基于数字相机的冬小麦物候和碳交换监测

利用数字相机自动、连续监测植被冠层物候变化,逐渐引起人们的广泛关注。依托中国陆地生态系统通量观测研究网络(ChinaFLUX),探讨了数字相机在监测冬小麦生长状况及生态系统碳交换方面的作用,得到如下结果:(1)利用数字相机图像提取的比值绿度指数G/R能较好地反映冬小麦冠层物候变化,通过分析比值绿度指数G/R的时间序列,得到了较为准确的冬小麦关键生育日期(与人工观测数据比较,误差<3 d),表明数字相机可以作为物候监测的一种有效手段;(2)数字相机图像获取的比值绿度指数能较好地模拟冬小麦总生态系统碳交换量GEE,R2为0.66,叶片最大光合同化速率与比值绿度指数G/R变化趋势基本一致。表明利用数字相机技术在一定程度上能够表征作物生理生态过程。从而为我国开展不同陆地生态系统自动连续物候监测,深入研究不同生态系统物候和碳循环的关系提供支持。     

基于数字相机图像的西藏当雄高寒草地群落物候模拟

物候现象是环境条件季节和年际变化最直观、敏感的综合指示器, 其发生时间不仅反映了陆地生态系统短期的动态特征, 其微小的变化还会对陆地生态系统产生重要的反馈作用。高寒草地是青藏高原分布广泛、极具代表性的植被类型, 准确地获取高寒草地群落的物候特征, 对于理解和预测气候变化对青藏高原生态系统的影响具有重要意义。该文以西藏当雄高寒草地为研究对象, 探讨了近地面数字相机图像在高寒草地群落季相监测中的作用, 结果如下: 1)通过比较不同绿度指数的差别, 确定了准确表征高寒草地植被群落季相变化的绿度指数——绝对绿度指数(2G_RB); 2)结合土壤含水量数据, 通过线性回归分析得知高寒草地植被群落生长过程与表层(≤10 cm)土壤含水量的变化较为一致(R ² > 0.70); 3)通过对比分析, 发现降水在高寒草地群落季相“变绿”过程中具有“触发”作用。研究表明, 数字相机技术可作为物候监测手段, 实现高寒草地植被群落季相的实时、连续获取, 为更好地揭示气候变化影响下景观尺度季相演变特征, 诊断地方、区域和全球尺度上生态系统对气候变化的快速响应提供了有效的手段。     

Seasonal Variation in Aboveground Production and Radiation-use Efficiency of Temperate rangelands Estimated through Remote Sensing

Aboveground net primary production (ANPP) of grasslands varies spatially and temporally. Spectral information provided by remote sensors is a promising new tool that may be able to estimate ANPP in real time and at low cost. The objectives of this study were (a) to evaluate at a seasonal scale the relationship between ANPP and the normalized difference vegetation index (NDVI), (b) to estimate seasonal variations in the coefficient of conversion of absorbed radiation into aboveground biomass (ε_a), and (c) to identify the environmental controls on such temporal changes. We used biomass-based field determinations of ANPP for two grassland sites in the Flooding Pampa, Argentina, and related them with NDVI data derived from the NOAA Advanced Very High Resolution Radiometer (AVHRR) satellites using three different models. Results were compared with data obtained from the new Moderate Resolution Imaging Spectroradiometer (MODIS) sensor at an additional site. The first model was based solely on NDVI; the second was based on the amount of photosynthetically active radiation absorbed by the green vegetation (APAR_g), which was derived from NDVI and incoming photosynthetically active radiation (PAR); the third was based on APAR_g and ε_a, which was in turn estimated from climatic variables. NDVI explained between 63 and 93% of ANPP variation, depending on the site considered. Estimates of ANPP were not improved by considering the variation in incoming PAR. At both sites, ε_a varied seasonally (from 0.2 to 1.2 g DM/MJ) and was significantly associated with combinations of precipitation and temperature. Combining ε_a variations with APAR_g increased our ability to account for seasonal ANPP variations at both sites. Our results indicate that NDVI produces good, direct estimates of ANPP only if NDVI, PAR, and ε_a are correlated throughout the seasons. Thus, in most cases, seasonal variations of ε_a associated with temperature and precipitation must be taken into account to generate seasonal ANPP estimates with acceptable accuracy.     

