Biografi

My work ranges from plant level ecophysiological processes to ecosystem level carbon, water and energy balance. I am particularly interested in the impact of climate change (including relevant extreme events, e.g., drought, flooding, snow storm, etc.) on these processes and their climate feedbacks. I use many state-of-the-art techniques in my research work, including eddy covariance for ecosystem level gas exchange observations, automatic static/dynamic chambers for plot-level or whole-plant-level gas exchange measurements and machine learning models for data analysis and prediction.   

 

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Professional appointments

2019 – present  Research Scientist  Norwegian Institute of Bioeconomy Research (NIBIO)

2016 – 2019  Postdoctoral associate  Florida International University (FIU)

2013 – 2015  Postdoctoral researcher  Swedish University of Agricultural Sciences (SLU)     

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Education

2013  Ph. D  University of Chinese Academy of Sciences, Beijing, China

2011 – 2012  Visiting Ph.D student  Max Planck Institute for Biogeochemistry, Jena, Germany

2007  B. S.  Yunnan University, Kunming, China

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Heat Field Deformation (HFD) is a widely used method to measure sap flow of trees based on empirical relationships between heat transfer within tree stems and the sap flow rates. As an alternative, the Linear Heat Balance (LHB) method implements the same instrumental configuration as HFD but calculates the sap flow rates using analytical equations that are derived from fundamental conduction-convection heat transfer theories. In this study, we systematically compared the sap flow calculated using the two methods based on data that were recorded using the same instrument. The measurements were conducted on four Norway spruce trees. We aimed to evaluate the discrepancies between the sap flow estimates from the two methods and determine the underlying causes. Diurnal and day-to-day patterns were consistent between the sap flow estimates from the two methods. However, the magnitudes of the estimated sap flow were different between them, where LHB resulted in much lower estimates in three trees and slightly higher estimates in one compared to HFD. We also observed larger discrepancies in negative (reversed flow) than in positive sap flow, where the LHB resulted in lower reversed flow than HFD. Consequently, the seasonal budget estimated by LHB can be as low as ∼20% of that estimated by HFD. The discrepancies can be mainly attributed to the low wood thermal conductivities for the studied trees that lead to substantial underestimations using the LHB method. In addition, the sap flow estimates were very sensitive to the value changes of the empirical parameters in the calculations and, thus, using a proper case-specific value is recommended, especially for the LHB method. Overall, we suggest that, despite the strong theoretical support, the correctness of LHB outputs depends largely on the tree individuals and should be carefully evaluated.

Sammendrag

Forests sequester atmospheric carbon dioxide (CO2) which is important for climate mitigation. Net ecosystem production (NEP) varies significantly across forests in different regions depending on the dominant tree species, stand age, and environmental factors. Therefore, it is important to evaluate forest NEP and its potential changes under climate change in different regions to inform forestry policy making. Norway spruce (Picea abies) is the most prevalent species in conifer forests throughout Europe. Here, we focused on Norway spruce forests and used eddy covariance-based observations of CO2 fluxes and other variables from eight sites to build a XGBoost machine learning model for NEP estimation. The NEP values from the study sites varied between −296 (source) and 1253 (sink) g C m−2 yr−1. Overall, among the tested variables, air temperature was the most important factor driving NEP variations, followed by global radiation and stand age, while precipitation had a very limited contribution to the model. The model was used to predict the NEP of mature Norway spruce forests in different regions within Europe. The NEP median value was 494 g C m−2 yr−1 across the study areas, with higher NEP values, up to >800 g C m−2 yr−1, in lower latitude regions. Under the “middle-of-the-road” SSP2-4.5 scenario, the NEP values tended to be greater in almost all the studied regions by 2060 with the estimated median of NEP changes in 2041–2060 to be +45 g C m−2 yr−1. Our results indicate that Norway spruce forests show high productivity in a wide area of Europe with potentially future NEP enhancement. However, due to the limitations of the data, the potential decrease in NEP induced by temperature increases beyond the photosynthesis optima and frequent ecosystem disturbances (e.g., drought, bark beetle infestation, etc.) still needs to be evaluated.

