Effects of climate variation on winter cereal production in Spain

Abstract

Climate variables responsible for inter-annual variations in the winter cereal yield in Spain were identified and climate information was translated into crop production. Empirical orthogonal functions and correlation analyses were applied to regional and large-scale climate variables to ascertain the links between climate and winter cereal yield. Interactions between climate and winter cereal productivity in Spain can be summarized as follows: the start of the growing season depends on minimum temperature, and crop maturity is affected by drought, maximum temperature, sea-level air pressure, moisture fluxes, and the jet stream, as well as by indices of the Scandinavian Pattern, the North Atlantic Oscillation, and the Southern Oscillation. A statistical approach has been derived to describe variability in cereal productivity in Spain taking into account the previous potential predictors. In general, the best atmospheric conditions for increasing winter cereal productivity in Spain are warmer winters, cooler and wet springs, with prevalent meridional circulation at upper levels. The observed trend of increasing sea level pressure toward the western Mediterranean could cause a loss in the winter cereal yield. KEY WORDS: Climate variability · Winter cereal · Principal component analysis · Regression model Resale or republication not permitted without written consent of the publisherClim Res 34: [223][224][225][226][227][228][229][230][231][232] 2007 ENSO and NAO on marine and terrestrial ecosystems. General Circulation Models (GCMs) provide new opportunities for investigating the impacts of climate change on agriculture. Within this line are the studies of Rosenzweig et al. (2002), who simulated the damage of heavy precipitation on crop growing, and Thomson et al. (2005), who found that winter wheat production under irrigation appears likely to increase under climate change. The simulation of winter wheat yields (Song et al. 2006) gives a trend towards yield increase in northern China and a yield decrease in southern China. Adejuwon (2006) obtained crop yield simulations from GCMs for Nigeria for 3 periods of the 21st century, explaining the lower yields in terms of global warming. In Europe, Schroter et al. (2005) analysed the vulnerability of crops due to climate change, and Harrison et al. (2000) assessed wheat yield simulation. Due to the imprecision of model simulations, Cantelaube & Terres (2005) considered the multimodel seasonal forecast information to provide an ensemble of yield simulations, while Mearns et al. (2003) considered higher resolution models to study the impact of climate variability and change on agriculture. and Hansen & Sivakumar (2006) provided the advances in climate-based crop forecasting.The estimation of the effects of climate variations on the production of Spanish winter cereal has only been evaluated at a few particular locations. For example, Vicente-Serrano et al. (2006) considered drought indices and remote sensing data to predict wheat and barley yields in Ebro v...

Wheat yield in Spain and associated solar radiation patterns

“…The PLS regression was also applied by Ceglar et al (2016) and Leng et al (2016) with the aim of selecting variables associated with crops and excluding co-variability among predictors. However, we used PLS regression not only for dimension reduction, as in EOF analysis applied in earlier studies (Cantelaube et al, 2004;Rodriguez-Puebla et al, 2007) but also to provide co-variability between wheat yield and SSRD. Thus, making the PLS approach better at identifying the response of wheat yield to solar radiation.…”

“…() identified relationships between the ENSO and the NAO with agricultural yield; Rodriguez‐Puebla et al . () found an association between winter cereal and the Southern Oscillation index, the Scandinavian and the NAO patterns; Capa‐Morocho et al . () found non‐stationary relationships between El Niño and maize.…”

“…In Morocco, Jarlan et al (2014) determined the association between wheat yield and the NAO and the ENSO. In Spain, Gimeno et al (2002) identified relationships between the ENSO and the NAO with agricultural yield; Rodriguez-Puebla et al (2007) found an association between winter cereal and the Southern Oscillation index, the Scandinavian and the NAO patterns; Capa-Morocho et al (2016) found non-stationary relationships between El Niño and maize. This paper is structured as follows: Section 2 presents the data and methods used, including the statistical approaches of partial least squares (PLS) regression, ensemble empirical mode decomposition (EEMD), and K-means cluster analysis.…”

Changes in seasonal precipitation in the Iberian Peninsula during 1946–2005

“…From an ecological point of view, the decrease in precipitation in winter and spring is not compensated by the increases observed in autumn due to the fact that the majority of Mediterranean species develop most of their vegetative period in these seasons (Ceballos et al, 2004;De Luis et al, 2009b). These changes presuppose lower availability of water at the beginning of the growth season and less water stored for summer drought, with obvious alterations in the growth patterns of forest species and clear implications for agriculture, particularly winter cereal crops (Rodríguez-Puebla et al, 2007). Given that winter and spring precipitation is crucial for many tree species, and for crops and pastures, there might be serious consequences in this respect if future trends are maintained.…”

Simulating the effect of the North Atlantic Oscillation on frost injury in winter wheat

“…The NAO has a significant effect on the agricultural sector, for example on the grain yield of wheat (Gi me no et al 2002, Cantelaube et al 2004, Rodriguez-Puebla et al 2007) and rye (Gimeno et al 2002), and on the grain quality of wheat (Atkinson et al 2005, Atkinson et al 2008. The NAO also affects non-cereal crops, such as lemons and olives in southern Europe (Gimeno et al 2002).…”