Taku M. Saitoh

Modeling CO2 exchange over a Bornean tropical rain forest using measured vertical and horizontal variations in leaf‐level physiological parameters and leaf area densities

Southeast Asian tropical rain forests are among the worlds most important biomes in terms of global carbon cycling; nevertheless, the impact of environmental factors on the ecosystem CO 2 flux remains poorly understood. One-dimensional multilayer biosphere-atmosphere models such as soil-vegetation-atmosphere transfer (SVAT) models are promising tools for understanding how interactions between environmental factors and leaf-level physiological parameters might impact canopy-level CO 2 exchange. To examine application of the SVAT model in tropical rain forests, which is expected to be difficult partly because of the complex canopy structure and large number of tree species, we measured vertical and horizontal variations in leaf-level physiological parameters and leaf area densities together with eddy covariance measurements using a canopy crane in a tropical rain forest in Sarawak, Malaysia. Despite differences in species and canopy positions, leaf nitrogen per unit area (N a ) within the canopy could be one-dimensionally described as a linear function of height. N a also clearly explained the other leaf-level physiological parameters across species and canopy positions. Even though the leaf area density profile likely varies in this tropical forest, the SVAT model satisfactorily reproduced the eddy covariance measurements. Furthermore, the CO 2 flux calculated on the assumption that N a measured in the upper canopy was distributed evenly throughout was almost the same as that taking the vertical gradient into consideration. These findings suggest that when reproducing the CO 2 flux in tropical rain forests using the SVAT model, the leaf area density profile obtained from the leaf area index (LAI) measured at one point and leaf-level physiological properties measured across species in the upper canopy are sufficient.

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

Abstract 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.

In situ examination of the relationship between various vegetation indices and canopy phenology in an evergreen coniferous forest, Japan

We examined the relationship between four vegetation indices and tree canopy phenology in an evergreen coniferous forest in Japan based on observations made using a spectral radiometer and a digital camera at a daily time step during a 4 year period. The colour of the canopy surface of Japanese cedar (Cryptomeria japonica) changed from yellowish-green to whitish-green from late May to July and turned reddish-green in winter. The normalized difference vegetation index (NDVI), enhanced vegetation index (EVI) and plant area index (PAI) showed no seasonality. In contrast, the green–red ratio vegetation index (GRVI) increased from March to June and then decreased gradually from July to December, resulting in a bell-shaped curve. GRVI revealed seasonal changes in the colour of the canopy surface. GRVI correlated more positively with the evaluated maximum photosynthetic rate for the whole forest canopy, A max, than did NDVI or EVI. These results suggest the possibility that GRVI is more useful than NDVI and EVI for capturing seasonal changes in photosynthetic capacity, as the green and red reflectances are strongly influenced by changes in leaf pigments in this type of forest.

Dataset of CarboEastAsia and uncertainties in the CO2 budget evaluation caused by different data processing

The datasets of net ecosystem CO2 exchange (NEE) were acquired from 21 forests, 3 grasslands, and 3 croplands in the eastern part of Asia based on the eddy covariance measurements of the international joint program, CarboEastAsia. The program was conducted by three networks in Asia, ChinaFLUX, JapanFlux, and KoFlux, to quantify, synthesize, and understand the carbon budget of the eastern part of Asia. An intercomparison was conducted for NEE estimated by three gap-filling procedures adopted by ChinaFLUX, JapanFlux, and KoFlux to test the range of uncertainty in the estimation of NEE. The overall comparison indicated good agreement among the procedures in the seasonal patterns of NEE, although a bias was observed in dormant seasons depending on the different criteria of data screening. Based on the gap-filled datasets, the magnitude and seasonality of the carbon budget were compared among various biome types, phenology, and stress conditions throughout Asia. The annual values of gross primary production and ecosystem respiration were almost proportional to the annual air temperature. Forest management, including clear-cutting, plantation, and artificial drainage, was significant and obviously affected the annual carbon uptake within the forests. Agricultural management resulted in notable seasonal patterns in the crop sites. The dataset obtained from a variety of biome types would be an essential source of knowledge for ecosystem science as well as a valuable validation dataset for modeling and remote sensing to upscale the carbon budget estimations in Asia.

