Influence of nitrogen and soil physical characteristics on belowground carbon flux dynamics of woody plants

At ecosystem level soil respiration (Rs) represents the largest carbon (C) flux after gross primary productivity, being mainly generated by root respiration (autotrophic respiration, Ra) and soil microbial respiration (heterotrophic respiration, Rh). In the case of terrestrial ecosystems, soils contain the largest C-pool, storing twice the amount of C contained in plant biomass. Soil organic matter (SOM), representing the main C storage in soil, is decomposed by soil microbial community. This process produces CO2 which is mainly released as Rh. It is thus relevant to understand how microbial activity is influenced by environmental factors like soil temperature, soil moisture and nutrient availability, since part of the CO2 produced by Rh, directly increases atmospheric CO2 concentration and therefore affects the phenomenon of climate change. Among terrestrial ecosystems, agricultural fields have traditionally been considered as sources of atmospheric CO2. In agricultural ecosystems, in particular apple orchards, I identified the role of root density, soil temperature, soil moisture and nitrogen (N) availability on Rs and on its two components, Ra and Rh. To do so I applied different techniques to separate Rs in its two components, the ”regression technique” and the “trenching technique”. I also studied the response of Ra to different levels of N availability, distributed either in a uniform or localized way, in the case of Populus tremuloides trees. The results showed that Rs is mainly driven by soil temperature, to which it is positively correlated, that high levels of soil moisture have inhibiting effects, and that N has a negligible influence on total Rs, as well as on Ra. Further I found a negative response of Rh to high N availability, suggesting that microbial decomposition processes in the soil are inhibited by the presence of N. The contribution of Ra to Rs was of 37% on average.

Effect of different management intensities on natural and human-induced carbon fluxes in a golf course in northern Italy

Turfgrasses are ubiquitous in urban landscape and their role on carbon (C) cycle is increasing important also due to the considerable footprint related to their management practices. It is crucial to understand the mechanisms driving the C assimilation potential of these terrestrial ecosystems Several approaches have been proposed to assess C dynamics: micro-meteorological methods, small-chamber enclosure system (SC), chrono-sequence approach and various models. Natural and human-induced variables influence turfgrasses C fluxes. Species composition, environmental conditions, site characteristics, former land use and agronomic management are the most important factors considered in literature driving C sequestration potential. At the same time different approaches seem to influence C budget estimates. In order to study the effect of different management intensities on turfgrass, we estimated net ecosystem exchange (NEE) through a SC approach in a hole of a golf course in the province of Verona (Italy) for one year. The SC approach presented several advantages but also limits related to the measurement frequency, timing and duration overtime, and to the methodological errors connected to the measuring system. Daily CO2 fluxes changed according to the intensity of maintenance, likely due to different inputs and disturbances affecting biogeochemical cycles, combined also to the different leaf area index (LAI). The annual cumulative NEE decreased with the increase of the intensity of management. NEE was related to the seasonality of turfgrass, following temperatures and physiological activity. Generally on the growing season CO2 fluxes towards atmosphere exceeded C sequestered. The cumulative NEE showed a system near to a steady state for C dynamics. In the final part greenhouse gases (GHGs) emissions due to fossil fuel consumption for turfgrass upkeep were estimated, pinpointing that turfgrass may result a considerable C source. The C potential of trees and shrubs needs to be considered to obtain a complete budget.

Emerging contaminants in agricultural ecosystems: impact of selected pharmaceutical on water and soil ecology and pratical implications

