Carbon fluxes and allocation pattern in an apple orchard

Carbon fluxes and allocation pattern, and their relationship with the main environmental and physiological parameters, were studied in an apple orchard for one year (2010). I combined three widely used methods: eddy covariance, soil respiration and biometric measurements, and I applied a measurement protocol allowing a cross-check between C fluxes estimated using different methods. I attributed NPP components to standing biomass increment, detritus cycle and lateral export. The influence of environmental and physiological parameters on NEE, GPP and Reco was analyzed with a multiple regression model approach. I found that both NEP and GPP of the apple orchard were of similar magnitude to those of forests growing in similar climate conditions, while large differences occurred in the allocation pattern and in the fate of produced biomass. Apple production accounted for 49% of annual NPP, organic material (leaves, fine root litter, pruned wood and early fruit drop) contributing to detritus cycle was 46%, and only 5% went to standing biomass increment. The carbon use efficiency (CUE), with an annual average of 0.68 ± 0.10, was higher than the previously suggested constant values of 0.47-0.50. Light and leaf area index had the strongest influence on both NEE and GPP. On a diurnal basis, NEE and GPP reached their peak approximately at noon, while they appeared to be limited by high values of VPD and air temperature in the afternoon. The proposed models can be used to explain and simulate current relations between carbon fluxes and environmental parameters at daily and yearly time scale. On average, the annual NEP balanced the carbon annually exported with the harvested apples. These data support the hypothesis of a minimal or null impact of the apple orchard ecosystem on net C emission to the atmosphere.

Modelling biogeochemical cycles in forest ecosystems: a Bayesian approach

Forest models are tools for explaining and predicting the dynamics of forest ecosystems. They simulate forest behavior by integrating information on the underlying processes in trees, soil and atmosphere. Bayesian calibration is the application of probability theory to parameter estimation. It is a method, applicable to all models, that quantifies output uncertainty and identifies key parameters and variables. This study aims at testing the Bayesian procedure for calibration to different types of forest models, to evaluate their performances and the uncertainties associated with them. In particular,we aimed at 1) applying a Bayesian framework to calibrate forest models and test their performances in different biomes and different environmental conditions, 2) identifying and solve structure-related issues in simple models, and 3) identifying the advantages of additional information made available when calibrating forest models with a Bayesian approach. We applied the Bayesian framework to calibrate the Prelued model on eight Italian eddy-covariance sites in Chapter 2. The ability of Prelued to reproduce the estimated Gross Primary Productivity (GPP) was tested over contrasting natural vegetation types that represented a wide range of climatic and environmental conditions. The issues related to Prelued's multiplicative structure were the main topic of Chapter 3: several different MCMC-based procedures were applied within a Bayesian framework to calibrate the model, and their performances were compared. A more complex model was applied in Chapter 4, focusing on the application of the physiology-based model HYDRALL to the forest ecosystem of Lavarone (IT) to evaluate the importance of additional information in the calibration procedure and their impact on model performances, model uncertainties, and parameter estimation. Overall, the Bayesian technique proved to be an excellent and versatile tool to successfully calibrate forest models of different structure and complexity, on different kind and number of variables and with a different number of parameters involved.

