Interannual and spatial variation in maximum leaf area index of temperate deciduous stands

Forest Ecology and Management 134 (2000) 71±81

Interannual and spatial variation in maximum leaf area index of temperate deciduous stands ValeÂrie Le Dantec*, Eric DufreÃne, Bernard Saugier Laboratoire d'Ecophysiologie VeÂgeÂtale, Universite de Paris XI, 91405 Orsay Cedex, France Received 1 February 1999; received in revised form 24 June 1999; accepted 16 August 1999

Abstract The aim of this study was to quantify, both spatial and temporal variations of maximum leaf area index (LAI) and to interpret LAI variation according to stand characteristics and meteorological conditions. We have compared maximum LAI, measured using the LI-COR LAI-2000 PCA, throughout 4 years and over 420 ha of a temperate forest across a range of stand structure (density, biomass, age) and site fertility (soil nutrient and water availability). LAI values ranged from 0.5 to 8 m2 mÿ2. This study has shown that maximal LAI was relatively stable between years. However, although the water stress did not affect LAI development in the current year, it reduced LAI of the following year only in stands with high LAI (above 5.5 m2 mÿ2). Spatial variations of maximal LAI were mainly dependent on forest management which affected tree density and stand diameter at breast height (DBH) through thinning and harvesting. Among the 34 deciduous stands studied, maximal LAI increased with tree density up to a value of about 1000 stems per ha and then it reached a plateau between 6 and 8 m2 mÿ2. Total leaf area per tree has a strong correlation to DBH for species with different sap conducting system (r2 ˆ 0.94). Decreases of maximal LAI with humus quality were observed, suggesting that, although forest management appears to be the main cause of LAI variations between stands and between years, soil fertility may be a determinant of stand LAI. # 2000 Elsevier Science B.V. All rights reserved. Keywords: Beech; Foliar nutrient concentrations; Humus; LAI; Oaks; Stand structure; Water stress

1. Introduction Leaf area index (LAI, the total one-sided foliage area per unit soil surface area) represents the main surface of exchange between plant canopy and the atmosphere. Because LAI controls, to a large extent, carbon and water ¯uxes and light interception, knowledge of LAI is important for quantifying productivity (Waring, 1983; Bonan, 1993; Jose and Gillespie, 1997). Numerous studies have established both theo*

Corresponding author. Tel.: ‡33-1-69-15-79-61; fax: ‡33-1-69-15-72-38. E-mail address: [email protected] (V. Le Dantec)

retical and empirical positive relationships between LAI and forest productivity (Jarvis and Leverenz, 1983; Linder, 1985; Vose and Allen, 1988; Coyea and Margolis, 1994; Maguire et al., 1998). LAI has been shown to explain 80±90% of the variation in the aboveground net primary production (ANPP) of forests in the United States (Gholz, 1982; Gower et al., 1992; Fassnacht and Gower, 1997). LAI is a variable of major importance for scaling-up physiological mechanisms occurring at leaf level (photosynthesis, respiration, transpiration) to the forest canopy level (Running and Coughlan, 1988). Both experimental and comparative studies have demonstrated the relationship between LAI and

0378-1127/00/$ ± see front matter # 2000 Elsevier Science B.V. All rights reserved. PII: S 0 3 7 8 - 1 1 2 7 ( 9 9 ) 0 0 2 4 6 - 7

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evapo-transpiration (Swank et al., 1988) that the LAI is in¯uenced by site water balance (Gholz et al., 1976; Grier and Running, 1977; Gholz, 1982; Long and Smith, 1990; Burton et al., 1991; Jose and Gillespie, 1997) and nutrient availability (Gower et al., 1992). Increases in productivity explained by higher LAI have been attributed to shifts in the allocation of growth from belowground to aboveground in response to increased soil nutrients (Gower et al., 1992), or to increased photosynthetic capacity associated with increased levels of foliar nitrogen (Gower et al., 1992), or to superior leaf area ef®ciency (ANPP/ LAI) with differences in stand structure (Long and Smith, 1990), canopy position (Gilmore and Seymour, 1997; Maguire et al., 1998) or site quality (Waring et al., 1980). Most of these studies have focused on the spatial variation of LAI across a large scale including gradients of soil typology, of precipitation, of species composition and none has been interested in the spatial variations in LAI at a forest scale. Most models predicting forest carbon balance, are not able to properly simulate seasonal and interannual changes in LAI. At the tree level, some attempts have been made to predict leaf area of individual trees using both the pipe model theory and the principle of functional balance (Valentine, 1985; MaÈkela, 1986; Thornley, 1991; West, 1993). But very little is known about the ``mechanisms'' inducing changes in LAI at the stand scale (Woodward and McKee, 1991), even the range in interannual LAI variations is very poorly documented (Vanseveren, 1976; BreÂda, 1994). Because direct and indirect methods for LAI measurements are time-consuming and laborious, remote sensing gives an opportunity to monitor its variability over large scales of time and space (Peterson et al., 1987; Curran et al., 1992; Spanner et al., 1994) and to parameterize process models at a regional scale (Running et al., 1989). This study was part of the European Multisensor Airborne Campaign (EMAC). This programme aimed to test the potential of remote sensing for scaling-up the carbon balance models from stand to the forest scale. The ®rst step of this programme was to collect ground data and in particular to measure LAI by using a Plant Canopy Analyser. The aim of this study was (i) to quantify both spatial and temporal variations of maximum LAI and (ii) to interpret LAI variation according to stand characteristics and meteorological conditions. We have com-

