May 2023 Research Review

Spring’s early bloom: Farmers’ adaptations and keeping crop models in sync

By Devan Craneand Emily Jack-ScottAspen Global Change Institute

In some parts of the world, spring brings rains, warmer temperatures, singing birds, and flowering blooms. We tend to think of spring’s arrival as something that just “happens,” but the spring awakening in the plant world is governed by the finely tuned relationship between plants, animals, and Earth’s weather and climate. Cues like precipitation, temperature, day length, and wind induce life events in plants such as bud burst, leaf out, flowering, pollen dispersal, and leaf senescence (Zhang and Liu 2022).

Climate change-induced warmer temperatures are causing many plants in temperate climates to exhibit spring behavior, like blooms and budburst, much earlier in the year (Figure 1, Vitasse et al. 2022). This change in the timing of the annual cycle of plant developmental stages, or phenology, in turn produces massive ripple effects that impact human health, cultural practices, farmer livelihoods, and food security (Zhang and Liu 2022; Minoli et al. 2022).

Figure 1. The average January-March global air temperatures for select regions (a), and the historical timing of blooms of different plants in those regions (c-g). The thick gray lines represent the ten-year moving average for each plant, shifting earlier in the year in conjunction with a great acceleration in warming average spring temperatures since 1950 (highlighted in yellow). Source: Vitasse et al. 2022.

The influence of climate change on plant phenology and increased pollen loads has significant implications for human health, particularly for individuals with asthma and allergies. Pollen-related medical bills in the United States alone have exceeded $3 billion annually.

Changing phenology also impacts plants with cultural and medicinal significance, some of which have been used for centuries to nourish the body, heal wounds, or aid in ceremonies. With optimal growing conditions rapidly favoring higher latitudes and elevations, plant populations unable to migrate quickly can decline at alarming rates and even face the threat of extinction. This is the case for dozens of medicinal plants in Nepal, where 83 percent of the population relies primarily on herbal remedies. The quality and medicinal properties of such plants can be impacted as well by suboptimal growing conditions.

Shifting plant phenology also affects the distribution and productivity of major food crops. Current research and modeling efforts increase our understanding of plant phenology and allow for informed decision-making and adaptation strategies.

Impacts of Changing Phenology on Food Crops

Recent studies have shown that the changing climate alters crop phenology, ultimately affecting crop yields (Zhang and Liu 2022; Minoli et al. 2022). Warming temperatures are projected to cause global reductions in future crop yields, though the extent of losses will vary by crop and region and depend on whether adaptation strategies are applied (Zhang and Liu 2022; Minoli et al. 2022; Ishtiaque 2023). Elevated temperatures are a primary mechanism through which climate change affects crop phenology (Minoli et al. 2022). As temperatures warm, spring begins earlier in many temperate climates, lengthening the growing season for some crops and shortening the growing season for others (Zhang and Liu 2022).

Development phases like anthesis, the flowering phase of a plant, are also affected by climate-driven phenological shifts. Flowering plants require a certain amount of daily light exposure, or photoperiod, to induce flowering. So while plants may sprout earlier in the year due to warmer temperatures, they still require the same photoperiod to flower, as sunlight is determined by the rotation of the Earth and remains relatively unchanged from year to year. Crops that mature earlier in the year, out of alignment with optimal photoperiods, can be stalled in their development (Zhang and Liu 2022). Overwintering crops sown in the fall may see a longer growing season due to earlier spring or warmer winters and, in turn, may not experience the number of cold hours they need to induce the next phenological phase (Zhang and Liu 2022; Minoli et al. 2022). When farmers sow their crops earlier to counter earlier warming, all subsequent phases of plant growth and development are affected (Zhang and Liu 2022). One way farmers can realign plant growth with phenological shifts is to choose cultivars with adapted growing requirements, such as high heat tolerances, improved drought tolerance, or later flowering or maturity (Minoli et al. 2022).

In a 2022 article in Forest and Agricultural Meteorology authors Jie Zhang and Yujie Liu analyze the impacts of climate change and adaptive management on various phenological phases of cash crops like peanuts, canola, and sorghum. These crops are in increasingly heavy demand in places like China, where rising incomes are leading to dietary shifts that favor their production.

Zhang and Liu grouped phenophases into growth periods for three cash crops: a) the whole growth period from when a seed is planted through its maturation into a harvestable crop; b) the vegetative growth period of the plant before it reaches the reproductive stage; and c) the reproductive growth period, including flowering, pollination, and development of a seed, nut, or fruit. The influence of climate change on phenological shift varies across the different crops (see Figure 2). The maturity date was delayed for sorghum and canola, while it advanced for peanuts. Adaptive management strategies can offset the effects of climate change positively in each crop at different stages (Zhang and Liu 2022).