Measurements and modeling of ozone fluxes in and above Norway spruce canopies

Ozon (O3) ist ein wichtiges Oxidierungs- und Treibhausgas in der Erdatmosphäre. Es hat Einfluss auf das Klima, die Luftqualität sowie auf die menschliche Gesundheit und die Vegetation. Ökosysteme, wie beispielsweise Wälder, sind Senken für troposphärisches Ozon und werden in Zukunft, bedingt durch Stürme, Pflanzenschädlinge und Änderungen in der Landnutzung, heterogener sein. Es ist anzunehmen, dass diese Heterogenitäten die Aufnahme von Treibhausgasen verringern und signifikante Rückkopplungen auf das Klimasystem bewirken werden. Beeinflusst wird der Atmosphären-Biosphären-Austausch von Ozon durch stomatäre Aufnahme, Deposition auf Pflanzenoberflächen und Böden sowie chemische Umwandlungen. Diese Prozesse zu verstehen und den Ozonaustausch für verschiedene Ökosysteme zu quantifizieren sind Voraussetzungen, um von lokalen Messungen auf regionale Ozonflüsse zu schließen.rnFür die Messung von vertikalen turbulenten Ozonflüssen wird die Eddy Kovarianz Methode genutzt. Die Verwendung von Eddy Kovarianz Systemen mit geschlossenem Pfad, basierend auf schnellen Chemilumineszenz-Ozonsensoren, kann zu Fehlern in der Flussmessung führen. Ein direkter Vergleich von nebeneinander angebrachten Ozonsensoren ermöglichte es einen Einblick in die Faktoren zu erhalten, die die Genauigkeit der Messungen beeinflussen. Systematische Unterschiede zwischen einzelnen Sensoren und der Einfluss von unterschiedlichen Längen des Einlassschlauches wurden untersucht, indem Frequenzspektren analysiert und Korrekturfaktoren für die Ozonflüsse bestimmt wurden. Die experimentell bestimmten Korrekturfaktoren zeigten keinen signifikanten Unterschied zu Korrekturfaktoren, die mithilfe von theoretischen Transferfunktionen bestimmt wurden, wodurch die Anwendbarkeit der theoretisch ermittelten Faktoren zur Korrektur von Ozonflüssen bestätigt wurde.rnIm Sommer 2011 wurden im Rahmen des EGER (ExchanGE processes in mountainous Regions) Projektes Messungen durchgeführt, um zu einem besseren Verständnis des Atmosphären-Biosphären Ozonaustauschs in gestörten Ökosystemen beizutragen. Ozonflüsse wurden auf beiden Seiten einer Waldkante gemessen, die einen Fichtenwald und einen Windwurf trennt. Auf der straßenähnlichen Freifläche, die durch den Sturm "Kyrill" (2007) entstand, entwickelte sich eine Sekundärvegetation, die sich in ihrer Phänologie und Blattphysiologie vom ursprünglich vorherrschenden Fichtenwald unterschied. Der mittlere nächtliche Fluss über dem Fichtenwald war -6 bis -7 nmol m2 s-1 und nahm auf -13 nmol m2 s-1 um die Mittagszeit ab. Die Ozonflüsse zeigten eine deutliche Beziehung zur Pflanzenverdunstung und CO2 Aufnahme, was darauf hinwies, dass während des Tages der Großteil des Ozons von den Pflanzenstomata aufgenommen wurde. Die relativ hohe nächtliche Deposition wurde durch nicht-stomatäre Prozesse verursacht. Die Deposition über dem Wald war im gesamten Tagesverlauf in etwa doppelt so hoch wie über der Freifläche. Dieses Verhältnis stimmte mit dem Verhältnis des Pflanzenflächenindex (PAI) überein. Die Störung des Ökosystems verringerte somit die Fähigkeit des Bewuchses, als Senke für troposphärisches Ozon zu fungieren. Der deutliche Unterschied der Ozonflüsse der beiden Bewuchsarten verdeutlichte die Herausforderung bei der Regionalisierung von Ozonflüssen in heterogen bewaldeten Gebieten.rnDie gemessenen Flüsse wurden darüber hinaus mit Simulationen verglichen, die mit dem Chemiemodell MLC-CHEM durchgeführt wurden. Um das Modell bezüglich der Berechnung von Ozonflüssen zu evaluieren, wurden gemessene und modellierte Flüsse von zwei Positionen im EGER-Gebiet verwendet. Obwohl die Größenordnung der Flüsse übereinstimmte, zeigten die Ergebnisse eine signifikante Differenz zwischen gemessenen und modellierten Flüssen. Zudem gab es eine klare Abhängigkeit der Differenz von der relativen Feuchte, mit abnehmender Differenz bei zunehmender Feuchte, was zeigte, dass das Modell vor einer Verwendung für umfangreiche Studien des Ozonflusses weiterer Verbesserungen bedarf.rn

