Use of remote sensing‑derived fPAR data in a grapevine simulation model for estimating vine biomass accumulation and yield variability at sub‑field level

Grapevine simulation models are mostly used to estimate plant development, growth and yield at plot scale. However, the spatial variability of pedologic and micro-climatic conditions can influence vine growth, leading to a sub-field heterogeneity in plant vigor and final yield that may be better estimated through the assimilation of high spatial resolution data in crop models. In this study, the spatial variability of grapevine intercepted radiation at fruit-set was used as input for a grapevine simulation model to estimate the variability in biomass accumulation and yield in two Tuscan vineyards (Sites A and B). In Site A, the model, forced with intercepted radiation data as derived from the leaf area index (LAI), measured at canopy level in three main vigor areas of the vineyard, provided a satisfactory simulation of the final pruning weight (r2 = 0.61; RMSE = 19.86 dry matter g m−2). In Site B, Normalized Difference Vegetation Index (NDVI) from Sentinel-2A images was firstly re-scaled to account for canopy fraction cover over the study areas and then used as a proxy for grapevine intercepted radiation for each single pixel. These data were used to drive the grapevine simulation model accounting for spatial variability of plant vigor to reproduce yield variability at pixel scale (r2 = 0.47; RMSE = 75.52 dry matter g m−2). This study represents the first step towards the realization of a decision tool supporting winegrowers in the selection of the most appropriate agronomic practices for reducing the vine vigor and yield variability at sub-field level

Stochastic smoothing of point processes for wildlife-vehicle collisions on road networks

Wildlife-vehicle collisions on road networks represent a natural problem between human populations and the environment, that affects wildlife management and raise a risk to the life and safety of car drivers. We propose a statistically principled method for kernel smoothing of point pattern data on a linear network when the first-order intensity depends on covariates. In particular, we present a consistent kernel estimator for the first-order intensity function that uses a convenient relationship between the intensity and the density of events location over the network, which also exploits the theoretical relationship between the original point process on the network and its transformed process through the covariate. We derive the asymptotic bias and variance of the estimator, and adapt some data-driven bandwidth selectors to estimate the optimal bandwidth. The performance of the estimator is analysed through a simulation study under inhomogeneous scenarios. We present a real data analysis on wildlife-vehicle collisions in a region of North-East of Spain

Modelling different cropping systems

Grapevine is a worldwide valuable crop characterized by a high economic importance for the production of high quality wines. However, the impact of climate change on the narrow climate niches in which grapevine is currently cultivated constitute a great risk for future suitability of grapevine. In this context, grape simulation models are considered promising tools for their contribution to investigate plant behavior in different environments. In this study, six models developed for simulating grapevine growth and development were tested by focusing on their performances in simulating main grapevine processes under two calibration levels: minimum and full calibration. This would help to evaluate major limitations/strength points of these models, especially in the view of their application to climate change impact and adaptation assessments. Preliminary results from two models (GrapeModel and STICS) showed contrasting abilities in reproducing the observed data depending on the site, the year and the target variable considered. These results suggest that a limited dataset for model calibration would lead to poor simulation outputs. However, a more complete interpretation and detailed analysis of the results will be provided when considering the other models simulations

Carbon sequestration capacity and productivity responses of Mediterranean olive groves under future climates and management options

The need to reduce the expected impact of climate change, finding sustainable ways to maintain or increase the carbon (C) sequestration capacity and productivity of agricultural systems, is one of the most important challenges of the twenty-first century. Olive (Olea europaea L.) groves can play a fundamental role due to their potential to sequester C in soil and woody compartments, associated with widespread cultivation in the Mediterranean basin. The implementation of field experiments to assess olive grove responses under different conditions, complemented by simulation models, can be a powerful approach to explore future land-atmosphere C feedbacks. The DayCent biogeochemical model was calibrated and validated against observed net ecosystem exchange, net primary productivity, aboveground biomass, leaf area index, and yield in two Italian olive groves. In addition, potential changes in C-sequestration capacity and productivity were assessed under two types of management (extensive and intensive), 35 climate change scenarios (ΔT-temperature from + 0 °C to + 3 °C; ΔP-precipitation from 0.0 to − 20%), and six areas across the Mediterranean basin (Brindisi, Coimbra, Crete, Cordoba, Florence, and Montpellier). The results indicated that (i) the DayCent model, properly calibrated, can be used to quantify olive grove daily net ecosystem exchange and net primary production dynamics; (ii) a decrease in net ecosystem exchange and net primary production is predicted under both types of management by approaching the most extreme climate conditions (ΔT = + 3 °C; ΔP = − 20%), especially in dry and warm areas; (iii) irrigation can compensate for net ecosystem exchange and net primary production losses in almost all areas, while ecophysiological air temperature thresholds determine the magnitude and sign of C-uptake; (iv) future warming is expected to modify the seasonal net ecosystem exchange and net primary production pattern, with higher photosynthetic activity in winter and a prolonged period of photosynthesis inhibition during summer compared to the baseline; (v) a substantial decrease in mitigation capacity and productivity of extensively managed olive groves is expected to accelerate between + 1.5 and + 2 °C warming compared to the current period, across all Mediterranean areas; (vi) adaptation measures aimed at increasing soil water content or evapotranspiration reduction should be considered the mostly suitable for limiting the decrease of both production and mitigation capacity in the next decades