losses through litterfall of branches and needles, plus belowground transfers of dead roots and root exudates to the soil. Decomposition rates for needles were obtained from 50 litterbags (2 mm mesh size, 10 g of needles) per plot placed in the stands in November Three bags were collected for mass loss measurement, monthly for the first three months and then bimonthly (from December 2000 to October 2002). A total of 702 samples were collected in this study (3 bags per plot 3 treatments 3 replicates 2 sites 13 sampling dates). Decomposition of needle and woody litter were simulated assuming that both fractions consisted of a single type of material and exhibited

6 214 Table 1 Parameter values used in the model and source by nutrient and experimental site Parameter N P K Ca Mg Units Reference A G A G A G A G A G Concentration Green needles % Experimental Dry needles % Blanco et al. (2003a) Branches % Blanco et al. (2003a) Stems % Experimental Soil ppm Experimental Decomposition rate Needles years 1 Blanco et al. (2003b) Branches years 1 Agren and Bosatta (1996) Roots % year 1 Mälkonen (1974) Litterfall fraction Needles % year 1 Experimental Branches % year 1 Experimental Atmospheric deposition kg ha 1 year 1 Ministerio de Medio Ambiente (2003) Weathering kg ha 1 year 1 Kimmins (2004), Fisher and Binkley (2000) Ratio above/below-ground biomass % Mälkonen (1974) Initial aboveground nutrient pool kg ha 1 Experimental Initial soil nutrient pool kg ha 1 Experimental A: Aspurz and G: Garde. After the first thinning mean total tree biomass was 243,850 kg ha 1 (P0), 181,404 kg ha 1 (P20) and 164,868 kg ha 1 (P30) in Aspurz, and 218,396 kg ha 1 (P0), 158,265 kg ha 1 (P20) and 135,813 kg ha 1 (P30) in Garde (see treatment description in Section 2.2). J.A. Blanco et al. / Forest Ecology and Management 213 (2005)

7 J.A. Blanco et al. / Forest Ecology and Management 213 (2005) negative exponential weight losses over time (Olson, 1963). We considered different needles cohorts, which fell down in different years and did not change either their chemical composition or their decomposition rate through the decomposition process. Nutrients released from decomposing litter were estimated as M t ¼ M 0 e kt where M t ismassremnantattimet,m 0 the initial mass and k is the decomposition rate (Olson, 1963). To estimate the amount of organic matter decomposition at a given time t (OMD t ), we estimated variation in soil organic matter as the balance between inputs from litterfall and losses from decomposition according to: OMD t ¼ OMlitterfall t OMdecomposition t This is OMdecomposed t ¼ OMlitterfall t OMD t ¼ OMlitterfall t ðom t OM t 1 Þ where OM t is the organic matter content in decomposing litter. Litter is composed of a number of cohorts generated at different times. At a given time organic matter is the sum of the remnant fraction in each of these cohorts, which can be estimated as a sum of negative exponential curves (see a CEN- TURY-based simplification by Bolker et al., 1998). Thus, the amount of organic matter that is lost at any given time from decomposing litter was estimated as OMdecomposed t ¼OMlitterfall t X x¼t ðomlitterfall x e kx Þ x¼0 ðomlitterfall x 1 e kðx 1Þ Þ Xx¼t x¼0 To calculate the decomposition of woody materials we used the rates reported by Agren and Bosatta (1996) (Table 1), following the same procedure as for needles. To simplify the model we assumed that nutrients and organic matter were lost at the same rate over the decomposition process (Andersson et al., 2000; Chertov et al., 2001; Potter et al., 2001). By expressing organic matter changes through time as a sum of first order exponential curves, we can quantify the sensitivity of the model to organic matter changes and make a better use of the data available (Bolker et al., 1998). As for roots, and given that they were not directly studied, we kept the decomposition process as simple as possible. Therefore, dead roots and roots exudates were pooled together and decomposition rate was estimated as a fixed percentage of total root biomass for all the soil profile following Mälkönen (1974) (Table 1) Soil B horizon samples were collected once in November To better characterize the upper A horizon we collected soil samples 5 cm deep bimonthly in all plots from April 2001 to April Soil and leaves (green and senescent) samples were ground with an electric mill. N (soil and leaves) was analyzed using the Kjeldhal method (Harwitte, 1980). Soil and foliar P were analyzed following Bray and Kurtz (1945) and the phosphomolibdo-vanadate method (MAFF, 1986), respectively. For both soil and leaves samples, Ca and Mg were analyzed by atomic absorption spectrophotometry and K by flame photometry. In the model, all soil horizons were pooled together excluding branches and needles in the forests floor. To calculate initial forest floor total nutrient content from which to initiate all simulations, we ran the model for 30 years starting from a soil with no organic layer. Values for different litter fractions at the end of the simulation were used as the initial values on posterior runs of the model (Mäkipää et al., 1998; Kimmins et al., 1999). Simulation of leaching losses of N, Ca and Mg was based on simulated available quantity of these nutrients less the amounts taken up by the trees. This approach is also used in BIOME-BGC (Hunt and Running, 1992), Q (Rolff and Agren, 1999), CenW (Kirschbaum, 1999), FORECAST (Kimmins et al., 1999) and NuCSS (Verbug and Johnson, 2001). In the case of P and K, it was assumed that nutrients not used by trees were inmobilized in the soil (Cooke, 1981). Atmospheric inputs data (wet and dry deposition) used in the model were taken from a nearby site (<40 km distant) by the Spanish Forest Protection Service (Ministerio de Medio Ambiente, Madrid, 2003); the values were similar to mean deposition rates in nonpolluted areas in Europe. Given that both experimental sites have similar parent material and that distance between them is less than 40 km, we assumed similar