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As a way to estimate evapotranspiration (ET), Heat Field Deformation (HFD) is a widely used method to measure sap flow of trees based on empirical relationships between heat transfer within tree stems and the sap flow rates. As an alternative, the Linear Heat Balance (LHB) method implements the same instrumental configuration as HFD but calculates the sap flow rates using analytical equations that are derived from fundamental conduction-convection heat transfer equations.

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Litter comprises a major nutrient source when decomposed via soil microbes and functions as subtract that limits gas exchange between soil and atmosphere, thereby restricting methane (CH4) uptake in soils. However, the impact and inherent mechanism of litter and its decomposition on CH4 uptake in soils remains unknown in forest. Therefore, to declare the mechanisms of litter input and decomposition effect on the soil CH4 flux in forest, this study performed a litter-removal experiment in a tropical rainforest, and investigated the effects of litter input and decomposition on the CH4 flux among forest ecosystems through a literature review. Cumulative annual CH4 flux was −3.30 kg CH4-C ha−1 y−1. The litter layer decreased annual accumulated CH4 uptake by 8% which greater in the rainy season than the dry season in the tropical rainforest. Litter decomposition and the input of carbon and nitrogen in litter biomass reduced CH4 uptake significantly and the difference in CH4 flux between treatment with litter and without litter was negatively associated with N derived from litter input. Based on the literature review about litter effect on soil CH4 around world forests, the effect of litter dynamics on CH4 uptake was regulated by litter-derived nitrogen input and the amount soil inorganic nitrogen content. Our results suggest that nitrogen input via litter decomposition, which increased with temperature, caused a decline in CH4 uptake by forest soils, which could weaken the contribution of the forest in mitigating global warming.

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The rapid conversion of tropical rainforests into monoculture plantations of rubber (Hevea brasiliensis) in Southeast Asia (SEA) necessitates understanding of rubber tree physiology under local climatic conditions. Frequent fog immersion in the montane regions of SEA may affect the water and carbon budgets of the rubber trees and the plantation ecosystems. We studied the effect of fog on various plant physiological parameters in a mature rubber plantation in southwest China over 3 years. During the study period, an average of 141 fog events occurred every year, and the majority occurred during the dry season, when the temperature was relatively low. In addition to the low temperature, fog events were also associated with low vapor pressure deficit, atmospheric water potential, relative humidity and frequent wet-canopy conditions. We divided the dry season into cool dry (November-February) and hot dry (March-April) seasons and classified days into foggy (FG) and non-foggy (non-FG) days. During the FG days of the cool dry season, the physiological activities of the rubber trees were suppressed where carbon assimilation and evapotranspiration showed reductions of 4% and 15%, respectively, compared to the cool dry non-FG days. Importantly, the unequal declines in carbon assimilation and evapotranspiration led to enhanced crop water productivity (WPc) on cool dry FG days but insignificant WPc values were found between FG and non-FG days of the hot dry season. Our results suggest that, by regulating plant physiology, fog events during the cool dry season significantly reduce water demand and alleviate water stress for the trees through improved WPc.

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Subtropical forests are important ecosystems globally due to their extensive role in carbon sequestration. Extreme climate events are known to introduce disturbances in the ecosystem that cause long-term changes in carbon balance and radiation reflectance. However, how these ecosystem function changes contribute to global warming in terms of radiative forcing (RF), especially in the years following a disturbance, still needs to be investigated. We studied an extreme snow event that occurred in a subtropical evergreen broadleaved forest in south-western China in 2015 and used 9 years (2011–2019) of net ecosystem CO2 exchange (NEE) and surface albedo (α) data to investigate the effect of the event on the ecosystem RF changes. In the year of the disturbance, leaf area index (LAI) declined by 40% and α by 32%. The annual NEE was −718 ± 128 g C m−2 as a sink in the pre-disturbance years (2011–2014), but after the event, the sink strength dropped significantly by 76% (2015). Both the vegetation, indicated by LAI, and α recovered to pre-disturbance levels in the fourth post-disturbance year (2018). However, the NEE recovery lagged and occurred a year later in 2019, suggesting a more severe and lasting impact on the ecosystem carbon balance. Overall, the extreme event caused a positive (warming effect) net RF which was predominantly caused by changes in α (90%–93%) rather than those in NEE. This result suggests that, compared to the climate effect caused by forest carbon sequestration changes, the climate effect of α alterations can be more sensitive to vegetation damage induced by natural disturbances. Moreover, this study demonstrates the important role of vegetation recovery in driving canopy reflectance and ecosystem carbon balance during the post-disturbance period, which determines the ecosystem feedbacks to the climate change.