pared maximum LAI throughout four years and over 420 ha of a deciduous temperate forest across a range of stand structure (density, biomass, age) and site fertility (nutrition and soil water availability). 2. Materials and methods 2.1. Site description Measurements were made in the Fontainebleau forest, located south east of Paris (488250 N, 28400 E) at a mean elevation of 120 m. It is a large mixed deciduous±coniferous forest extending over 17 000 ha. The region is characterised by a temperate climate with a mean annual temperature of 10.28C and an annual precipitation of 720 mm. Monthly means of precipitation, established over 30 years, show that rainfall is fairly well distributed throughout the year, resulting in an excess of precipitation in winter and a de®cit in summer (July±September). This de®cit is especially noticeable in some years. Dominant species are oaks (Quercus petraea (Matus) Liebl. and Quercus robur (Matus) Liebl.), beech (Fagus sylvatica L.) and Scots pine (Pinus sylvestris L.). Main understory species consist of hornbeam (Carpinus betulus L.) and beech. The actual landscape in Fontainebleau, which is due to the succession of different geological sediments, is composed mainly by (1) a plateau of limestone and mound of sandstone, which are at an altitude of 130 m, (2) plains situated on the sandy Stampian and/or on the eroded Brie formation (limestone) at 80±90 m and (3) slopes which are on the sandy Stampian. Windborne sands, resulting of wind erosion of sandy Stampian with an addition of loam and clay coming from the limestone alteration, cover all plateaus, plains and slopes with very different depth from place to place (Robin, 1993; Robin and Duchaufour, 1995). Most of the deciduous stands are located on ¯at ground (i.e. on windborne sands), while coniferous species are found on the hilly part of the forest (i.e. on the sandy Stampian, poor in cations or on the sandstone, with a shallow soil). Deciduous trees exhibit a pronounced seasonality throughout the year, characterised by budbreak occurring in April, and leaf-fall in November, with a growing period of about six months. The forest is

V. Le Dantec et al. / Forest Ecology and Management 134 (2000) 71±81

managed by the ``Of®ce National des ForeÃts'' (ONF). Regular thinning (about every ®ve years in young beech pole stands) modify both the structure and the species composition of the forest stands. Stands dominated by oaks represent 50%, beech 10% and Scots pine 40% of the Fontainebleau forest. 2.2. LAI measurements 34 plots were selected in the southern part of the forest according to the following characteristics: (i) each stand was as homogeneous as possible in its structure (height, tree diameter, canopy closure) and in

73

species composition (only one or two dominant species); (ii) the ground is nearly ¯at. This sample of 34 plots was representative of the main types of pure deciduous stands present in Fontainebleau in terms of age (except of the thickets), tree density, stand biomass (ranging from 42 to 471 tDM haÿ1). Among them, 18 were oak-dominant stands, 11 were beech-dominant stands and ®ve were mixed deciduous stands (beeches and oaks) (see Table 1). Budburst generally occurs from mid-April to midMay, and leaf expansion is complete 3 or 4 weeks later. Thus we chose to measure maximum LAI between the

Table 1 Structural characteristics for the 34 deciduous stands (DBH: diameter at breast height, i.e. 130 cm, SA: sample area for LAI measurements, SAb: sample area for biometrical measurements, MF: mature forest, ST: seed tree stand, SS: sapling stand, PS: pole stand) Site name

Dominant species

Forestry

Maximum height (m)

Mean DBH (cm)

Density (stems haÿ1)

Basal area (m2 haÿ1)

Stand area (ha)

SA/stand area (%)

SAb/stand area (%)

O1 O2 O3 O4 O5 O6 O7 O8 O9 O10 O11 O12 O13 O14 O15 O16 O17 O18 OB1 OB2 OB3 OB4 OB5 B1 B2 B3 B4 B5 B6 B7 B8 B9 B10 B11

Oaks Oaks Oaks Oaks Oaks Oaks Oaks Oaks Oaks Oaks Oaks Oaks Oaks Oaks Oaks Oaks Oaks Oaks Oak±Beech Oak±Beech Oak±Beech Oak±Beech Oak±Beech Beech Beech Beech Beech Beech Beech Beech Beech Beech Beech Beech

MF MF MF MF ST MF ST MF ST ST ST SS SS PS MF ST ST SS MF MF ST MF MF PS PS MF MF PS PS MF PS ST MF SS

29.9 27.4 32.1 31.9 40.8 39.2 28.3 24.4 33.3 31.8 30.7 8.7 9.4 13.0 34.3 32.7 30.1 15.9 23.9 37.7 30.4 32.1 29.4 21.5 22.4 31.6 32.8 18.6 19.9 33.3 16.0 30.8 23.0 14.7

16.6 12.4 18.1 19.1 51.6 19.7 47.4 24.5 52.5 64.9 38.2 7.3 4.5 2.5 26.1 51.2 62.1 6.0 15.0 14.0 39.8 11.8 27.7 10.5 14.6 14.3 17.2 9.2 9.9 17.8 7.3 18.1 13.1 6.0

810 1090 755 489 71 521 105 433 71 21 112 1988 4103 4872 518 55 33 5053 1022 641 89 1025 297 1271 699 608 639 2217 2192 622 3563 413 765 4954

40.2 34.2 35.2 30.2 22.1 33.3 22.2 25.6 18.9 7.2 15.3 10.5 9.5 21.1 48.3 13.7 11.7 25.2 29.6 29.1 13.2 31.3 31.3 15.8 15.2 29.3 31.9 24.1 21.0 32.8 20.1 21.0 20.1 22.4

9.8 19.0 18.6 6.4 13.2 21.2 15.8 10.9 14.3 10.8 16.9 10.2 11.2 4.6 6.6 14.7 20.5 5.6 14.9 12.1 19.4 10.2 11.6 6.0 6.6 14.8 8.6 2.7 8.2 11.8 6.7 10.2 10.4 14.7