8 216 J.A. Blanco et al. / Forest Ecology and Management 213 (2005) atmospheric inputs and geological weathering for both locations. Forest soil weathering rates for this type of bedrock have been reported in Global data base sets elaborated by Kimmins (2004) and Fisher and Binkley (2000) Model analysis: verification and sensitivity analysis We verified our model in several ways. Predicted versus observed values for short-term responses to thinning were evaluated for the 3 years following thinning. We simulated changes in nutrient contents in the control plots after thinning, and then compared model estimates with data from the thinned plots at both locations. A more detailed deviation analysis between observed and simulated data was carried out for N as this nutrient is the most commonly limiting nutrient in forests (e.g. Parton et al., 1996; Gilmanov et al., 1997). The mean absolute deviation (D abs ) was calculated as: D abs ¼ 1 n Xn i¼1 jx est ðt i Þ X obs ðt i Þj where X est and X obs are estimated and observed values for a given variable, and t i (i =1,..., n) represents time in years. Maximum N was defined as the maximun observed value of a particular flux or pool of N in the experimental plots. We compared for each type of N flux or pool the percentage of the maximum N value accounted by the D abs with the percentage of the maximum N value accounted by the standard error of the observed data. To determine the sensitivity of the output variables to variation in input parameter values, we varied each parameter input 10% when the trees reached 100 years, and then assessed the changes shown by aboveground nutrient content of tree biomass (stems + - branches + needles), decomposing plant debris (woody litter + needles) and the totals for all soil horizons (soil + woody litter + needles). The percentage change in the output variables was partitioned into percentage variation due to each parameter, obtaining a sensitivity percentage. Thus, a sensitivity value higher than 100% indicates that the model amplifies parameter changes while a value lower than 100% indicates that model internal dynamics reduce them (Kirschbaum, 1999) Management scenarios To simulate different thinning treatments we imposed different combinations of thinning intensity (percentage removal of basal area), thinning frequency (number of years between two successive thinnings) and removal types (stems or whole-trees). In addition, we have analyzed current management prescriptions for these forests in Spain (Díez and Fernández-Golfín, 1997; Del Río and Montero, 2001) and specifically those adapted to Navarre (Puertas, 2003). According to these prescriptions the exploitation cycle may be reduced to 80 years in high quality stands. Thinning initiates when stands are 20 or 25 years old, and continues every 10 years removing 30% of the total basal area when timber extracted exceeds 50 m 3 ha 1 (economic criteria). This prescription was simulated for Aspurz. A low intensity thinning in low quality stands, however, is not profitable and production cycles can be as long as 120 years, with a thinning program that removes 20% of the total basal area every 15 years. This was the thinning program simulated for Garde. We established a 100-year production cycle for both localities. 3. Results 3.1. Model analysis: verification and sensitivity analysis There was a strong correlation between predicted and observed values for all nutrients inspected (Table 2). D abs of N removed within the stems was 3.9 kg N ha 1, representing 5% of the maximum observed value in this pool (89.1 kg N ha 1 ). This percentage was similar to the result of the maximum observed N pool accounted for by the standard error of the observed values (6%). For N in branches, the D abs percentage (6%) was slightly lower than the percentage for the observations error (7%). For N in needles, the D abs percentage (12%) was similar to the observational error percentage (9%). D abs for N in needle litterfall (1.3 kg N ha 1 ) was within the precision range of the measurements and its percentage (5%) was almost equal to the observational error percentage (4%). Finally, for woody litterfall (10.1 kg N ha 1 ), the D abs percentage (11%) was bigger than the observational

