minimal temperature, mean temperature, solar zenith angle at noon, air pressure and wind speed ; diameter data from field measurement and natio

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1 2003, 27 (3) Ξ Acta Phytoecologica Sinica 3S (1, ) (2, ) (3, ) ( LUE),, (TM), LUE (LAI) ; ( EPPML), ( NPP) LUE ; ( GIS), EPPML NPP, LUE LUE, LUE,, LUE NPP, % LUE % % % % LUE %, % %, ( Pinus koraiensis) ( %), ( %) LUE, 3S SIMULATION OF TEMPORAL AND SPATIAL DISTRIBUTION OF NATURAL VEGETATION L IGHT UTIL IZATION EFFICIENCY BASED ON 3S ZHANG Na 1 YU Gui- Rui 2 YU Zhen-Liang 3 and ZHAO Shi-Dong 2 (1 College of Earth Science, Graduate School, the Chinese Academy of Sciences, Beijing , China) (2 Institute of Geographic Sciences and Natural Resources Research, the Chinese Academy of Sciences, Beijing , China) (3 National Natural Science Foundation of China, Beijing , China) Abstract Light utilization efficiency ( LUE) directly influences the distribution of energy and rate of photo2 synthesis in all layers of vegetation. LUE is very valuable in deciding the integrated limits of environment to photosynthesis and plant growth allocation of aboveground, and is an important index in weighing functions of system. In China, the studies on LUE focus usually on crops, rarely on natural vegetations, and mostly calcu2 late mean LUE over the country. The studies on LUE of natural vegetations in some regions are limited to one or two types of vegetation. Thus, it is very difficult to reflect the total conditions of all vegetations over these regions in different periods. In the study, leaf area index ( LAI) that greatly influences LUE of vegetation was received from remote sensing images. The ecosystem productivity process model at landscape scale ( EPPML) that described carbon cycle and water cycle of system was built by computer program (Visual C + + ), and seasonal dynamics and spatial distributions of total solar radiation, net primary productivity ( N PP) and LUE in Changbai Mountain Nature Reserve were simulated. Geographical Information System ( GIS) was used to process, analyze and dis2 play spatial data. Thus, we could extend and convert the studies on physiological ecology of plants from small scale to a larger scale. EPPML uses the principles of Century, BIOM-BGC, Forest-BGC and BEPS for quanti2 fying the biophysical processes governing ecosystem productivity, but the original model is modified to better represent Changbai Mountain region. A numerical scheme is developed to integrate different data types : remote sensing data ( TM), gridded vegetation, soil and topographic maps at 30- m resolution in Albers projection ; daily meteorological data in Changbai Mountain station in 1995, including precipitation, maximal temperature, Ξ : : : (CX10G-C00-01) ( ) ac. cn