Estimating Annual CO2 Flux for Lutjewad Station Using Three Different Gap-Filling Techniques

Long-term measurements of CO2 flux can be obtained using the eddy covariance technique, but these datasets are affected by gaps which hinder the estimation of robust long-term means and annual ecosystem exchanges. We compare results obtained using three gap-fill techniques: multiple regression (MR), multiple imputation (MI), and artificial neural networks (ANNs), applied to a one-year dataset of hourly CO2 flux measurements collected in Lutjewad, over a flat agriculture area near the Wadden Sea dike in the north of the Netherlands. The dataset was separated in two subsets: a learning and a validation set. The performances of gap-filling techniques were analysed by calculating statistical criteria: coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), maximum absolute error (MaxAE), and mean square bias (MSB). The gap-fill accuracy is seasonally dependent, with better results in cold seasons. The highest accuracy is obtained using ANN technique which is also less sensitive to environmental/seasonal conditions. We argue that filling gaps directly on measured CO2 fluxes is more advantageous than the common method of filling gaps on calculated net ecosystem change, because ANN is an empirical method and smaller scatter is expected when gap filling is applied directly to measurements.

Pasture degradation modifies the water and carbon cycles of the Tibetan highlands

The Tibetan Plateau has a significant role with regard to atmospheric circulation and the monsoon in particular. Changes between a closed plant cover and open bare soil are one of the striking effects of land use degradation observed with unsustainable range management or climate change, but experiments investigating changes of surface properties and processes together with atmospheric feedbacks are rare and have not been undertaken in the world's two largest alpine ecosystems, the alpine steppe and the Kobresia pygmaea pastures of the Tibetan Plateau. We connected measurements of micro-lysimeter, chamber, 13C labelling, and eddy covariance and combined the observations with land surface and atmospheric models, adapted to the highland conditions. This allowed us to analyse how three degradation stages affect the water and carbon cycle of pastures on the landscape scale within the core region of the Kobresia pygmaea ecosystem. The study revealed that increasing degradation of the Kobresia turf affects carbon allocation and strongly reduces the carbon uptake, compromising the function of Kobresia pastures as a carbon sink. Pasture degradation leads to a shift from transpiration to evaporation while a change in the sum of evapotranspiration over a longer period cannot be confirmed. The results show an earlier onset of convection and cloud generation, likely triggered by a shift in evapotranspiration timing when dominated by evaporation. Consequently, precipitation starts earlier and clouds decrease the incoming solar radiation. In summary, the changes in surface properties by pasture degradation found on the highland have a significant influence on larger scales.

Isotopic composition of water in fog, rain, throughfall and stemflow in the Monte Verde, Costa Rica

Fog deposition, precipitation, throughfall and stemflow were measured in a windward tropical montane cloud forest near Monteverde, Costa Rica, for a 65-day period during the dry season of 2003. Net fog deposition was measured directly using the eddy covariance (EC) method and it amounted to 1.2 ± 0.1 mm/day (mean ± standard error). Fog water deposition was 5-9% of incident rainfall for the entire period, which is at the low end of previously reported values. Stable isotope concentrations (d18O and d2H) were determined in a large number of samples of each water component. Mass balance-based estimates of fog deposition were 1.0 ± 0.3 and 5.0 ± 2.7 mm/day (mean ± SE) when d18O and d2H were used as tracer, respectively. Comparisons between direct fog deposition measurements and the results of the mass balance model using d18O as a tracer indicated that the latter might be a good tool to estimate fog deposition in the absence of direct measurement under many (but not all) conditions. At 506 mm, measured water inputs over the 65 days (fog plus rain) fell short by 46 mm compared to the canopy output of 552 mm (throughfall, stemflow and interception evaporation). This discrepancy is attributed to the underestimation of rainfall during conditions of high wind.

