Data Integration and Modelling for the Assessment of Future Climate Change Impacts on Natural Pasturelands of the Alps

Evidence shows that in the last century in the Alps area warming was roughly three times the global average and, according to future projections, this trend is expected to worsen in the next decades. Moreover, the species-rich permanent grasslands characterizing the marginal areas of the Alpine landscape are acknowledged as very sensitive and vulnerable ecosystems to climate change (IPCC 2007). So far several studies have investigated the climate effects only on specific Alpine grassland species at a very small scale, while a comprehensive assessment of the impact of climate change on Alpine mountain grasslands distribution and composition at a territorial scale is still lacking. Building on these premises, ground-breaking tools (classification models coupled with data integration by GIS techniques) were used to identify and environmentally characterize the main pastoral communities over the Alpine chain and to assess future climate change impacts on these fragile resources

Pastoral suitability driven by future climate change along the Apennines

This work aims at evaluating the impacts of climate change on pastoral resources located along the Apennines chain. To this end, random forest machine learning model was first calibrated for the present period and then applied to future conditions, as projected by HadCM3 general circulation model, in order to simulate possible spatial variation/shift of pastoral areas in two time slices (centred on 2050 and 2080) under A2 and B2 SRES scenarios. Pre-existent spatial database, namely Corine land cover map and WorldClim, were integrated and harmonised in a GIS environment in order to extract climate variables (mean seasonal precipitation, mean maximum temperature of the warmest month and minimum temperature of the coldest month) and response variables (presence/absence of pastures) to be used as model predictors. Random forest model resulted robust and coherent to simulate pastureland suitability under current climatology (classification accuracy error=19%). Accordingly, results indicated that increases in temperatures coupled with decreases in precipitation, as simulated by HadCM3 in the future, would have impacts of great concern on potential pasture distribution. In the specific, an overall decline of pasturelands suitability is predicted by the middle of the century in both A2 (–46%) and B2 (–41%) along the entire chain. However, despite alarming reductions in pastures suitability along the northern (–69% and –71% under A2 and B2 scenarios, respectively) and central Apennines (–90% under both scenarios) by the end of the century, expansions are predicted along the southern areas of the chain (+96% and +105% under A2 and B2 scenarios, respectively). This may be probably due to expansions in pastures dominated by xeric and thermophiles species, which will likely benefit from warmer and drier future conditions predicted in the southern zone of the chain by the HadCM3. Hence, the expected climate, coupled with an increasing abandonment of the traditional grazing practices, will likely threat grassland biodiversity as well as pastoral potential distribution currently dominating the Apennines chain

Needs on model improvement

The need to answer new scientific questions can be satisfied by an increased knowledge of physiological mechanisms which, in turn, can be used for improving the accuracy of simulations of process-based models. In this context, this report highlights areas that need to be further improved to facilitate the operational use of simulation models. It describes missing approaches within simulation models which, if implemented, would likely improve the representation of the dynamics of processes underlying different compartments of crop and grassland systems (e.g. plant growth and development, yield production, GHG emissions), as well as of the livestock production systems. The following rationale has been used in the organization of this report. We first briefly introduced the need to improve the reliability of existing models. Then, we indicated climate change and its influence on the global carbon balance as the main issue to be addressed by existing crop and grassland (section 2), and livestock (section 3) models. In section 2, among the major aspects that if implemented may reduce the uncertainty inherent to model outputs, we suggested: i) quantifying the effects of climate extremes on biological systems; ii) modelling of multi-species sward; iii) coupling of pest and disease sub-models; iv) improvement of the carry-over effect. In section 3, as the most important aspects to consider in livestock models we indicated: i) impacts and dynamics of pathogens and disease; ii) heat stress effects on livestock; iii) effects on grassland productivity and nutritional values; iv) improvement of GHG emissions dynamics. In Section 4, remarks are made concerning the need to implement the suggested aspects into the existing models

Model comparison and improvement: Links established with other consortia

XC1 has established links to other research activities and consortia on model comparison and improvement. They include the global initiatives AgMIP (http://www.agmip.org) and GRA (http://www.globalresearchalliance.org), and the EU-FP7 project MODEXTREME (http://modextreme.org). These links have allowed sharing and communication of recent results and methods, and have created opportunities for future research calls

Near future climate change projections with implications for the agricultural sector of three major Mediterranean islands

