Back

Simulating the Impacts of Climate Change on UH Manoa Lettuce (Lactuca sativa) Growth by Modifying Air Temperature, Soil Water Availability, and Atmospheric CO2 Concentration

Yos, N.; Mora, C.; Webster, K.; McDowell, K.

2025-08-18 plant biology
10.1101/2025.08.13.670242 bioRxiv
Show abstract

Plant species are adapted to survive under specific ranges of temperature, water availability, and atmospheric CO2 concentration. Climate change-induced shifts in these environmental conditions have the potential to significantly affect nearly all terrestrial plants. A number of studies have explored the impacts of changing one or two of the conditions listed above, but few have examined the combined effects of all three. To study the cumulative influences of the three environmental conditions, 350 M[a]noa lettuce (Lactuca sativa) plants were grown in indoor growth chambers. Within the chambers, plants were grown under varying degrees of CO2 concentration, water availability, and temperature for 21 days. At the end of this period, the leaf mass (biomass) of each plant was cut, dried, and weighed. Percent mortality and nitrogen content were also measured. Across all combinations of temperature and water availability, elevated CO2 concentrations were associated with increased biomass production and survival rates. Survival and biomass decreased under high temperatures and both high and low water availability. The combination of environmental conditions that produced the largest amount of biomass was 750 ppm CO2, 80% of soil water capacity, and 24 {degrees}C while the treatment that produced the least amount was ambient CO2, 60% of soil water capacity, and 36 {degrees}C. Nitrogen content increased under high temperatures and water availability. These results suggest that although increased atmospheric CO2 levels have the potential to promote lettuce growth, lettuce yield is still likely to decrease in many regions due to the negative effects of high temperatures, drought, and flooding.

Matching journals

The top 1 journal accounts for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.