Advances in Agronomy

1. Auflage 2015
ISBN: 978-0-12-803050-9
Verlag: Elsevier Science & Techn.
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, Band Volume 133, 260 Seiten

Reihe: Advances in Agronomy

Advances in Agronomy continues to be recognized as a leading reference and a first-rate source for the latest research in agronomy. Each volume contains an eclectic group of reviews by leading scientists throughout the world. As always, the subjects covered are varied and exemplary of the myriad of subject matter dealt with by this long-running serial. - Timely and state-of-the-art reviews - Distinguished, well recognized authors - A venerable and iconic review series - Timely publication of submitted reviews

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Chapter Two Climate Change Effects on the Suitability of an Agricultural Area to Maize Cultivation
Application of a New Hybrid Land Evaluation System
Antonello Bonfante*,1, Eugenia Monaco*, Silvia M. Alfieri*, Francesca De Lorenzi*, Piero Manna*, Angelo Basile* and Johan Bouma§     *Institute for Mediterranean Agricultural and Forest Systems (CNR-ISAFOM), Ercolano, Italy     §Soils Department, Wageningen University, The Netherlands
1 Corresponding author: E-mail: [e-mail] 
Abstract
Climate change is likely to have a major impact on agricultural production in Mediterranean regions, due to higher temperatures and lower water availability for irrigation. A Hybrid Land Evaluation System (HLES) is proposed allowing a comparison between plant demands on the one hand and estimated future temperatures and soil water regimes on the other. A storyline is followed for each plant species hybrid and each soil mapping unit in the area to be studied, starting with step 1: evaluation of thermal conditions, followed by step 2: a traditional empirical land evaluation procedure identifying limiting features that are not covered by crop simulation models (such as flooding, surface stones, salt). Step 3 applies the quantitative Soil–Water–Atmosphere–Plant (SWAP) model and calculates soil water regimes and associated productions, at 100%, 80%, and 60% hypothetical irrigation water availability. HLES was applied in the Destra Sele area in Italy, comparing two climates: “reference” (1961–1990) and “future” (2021–2050), studying 11 maize hybrids and showing that in future, 6 hybrids suffered severely at 80% water availability and 7 could not meet requirements at 60%. HLES allows a proactive approach to future water allocation issues and provides data for genetic modification studies in terms of defining hydrological conditions for sites of native plants and for areas where new hybrids are to be introduced. HLES presents options, to be explored in close interaction with users, rather than one-way judgments. Keywords
Climate change; Food security; Land evaluation; Maize; SWAP 1. Introduction
Climate change has a major impact on agriculture depending on the level of climatic change and the type of change in terms of, for example, precipitation and temperature patterns, in comparison with the local capacity to absorb the effects (Li et al., 2011). Important effects have been reported as a function of changes in the length of the growing season and occurrence of extreme events in critical phases of crop development (e.g., Southworth et al., 2000; Cutforth et al., 2007; Tingem and Rivington, 2009; Hatfield et al., 2011). Production potential depends on radiation and is greatly affected by temperature and rainfall (e.g., Olesen and Bindi, 2002) to the point that water shortages and heat stress represent the two most important environmental factors limiting crop growth, development, and yield (Meza et al., 2008; Prasad et al., 2008; Gornall et al., 2010). Only a few days of extreme temperatures (Tmax > 32 °C) at the ?owering stage can drastically reduce yields of many crops (Wheeler et al., 2000). A wide variety of studies have addressed the impacts of climatic change on agriculture (e.g., Kaiser et al., 1993; Rosenzweig and Parry, 1994; Riha et al., 1996; Izaurralde et al., 2003; Reilly et al., 2003; Tao et al., 2006) expressing impacts in terms of absolute or relative changes in crop productivity, water uptake, and resource use. In these studies relatively little attention is paid to the role of soils in determining the soil water regime. While the temperature directly affects crop growth, influencing the length of the growing season or the establishment of the different phenological stages, the effects of rainfall and irrigation on crop water availability are strongly related to the soil physical system as it is governed by soil horizons and their hydrological properties and to other climatic variables, such as evapotranspiration, strongly affecting the soil water balance. Even with identical climatic conditions, two soils with different hydrological behavior, may show a