AbstractThe paper presents the analysis of a sub-set of high-resolution bias-adjusted simulations from the EURO-CORDEX initiative, in order to examine the changes in the mean climate and the extremes in three Mediterranean islands, namely, Sicily, Crete and Cyprus, in the near future (2031–2060) compared to the present climate (1971–2000), under two future scenarios, i.e. RCP4.5 and RCP8.5. The analysis entails commonly used climatic indices of interest related to the islands' agricultural sector. The results indicate robust increases for both the mean maximum and minimum temperatures on a seasonal basis, as well as for the temperature related extremes under both climate scenarios. On the contrary, the changes in precipitation are less pronounced as the changes in the seasonal precipitation are not found statistically significant for the three islands under both scenarios. The projected warming combined with the projected unchanged precipitation pattern in the future, especially in spring and summer, might expose the crops to conditions with a negative impact on the plants' phenology, leading to implications on crop production and quality. The results presented here might be the basis for the development of an adaptation strategy specifically targeted on the three islands but also replicable to other Mediterranean islands

Application of Virtual Fencing for the management of Limousin cows at pasture

A potential use of pasture-based systems requires an efficient grazing management strategy. Thanks to the Virtual Fencing (VF) physical fences are replaced by virtual ones and, when the animals approach the boundaries, they receive a paired stimulus: an audio cue followed by a low electrical pulse if animals cross over the fences. This study aims to i) to evaluate the animal’s ability to learn, and then respond positively, to VF ii) VFs’ efficiency to manage the herd within grazing areas virtually delimitated; iii) to assess the chronic stress related to the VF, evaluating the hair cortisol concentration (HCC), during the experiment. Twenty Limousine cows were fitted with a commercial VF-GPS collars (Nofence AS, Batnfjordsør, Norway). The experiment was divided into four trials: Trial zero (T0) with inactive collars to let the animals get acquainted with them; Trial one (T1) where three of the four virtual boundaries coincided with the physical ones, while the virtual one was set across the pasture to restrict the grazing area; Trial two (T2) in which the grazing area was further extended moving forwards the virtual board; Trial three (T3) in which the virtual line was set longways to the pasture. Results show a significant decrease of stimuli delivered (i.e., sounds and electrical pulses) (p < 0.001), among trials. Moreover, a reduction (p < 0.0250) in the ratio between sounds and electrical pulses was observed between T1 and T3, with T2 being like both. Regarding the cows’ learning capacity, the events in which the sounds were followed by electrical pulses were significantly less in T3 (p < 0.001). Furthermore, in T3 the duration of the audio tones was lower than T1 and T2 (p < 0.0005). Animals were increasingly kept inside the inclusion zones during the trials, with the lowest number of escape events from the inclusion zone registered in T3 (p < 0.001). No differences were observed in the HCC before and after the VF treatment. The progressive reduction of the studied parameters between following sessions, indicates an increase in associative learning through time. VF virtual fencing has proven to be an effective tool in managing Limousin cows at pasture. However, future research is needed to evaluate the animals’ performances in terms of grazing activities and on the assessment of chronic stress conditions as well

Is new olive farming sustainable? A spatial comparison of productive and environmental performances between traditional and new olive orchards with the model OliveCan

Olive (Olea europaea L.) is a widely spread tree species in the Mediterranean. In the last decades, olive farming has known major management changes with high economic and environmental impacts. The fast track expansion of this modern olive farming in these recent years casts doubts on the sustainability of such important tree plantation across the Mediterranean. In this work, we performed a spatial modelling analysis to investigate the implications of climate variability and farming management on the productivity and environmental performances of olive orchards around the Mediterranean. Implementation of this research is based on the use of OliveCan; a process-based model able to illustrate responses of water and carbon balances to weather variables, soil characteristics and management techniques enabling the comprehension of olive orchard dynamics under heterogeneous conditions of climate and agricultural practices. Four main intensification levels were adopted to reflect the main olive grove types from traditional to new intensive plantations: low density LD (100 trees ha−1), medium density MD (200 trees ha−1), high density HD (400 trees ha−1) and super high density SHD (1650 trees ha−1). Managements tested were intensification, water supply (rainfed, deficit and full irrigated) and the fate of pruning residues (exported or left on the soil). Two cases studies in two of the main Mediterranean olive-growing regions with contrasting environmental conditions, Tuscany and Jaen regions, focused on mitigation alternative managements for carbon sequestration. Results showed that olive orchards responses in terms of yield and Net Ecosystem Productivity (NEP) vary along with climatic conditions. Water supply was the main driver with a production function that varies for different atmospheric demands. Application of deficit irrigation proved to boost water use efficiency. Besides, intensification from LD to SHD, presented the greatest improvements, 28–73% for yield and 50–100% for NEP. The C sequestration potential of olive orchards was confirmed. In fact, soil organic carbon (SOC) increased continuously over 400 years of simulation, reaching a state of equilibrium. Moreover, intensification and irrigation improved total carbon sequestration. Management of incorporating pruning residues in the soil increased SOC of 10.5 t C ha−1 for Tuscany and 10.8 t C ha−1 for Jaen. Findings of this research enabled the identification of the main drivers influencing the productive and environmental performance of olive groves in the different Mediterranean sub-climates. Impacts of management innovations on olive farming sustainability were also quantified which may help improve production systems for a more sustainable olive cultivation