27.2 16.1 19.3 27.8 24.2 18.6 22.1 29.9 28.4 26.4 16.2 5.7 7.4 18.8 40.8 25.0 16.4 28.4 19.7 21.0 19.2 31.5 19.8 24.2 18.9 21.5 29.8 30.7 27.2 13.1 18.5 30.3 22.3 11.1

9.4 9.3 5.4 38.2 26.7 7.1 15.6 7.2 24.1 84.5 52.8 4.2 2.0 6.7 42.7 16.8 67.7 4.4 5.2 10.5 14 10.8 5.2 9.8 15.5 31.5 13 6.6 3.3 19.8 2.4 14.8 8.1 2.2

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end of June and the middle of July. This was done in each plot for four successive years (from 1994 to 1997). LAI was estimated by using a Plant Canopy Analyser (LI-COR LAI-2000). This is a portable light sensor system designed to measure diffuse light, using ®ve concentric light-detecting silicon rings that receive radiation from ®ve sky sectors centred on the zenithal angles 78, 238, 388, 538 and 688 (Welles and Norman, 1991). The light level was measured in clearings without trees and below the canopy. The ratio of the two values give the transmittance simultaneously for each sky sector (LI-COR, 1992). Then LAI was estimated from averaged gap fraction assuming that leaves were randomly distributed within canopy. Collected data correspond to the plant area index (PAI) which is the projected area of all canopy components including woody parts. For the deciduous stands considered here, the PAI is very closed to the LAI during the leafy period (DufreÃne and BreÂda, 1995). Consequently we will use LAI instead of PAI hereafter. According to plot size (see Table 1), 40±150 measurements were taken at intervals ranging from 5 to 10 m and on several transects. The transects were chosen to cross the stands by two diagonal ways at least to obtain a representative sample of the canopy. The sampled areas (SAs) represented 5±90% of the total stand area (see SA in Table 1). All measurements were made during clear sky days to avoid rapid changes in sky conditions and incident radiation levels. All measurements were made during periods of very low solar elevation (for less than 2 h after sunrise or before sunset) using a view restrictor (1808) to prevent direct sunlight on the sensor. Radiation reference measurements were taken in open areas (e.g. large clearings, roads) close to the stand (300 m or less). Only one instrument was available and was used to measure incident and transmitted light in turn. For each stand a set of ten references (i.e. incident light values) was measured before and after measurements below the canopy. Computation of LAI was done by the LI-COR program (C2000; LI-COR, 1992) using linearly interpolated values of incident light. Assumptions about the linearity of changing incident radiation with time was tested and remained valid for a short time delay between reference series (less than 30 min) and for low solar elevations. According to the small

size of open areas where the incident light was measured the two lowest sectors (zenith angles 538 and 688) were discarded for the calculation of LAI (DufreÃne and BreÂda, 1995). 2.3. Leaf dimensions and foliar nutrient concentrations Leaf dimensions and foliar nutrient concentrations were measured on leaves from the top of the canopy (i.e. sun leaves). Leaf dimensions and foliar concentrations of nitrogen, lignin, cellulose and hemicellulose were measured in 23 plots among the 34 deciduous stands and leaf mineral concentrations (P, K, Ca and Mg), in 15 plots only. Leaf samples were collected in July 1994 on ®ve trees of the dominant species in stands with only one dominant species, or on three trees per species in stands with several codominant species. For each tree, one small branch at the top of the crown, was collected using a shotgun. Ten leaves per branch were sampled individually to estimate leaf mass per area (LMA). The rest of the leaves was dried at 608C and ground for biochemical measurements. 2.3.1. LMA (leaf mass per area) and leaf area LMA estimates were obtained by measuring for each leaf: (i) the area with an area meter (Delta-T area meter, Delta-T Devices, Burwell, UK), (ii) the weight after drying at 608C. The mode of sampling tended to reduce some factors affecting the LMA variation such as the seasonality (sampling after the stabilisation of LMA) and the position in the crown (leaves only at canopy top). It thus allowed the expression of other effects such as the species and the stand variability. 2.3.2. Foliar nutrient concentrations The concentrations of different nutrient compounds were determined on ground dried leaves. Foliar concentrations of nitrogen, lignin, cellulose and hemicellulose were measured with the near-infrared spectroscopy method (NIRS) (Joffre et al., 1992). According to Le Dantec (1995), the NIRS method gives similar values of nutrient concentrations, compared with the two conventional wet chemical analysis, i.e. the Kjeldahl and Van Soest methods. Concentrations of calcium, magnesium, potassium and phosphorus were determined by the Laboratoire

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75

d'Etudes et de Recherches MeÂthodologiques en Analyses VeÂgeÂtales et Environnementales (LERMAVE, Institut National de Recherches Agronomiques, Bordeaux, France).

equation gives the evaporation rate of a short wet lawn, it has found to be useful also as a reference for forest transpiration.

2.4. Stand structure

3. Results

For each plot, in a sample area (SAb in Table 1) which was chosen as homogeneous and representative of the stand, we have measured the DBH (diameter at breast height, 130 cm) of each stem and recorded the species name. Knowing the sample area, stem density and basal area have been calculated for each stand and for each species. The maximum height of each stand was obtained by averaging the height of 8±15 of the tallest trees.