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With large area of primary tropical rainforest converted into rubber (Hevea brasiliensis) plantation in Southeast Asia, it is necessary to examine the change in soil CO2 and CH4 emissions, and their underlying drivers in tropical rainforest (TRF) and rubber plantation. In TRF and RP in Xishuangbanna Southwest China, we measured the soil CO2 , CH4 , temperature, and water content once each week from 2003 to 2008, and twice weeks in 2013 and 2014. Additionally, the concentrations of soil carbon (C) and nitrogen (N) fractions from 2013 to 2014 were observed. Inputs of litter and live, dead, decomposed fine roots dynamics were also included. TRF transplanted to RP did not change significantly the annual soil CO2 emissions (TRF, 359 ± 91 and RP 352 ± 41 mg CO2 m−2 h−1) but decreased soil CH4 uptake significantly (TRF, −0.11 ± 0.18 mg CH4 m−2 h−1) RP, −0.020 ± 0.087 mg CH4 m−2 h−1). The most important influence on soil CO2 and CH4 emissions in the RP was the leaf area index and soil water content, respectively, whereas the soil water content, soil temperature, and dead fine roots were the most important factors in the TRF. Variations in the soil CO2 and CH4 caused by land-use transition were individually explained by soil temperature and fine root growth and decomposition, respectively. The results show that land-use change varied the soil CH4 and CO2 emission dynamics and drivers by the variation of soil environmental and plant's factors.

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Premise Wetland plants regularly experience physiological stresses resulting from inundation; however, plant responses to the interacting effects of water level and inundation duration are not fully understood. Methods We conducted a mesocosm experiment on two wetland species, sawgrass (Cladium jamaicense) and muhly grass (Muhlenbergia filipes), that co-dominate many freshwater wetlands in the Florida Everglades. We tracked photosynthesis, respiration, and growth at water levels of −10 (control), 10 (shallow), and 35 cm (deep) with reference to soil surface over 6 months. Results The response of photosynthesis to inundation was nonlinear. Specifically, photosynthetic capacity (Amax) declined by 25% in sawgrass and by 70% in muhly grass after 1–2 months of inundation. After 4 months, Amax of muhly grass in the deep-water treatment declined to near zero. Inundated sawgrass maintained similar leaf respiration and growth rates as the control, whereas inundated muhly grass suppressed both respiration and growth. At the end of the experiment, sawgrass had similar nonstructural carbohydrate pools in all treatments. By contrast, muhly grass in the deep-water treatment had largely depleted sugar reserves but maintained a similar starch pool as the control, which is critical for post-stress recovery. Conclusions Overall, the two species exhibited nonlinear and contrasting patterns of carbon uptake and use under inundation stress, which ultimately defines their strategies of surviving regularly flooded habitats. The results suggest that a future scenario with more intensive inundation, due to the water management and climate change, may weaken the dominance of muhly grass in many freshwater wetlands of the Everglades.

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How aquatic primary productivity influences the carbon (C) sequestering capacity of wetlands is uncertain. We evaluated the magnitude and variability in aquatic C dynamics and compared them to net ecosystem CO2 exchange (NEE) and ecosystem respiration (Reco) rates within calcareous freshwater wetlands in Everglades National Park. We continuously recorded 30-min measurements of dissolved oxygen (DO), water level, water temperature (Twater), and photosynthetically active radiation (PAR). These measurements were coupled with ecosystem CO2 fluxes over 5 years (2012–2016) in a long-hydroperiod peat-rich, freshwater marsh and a short-hydroperiod, freshwater marl prairie. Daily net aquatic primary productivity (NAPP) rates indicated both wetlands were generally net heterotrophic. Gross aquatic primary productivity (GAPP) ranged from 0 to − 6.3 g C m−2 day−1 and aquatic respiration (RAq) from 0 to 6.13 g C m−2 day−1. Nonlinear interactions between water level, Twater, and GAPP and RAq resulted in high variability in NAPP that contributed to NEE. Net aquatic primary productivity accounted for 4–5% of the deviance explained in NEE rates. With respect to the flux magnitude, daily NAPP was a greater proportion of daily NEE at the long-hydroperiod site (mean = 95%) compared to the short-hydroperiod site (mean = 64%). Although we have confirmed the significant contribution of NAPP to NEE in both long- and short-hydroperiod freshwater wetlands, the decoupling of the aquatic and ecosystem fluxes could largely depend on emergent vegetation, the carbonate cycle, and the lateral C flux.