表征亚热带常绿林光合作用季节变化特征的多种植被指数

利用遥感方法可以在区域尺度反演地表植被的光合生理状况和生产力变化,但亚热带常绿林冠层结构季节变化较小,传统的光谱植被指数对植被光合作用难以准确捕捉。利用2014—2015年中国科学院广东省鼎湖山森林生态试验站多角度自动光谱观测系统的光谱反射数据,分别反演传统冠层结构型植被指数(NDVI)、光合生理生化型植被指数(CCI)和叶绿素荧光型植被指数(NDFI_(685)和NDFI_(760)),并利用不同类型植被指数的组合,构建多元线性回归模型。结果表明:亚热带常绿针阔混交林三种类型植被指数均与GPP的动态变化有显著的相关性,其中,NDVI是表征GPP较优的植被指数(R~2=0.60,P0.01),其次为CCI(R~2=0.55,P0.01),而NDFI能够作为辅助指数,有效提高NDVI(R~2=0.68,P0.001)和CCI(R~2=0.67,P0.001)表征GPP的程度。多个植被指数参与构建的多元回归模型能够有效提高亚热带地区常绿林GPP季节动态变化的拟合精度,提升遥感精确评估亚热带森林生产力的能力。     

Satellite microwave detection of boreal forest recovery from the extreme 2004 wildfires in Alaska and Canada

The rate of vegetation recovery from boreal wildfire influences terrestrial carbon cycle processes and climate feedbacks by affecting the surface energy budget and land‐atmosphere carbon exchange. Previous forest recovery assessments using satellite optical‐infrared normalized difference vegetation index (NDVI) and tower CO₂ eddy covariance techniques indicate rapid vegetation recovery within 5–10 years, but these techniques are not directly sensitive to changes in vegetation biomass. Alternatively, the vegetation optical depth (VOD) parameter from satellite passive microwave remote sensing can detect changes in canopy biomass structure and may provide a useful metric of post‐fire vegetation response to inform regional recovery assessments. We analyzed a multi‐year (2003–2010) satellite VOD record from the NASA AMSR‐E (Advanced Microwave Scanning Radiometer for EOS) sensor to estimate forest recovery trajectories for 14 large boreal fires from 2004 in Alaska and Canada. The VOD record indicated initial post‐fire canopy biomass recovery within 3–7 years, lagging NDVI recovery by 1–5 years. The VOD lag was attributed to slower non‐photosynthetic (woody) and photosynthetic (foliar) canopy biomass recovery, relative to the faster canopy greenness response indicated from the NDVI. The duration of VOD recovery to pre‐burn conditions was also directly proportional (P < 0.01) to satellite (moderate resolution imaging spectroradiometer) estimated tree cover loss used as a metric of fire severity. Our results indicate that vegetation biomass recovery from boreal fire disturbance is generally slower than reported from previous assessments based solely on satellite optical‐infrared remote sensing, while the VOD parameter enables more comprehensive assessments of boreal forest recovery.     

