The presented protocol uses the eddy covariance method at non-typical locations, applicable to all types of short-canopy ecosystems with limited area, on a currently reforested windthrow site in Poland. Details of measuring site setup rules, flux calculations and quality control, and final result analysis, are described.
This protocol is an example of utilizing the eddy covariance (EC) technique to investigate spatially and temporally averaged net CO2 fluxes (net ecosystem production, NEP), in non-typical ecosystems, on a currently reforested windthrow area in Poland. After a tornado event, a relatively narrow “corridor” was created within surviving forest stands, which complicates such kind of experiments. The application of other measuring techniques, such as the chamber method, is even more difficult under these circumstances, because especially at the beginning, fallen trees and in general great heterogeneity of the site provide a challenging platform to perform flux measurements and then to properly upscale obtained results. In comparison with standard EC measurements carried out in untouched forests, the case of windthrow areas requires special consideration when it comes to the site location and data analysis in order to ensure their representativeness. Therefore, here we present a protocol of real-time, continuous CO2 flux measurements at a dynamically changing, non-ideal EC site, which includes (1) site location and instrumentation setup, (2) flux computation, (3) rigorous data filtering and quality control, and (4) gap filling and net fluxes partitioning into CO2 respiration and absorption. The main advantage of the described methodology is that it provides a detailed description of the experimental setup and measurement performance from scratch, which can be applied to other spatially limited ecosystems. It can also be viewed as a list of recommendations on how to deal with unconventional site operation, providing a description for non-specialists. Obtained quality-checked, gap filled, half-hour values of net CO2, as well as absorption and respiration fluxes, can be finally aggregated into daily, monthly, seasonal or annual totals.
Nowadays, the most commonly used technique in the atmosphere-land ecosystem carbon dioxide (CO2) exchange studies is the eddy covariance (EC) technique1. The EC method has been used for decades, and comprehensive descriptions of issues concerning all the methodological, technical and practical aspects have already been published2,3,4. Compared with other techniques used for similar purposes, the EC method allows for obtaining the spatially and temporally averaged net CO2 fluxes from automatic, point measurements that consider the contribution of all elements in complicated ecosystems, instead of laborious, manual measurements (e.g., chamber techniques) or the requirement of taking many samples1.
Among land ecosystems, forests play the most significant role in C cycling and many scientific activities have focused on investigating their CO2 cycle, carbon storage in woody biomass and their mutual relationships with changing climatic conditions by both direct measurement or modeling5. Many EC sites, including one of the longest flux records6, were set up above different types of forests7. Usually, the site location was carefully chosen before the measurements started, with the goal of the most homogenous and largest area possible. Although, in disturbed forest sites, such as windthrows, the number of EC measuring stations are still insufficient8,9,10. One reason is logistical difficulties in measuring site setup and, most of all, a small number of suddenly appearing locations. In order to obtain the most informative results at windthrow areas, it is crucial to start as soon as possible after such an incidental event, which may cause additional problems. In contrast to untouched forest sites, the EC measurements at windthrow sites are more challenging and can deviate from already established procedures3. Since some extreme wind phenomena create spatially limited areas, there is a need for a thoughtful measuring station location and careful data processing in order to derive as much reliable flux values as possible. Similar difficulties in EC method application have occurred (e.g., Finish studies performed above a long but narrow lake) where measured CO2 fluxes required rigorous data filtering11,12 in order to assure their spatial representativeness.
Hence, the presented protocol is an example of the use of the EC method at non-typical locations, designed not only for windthrow areas, but for all other types of short vegetation with the limited area (e.g., croplands situated between taller vegetation types). The biggest advantage of the proposed methodology is a general description of complicated procedures, requiring advanced knowledge, from the site location choice and instrumentation set up to the final outcome: a complete dataset of high-quality CO2 fluxes. The technical novelty of the measuring protocol is the use of a unique base construction for the EC system placement (e.g., tripod with a defined height that is a “mini- tower” with an adjustable, electrically operated mast, allowing changing the final height of sensors according to individual needs).
1. Site location and instrumentation setup
2. CO2 flux computation
3. Filtering and quality control of fluxes
4. Gap filling and net flux partitioning into CO2 respiration and absorption
One of the crucial steps in flux filtering and quality control at non-ideal EC sites is the assessment of the measured fluxes’ spatial representativeness. The simplest way to perform such analysis, given the fact that calculations were done using commercial, widely applied software, is to include measurements from desired area only, on the basis of wind direction and footprint estimations (see section 3.7). Thus, the wind rose plot, with a chosen wind direction and maximal acceptable extend of fluxes footprint, marked as shaded polygons, on the background of the satellite picture from the Tlen I site, is shown here as a visual representation of the analysis result (Figure 1).
In principle, wind speed and trace gas concentration are measured by the eddy covariance system, which are then used to compute net CO2 exchange fluxes (NEP). Raw flux values have to be then post-processed in order to exclude errors and low-quality data. Figure 2 shows the results of a filtering procedure on the example of one year of NEP fluxes measurements from the Tlen I windthrow site.