Sammendrag

Forests have climate change mitigation potential since they sequester carbon. However, their carbon sink strength might depend on management. As a result of the balance between CO2 uptake and emission, forest net ecosystem exchange (NEE) reaches optimal values (maximum sink strength) at young stand ages, followed by a gradual NEE decline over many years. Traditionally, this peak of NEE is believed to be concurrent with the peak of primary production (e.g., gross primary production, GPP); however, in theory, this concurrence may potentially vary depending on tree species, site conditions and the patterns of ecosystem respiration (Reco). In this study, we used eddy-covariance (EC)-based CO2 flux measurements from 8 forest sites that are dominated by Norway spruce (Picea abies L.) and built machine learning models to find the optimal age of ecosystem productivity and that of CO2 sequestration. We found that the net CO2 uptake of Norway spruce forests peaked at ages of 30-40 yrs. Surprisingly, this NEE peak did not overlap with the peak of GPP, which appeared later at ages of 60-90 yrs. The mismatch between NEE and GPP was a result of the Reco increase that lagged behind the GPP increase associated with the tree growth at early age. Moreover, we also found that newly planted Norway spruce stands had a high probability (up to 90%) of being a C source in the first year, while, at an age as young as 5 yrs, they were likely to be a sink already. Further, using common climate change scenarios, our model results suggest that net CO2 uptake of Norway spruce forests will increase under the future climate with young stands in the high latitude areas being more beneficial. Overall, the results suggest that forest management practices should consider NEE and forest productivity separately and harvests should be performed only after the optimal ages of both the CO2 sequestration and productivity to gain full ecological and economic benefits. How to cite: Zhao, J., Lange, H., and Meissner, H.: Mismatch between the optimal ages for ecosystem productivity and net CO2 sequestration in Norway spruce forests, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4257, https://doi.org/10.5194/egusphere-egu21-4257, 2021.

Sammendrag

In a young Norway spruce stand (planted in 2012) at Hoxmark, Southeast Norway, Net Ecosystem Exchange (NEE) was measured using Eddy Covariance. The data were carefully processed with time-dependent stand parameters (i.e. canopy height), a detailed footprint analysis and calculated at 30 min temporal resolution. Photosynthetic Active Radiation (PAR) as the primary driver for carbon uptake was also available at the site. Despite its young age, the plantation already acted as a net carbon sink according to the annual NEE budget, e.g. by ca. 300 g C m-2 in 2019. However, the response of the system depended strongly on hydrometeorological conditions. We demonstrate this by investigating the relationship between NEE and PAR for this system in a temporally local fashion (30 days moving windows), using a Michaelis-Menten approach involving three parameters. Although the regression captured up to ca. 80% of the variance, the parameter estimates differed substantially throughout the season, and were contrasting between the very dry year 2018 and the close to normal year 2019. Comparison with other EC-equipped sites in a future study will clarify whether this variable sensitivity is due to the young age or is a pattern pertaining also to mature spruce stands. https://doi.org/10.5194/egusphere-egu21-5028

