中国森林生态系统土壤呼吸温度敏感性空间变异特征及影响因素

土壤呼吸的温度敏感性(Q₁₀)是陆地碳循环与气候系统间相互作用的关键参数。尽管已有大量关于不同类型森林Q₁₀季节和年际变化规律的研究, 但是对Q₁₀在区域尺度的空间变异特征及其影响因素仍认识不足, 已有结果缺乏一致结论。该研究通过整合已发表论文, 构建了中国森林生态系统年尺度Q₁₀数据集, 共包含399条记录、5种森林类型(落叶阔叶林(DBF)、落叶针叶林(DNF)、常绿阔叶林(EBF)、常绿针叶林(ENF)、混交林(MF))。分析了不同森林类型Q₁₀的空间变异特征及其与地理、气候和土壤因素的关系。结果显示, 1) Q₁₀介于1.09到6.24之间, 平均值(±标准误差)为2.37 (± 0.04), 且在不同森林类型之间无显著差异; 2)当考虑所有森林类型时, Q₁₀随纬度、海拔、土壤有机碳含量(SOC)和土壤全氮含量(TN)的增加而增大, 随经度、年平均气温(MAT)、平均年降水量(MAP)的增加而减小。气候(MAT、MAP)和土壤(SOC、TN)因素间存在相互作用, 共同解释了33%的Q₁₀空间变异, 其中MAT和SOC是Q₁₀空间变异的主要驱动因素; 3)不同类型森林Q₁₀对气候和土壤因素的响应存在差异。在DNF中Q₁₀随MAP的增加而减小, 而其他类型森林中Q₁₀与MAP无显著相关性; 在EBF、DBF、ENF中Q₁₀随TN的增加而增大, 但Q₁₀对TN的敏感性在EBF中最高, 在ENF中最低。这些结果表明, 尽管Q₁₀有一定的集中分布趋势, 但仍有较大范围的空间变异, 在进行碳收支估算时应注意尺度问题。Q₁₀的主要驱动因素和Q₁₀对环境因素的响应随森林类型而变化, 在气候变化情景下, 不同森林类型间Q₁₀可能发生分异。因此, 未来的碳循环-气候模型还应考虑不同类型森林碳循环关键参数对气候变化的响应差异。     

High-altitude tree growth responses to climate change across the Hindu Kush Himalaya

兴都库什喜马拉雅地区高海拔树木生长对气候变化的响应 高海拔地区快速升温可能导致树木对温度响应更为敏感,而限制高海拔地区树木生长的关键气候因子以及气候变化对树木生长产生多大程度的影响尚不清楚。本研究在兴都库什喜马拉雅地区收集了73 个样点的树轮数据,包括3个优势属的树种(Abies属、Juniperus属和Picea属),样点海拔均在3000 m以上。 将时间动态规整(dynamic time warping)的方法用于建立亚区域年表,以考虑不同站点年表之间变化的同步 性。同时,定量分析了气候因子对树木生长的贡献以及树木生长与气候因子关系的时空动态。研究结果发现,73个站点年表可以聚为3类,且与其所处的生物气候区相对应,即西喜马拉雅地区,中东喜马拉雅地区和藏东南地区。在干旱的西喜马拉雅地区,树木生长与冬、春两季的降水呈正相关关系,而在湿润的藏东南地区,树木生长与冬季温度和春季降水呈正相关关系。树木生长受最低温度的影响最大,特别是冬季温度,其重要性从西到东呈现递增趋势。滑动窗口相关分析表明,在中西喜马拉雅地区,影响树木生长的冬季温度信号在减弱,然而在藏东南地区该信号随着1980年以来的快速升温而增强。本研究结果表明,若该地区升温持续,在西喜马拉雅地区可能会因变暖引起的水分亏缺而造成森林衰退,而在藏东南地区因树木生长得益于变暖而使得森林扩张。     

Modeling vegetation greenness and its climate sensitivity with deep‐learning technology

Climate sensitivity of vegetation has long been explored using statistical or process‐based models. However, great uncertainties still remain due to the methodologies’ deficiency in capturing the complex interactions between climate and vegetation. Here, we developed global gridded climate–vegetation models based on long short‐term memory (LSTM) network, which is a powerful deep‐learning algorithm for long‐time series modeling, to achieve accurate vegetation monitoring and investigate the complex relationship between climate and vegetation. We selected the normalized difference vegetation index (NDVI) that represents vegetation greenness as model outputs. The climate data (monthly temperature and precipitation) were used as inputs. We trained the networks with data from 1982 to 2003, and the data from 2004 to 2015 were used to validate the models. Error analysis and sensitivity analysis were performed to assess the model errors and investigate the sensitivity of global vegetation to climate change. Results show that models based on deep learning are very effective in simulating and predicting the vegetation greenness dynamics. For models training, the root mean square error (RMSE) is <0.01. Model validation also assure the accuracy of our models. Furthermore, sensitivity analysis of models revealed a spatial pattern of global vegetation to climate, which provides us a new way to investigate the climate sensitivity of vegetation. Our study suggests that it is a good way to integrate deep‐learning method to monitor the vegetation change under global change. In the future, we can explore more complex climatic and ecological systems with deep learning and coupling with certain physical process to better understand the nature.     