Responses of Soil, Heterotrophic, and Autotrophic Respiration to Experimental Open-Field Soil Warming in a Cool-Temperate Deciduous Forest

How global warming will affect soil respiration (RS) and its source components is poorly understood despite its importance for accurate prediction of global carbon (C) cycles. We examined the responses of RS, heterotrophic respiration (RH), autotrophic respiration (RA), nitrogen (N) availability, and fine-root biomass to increased temperature in an open-field soil warming experiment. The experiment was conducted in a cool-temperate deciduous forest ecosystem in northern Japan. As this forest is subjected to strong temporal variation in temperature, on scales ranging from daily to seasonal, we also investigated the temporal variation in the effects of soil warming on RS, RH, and RA. Soil temperature was continuously elevated by about 4.0°C from 2007 to 2014 using heating wires buried in the soil, and we measured soil respiratory processes in all four seasons from 2012 to 2014. Soil warming increased annual RS by 32–45%, but the magnitude of the increase was different between the components: RH and RA were also stimulated, and increased by 39–41 and 17–18%, respectively. Soil N availability during the growing season and fine-root biomass were not remarkably affected by the warming treatment. We found that the warming effects varied seasonally. RH increased significantly throughout the year, but the warming effect showed remarkable seasonal differences, with the maximum stimulation in the spring. This suggests that warmer spring temperature will produce a greater increase in CO2 release than warmer summer temperatures. In addition, we found that soil warming reduced the temperature sensitivity (Q10) of RS. Although the Q10 of both RH and RA tended to be reduced, the decrease in the Q10 of RS was caused mainly by a decrease in the response of RA to warming. These long-term results indicate that a balance between the rapid and large response of soil microbes and the acclimation of plant roots both play important roles in determining the response of RS to soil warming, and must be carefully considered to predict the responses of soil C dynamics under future temperature conditions.

Detection of the different characteristics of year-to-year variation in foliage phenology among deciduous broad-leaved tree species by using daily continuous canopy surface images

Abstract Clarification of species-specific year-to-year variations of the timings of the start of leaf-expansion (SLE) and the end of leaf-fall (ELF) is an important and challenging task because these timings may alter spatial and temporal variations in ecosystem services such as carbon stock and climate control. Although many previous studies have applied automatically captured digital camera images to observe the timings of SLE and ELF, the evaluation of the long-term variation in both timings of each tree species based on image analysis has not yet been sufficiently investigated. In this study, we investigated the year-to-year variation in the timings of SLE and ELF for multiple deciduous broad-leaved tree species in a cool-temperate deciduous broad-leaved forest in Japan by using long-term and daily hemispherical (“fish-eye”) canopy surface images from 2004 to 2013. We found that (1) differences in the characteristics of year-to-year variations in the timing of ELF among the tree species were more apparent than those of the timing of SLE among the tree species, (2) the threshold value of the camera-based index (green excess index) for detecting the timing of ELF varied depending on the spatial and temporal distribution of understories and the visual distortion of the fish-eye images, and (3) the phenological sensitivity of the timing of ELF to air temperature was lower than that of the timing of SLE. Our results indicate that it might be helpful for ecologists to use daily continuous canopy surface images for monitoring of species-specific characteristics of spatial and temporal changes in foliage phenology in mixed-species deciduous broad-leaved forests.

Examination of the extinction coefficient in the Beer–Lambert law for an accurate estimation of the forest canopy leaf area index

