Scientific and technological project description

The aim of this project is to provide accurate tools to test the effectiveness of adaptation/mitigation management strategies to support long-term investment decision making. Central to this evaluation will be the harmonization between farmers’ and sustainable ecosystems objectives, coupling profitability with the capacity of providing environmental services, to be reached by purposely-developed simulation tools to support decision-making.
Advanced modelling approaches will be used to integrate available physiological knowledge into existing and well established modelling platforms, to assess climate change impact and evaluate mitigation/adaptation strategies by tuning agro-management factors. The analysis will be based on a consistent set of data layers, including weather, soils, and current agro-management information, and it will be conducted against present-time and short to mid-term future scenarios of climate change, derived from global circulation models
The research will produce modelling solutions to assess climate change impact on olive farming systems in Mediterranean environments, to support the development of sustainable and resilient agro-management strategies.
Simulation of olive fundamental growth and development processes will be based on the OLIVECAN model, developed at the University of Cordoba and IAS-CSIC. OLIVECAN is a simulation model of development, growth and yield of olives in response to climate, soil and orchard characteristics. It is a detailed mechanistic model with a high explanatory power.
The model incorporates a submodel of water balance which simulates soil evaporation (Bonachela et al., 1999; Bonachela et al., 2001), tree transpiration (Villalobos et al., 2000; Villalobos et al., 2013) and surface runoff (Romero et al., 2007). Biomass accumulation is simulated using a Radiation-Use Efficiency approach (Mariscal et al., 2000a) with radiation interception calculated with the model of Mariscal et al. (2000b). Partitioning of biomass to fruit and oil production is simulated according to Villalobos et al. (2006) and Iniesta et al. (2009) when water deficit occurs. The model incorporates the simulation of flowering date according to Melo-Abreu et al. (2004). A new version of OLIVECAN is being developed to include the effects of extreme temperature and water stress on growth and yield (project FP7-MODEXTREME). The model is currently being improved with the following features:
a) a more advanced and detailed simulation of photosynthesis and carbon assimilation using an approach relying on the Farquhar model (Farquhar et al., 1980) which will allow to better assess the crop performance under future conditions of increased atmospheric CO2 concentration. The Farquhar model parameters for olive are already available for the cultivar “Manzanilla” and a project has recently started in Córdoba to obtain such parameters for other widely cultivated olive cultivars.
b) simulation of oil accumulation using a thermal time approach as that developed by Villalobos et al. (1996) for sunflower.
c) simulation of the soil-plant-atmosphere continuum (Williams et al, 1996) with explicit account of soil, root and shoot hydraulic resistance (Sperry et al, 1998) and response of stomatal conductance to leaf water potential using the model of Tuzet et al. (2003). This feature will further improve the model response to water shortage conditions, especially in the diurnal cycle. An alternative for simulating photosynthesis and respiration at the stand level based on Villalobos et al. (2012) and Perez-Priego et al. (2014) is also available.
The model will also be improved by incorporating newly developed modules to simulate previously uncovered topics, such as interactions with pest/diseases and the dependence of olive quality-related variables on climatic factors.
Simulation of pests and pathogens, such as the olive fruit fly, will ameliorate yield estimates in scenario and present-time analysis, and contribute to reduce the pesticides environmental impact and of the amount of pesticide residues in the oil.
Since OLIVECAN does not explicitly account for yield quality, a statistical model will be developed for exploring causal relationships between environmental factors and quality- parameters .
The modelling solutions will be implemented into the BioMA platform, (, currently used by the European Commission, which is designed upon component-oriented principles to allow model integration and reusability. This is particularly appropriate also for developing tasks, as it allows to easily implement and evaluate alternative modelling strategies.
The BioMA framework already includes a flexible and extensible agro-management rule-based model, enabling the evaluation of different operational options in any cropping system.
To be of any practical relevance, the study should be conducted at a local scale at high spatial resolution, therefore, part of the activity will be focused on the collection of spatial data (including RCP climate scenarios) at highest spatial resolution (1-10 km maximum).
