Evaluation of the "Advanced Canopy-Atmosphere Soil Algorithm" (ACASA) model performance using micrometeorological techniques

In recent years, climate change and global warming are important topics. Kyoto Conference participants agreed that the addition of carbon dioxide to the atmosphere by fossil fuel emissions, the removal of carbon dioxide by crops and natural ecosystems, and the effect of deforestation on carbon balance require future monitoring. This research was conducted as part of that effort and the main objective was to understand and quantify ecosystems capacity to absorb atmospheric carbon for planning long-term political action and sustainable development. This research project used Eddy Covariance measurements to monitor mass and energy fluxes in two different ecosystems: a natural ecosystem (Mediterranean maquis) and an agricultural ecosystem (wine grape vineyard). For this research we also used one of the more elaborate higher-order closure models for flux modelling: the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA) model. ACASA model flux outputs were compared with field measurements from three consecutive years (2004-2006) over Mediterranean maquis in North-western Sardinia, and for two different seven-day periods (2005) and about one month (2006) over a wine grape vineyard in Tuscany, near Montalcino, Italy. ACASA simulations were compared with measured fluxes of net radiation, sensible heat, latent heat, soil heat, and CO2 fluxes. Comparisons were evaluated using linear regression, root mean squared error, mean absolute error, and mean bias error. In general, model output matched well the observations. The use of ACASA model to predict energy and mass fluxes between the vegetation and atmosphere is promising and it could greatly improve our ability to estimate fluxes for use in carbon balance studies

Ecophysiological Responses to Rainfall Variability in Grassland and Forests Along a Latitudinal Gradient in Italy

In the Mediterranean region, ecosystems are severely affected by climate variability. The Italian Peninsula is a hot spot for biodiversity thanks to its heterogeneous landscape and the Mediterranean, Continental, and Alpine climates hosting a broad range of plant functional types along a limited latitudinal range from 40′ to 46′ N. In this study we applied a comparative approach integrating descriptive statistics, time series analysis, and multivariate techniques to answer the following questions: (i) do the climatic variables affect Gross Primary Productivity (GPP), Reco, Water Use Efficiency (WUE), and ET to a similar extent among different sites? (ii) Does a common response pattern exist among ecosystems along a latitudinal gradient in Italy? And, finally (iii) do these ecosystems respond synchronically to meteorological conditions or does a delayed response exist? Six sites along a latitudinal, altitudinal, and vegetational gradient from semi-arid (southern Italy), to a mountainous Mediterranean site (central Italy), and sub-humid wet Alpine sites (northern Italy) were considered. For each site, carbon and water fluxes, and meteorological data collected during two hydrologically-contrasting years (i.e., a dry and a wet year) were analyzed. Principal Component Analysis (PCA) was adopted to identify temporal and spatial variations in GPP, Ecosystem Respiration (Reco), WUE, and Evapotranspiration (ET). The model outlined differences among Mediterranean semi-arid, Mediterranean mountainous, and Alpine sites in response to contrasting precipitation regimes. GPP, Reco, WUE, and ET increased up to 16, 19, 25, and 28%, respectively in semi-arid Mediterranean sites and up to 15, 32, 15, and 11%, respectively in Alpine sites in the wet year compared to the dry year. Air temperature was revealed to be one of the most important variables affecting GPP, Reco, WUE, and ET in all the study sites. While relative air humidity was more important in southern Mediterranean sites, global radiation was more significant in northern Italy. Our work suggests that a realistic prediction of the main responses of Italian forests under climate change should also take in account delayed responses due to acclimation to abiotic stress or changing environmental conditions

Orientamenti per l'irrigazione del mirto

Preliminary observations on ecophysiology of Myrtus communis L. in cultural conditions are reported. Responses of plants to different moisture soil conditions were observed using the stem water potential methodology. Plants showed optimal ecophysiological behaviour under moderate stress condition. Stress symptoms appear only with very low soil moisture content. These first results show that this species requires only few water applications or regulated deficit irrigation

Ecophysiological Responses to Rainfall Variability in Grassland and Forests Along a Latitudinal Gradient in Italy

In the Mediterranean region, ecosystems are severely affected by climate variability. The Italian Peninsula is a hot spot for biodiversity thanks to its heterogeneous landscape and the Mediterranean, Continental, and Alpine climates hosting a broad range of plant functional types along a limited latitudinal range from 40\u2032 to 46\u2032 N. In this study we applied a comparative approach integrating descriptive statistics, time series analysis, and multivariate techniques to answer the following questions: (i) do the climatic variables affect Gross Primary Productivity (GPP), Reco, Water Use Efficiency (WUE), and ET to a similar extent among different sites? (ii) Does a common response pattern exist among ecosystems along a latitudinal gradient in Italy? And, finally (iii) do these ecosystems respond synchronically to meteorological conditions or does a delayed response exist? Six sites along a latitudinal, altitudinal, and vegetational gradient from semi-arid (southern Italy), to a mountainous Mediterranean site (central Italy), and sub-humid wet Alpine sites (northern Italy) were considered. For each site, carbon and water fluxes, and meteorological data collected during two hydrologically-contrasting years (i.e., a dry and a wet year) were analyzed. Principal Component Analysis (PCA) was adopted to identify temporal and spatial variations in GPP, Ecosystem Respiration (Reco), WUE, and Evapotranspiration (ET). The model outlined differences among Mediterranean semi-arid, Mediterranean mountainous, and Alpine sites in response to contrasting precipitation regimes. GPP, Reco, WUE, and ET increased up to 16, 19, 25, and 28%, respectively in semi-arid Mediterranean sites and up to 15, 32, 15, and 11%, respectively in Alpine sites in the wet year compared to the dry year. Air temperature was revealed to be one of the most important variables affecting GPP, Reco, WUE, and ET in all the study sites. While relative air humidity was more important in southern Mediterranean sites, global radiation was more significant in northern Italy. Our work suggests that a realistic prediction of the main responses of Italian forests under climate change should also take in account delayed responses due to acclimation to abiotic stress or changing environmental conditions

