Assessing crop coefficients for natural vegetated areas using satellite data and eddy covariance stations

The Food and Agricultural Organization (FAO) method for potential evapotranspiration assessment is based on the crop coefficient, which allows one to relate the reference evapotranspiration of well irrigated grass to the potential evapotranspiration of specific crops. The method was originally developed for cultivated species based on lysimeter measurements of potential evapotranspiration. Not many applications to natural vegetated areas exist due to the lack of available data for these species. In this paper we investigate the potential of using evapotranspiration measurements acquired by micrometeorological stations for the definition of crop coefficient functions of natural vegetated areas and extrapolation to ungauged sites through remotely sensed data. Pastures, deciduous and evergreen forests have been considered and lower crop coefficient values are found with respect to FAO data

An Enkf-Based Scheme for Snow Multivariable Data Assimilation at an Alpine Site

Abstract The knowledge of snowpack dynamics is of critical importance to several real-time applications especially in mountain basins, such as agricultural production, water resource management, flood prevention, hydropower generation. Since simulations are affected by model biases and forcing data uncertainty, an increasing interest focuses on the assimilation of snow-related observations with the purpose of enhancing predictions on snowpack state. The study aims at investigating the effectiveness of snow multivariable data assimilation (DA) at an Alpine site. The system consists of a snow energy-balance model strengthened by a multivariable DA system. An Ensemble Kalman Filter (EnKF) scheme allows assimilating ground-based and remotely sensed snow observations in order to improve the model simulations. This research aims to investigate and discuss: (1) the limitations and constraints in implementing a multivariate EnKF scheme in the framework of snow modelling, and (2) its performance in consistently updating the snowpack state. The performance of the multivariable DA is shown for the study case of Torgnon station (Aosta Valley, Italy) in the period June 2012 - December 2013. The results of several experiments are discussed with the aim of analyzing system sensitivity to the DA frequency, the ensemble size, and the impact of assimilating different observations

Remote sensing-based estimation of gross primary production in a subalpine grassland

This study investigates the performances in a terrestrial ecosystem of gross primary production (GPP) estimation of a suite of spectral vegetation indexes (VIs) that can be computed from currently orbiting platforms. Vegetation indexes were computed from near-surface field spectroscopy measurements collected using an automatic system designed for high temporal frequency acquisition of spectral measurements in the visible near-infrared region. Spectral observations were collected for two consecutive years in Italy in a subalpine grassland equipped with an eddy covariance (EC) flux tower that provides continuous measurements of net ecosystem carbon dioxide (CO2) exchange (NEE) and the derived GPP. Different VIs were calculated based on ESA-MERIS and NASA-MODIS spectral bands and correlated with biophysical (Leaf area index, LAI; fraction of photosynthetically active radiation intercepted by green vegetation, f IPARg), biochemical (chlorophyll concentration) and ecophysiological (green light-use efficiency, LUEg) canopy variables. In this study, the normalized difference vegetation index (NDVI) was the index best correlated with LAI and f IPARg (r = 0.90 and 0.95, respectively), the MERIS terrestrial chlorophyll index (MTCI) with leaf chlorophyll content (r = 0.91) and the photochemical reflectance index (PRI551), computed as (R531 −R551)/(R531 +R551) with LUEg (r = 0.64). Subsequently, these VIs were used to estimate GPP using different modelling solutions based on Monteith’s lightuse efficiency model describing the GPP as driven by the photosynthetically active radiation absorbed by green vegetation (APARg) and by the efficiency (") with which plants use the absorbed radiation to fix carbon via photosynthesis. Results show that GPP can be successfully modelled with a combination of VIs and meteorological data or VIs only. Vegetation indexes designed to be more sensitive to chlorophyll content explained most of the variability in GPP in the ecosystem investigated, characterised by a strong seasonal dynamic of GPP. Accuracy in GPP estimation slightly improves when taking into account high frequency modulations of GPP driven by incident PAR or modelling LUEg with the PRI in model formulation. Similar results were obtained for both measured daily VIs and VIs obtained as 16-day composite time series and then downscaled from the compositing period to daily scale (resampled data). However, the use of resampled data rather than measured daily input data decreases the accuracy of the total GPP estimation on an annual basis.JRC.H.4-Monitoring Agricultural Resource

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

Phenological diversity is linked to the diversity of functional traits in alpine grasslands

Climate change is exerting a profound influence on the timing of seasonal development of vegetation, i.e. phenology, worldwide - and particularly in mountain grasslands. A key feature controlling the resilience of alpine plant communities to climate change is phenological plasticity: the ability to express different phenologies within a given plant assemblage can help the community to better cope with climate shifts and extremes. Recent work has shown a tight relationship between phenology and certain plant functional traits, especially those associated to competition and growth rate. Phenocameras proved to be an effective mean to monitor community-level phenology by retrieving average phenological signals across a portion of the field of view of digital cameras. Here we used pixel-level information to quantify spatially-explicit phenology from multi-year imagery acquired over 5 alpine grasslands in the western Alps. Concurrently, based on site-specific species inventories we retrieved information about functional traits from the global plant trait database TRY. The objectives of this work are: 1) to assess the link between phenological diversity and plant functional trait diversity in alpine grasslands; 2) to test the consistency in space and time of the functional diversity-phenological diversity relationship. A total of 19 year-sites of phenocam images were processed to obtain maps of phenological metrics. We focused on either spring (start of season, moment of greenness peak, spring recovery rate), autumn (end of season, start of senescence, autumn senescence rate) or full season (length of season, greenness integral) metrics. To describe the spatial distribution of phenological metrics we used indexes such as the Moran Index and the Entropy index. The FD R package was used to compute multidimensional functional diversity. We will illustrate the traits that best correlate with phenological diversity across the 5 different grasslands included in this study and discuss inter-year and inter-site variability in the relationships in the light of climate variability

Trade-offs between global warming and day length on the start of the carbon uptake period in seasonally cold ecosystems

8openInternationalIt is well established that warming leads to longer growing seasons in seasonally cold ecosystems. Whether this goes along with an increase in the net ecosystem carbon dioxide (CO2) uptake is much more controversial. We studied the effects of warming on the start of the carbon uptake period (CUP) of three mountain grasslands situated along an elevational gradient in the Alps. To this end, we used a simple empirical model of the net ecosystem CO2 exchange, calibrated, and forced with multiyear empirical data from each site. We show that reductions in the quantity and duration of daylight associated with earlier snowmelts were responsible for diminishing returns, in terms of carbon gain, from longer growing seasons caused by reductions in daytime photosynthetic uptake and increases in nighttime losses of CO2. This effect was less pronounced at high, compared to low, elevations, where the start of the CUP occurred closer to the summer solstice when changes in day length and incident radiation are minimalopenWohlfahrt, G.; Cremonese, E.; Hammerle, A.; Hörtnagl, L.; Galvagno, M.; Gianelle, D.; Marcolla, B.; Morra di Cella, U.Wohlfahrt, G.; Cremonese, E.; Hammerle, A.; Hörtnagl, L.; Galvagno, M.; Gianelle, D.; Marcolla, B.; Morra di Cella, U

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