Negative relationship between photosynthesis and late-stage canopy development and senescence over Tibetan Plateau

Canopy greening, which is associated with significant canopy structure changes, is the most notable signal of ecosystem changes in response to anthropogenic climate change. However, our knowledge of the changing pattern of canopy development and senescence, and its endogenous and climatic drivers is still limited. Here, we used the Normalized Difference Vegetation Index (NDVI) to quantify the changes in the speed of canopy development and senescence over the Tibetan Plateau (TP) during 2000–2018, and used a solar-induced chlorophyll fluorescence dataset as a proxy for photosynthesis, in combination with climate datasets to decipher the endogenous and climatic drivers of the interannual variation in canopy changes. We found that the canopy development during the early green-up stage (April–May) is accelerating at a rate of 0.45–0.8 × 10⁻³ month⁻¹ year⁻¹. However, this accelerating canopy development was largely offset by a decelerating canopy development during June and July (−0.61 to −0.51 × 10⁻³ month⁻¹ year⁻¹), leading to the peak NDVI over the TP increasing at a rate of only one fifth of that in northern temperate regions, and less than one tenth of that in the Arctic and boreal regions. During the green-down period, we observed a significant accelerating canopy senescence during October. Photosynthesis was found to be the dominant driver for canopy changes over the TP. Increasing photosynthesis stimulates canopy development during the early green-up stage. However, slower canopy development and accelerated senescence was found with larger photosynthesis in late growth stages. This negative relationship between photosynthesis and canopy development is probably linked to the source–sink balance of plants and shifts in the allocation regime. These results suggest a sink limitation for plant growth over the TP. The impact of canopy greening on the carbon cycle may be more complicated than the source-oriented paradigm used in current ecosystem models.     

Future atmospheric CO2 leads to delayed autumnal senescence

Growing seasons are getting longer, a phenomenon partially explained by increasing global temperatures. Recent reports suggest that a strong correlation exists between warming and advances in spring phenology but that a weaker correlation is evident between warming and autumnal events implying that other factors may be influencing the timing of autumnal phenology. Using freely rooted, field‐grown Populus in two Free Air CO₂ Enrichment Experiments (AspenFACE and PopFACE), we present evidence from two continents and over 2 years that increasing atmospheric CO₂ acts directly to delay autumnal leaf coloration and leaf fall. In an atmosphere enriched in CO₂ (by ～45% of the current atmospheric concentration to 550 ppm) the end of season decline in canopy normalized difference vegetation index (NDVI) – a commonly used global index for vegetation greenness – was significantly delayed, indicating a greener autumnal canopy, relative to that in ambient CO₂. This was supported by a significant delay in the decline of autumnal canopy leaf area index in elevated as compared with ambient CO₂, and a significantly smaller decline in end of season leaf chlorophyll content. Leaf level photosynthetic activity and carbon uptake in elevated CO₂ during the senescence period was also enhanced compared with ambient CO₂. The findings reveal a direct effect of rising atmospheric CO₂, independent of temperature in delaying autumnal senescence for Populus, an important deciduous forest tree with implications for forest productivity and adaptation to a future high CO₂ world.     

Usability of time-lapse digital camera images to detect characteristics of tree phenology in a tropical rainforest

We evaluated the usability of the red (R), green (G), and blue (B) digital numbers (DN_RGB) extracted from daily phenological images of a tropical rainforest in Malaysian Borneo. We examined temporal patterns in the proportions of DN_R, DN_G, and DN_B as percentages of total DN (denoted as %R, %G and %B), in the hue, saturation, and lightness values in the HSL color model, and in a green excess index (GEI) of the whole canopy and of individual trees for 2 years. We also examined temporal patterns in the proportions of the red, green, and blue reflectance of the whole canopy surface as percentages of total reflectance (denoted as %ref_R, %ref_G, and %ref_B), and vegetation indices (the normalized-difference vegetation index, enhanced vegetation index, and green–red vegetation index) of the whole canopy by using daily measurements from quantum sensors. The temporal patterns of %RGB and saturation of individual trees revealed the characteristics of tree phenology caused by flowering, coloring, and leaf flushing. In contrast, those of the whole canopy did not, nor did those of %ref_R, %ref_G, or %ref_B, or the vegetation indices. The temporal patterns of GEI, however, could detect differences among individual trees caused by leaf flushing and coloring. Our results show the importance of installing multiple time-lapse digital cameras in tropical rainforests to accurately evaluate the sensitivity of tree phenology to meteorological and climatic changes. However, more work needs to be done to adequately describe whole-canopy changes.     

