Climate dependent variations in leaf respiration

叶子呼吸的气候依赖性变化

• 批准号: NE/D012856/1
• 负责人: Owen Atkin
• 金额: $ 10.92万
• 依托单位: University of Leeds
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2006
• 资助国家: 英国
• 起止时间: 2006 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FD012856%2F1
• 关键词: Climate; dependent; variations; leaf; respiration

Plants play a vital role in regulating the concentration of atmospheric carbon dioxide (CO2, an important greenhouse gas). Critical in determining atmospheric CO2 concentrations and magnitude of global warming is the rate of respiration exhibited by plants; globally, near 60 Gt C per year is released into the atmosphere by plant respiration. This is a large flux compared with the relatively small release of CO2 from the combustion of fossil fuels (< 6 Gt C per year). To predict future atmospheric CO2 concentrations and global surface temperatures, we need to accurately model how plant respiration responds to climate. At present, most climate models assume that plant respiration responds to climate in a simplistic, predictable manner. For example, respiration is assumed to double in rate for every 10oC rise in temperature. Moreover, rates of leaf respiration are assumed to be the same in the light as in darkness, when measured at the same temperature. There is, however, growing evidence that neither assumption is correct. For example, we know that the temperature response of respiration is highly dynamic and adjusts to long-term changes in temperature (i.e. respiration 'acclimates'). Moreover, we know that light inhibits leaf respiration, particularly at high daytime temperatures. Failure to account for such dynamic responses of respiration results in large errors in predicted rates of net ecosystem C exchange; such errors are likely particularly important in low productivity ecosystems where plant respiration represents a large proportion of overall C exchange. It is vital, therefore, that such dynamic variations in respiration be accounted for in ecosystem gas exchange models predicting the impacts of future climate change on the biosphere. To do this, we need to first carefully quantify how plant respiration responds to variations in climate (both in darkness and in the light). This data can then be used to develop mathematical equations that allow the effects of variations in plant respiration to be incorporated into C exchange models that accurately predict current and future rates of plant C exchange, both in individual ecosystems and globally. Our research will focus on the effects of climate on leaf gas exchange of three low productivity forest ecosystems that are globally widespread (Mediterranean dryland, boreal evergreen conifer and boreal deciduous conifer forests), often experience high day-time leaf temperatures during the summer and operate close to the threshold of positive growth; minor changes in leaf respiration can result in such forests switching from net absorbers of atmospheric C to net emitters of C. At present, our understanding of how climate dependent variations in leaf respiration impact on rates of net CO2 exchange of low productivity forests is limited. In particular, the role light inhibition of leaf respiration in determining rates net CO2 exchange on hot summer days is unknown. Our research will quantify the importance of variations in leaf respiration due to seasonal acclimation and inhibition in the light on overall plant carbon balances of trees growing in these low productivity ecosystems. Thus, in addition to providing the data necessary for improving the predictive power of climate models, our research will establish for the first time the quantitative importance of leaf respiration in determining the C economy, and thus growth, of these globally widespread low productivity ecosystems. Because the knowledge obtained will be based on general principles, we will also be able to apply the findings to other ecosystems where leaf respiration potentially represents an important determinant of net ecosystem CO2 exchange (e.g. light-limited under-storey plants in tropical forests). In such environments, small changes in whole plant carbon balances may have important consequences for seedling growth and survival.

植物在调节大气二氧化碳（CO2，一种重要的温室气体）浓度方面发挥着至关重要的作用。确定大气二氧化碳浓度和全球变暖程度的关键是植物的呼吸速率；在全球范围内，每年有近 60 Gt C 通过植物呼吸释放到大气中。与化石燃料燃烧释放的二氧化碳相对较少（每年 < 6 Gt C）相比，这是一个很大的通量。为了预测未来大气二氧化碳浓度和全球表面温度，我们需要准确模拟植物呼吸对气候的反应。目前，大多数气候模型都假设植物呼吸以一种简单化、可预测的方式对气候做出反应。例如，假设温度每升高 10°C，呼吸速率就会增加一倍。此外，在相同温度下测量时，假定叶片呼吸速率在光照下和黑暗中相同。然而，越来越多的证据表明这两种假设都不正确。例如，我们知道呼吸的温度响应是高度动态的，并且会根据温度的长期变化进行调整（即呼吸“适应”）。此外，我们知道光会抑制叶子呼吸，特别是在白天高温下。未能考虑呼吸的这种动态响应会导致生态系统净碳交换率的预测出现巨大误差；在低生产力生态系统中，此类错误可能尤其重要，因为植物呼吸在整个碳交换中占很大比例。因此，在预测未来气候变化对生物圈影响的生态系统气体交换模型中考虑呼吸的这种动态变化至关重要。为此，我们首先需要仔细量化植物呼吸如何响应气候变化（在黑暗和光照下）。然后，这些数据可用于开发数学方程，将植物呼吸变化的影响纳入碳交换模型中，从而准确预测单个生态系统和全球范围内植物碳交换的当前和未来速率。我们的研究将重点关注气候对全球广泛分布的三种低生产力森林生态系统（地中海旱地、北方常绿针叶林和北方落叶针叶林）叶子气体交换的影响，这些生态系统在夏季通常会经历较高的白天叶子温度，并接近正生长的阈值；叶子呼吸的微小变化可能导致这些森林从大气碳的净吸收者转变为碳的净排放者。目前，我们对叶子呼吸的气候依赖性变化如何影响低生产力森林的二氧化碳净交换率的理解有限。特别是，光抑制叶片呼吸在确定炎热夏季净二氧化碳交换率中的作用尚不清楚。我们的研究将根据这些低生产力生态系统中生长的树木的整体植物碳平衡，量化由于季节性适应和抑制而导致的叶子呼吸变化的重要性。因此，除了提供提高气候模型预测能力所需的数据外，我们的研究还将首次确定叶片呼吸在确定碳经济以及这些全球普遍存在的低生产力生态系统的增长方面的定量重要性。由于获得的知识将基于一般原则，因此我们还能够将研究结果应用于其他生态系统，在这些生态系统中，叶子呼吸可能是净生态系统二氧化碳交换的重要决定因素（例如热带森林中光受限的地下植物）。在这种环境中，整个植物碳平衡的微小变化可能会对幼苗的生长和生存产生重要影响。