3.1. Interannual variation

2.5. Soil characteristics To establish a typology of forest sites in Fontainebleau, the French National Of®ce for Forestry (ONF) has made a data base of soil characteristics. It contains, among others, depth, texture and thickness of soil layers and the humus type based on the classi®cation of Jabiol (Jabiol et al., 1995; Baize and Jabiol, 1995; BreÃthes et al., 1995). The sampling density was 0.5±1 soil core per hectare, resulting in 1±10 soil cores per plot for our stands. Using all the samples available, we have estimated for each stand a mean of soil parameters such as the humus class and the available water capacity (AWC), which is calculated using thickness and texture of each layer (Baize, 1988). Five types of humus were considered according to the descending order of the decomposition rate: mull, acid mull, mull-moder, moder and mor. 2.6. Meteorological data All meteorological data were supplied by the French meteorological organisation ``MeÂteÂo France''. Air temperature (daily minimum, maximum and average) and daily rainfalls were measured at the meteorological station of Fontainebleau (located in the middle of the forest) and insolation and wind speed, at Melun station (about 10 km North of Fontainebleau). With this meteorological data base, we have calculated a potential evaporation (Ep) using the Penman equation (Penman, 1948). Although the Penman

Yearly maximal values of LAI (LAImax) measured from 1994 to 1997 range from 0.5 to 8.0 m2 mÿ2 (see Table 2), which is similar to the range reported for temperate deciduous forests (Jarvis and Leverenz, 1983). Since 1994, several stands have been submitted to partial cuts. According to intensity of thinning or harvesting, the decrease in LAImax varied from 0.6 to 3.8 m2 mÿ2 in the following summer (see Table 2). The recovery rate of LAImax ranged from 0.5 to 1 m2 mÿ2 per year (see stand B1 and B2 in Fig. 1) and LAI reached 90% of LAImax after three years in stand B3 (see Fig. 1). For uncut stands, interannual variation of LAImax from 1994 to 1996, was similar in all stands (Fig. 2). The slope and the constant of the relationship between the LAImax of two consecutive years were not signi®cantly different from 1 (p ˆ 0.45) and from 0 (p ˆ 0.36), respectively. For the 10 stands with a LAImax higher than 5.5 m2 mÿ2, the values obtained in 1997 were lower than in the three previous years (Fig. 2). During 1996, rainfall showed a de®cit of 173 mm (568 mm) unlike the others years which were in excess (812 mm in 1994, 820 mm in 1995, 854 mm in 1997), compared with the mean over 30 years (741 mm with a con®dence interval of 55 mm). To quantify this de®cit, an index of water stress was de®ned as the ratio of precipitation (P) over potential evaporation (Ep) calculated for the active leafy period (April±October). During 1996, this index (computed for periods in which P < Ep) was lower (0.51) than in 1994 (0.73) and 1995 (0.99). Drought also lasted longer: seven months in 1996 against ®ve in 1994 and four in 1995. It affected 80% of the leafy period in 1996. The water stress before budburst (March) and during the leaf expansion period (April and May) was high and similar for 1996 and 1997. However all stands did not experience the same intensity of water stress, which was buffered by local maximal soil water availability.

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Table 2 Values of annual LAI (LAImax) measured throughout 4 years and potential values of maximal LAI (LAIpot, i.e. without forest management or climatic drought) in the 34 deciduous stands Stands

LAImax 1994

LAImax 1995

LAImax 1996

LAImax 1997

LAIpot

O1 O2 O3 O4 O5 O6 O7 O8 O9 O10 O11 O12 O13 O14 O15 O16 O17 O18 OB1 OB2 OB3 OB4 OB5 B1 B2 B3 B4 B5 B6 B7 B8 B9 B10 B11

6.39 6.21 6.61 n.m.b 2.22 4.97a 1.44 n.m.b 1.88 n.m.b 1.39 n.m.b n.m.b 6.26 5.61 1.18 1.19 6.43 6.07 n.m.b 1.54 6.27 n.m.b 3.58a 3.21a 4.27 n.m.b 7.69 5.21a 4.08 7.96 n.m.b n.m.b 8.06

6.28 6.85 4.86a 4.88a 2.23 5.39 1.89 3.81 2.63 0.51 1.35 3.26 2.05a 6.85 5.45 1.40 1.61 6.48 6.64 6.71 1.65 6.50 6.55 4.29 3.90 2.84a 4.18a 6.76 6.03 4.12 7.72 2.59 5.33 7.21

6.79 7.02 5.38 5.88 2.51 5.57 1.76 3.52 1.57 0.40 1.78 3.32 4.31 n.m.b 5.54 2.01 n.m.b 6.60 7.11 6.02 2.13 6.85 7.05 4.94 4.69 3.09 4.95 7.30 6.49 3.80 7.83 2.86 6.10 7.65

5.72 5.84 4.69 5.40 n.m.b 4.98 2.40 2.90a 2.41 n.m.b 2.66 3.08 3.01 6.39 5.65 1.92a 1.04 5.82 6.13 5.32 2.45 5.50 5.87 5.49 5.04 4.11 4.60 3.47a 5.56a 3.49 6.20 n.m.b 5.52 6.12

6.79 7.02 6.61 5.88 2.51 5.57 2.40 3.81 2.63 0.51 2.66 3.32 4.31 6.85 5.65 2.01 1.61 6.60 7.11 6.71 2.45 6.85 7.05 5.49 5.04 4.27 4.95 7.69 6.49 4.12 7.96 2.86 6.10 8.06

a b

Forest management (thinning or harvesting) occurred between LAI measurement of year N and LAI measurement of year Nÿ1. Not measured.

3.2. Spatial variation We have estimated a potential value of maximal LAI (see LAIpot in Table 2) selecting the absolute maximum of LAImax throughout four years of measurement. Doing this, we have suppressed most of the interannual variability due to severe drought and forest management. Then we assumed that the residual variability is a spatial one and we used this LAIpot to test the hypothetical relationships between stand leaf area and both stand structure and site fertility.