Figure 2. “Changing trends of phenology caused by climatic factors.” Trends are broken down by each crop’s phenological phases and the change of day + or – per year. “Central horizontal line: median; white dots: average; box limit: 25th and 75th percentiles; whiskers: minimum and maximum values.” WGP – Whole Growth Period, RGP – Reproductive Growth Period, VGP – Vegetative Growth Period – phenophases within each growth period vary by crop.” Source: Zhang and Liu 2022.

How Farmers Are Adapting to Changing Phenology

So how are farmers responding to the impacts of such dramatic changes in plant phenology?

In a 2023 review paper published in Environmental Research Climate, Asif Ishtiaque comprehensively reviewed published scientific papers on how U.S. farmers are adapting to climate change and preparing for the future; the paper also included farmer perspectives on whether to adapt at all.

Ishtiaque identified five types of adaptation strategies: water management, crop management, nutrient management, technological management, and financial management. While the reviewed studies focused on adaptation to various climate change impacts (e.g., drought, flooding, other hazards), many of the strategies identified have relevance for adapting to the changing phenology of crops.

Ishtiaque found that U.S. farmers are already adapting by planting different crop varieties (or cultivars), diversifying and rotating which crops are grown, shifting planting dates, improving soil health and applying fertilizers, adopting new irrigation practices, trying out new technologies, and investing in crop insurance. These adaptations mirror the strategies Zhang and Liu refer to in their analysis on phenological shifts of cash crops amid adaptive management.

Often, farmers adopt multiple strategies at once to adapt to changing plant phenology. For instance, a farmer may plant earlier in the season; plant a new, hardier cultivar better adapted to a changing growing season; install hail nets to protect the crop during earlier growing conditions; and invest in crop insurance to mitigate potential yield losses from droughts or other hazards stemming from new planting dates and crop varieties.

Some articles in Ishtiaque’s study also underscore the challenge of adaptation. Research finds that U.S. farmers often have taken a reactive approach to adapting to changing phenology and climate impacts more generally. Many U.S. farmers are not connected to, inclined to access, or trained to use climate information about future conditions that could inform longer-term planning. Rather, they respond to weather and climate impacts after they occur.

Farmers’ adoption of adaptation strategies also has been heavily tied to whether they believe climate change is human caused and happening now. In addition, farmers with a high level of “techno-optimism” are slower to implement adaptations, believing that technological solutions alone will be sufficient to mitigate crop losses.

Farmers who are disconnected from climate information, or disinclined to believe it, run a greater risk of jeopardizing their own long-term livelihoods as well as future food security.

Representing Adaptations on Farms in Models

One takeaway of Ishtiaque’s review is the need to better document adaptation strategies. This same conclusion is emphasized in a 2023 paper published in Current Opinion in Environmental Sustainability by Aidan Farrell, Delphine Deryng, and Henry Neufeldt on the extent to which crop models currently capture crop adaptations on the ground.

Farrell and colleagues found that crop yield models can represent a few adaptations, like improved fertilizer and water management or planting timelines relatively well, but the vast majority of adaptation options available to farmers are not included in models sufficiently, if at all (see Table 1). In large part, this is because many agricultural models are process driven and require large volumes of data to represent detailed biophysical climate processes and factors that affect crop yields, such as photosynthesis rates; soil, water, and nutrient dynamics; heat and water stress; evapotranspiration; and CO2 effects.

When data is limited, as is the case for many adaptation strategies that are adopted on small scales, there simply isn’t enough information to include the full array of adaptation options available in process-driven models. So these models often can’t analyze scenarios that accurately portray the diversity of adaptations available to farmers, let alone their efficacy in mitigating climate impacts on specific crop yields.

Table 1. “On-farm adaptation options and the frequency with which they are included in modelling studies.” Source: Farrell et al. 2023.

The underrepresentation of farm adaptations in models is important because model scenarios are one of the ways policymakers and other decision-makers assess and prepare for the impacts of climate change on our food systems. Also, using models that do not consider human responses and adaptations can overestimate the impacts of climate change on crops (Minoli et al. 2022).

One way to address this challenge is to improve data availability on the implementation and evaluation of different adaptation strategies actively used on farms. This would require interdisciplinary collaboration and a more standardized data-gathering process when adaptations are implemented on farms. Big data and machine learning may prove critical in surmounting this barrier.

