森林生态系统碳循环的基本概念和野外测定方法评述

全球气候变化与森林生态系统碳循环息息相关,定量评估森林碳收支是生态系统与全球变化研究的重要任务。30年来森林生态系统碳循环研究已经取得了长足的进展,但全球和区域森林碳收支仍然存在很大的不确定性。这一方面与森林生态系统本身的复杂性有关,另一方面也与具体研究方法有关。评述了森林生态系统碳循环的基本概念和主要野外测定方法,为我国森林生态系统碳循环研究提供可参考的方法论。从生态系统碳浓度、密度、通量、分配和周转5个方面回顾了碳循环相关概念,指出碳浓度和碳储量是对碳库的静态描述,而碳通量和碳周转是对碳库的动态描述。净初级生产力是测量最普遍的碳通量组分,但大多数情况下因忽略了一些细节而被系统低估。普遍使用的净生态系统生产力,由于没有包含非CO2形式的水文、气象和干扰过程产生的碳通量,通常情况下高于生态系统净碳累积速率。在详细介绍碳通量组分的基础上,改进了森林生态系统碳循环的概念模型。重点讨论了碳通量的3种地面实测方法:测树学方法、箱法和涡度协方差法,并指出了其注意事项和不确定性来源。针对当前碳循环研究的突出问题,建议从4个方面减小碳循环测定的不确定性:(1)恰当运用生物量方程估算乔木生物量;(2)尽可能全面测定生态系统碳组分;(3)给出碳通量估算值的不确定性;(4)多种途径交互验证。

Fundamental concepts and field measurement methods of carbon cycling in forest ecosystems: a review

Global climate change is closely linked with forest ecosystem carbon (C) cycling. Quantitative assessment of forest C budgets is of importance in ecosystem and global change sciences. Studies on forest ecosystem C cycling have been advanced considerably during the past 30 years, but there are still large uncertainties in the C budgets at both global and regional scales. These uncertainties can be attributed not only to the complexity of forest ecosystems but also to the methodology applied. In this paper, we reviewed the fundamental concepts and major field measurement methods of C cycling in forest ecosystems. First, we the concepts of concentration, density, flux, allocation and turnover. Carbon concentration and stock are static attributes of the C cycling, while C flux and turnover are dynamic ones. In meteorology, CO₂ concentration can be expressed in three ways: mass/molar density, molar fraction to the moist air, and mass/molar fraction to the dry air, among which the dry molar fraction is the most convenient and conservative. In ecology, the C concentrations in biomass, necromass and soil are mostly expressed as mass fraction to the dry weight. Carbon density is defined as the C stock per unit forest area. Carbon flux is the mass flow per unit time through unit forest area (or particular organ of an individual tree). Carbon allocation pertains to standing biomass distribution, the absolute and relative partitioning of gross primary production to C flux components. Net primary production, the most frequently investigated C flux, is often underestimated due to missing components. Net ecosystem production is often higher than the net C accumulation rate of the ecosystem. After clarifying the related concepts and terminologies, we modified the conceptual framework of forest C cycling. In the second part, we discussed field measurement methods of forest C cycling, focusing on principles, pros and cons, and potential uncertainties in measuring forest C fluxes with biometry (or inventory), chamber and eddy covariance methods. The biometry method is the most widely-used method for measuring forest C pools particularly for aboveground biomass, which requires little equipment or technology but long-term commitment, and lacks of fine temporal resolutions. The chamber method (e.g. ecophysiological approach) often focuses on specific ecological processes such as photosynthesis and respiration, which provides process-based parameters for forest C cycling modeling with fine temporal resolutions, but needs sophisticated expensive instrumentation and is difficult to up scale. The eddy covariance method directly measures C and water vapor between forest canopy and the atmosphere at ecosystem level. It provides continuous automated measurements with high frequency and reduces potential human errors, but it required expensive instrumentation and sophisticated data-processing and is limited by spatially-representative sampling locations. In the last part of this paper, we recommend four ways to reduce uncertainties in forest C accounting: (1) Appropriately use biomass allometric models to estimate tree biomass and its increment; (2) measure all C flux components in the forest ecosystem, or at least report the missing components; (3) estimate the uncertainty of C fluxes rather than only report the mean value of estimation; and (4) cross-validate the C fluxes with independent methods.