9 J.A. Blanco et al. / Forest Ecology and Management 213 (2005) Table 2 Results of verification regressions (R 2 ) of observed data vs. simulated data for nutrient amount (kg ha 1 )infive different fluxes Nutrient Extracted stems Extracted branches Extracted needles Leaf litterfall Woody litterfall N ** ** ** * ** P ** ** ** * ** K ** ** ** * ** Ca ** ** ** * ** Mg ** ** ** * ** * P < ** P < error percentage (6%). Sensitivity analysis showed that the model behaved similarly in both localities, diminishing the changes for all the parameters (less than 100% of variation for all variables, see Section 2). The most sensitive variable was N content in decomposing leaf litter (needles + woody litter), as it varied 55% in Aspurz when the litterfall fraction parameter was changed. For other parameters sensitivity values were lower than those for the N content in decomposing litter Changes in nutrient pools over time Woody litter was the main pool for N in the control stands as its low decomposition rates favoured accumulation, particularly in Garde (Olson s k was 42% lower than in Aspurz; Blanco et al., 2003b)(Figs. 3 and 4). On the contrary, stems were the pool with the lowest N contents in the control stands. A total of 1819 kg N ha 1 had accumulated in Aspurz at the end of the simulation, which represented 55% more than that accumulated in Garde (1177 kg N ha 1 ). The simulated thinning cycle caused a 60 and a 27% total N reduction in Aspurz and Garde, respectively (Figs. 3 and 4). The most and the least sensitive pools were needles and woody litter, respectively. These differences caused changes in the relative importance of each pool, particularly for needles, which ranked first before thinning, and second after thinning in both sites. For P, the branches were the most important pool in the control stands with 39 kg P ha 1 in Aspurz and 44 kg P ha 1 in Garde at the end of the simulation. The relative importance of woody litter increased over time, and became the second most important pool in both sites at the end of the simulation. Total aboveground content of P was 145 and 131 kg ha 1 in Aspurz and Garde, respectively. The distribution of P among pools changed dramatically after applying the recommended management practices (Figs. 3 and 4). Thus, total P content in leaf litter increased 69% and 37% in Aspurz and Garde, respectively, while total aboveground content of P decreased 19% and 21% in Aspurz and Garde, respectively. Unlike P and N, K content in the thinning plots was smallest in the decomposing pools (leaf litter and woody litter), while in the control plots the pools with the highest K content were stems and branches. At the end of the simulation, the stems had 322 kg K ha 1 in Aspurz and 296 kg K ha 1 in Garde. Total K content was similar in both forests (913 kg kg K ha 1 in Aspurz and 834 kg K ha 1 in Garde; Figs. 3 and 4). The decomposing woody litter was the most important pool for K in Aspurz after thinning, but in Garde the stems and the branches were the most important pool before and after thinning (Figs. 3 and 4). In addition, only 39 and 73% of K remained in Aspurz and in Garde, respectively, at the end of the simulation. The response of Ca reflected its structural role in stems, being the pool with the highest contents. In the reference plots, Ca accumulation in the stems was 780 kg ha 1 in Aspurz and 468 kg ha 1 in Garde. After thinning, total Ca showed a 52% reduction, but in Garde it only diminished 2%. Finally, differences between sites were higher for Mg than for Ca (Figs. 3 and 4). Decomposing leaf litter was the most important pool (170 kg Mg ha 1 at the end of the simulation) in Aspurz baseline plots. In Garde, however, stems were the most important pool with 124 kg Mg ha 1. Thinning caused little changes in the relative importance of Mg among pools in both sites, although the total content of Mg decreased 68% in Aspurz and 27% in Garde Potential nutrient losses due to the thinning and tree removal method Potential nutrient losses are defined as the sum of nutrients extracted due to tree removal and nutrients

