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1. Widespread Advances in Corn and Soybean Phenology in Response to Future Climate Change Across the United States

   https://doi.org/10.1029/2024JG008266  

   Yang, Yanjun; Tao, Bo; Ruane, Alex C; Shen, Chaopeng; Matteson, David S; Cousin, Rémi; Ren, Wei (April 2025, Journal of Geophysical Research: Biogeosciences)

   Abstract Crop phenology regulates seasonal carbon and water fluxes between croplands and the atmosphere and provides essential information for monitoring and predicting crop growth dynamics and productivity. However, under rapid climate change and more frequent extreme events, future changes in crop phenological shifts have not been well investigated and fully considered in earth system modeling and regional climate assessments. Here, we propose an innovative approach combining remote sensing imagery and machine learning (ML) with climate and survey data to predict future crop phenological shifts across the US corn and soybean systems. Specifically, our projected findings demonstrate distinct acceleration patterns—under the RCP 4.5/RCP 8.5 scenarios, corn planting, silking, maturity, and harvesting stages would significantly advance by 0.94/1.66, 1.13/2.45, 0.89/2.68, and 1.04/2.16 days/decade during 2021–2099, respectively. Soybeans exhibit more muted responses with phenological stages showing relatively smaller negative trends (0.59, 1.08, 0.07, and 0.64 days/decade under the RCP 4.5 vs. 1.24, 1.53, 0.92, and 1.04 days/decade under the RCP 8.5). These spatially explicit projections illustrate how crop phenology would respond to future climate change, highlighting widespread and progressively earlier phenological timing. Based on these findings, we call for a specific effort to quantify the cascading effects of future phenology shifts on crop yield and carbon, water, and energy balances and, accordingly, craft targeted adaptive strategies. 

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2. Observation-based sowing dates and cultivars significantly affect yield and irrigation for some crops in the Community Land Model (CLM5)

   https://doi.org/10.5194/gmd-16-7253-2023  

   Rabin, Sam S; Sacks, William J; Lombardozzi, Danica L; Xia, Lili; Robock, Alan (January 2023, Geoscientific Model Development)

   Abstract. Farmers around the world time the planting of their crops to optimize growing season conditions and choose varieties that grow slowly enough to take advantage of the entire growing season while minimizing the risk of late-season kill. As climate changes, these strategies will be an important component of agricultural adaptation. Thus, it is critical that the global models used to project crop productivity under future conditions are able to realistically simulate growing season timing. This is especially important for climate- and hydrosphere-coupled crop models, where the intra-annual timing of crop growth and management affects regional weather and water availability. We have improved the crop module of the Community Land Model (CLM) to allow the use of externally specified crop planting dates and maturity requirements. In this way, CLM can use alternative algorithms for future crop calendars that are potentially more accurate and/or flexible than the built-in methods. Using observation-derived planting and maturity inputs reduces bias in the mean simulated global yield of sugarcane and cotton but increases bias for corn, spring wheat, and especially rice. These inputs also reduce simulated global irrigation demand by 15 %, much of which is associated with particular regions of corn and rice cultivation. Finally, we discuss how our results suggest areas for improvement in CLM and, potentially, similar crop models. 

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3. Modeling the Impacts of Climate Change on Crop Yield and Irrigation in the Monocacy River Watershed, USA

   https://doi.org/10.3390/cli8120139  

   Paul, Manashi; Dangol, Sijal; Kholodovsky, Vitaly; Sapkota, Amy R.; Negahban-Azar, Masoud; Lansing, Stephanie (December 2020, Climate)

   null (Ed.)

