MARS Bulletin Vol 18 No 1

The annexed document is the template for the bulletin that will be issued on the 9th March. This bulletin covers meteorological analysis and crop yield forecasts for the period 1st November 2009 to 28 February 2010JRC.DG.G.3-Monitoring agricultural resource

MARS Bulletin 2011 Vol.19 No.7

Despite rainfall in Western Europe yields are revised down At the beginning of June the dry period in western Europe ended. Countries most affected by the dry spell received some beneficial rainfall and more rain is forecast in the coming 10 days bringing the precipitation since 1st June to average or even surplus values in the United Kingdom, France, Germany and northern Italy. This rainfall will not entirely compensate, especially in France, for the long lasting dry spell depleting soil reservoirs. Ukraine appears as a new area of concern with lacking precipitation while crops have a high water demand. Compared to our last forecasts from 17th May yield expectations for all cereals except spring barley decreased at EU 27 level due to the unfavourable weather conditions mainly in United Kingdom, France and Germany affecting yield prospects in these countries. Spain is experiencing a very promising year and yields have been revised up.JRC.DDG.H.4-Monitoring agricultural resource

MARS Bulletin Vol. 20 No. 1

There were milder than usual thermal conditions over most of Europe, providing favourable conditions for the development and wintering of all winter crops. Frost events were less frequent than usual. Precipitation exceeded the average by far in the western part of Europe and in the Aegean region. It was seasonal in eastern Europe, but significantly below the norm in Spain, Portugal and Morocco. The analysis of winter kill indices indicates no or little damage so far.JRC.H.4-Monitoring Agricultural Resource

A plant ecology approach to digital soil mapping, improving the prediction of soil organic carbon content in alpine grasslands

The influence of organisms on pedogenesis is acknowledged in the scorpan model; however organisms, plants in particular, might be seen in a different light within the scorpan model. In fact, in minimally managed terrestrial ecosystems, biota coexists with soil as part of a feedback system, in which the biota not only influences soil development, but is also in turn influenced by it. This means that in natural environments a particular soil is usually associated with a typical combination of plant species which thrive in the biotope defined by the soil physical and chemical properties. Changes in soil features will favor certain species over others, thus modifying the structure of the resident plant communities. This makes plant communities very effective proxies of soil properties, effectively acting as widespread biological sensors. In this paper we will show how plant communities can be utilized to improve the quality of digital soil maps, effectively reducing the amount of field work needed by soil surveys, through a combination of relatively swifter and cheaper vegetation surveys and remote sensing data. The approach we propose is based on the spectral and textural properties of plant communities which can be summarized from high resolution remotely sensed images and LIDAR data through the use of geostatistical, spectral and geomorphometric descriptors. These descriptors are then associated with the scores obtained from the ordination of the plant communities' relative coverage. Ordination projects the high dimensional plant cover data into a lesser dimensional space, thus making easier to establish a relation between ecological space and geostatistical descriptors. Once established this relation can be exploited through the use of regression techniques in a regression kriging framework. In this case study, we applied the proposed model to the prediction of soil organic carbon content in an alpine grassland. The use of plant communities cover almost doubled the predictive power of the model from an R2 of 0.32 to an R2 of 0.66 in cross-validation, a result which strongly advocates for the efficiency of the proposed approach.JRC.H.5-Land Resources Managemen

