Jeffrey R. Taylor and Dr. Bruce A. Roundy, Botany and Range Science
A hydrothermal time model can be a useful tool to predict when seeds will germinate. These models use soil moisture and temperature data to predict when a seed will germinate and can be applied to a variety of species and under the dynamic environmental conditions of field seedbeds.1 Understanding the conditions necessary for desirable or weedy species to emerge can help land managers control weedy species and establish useful plants. Validation of hydrothermal models require accurate measurements of soil water potential in the vicinity of seeds. The purpose of this experiment was twofold: 1) To compare four soil moisture sensors 2) To see how well each soil moisture sensor predicts germination using a hydrothermal time model.
Weedy plants have been problematic for many years. Species such as cheatgrass [Bromus tectorum] have disrupted native plant communities by competing with other species and by increasing fire frequency. In some areas, desirable species are less numerous because of competition, stress, or changes in the environment. By understanding germination requirements necessary for different plants, it may be possible for land managers to plant species that will compete with weedy species. We studied germination for six species of grass to better understand these requirements. These species were Bromus tectorum, Stipa capensis, Bromus fasciculatus, Brachypodium distachyon, Crithopsis deliciana, and Sitanion hystrix.
We used four different soil moisture sensors in this experiment: gypsum blocks, Colman cells, Watermark sensors, and time domain reflectometry (TDR). In addition to soil moisture sensors, we also used thermocouple wire to measure soil temperature. We placed the sensors in plastic containers and then filled the containers with a sandy, structureless soil. Four sensors of each type were placed at two depths (both 1-3 cm and 4-6 cm below the soil surface) except for the TDR sensor (a single large sensor which was placed 4.5 cm below the soil surface). The containers were placed in a growth chamber that was programmed to approximate the air temperature of an average spring day in Provo, Utah. Each of the sensors was connected to a multiplexer and then to a micrologger that recorded the data. In addition, we planted 50 seeds of 11 seed accessions in each container. The containers were then watered with one of four watering treatments and seedling density was recorded for each seed accession during subsequent days.
Soil water content data were converted into matric potential (MPa). Matric potential is a measurement of how tightly water is held to soil particles. Low numbers (less than -1.5 MPa) generally mean that the soil is very dry and the water in the soil is less available to plants. In contrast, higher numbers (close to 0 MPa) mean that there is more water in the soil and that it is more available to plants. Soil moisture data varied among all of the sensors. The Colman cells showed the greatest sensitivity. The other sensors remained fairly consistent with one another although the gypsum blocks showed that the soil was dry before the Watermark and the TDR sensors. The Watermark and the TDR sensors generally showed that the soil was wetter than the Colman cells and the gypsum blocks.
Seedling emergence varied greatly between treatments. No seedlings germinated in the driest watering treatment. The second driest watering treatment provided enough water so that Stipa capensis, Bromus tectorum, Crithopsis deliciana and Bromus fasciculatus seeds germinated. In addition to the aforementioned species, the wettest two treatments provided enough water for Brachypodium distachyon seeds to germinate. Only the wettest treatment provided enough water for Sitanion hystrix seeds to germinate. The results show that different species can germinate in drier conditions than others. One advantage that weedy plants such as Bromus tectorum have is that they germinate early and can use available soil moisture before other species can become established. Other species, such as Sitanion hystrix, require a longer period of water availability to germinate and become established.
The next step is to take the soil moisture data and soil temperature data that we collected and input it into the hydrothermal time model. Then we can compare predicted germination from the hydrothermal time model with actual emergence. There are three possible outcomes of this part of the experiment: 1) The sensors help predict when a seed will germinate; 2) The sensors are not sensitive enough to help predict when a seed will germinate; 3) The sensors do not help predict when a seed will germinate. We observed that most seeds germinated between two and six days after being watered. The Colman cells and the gypsum blocks appear to be the only sensors that are sensitive enough to reflect how a seed might perceive soil moisture conditions. In the driest watering treatment, no seedlings emerged while in the second driest watering treatment some seedlings did emerge. For both watering treatments, however, the TDR sensors and the Watermark sensors showed that the soil was wet regardless of the treatment. The Colman cells and the gypsum blocks, on the other hand, showed that the driest treatment actually dried out sooner (day 3 instead of day 6 for the Colman cells and day 5 instead of day 8 for the gypsum blocks) than the second driest treatment.
If the sensors we used do not provide data that would allow scientists to predict germination using hydrothermal models, perhaps other approaches for modeling germination would be necessary. The next step may be to modify an energy budget model that would accurately estimate near-surface water potential in the vicinity of seeds.2
References and Acknowledgements
- Christensen, M., S. E. Meyer, and P. S. Allen. 1996. A hydrothermal time model of seed after-ripening in Bromus tectorum L. Seed Science Research 6:1-9.
- I would like to thank Bruce L. Webb from the BYU Department of Agronomy and Horticulture and Susan E. Meyer from the USDA Forest Service Shrub Lab for their assistance.