Modelling the biogenic CO2 exchange in urban and non-urban ecosystems through the assessment of light-response curve parameters

The biogenic CO2 surface atmosphere exchange is investigated and linked to vegetation cover fraction for seven sites (three urban and four non-urban) in the northern hemisphere. The non-rectangular hyperbola (NRH) is used to analyse the light-response curves during period of maximum ecophysiological processes, and to develop two models to simulate biogenic vertical CO2 fluxes. First, a generalised set of NRH coefficients is calculated after linear regression analysis across urban and non-urban ecosystems. Second, site-specific NRH coefficients are calculated for a suburban area in Helsinki, Finland. The model includes a temperature driven equation to estimate ecosystem respiration, and variation of leaf area index to modulate emissions across the year. Eddy covariance measured CO2 fluxes are used to evaluate the two models at the suburban Helsinki site and the generalised model also in Mediterranean ecosystem. Both models can simulate the mean daily trend at monthly and seasonal scales. Modelled data typically fall within the range of variability of the observations (differences of the order of 10%). Additional information improves the models performance, notably the selection of the most vegetated wind direction in Helsinki. The general model performs reasonably well during daytime but it tends to underestimate CO2 emissions at night. This reflects the model capability to catch photosynthesis processes occurring during the day, and the importance of the gross primary production (GPP) in modifying the net ecosystem exchange (NEE) of urban sites with different vegetation cover fraction. Therefore, the general model does not capture the differences in ecosystem respiration that skew nocturnal fluxes. The relation between the generalised NRH plateau parameter and vegetation cover improves (R-2 from 0.7 to 0.9) when only summer weekends with wind coming from the most vegetated sector in Helsinki and well-watered conditions for Mediterranean sites are included in the analysis. In the local model, the inclusion of a temperature driven equation for estimating the ecosystem respiration instead of a constant value, does not improve the long-term simulations. In conclusion, both the general and local models have significant potential and offer valid modelling options of biogenic components of carbon exchange in urban and non-urban ecosystems.(C) 2016 Elsevier B.V. All rights reserved.Peer reviewe

Il Modello ACASA per la stima degli scambi di carbonio negli ecosistemi mediterranei

L’attività di ricerca finalizzata allo sviluppo e alla validazione di modellistica avanzata per la contabilizzazione del bilancio del carbonio nei sistemi agrari e forestali nasce da una intensa collaborazione con l’Università della California. In particolare è in fase di studio il modello ACASA (Advanced Canopy-Atmosphere-Soil Algorithm), che è attualmente uno dei modelli del tipo soil-vegetation-atmosphere transfer (SVAT) più sofisticati. ACASA contiene equazioni differenziali di terzo ordine per simulare i flussi di energia e materia nella canopy (10 strati atmosferici all’interno e 10 al di sopra), mentre il suolo è suddiviso in 15 strati. Una combinazione delle equazioni di Ball-Berry e Farquhar è utilizzata per stimare il flusso di CO2. Il modello considera gli effetti dello stress idrico sulla traspirazione e sull’assimilazione della vegetazione

Advanced-Canopy-Atmosphere-Soil Algorithm (ACASA model) for estimating mass and energy fluxes

There is a recognized need to improve land surface models that simulate mass and energy fluxes between terrestrial ecosystems and atmosphere. In particular, long-term land planning strategies at local and regional scales require better understanding of agricultural ecosystem capacity to exchange CO2 and water. One of the more elaborate models for flux modelling is the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA) model (Pyles et al., 2000), which provides micro-scale and regional-scale fluxes. The ACASA model allows for characterization of energy and carbon fluxes. It is a higher-order closure model used to estimate fluxes and profiles of heat, water vapor, carbon and momentum within and above canopy using third-order closure equations. It also estimates turbulent profiles of velocity, temperature, humidity within and above canopy. The ACASA model estimates CO2 fluxes using a combination of Ball-Berry and Farquhar equations. In addition, the effects of water stress on stomata, transpiration and CO2 assimilation are considered. The model was mainly used over dense canopies (Pyles et al. 2000, 2003) in the past, so the aim of this work was to test the ACASA model over a sparse canopy for estimating mass and energy fluxes, comparing model output with field measurements taken over a vineyard located in Montalcino, Tuscany, Italy

Direct observations of CO2 emission reductions due to COVID-19 lockdown across European urban districts

The measures taken to contain the spread of COVID-19 in 2020 included restrictions of people's mobility and reductions in economic activities. These drastic changes in daily life, enforced through national lockdowns, led to abrupt reductions of anthropogenic CO(2 )emissions in urbanized areas all over the world. To examine the effect of social restrictions on local emissions of CO2, we analysed district level CO(2 )fluxes measured by the eddy-covariance technique from 13 stations in 11 European cities. The data span several years before the pandemic until October 2020 (six months after the pandemic began in Europe). All sites showed a reduction in CO2 emissions during the national lockdowns. The magnitude of these reductions varies in time and space, from city to city as well as between different areas of the same city. We found that, during the first lockdowns, urban CO2 emissions were cut with respect to the same period in previous years by 5% to 87% across the analysed districts, mainly as a result of limitations on mobility. However, as the restrictions were lifted in the following months, emissions quickly rebounded to their pre-COVID levels in the majority of sites.Peer reviewe