3.2.1. Stand structure First, according to Fig. 3, LAIpot of beech stands increased with the mean area of ``sun'' leaves whereas no such trend was observed in oak and mixed oak± beech stands. Except for two young oak plantations (see O12 and O13 in Table 1), LAIpot increased with stem density, up to a value of about 1000 stems haÿ1. It then reached a plateau between 6 and 8 m2 mÿ2 (Fig. 4). For each stand, we have calculated an average leaf area per tree (LAtree, m2 per tree) equal to the LAIpot dividing by

V. Le Dantec et al. / Forest Ecology and Management 134 (2000) 71±81

77

Fig. 3. Variation of maximal LAI (LAIpot) with the mean area (L, cm2) of top crown leaves (sunlit) in beech and oak stands. For beech stands: LAIpot ˆ 0.516 L ± 4.36 (n ˆ 8, r2 ˆ 0.70).

Fig. 1. Interannual evolution of maximal LAI (LAImax, m2 mÿ2) in three beech stands according to forest management, which is represented by vertical arrow.

tree density. LAtree increased linearly with the DBH averaged over the stand whatever the species considered (Fig. 5). But the best relationship was obtained in removing stand number O10. Indeed, this seed tree stand showed a very low value of LAIpot (0.51 m2 mÿ2) and a small error in this value will strongly affect calculated LAItree. On the other hand, variation of stem density was well explained by stand age (ANOVA, p ˆ 0.001) including or not the seed tree stands (data not shown). 3.2.2. Soil water and nutrient availability We did not observe signi®cant relationships between LAIpot and AWC whatever the stand age

Fig. 2. Interannual variation of maximal LAI (LAImax) throughout four seasons (from 1994 to 1997) in the stands without sylvicultural interventions. The slope and the constant of the relationship between the LAImax of two consecutive years were not significantly different from 1 (p ˆ 0.45) and from 0 (p ˆ 0.36), respectively: LAI95 ˆ 0.92LAI94 ‡ 0.46 (n ˆ 18, r2 ˆ 0.97, broken line); LAI96 ˆ 1.01LAI95 ‡ 0.19 (n ˆ 28, r2 ˆ 0.96, solid line).

Fig. 4. Potential value of maximal LAI (LAIpot, m2 mÿ2) increased with stem density (d, stems haÿ1) up to a value of about 1000 stems haÿ1. It then reached a plateau between 6 and 8 m2 mÿ2. Two young oak plantations (i.e. O12 and O13, represented by open diamond symbols), were excluded from the relationship: LAIpot ˆ (7.50 d)/(189.23 ‡ d) (n ˆ 32, r2 ˆ 0.80).

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V. Le Dantec et al. / Forest Ecology and Management 134 (2000) 71±81

management (low tree density) like the seed tree stands and the two young oak plantations (O12 and O13). The humus type of the three stands with the highest values of LAIpot (i.e. B5, B8, B11) was a mull whereas it was a mor or moder in the three stands with LAIpot of about 4 m2 mÿ2 (i.e. B3, B4, B7). The value of the probability was just lower than the statistical level of 5%. This results may be due to two stands (B01 and B02) which perhaps did not reach the maximal value of potential LAI three years after thinning. Fig. 5. Variation of the mean leaf area per tree (LAtree, m2 treeÿ1) with diameter at breast height (DBH, cm) averaged over the stand. The full circle symbol corresponds to the stand O10, excluded from the relationship. LAtree is linearly related to DBH whatever tree species. We used a weighted model (with confidence interval for p ˆ 0.05 in brackets, n ˆ 33, r2 ˆ 0.94): LAtree ˆ 6.93 (0.69)
DBH ± 26.62 (18.39).

(r2 ˆ 0.005, n ˆ 34). The value of the determination coef®cient was low, even in considering the mature stands only (r2 ˆ 0.007, n ˆ 16). With respect of soil fertility, we have considered the foliar nutrient concentrations as a possible indicator. But, although LMA and nutrient concentrations of sun leaves were different between species (Table 3), they were not related to LAIpot (data not shown). We found a signi®cant decrease of LAIpot with the decrease of humus quality (ANOVA, p ˆ 0.047) in removing the stands whose LAIpot was mainly determined by forest

4. Discussion Forest management appears to be the main cause of LAI variations between stands and between years, because by thinning and harvesting, it changes stand structure as tree density and average DBH. For a long time, foresters have established empirical allometric relationships between foliage area (or biomass) and DBH. More recently, the pipe model theory (Shinozaki et al., 1964) was an attempt to give a mechanistic explanation for the link between DBH and leaf area. It relates the LAI (transpiration area) to the sapwood area (conducting area in the woody organs). Surprisingly, the proportionality between DBH and leaf area per tree observed in Fontainebleau was the same for oaks and beech, which have two different sap conducting systems (porous-ring and diffuse-ring

Table 3 Mean (with CI, the 95% confidence interval) of nutrient concentrations (% or % dry matter) and LMA (g dry matter mÿ2) of ``sun'' leaves of beech (Fagus sylvatica) and oaks (Quercus petraea, Quercus robur)a Per thousand

b

Cellulose (% DM) Hemicelluloseb (% DM) Ligninb (% DM) Nitrogenb (% DM) LMAb (g DM mÿ2 ) Ca (% DM) Kbb (% DM) Mg (% DM) P (% DM) a b

Oaks

Beech

Mean

CI

Mean

CI

15.1 24.2 9.8 2.8 96.1 6.6 6.7 1.5 1.0

0.3 1.0 0.6 0.1 5.3 1.2 1.1 0.2 0.1

19.8 22.2 14.8 2.6 75.0 8.6 5.3 1.4 1.0

0.3 0.4 0.7 0.1 5.4 1.5 0.5 0.2 0.1

Cellulose, hemicellulose, lignin, nitrogen concentrations and LMA were measured in 23 stands, and P, K, Ca and Mg, in 15 stands. Means that the difference between beech and oaks is significant (ANOVA, p < 0.05).