An Improved Model to Simulate Rice Yield

Rice is the staple food for about half of the world's population. Although global production has more than doubled in the last 40 years, food security problems still persist and need to be managed based on early and reliable forecasting activities. This is especially true since the frequency of extreme weather events is forecasted to increase by the intergovernmental panel on climate change (IPCC). The most advanced crop yield forecasting systems are based on simulation models. However, examples of operational systems implementing models which are suitable for reproducing the peculiarities of paddy rice, especially on small scales, are missing. The rice model WARM is used within the crop yield forecasting system of the European Commission. In this article we evaluated the WARM model for the simulation of rice growth under flooded and unflooded conditions in China and Italy. The WARM model simulates crop growth and development, floodwater effect on the vertical thermal profile, blast disease, cold-shock induced spikelet sterility during the pre-flowering period and hydrological peculiarities of paddy soils. We identified the most relevant model parameters through sensitivity analyses carried out using the Sobol' method and then calibrated using the simplex algorithm. Data from 11 published experiments, covering 13 locations and 10 years, were used. Two groups of rice varieties were identified for each country. Our results show that the model was able to reproduce rice growth in both countries. Specifically, the average relative root mean square error calculated on aboveground biomass curves was 21.9% for the calibration and 23.6% for validation. The parameters of the linear regression equation between measured and simulated values were always satisfactory. Indeed, intercept and slope were always close to their optima and R2 was always higher than 0.79. For some of the combinations of country and simulated variable, the indices of agreement calculated for the validation datasets were better then the corresponding ones computed at the end of the calibration, indirectly proving the robustness of the modeling approach. WARM's robustness and accuracy, combined with the low requirements in terms of inputs and the implementation of modules for reproducing biophysical processes strongly influencing the year-to-year yield variation, make the model suitable for forecasting rice yields on regional, national and international scales.JRC.G.3 - Monitoring agricultural resource

MARS Bulletin Vol.19 No. 5 - Agrometeorological analysis and weather forecast

Period of analysis 21 March - 10 April 2011 Starting from the beginning of April the weather turned warm in almost all Europe. Thermal sums exceeded the average by +30-40% and this in conjunction with scarce rainfall and high irradiance levels led to a strong transpirative demand. On the contrary in the East (Russia especially) rainfall were abundant and the thermal anomalies rather negative. In the next few days the Atlantic regions will be warmer than usual, whereas a relative cold air intrusion is forecast in central and eastern Europe. Large areas of Europe will experience only scarce rain whereas in the Black Sea area slightly wetter than usual conditions can be expectedJRC.DDG.H.4-Monitoring agricultural resource

A Plant ecology approach to digital soil mapping, improving the prediction of soil organic carbon content in alpine grasslands

The influence of organisms on pedogenesis is acknowledged in the scorpan model; however organisms, plants in particular, might be seen in a different light within the scorpan model. In fact, in minimally managed terrestrial ecosystems, biota coexists with soil as part of a feedback system, in which the biota not only influences soil development, but is also in turn influenced by it. This means that in natural environments a particular soil is usually associated with a typical combination of plant species which thrive in the biotope defined by the soil physical and chemical properties. Changes in soil features will favor certain species over others, thus modifying the structure of the resident plant communities. This makes plant communities very effective proxies of soil properties, effectively acting as widespread biological sensors. In this paper we will show how plant communities can be utilized to improve the quality of digital soil maps, effectively reducing the amount of field work needed by soil surveys, through a combination of relatively swifter and cheaper vegetation surveys and remote sensing data. The approach we propose is based on the spectral and textural properties of plant communities which can be summarized from high resolution remotely sensed images and LIDAR data through the use of geostatistical, spectral and geomorphometric descriptors. These descriptors are then associated with the scores obtained from the ordination of the plant communities' relative coverage. Ordination projects the high dimensional plant cover data into a lesser dimensional space, thus making easier to establish a relation between ecological space and geostatistical descriptors. Once established this relation can be exploited through the use of regression techniques in a regression kriging framework. In this case study, we applied the proposed model to the prediction of soil organic carbon content in an alpine grassland. The use of plant communities cover almost doubled the predictive power of the model from an R2 of 0.32 to an R2 of 0.66 in cross-validation, a result which strongly advocates for the efficiency of the proposed approach.</br

MARS Bulletin 2011 Vol.19 No.12 - Rice monitoring in Europe

Highlights Rice production at EU-27 level is forecast to be close to last year’s values (+0.7%) and is characterized by average yield potential all over Europe. In fact with the exception of very good expectation in France (+10.4%) and Spain (+3.2) yields were around the 5-year average. The decrease in surface at EU-27 level is attributed to the reduction in the cultivated areas in Italy (-0.5% with respect to 2010), Spain (-0.3%) and especially in France (-10.8%) where the lack of rainfall might have further reduced the rice fields.JRC.H.4-Monitoring agricultural resource