2 minimal temperature, mean temperature, solar zenith angle at noon, air pressure and wind speed ; diameter data from field measurement and national forest survey ; data from literatures for inputs to EPPML and valida2 tion of EPPML. Vegetation index is derived from remote sensing data for estimating daily LAI and biomass at landscape scale. The information about vegetation type, soil type, elevation, slope and aspect can be derived from vegetation, soil and topographic maps. EPPML uses the biochemical model for photosynthesis of leaves developed by Farquhar et al. (1980) to simulate the rate of photosynthesis. N PP is the organic matter elimi2 nating respiration from gross photosynthetic productivity ( GPP). In addition, EPPML uses the sub- module MT-Clim in Forest-BGC to calculate total solar radiation. In EPPML, the spatial scale is 30 m and temporal scale is daily and yearly. The whole simulating process is easily understood and realized. EPPML is run and values are cumulated in each pixel. The major outputs include seasonal dynamics and spatial distributions of some carbon cycle and water cycle variables including N PP and LUE. The results indicated that the seasonal variation of LUE of vegetations in Changbai Mountain was similar to that of N PP with peak value in July (2. 9 %). The LUE in spring, summer, autumn and winter averaged %, %, % and % respectively. The annual LUE of all vegetation types averaged %, varying from % to %. The maximal annual LUE appeared in mixed broad-leaved and korean pine forests ( %), minimum in alpine grasses ( %), others being Changbai larch for2 est ( %), spruce-fir forest ( %), meadow ( %), broad-leaved forest ( %), shrub ( %), alpine tundra ( %) and Betula ermanii forest ( %). Though the LUE of mixed broad- leaved and korean pine forests were very high, it still had great increasing potential. In conclusion, EPPML could well and truly simulate N PP and total solar radiation of main vegetations at landscape scale in Changbai Mountain Nature Reserve. Therefore, it could well reflect the seasonal dynamic and spatial distribution of LUE. The LUE values simulated from EPPML were mostly in the range of those of Chinese forests. It indicates that we can simulate LUE of natural vegetation at the middle and large scale by model. The study supplies a gap in developing dynamic model for LUE of natural vegetation at the middle and large scale in China. However, because of lack of field survey data about LUE of different vegetation types, only limited validations were carried out in the study. Key words 3S, Light utilization efficiency, Net primary productivity, Total solar radiation, Seasonal dynam2 ics, Spatial distribution, perata) ( Larix gmelinii) ( Ulmus pumila), ( Populus spp. ) ( Pinus koraiensis),, 90 % ( Caragana microphylla ) ( Tamarix chinensis) ( Hippophae rhamnoides) ( Robinia pseuodacacia) ) (,1999), ( LUE) (,, ( 2001) (1999) ) John Monteith LUE,, ( 1 ) LUE (, ( PAR), ;,1985 ;,2001), 1977 LUE (Waring & Running, 1998) LUE,,,, LUE LUE (Waring & Running, 1998),,,,, (,1999) ( GIS) LUE, ( Ecosystem Productivity Process Model at Landscape,Scale, EPPML), LUE LUE,, ( ( Picea as2

3 3 : 3S ,EPPML, 1995, ( E, N, ) ( ), ( LAI ( ) 1981 ) hm 2 (,1988),, 1995, N PP,,, LUE EPPML, (,2003) : ( m) ( ) ( m) ( ( Abies nephrolepis) ( Betula er2 manii) ) (1 800 ;, m) (2 100 m ) (,1999) EPPML ( Photinia serrulata) ) LUE LUE :, L d = N PP d / PAR d (1), (1), L d LUE ( %) ; N PP d ( Larix olgensis) ; (MJ m - 2 d - 1 ) ; PAR d ( Populus davidiana) ( Betu2 (MJ m - 2 d - 1 ) la platyphylla) ; 4 N PP d = N PP day Q 44/ (2) (2), N PP day N PP (kgc m - 2 d - 1 ) ; Q (,1988), 1gCO 2, 1. 2 (TM), C ( N PP) LUE ( LAI) ; (Visual C ++ ) (3), k ( EPPML), (0. 5) ; S d (MJ m - 2 d - 1 ) N PP LUE ; GIS (4), L y LUE ( %) ; N PP y EPPML Century ( Parton et al., 1993) Forest-BGC ( Running & Coughlan, 1988) BIOM-BGC, 30 m, TM, LUE,, MJ g CO 1 2 (,1991) ;44/ 12 CO 2 PAR d = k S d (3) L y = N PP y / PAR y (4) (MJ m - 2 a - 1 ) ; PAR y (MJ m - 2 a - 1 ) (Running & Hunt, 1993) BEPS(Liu et al., 1997) N PP y = N PP Q 44/ (5) (5), N PP N PP(kgC m - 2 a - 1 ), PAR y = k S d (6) EPPML , EPPML,,, C 4, C 4

