3 resultados para forest ecosystem
em AMS Tesi di Dottorato - Alm@DL - Università di Bologna
Resumo:
Atmospheric CO2 concentration ([CO2]) has increased over the last 250 years, mainly due to human activities. Of total anthropogenic emissions, almost 31% has been sequestered by the terrestrial biosphere. A considerable contribution to this sink comes from temperate and boreal forest ecosystems of the northern hemisphere, which contain a large amount of carbon (C) stored as biomass and soil organic matter. Several potential drivers for this forest C sequestration have been proposed, including increasing atmospheric [CO2], temperature, nitrogen (N) deposition and changes in management practices. However, it is not known which of these drivers are most important. The overall aim of this thesis project was to develop a simple ecosystem model which explicitly incorporates our best understanding of the mechanisms by which these drivers affect forest C storage, and to use this model to investigate the sensitivity of the forest ecosystem to these drivers. I firstly developed a version of the Generic Decomposition and Yield (G’DAY) model to explicitly investigate the mechanisms leading to forest C sequestration following N deposition. Specifically, I modified the G’DAY model to include advances in understanding of C allocation, canopy N uptake, and leaf trait relationships. I also incorporated a simple forest management practice subroutine. Secondly, I investigated the effect of CO2 fertilization on forest productivity with relation to the soil N availability feedback. I modified the model to allow it to simulate short-term responses of deciduous forests to environmental drivers, and applied it to data from a large-scale forest Free-Air CO2 Enrichment (FACE) experiment. Finally, I used the model to investigate the combined effects of recent observed changes in atmospheric [CO2], N deposition, and climate on a European forest stand. The model developed in my thesis project was an effective tool for analysis of effects of environmental drivers on forest ecosystem C storage. Key results from model simulations include: (i) N availability has a major role in forest ecosystem C sequestration; (ii) atmospheric N deposition is an important driver of N availability on short and long time-scales; (iii) rising temperature increases C storage by enhancing soil N availability and (iv) increasing [CO2] significantly affects forest growth and C storage only when N availability is not limiting.
Resumo:
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.
Resumo:
Population growth in urban areas is a world-wide phenomenon. According to a recent United Nations report, over half of the world now lives in cities. Numerous health and environmental issues arise from this unprecedented urbanization. Recent studies have demonstrated the effectiveness of urban green spaces and the role they play in improving both the aesthetics and the quality of life of its residents. In particular, urban green spaces provide ecosystem services such as: urban air quality improvement by removing pollutants that can cause serious health problems, carbon storage, carbon sequestration and climate regulation through shading and evapotranspiration. Furthermore, epidemiological studies with controlled age, sex, marital and socio-economic status, have provided evidence of a positive relationship between green space and the life expectancy of senior citizens. However, there is little information on the role of public green spaces in mid-sized cities in northern Italy. To address this need, a study was conducted to assess the ecosystem services of urban green spaces in the city of Bolzano, South Tyrol, Italy. In particular, we quantified the cooling effect of urban trees and the hourly amount of pollution removed by the urban forest. The information was gathered using field data collected through local hourly air pollution readings, tree inventory and simulation models. During the study we quantified pollution removal for ozone, nitrogen dioxide, carbon monoxide and particulate matter (<10 microns). We estimated the above ground carbon stored and annually sequestered by the urban forest. Results have been compared to transportation CO2 emissions to determine the CO2 offset potential of urban streetscapes. Furthermore, we assessed commonly used methods for estimating carbon stored and sequestered by urban trees in the city of Bolzano. We also quantified ecosystem disservices such as hourly urban forest volatile organic compound emissions.