Assessment of different components of the Carbon flux in forest and agricultural ecosystems using remote sensing data and field measurements

Resumo

The assessment of carbon cycle in the ecosystems is essential for studying climate change. The two main components of the carbon cycle are Gross Primary Production (GPP) and Soil Respiration (Rs). The first one represents the carbon uptake of ecosystems through photosynthesis and it is the largest flux of the global carbon balance. The second one is the most important source of CO2 in most ecosystems. The high spatial and temporal variability of these fluxes can make forest and agricultural ecosystems behave as a sink or as a source of CO2 over the years depending on the interaction of meteorological and ecological factors. Therefore, developing suitable methods and techniques for estimating GPP and Rs are crucial to obtain accurate estimations. The main objective of this thesis is to assess these two main components of the carbon cycle in agricultural and forest ecosystems by new remote sensing and field techniques. This objective has been carried out with four experiments, two assessing Rs in agroecosystems and two assessing GPP in forest ecosystems. In the first study total soil respiration (Rs) and its autotrophic component (Ra) were assessed through spectral information acquired by field spectroscopy in a row irrigated corn crop (Zea mays L.) throughout the growing period. The relationships between Rs and Ra with leaf area index (LAI), spectral indexes and abiotic factors (soil moisture and soil temperature) were assessed by linear regression models. Results showed that Spectral indexes contain significant functional information, beyond mere structural changes, that could be related to Rs and Ra. However, specific models should be applied for the different phenological stages and there is a need to be cautious when upscaling remote sensing models. The aim of the second study was to assess Rs linked to crop phenology of a rainfed barley crop throughout two seasons based on spectral indices calculated from field spectroscopy data. The relationships between Rs, Leaf Area Index (LAI) and spectral indices were assessed by linear regression models with the adjusted coefficient of determination. Results showed that most of the spectral indices provided better information than LAI throughout the studied period and that soil moisture and temperature were relevant variables in specific periods. During vegetative stages, indices based on the visible (VIS) region showed the best relationship with Rs. On the other hand, during reproductive stages indices containing the near infrared-shortwave infrared (NIR-SWIR) spectral region and those related to water content showed the highest relationship. The inter-annual variability found in Mediterranean regions was also observed in the estimated ratio of carbon emission to carbon fixation between years. Our results show the potential capability of spectral information to assess soil respiration linked to crop phenology across several temporal and spatial scales. In the third work, our overall objective was to assess the GPP dynamics of a Dehesa ecosystem in Central Spain by analysing the time series (2004–2008) of two models: (1) GPP provided by remote sensing images from the MODIS sensor (MOD17A2 product); and (2) GPP estimated by the implementation of a site-specific light use efficiency model taking into account local ecological and meteorological parameters. Both models were compared to the production provided by an eddy covariance flux tower located in our study area. Our results indicated that both models of GPP showed a typical Dehesa dynamic where there are primarily two layers, the arboreal and the herbaceous strata. However, MODIS underestimates the production of the dehesa in a Mediterranean climate due to the different ecological and meteorological parameters used in the MODIS model. Finally, the Granger causality tests indicate that GPP prediction can be improved by including precipitation or soil water in the models. In the last work, our overall objective was to assess the GPP dynamics and the energy partitioning patterns in three different European forest ecosystems by time series analysis. Results show that temperature and solar radiation were the main limiting factors in the Evergreen Needleleaf forest of Finland while water availability was determinant for growth in the Mediterranean Dehesa ecosystem. The Deciduous Broadleaf Forest in Denmark showed a different GPP cycle related with an interaction of various factors during all the growing season. In Finland, latent heat was coupled to GPP during all growing season due to the factor of temperature while in Denmark began to be strongly coupled when leaf emergence occurred. In Spain, latent heat was coupled to GPP during all growing season conditioned by water availability. The vegetation dynamics of the three ecosystems were directly responsible for the energy fluxes partitioning and water fluxes dynamics providing a feedback to atmosphere influencing the energy partitioning in a different way. Results from this thesis show the capacity of new methods to measure and estimate soil respiration and Gross Primary Production in different forest and agricultural ecosystems at different spatial and temporal scales. Further research is needed to improve the estimations of these two components of the carbon cycle and to assess the role of ecosystems in the climate change.