4 (,1999), C 3 (9) (10) (12) (13), C a CO 2 (Pa),EPPML C a, EPPML (9) (10), K ( ) (Pa), Rubisco CO 2 O 2 CO 2 (,1997 ;,1991) (,1999), EPPML LAI ( EPPML Farquhar (1980) : ), K = K c (1 + O 2 / K o ) (17) (17),O 2 ( Pa) Farquhar 21 %,O ( Farquhar et al., 1980 ; Chen, 1996b) Menten ( Pa), K o Rubisco,, Michaelis-Menten (Pa) K c K o, EPPML, Arrhenius 25, EPPML Collatz (1991) RuBP (1,5- K c K o : ) ( A j ) ( T - T ) K c = K c25 Q 10 Kc b / 10 (18) Rubisco (RuBP /, Ribulose bisphosphate (18), Tb ( 25 ) ; T carboxylase-oxygenase) ( ) ; K c25 25 K c (40. 4Pa) ; Q 10 kc ( A v ) Farquhar, K c (2. 1), 10,Ru2 EPPML bisco 2. 1 : A = min ( Av, Aj) (7) ( T - Tb) / 10 (7), A ( mol m - 2 s - 1 K o = K o25 Q 10 Ko (19) ), Av (19), K Aj, A A sun ; o25 25 K o ( Pa) ;, A Q A shade Av Aj : 10 ko K o (1. 2) (10) (12) g min ) - A = ( g n - g min ) ( a ( g2 n - g 2 min) + c 0. 5 ( g n - (2 ag n + b) d 4 a + (2 ag min + b) c a + 4 ac - b2 8 a 1. 5 ln 2 ag n + b + 2 a 0. 5 d 2 ag min + b + 2 a c 5) (8) (10) (11), V m Rubisco ( mol m - 2 s - 1 ) V m, Arrhe2 (8), g min nius 25, ( mol m - 2 s - 1 Pa - 1 ),, g min 0. 0 N (Chen,1996a) : Av, a = ( K + C a ) 2 (9) b = 2 (2 + K - C a ) V m + 2 ( C a + K) R d (10) c = ( V m - R d ) 2 (11) Aj, a = ( C a ) 2 (12) b = 0. 4 ( C a ) J + 2 ( C a ) R d (13) c = (0. 2 J - R d ) 2 (14) Av Aj, d = ( ag n 2 + bg n + c) 1/ 2 (15) e = ( b 2-4 ac) / (8 ( a) 3/ 2 ) (16) K Rubisco, K c Rubisco Michaelis- (13), CO 2 (Pa), EPPML Collatz (1991) Sell2 ers (1992) : = O ( T - Tb) / 10 (20) ( T - Tb) / V m = V m25 Q act f ( T) f ( N) (21) (21), V m25 25 RuBP ( mol m - 2 s - 1 ), Rubisco ; Q 10act Rubisco (2. 4) ; f ( T) ; f (N) N EPPML Collatz (1991) Bonan (1995) : f ( T) = [1 + exp ( O ( T + 273) ) ] R gas (T + 273) - 1 (22) (22), R gas ( m 3 Pa

5 3 : 3S 329 mol - 1 K - 1 ) A shade ( mol m - 2 s - 1 ) ; EPPML Bonan (1995) N LAI sun LAI (m 2 m - 2 ) ; LAI shade : LAI(m 2 m - 2 ) EPPML Chen (1996b) Chen f ( N) = N/ N m (23) Cihlar(1995) Chen (1997) Norman (1982) (23), N N ( %) ; N m N LAI sun LAI shade : ( %) ( 1) (13) (14), J LAI sun = 2 cos (1 - exp ( LAI/ cos ) ) ( mol m - 2 s - 1 ), EPPML Farquhar (1982) Wullschleger (1993) J : (31) (31), PAR J = J max PPFD/ ( PPFD J max ) (24), (Chen, 1996a ; Liu et (24), J max ( mol al., 1997) LAI LAI (m 2 m - 2 ) m - 2 s - 1 ), J max EPPML Wullschleger (1993) : J max = V m (25) = 1 ;, 1 (24), PPFD ( Photosynthetic BEPS (Liu et al., 1997) ( photon flux density) ( mol m - 2 s - 1 ) 1), PPFD = S sun,day (26) LAI shade = LAI - LAI sun (32), PPFD = S shade,day (27) (26) (27),2. 04 W m - 2 mol m - 2 s - 1, N PP ; S sun,day (W m - 2 ) ; S shade,day, (W m - 2 ) (10) (11) (13) (14), R d ( mol m - 2 s - 1 ), Collatz (1991) : R d = V m (28) g n = 10 6 g s / 1. 6/ ( R gas ( T + 273) ) (29) ( ),, (,1990), N PP day = GPP - R a = GPP - R m - R g - R p (33) (15), g n ( mol m - 2 s - 1 Pa - 1 ), (33), N PP day N PP (kgc m - 2 d - 1 ) ; GPP m s - 1 mol m - 2 s - 1 (kgc m - 2 d - 1 ) ; R a Pa - 1 : (kgc m - 2 d - 1 ) ; R m (kgc m - 2 d - 1 ) ; R g (kgc m - 2 d - 1 ) ; R p (29),1. 6 H 2 O CO 2 (kgc m - 2 d - 1 ),, EPPML ( ) g s (m s - 1 ), EPPML GPP = A canopy DAYL (34) Jarvis Morison(1981) (34) A canopy ( mol m - 2 s - 1 ) GPP (kgc m - 2, d - 1 ) DAYL (s),12. 01, (g mol - 1 ) (Waring & Running, 1998), R m = R m, i = R m, s + R m, b + R m, r + R m, l = ( T - Tb) / ( M i r m, i Q ) (35) CO 2 (,2003) (35), i, l b s r : A canopy = A sun LAI sun + A shade ; M i ( LAI shade (30) ) (kgc m - 2 ) ; r m, i i (30), A canopy ( mol (kgc d - 1 kg - 1 ) ( 1) ; Q 10 m - 2 s - 1 ),,, 5 CO , (Liu et ; A sun ( mol m - 2 s - 1 ) ; al., 1997 ; Running & Coughlan, 1988)