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respectively). Moreover, according to Hillis (1987) the sapwood area of beech includes several tens of years of rings, whereas for porous-ring species, the sapwood area is usually made up of the two or three external rings (Roger and Hinckley, 1979) with a maximum of ten rings. But, according to Poiseuille's law, water conductivity depends not only on sapwood area but also it increases with vessel diameter (Tyree and Ewers, 1991). The larger sapwood area in beech may compensate the smaller size of its vessels (Gasson, 1987), resulting in similar water conductivity in both species. This would explain the unique relationship found between DBH and total leaf area per tree (LAtree). On the other hand, this relationship between DBH and LAtree may be interpreted in terms of carbon balance since stem growth is the result of photosynthesis, which depends on leaf area. According to Pressler (1865), the increase in ring area at a given height represents the contribution of all the leaves located above this height. Leaf nitrogen content in our deciduous stands was equal to or above the optimal values according to Bonneau (1988). Thus no nitrogen de®ciency was observed in deciduous stands of Fontainebleau forest. This explains why there was no relationship between LAI and the nitrogen content of the sunlit leaves. Indeed Vose and Allen (1988) have shown that the nitrogen content at the leaf scale was related to LAI only in the case of a stand of low fertility. The only relationship found with the soil fertility, was the decrease of the potential maximal LAI with the quality of humus. Indeed the humus type is an indicator of the mineralisation rate which depends on the soil fauna activity and the degradability of litter. The decomposition of litter is controlled, in part, by nutrient concentrations, in particular, the C/N ratio observed in leaf litter. Since the nutrient concentrations and the C/N ratio of fresh leaves were not related to the humus type in our stands (data not shown), the humus type can be considered here as a good indicator of soil nutrient availability and not only as a result of the quantity (LAI) and quality (foliar nutrient concentrations) of leaves in litter. Among parameters likely to in¯uence maximal LAI in temperate deciduous forests, water stress is one of the most important. Except for the work of Hebert and Jack (1998), many studies, focused on the spatial variation of LAI across a precipitation gradient, have

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shown a direct relationship between LAI and water availability (Gholz et al., 1976; Grier and Running, 1977; Gholz, 1982; Long and Smith, 1990; Burton et al., 1991; Jose and Gillespie, 1997). Hebert and Jack (1998) attributed the lack of correlation between soil moisture availability indices (actual evapo-transpiration and soil moisture de®cit) and LAI to the deviation from historical precipitation patterns during the years just prior to sampling, which eliminated the precipitation gradient. In the case of Fontainebleau, we have not found such a relationship ``soil water availability± LAI'' because of an important variability of soil type and depth inside each stand. Indeed in the same plot, some soil cores have shown a deep soil with a deep clay layer and others, a shallow soil above a limestone bedrock. This variability in soil depth resulted in a large uncertainty in estimating soil maximal AWC at the stand scale. Water stress is believed to limit not only the size of individual leaves, but also the number of leaves (Taiz and Zeigler, 1991; Hennessey et al., 1992). Drought can act in the leaf area both, directly by reducing growth rate during lamina expansion (Gaudillere, 1989) and indirectly through the carbon balance. Drought can reduce CO2 assimilation through stomatal closure and thus the carbon level during initiation of buds in summer or the carbon available in spring during lamina expansion. In beech and oaks to a large extent, the number and the anatomy of leaves are determined during the bud formation in July (Eschich et al., 1989). Moreover, for oaks, the stem wood formation begins before budburst. Thus the amount of the assimilates available for leaf development during one year is lowered when severe drought occurred the previous year. In beeches, the reserves are used ®rst for leaf growth (Muller, 1993), and water de®cit can be severe enough to reduce the level of carbohydrate reserves used for the lamina expansion, and then to affect the LAImax of the beech stands in the following season. In our study, although the beginning of the season was characterised by a severe and similar water stress during 1996 and 1997, the yearly maximal LAI was only affected in 1997. Then we can assume that the drought of 1996, which has continued during 80% of the leafy period, did not have a direct effect on leaf development during the current year but it reduced the LAImax one year later through the carbon balance (leaf

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number per bud and carbohydrate reserves available for leaf growth). We did not have leaf dimension measurements during the four years of the study. But if we extrapolate the relationship LAImax±leaf area obtained across spatial scales (Fig. 5) to interannual variations, we can suppose that water stress would cause a decrease of LAImax by reducing the leaf area in beech stands and by reducing the leaf number in oak stands. However the drought effect was limited to high LAI (above 5.5 m2 mÿ2) and this, despite a strong water stress (the strongest observed in the last 20 years). Consequently, the direct effect of water stress on stomatal conductance and assimilation appears to be higher than the indirect effect through a decrease in LAI. Finally, we can not exclude that a series of dry years can affect strongly LAI and carbon assimilation. Among parameters likely to in¯uence LAImax in temperate deciduous forests, water stress is one of the most important. Throughout the four years of LAI measurements, this study has shown that water stress can affect LAI with a lag of one year through the carbon balance. However this effect was limited to high values of stand LAI (above 5.5 m2 mÿ2) and this despite a very severe water stress (the most severe in the last 20 years). In conclusion, forest management appears to be the main cause of LAI variations between stands and between years, because thinning and harvesting strongly changes stand structure. Thus if one wants to predict forest carbon sequestration in the future, a management scenario would be introduced to force interannual LAI changes in mechanistic models. Acknowledgements We would like to thank Myriam Legay from the Of®ce National des ForeÃts (ONF, the French National Of®ce for Forestry) for giving us several facilities during this study and for providing us with the Fontainebleau soil data base. We also wish to acknowledge the numerous people who did help us to collect the ground data. The ground data collection was supported by the French National Program for Remote Sensing (PNTS), by the French Program for Environment (SEAH) and by the National Center of Scienti®c Research (CNRS).