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In order to predict the effects of climate change on the global carbon cycle, it is crucial to understand the environmental factors that affect soil carbon storage in grasslands. In the present study, we attempted to explain the relationships between the distribution of soil carbon storage with climate, soil types, soil properties and topographical factors across different types of grasslands with different grazing regimes. We measured soil organic carbon in 92 locations at different soil depth increments, from 0 to 100 cm in southwestern China. Among soil types, brown earth soils (Luvisols) had the highest carbon storage with 19.5 ± 2.5 kg m−2, while chernozem soils had the lowest with 6.8 ± 1.2 kg m−2. Mean annual temperature and precipitation, exerted a significant, but, contrasting effects on soil carbon storage. Soil carbon storage increased as mean annual temperature decreased and as mean annual precipitation increased. Across different grassland types, the mean carbon storage for the top 100 cm varied from 7.6 ± 1.3 kg m−2 for temperate desert to 17.3 ± 2.9 kg m−2 for alpine meadow. Grazing/cutting regimes significantly affected soil carbon storage with lowest value (7.9 ± 1.5 kg m−2) recorded for cutting grass, while seasonal (11.4 ± 1.3 kg m−2) and year-long (12.2 ± 1.9 kg m−2) grazing increased carbon storage. The highest carbon storage was found in the completely ungrazed areas (16.7 ± 2.9 kg m−2). Climatic factors, along with soil types and topographical factors, controlled soil carbon density along a soil depth in grasslands. Environmental factors alone explained about 60% of the total variation in soil carbon storage. The actual depth-wise distribution of soil carbon contents was significantly influenced by the grazing intensity and topographical factors. Overall, policy-makers should focus on reducing the grazing intensity and land conversion for the sustainable management of grasslands and C sequestration.

Sammendrag

Soil respiration is an important ecosystem process that releases carbon dioxide into the atmosphere. While soil respiration can be measured continuously at high temporal resolutions, gaps in the dataset are inevitable, leading to uncertainties in carbon budget estimations. Therefore, robust methods used to fill the gaps are needed. The process-based non-linear least squares (NLS) regression is the most widely used gap-filling method, which utilizes the established relationship between the soil respiration and temperature. In addition to NLS, we also implemented three other methods based on: 1) artificial neural networks (ANN), driven by temperature and moisture measurements, 2) singular spectrum analysis (SSA), relying only on the time series itself, and 3) the expectation-maximization (EM) approach, referencing to parallel flux measurements in the spatial vicinity. Six soil respiration datasets (2017–2019) from two boreal forests were used for benchmarking. Artificial gaps were randomly introduced into the datasets and then filled using the four methods. The time-series-based methods, SSA and EM, showed higher accuracies than NLS and ANN in small gaps (<1 day). In larger gaps (15 days), the performance was similar among NLS, SSA and EM; however, ANN showed large errors in gaps that coincided with precipitation events. Compared to the observations, gap-filled data by SSA showed similar degree of variances and those filled by EM were associated with similar first-order autocorrelation coefficients. In contrast, data filled by both NLS and ANN exhibited lower variance and higher autocorrelation than the observations. For estimations of the annual soil respiration budget, NLS, SSA and EM resulted in errors between −3.7% and 5.8% given the budgets ranged from 463 to 1152 g C m−2 year−1, while ANN exhibited larger errors from −11.3 to 16.0%. Our study highlights the two time-series-based methods which showed great potential in gap-filling carbon flux data, especially when environmental variables are unavailable.

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The measurement network Integrated Carbon Observation System (ICOS) is dedicated to the quantification of fluxes of CO2, H2O, N2O and CH4 at the boundary between vegetation surfaces and the lower atmosphere. The implementation of observations sites follows strict protocols and a challenging labelling process to ensure standardized intercomparable observations. We report on our experiences in attempting to establish the only Norwegian ICOS Ecosystem site thus far, NO-Hur, located in an old-growth spruce forest at Hurdal in Southeast Norway. NOHur is planned as a class 2 site, with the option to an upgrade to class 1 later. The instrumentation and sensors needed, the requirements for spatial homogeneity and a detailed analysis of a digital terrain model are presented. The current status of the tower construction, the preliminary measurements obtained with the existing ICOScertified equipment at a test site, and the plans for integrating the measurements operationally into the network are shown