Pharmaceuticals are useful tools to prevent and treat human and animal diseases. Following administration, a significant fraction of pharmaceuticals is excreted unaltered into faeces and urine and may enter the aquatic ecosystem and agricultural soil through irrigation with recycled water, constituting a significant source of emerging contaminants into the environment. Understanding major factors influencing their environmental fate is consequently needed to value the risk, reduce contamination, and set up bioremediation technologies. The antiviral drug Tamiflu (oseltamivir carboxylate, OC) has received recent attention due to the potential use as a first line defence against H5N1 and H1N1 influenza viruses. Research has shown that OC is not removed during conventional wastewater treatments, thus having the potential to enter surface water bodies. A series of laboratory experiments investigated the fate and the removal of OC in surface water systems in Italy and Japan and in a municipal wastewater treatment plant. A preliminary laboratory study investigated the persistence of the active antiviral drug in water samples from an irrigation canal in northern Italy (Canale Emiliano Romagnolo). After an initial rapid decrease, OC concentration slowly decreased during the remaining incubation period. Approximately 65% of the initial OC amount remained in water at the end of the 36-day incubation period. A negligible amount of OC was lost both from sterilized water and from sterilized water/sediment samples, suggesting a significant role of microbial degradation. Stimulating microbial processes by the addition of sediments resulted in reduced OC persistence. Presence of OC (1.5 μg mL-1) did not significantly affect the metabolic potential of the water microbial population, that was estimated by glyphosate and metolachlor mineralization. In contrast, OC caused an initial transient decrease in the size of the indigenous microbial population of water samples. A second laboratory study focused on basic processes governing the environmental fate of OC in surface water from two contrasting aquatic ecosystems of northern Italy, the River Po and the Venice Lagoon. Results of this study confirmed the potential of OC to persist in surface water. However, the addition of 5% of sediments resulted in rapid OC degradation. The estimated half-life of OC in water/sediment of the River Po was 15 days. After three weeks of incubation at 20 °C, more than 8% of 14C-OC evolved as 14CO2 from water/sediment samples of the River Po and Venice Lagoon. OC was moderately retained onto coarse sediments from the two sites. In water/sediment samples of the River Po and Venice Lagoon treated with 14C-OC, more than 30% of the 14C-residues remained water-extractable after three weeks of incubation. The low affinity of OC to sediments suggests that the presence of sediments would not reduce its bioavailability to microbial degradation. Another series of laboratory experiments investigated the fate and the removal of OC in two surface water ecosystems of Japan and in the municipal wastewater treatment plant of the city of Bologna, in Northern Italy. The persistence of OC in surface water ranged from non-detectable degradation to a half-life of 53 days. After 40 days, less than 3% of radiolabeled OC evolved as 14CO2. The presence of sediments (5%) led to a significant increase of OC degradation and of mineralization rates. A more intense mineralization was observed in samples of the wastewater treatment plant when applying a long incubation period (40 days). More precisely, 76% and 37% of the initial radioactivity applied as 14C-OC was recovered as 14CO2 from samples of the biological tank and effluent water, respectively. Two bacterial strains growing on OC as sole carbon source were isolated and used for its removal from synthetic medium and environmental samples, including surface water and wastewater. Inoculation of water and wastewater samples with the two OC-degrading strains showed that mineralization of OC was significantly higher in both inoculated water and wastewater, than in uninoculated controls. Denaturing gradient gel electrophoresis and quantitative PCR analysis showed that OC would not affect the microbial population of surface water and wastewater. The capacity of the ligninolytic fungus Phanerochaete chrysosporium to degrade a wide variety of environmentally persistent xenobiotics has been largely reported in literature. In a series of laboratory experiments, the efficiency of a formulation using P. chrysosporium was evaluated for the removal of selected pharmaceuticals from wastewater samples. Addition of the fungus to samples of the wastewater treatment plant of Bologna significantly increased (P < 0.05) the removal of OC and three antibiotics, erythromycin, sulfamethoxazole, and ciprofloxacin. Similar effects were also observed in effluent water. OC was the most persistent of the four pharmaceuticals. After 30 days of incubation, approximately two times more OC was removed in bioremediated samples than in controls. The highest removal efficiency of the formulation was observed with the antibiotic ciprofloxacin. The studies included environmental aspects of soil contamination with two emerging veterinary contaminants, such as doramectin and oxibendazole, wich are common parasitic treatments in cattle farms.

Modelling the effects of nitrogen deposition and carbon dioxide enrichment on forest carbon balance

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.

New techniques for the remote sensing of foliar nitrogen concentration in forest ecosystems.