References Baize, D., 1988. Guide des analyses courantes en peÂdologie. INRA, Paris 172 pp. Baize, D., Jabiol, B., 1995. Guide pour la description des sols. INRA, Paris, 375 pp. Bonan, G.B., 1993. Importance of leaf area index and forest type when estimating photosynthesis in boreal forest. Remote sensing of environment 43, 303±314. Bonneau, M., 1988. Le diagnostic foliaire. Revue ForestieÁre Franc,aise XL, 19±28. BreÂda, N., 1994. Analyse du fonctionnement hydrique des cheÃnes sessiles (Quercus petraea) et peÂdoncule (Quercus robur) en conditions naturelles; effets des facteurs du milieu et de l'eÂclaircie. Ph.D. Thesis. University of Henri PointcareÂ, Nancy I, 59 pp. BreÃthes, A., Brun, J.J., Jabiol, B., Ponge, J., Toutain, F., 1995. Classification of forest humus forms: a French proposal. Ann. For. Sci. 52, 535±546. Burton, A.J., Pregitzer, K.S., Reed, D.D., 1991. Leaf area and foliar biomass relationships in northern hardwood forests located along an 800 km acid deposition gradient. For. Sci. 37 (4), 1011±1059. Coyea, M.R., Margolis, H.A., 1994. The historical reconstruction of growth efficiency and its relationship to tree mortality in balsam fir ecosystems affected by spruce budworm. Can. J. For. Res. 24, 2208±2221. Curran, P.J., Dungan, J.L., Gholz, H.L., 1992. Seasonal LAI in slash pine estimated with landsat TM. Remote sensing of environment 39, 3±13. DufreÃne, E., BreÂda, N., 1995. Estimation of deciduous forest leaf area index using direct and indirect methods. Oecologia 935, 1± 7. Eschich, W., Burchardt, R., Essiamah, S., 1989. The induction of sun and shade leaves of the European beech (Fagus sylvatica L.): anatomical studies. Trees 3, 1±10. Fassnacht, K.S., Gower, S.T., 1997. Interrelationships among the edaphic and stand characteristics, leaf area index, and aboveground net primary production of upland forest ecosystems in north central Wisconsin. Can. J. For. Res. 27, 1058± 1067. Gasson, P., 1987. Some implications of anatomical variations in the wood of pedunculate oak (Quercus robur L.). IAWA Bull. 8 (2), 149±165. Gaudillere, J.P., 1989. Leaf number, water stress and carbon nutrition effects on poplar leaf growth. International Symposium on Forest Tree Physiology, 25±30 September 1988. Philips Research Labs, Einethoven, Netherlands. Gholz, H.L., 1982. Environmental limits on aboveground net primary production, leaf area and biomass in vegetation zones of the Pacific Northwest. Ecology 53, 469±481. Gholz, H.L., Fitz, F.K., Waring, R.H., 1976. Leaf area difference associated with old-growth forest communities in the western Oregon Cascades. Can. J. For. Res. 6, 49±57. Gilmore, D.W., Seymour, R.S., 1997. Crown architecture of Abies balsamea from four canopy positions. Tree Physiol. 17, 71±80.

