Seasonal dynamics in leaf area index in three typical temperate montane forests of China: a comparison of multi-observation methods

doi:10.3724/SP.J.1258.2012.00231

Abstract

Abstract:

Aims Leaf area index (LAI) is one of the most frequently used parameters for analysis of canopy structure and forest productivity. It can be determined by direct or indirect methods. Sources of errors in indirect LAI measurements with optical instruments include non-photosynthetic components, element clumping, and a topography effect. Our objective was to find an appropriate method for evaluating LAI and its seasonal dynamics in typical temperate montane forest.
Methods We examined the applicability of three indirect methods (LAI-2000 plant canopy analyzer, CI-110 plant canopy analyzer and digital hemispherical photograph (DHP)) and one direct method (litterfall) to determine the seasonal dynamics of LAI in three typical temperate forests in Dongling Mountain of Beijing. The forests included a secondary deciduous broad-leaved forest dominated by Quercus mongolica and two plantations (Larix gmelinii var. principis-rupprechtii and Pinus tabuliformis). These represent deciduous broad-leaved forest, deciduous needle-leaved forest and evergreen needle-leaved forest, respectively. The optically-based effective leaf area index (LAI_e) values were corrected to eliminate wood elements and clumping effects and then compared with the direct measurement of LAI based on litter collection.
Important findings For all the three forests, the LAI seasonal dynamic shows a uni-modal pattern with a peak in July. Optically-based LAI_e underestimated the amplitude of the seasonal dynamics. Wood element elimination can strengthen the seasonal sensitivity of LAI, especially in the seasonally distinct deciduous forest. The order of LAI_e measured by the three optically-based methods in three stands is LAI-2000 plant canopy analyzer > DHP > CI-110 plant canopy analyzer. There was good correspondence with the direct measurement LAI for the corrected LAI of LAI-2000 plant canopy analyzer and DHP. The correction method based on gap-size distribution was appropriate for the LAI-2000 plant canopy analyzer and the method based on both gap fraction and gap-size distribution for DHP. Considering economics and practical convenience, we recommend DHP for LAI evaluation in these temperate montane forests.

Key words: clumping effects, effective leaf area index, optically-based methods

SU Hong-Xin, BAI Fan, LI Guang-Qi. Seasonal dynamics in leaf area index in three typical temperate montane forests of China: a comparison of multi-observation methods[J]. Chin J Plant Ecol, 2012, 36(3): 231-242.

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URL: https://www.plant-ecology.com/EN/10.3724/SP.J.1258.2012.00231

https://www.plant-ecology.com/EN/Y2012/V36/I3/231

Figures/Tables 9

Fig. 1 Mean monthly air temperatures and monthly precipitation (mean ± SD) during 1993 to 2010 from the meteorological station (39°58′ N, 115°26′ E, 1 150 m a.s.l.) adjacent to study site.

Table 1 Basic information of three permanent sample plots

森林类型 Forest type	海拔 Altitude (m)	坡向 Slope aspect	坡度 Slope	乔木密度¹⁾ Tree density¹⁾ (ind.·hm^-2)	胸断面积 Area at breast height (m²)	树高(平均值± 标准偏差) Tree hight (mean ± SD) (m)	主要乔木树种 Main tree species
落叶阔叶林 DBH	1 200	28°	35° NW	2 333	23.41	7.9 ± 1.4	蒙古栎 Quercus mongolica 黑桦 Betula dahurica 五角枫 Acer pictum subsp. mono
落叶针叶林 DNF	1 200	26°	40° NW	3 294	24.51	10.4 ± 1.1	华北落叶松 Larix gmelinii var. principis-rupprechtii
常绿针叶林 ENF	1 150	30°	60° NE	1 333	25.16	10.9 ± 0.3	油松 Pinus tabuliformis