ERA-interim reanalysis debiased at FLUXNET sites

(preliminary) Exchanges of carbon, water and energy between the land surface and the atmosphere are monitored by eddy covariance technique at the ecosystem level. Currently, the FLUXNET database contains more than 500 sites registered and up to 250 of them sharing data (Free Fair Use dataset). Many modelling groups use the FLUXNET dataset for evaluating ecosystem model's performances but it requires uninterrupted time series for the meteorological variables used as input. Because original in-situ data often contain gaps, from very short (few hours) up to relatively long (some months), we develop a new and robust method for filling the gaps in meteorological data measured at site level. Our approach has the benefit of making use of continuous data available globally (ERA-interim) and high temporal resolution spanning from 1989 to today. These data are however not measured at site level and for this reason a method to downscale and correct the ERA-interim data is needed. We apply this method on the level 4 data (L4) from the LaThuile collection, freely available after registration under a Fair-Use policy. The performances of the developed method vary across sites and are also function of the meteorological variable. On average overall sites, the bias correction leads to cancel from 10% to 36% of the initial mismatch between in-situ and ERA-interim data, depending of the meteorological variable considered. In comparison to the internal variability of the in-situ data, the root mean square error (RMSE) between the in-situ data and the un-biased ERA-I data remains relatively large (on average overall sites, from 27% to 76% of the standard deviation of in-situ data, depending of the meteorological variable considered). The performance of the method remains low for the Wind Speed field, in particular regarding its capacity to conserve a standard deviation similar to the one measured at FLUXNET stations.

Carbon pools and fluxes measured during a field campaign conducted in 2010 on the Tibetan Plateau at Kema

The Tibetan highlands host the largest alpine grassland ecosystems worldwide, bearing soils that store substantial stocks of carbon (C) that are very sensitive to land use changes. This study focuses on the cycling of photoassimilated C within a Kobresia pygmaea pasture, the dominating ecosystems on the Tibetan highlands. We investigated short-term effects of grazing cessation and the role of the characteristic Kobresia root turf on C fluxes and belowground C turnover. By combining eddy-covariance measurements with 13CO2 pulse labeling we applied a powerful new approach to measure absolute fluxes of assimilates within and between various pools of the plant-soil-atmosphere system. The roots and soil each store roughly 50% of the overall C in the system (76 Mg C/ha), with only a minor contribution from shoots, which is also expressed in the root:shoot ratio of 90. During June and July the pasture acted as a weak C sink with a strong uptake of approximately 2 g C/m**2/ in the first half of July. The root turf was the main compartment for the turnover of photoassimilates, with a subset of highly dynamic roots (mean residence time 20 days), and plays a key role for the C cycling and C storage in this ecosystem. The short-term grazing cessation only affected aboveground biomass but not ecosystem scale C exchange or assimilate allocation into roots and soil.

Water balance measurements on Samoylov Island during campaign Lena2011

The summer water balance of a typical Siberian polygonal tundra catchment is investigated in order to identify the spatial and temporal dynamics of its main hydrological processes. The results show that, besides precipitation and evapotranspiration, lateral flow considerably influences the site-specific hydrological conditions. The prominent microtopography of the polygonal tundra strongly controls lateral flow and storage behaviour of the investigated catchment. Intact rims of low-centred polygons build hydrological barriers, which release storage water later in summer than polygons with degraded rims and troughs above degraded ice wedges. The barrier function of rims is strongly controlled by soil thaw, which opens new subsurface flow paths and increases subsurface hydrological connectivity. Therefore, soil thaw dynamics determine the magnitude and timing of subsurface outflow and the redistribution of storage within the catchment. Hydraulic conductivities in the elevated polygonal rims sharply decrease with the transition from organic to mineral layers. This interface causes a rapid shallow subsurface drainage of rainwater towards the depressed polygon centres and troughs. The re-release of storage water from the centres through deeper and less conductive layers helps maintain a high water table in the surface drainage network of troughs throughout the summer.