During my Doctoral study I researched about the remote detection of canopy N concentration in forest stands, its potentials and problems, under many overlapping perspectives. The study consisted of three parts. In S. Rossore 2000 dataset analysis, I tested regressions between N concentration and NIR reflectances derived from different sources (field samples, airborne and satellite sensors). The analysis was further expanded using a larger dataset acquired in year 2009 as part of a new campaign funded by the ESA. In both cases, a good correlation was observed between Landsat NIR, using both TM (2009) and ETM+ (2000) imagery, and N concentration measured by a CHN elemental analyzer. Concerning airborne sensors I did not obtain the same good results, mainly because of the large FOV of the two instruments, and to the anisotropy of vegetation reflectance. We also tested the relation between ground based ASD measures and nitrogen concentration, obtaining really good results. Thus, I decided to expand my study to the regional level, focusing only on field and satellite measures. I analyzed a large dataset for the whole of Catalonia, Spain; MODIS imagery was used, in consideration of its spectral characteristics and despite its rather poor spatial resolution. Also in this case a regression between nitrogen concentration and reflectances was found, but not so good as in previous experiences. Moreover, vegetation type was found to play an important role in the observed relationship. We concluded that MODIS is not the most suitable satellite sensor in realities like Italy and Catalonia, which present a patchy and inhomogeneous vegetation cover; so it could be utilized for the parameterization of eco-physiological and biogeochemical models, but not for really local nitrogen estimate. Thus multispectral sensors similar to Landsat Thematic Mapper, with better spatial resolution, could be the most appropriate sensors to estimate N concentration.

Chemical, biochemical and microbiological indicators to assess soil quality in temperate agro-ecosystems

Soil is a critically important component of the earth’s biosphere. Developing agricultural production systems able to conserve soil quality is essential to guarantee the current and future capacity of soil to provide goods and services. This study investigates the potential of microbial and biochemical parameters to be used as early and sensitive soil quality indicators. Their ability to differentiate plots under contrasting fertilization regimes is evaluated based also on their sensitivity to seasonal fluctuations of environmental conditions and on their relationship with soil chemical parameters. Further, the study addresses some of the critical methodological aspects of microplate-based fluorimetric enzyme assays, in order to optimize assay conditions and evaluate their suitability to be used as a toll to asses soil quality. The study was based on a long-term field experiment established in 1966 in the Po valley (Italy). The soil was cropped with maize (Z. mays L.) and winter wheat (T. aestivum L.) and received no organic fertilization, crop residue or manure, in combination with increasing levels of mineral N fertilizer. The soil microbiota responded to manure amendment increasing it biomass and activity and changing its community composition. Crop residue effect was much more limited. Mineral N fertilization stimulated crop residue mineralization, shifted microbial community composition and influenced N and P cycling enzyme activities. Seasonal fluctuations of environmental factors affected the soil microbiota. However microbial and biochemical parameters seasonality did not hamper the identification of fertilization-induced effects. Soil microbial community abundance, function and composition appeared to be strongly related to soil organic matter content and composition, confirming the close link existing between these soil quality indicators. Microplate-based fluorimetric enzyme assays showed potential to be used as fast and throughput toll to asses soil quality, but required proper optimization of the assay conditions for a precise estimation of enzymes maximum potential activity.

Use of bioassays and biomarkers in Daphnia magna to assess the effect of pharmaceutical residuals in freshwater ecosystems

Widespread occurrence of pharmaceuticals residues has been reported in aquatic ecosystems. However, their toxic effects on aquatic biota remain unclear. Generally, the acute toxicity has been assessed in laboratory experiments, while chronic toxicity studies have rarely been performed. Of importance appears also the assessment of mixture effects, since pharmaceuticals never occur in waters alone. The aim of the present work is to evaluate acute and chronic toxic response in the crustacean Daphnia magna exposed to single pharmaceuticals and mixtures. We tested fluoxetine, a SSRI widely prescribed as antidepressant, and propranolol, a non selective β-adrenergic receptor-blocking agent used to treat hypertension. Acute immobilization and chronic reproduction tests were performed according to OECD guidelines 202 and 211, respectively. Single chemicals were first tested separately. Toxicity of binary mixtures was then assessed using a fixed ratio experimental design with concentrations based on Toxic Units. The conceptual model of Concentration Addition was adopted in this study, as we assumed that the mixture effect mirrors the sum of the single substances for compounds having similar mode of action. The MixTox statistical method was applied to analyze the experimental results. Results showed a significant deviation from CA model that indicated antagonism between chemicals in both the acute and the chronic mixture tests. The study was integrated assessing the effects of fluoxetine on a battery of biomarkers. We wanted to evaluate the organism biological vulnerability caused by low concentrations of pharmaceutical occurring in the aquatic environment. We assessed the acetylcholinesterase and glutathione s-transferase enzymatic activities and the malondialdehyde production. No treatment induced significant alteration of biomarkers with respect to the control. Biological assays and the MixTox model application proved to be useful tools for pharmaceutical risk assessment. Although promising, the application of biomarkers in Daphnia magna needs further elucidation.