The analysis will be targeted at evaluating agro-management options focused around the following issues:
1) Water use. Where irrigation is an unavoidable option, the objective is to find how to maximize yield per unit land area and per unit irrigation water used, and/or how to reduce water inputs, by evaluating management options (e.g. planting density, regulated or continuous deficit irrigation, canopy geometry/size). For rainfed orchards, the aim will be the optimization of the productivity of the system in the long term (including quality of the main product, quantity-availability of the by-products and safety of the investment on the long term) under the constraint of soil water availability in actual and future climatic conditions
2) Soil protection. In olive groves soil erosion risk is elevated due to high fraction of uncovered surface and difficulty of growing a cover crop without impacting on water use. Appropriate management strategies for cover crop must be designed to avoid competition for water, adjusting planting and killing dates, and testing alternative species, e.g. leguminosae, which fix N and reduce N external inputs, or cereals, which would give byproducts for human/livestock food or C sequestration through soil biomass incorporation.
The analysis will also consider the protective effect of incorporating organic wastes from oil industry in the soil as well as possible drawbacks (groundwater pollution).
3) Carbon balance. The effect of different irrigation strategies (timing and amount) and soil management (presence/type of cover crop; waste or biomass incorporation) on net carbon exchange will be assessed in the long-term, considering also the effect of increasing CO2 in the atmosphere.
4) Agro-energy potential. The model can quantify the amount of biomass that can be produced by olive groves as pruning material, which is already an energy source designed for small power plants. This research will evaluate the agro-energy potential in the various agro-management scenarios, under the additional constraint of spatial distribution which impacts on distribution costs and power plants logistic.
5) Pests/diseases. Dynamical modelling of olive fly population in response on temperature variation has already been proposed in recent publications. Here it is proposed to implement a dedicated model to be integrated into a wider simulation framework, to analyze the impact of pest attacks in future scenarios in relation to a wider set of conditions.
6) Quality. Environment variables have a major influence on olive fruit and oil composition, hence climate change are expected to significantly impact on the sensory attributes and marketing parameters, with a high chance of irreversibly altering many local typicalities. As quality and local characterizations play a key role in the olive/oil market, a comprehensive assessment of future scenarios should take them into proper account. However, quality modelling is still an almost unexplored issues, with scarce literature background. The research will undertake a first modelling action, based on a geographically wide-ranging dataset assembled from germplasm collections and other scientific institutions. Olive oil chemistry profiles will be analyzed with multivariate approaches to individuate causal relationships between climate variables and quality-related traits. The resulting model will be incorporated in a dedicated software package to be integrated in the modelling solutions.
7) Olive farming design: olive growing has recently experienced a revolution in orchard design, increasing the planting density from 100-200 (traditional) to 400-600 (high density) to >1500 trees/ha (hedgerow), the last one with the objective to allow mechanical harvesting thus reducing drastically the main production cost. The sustainability of this new olive farming systems (both in current and in future climatic conditions) is still to be assessed in many environments: the simulations with OLIVECAN will help understanding in which zones and climates the new hedgerow orchards are viable, productive and what are their long-term environmental and economic risks under the common and forecasted constraints.
Novelty of the proposal
Assessments of global change impact in agriculture have so far focused mainly on mere production criteria, rather than considering agriculture as a ‘holistic’ system where both positive (direct economic income) and negative externalities (e.g. soil erosion, increase of water pollutants and water scarcity) should be taken into account for a more comprehensive evaluation of system sustainability. Conversely, this project aims at analysing the different aspects of the olive production across the Mediterranean basin, including production, quality, resource use and optimization, by-product estimation, abiotic and biotic stressors and impact indicators. The simulations results will therefore provide more insights into the trade-offs between crop yield and ecosystem services as affected by climate change, providing a basis for a cost/benefit analysis on the short term. On a long term, the analysis of carbon sequestration and yield will help to bridge the gap between adaptation and mitigation by finding the best combination amongst the strategies that optimize crop yield while reduces greenhouse gas emission.
Furthermore, the project is highly innovative to the extent that though the impact of climate change and adaptation options are evaluated over a large domain (the northern Mediterranean basin), the results are strictly linked to the local scale. This allows tailoring the adaptation measures on the actual local conditions rather than on regional or national scale.