Utility of information in photographs taken upwards from the floor of closed-canopy deciduous broadleaved and closed-canopy evergreen coniferous forests for continuous observation of canopy phenology

Hemispherical photographs taken on forest floors are used to monitor seasonal changes in canopy openness or leaf area index in ecological studies. Those analyses usually use black and white images converted from the original colour images. Photographs taken by downwards-facing cameras installed on towers are used to provide detailed information on leaf expansion, maturation and senescence of various tree species through the analysis of red, green and blue ‘digital numbers’ (DN_RGB) extracted from those images. To examine the usefulness of colour information encoded in upwards hemispherical photographs in monitoring canopy phenological characteristics, we examined the consistency of DN_RGB values between downwards and upwards images in deciduous broadleaved and evergreen coniferous forests in Japan. In the deciduous broadleaved forest, the DN_RGB values in the upwards images were able to detect canopy phenology almost as well as those in the downwards images. However, we found the effects on DN_RGB of (1) the spatial heterogeneity among observed points, (2) low-vegetation (before the beginning of leaf-expansion and after the end of leaf-fall period) and (3) white balance settings. In the evergreen coniferous forest, in contrast, the DN_RGB values in the upwards images did not capture canopy phenology. These different results may be attributable to the light attenuation characteristics in the canopies due to the geometries of leaves and branches. Thus, the DN_RGB values obtained from upwards images are almost as good as those of downwards images for monitoring detailed canopy phenology in deciduous broadleaved forests with a closed canopy.     

Scaling gross ecosystem production at Harvard Forest with remote sensing: a comparison of estimates from a constrained quantum-use efficiency model and eddy correlation

Two independent methods of estimating gross ecosystem production (GEP) were compared over a period of 2 years at monthly integrals for a mixed forest of conifers and deciduous hardwoods at Harvard Forest in central Massachusetts. Continuous eddy flux measurements of net ecosystem exchange (NEE) provided one estimate of GEP by taking day to night temperature differences into account to estimate autotrophic and heterotrophic respiration. GEP was also estimated with a quantum efficiency model based on measurements of maximum quantum efficiency (Qmax), seasonal variation in canopy phenology and chlorophyll content, incident PAR, and the constraints of freezing temperatures and vapour pressure deficits on stomatal conductance. Quantum efficiency model estimates of GEP and those derived from eddy flux measurements compared well at monthly integrals over two consecutive years (R²= 0–98). Remotely sensed data were acquired seasonally with an ultralight aircraft to provide a means of scaling the leaf area and leaf pigmentation changes that affected the light absorption of photosynthetically active radiation to larger areas. A linear correlation between chlorophyll concentrations in the upper canopy leaves of four hardwood species and their quantum efficiencies (R²= 0–99) suggested that seasonal changes in quantum efficiency for the entire canopy can be quantified with remotely sensed indices of chlorophyll. Analysis of video data collected from the ultralight aircraft indicated that the fraction of conifer cover varied from < 7% near the instrument tower to about 25% for a larger sized area. At 25% conifer cover, the quantum efficiency model predicted an increase in the estimate of annual GEP of < 5% because unfavourable environmental conditions limited conifer photosynthesis in much of the non-growing season when hardwoods lacked leaves.     