6 Parameter Alpine Alpine tundra grasses r m, l (20 ) r m, b (20 ) r m, s (20 ) r m, r (20 ) N m EPPML Table 1 Biological parameters for different vegetation types in EPPML Betula Broadleaved Meadows ermanii forests forests Mixed Picea asperata and Abies nephrolepis forests Mixed broadleaved and Pinus koraiensis forests Larix olgensis forests Shrubs Reference 1 1, 2, 3, 4 1, 2, 3, 4 1, 2, 3, 4 1, 2, 3, Liu et al. (1997) 2. Chen et al. (1999) 3. Liu et al. (1999) 4. Running & Coughlan (1988) 5. Waring & Running (1998) 6. (1995) Xu G. S. et al. (1995) R g, (39), rad (W m - 2 ) ; sraddir (W m - 2 ) ; srad- dif,, R g GPP ( 1), i R g, i R g r i : R g = GPP (36) R g, i = r i R g (37) N PP : N PP = N PP day (38) (40) (41), slope-potrad (W m - 2 ) ; flat-potrad Forest-BGC (W m - 2 ) ; t-final ; pdir MT-Clim, ; pdif MT-Clim ; sky-prop, ; DIF-ALB (dif2, fuse albedo for horizon correction) (0. 6) 3 :1) Garnier Ohmura, rad W m - 2 MJ m - 2 (1968) d - 1, ( S d = rad DAYL/ (42) ) 2) Bristow Campbell (1984) 2, :, ( ) 2. 1, (1981), 1, N PP, / ( R 2 = 0. 74, n = 13) ,, 1 km, N PP, 3) %, % (Waring & Running, 1998),,, EPPML rad = srad- dir + srad- dif + snowc (39) (W m - 2 ) ; snowc (W m - 2 ) srad- dir = slope-potrad t-final pdir (40) srad- dif = flat-potrad t-final pdif ( sky-prop + DIF-ALB ( sky-prop) ) (41) N PP

7 3 : 3S 331 ; N PP ; EPPML 1995 N PP MJ m - 2,, 0. 5 % ; N PP ( MJ m - 2 ) MJ m - 2, 4. ; N PP 34 %,7 (1981), 90 MJ m - 2, 19 % ; 5, ; 0, 19 %, (1995), kgc m - 2 a - 1 EPPML, N PP ; 7 1, kgc m - 2 a - 1, kgc m - 2 a - 1 ; kgc m - 2 a - 1,,,,,EPPML N PP (1993), MJ 1 NPP Fig. 1 Comparison of measured and modeled annual NPP for main ( %) vegetation types in Changbai Mountain NPP : Net primary productivity, (1995), 7 m - 2, MJ m - 2, 2. 9 % 0. 7 %( 2) EPPML,,,,,,, EPPML, 2. 3 (1995) (5 9 ) LUE 5. 4 %, % ; LUE 2. 8 %, ( %) ( 3) %, 2. 2 LUE, 1995 (1985) MJ m - 2, 4, % MJ m - 2, LUE %( ),, MJ m - 2 (,1995), LUE( %),, LUE,, ( m) 0. 5 % (,,1986), LUE