Table 2 Specific leaf area (SLA, cm2 ·g-1) for main tree species

树种 Tree species	比叶面积 Specific leaf area (SLA)
树种 Tree species	平均值±标准偏差 Mean ± SD	最小值 Minimum	最大值 Maximum
蒙古栎 Quercus mongolica	125.65 ± 21.86	94.98	143.89
黑桦 Betula dahurica	164.12 ± 17.73	149.60	194.55
五角枫 Acer pictum subsp. mono	204.98 ± 22.67	175.48	239.25
白桦 Betula platyphylla	163.23 ± 11.83	151.33	177.25
糠椴 Tilia mandshurica	197.20 ± 24.16	175.15	234.68
黄花柳 Salix caprea	177.27 ± 8.66	166.79	189.41
北京花楸 Sorbus discolor	209.77 ± 45.76	138.85	249.46
青杨 Populus cathayana	200.40 ± 20.07	165.61	215.14
胡桃楸 Juglans mandshurica	158.25 ± 21.51	131.84	182.76
花曲柳 Fraxinus chinensis subsp. rhynchophylla	203.52 ± 29.37	174.36	244.55
蒿柳 Salix schwerinii	135.01 ± 14.11	120.44	156.46
大果榆 Ulmus macrocarpa	197.48 ± 38.30	134.71	237.68
裂叶榆 Ulmus laciniata	221.15 ± 22.56	187.21	248.75
其他阔叶树 Other broad-leaved species	181.39 ± 36.68	94.98	249.46

Fig. 2 Seasonal dynamics of canopy element clumping index based on digital hemispherical photograph. A, deciduous broad-leaved forest. B, deciduous needle-leaved forest. C, evergreen needle-leaved forest. CC, canopy element clumping index based on gap size; CLX, canopy element clumping index based on both gap fraction and gap size distribution; LX, canopy element clumping index based on gap fraction.

Fig. 3 Seasonal dynamics of effective leaf area index (LAIe) measured by three kinds of instruments (mean ± SD). A, deciduous broad-leaved forest. B, deciduous needle-leaved forest. C, evergreen needle-leaved forest. CI-110, CI-110 plant canopy analyzer. DHP, digital hemispherical photograph. LAI- 2000, LAI-2000 plant canopy analyzer.

Fig. 4 Seasonal dynamics of leaf area index (LAI) (mean ± SD). A, deciduous broad-leaved forest. B, deciduous needle-leaved forest. C, evergreen needle-leaved forest. 1, CI-110 plant canopy analyzer. 2, digital hemispherical photograph. 3, LAI-2000 plant canopy analyzer. CC, LAI by correction method based on the gap size clumping index; CLX, LAI by correction method both based on the gap fraction and gap size distribution clumping index; Col, LAI by direct measurement based on litter collection; LX, LAI by correction method based on the gap fraction clumping index.

Table 3 Variance analysis of effective leaf area index (LAIe) and leaf area index (LAI)

林型 Forest type	月份 Month	LAI_Col	CI-110冠层分析仪 CI-110 plant canopy analyzer				半球摄影法 Digital hemispherical photograph				LAI-2000冠层分析仪 LAI-2000 plant canopy analyzer
林型 Forest type	月份 Month	LAI_Col	LAI_e	LAI_CC	LAI_LX	LAI_CLX	LAI_e	LAI_CC	LAI_LX	LAI_CLX	LAI_e	LAI_CC	LAI_LX	LAI_CLX
落叶阔叶林 Deciduous broad- leaved forest	MJ	-	***	***	*	***	*	***	*	***	*	***	*	***
落叶阔叶林 Deciduous broad- leaved forest	JO	***	N	N	*	*	N	N	*	*	N	***	*	*
落叶针叶林 Deciduous needle- leaved forest	MJ	-	*	*	***	*	***	*	***	*	***	*	***	*
落叶针叶林 Deciduous needle- leaved forest	JO	***	*	*	***	*	***	*	***	*	*	*	***	*
常绿针叶林 Evergreen needle- leaved forest	MJ	-	*	*	*	*	N	*	*	N	*	*	*	N
常绿针叶林 Evergreen needle- leaved forest	JO	***	N	N	***	*	*	N	*	*	*	N	*	*

Fig. 5 Comparison of effective leaf area index (LAIe) and reconstructed LAI by direct measurement based on litter collection (LAICol) (mean ± SD). A, Deciduous broad-leaved forest. B, Deciduous needle-leaved forest. C, Evergreen needle-leaved forest. CI-110, CI-110 plant canopy analyzer; DHP, digital hemispherical photograph; LAI-2000, LAI-2000 plant canopy analyzer.

Fig. 6 Comparison of leaf area indexes (LAI) between by optical instruments and reconstruction based on litter collection (LAICol) (mean ± SD). A, Deciduous broad-leaved forest. B, Deciduous needle-leaved forest. C, Evergreen needle-leaved forest. 1, CI-110 plant canopy analyzer. 2, Digital hemispherical photograph (DHP). 3, LAI-2000 plant canopy analyzer. CC, LAI by correction method based on the gap size clumping index; CLX, LAI by correction method both based on the gap fraction and gap size distribution; LX, LAI by correction method based on the gap fraction clumping effect index.

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