Reply to Manger’s Commentary on “A quantitative test of the thermogenesis hypothesis of cetacean brain evolution,using phylogenetic comparative methods”

In his Commentary (Manger PR. 2009. Subglacial cetaceans and other mathematical mysteries: a Commentary on “A quantitative test of the thermogenesis hypothesis of cetacean brain evolution, using phylogenetic comparative methods” by C. Maximino. Mar Fresh Behav Physiol. 42: 359–362) on my paper (Maximino C. 2009. A quantitative test of the thermogenesis hypothesis of cetacean brain evolution, using phylogenetic comparative methods. Mar Freshwater Behav Physiol. 42:1–17), Dr Paul Manger noted four errors in the quantitative analysis of the relationship between cetacean encephalization quotients (EQs) and water temperatures, which I suggested was a test of his thermogenesis hypothesis (Manger PR. 2006 Manger, PR. 2006. An examination of cetacean brain structure with a novel hypothesis correlating thermogenesis to the evolution of a big brain. Biol Rev Camb Philos Soc, 81: 293–338.  [Google Scholar]. An examination of cetacean brain structure with a novel hypothesis correlating thermogenesis to the evolution of a big brain. Biol Rev Camb Philos Soc. 81:293–338). These referred to incorrect raw data on water temperatures for two species, odd use of midpoint temperatures as independent variable, lack of inclusion of data on Mysticeti and the use of a differently derived EQ and midpoints instead of the EQs proposed by Manger and temperature ranges; Dr Manger proposed that these errors invalidate the analysis, with special emphasis in an observation that, since my paper did not address the relationship between EQs and temperature range, it did not actually test the thermogenesis hypothesis. In this Reply, I apologize for the mistakes which were made, and show that re-analysis using all the proposed alterations do not qualitatively or quantitatively alter the final result. I also argue that the relationship between phylogenetically correct EQs and midpoint temperatures is a better test of the thermogenesis hypothesis than the relationship between non-phylogenetic EQs and temperature ranges.     

Surface EMG-force modelling for the biceps brachii and its experimental evaluation during isometric isotonic contractions

The aim of this study was to evaluate a surface electromyography (sEMG) signal and force model for the biceps brachii muscle during isotonic isometric contractions for an experimental set-up as well as for a simulation. The proposed model includes a new rate coding scheme and a new analytical formulation of the muscle force generation. The proposed rate coding scheme supposes varying minimum and peak firing frequencies according to motor unit (MU) type (I or II). Practically, the proposed analytical mechanogram allows us to tune the force contribution of each active MU according to its type and instantaneous firing rate. A subsequent sensitivity analysis using a Monte Carlo simulation allows deducing optimised input parameter ranges that guarantee a realistic behaviour of the proposed model according to two existing criteria and an additional one. In fact, this proposed new criterion evaluates the force generation efficiency according to neural intent. Experiments and simulations, at varying force levels and using the optimised parameter ranges, were performed to evaluate the proposed model. As a result, our study showed that the proposed sEMG–force modelling can emulate the biceps brachii behaviour during isotonic isometric contractions.     

Static magnetic field effect on microcirculation,direct versus baroreflex-mediated approach

We compared in conscious rabbits, sedated using pentobarbital intravenous (i.v.) infusion (5 mg kg^{? 1} h^{? 1}), the effect of a static magnetic field (SMF), generated by Nd₂–Fe₁₄–B magnets, on microcirculation during its 40 min local exposure to the microvascular network in cutaneous tissue [20 sham exposure and 20 SMF (0.25 T) exposure runs] or to sinocarotid baroreceptors [14 sham exposure and 14 SMF (0.35 T) exposure runs]. Mean femoral artery blood pressure (BP), heart rate (HR), arterial baroreflex sensitivity (BRS), assessed from HR and BP responses to i.v. bolus of nitroprusside and phenylephrine, and microcirculatory blood flow, using microphotoelectric plethysmography (MPPG), were simultaneously monitored. SMF significantly increased microcirculation on a 17.8% in microvascular and on a 23.3% in baroreceptor exposure series. In baroreceptor exposure series, SMF significantly decreased BP, increased heart rate variability, BRS and sodium nitroprusside (NO-donor) i.v. bolus microcirculatory vasodilatory effect. These suggest augmentation of the arterial baroreflex capacity support NO-dependent vasodilation, by increased sensitivity of vessels to NO, to be a new physiological mechanism of BP buffering and microcirculatory control. A significant positive correlation was also found between increase in BRS and in MPPG (r = 0.66, p < 0.009), indicating baroreflex participation in the regulation of the microcirculation and its enhancement after SMF exposure. Both direct and baroreflex-mediated approaches demonstrate SMF significant vasodilatory effect with potential clinical implication in macro- and microcirculatory disorders.     

Minimal Erythema Dose (MED) Testing

Ultraviolet radiation (UV) therapy is sometimes used as a treatment for various common skin conditions, including psoriasis, acne, and eczema. The dosage of UV light is prescribed according to an individual''s skin sensitivity. Thus, to establish the proper dosage of UV light to administer to a patient, the patient is sometimes screened to determine a minimal erythema dose (MED), which is the amount of UV radiation that will produce minimal erythema (sunburn or redness caused by engorgement of capillaries) of an individual''s skin within a few hours following exposure. This article describes how to conduct minimal erythema dose (MED) testing. There is currently no easy way to determine an appropriate UV dose for clinical or research purposes without conducting formal MED testing, requiring observation hours after testing, or informal trial and error testing with the risks of under- or over-dosing. However, some alternative methods are discussed.