10 218 J.A. Blanco et al. / Forest Ecology and Management 213 (2005) Fig. 3. Mass evolution of N, P, K, Ca and Mg in every pool along stand life in Aspurz. Left column is a non-managed forest and right column is a simulation under recommended thinning prescription (thinning of 30% basal area every 10 years, stem removal). lixiviation when mineralization rates exceed root absorption. Accumulated potential losses resulting from simulations in Aspurz averaged 345 kg N ha 1 when only tree stems were removed, and 635 kg N ha 1 for whole-tree removal. These values were lower in Garde: 269 and 523 kg N ha 1, respectively. An increase in thinning intensity up to 20% resulted in higher potential losses particularly for whole-tree

11 J.A. Blanco et al. / Forest Ecology and Management 213 (2005) Fig. 4. Mass evolution of N, P, K, Ca and Mg in every pool along stand life in Garde. Left column is a non-managed forest and right column is a simulation under recommended thinning prescriptions (thinning of 20% basal area every 15 years, stem removal). removal (Fig. 5). The rate of increase diminished after a thinning intensity of approximately 20%. Phosphorus mean potential losses for stem removal equalled 18 kg P ha 1 in Aspurz and 10 kg P ha 1 in Garde, and considerably increased if the whole tree was removed (41 kg P ha 1 in Aspurz and 42 kg P ha 1 in Garde). Maximum losses in Garde occurred for a range of thinning intensities between 20 and 30%, while in Aspurz, nutrient losses increased and reached a plateau after 10% of the basal area was removed (Fig. 6). Mean

12 220 J.A. Blanco et al. / Forest Ecology and Management 213 (2005) Fig. 5. Potential N losses caused by management (thinning + lixiviation) in the two experimental sites, with stem (top) and whole-tree (bottom) removal as a function of thinning intensity and rotation. The point labelled by a solid dot represents recommended thinning intensity and frequency. The horizontal solid line represents accumulated external N inputs by deposition and mineral weathering. potassium losses in Aspurz equalled 163 kg K ha 1 for stem-only extraction and 400 kg K ha 1 for whole-tree removal and 161 and 370 kg K ha 1 in Garde, respectively. Maximum potassium losses in Garde were found for thinning intensities around 30% (wholetree removal). These trends were not as pronounced in the Aspurz plots (Fig. 7). For calcium, differences between the two types of tree removal were not as dramatic 423 and 510 kg Ca ha 1 in Aspurz, and 276 and 340 kg Ca ha 1 in Garde for stem and whole-tree removal, respectively. Loss rates increased dramatically with thinning intensity up to 20% and were less pronounced after 20% to decrease afterwards (Fig. 8). Similar trends were described for magnesium with average potential losses of 87 and 138 kg Mg ha 1 (Aspurz) and 83 and 114 kg Mg ha 1 (Garde), respectively, for stem and whole-tree removal (Fig. 9). Overall, a strong interaction between silvicultural treatments and sites was observed. For each nutrient, thinning resulted in a broader range of variation of potential nutrient losses (difference between maximum and minimum losses) in Garde when compared to Aspurz. This variation was also affected differentially by tree removal procedure in each site, being more pronounced in Garde than in Aspurz. In particular, whole-tree removal amplified this variation in Garde but ameliorated it in Aspurz. With respect to thinning frequency, an increment from 5 to 25 years resulted in losses of around 50% for each nutrient in both sites (Figs. 5 9).

13 J.A. Blanco et al. / Forest Ecology and Management 213 (2005) Fig. 6. Potential P losses caused by management (thinning) in the two experimental sites, with stem (top) and whole-tree (bottom) removal as a function of thinning intensity and rotation. The point labelled by a solid dot represents recommended thinning intensity and frequency. The horizontal solid line represents accumulated external P inputs by deposition and mineral weathering. 4. Discussion Despite its simplicity, our model was in a good agreement with the observations over a short-time frame (Table 2). Also, low model sensitivity suggests that model structure is robust with respect to error propagation of initial estimates (Chertov et al., 2001) Factors influencing sustainability of forestry practices Site quality at each location was the most important factor influencing sustainability of forest management. Potential N losses in Garde, a site with poorer site productivity and N stem content, were significantly lower than those found in Aspurz (Fig. 5). Similar patterns were observed for Ca and Mg. For P and K, however, lower outputs were compensated by larger nutrient concentrations found in Garde trees. Thus, potential nutrient P and K losses were similar in both sites. Comparable results have been found by Morris et al. (1997) who pointed out that sustainability of forestry practices may critically depend on site ecological features such as decomposition rate (in our study higher in Aspurz than in Garde, see Blanco et al., 2003b). Potential lixiviation rates for N, Ca and Mg were estimated as the difference between mineralization release and root uptake. Thus, higher mineralization rates may result in higher potential losses. Also, an increment in lixiviated nutrients after thinning has