Leaf area index (LAI) is a crucial ecological parameter that represents canopy structure and controls many ecosystem functions and processes, but direct measurement and long-term monitoring of LAI are difficult, especially in forests. An indirect method to estimate the seasonal pattern of LAI in a given forest is to measure the attenuation of photosynthetically active radiation (PAR) by the canopy and then calculate LAI by the Beer–Lambert law. Use of this method requires an estimate of the PAR extinction coefficient (k), a parameter needed to calculate PAR attenuation. However, the determination of k itself requires direct measurement of LAI over seasons. Our goals were to determine (1) the best way to model k values that may vary seasonally in a forest, and (2) the sensitivity of estimates of canopy ecosystem functions to the errors in estimated LAI. We first analyzed the seasonal pattern of the “true” k (k p) under cloudy and sunny conditions in a Japanese deciduous broadleaved forest by using the inverted form of the Beer–Lambert law with the true LAI and PAR. We next calculated the errors of PAR-based LAIs estimated with an assumed constant k (LAIpred) and determined under what conditions we should expect k to be approximately constant during the growing period. Finally, we examined the effect of errors in LAIpred on estimates of gross primary production (GPP), net ecosystem production (NEP), and latent heat flux (LE) calculated with a land-surface model using LAIpred as an input parameter. During the growing period, cloudy k p varied from 0.47 to 1.12 and sunny k p from 0.45 to 1.59. Results suggest that the value of LAIpred was adequately estimated with the k p obtained under cloudy conditions during the fully-leaved period (0.53–0.57). However, LAIpred was overestimated by up to 0.6 m2 m–2 in May and November. The errors in LAIpred propagated to errors in modeled carbon and latent heat fluxes of –0.21 to 0.32 g C m–2 day–1 in GPP, –0.09 to 0.19 g C m–2 day–1 in NEP, and –3.2 to 3.9 W m–2 in LE, which is close to the measurement errors recognized in the tower flux measurement. LAIpred estimated with an assumed constant k can be useful for some ecosystem studies as a second-best alternative if k is equated to the value of k p measured under cloudy conditions especially during the fully-leaved period.

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

Abstract 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’ (DNRGB) 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 DNRGB values between downwards and upwards images in deciduous broadleaved and evergreen coniferous forests in Japan. In the deciduous broadleaved forest, the DNRGB 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 DNRGB 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 DNRGB 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 DNRGB 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.

New data-driven estimation of terrestrial CO2 fluxes in Asia using a standardized database of eddy covariance measurements, remote sensing data, and support vector regression

The lack of a standardized database of eddy covariance observations has been an obstacle for data-driven estimation of terrestrial CO2 fluxes in Asia. In this study, we developed such a standardized database using 54 sites from various databases by applying consistent postprocessing for data-driven estimation of gross primary productivity (GPP) and net ecosystem CO2 exchange (NEE). Data-driven estimation was conducted by using a machine learning algorithm: support vector regression (SVR), with remote sensing data for 2000 to 2015 period. Site-level evaluation of the estimated CO2 fluxes shows that although performance varies in different vegetation and climate classifications, GPP and NEE at 8days are reproduced (e.g., r2=0.73 and 0.42 for 8day GPP and NEE). Evaluation of spatially estimated GPP with Global Ozone Monitoring Experiment 2 sensor-based Sun-induced chlorophyll fluorescence shows that monthly GPP variations at subcontinental scale were reproduced by SVR (r2=1.00, 0.94, 0.91, and 0.89 for Siberia, East Asia, South Asia, and Southeast Asia, respectively). Evaluation of spatially estimated NEE with net atmosphere-land CO2 fluxes of Greenhouse Gases Observing Satellite (GOSAT) Level 4A product shows that monthly variations of these data were consistent in Siberia and East Asia; meanwhile, inconsistency was found in South Asia and Southeast Asia. Furthermore, differences in the land CO2 fluxes from SVR-NEE and GOSAT Level 4A were partially explained by accounting for the differences in the definition of land CO2 fluxes. These data-driven estimates can provide a new opportunity to assess CO2 fluxes in Asia and evaluate and constrain terrestrial ecosystem models. (Less)

Spatio-temporal distribution of the timing of start and end of growing season along vertical and horizontal gradients in Japan

We detected the spatio-temporal variability in the timing of start (SGS) and end of growing season (EGS) in Japan from 2003 to 2012 by analyzing satellite-observed daily green-red vegetation index with a 500-m spatial resolution. We also examined the characteristics of SGS and EGS timing in deciduous broadleaf and needleleaf forests along vertical and horizontal gradients and then evaluated the relationship between their timing and daily mean air temperature. We found that for the timing of SGS and EGS, changes along the vertical gradient in deciduous broadleaf forest tended to be larger than those in deciduous needleleaf forest. For both forest types, changes along the vertical and horizontal gradients in the timing of EGS tended to be smaller than those of SGS. Finally, in both forest types, the sensitivity of the timing of EGS to air temperature was much less than that of SGS. These results suggest that the spatio-temporal variability in the timing of SGS and EGS detected by satellite data, which may be correlated with leaf traits, photosynthetic capacity, and environment conditions, provide useful ground-truthing information along vertical and horizontal gradients.