M. Ines Minguez

Cereal–legume rotations in a Mediterranean environment: biomass and yield production

Abstract The effects of various crop rotations on the biomass and yield of barley (Hordeum vulgare L.), faba bean (Vicia faba L.), and pea (Pisum sativum L.) grown under Mediterranean conditions were studied during three growing seasons in the semiarid Spanish Central Plateau. The treatments comprised six crop sequences: barley monoculture, fallow–barley (currently used in the area), faba bean–barley, pea–barley, fallow–barley–faba bean, and fallow–barley–pea. The fallow was of 16-month duration. The site is representative of cultivated areas of the Plateau, and the soil has a loam texture. Results concentrate on barley as the main crop. Season distribution of rainfall restricted the effectiveness of the management practices and in consequence there were few differences between rotations. Barley had greater biomass and yield after fallow than after other crops but significant differences were dependent on year. Legumes, an alternative to fallow, increased land use, permitted alternative weed control measures, and reduced the need for fertiliser. The intensification of the fallow–barley cropping system is best achieved by reducing the frequency of fallow and including other crops of relatively small biomass production, thereby minimising the impact on yield of the succeeding barley crop.

Estimating fAPAR from Nine Vegetation Indices for Irrigated and Nonirrigated Faba Bean and Semileafless Pea Canopies

Abstract Canopy reflectance measurements of semileafless pea and faba bean crops grown under irrigated and rain-fed conditions were taken with a field spectroradiometer. These legume crops have different canopy architectures. During crop growth nine vegetation indices (VIs) were calculated from reflectance measurements taken in TM2, TM3, TM4, and TM5 bands. Five VIs were ratio indices, (RVI, NDVI, SAVI2, TSAVI, and RDVI), two were orthogonal indices (PVI and GVI3), and the other two (STVI and CRVI) included the mid-infrared band. The fraction of absorbed photosynthetically active radiation (fAPAR) from a ceptometer and reflectance were measured simultaneously. Linear, exponential, and power relationships between VI and fAPAR were constructed to evaluate the capability of each VI to estimate fAPAR in these crops. The influence of solar angle on VI determination was also studied, using reflectance measurements at several hours during the day at two different crop growth stages. Results show that, in both species, different relationships are needed for pre-and postmaximum leaf area index (LAImax) phases of development. In pre-LAImax of both species, all VI correlated highly with fAPAR, but the coefficients of determination ( R 2 ) for ratio indices were generally higher than orthogonal indices (PVI and GVI3) and indices with the TM5 band (STVI and CRVI). Among ratio indices, in pre-LAImax, R 2 did not differ significantly between those that included the soil effect (SAVI2 and TSAVI) and those that did not (RVI, NDVI, and RDVI). Relationships with indices that include the TM5 band (STVI and CRVI) showed a great slope, increasing the sensitivity of the estimation of fAPAR to errors and frequency of the reflectance measurements. During pre-LAImax phase, curvilinear relationships are better for pea canopies, while linear ones were found more appropriate for faba beans. In post-LAImax, linear relations were in general better, especially in peas. Relationships did not differ between irrigated and rainfed treatments within crops, even in early stages of growth with poor soil cover, so that only one was proposed for each species. All VI values were greatly affected by the hour of measurement at solar angles greater than 45°. The indices most affected by solar angle changes were STVI and CRVI. We can conclude that simple indices, RVI and NDVI, based on reflectance measurements in TM3 and TM4 bands can be used to accurately asses canopy development in faba bean and semileafless peas, allowing good and fast estimations of fAPAR and LAI, both important parameters in crop physiology and modeling. More research in different type of soils is needed to check if ratio, SAVI2 and TSAVI, or orthogonal, PVI and GVI3, indices that include the effect of soils can improve the estimation of fAPAR in these two crops.

Contribution of crop model structure, parameters and climate projections to uncertainty in climate change impact assessments

Climate change impact assessments are plagued with uncertainties from many sources, such as climate projections or the inadequacies in structure and parameters of the impact model. Previous studies tried to account for the uncertainty from one or two of these. Here, we developed a triple-ensemble probabilistic assessment using seven crop models, multiple sets of model parameters and eight contrasting climate projections together to comprehensively account for uncertainties from these three important sources. We demonstrated the approach in assessing climate change impact on barley growth and yield at Jokioinen, Finland in the Boreal climatic zone and Lleida, Spain in the Mediterranean climatic zone, for the 2050s. We further quantified and compared the contribution of crop model structure, crop model parameters and climate projections to the total variance of ensemble output using Analysis of Variance (ANOVA). Based on the triple-ensemble probabilistic assessment, the median of simulated yield change was -4% and +16%, and the probability of decreasing yield was 63% and 31% in the 2050s, at Jokioinen and Lleida, respectively, relative to 1981-2010. The contribution of crop model structure to the total variance of ensemble output was larger than that from downscaled climate projections and model parameters. The relative contribution of crop model parameters and downscaled climate projections to the total variance of ensemble output varied greatly among the seven crop models and between the two sites. The contribution of downscaled climate projections was on average larger than that of crop model parameters. This information on the uncertainty from different sources can be quite useful for model users to decide where to put the most effort when preparing or choosing models or parameters for impact analyses. We concluded that the triple-ensemble probabilistic approach that accounts for the uncertainties from multiple important sources provide more comprehensive information for quantifying uncertainties in climate change impact assessments as compared to the conventional approaches that are deterministic or only account for the uncertainties from one or two of the uncertainty sources.