14 222 J.A. Blanco et al. / Forest Ecology and Management 213 (2005) Fig. 7. Potential K losses by management (thinning + lixiviation) in the two experimental sites, with stem (top) or whole-tree (bottom) removal as a function of thinning intensity and rotation. The point labelled by a solid dot represents recommended thinning intensity and frequency. Accumulated K inputs are 2836 kg ha 1 in Aspurz and 2627 kg ha 1 in Garde (beyond figure limits). been evidenced in experimental studies by Baeumler and Zech (1998). In addition to the site, tree removal procedure (stem versus whole-tree) had the second impact on sustainability. For all nutrients and sites, whole-tree removal resulted in significantly higher potential losses with respect to traditional on-site tree processing, allowing nutrients within leaves, twigs and branches to recycle. Increments in potential nutrient losses due to wholetree removal were particularly critical for P and K and are mostly located in branches and needles. Nutrient losses were less for Ca and Mg, which are primarily found in the stems. According to the model results, these increments turn out to be critical for the longterm sustainability of current thinning practices. For example, in Aspurz, N inputs compensate for N losses for a range of thinning regimes but this balance reverses under whole-tree removal operations. This leads to important reductions in nutrient reserves that may compromise future forest productivity. Similar results have been found by Morris et al. (1997) and Rolff and Agren (1999). Our model is conservative with respect to other factors such as competition of understory plants that may amplify this reduction (Jacobson et al., 2000). The third determinant of sustainability was thinning intensity. Potential nutrient losses increased dramatically between unmanaged and managed stands for all sites and nutrients. Thinning effects on nutrient losses increased up to a maximum for a basal area removal of approximately 20%, and decreased afterwards. The effect of thinning intensity interacted with

15 J.A. Blanco et al. / Forest Ecology and Management 213 (2005) Fig. 8. Potential Ca losses by management (thinning + lixiviation) in the two experimental sites, with stem (top) or whole-tree (bottom) extraction as a function of thinning intensity and rotation. The point labelled by a solid dot represents recommended thinning intensity and frequency. Accumulated Ca inputs are 3366 kg ha 1 in Aspurz and 3069 kg ha 1 in Garde (beyond figure limits). site. In Garde, maximum P and K losses were found under thinning intensities around 30% and tended to decrease at higher intensities. These variations, however, were significantly smoother in Aspurz (Figs. 6 and 7). At intermediate thinning intensities, the increment in standing crop due to increased growth of released trees, compensates for the decrease in production derived from lower tree density. Hence, it may be possible to maintain or even to increase wood extraction relative to that of lower intensity thinning regimes. At higher thinning intensities, however, a point is reached in which reduction in tree density is so severe than growth increments of remnant trees do not compensate for the density reduction and, thus wood extracted in each cycle tends to decrease. On the other hand, decrease in decomposition rates in response to thinning in Aspurz (Blanco et al., 2003b) resultsina decrease in mineralization rates and likely a reduction in lixiviation. Nutrient losses due to extraction were relatively higher than those caused by an increase in lixiviation and were therefore in agreement with previous studies (Grigal, 2000; Zhu et al., 2003; Kimmins, 2004). Johnson and Todd (1987) also showed that this difference had significant effects for N and P concentrations in forests in Tennessee (USA). As these authors suggest it is unlikely that lixiviation alone results in a decrease in productivity, even during late successional stages when losses due to lixiviation equal ecosystem inputs (Vitousek and Reiners, 1975). Finally, according to model results, sustainability of the thinning regime is influenced by its frequency or