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The measurement network Integrated Carbon Observation System (ICOS) is dedicated to the quantification of fluxes of CO2, H2O, N2O and CH4 at the boundary between vegetation surfaces and the lower atmosphere. The implementation of observations sites follows strict protocols and a challenging labelling process to ensure standardized intercomparable observations. We report on our experiences in attempting to establish the only Norwegian ICOS Ecosystem site thus far, NO-Hur, located in an old-growth spruce forest at Hurdal in Southeast Norway. NOHur is planned as a class 2 site, with the option to an upgrade to class 1 later. The instrumentation and sensors needed, the requirements for spatial homogeneity and a detailed analysis of a digital terrain model are presented. The current status of the tower construction, the preliminary measurements obtained with the existing ICOScertified equipment at a test site, and the plans for integrating the measurements operationally into the network are shown

Sammendrag

As the main drivers of climate change, greenhouse gas (e.g., CO2 and CH4) emissions have been monitored intensively across the globe. The static chamber is one of the most commonly used approaches for measuring greenhouse gas fluxes from ecosystems (e.g., stem/soil respiration, CH4 emission, etc.) because of its easy implementation, high accuracy and low cost (Pumpanen et al., 2004). To perform the measurements, a gas analyzer is usually used to measure the changes of greenhouse gas concentrations within a closed chamber that covers an area of interest (e.g., soil surface) over a certain period of time (usually several minutes). The flux rates (F) are then calculated from the recorded gas concentrations assuming that the changing rate is linear: F = vol/(R · T a · area) · dG/dt where vol is the volume of the chamber (l), R is the universal gas constant (l atm K-1 mol-1), Ta is the ambient temperature (K), area is the area of the chamber base (m2 ), and dG/dt is the rate of the measured gas concentration change over time t (ppm s-1) (i.e., the slope of the linear regression).

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Climate change has altered global precipitation patterns and has led to greater variation in hydrological conditions. Wetlands are important globally for their soil carbon storage. Given that wetland carbon processes are primarily driven by hydrology, a comprehensive understanding of the effect of inundation is needed. In this study, we evaluated the effect of water level (WL) and inundation duration (ID) on carbon dioxide (CO2) fluxes by analysing a 10‐year (2008–2017) eddy covariance dataset from a seasonally inundated freshwater marl prairie in the Everglades National Park. Both gross primary production (GPP) and ecosystem respiration (ER) rates showed declines under inundation. While GPP rates decreased almost linearly as WL and ID increased, ER rates were less responsive to WL increase beyond 30 cm and extended inundation periods. The unequal responses between GPP and ER caused a weaker net ecosystem CO2 sink strength as inundation intensity increased. Eventually, the ecosystem tended to become a net CO2 source on a daily basis when either WL exceeded 46 cm or inundation lasted longer than 7 months. Particularly, with an extended period of high‐WLs in 2016 (i.e., WL remained >40 cm for >9 months), the ecosystem became a CO2 source, as opposed to being a sink or neutral for CO2 in other years. Furthermore, the extreme inundation in 2016 was followed by a 4‐month postinundation period with lower net ecosystem CO2 uptake compared to other years. Given that inundation plays a key role in controlling ecosystem CO2 balance, we suggest that a future with more intensive inundation caused by climate change or water management activities can weaken the CO2 sink strength of the Everglades freshwater marl prairies and similar wetlands globally, creating a positive feedback to climate change.

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Many nonlinear methods of time series analysis require a minimal number of observations in the hundreds to thousands, which is not always easy to achieve for observations of environmental systems. Eddy Covariance (EC) measurements of the carbon exchange between the atmosphere and vegetation provide a noticeable exception. They are taken at high temporal resolution, typically at 20 Hz. This generates very long time series (many millions of data points) even for short measurement periods, rendering finite size effects unimportant. In this presentation, we investigate high-resolution raw data of 3D wind speed, CO2 concentrations, water vapor and temperature measured at a young forest plantation in Southeast Norway since July 2018. Guiding for the analysis is the gain or added value of the high resolution compared to more aggregated data, i.e. the scaling behavior of nonlinear properties of the time series. We present results of complexity analysis, Tarnopolski diagrams, q-Entropy, Hurst analysis, Empirical Mode Decomposition and Singular System Analysis. This provides detailed insights into the nature of dynamics of carbon fluxes across this system boundary at different temporal scales.