   Crop yield depends on multiple factors, including climate conditions, soil characteristics, and available water. The objective of this study was to evaluate the impact of projected temperature and precipitation changes on crop yields in the Monocacy River Watershed in the Mid-Atlantic United States based on climate change scenarios. The Soil and Water Assessment Tool (SWAT) was applied to simulate watershed hydrology and crop yield. To evaluate the effect of future climate projections, four global climate models (GCMs) and three representative concentration pathways (RCP 4.5, 6, and 8.5) were used in the SWAT model. According to all GCMs and RCPs, a warmer climate with a wetter Autumn and Spring and a drier late Summer season is anticipated by mid and late century in this region. To evaluate future management strategies, water budget and crop yields were assessed for two scenarios: current rainfed and adaptive irrigated conditions. Irrigation would improve corn yields during mid-century across all scenarios. However, prolonged irrigation would have a negative impact due to nutrients runoff on both corn and soybean yields compared to rainfed condition. Decision tree analysis indicated that corn and soybean yields are most influenced by soil moisture, temperature, and precipitation as well as the water management practice used (i.e., rainfed or irrigated). The computed values from the SWAT modeling can be used as guidelines for water resource managers in this watershed to plan for projected water shortages and manage crop yields based on projected climate change conditions. 

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4. Precipitation versus temperature as phenology controls in drylands

   https://doi.org/10.1002/ecy.3793  

   Currier, Courtney M.; Sala, Osvaldo E. (July 2022, Ecology)

   Abstract Cycles of plant growth, termed phenology, are tightly linked to environmental controls. The length of time spent growing, bounded by the start and end of season, is an important determinant of the global carbon, water, and energy balance. Much focus has been given to global warming and consequences for shifts in growing‐season length in temperate regions. In conjunction with warming temperatures, altered precipitation regimes are another facet of climate change that have potentially larger consequences than temperature in dryland phenology globally. We experimentally manipulated incoming precipitation in a semiarid grassland for over a decade and recorded plant phenology at the daily scale for 7 years. We found precipitation to have a strong relationship with the timing of grass greenup and senescence but temperature had only a modest effect size on grass greenup. Pre‐season drought strongly resulted in delayed grass greenup dates and shorter growing‐season lengths. Spring and summer drought corresponded with earlier grass senescence, whereas higher precipitation accumulation over these seasons corresponded with delayed grass senescence. However, extremely wet conditions diluted this effect and caused a plateaued response. Deep‐rooted woody shrubs showed few effects of variable precipitation or temperature on phenology and displayed consistent annual phenological timing compared with grasses. Whereas rising temperatures have already elicited phenological consequences and extended growing‐season length for mid and high‐latitude ecosystems, precipitation change will be the major driver of phenological change in drylands that cover 40% of the land surface with consequences for the global carbon, water, and energy balance. 

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5. Characterizing Growing Season Length of Subtropical Coniferous Forests with a Phenological Model

   https://doi.org/10.3390/f12010095  

   Gong, Yuan; Staudhammer, Christina L.; Wiesner, Susanne; Starr, Gregory; Zhang, Yinlong (January 2021, Forests)

   null (Ed.)

   Understanding plant phenological change is of great concern in the context of global climate change. Phenological models can aid in understanding and predicting growing season changes and can be parameterized with gross primary production (GPP) estimated using the eddy covariance (EC) technique. This study used nine years of EC-derived GPP data from three mature subtropical longleaf pine forests in the southeastern United States with differing soil water holding capacity in combination with site-specific micrometeorological data to parameterize a photosynthesis-based phenological model. We evaluated how weather conditions and prescribed fire led to variation in the ecosystem phenological processes. The results suggest that soil water availability had an effect on phenology, and greater soil water availability was associated with a longer growing season (LOS). We also observed that prescribed fire, a common forest management activity in the region, had a limited impact on phenological processes. Dormant season fire had no significant effect on phenological processes by site, but we observed differences in the start of the growing season (SOS) between fire and non-fire years. Fire delayed SOS by 10 d ± 5 d (SE), and this effect was greater with higher soil water availability, extending SOS by 18 d on average. Fire was also associated with increased sensitivity of spring phenology to radiation and air temperature. We found that interannual climate change and periodic weather anomalies (flood, short-term drought, and long-term drought), controlled annual ecosystem phenological processes more than prescribed fire. When water availability increased following short-term summer drought, the growing season was extended. With future climate change, subtropical areas of the Southeastern US are expected to experience more frequent short-term droughts, which could shorten the region’s growing season and lead to a reduction in the longleaf pine ecosystem’s carbon sequestration capacity. 

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