Category Archives: Experimental Design

Stomatal Peels (procedure)

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Nine populations were selected that represent three different degrees of aridity. Climate data for each collection site will be gathered using a program called Climate WNA. These data will be used to group each population into one of three groups according to an aridity index. This aridity index is calculated using the ratio of mean annual precipitation (P) and mean annual potential evapotranspiration (PET) and is currently used by the United Nations Environment Programme (2006) to categorize arid regions.

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Twenty-four replicates from each collection site were planted in a randomized block design and grown in a growth chamber set to 61 degrees F with diurnal lighting in twelve hour cycles. Plants will be grown under optimal conditions until leaves develop that are conducive to stomatal measurements (approx. 3 weeks).

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The central portion of the longest leaf from each plant will be coated in nail varnish on both the adaxial and abaxial surfaces. Once dry, the varnish will be peeled away from the grass blade and mounted onto microscope slides.

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Stomates will be counted manually using a compound microscope at 200X magnification. All stomates within a predefined area will be counted at three different locations along the length of the midrib and averaged.

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References:

United Nations Environment Programme. 2006. “The Desert Biome: A Global Perspective.” Global Deserts Outlook chapter 1. http://www.unep.org/geo/gdoutlook/016.asp.

Stomatal Density

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StomatalPeel

A potentially important seedling trait is stomatal density. Woodward (1987) found that stomatal density and distribution may affect gas exchange and associated relationships with environmental factors such as light, CO2, and water status.

Xu and Zhou (2008) found that stomatal density increased, but the number of stomata per-leaf decreased with water stress, and this change in stomatal density was correlated to changes in specific leaf area water use efficiency in another species of perennial grass.

Stomatal density may therefore be an important adaptive trait for bluebunch wheatgrass in the Great Basin. We aim to fill the knowledge gap surrounding seedling stomatal density in bluebunch wheatgrass to determine whether adaptation to climate exists for this trait.

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Hypothesis & objective:

We hypothesize that stomatal density is a driver of drought tolerance in young bluebunch wheatgrass plants and that the variability in this trait is caused by natural selection and local adaptation. Our objective is to determine the range of variability in stomatal density in populations along an aridity gradient and to tie this trait to selection through climate. Using an exploratory approach, we will measure stomatal densities from young plants (grown from seed-sources along an aridity gradient) and determine their relationship to climate in terms of aridity.

Expected results and interpretations:

We predict that there is a negative correlation between stomatal density and aridity. If this prediction is supported, then there is evidence that natural selection has reduced stomatal density in arid environments as compared to less arid environments. If this prediction is not supported, then we must conclude that stomatal density does not change in relation to aridity.

References:

Woodward, F. I. 1987. “Stomatal Numbers Are Sensitive to Increases in CO2 from Pre-Industrial Levels.” Nature 327 (6123): 617–18. doi:10.1038/327617a0.

Xu, Zhenzhu, and Guangsheng Zhou. 2008. “Responses of Leaf Stomatal Density to Water Status and Its Relationship with Photosynthesis in a Grass.” Journal of Experimental Botany 59 (12): 3317–25. doi:10.1093/jxb/ern185.

 

Root & Shoots (scanning)

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After monitoring all of the bluebunch wheatgrass seeds for germination and allowing them to grow for 10 days, it is time to digitally scan the roots and shoots for analysis.

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Each seedling was removed from the sand-filled conetainer so the roots could be cleaned and prepared for scanning. The shoot and roots were severed from the seed and scanned separately.IMG_20160125_123225075

To analyze root morphology, my mentor and collaborator Holly Prendeville will be inputting the root images into specialized root software called WinRhizo.

The shoot portion of the plant will be measured using ImageJ. For this portion of the experiment, I will measure the length and width of the longest leaf on each plant. These data will be used in conjunction with biomass data to calculate leaf shape, and root-to-shoot ratio for each seedling in the experiment.

After the roots and shoots were both scanned all of the plant parts were placed into envelopes for drying and eventual dry-biomass measurements.

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