16 224 J.A. Blanco et al. / Forest Ecology and Management 213 (2005) Fig. 9. Potential Mg losses by management (thinning + lixiviation) in the two experimental sites, with stem (top) or whole-tree (bottom) extraction, depending on thinning intensity and frequency. The point labelled by a solid dot represents recommended thinning intensity and frequency. Accumulated Mg inputs are 877 kg ha 1 in Aspurz and 813 kg ha 1 in Garde (beyond figure limits). rotation cycle, which determines the average number of years between two consecutive forest operations. The shorter the cycle, the larger the number of interventions and thus, the larger potential losses of nutrients. This trend can be observed for all the nutrients considered (Figs. 5 9), and interacts with thinning intensity, so its effect is relatively larger for low-thinning intensities. This reflects forest capability to recover initial biomass after moderate interventions. The remnant trees can restore or even surpass the previous standing crop density, providing that operational lag is long enough (Thornley and Cannell, 2000). However, if thinning intensity is greater than 30% stand ability to restore its initial biomass decreases (Montero et al., 1999). In this case, a longer interval between interventions does not allow for stand recovery and the relative impact of thinning frequency decreases. Short rotations also may increase the time of soil exposure and low forest cover (increasing the period over which mineralization rates are greater than tree demand) therefore, increasing lixiviation. Rolff and Agren (1999) predicted a decrease in productivity for shorter time intervals between interventions, while Seely et al. (2002) observed that shorter rotations can result in a substantial decrease in forest nutrient reserves in the long-term. Our modelling results suggest that thinning frequency effects on nutrient reserves are not as critical as those of the tree removal procedure and thinning intensity. This does not imply, however, that

17 J.A. Blanco et al. / Forest Ecology and Management 213 (2005) this aspect of forest management is not critical for other components of sustainability Silvicultural implications All situations that compromise ecosystem nutrient recharge capability should be avoided as they will result in a gradual decrease of nutrient reserves and productivity (Kimmins, 2004). Nevertheless, it is possible, to attain a level of exploitation that allows to sustain long-term forest productivity or even to induce a recovery of nutrient reserves (Morris et al., 1997). Our modelling study suggests that P reserves can be particularly sensitive to overexploitation (Fig. 6). This is in agreement with previous experimental studies conducted at our site, which suggest P limitations (Blanco et al., unpublished data) and indicate the need to pay more attention to phosphorus cycling under different site and thinning regimes, as well as its effects on site productivity and community composition. The strong variability across sites regarding their response to thinning suggests that results should not be extrapolated from one site to another. Chiefly, site dependency of tree growth rates result in quantitative and qualitative differential responses in nutrient dynamics (Figs. 3 and 4). Thus, forestry prescriptions for P. sylvestris in the Central and Iberian ranges in Spain (Del Río and Montero, 2001) may result in nutrient reserve dynamics close to recharge capability. In particular, for P reserves application of these prescriptions may result in values above the sustainability threshold in the most productive site, and on the verge of this threshold in the least productive site. On the high quality site these practices may result in N losses below inputs, but for P reserves the balance results in significant net losses suggesting the need to reduce thinning intensity or rotation cycles. Wholetree extraction is not advised in any of our sites as it resulted into unsustainable P losses for all thinning regimes considered. This practice would only be justified if applied along with N P fertilization as proposed by Rolff and Agren (1999), although its costs are likely not viable in this region. Finally, other forest interventions such as fine wood extraction to decrease fire risk, slash crushing to accelerate decomposition or the use of litter for gathering game or domestic range could have very different impact on natural versus managed forests. This may be especially true when decomposing material is the most important forest nutrient reserve, which among other factors, depends on the nutrient considered, locality and management practice. In this context, in order to ameliorate CO 2 emissions, using biomass such as leaves and branches as a substitute for fossil fuels has been claimed to be more beneficial from social and economic perspectives than sequestering the carbon in forests (Hall, 1997). However, the results from this study suggest caution to favour this practice without proper evaluation as forest sustainability may be negatively affected by removing the whole tree from the forest Model limitations and further work Firstly, we have only considered nutrient cycling associated with P. sylvestris while understory effects that can have an influence on nutrient retention and reduce lixiviation have been ignored. Secondly, we have oversimplified root description and despite low model sensitivity, the decomposition of dead roots and exudates should be adequately described as they can constitute an important soil biomass input (Beets et al., 1999). Thirdly, our experimental data do not indicate effects of thinning on decomposition rates at Garde after 2 years of study but show a lowering effect at Aspurz, possibly due to alterations of the decomposer community (Blanco et al., 2003b). We have tentatively explored how these latter results may affect nutrient losses but we need further empirical studies to understand in which direction these changes will take place. For example, increments in incident radiation and temperature, due to a reduction in tree density, may stimulate mineralization and result in losses from lixiviation higher than the ones described in our model. Fourthly, if nutrient concentration in trees declines with age (Kimmins, 2004), losses from wood removal would be lower than those simulated. Fifth, the external components of the nutrient cycle (runoff, erosion, etc.) should be adequately described to assess its relative contribution to other fluxes in our model. Finally, simulated estimates of nutrient losses can be misleading. For example, in unmanaged forests nutrient outputs can be naturally high (e.g. Ca in calcareous locations), or there may be managed forests in which high-nutrient reserves allow for more intense exploitation. Thus, it may be more