Effects of N fertilization on forest trees and ecosystems: water use, WUE, growth

During my three academic years, I focused on the effects of N fertilization on growth and function of plants and forest stands. The study had the dual objective of estimating the effects of atmospheric N deposition and evaluating the potential management value of N fertilization itself. In particular, the analysis took into account the changes induced in water use and intrinsic transpiration efficiency (ITE), an aspect often overlooked in world literature but of great importance especially in Mediterranean environment, where the positive effects of N fertilization may be denied by the parallel increased transpiration and exacerbated water stress.

Distributed Smart City Services for Urban Ecosystems

A Smart City is a high-performance urban context, where citizens live independently and are more aware of the surrounding opportunities, thanks to forward-looking development of economy politics, governance, mobility and environment. ICT infrastructures play a key-role in this new research field being also a mean for society to allow new ideas to prosper and new, more efficient approaches to be developed. The aim of this work is to research and develop novel solutions, here called smart services, in order to solve several upcoming problems and known issues in urban areas and more in general in the modern society context. A specific focus is posed on smart governance and on privacy issues which have been arisen in the cellular age.

Geomorphological and statistical analysis on Ravenna dune fields changes, based on Terrestrial Laser Technology

Coastal sand dunes represent a richness first of all in terms of defense from the sea storms waves and the saltwater ingression; moreover these morphological elements constitute an unique ecosystem of transition between the sea and the land environment. The research about dune system is a strong part of the coastal sciences, since the last century. Nowadays this branch have assumed even more importance for two reasons: on one side the born of brand new technologies, especially related to the Remote Sensing, have increased the researcher possibilities; on the other side the intense urbanization of these days have strongly limited the dune possibilities of development and fragmented what was remaining from the last century. This is particularly true in the Ravenna area, where the industrialization united to the touristic economy and an intense subsidence, have left only few dune ridges residual still active. In this work three different foredune ridges, along the Ravenna coast, have been studied with Laser Scanner technology. This research didn’t limit to analyze volume or spatial difference, but try also to find new ways and new features to monitor this environment. Moreover the author planned a series of test to validate data from Terrestrial Laser Scanner (TLS), with the additional aim of finalize a methodology to test 3D survey accuracy. Data acquired by TLS were then applied on one hand to test some brand new applications, such as Digital Shore Line Analysis System (DSAS) and Computational Fluid Dynamics (CFD), to prove their efficacy in this field; on the other hand the author used TLS data to find any correlation with meteorological indexes (Forcing Factors), linked to sea and wind (Fryberger's method) applying statistical tools, such as the Principal Component Analysis (PCA).

Engineering Complex Computational Ecosystems

Self-organising pervasive ecosystems of devices are set to become a major vehicle for delivering infrastructure and end-user services. The inherent complexity of such systems poses new challenges to those who want to dominate it by applying the principles of engineering. The recent growth in number and distribution of devices with decent computational and communicational abilities, that suddenly accelerated with the massive diffusion of smartphones and tablets, is delivering a world with a much higher density of devices in space. Also, communication technologies seem to be focussing on short-range device-to-device (P2P) interactions, with technologies such as Bluetooth and Near-Field Communication gaining greater adoption. Locality and situatedness become key to providing the best possible experience to users, and the classic model of a centralised, enormously powerful server gathering and processing data becomes less and less efficient with device density. Accomplishing complex global tasks without a centralised controller responsible of aggregating data, however, is a challenging task. In particular, there is a local-to-global issue that makes the application of engineering principles challenging at least: designing device-local programs that, through interaction, guarantee a certain global service level. In this thesis, we first analyse the state of the art in coordination systems, then motivate the work by describing the main issues of pre-existing tools and practices and identifying the improvements that would benefit the design of such complex software ecosystems. The contribution can be divided in three main branches. First, we introduce a novel simulation toolchain for pervasive ecosystems, designed for allowing good expressiveness still retaining high performance. Second, we leverage existing coordination models and patterns in order to create new spatial structures. Third, we introduce a novel language, based on the existing ``Field Calculus'' and integrated with the aforementioned toolchain, designed to be usable for practical aggregate programming.

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.