different degree of suitability for specific crop cultivation. This study will therefore pay special attention to the soil moisture regime. Different approaches are used in literature to examine the potential impact of climate change on crop yields: 1. Empirical, semiquantitative approaches to estimate crop productivity under climate change were, for instance, applied by Ewert et al. (2005) in Europe, documenting by surveys regional yield variability and temporal changes due to crop and management improvement. Hood et al. (2006) applied an expert-based multicriteria evaluation approach to assess land suitability for grapes and possible impacts of climate change (quanti?cation of climate impacts was based on climate indices such as heat degree days, frost days, and rainfall aggregated over speci?c periods). Brown et al. (2008) derived their evaluation of agricultural suitability from estimates of soil moisture de?cit and accumulated temperature over the growing period. Tuan et al. (2011) applied a multicriteria evaluation of temperature and precipitation to suitability for winter wheat and maize in the Huang-Huai-Hai Plain in China. Land suitabilities have widely been determined using traditional land evaluation (LE) procedures, comparing crop demands with land qualities, expressed in terms of soil characteristics. So far, this was not particularly focused on climate change (e.g., FAO, 1976; Bonfante et al., 2011; van Delden et al., 2011; Bouma et al., 2012). Such land suitability evaluations are based on qualitative and semiquantitative approaches that require a basic understanding of landscape conditions and crop yields, subject to future climatic and hydrological conditions. This type of evaluation is nearly impossible because the dynamic processes of the soil–plant–atmosphere system are not considered when coping with rapidly changing scenarios for agricultural and environmental issues (Manna et al., 2009). Finally, empirical evaluation approaches focusing on crops are based on agroclimatic indices calculated on an annual basis for relevant phenological phases (Holzkämper et al., 2013). 2. Statistical approaches in which historical data on crop yields and weather are used to calibrate relatively simple regression equations. Lobell and Burke (2010) identified, for instance, three main types of statistical approaches in scientific literature: those based purely on time series data from a single point or area (time series methods); those based on variations both in time and space (panel methods) and those based solely on variations in space (cross-section methods) (e.g., Lobell and Ortiz-Monasterio, 2007). Statistical approaches are often limited by data quality and quantity (e.g., time series) or by unavailable variables such as soil quality or fertilizer inputs that vary spatially (Lobell and Burke, 2010). In particular, they are subject to problems of colinearity between predictor variables (e.g., temperature and precipitation), unrealistic assumptions of stationarity (e.g., that past relationships will hold in the future, even if management systems evolve), and low signal-to-noise ratios in yield or weather records in many locations (Lobell and Burke, 2010). An example of the colinearity problem was highlighted by Sheehy et al. (2006) with respect to the statistical models of Peng et al. (2004), which showed a 10% decline of Philippine rice yields with a 1 °C increase in average minimum temperature (Tmin). Sheehy et al. (2006) argued that solar radiation was a strong negative correlate of Tmin, and thus an apparent negative effect of warming could easily arise from a positive effect of higher solar radiation. 3. Process-based crop simulation models (hereafter referred to as crop models) are a commonly used tool for impact assessment of climate variability and change on crop yields on large areas (e.g., Olesen and Bindi, 2002; Parry et al., 2004; Xiong et al., 2008; Challinor et al., 2010; Rötter et al., 2011; Xiang et al., 2011); CERES–maize or EPIC models (Phillips et al., 1999; Rosenzweig et al., 2002; Tan and Shibasaki, 2003), CropSyst (Sommer et al., 2013) or APSIM model (Akponikpe et al., 2010; Tachie-Obeng et al., 2012) provide process-based simulation of agricultural systems response to climatic changes. Crop simulation models require: (1) a thorough understanding of the soil–plant–atmosphere system; (2) an adequate and robust data set, which is often lacking; (3) site-specific calibration and validation of the model, which is indispensable to improve the accuracy of yield estimations in climate change studies (Wolf et al., 1996; Jagtap et al., 2002); (4) an updated crop parameter data set because available model parameters often refer to old varieties; (Rötter et al., 2011) and (5) a high computational capacity. The application of complex crop models can be computationally intensive and, due to model...