18 226 J.A. Blanco et al. / Forest Ecology and Management 213 (2005) suitable to establish relative comparisons among alternate thinning regimes to rank them in terms of potential risk. All these limiting factors caution against our quantitative predictions. Despite these limitations, our work shows how simple simulation models, based on parameters which can be easily obtained from standard forest ecosystem studies (litter traps and decomposition bags, chemical analyses of soil, needles, branches, wood) can be used as diagnosis tools to compare the potential impact of alternate interventions on long-term sustainability and suggest critical processes that may not be intuitively obvious. The main challenge to developing explanatory and yet useful models of ecosystem function from a management point of view is to achieve a reasonable balance between model complexity, parameter observability and biological realism. We feel that an iterative approximation of experimental studies and modelling within an adaptive management context is the most promising direction. 5. Conclusions It has been shown that suitability of recommended forestry practices in such a heterogeneous region is very site dependent. Firstly, we caution against extrapolation from one site to another without a specific impact evaluation. It is possible that many studies from temperate P. sylvestris regions must be interpreted with caution. Secondly, differences in ecosystem function in nutrient cycling between a Mediterranean climate (Aspurz) and a more continental climate (Garde), are in part overridden by the impact of biomass extraction. However, faster decomposition rates under Mediterranean conditions can make these forests more sensitive to human intervention. Thirdly, current recommendations seem adequate for N, K, Ca and Mg but their consequences on P reserves should be investigated in more detail. Finally, the single most important silvicultural factor in a thinning operation is the tree harvesting method. For all the cases analyzed in this study whole-tree removal should not be used as it may compromise long-term sustainability. Results from simple models of this sort for evaluation of long-term effects on current silvicultural practices must be evaluated for management effects on regeneration, harvesting age or size as well as forest operation costs to compile with current economic demands and ecological sustainability of forest resource management. Acknowledgements Juan A. Blanco was supported by a research grant from CICYT ( Ministerio de Ciencia y Tecnología ) during his stay at the University of Alcalá. We thank Gobierno de Navarra, Departamento de Educacióny Cultura for financial support and Departamento del Medio Ambiente for experimental setting of silvicultural treatments and financial support. In particular, we acknowledge Fernando Puertas, Carmen Traver and Ana Iriarte for assistance at several stages of this work. We are grateful to the scientific forest network GLOBIMED ( for hosting meetings where the cooperation between our universities was initiated. We are also grateful to Dr. J.P. Kimmins, Tanya Seebacher and two anonymous reviewers for their useful suggestions and comments on the manuscript. References Aerts, R., Verhoeven, J.T.A., Whigham, D.F., Plant-mediated controls on nutrient cycling in temperate fens and bogs. Ecology 80, Agren, G.I., Nitrogen productivity of some conifers. Can. J. For. Res. 13, Agren, G.I., Bosatta, E., Theoretical Ecosystem Ecology. Understanding Element Cycles. Cambridge University Press, Cambridge. Agren, G.I., Knecht, M., Simulation of soil carbon and nutrient development under Pinus sylvestris and Pinus contorta. For. Ecol. Manage. 141, Andersson, F.O., Agren, G.I., Führer, E., Sustainable tree biomass production. For. Ecol. Manage. 132, Baeumler, R., Zech, W., Soil solution chemistry and impact of forest thinning in mountain forests in the Bavarian Alps. For. Ecol. Manage. 108, Battaglia, M., Sands, P.J., Process-based forest productivity models and their application in forest management. For. Ecol. Manage. 102, Beets, P.N., Robertson, K.A., Ford-Robertson, J.B., Gordon, J., Maclaren, J.P., Description and validation of C_Change: a model for simulating carbon content in managed Pinus radiata stands. N. Z. J. For. Sci. 29,