It should be noted that the proposed procedure of flux quality check and assurance resulted in substantial data loss, to a much greater extent than in typical EC sites. The reduction to acceptable NEP fluxes, relative to the previous stage, was similar in sections 3.6 and 3.7, while the smallest number of data points was discarded due to unfavorable weather conditions and instrument malfunctions (section 3.5). The last part of the quality assurance protocol (chosen footprint and wind direction sectors) yielded a final data coverage of only 1/3 of all raw NEP fluxes measured by EC. In general, step 3.7 is the most crucial part of the filtering procedure here, assuring that obtained fluxes represent the gas exchange of the investigated area.
High-quality NEP fluxes can be finally used to derive daily, monthly, seasonal or annual totals. However, they must be gap filled before each action. In Figure 3, the relationship between NEP fluxes, gap filled using two different approaches: process-based (FCRN) and statistical method (REddyProc), is shown.
The presented simple linear regression suggests that in general both techniques are comparable (statistically significant regression with r2=0.89) and thus can be used for NEP fluxes gap filling, giving satisfactorily similar results (the regression line slope equal 0.90, which suggest only 10% difference between gap filled fluxes on average). With only net CO2 flux values, nothing can be said about individual impacts of absorption (GPP) and respiration (Reco) processes. Therefore, along with gap filling, so-called flux partitioning procedure was realized as well, by use of the same two methods. Daily totals of Reco fluxes are presented in Figure 4 as examples of two different method performances in net CO2 fluxes partitioning.
The results of Reco flux computation with two different methods, although the same model of Reco vs T was used in both cases, are examples of a potential source of erroneous conclusions regarding a contribution of respiration to the overall NEP fluxes or consequently the absorption rates (GPP fluxes). However, it cannot be clearly indicated which method gives more reliable results without additional analysis in this manner. What can be done, in our opinion, is either plotting measured nighttime fluxes against modeled Reco fluxes to look over the differences, or to compare estimated values with respiration fluxes directly measured with other technique (e.g., chambers). The differences in modeled Reco fluxes between presented approaches may come from the fact, that in one method some parameters are set as constant, while in the other they are estimated. Even the ones, which do not change in both cases (as a reference temperature – Tref), were not the same in given example (in FCRN Tref = 283.25 K, while in REddyProc Tref = 288.15 K). It was done on purpose to make potential users realize that even such slight changes may result in significant discrepancies. The other issue is that a statistical approach is not able to fill big gaps successfully, which in the case of presented non-ideal EC site, where there was only 1/3 of measured fluxes left after filtering and quality check procedure, might be a reason for concern. We do not attempt to provide a “better solution” with this analysis, but rather present options. A more thorough investigation needs to be done in this case.
Figure 1: Wind rose plot on the background of the Tlen I site area. The blue shaded polygons represent the chosen wind direction and red shaded polygons within them show sectors of a circle with a radius of 200 m (maximal acceptable extend of fluxes footprint). Please click here to view a larger version of this figure.
Figure 2: The course of 30-min averaged NEP fluxes at each step of data filtering (described in the Protocol), on the background of unprocessed, raw NEP fluxes values. The relative number of data points remaining after each stage is given at the top of each plot. Please click here to view a larger version of this figure.
Figure 3: The relationship between NEP fluxes, gap filled with a process-based method (FCRN) and a statistical approach (REddyProc online tool), measured at Tlen I windthrow site. Please click here to view a larger version of this figure.
Figure 4: Daily ecosystem respiration (Reco) fluxes totals obtained from partitioning procedure, performed with a process-based method (FCRN) and a statistical approach (REddyProc online tool) at the Tlen I windthrow site. Please click here to view a larger version of this figure.
This protocol presents the eddy covariance (EC) method to be used at non-ideal sites (here a reforested windthrow site): site location and measuring infrastructure setup, net CO2 fluxes computation and post-processing, as well as some issues regarding gap filling and fluxes partitioning procedures.
Even though the EC technique is commonly used at many measuring sites around the world, most of them are non-disturbed ecosystems, where the design and the following data processing can be done according to standard solutions (e.g., FLUXNET or ICOS network protocols). Although, in such demanding and often spatially limited areas as windthrow sites, such experiments should be planned and performed with special caution. Additionally, in the long run, measurements at dynamically growing ecosystems would require a change in EC system height in the future, along with new vegetation growth and development. Therefore, we recommend using a unique base construction, which is an innovative “mini-tower” with an electrically operated, extendable mast. This technical solution allows meeting one of the basic requirements of the method itself: the EC system placement in a mixed boundary layer, without the need of reconstruction or instruments demounting, which may result in further data losses in already depleted dataset. Furthermore, the easily moving electrical mast also makes the sensors’ maintenance at the site a lot easier (e.g., when one needs to clean the optical path of the analyzer, the whole EC system can be brought down to desired, convenient height). Nevertheless, it must be noted, that increasing the height of the instrument’s placement will have consequences in the extension of an area of influence (flux footprint), which will further result in more data being excluded due to an insufficient flux footprint. In the worst-case scenario, the measured fluxes would probably no longer be representative for the investigated area or even the EC method requirements would not be met anymore.