日光诱导叶绿素荧光对亚热带常绿针叶林物候的追踪

植被物候期(春季返青和秋季衰老)是表征生物响应和陆地碳循环的基础信息。由于常绿针叶林冠层绿度的季节变动较弱,遥感提取常绿针叶林的物候信息存在着较大的不确定性,是目前区域物候监测中的难点。利用MODIS植被指数(归一化植被指数NDVI和增强型植被指数EVI)、GOME-2日光诱导叶绿素荧光(SIF)和通量数据(总初级生产力GPP)估算2007—2011年亚热带常绿针叶林物候期,用来比较三类遥感指数估算常绿针叶林物候的差异。结果表明:基于表征光合作用物候的通量GPP数据估算得到5年内亚热带常绿针叶林生长季开始时间(SOS_(GPP))为第63天,生长季结束时间(EOS_(GPP))为第324天,生长季长度为272天;基于反映植被光合作用特征的SIF曲线获得物候信息要滞后GPP物候期,其中生长季开始时间滞后19天,生长季结束时间滞后2天;基于传统植被指数NDVI和EVI的物候期滞后GPP物候期的时间要大于SIF滞后期,其中植被指数SOS滞后SOS_(GPP)31天,植被指数EOS滞后EOS_(GPP)10—17天。虽然基于3种遥感指数估算的春季和秋季物候都滞后于通量GPP的物候期,但是卫星SIF的物候信息能够更好地捕捉常绿针叶林的生长阶段。同时,春季温度是影响森林生长季开始时间的最重要因素;秋季水分和辐射是影响生长季结束时间的关键因素。由此可见,SIF估算的亚热带常绿针叶林的春季和秋季物候的滞后时间要短于传统植被指数,能更好地追踪常绿林光合作用的季节性,为深入研究陆地生态系统碳循环及其对气候变化的响应提供重要的基础。     

Determination of the gas exchange phenology in an evergreen coniferous forest from 7 years of eddy covariance flux data using an extended big-leaf analysis

We defined gas exchange phenology as the seasonality of the gas exchange characteristics of a forest canopy, and investigated how the gas exchange phenology could be directly detected from an eddy covariance (EC) dataset and its influence on the canopy fluxes within an evergreen Japanese cypress forest. For the detection of gas exchange phenology, we derived three bulk parameters of the extended big-leaf model (Kosugi et al. 2005) inversely from EC flux data over a 7-year period: surface conductance (g _c), maximum rate of carboxylation of the “big leaf” (V _CMAX), and intercellular CO₂ concentration of the “big leaf” (C _I). The relationship between g _c and the vapor pressure deficit declined in winter and spring. The relationship between the daily ecosystem respiration and air temperature was greater in the spring than in the other seasons. The temperature dependence curve of V _CMAX decreased substantially in the winter and was different from that of an evergreen broadleaved forest. A decrease in C _I was occasionally coupled with the decrease in canopy gross primary production during April and August, indicating that stomatal closure was responsible for a decline in canopy photosynthesis. Gas exchange phenology should be quantified when understanding the determining factors of the seasonality of canopy fluxes at evergreen coniferous forests.     

林下植被对遥感估算马尾松LAI的影响

叶面积指数是一项极其重要的描述植被冠层结构的植被特征参量。根据植被物候规律,利用中国环境卫星CCD多光谱影像和野外马尾松样区调查数据,通过建立不同季节和不同郁闭度样区马尾松LAI和影像NDVI经验回归模型,并利用一个新的LAI观测方式定量比较乔木层LAI和生态系统总LAI(包括草本层、灌木层和乔木层)的差异,研究林下植被对马尾松反演的影响程度。结果表明:(1)由于林下植被的物候变化,冬季林下植被对马尾松LAI反演影响最小,马尾松NDVI和LAI线性关系R2维持在0.65;夏季林下植被影响最大,线性关系R2只有0.25;春季和秋季影响居中,NDVI和LAI线性关系R2在0.47附近。但是,受林下植被影响较小的A类样区4个季节内NDVI和LAI线性关系基本都在0.60以上(夏季略低于0.60);(2)乔木层LAI和总LAI差距非常大,最大差距达到2.93,相差的比例最大达到了2.45倍;(3)总LAI和NDVI相关关系显著,其中线性关系R2达到0.66,对数关系R2可达到0.68,而乔木层LAI和NDVI相关关系较差,线性关系R2只有0.30。分别建立冬季和其它季节实测总LAI和NDVI的关系,可以估算出林下植被对马尾松LAI反演的影响程度。     