Another solution could be to include results from other model types alongside the results from process-based models. Integrated assessment models, for example, have more flexible data requirements and modeling approaches, so they can represent a wider array of adaptation strategies, farmer management practices, crop phenological phases and development parameters, and dynamic planting calendars (Franke et al. 2021; Minoli et al. 2022).

Including these parameters in crop models is critical because they can drastically change yield scenarios (Franke et al. 2021; Zhang and Liu 2022; Minoli et al. 2022). Figure 3 shows the benefits to global yield when adaptation strategies are used. “All crops saw increased yields with adaptation strategies and the highest yields were seen when both sowing and cultivar adaptation are combined (except for wheat)” (Minoli et al. 2022).

Figure 3. “Benefits of sowing and cultivar adaptation on global crop yields under the RCP6.0 climate model projections for 2080-2099. Benefits on global yields are reported for all crops aggregated and for each individual crop, along with the uncertainty under different climate scenarios. The four adaptation scenarios indicate different levels of adaptation (adapt.): timely adaptation, sowing dates and cultivars adapted as the climate is changing (2080−2099); cultivar adaptation, sowing fixed at the reference level, only cultivars adapted as in timely adaptation; sowing date adaptation, only sowing dates adapted as in timely adaptation, cultivars fixed at the reference level; delayed adaptation both sowing dates and cultivar adapted but with 20-years delay, to 2060−2079 climate. The global yield of an individual crop is computed as the area- weighted mean yield across all grid cells growing that crop. In grid cells where adaptation of growing periods returned either no benefit or maladaptation (yield difference is equal or larger zero) yield losses were considered equal zero. Bars represent the mean across GCMs (n = 4 GCMs), whiskers display the range across GCMs, and gray symbols refer to individual GCMs.” Source: Minoli et al. 2022.

Future Opportunities

Several of the study authors mentioned here have proposed priority areas for future inquiry and research application.

Ishtiaque advocates for improved study of under-modeled adaptation strategies. In the meantime, he emphasizes that as policymakers and decision-makers consider on-farm adaptation strategies, it is critical they not minimize the potential of not-yet-to-scale options to be included in models. Farrell and colleagues argue that many of the underrepresented adaptation strategies (such as agroforestry, soil conservation, and crop diversification) have promise and should not be overlooked by policymakers and climate adaptation professionals when giving farmers climate information and guidance on how to plan for food security.

Ishtiaque also calls for better analysis of how farmers’ race and ethnicity factors into their adoption of adaptation strategies, as race and ethnicity greatly influence farmers’ relationships with and trust of public agencies, their access to information, and their access to lines of credit for adaptation investments. Black farmers disproportionately have marginalized land that is more hazard prone, especially in a changing climate.

For all farmers, the financial implications of reactive versus proactive adaptation strategies need to be better understood. Farmer perspectives and psychological barriers should also be better researched and considered as government agencies work to develop messaging and strategies to share information on future climate conditions.

Featured research:

Farrell, A.D., D. Deryng, D. and H. Neufeldt, H., 2023. “Modelling Adaptation and Transformative Adaptation in Cropping Systems: Recent Advances and Future Directions,”. Current Opinion in Environmental Sustainability, 61, (2023): p.101265.

Franke, J.A., Müller, C., Minoli, S., Elliott, J., Folberth, C., Gardner, C., Hank, T., Izaurralde, R.C., Jägermeyr, J., Jones, C.D. and Liu, W., 2022., “Agricultural Breadbaskets Shift Poleward Given Adaptive Farmer Behavior Under Climate Change,”. Global Change Biology, 28, no.1 (2022): pp. 167-181.

Ishtiaque, A., 2023.  “US Farmers’ Adaptations to Climate Change: A Systematic Review of the Adaptation-Focused Studies in the US Agriculture Context,”. Environmental Research: Climate. 2 (2023): 022001.

Minoli , S., Jägermeyr, J., Asseng, S., Urfels, A. and Müller, C., 2022., “Global Crop Yields Can Be Lifted by Timely Adaptation of Growing Periods to Climate Change,”. Nature Communications, 13, no. 1 (2022): p.7079.

Vitasse, Y., Baumgarten, F., Zohner, C.M., Rutishauser, T., Pietragalla, B., Gehrig, R., Dai, J., Wang, H., Aono, Y. and Sparks, T.H., 2022. “The Great Acceleration of Plant Phenological Shifts,”. Nature Climate Change, 12, no. 4, (2022): pp.300-302.

Zhang, J. and Y. Liu, Y., 2022. “Decoupling of Impact Factors Reveals the Response of Cash Crops Phenology to Climate Change and Adaptive Management Practice,”. Agricultural and Forest Meteorology, 322, (2022):  p.109010.