Adopting soil organic carbon management practices in soils of varying quality : Implications and perspectives in Europe

Acknowledgements We wish to thank all participants to the SmartSOIL project for their inspiring inputs and debates and for having shared their valuable expertise, contributing to the success of this project. Furthermore, we are grateful to the financial support from the 7th Framework Programme of the European Union (Call identifier: FP7-KBBE-2011-5; project number: 289694).Peer reviewedPostprin

Use of Sentinel-2 Derived Vegetation Indices for Estimating fPAR in Olive Groves

Olive tree cultivation is currently a dominant agriculture activity in the Mediterranean basin, where the increasing impact of climate change coupled with the inefficient management of olive groves is negatively affecting olive oil production and quality in some marginal areas. In this context, satellite imagery may help to monitor crop growth under different environmental conditions, thus providing useful information for optimizing olive grove management and final production. However, the spatial resolution of freely-available satellite products is not yet adequate to estimate plant biophysical parameters in complex agroecosystems such as olive groves, where both olive trees and grass cover contribute to the vegetation indices (VIs) signal at pixel scale. The aim of this study is therefore to test a disentangling procedure to partition the VIs signal among the different components of the agroecosystem to use this information for the monitoring of olive growth processes during the season. Specifically, five VIs (GEMI, MCARI2, NDVI, OSAVI, MCARI2/OSAVI) as recorded by Sentinel-2 at a spatial resolution of 10 m over five olive groves in the Montalbano area (Tuscany, Central Italy), were tested as a proxy for olive tree intercepted radiation. The olive tree volume per pixel was initially used to linearly rescale the VIs signal into the relevant value for the grass cover and olive trees. The models, describing the relationship between rescaled VIs and observed fraction of Photosynthetically Active Radiation (fPAR), were fitted and then validated against independent datasets. While in the calibration phase, a greater robustness at predicting fPAR was obtained using NDVI (r = 0.96 and RRMSE = 9.86), the validation results demonstrating that GEMI and MCARI2/OSAVI provided the highest performances (GEMI: r = 0.89 and RRMSE = 21.71; MCARI2/OSAVI: r = 0.87 and RRMSE = 25.50), in contrast to MCARI2 that provided the lowest (r = 0.67 and RRMSE = 36.78). These results may be related to the VIs’ intrinsic features (e.g., lower sensitivity to atmosphere and background effects), which make some of these indices, compared to others, less sensitive to saturation effects by improving fPAR estimation (e.g., GEMI vs. NDVI). On this basis, this study evidenced the need to improve the current methodologies to reduce inter-row effects and select appropriate VIs for fPAR estimation, especially in complex agroecosystems where inter-row grass growth may affect remote sensed-derived VIs signal at an inadequate pixel resolution

Communicating soil carbon science to farmers: incorporating credibility, salience and legitimacy

A key narrative within climate change science is that conserving and improving soil carbon through agricultural practices can contribute to agricultural productivity and is a promising option for mitigating carbon loss through sequestration. This paper examines the potential disconnect between science and practice in the context of communicating information about soil carbon management. It focuses on the information producing process and on stakeholder (adviser, farmer representative, policy maker etc) assessment of the attributes credibility, salience and legitimacy. In doing this it draws on results from consultations with stakeholders in the SmartSOIL project which aimed to provide decision support guidelines about practices that optimise carbon mitigation and crop productivity. An iterative methodology, used to engage stakeholders in developing, testing and validating a range of decision support guidelines in six case study regions across Europe, is described. This process enhanced legitimacy and revealed the importance, and the different dimensions, of stakeholder views on credibility and salience. The results also highlight the complexities and contested nature of managing soil carbon. Some insights are gained into how to achieve more effective communication about soil carbon management, including the need to provide opportunities in projects and research programmes for dialogue to engender better understanding between science and practice