Effects of seasonal and interannual variations in leaf photosynthesis and canopy leaf area index on gross primary production of a cool-temperate deciduous broadleaf forest in Takayama, Japan

Revealing the seasonal and interannual variations in forest canopy photosynthesis is a critical issue in understanding the ecological mechanisms underlying the dynamics of carbon dioxide exchange between the atmosphere and deciduous forests. This study examined the effects of temporal variations of canopy leaf area index (LAI) and leaf photosynthetic capacity [the maximum velocity of carboxylation (V _cmax)] on gross primary production (GPP) of a cool-temperate deciduous broadleaf forest for 5 years in Takayama AsiaFlux site, central Japan. We made two estimations to examine the effects of canopy properties on GPP; one is to incorporate the in situ observation of V _cmax and LAI throughout the growing season, and another considers seasonality of LAI but constantly high V _cmax. The simulations indicated that variation in V _cmax and LAI, especially in the leaf expansion period, had remarkable effects on GPP, and if V _cmax was assumed constant GPP will be overestimated by 15%. Monthly examination of air temperature, radiation, LAI and GPP suggested that spring temperature could affect canopy phenology, and also that GPP in summer was determined mainly by incoming radiation. However, the consequences among these factors responsible for interannual changes of GPP are not straightforward since leaf expansion and senescence patterns and summer meteorological conditions influence GPP independently. This simulation based on in situ ecophysiological research suggests the importance of intensive consideration and understanding of the phenology of leaf photosynthetic capacity and LAI to analyze and predict carbon fixation in forest ecosystems.     

Assessing the use of camera-based indices for characterizing canopy phenology in relation to gross primary production in a deciduous broad-leaved and an evergreen coniferous forest in Japan

Recent studies have reported that seasonal variation in camera-based indices that are calculated from the digital numbers of the red, green, and blue bands (RGB_DN) recorded by digital cameras agrees well with the seasonal change in gross primary production (GPP) observed by tower flux measurements. These findings suggest that it may be possible to use camera-based indices to estimate the temporal and spatial distributions of photosynthetic productivity from the relationship between RGB_DN and GPP. To examine this possibility, we need to investigate the characteristics of seasonal variation in three camera-based indices (green excess index [GE], green chromatic coordinate [rG], and HUE) and the robustness of the relationship between these indices and tower flux-based GPP and how it differs among ecosystems. Here, at a daily time step over multiple years in a deciduous broad-leaved and an evergreen coniferous forest, we examined the relationships between canopy phenology assessed by using the three indices and GPP determined from tower CO₂ flux observations, and we compared the camera-based indices with the corresponding spectra-based indices estimated by a spectroradiometer system. We found that (1) the three camera-based indices and GPP showed clear seasonal patterns in both forests; (2) the amplitude of the seasonal variation in the three camera-based indices was smaller in the evergreen coniferous forest than in the deciduous broad-leaved forest; (3) the seasonal variation in the three camera-based indices corresponded well to seasonal changes in potential photosynthetic activity (GPP on sunny days); (4) the relationship between the three camera-based indices and GPP appeared to have different characteristics at different phenological stages; and (5) the camera-based and spectra-based HUE indices showed a clear relationship under sunny conditions in both forests. Our results suggest that it might be feasible for ecologists to establish comprehensive networks for long-term monitoring of potential photosynthetic capacity from regional to global scales by linking satellite-based, in situ spectra-based, and in situ camera-based indices.     

