Apple growers in the northeastern United States often experience spring freeze injury to their crops. During recent years, the cumulative effect of relatively mild winter temperatures has advanced leaf-emergence and bloom, leaving critical development stages vulnerable to the occurrence of subfreezing temperatures later in the spring. Such trends toward earlier leafing and bloom dates have been widely reported in the literature both for domestic fruit crops (Legave et al., 2013; Wolfe et al., 2005) and native species (Schwartz et al., 2006). This has raised concerns that warming winter temperatures may paradoxically increase the risk of spring freeze injury as accelerated development may not outpace the decline in the probability of subsequent below-freezing temperatures (Gu et al., 2008; Rosenzweig et al., 2011).
Globally, studies using both historical observations and estimates of future freeze risk in apples exhibit considerable regional variation. Across Japan, historical freeze risk has increased in the north, but not in other parts of the country (Sugiura, 2010). Historical spring freeze risk in apple-growing regions of Germany and central Europe shows little change in apple freeze risk which is consistent with similar trends toward earlier dates of both flowering and the last spring freeze (Kunz and Blanke, 2011; Scheifinger et al., 2003). Future estimates of apple freeze risk range from decreases in parts of Italy (Eccel et al., 2009) and Finland (Kaukoranta et al., 2010) to increases in Britain (Cannell and Smith, 1986) and parts of Germany (Hoffmann et al., 2012).
Hoffmann and Rath (2013) suggest that these differences arise from deficiencies in the biological models used to estimate phenology. They show that some improvement can be achieved by incorporating daylength in addition to temperature into apple development models, but find little physiological evidence for including this variable. The reliance on single climate model realizations coupled with inadequate adjustment for inherent biases in the models’ historical period simulations is also posed as a potential contributor to these differences.
Cannell and Smith (1986) summarized the complexities of assessing spring freeze risk. They point to three factors that must be considered to adequately estimate freeze risk: 1) the accumulation of winter chill units (CU); 2) the accumulation of growth units following the satisfaction of the winter chilling requirement; and 3) the probability of the occurrence of injurious subfreezing temperatures at the various stages of bud, leaf, and fruit development. Rigby and Porporato (2008) account for two of these factors in their generic assessment of spring freeze risk, but assume that the fulfillment of the winter chill requirement is fixed at 1 Mar., regardless of climate. Nonetheless, their study is an improvement over previous approaches in that they assess the impact of changes in parameters of the temperature distribution other than the mean. Using stochastically generated temperature series and a probabilistic freeze risk model, they conclude that changes in the daily variance of temperature are a more important determinant for freeze risk than changes in the mean.
Eccel et al. (2009) used a more sophisticated growth model (Rea and Eccel, 2006) to assess spring freeze risk to apple production. The model, a refinement of the Utah model (Ashcroft et al., 1977), accounts for winter chilling, developmental growth unit accumulation, and cold-temperature susceptibility. Downscaled global circulation model data were used to assess future freeze damage risk, but the changes in temperature mean and variance were constrained to those simulated in a the single model. They found little change (slight decline) in future freeze risk compared with today.
In this article, the approaches of Eccel et al. (2009) and Rigby and Porporato (2008) are combined. A stochastic model of daily maximum and minimum temperature that both replicates current conditions and can be modified to reflect changes consistent with climate model projections is combined with a freeze risk model that accounts for the satisfaction of winter chilling requirements, the accumulation of developmental growth units, and the freeze tolerance of various stages of plant development. The methods are applied to data representative of three apple-growing states. Regional differences in the seasonal cycle of mean temperature and daily temperature variance are proposed to be an important determinant of location-specific differences in future freeze risk.
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