Use of growing degree indicator for developing adaptive responses: A case study of cotton in Florida

Abstract

Significant variabilities in planting and harvesting dates of crops have been observed throughout Florida in recent decades, indicating a change in their phenology. This study innovatively uses an agroecosystem indicator, growing degree days (GDD), to understand the change in cotton crop phenology throughout the region and develop adaptation strategies using the Driver‐Pressure‐State‐Impact‐Response (DPSIR) framework. GDD is the amount of heat absorbed by the growing stages of cotton. It is computed from temperature simulations obtained from the 21 models participating in the Coupled Model Inter-comparison Project Phase 5 (CMIP5) for the historical (1950–2005) and future scenarios (Representative concentration pathway (RCP) 8.5, 2006–2100) at a spatial resolution of 0.125°x0.125°. The future projections from the 21 models show an increase in surface temperature ranging from 3.5 °C to 5.5 °C. Additionally, the variability in dates for the different phenological stages shows an early occurrence of the simulation’s growth stages. Historically, the minimum and maximum ranges of trend shift towards the funnel’s negative side in the RCP 8.5 scenarios. The trends are estimated for two time-periods during historical (1950–1975 and 1976–2005) and future (2006–2050 and 2015–2100) periods of time. They ranged from −3.5 to 3.4 days per decade and −3.6 to 0 (no change) days per decade, respectively, among the six stages namely: emergence stage, the appearance of the first square, the appearance of the first flower, peak blooming, first open boll, and defoliation. Warming accelerated plant growth and shortened the growing period, which is translated to develop adaptation strategies for a climate-resilient crop production system, using casual chain/loops and the DPSIR framework. Identifying the multiple adaptation strategies for levels of adaptation and degree of climate change and variability can be used by different stakeholders and policymakers as a guide for making decisions to adapt cotton to climate change better. Although this methodology is applied to the cotton crop in Florida, it can be used for other crops and regions of the world.