Chlorophyll fluorescence tracks seasonal variations of photosynthesis from leaf to canopy in a temperate forest

Accurate estimation of terrestrial gross primary productivity (GPP) remains a challenge despite its importance in the global carbon cycle. Chlorophyll fluorescence (ChlF) has been recently adopted to understand photosynthesis and its response to the environment, particularly with remote sensing data. However, it remains unclear how ChlF and photosynthesis are linked at different spatial scales across the growing season. We examined seasonal relationships between ChlF and photosynthesis at the leaf, canopy, and ecosystem scales and explored how leaf‐level ChlF was linked with canopy‐scale solar‐induced chlorophyll fluorescence (SIF) in a temperate deciduous forest at Harvard Forest, Massachusetts, USA. Our results show that ChlF captured the seasonal variations of photosynthesis with significant linear relationships between ChlF and photosynthesis across the growing season over different spatial scales (R² = 0.73, 0.77, and 0.86 at leaf, canopy, and satellite scales, respectively; P < 0.0001). We developed a model to estimate GPP from the tower‐based measurement of SIF and leaf‐level ChlF parameters. The estimation of GPP from this model agreed well with flux tower observations of GPP (R² = 0.68; P < 0.0001), demonstrating the potential of SIF for modeling GPP. At the leaf scale, we found that leaf F_q’/F_m’, the fraction of absorbed photons that are used for photochemistry for a light‐adapted measurement from a pulse amplitude modulation fluorometer, was the best leaf fluorescence parameter to correlate with canopy SIF yield (SIF/APAR, R² = 0.79; P < 0.0001). We also found that canopy SIF and SIF‐derived GPP (GPP_SIF) were strongly correlated to leaf‐level biochemistry and canopy structure, including chlorophyll content (R² = 0.65 for canopy GPP_SIF and chlorophyll content; P < 0.0001), leaf area index (LAI) (R² = 0.35 for canopy GPP_SIF and LAI; P < 0.0001), and normalized difference vegetation index (NDVI) (R² = 0.36 for canopy GPP_SIF and NDVI; P < 0.0001). Our results suggest that ChlF can be a powerful tool to track photosynthetic rates at leaf, canopy, and ecosystem scales.     

Green light drives photosynthesis in mosses

Temperate forests are characterised by variable light quality (i.e. spectral composition of light) at or near the forest floor. These understory environments have a high concentration of green light, as red and blue light are preferentially absorbed by upper canopy leaves. Understory species may be well-adapted for using green light to drive photosynthesis. Angiosperms have been shown to use green light for photosynthesis, but this ability has not been demonstrated in shade-dwelling bryophytes. In this study, net photosynthetic rate (P_N) of three temperate understory species of moss (Dichodontium pellucidum (Hedw.) Schimp., Leucobryum albidum (Brid. ex P.Beauv) Lindb. and Amblystegium serpens (Hedw.) Schimp.) was measured under green, red?+?blue, and red?+?blue?+?green light to assess green light use efficiency. All three species were capable of photosynthesising beyond their respiratory demands using solely green light, with higher green light use efficiency measured in plants collected from areas with greater canopy cover, suggesting growth in a green light concentrated environment increases green light use efficiency. Each species was also collected from sites differing in their degree of canopy cover and grown under three light treatments (high light, low light, and green light). Photosynthetic efficiency (chlorophyll fluorescence), tissue nitrogen and carbon isotope concentrations were assessed after a short growth period. Growth conditions had little effect on leaf chemistry and monochromatic green light did not significantly degrade photosynthetic efficiency. This study provides the first evidence to date of positive net ‘green light photosynthesis’ in mosses.     