V. Le Dantec et al. / Forest Ecology and Management 134 (2000) 71±81 Gower, S.T., Vogt, K.A., Grier, C.C., 1992. Carbon dynamics of Rocky Mountain Douglas-fir: influence of water and nutrient availability. Ecol. Monogr. 62, 43±65. Grier, C.C., Running, S.W., 1977. Leaf area of mature northwestern coniferous forests: relation to site water balance. Ecology 58, 893±899. Hebert, M.T., Jack, S.B., 1998. Leaf area index and site water balance of loblolly pine (Pinus taeda L.) across a precipitation gradient in East Texas. For. Ecol. Mgmt. 105, 273±282. Hennessey, T.C., Dougherty, P.M., Cregg, B.M., Writtwer, R.F., 1992. Needle fall patterns in loblolly pine in relation to climate and stand density. For. Ecol. Mgmt. 51, 329±338. Hillis, W.E., 1987. Heartwood and Tree Exudates. Springer Series in Wood Science. Springer, Berlin. Jabiol, B., BreÃthes, A., Ponge, J.F., Toutain, F., Brun, J.J., 1995. L'humus sous toutes ses formes. ENGREF-Nancy, 63 pp. Jarvis, P.G., Leverenz, J.W., 1983. Productivity of temperate, deciduous and evergreen forests. In: Lango, O.L., Nobel, P.S., Osmond, C.B., Ziegler, H. (Eds.), Ecosystem processes: mineral cycling, productivity and man's influence, vol. 12D. Physiological plant ecology new series. Encyclopaedia in physiology, NS. Springer, Berlin, pp. 233±280. Joffre, R., Gillon, D., Dardenne, P., Agneessens, R., Biston, R., 1992. The use of near-infrared reflectance spectroscopy in litter decomposition studies. Ann. For. Sci. 49, 481±488. Jose, S., Gillespie, A.R., 1997. Leaf area-productivity relationships among mixed-species hardwood forest communities of the central hardwood region. For. Sci. 43 (1), 56±64. Le Dantec, V., 1995. Utilisation de la teÂleÂdeÂtection multi-spectrale en vue de modeÂliser le bilan carbone d'un massif forestier. DEA Ecologie GeÂneÂrale. University of Paris XI-Orsay, 35 pp. LI-COR, 1992. LAI-200 Plant Canopy Analyser Operating Manual. LI-COR, Lincoln, NE, USA, 90 pp. Linder, S., 1985. Potential and actual production in Australian forest stands. In: Landsberg, J.J., Parson, W. (Eds.), Research for Forest Management. CSIRO, Melbourne, pp. 11±35. Long, J.N., Smith, F.W., 1990. Determinant of stemwood production in Pinus contorta var. latifolia forest: the influence of site quality and stand structure. J. Appl. Ecol. 27, 847±856. Maguire, D.A., Brissette, J.C., Gu, L., 1998. Crown architecture and growth efficiency of red spruce in uneven-aged, mixedspecies stands in Maine. Can. J. For. Res. 28, 1233±1240. MaÈkela, A., 1986. Implication of the pipe model theory on dry matter partitioning and height growth in trees. J. Theoret. Biol. 123, 103±120. Muller, N., 1993. Etude dendromeÂtrique et anatomique de la croissance radiale intra-annuelle du heÃtre (Fagus sylvatica L.). DEA Sciences agronomiques, ENSAIA, 33 pp. Penman, H.L., 1948. Natural evaporation from open water, bare soil, bare soil and grass. Proc. R. Soc. London, Ser. A 193, 120±145. Peterson, D.-L., Spanner, M.-A., Running, S.-W., Teuber, K.-B., 1987. Relationships of thematic mapper simulator data to leaf area index of temperature coniferous forests. Remote sensing of environment. 22, 323±341. Pressler, R., 1865. Das Gesetz der Stammbildung. Arnoldische Buchhandlung (Leipzig), 153 pp.

81

Robin, A.-M., 1993. Catalogue des principales stations forestieÁres de la foreÃt de Fontainebleau. ONF/Universite Pierre et Marie Curie, 371 pp. Robin, A.-M., Duchaufour, P., 1995. La typologie des stations forestieÁres du massif de Fontainebleau. Ecologie 26 (3), 159± 168. Roger, R., Hinckley, T.M., 1979. Foliar weight and area related to current sapwood area in oak. For. Sci. 25 (2), 298±303. Running, S.-W., Coughlan, J., 1988. A general model of forest ecosystem processes for regional applications. I. Hydrologic balance, canopy gas exchange, canopy gas exchange and primary production processes. Ecol. modeling 42, 125±154. Running, S.-W., Nemani, R.-R., Peterson, D.-L., Ban, L.-E., Potts, D.-F., Pierce, L.-L., Pierce, L.-L., Spanner, M.-A., 1989. Mapping regional forest evapo-transpiration and photosynthesis by coupling satellite data with ecosystem simulation. Ecology 70 (4), 1090±1101. Shinozaki, K., Yoda, K., Hozumi, K., Kira, T., 1964. A quantitative analysis of plant form the pipe model theory. I. Basic analysis. Jpn. J. Ecol. 14 (3), 97±104. Spanner, M.-A., Johnson, L., Miller, J., McCreight, R., Freemantle, J., Runyon, J., Gong, P., 1994. Remote sensing of seasonal leaf area index across the Oregon transect. Ecol. Appl. 4 (2), 258± 271. Swank, W.T., Swift, L.W., Douglass, J.E., 1988. Streamflow changes associated with forest cutting, species conversions and natural disturbances. In: Swank, W.T., Crossley Jr., D.A. (Eds.), Ecological Studies: Forest Hydrology and Ecology at Coweeta, vol. 66. Springer, New York, pp. 297±312. Taiz, L., Zeigler, E., 1991. Plant Physiology. Benjamin/Cummings, Menio Park, CA, 559 pp. Thornley, J.H.M., 1991. A transport-resistance model of forest growth and partitioning. Ann. Botany 68, 211±226. Tyree, M.T., Ewers, F.W., 1991. The hydraulic architecture of trees and other woody plants Ð Tansley Review no. 34. New Phytol. 119, 345±360. Valentine, H.T., 1985. Tree growth models: derivation employing the pipe model theory. J. Theoret. Biol. 117, 579±585. Vanseveren, J.-P., 1976. Facteurs extrinseÁques et intrinseÁques de productivite dans quelques biogeÂoceÂnoses forestieÁres de haute Belgique. Ph.D. Thesis. Universite libre de Bruxelles, 259 pp. Vose, J.M., Allen, H.L., 1988. Leaf area, stemwood growth, stemwood growth and nutrition relationships in loblolly pine. For. Sci. 34, 546±563. Waring, R.H., 1983. Estimating forest growth and efficiency in relation to canopy leaf area. Adv. Ecol. Res. 13, 327±354. Waring, R.H., Thies, W.G., Muscato, D., 1980. Stem growth per unit leaf area: a measure of tree vigor. For. Sci. 26, 112±117. Welles, J.M., Norman, J.M., 1991. An instrument for indirect measurement of canopy architecture. Agronomy J. 83, 818± 825. West, P.W., 1993. Model of above-ground assimilate partitioning and growth of individual trees in even aged forest monoculture. J. Theoret. Biol. 161, 369±394. Woodward, F.I., McKee, I.F., 1991. Vegetation and Climate. Environ. Int. 17, 535±546.