8 %, 0. 5 % 1. 5 % (,, 1993) ;, LUE, 5 % (,2001) EPPML LUE,), 28 LUE %, (, 3,, LUE ;, LUE 2 (1995 ) (MJ m - 2 ) Table 2 Comparison of measured and modeled total solar radiation in Changbai Mountain Station (1995) (MJ m - 2 ) Item Measured value 1 Jan. 2 Feb. 3 Mar. 4 Apr. 5 May 6 Jan. 7 Jul. 8 Aug. 9 Sep. 10 Oct. 11 Nov. 12 Dec. Total Modeled value 1) Absolute error ( %) Relative error Modeled value 2) Absolute error ( %) Relative error 1) EPPML MT-Clim Represents modeled value using the method from MT-Clim in EPPML 2) (1993) Represents modeled value using the method from Zuo D. K. (1993) Vegetation type Mixed broad-leaved and Pinus koraiensis forests 3 (1995) Table 3 Annual light utilization efficiency for main vegetations (1995) Modeled Measured value ( %) value ( %) Absolute Relative Place and characteristic of field stands error ( %) error ( %) Artificial Pinus koraiensis trees in Maoer Mountain in Hei2 longjiang province 1) Larix olgensis forests Artificial Xing an larch ( Larix gmelinii) trees in Maoer Moun tain in Heilongjiang province 2) Artificial Larix gmelinii trees in Huangjia Ercha Watershed 3) Mixed Picea asperata and Abies nephrolepis forests Artificial Picea asperata trees in Huangjia Ercha Watershed 3) Total ,1. 0 1),4),5) General forests in China 1) (1993) From Zhang Y. D. et al. (1993) 2) (1990) From Liu S. R. et al. (1990) 3) (1999) From Li Z. K. (1999) 4) (2001) From Wu J. M. (2001) 5) (1986) From He Q. T. et al. (1986)

9 3 : 3S 333,,, ; 7, LUE, ( %), 2 % 3 % ;, ( %) ; : ( %), ( %) ( %) LUE N PP, ( 2), N PP, kgc m - 2 d kgc m - 2 d LUE N PP ( kgc m - 2 d - 1 ),,4 5 LUE 7 (488.,7 (2. 9 %), % %( %),9 10,12, N PP ( %) (2 4 ) (5 7 ) (8 10 ) (11 1 ) 4 LUE LUE % % % % ( 4), % % ( %) % % ( %) % % ( %) % % ( %),, ( %) ( %), 3. 0 % ; % ; ( %) 7 LUE 656 MJ m - 2 ), LUE, ( kgc m - 2 d - 1 ), 7 ( MJ m - 2 ), LUE,,, LUE :, LUE, N PP :, LUE %, 2 Fig. 2 Seasonal dynamics of light utilization efficiency ( LUE) for different vegetation types in Changbai Mountain The lines representing error in the Fig. 2 mean standard deviation

10 ;,, N PP, N PP,LUE N PP LUE % 3. 2 ( R 2 = ) % %, %( 4) LUE 3 : 1. ( %) ;, 849 % %, ; ; % %, ( R 2 = ), LUE LAI LUE - LUE ( %), 0. 0 % %, % %, ; LUE 0. 9 %, % ( 79. LUE % % 36 %) ( %), LUE ( %), LUE : % %( 4) 4 ( %) Table 4 Seasonal and annual light utilization efficiency for different vegetation types in Changbai Mountain Nature Reserve ( %) Vegetation type Alpine grasses Alpine tundra Betula ermanii forests Mixed Picea asperata and Abies nephrolepis forests Mixed broad-leaved and Pinus koraiensis forest Broad-leaved forests Larix olgensis forests Meadows Shrubs (2 4 ) Spring (Feb. 2Apr. ) Light utilization efficiency ( LUE) (5 7 ) Summer (May2Jul. ) (8 10 ) Autumn (Aug. 2Oct. ) (1121 ) Winter (Nov. 2Jan. ) Annual mean Total ,,,,,,, LUE (,1999),,, LUE,,,,,,,, LUE 4,,,LUE (Waring & 1) EPPML Running, 1998), N PP,,, LUE 2 3

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