Use of digital cameras for phenological observations

Vegetation phenology such as the onset of green-up and senescence is strongly controlled by climate and other environmental factors, and in turn affects the terrestrial carbon balance. Therefore, phenological observation is important as an indicator of global warming and for estimation of the terrestrial carbon balance. Because phenological responses differ from species to species, precise monitoring from the species scale to the global scale is required. In this study, we analyzed images from digital cameras, which have proliferated in recent years, to investigate their utility as remote sensors. We collected daily images taken by digital cameras in national parks across Japan over 8 years in wetland mixed deciduous forest, and evergreen broadleaved forest. Values of red, green, and blue (RGB) channels in each pixel within images were extracted, and a vegetation green excess index (2G-RBi) was calculated to detect phenology. The time series of 2G-RBi showed clear phenological patterns of each vegetation type in each year at the species or community scale. Even physiological damage due to a typhoon was detected. The dates of green-up were estimated easily and objectively from the second derivative of 2G-RBi, and a trend in yearly green-up dates of various types of vegetation was demonstrated. Furthermore, a strong correlation between interannual variations in green-up dates and local spring temperature was found, and the sensitivity of green-up date to temperature was revealed. The results suggest the utility of digital cameras for phenological observations at precise temporal and spatial resolutions, despite a year-to-year drift of color balance of camera as a technical device. As a form of near-surface remote sensing, digital cameras could obtain significant ecological information. Establishing camera networks could help us understand phenological responses at a wide range of scales.     

克氏针茅物候对气候变暖和水分变化的响应及其光合生理生态机制

物候对气候变化具有重要指示作用,然而现有研究主要关注植物物候变化与环境因子的关系,对于物候变化的生理生态机制研究较为缺乏。基于内蒙古自治区克氏针茅草原红外线辐射增温与控水相结合的原位模拟试验资料,探究了克氏针茅物候变化的光合生理生态机制及其对水热环境因子的响应。研究结果表明：（1）增温使克氏针茅返青期和抽穗期提前2.8 d和7.8 d、枯黄期推迟6.8 d;水热协同作用主要影响抽穗期,增温增水（气候暖湿化）较增温减水（气候暖干化）提前7.4 d。（2）增温增水使得克氏针茅返青期和抽穗期的净光合速率、气孔导度和蒸腾速率显著高于增温减水,而对水分利用效率的影响则相反（P<0.05）,增温增水与增温减水对克氏针茅枯黄期的光合生理生态特征影响无显著差异。（3）净光合速率是影响克氏针茅物候变化的决策因子,温度是影响克氏针茅植物返青期和枯黄期的限制因子,水分则是影响克氏针茅植物抽穗期的限制因子。研究发现克氏针茅物候与其光合生理生态特征和环境因子密切相关,研究结果可为植物物候模型发展和物候机理研究提供理论支撑。     

Seasonal variability in the effect of elevated CO2 on ecosystem leaf area index in a scrub-oak ecosystem

We report effects of elevated atmospheric CO₂ concentration (C_a) on leaf area index (LAI) of a Florida scrub‐oak ecosystem, which had regenerated after fire for between three and five years in open‐top chambers (OTCs) and was yet to reach canopy closure. LAI was measured using four nondestructive methods, calibrated and tested in experiments performed in calibration plots near the OTCs. The four methods were: PAR transmission through the canopy, normalized difference vegetation index (NDVI), hemispherical photography, and allometric relationships between plant stem diameter and plant leaf area. Calibration experiments showed: (1) Leaf area index could be accurately determined from either PAR transmission through the canopy or hemispherical photography. For LAI determined from PAR transmission through the canopy, ecosystem light extinction coefficient (k) varied with season and was best described as a function of PAR transmission through the canopy. (2) A negative exponential function described the relationship between NDVI and LAI; (3) Allometric relationships overestimated LAI. Throughout the two years of this study, LAI was always higher in elevated C_a, rising from, 20% during winter, to 55% during summer. This seasonality was driven by a more rapid development of leaf area during the spring and a relatively greater loss of leaf area during the winter, in elevated C_a. For this scrub‐oak ecosystem prior to canopy closure, increased leaf area was an indirect mechanism by which ecosystem C uptake and canopy N content were increased in elevated C_a. In addition, increased LAI decreased potential reductions in canopy transpiration from decreases in stomatal conductance in elevated C_a. These findings have important implications for biogeochemical cycles of C, N and H₂O in woody ecosystems regenerating from disturbance in elevated C_a.