The site location in a relatively homogeneous and flat terrain, as described in the Protocol, is the most desired option. Under such conditions, advection issues are generally neglected. However, if the area of interest is located on a hilly terrain, it must be taken into account in the measured flux analysis, which implies more advanced knowledge to be gained.
The suggested software (EddyPro) for flux calculation from the raw, high frequency data, is a free, complex and user-friendly tool, designed for EC flux computation. All embedded equations and corrections have the scientific background and corresponding references to the methods used are given15. Moreover, it is constantly adjusted and developed by specialists-scientists in order to implement the most current state of knowledge.
Once temporally averaged CO2 fluxes are computed, they need to be carefully processed in order to assure their high quality and representativeness. One of the prosaic sources of errors are disturbances in instruments’ operation: precipitation, pollen, dirt, ice deposition on gas analyzer window (open-path analyzer) or inside intake tube (enclosed- and closed-path analyzers), which affect CO2 fluxes measurements. Such events can also disrupt wind speed measurement to some extent (sonic anemometer). Thus, in this protocol, subsequent stages of NEP fluxes filtering were presented, in which the last step is of the biggest importance for the non-ideal, spatially limited sites. Even though the number of data points, after accounting for representative wind direction sectors and footprint, was very small (Figure 2), it must be remembered that it is crucial not to include “false” signals, coming from different areas than the ones we are interested in. In contrast to the first two steps, the above-mentioned flux filtering procedure (mainly wind direction constraints) is not commonly used in EC forest sites, since the undisturbed site location is usually chosen in a way to ensure the best representative area possible. Windthrow sites, on the other hand, appear as a result of unpredictable phenomena; therefore, some compromises have to be made in order to carry out EC measurements at these scientifically valuable areas. Unlike in this study, proposed footprint limits can have different values in different wind directions. It is also worth mentioning that there are other kinds of flux representativeness estimations than the one presented here (e.g., 2D footprint climatology approach32, which is free to use online and gives more complex results). In such complicated sites, this approach can be even more helpful in specifying the area of the greatest influence on the measured fluxes. However, to simplify post-processing of fluxes, calculated using chosen commercial software, it was decided to use only information given in its output files.
The weakest point of the protocol is the gap filling and flux partitioning description. The two suggested methods were individually developed by other specialists before and only implemented here as proposed techniques. What is more, the FCRN method requires much more contribution from the user since there is no ready tool to perform this procedure. The comparative analysis of corresponding gap filled (NEP) and partitioned fluxes (GPP and Reco), which might have been of a greater interest among potential users, require a more thorough investigation in order to be fully applicable (Figure 3 and Figure 4).
There is still a room for improvement regarding both the technical details of EC measurements and data processing presented in this protocol. One potential possibility is the fusion of processed-based and statistical method for data gap filling and partitioning (e.g., ReddyProc method for gap filling and then FCRN for fluxes partitioning), according to individual needs, or simply the use of neural networks approach.
The authors have nothing to disclose.
This research was supported by funding from General Directorate of the State Forests, Warsaw, Poland (project LAS, No OR-2717/27/11). We would like to express our gratitude to the entire research group from the Department of Meteorology, Poznan University of Life Sciences, Poland, involved in this protocol implementation and their help during creating its visual version.
Adjustable mast with metal rails and electric engine (24 V) | maszty.net | – | Alternative basic construction. To be designed and made by professionals |
EddyPro | LI-COR, Inc. | ver. 6.2.0. | Free commercial software for fluxes calculation. Available on a website: https://www.licor.com/env/products/eddy_covariance/software.html, on request |
Enclosed-path infrared gas analyzer | LI-COR, Inc. | LI-7200 | One of two instruments of the eddy covariance system (EC) used for CO2 fluxes measurements. Other types of fast analyzers (>10Hz sampling frequency) can be used |
REddyProc | – | – | Free software for EC fluxes gap filling and partitioning. Available on Max Planck Institute for Biogeochmistry: https://www.bgc-jena.mpg.de/bgi/index.php/Services/REddyProcWeb. Both online tool and R package are provided. |
Short aluminum tower base with concrete foundation | maszty.net | – | Alternative basic construction (pioneering solution). To be designed and made by professionals |
Sonic anemometer | Gill Instruments | Gill Windmaster | One of two instruments of the eddy covariance system (EC) used for wind speed measurements. Other types of three-dimensional sonic anemometers can be used |
Stainless-steel tripod | Campbel Scientific, Inc. | CM110 10 ft | The basic construction for eddy covariance (EC) system. Can be constructed by yourself- materials to be found in a hardware store |
Sunshine sensor | Delta-T Devices Ltd. | BF5 | One of the exemplary instruments for photosynthetic photon flux density measurements (PPFD). To be bought from several commercial companies. Remember to place it above the canopy, far from reflective surfaces. |
Thermistors | Campbel Scientific, Inc. | T107 | One of the exemplary instruments for soil temperature measurements. To be bought from several commercial companies. It is advisable to have a profile of soil temperature |
Thermohygrometer | Vaisala Oyj | HMP155 | One of the exemplary instruments for air temperature and humidity measurements. To be bought from several commercial companies. Remember to place it inside radiation shield at similar height as the EC system. |