Introduction & Background

Despite the growing number of scientists, federal and state agencies, private citizens, and non-profit organizations working to restore damaged ecosystems in the Great Basin, intact native plant communities continue to decline. The shift away from native-perennial to invasive annual-grass dominated systems has reduced biodiversity, increased wildfire severity and frequency, and has expedited desertification.

To combat this ecosystem overhaul, the most up-to-date and relevant science must be used to guide the restoration of Great Basin plant communities. Improving native plant establishment rates in the restoration setting is one of the biggest challenges faced by land managers. Bluebunch wheatgrass (Pseudoroegneria spicata) is a commonly used native species in restoration but seedling establishment is modest. The goal of our study is to fill knowledge gaps surrounding seedling adaptation to  soils.

The information from a study by St. Clair et al. (2013) was used to delineate seed transfer zones for bluebunch wheatgrass. A seed zone is a geographic area across which native seed can be collected and planted without risking maladaptation. To delineate seed zones, seed is collected from wild populations across the geographic range of a species. Plants are grown to adulthood in several common garden locations that span this geographic range. Climatic data are matched with phenotypes. Each phenotype is defined by observed adult plant traits measured in each common garden (e.g. leaf width, leaf length, pubescence, crown width). Phenotype and climate data are mapped together using a spatial model (Westfall 1992). The final step in creating a seed zone is to empirically verify whether using delineated seed zone maps to guide plant material selection actually enhances plant fitness.

An important knowledge gap I have identified is the role of soils in the adaptation of bluebunch wheatgrass. There exists only a moderate correlation between population-level phenotypic trait variability and seed-source climates, even though traits associated with size, phenology, and leaf morphology varied considerably among the populations sampled (St. Clair et al 2013). Adaptive phenotypic traits are visible expressions of genetic variation caused by environmental factors (i.e. leaf length, flowering phenology, pubescence etc.). This moderate correlation between phenotypic traits and climate may suggest that other factors contribute significantly to local adaptation in bluebunch wheatgrass.

Soils are natural bodies that consist of living organisms, organic matter, minerals, air, water, are comprised of horizons, and have the ability to support plant life (NRCS 2016). The complex array of factors inherent in soils makes generalizing about them challenging. Many studies link plant survival to soil texture class (i.e. percentage sand, silt, and clay) and soil-water dynamics (Letey 1958, Ullah and Hulbert 1969). Others such as Jensen et al. (1990) used soil traits and discriminant analysis to predict sagebrush-dominated plant community types using soil traits such as soil depth, subsoil clay content, total water holding capacity, and A-horizon thickness. Still other studies correlate seedling emergence and germination to aggregate size and bulk density (Nasr and Selles 1995). I aim to determine whether observed phenotypic traits of bluebunch wheatgrass vary with soil traits such as soil texture, soil depth, pH, aggregate structure and water holding capacity.

My study will utilize existing phenotypic trait data and soils maps to explore links between soil order, soil series, plant traits, seed zones, and ecoregions. I predict that phenotypic trait divergence will be correlated to soil gradients that exist across seed zones. Information obtained from this work will either support current seed zones for bluebunch wheatgrass or create better seed zones, and help land managers to achieve higher success rates in restoration.

Description of Datasets

1. The seed zones for bluebunch wheatgrass have been delineated into shapefiles. Each polygon represents a seed zone. The boundaries of these polygons were delineated using ArcMap spatial analysis of climate (precipitation / temperature), elevation, and plant traits (leaf length, leaf width, crown width etc.). This dataset / map was developed in 2013 and is based on two years of data collection at common-garden sites in the Great Basin.
2. The Phenotypic trait dataset contains measurements of individual plants at sixteen different common gardens spread throughout the study area. Each seed zone is represented by two common gardens, and each common garden contains 4-5 populations from each seed zone. Measurements such as leaf length, width, and reproduction stage scores were gathered from each individual plant in all sixteen gardens. Each population of bluebunch wheatgrass growing in the common gardens is associated with a collection site (UTM / elevation / approximate area in acres). Each common garden also has an associated (UTM, elevation / and dimensions in meters).

1. “The gSSURGO (soils) database is derived from the official Soil Survey Geographic (SSURGO) database. SSURGO generally has the most detailed level of soil geographic data developed by the National Cooperative Soil Survey (NCSS) in accordance with NCSS mapping standards. The tabular data represent the soil attributes and are derived from properties and characteristics stored in the National Soil Information System (NASIS). The gSSURGO data were prepared by merging the traditional vector-based SSURGO digital map data and tabular data into statewide extents, adding a statewide gridded map layer derived from the vector layer, and adding a new value-added look up table (valu) containing “ready to map” attributes. The gridded map layer is in an ArcGIS file geodatabase in raster format. The raster and vector map data have a statewide extent. The raster map data have a 10-meter cell size that approximates the vector polygons in an Albers Equal Area projection. Each cell (and polygon) is linked to a map unit identifier called the map unit key. A unique map unit key is used to link the raster cells and polygons to attribute tables” (Soil survey staff 2015).

Hypotheses

I hypothesize that some phenotypic trait variability in bluebunch wheatgrass can be explained by adaptation to certain soil traits. My objective is to determine if phenotypic trait variability in bluebunch wheatgrass corresponds to soil order, soil series, or other distinct soil trait groupings, and if the existing seed zones for bluebunch wheatgrass and/or ecoregion account for the spatial distribution of these soil trait groups.

Approaches

1. Soil maps containing soil order polygons will be compared to existing bluebunch wheatgrass seed zone polygons to determine the extent to which soil order is contained within existing seed zones.
2. Plant trait data from all 16 common gardens will be compared to the soil traits (i.e. order, series, texture class or other) to look for correlations between source population soils and genetic expressions in bluebunch wheatgrass.
3. Soil maps containing soil series polygons will be compared to existing bluebunch wheatgrass seed zone polygons.
4. Available soil maps containing soil order and series will be compiled for our study area. Soil series and pedon descriptions will be used to assemble a set of soil traits that are relevant to plant growth and that exist in the study area. These traits will include, depth to bedrock, A and B horizon texture classes, percent gravel, pH, aggregate structure, and depth to impermeable layers. These data will be organized into a database for statistical analysis in PC-Ord (a multivariate statistical analysis software). Phenotypic trait data (such as leaf length, basal width, and seed production) will be gathered from a previous study involving sixty bluebunch wheatgrass populations grown in sixteen common gardens spread across the study area (figure 1).

Expected Outcomes

I expect to find that bluebunch wheatgrass phenotypes are correlated with soil order and may be correlated with other soil traits such as texture and aggregate structure.

Significance

A relationship between soil and bluebunch wheatgrass phenotypic expression suggests that soils information should factor into the seed-zone delineation process.

Level of preparation

I have moderate experience with ArcMap but have never used the program to do spatial analysis. Similarly, I have two terms of introductory statistics that used R but have never explored multivariate datasets.

References:

Predeville, Holly. 2016. Depiction of data gathered in a study by St. Clair et al. 2013 in google maps. https://www.google.com/maps/d/edit?mid=zxFzk9yulKc0.klEzA-cxckLY

Jensen, M. E., G. H. Simonson, and M. Dosskey. 1990. “Correlation between Soils and Sagebrush-Dominated Plant Communities of Northeastern Nevada.” Soil Science Society of America Journal 54 (3): 902. doi:10.2136/sssaj1990.03615995005400030049x.

Letey, J. 1958. “Relationship between Soil Physical Properties and Crop Production.” In Advances in Soil Science, edited by B. A. Stewart, 277–94. Advances in Soil Science 1. Springer New York. http://link.springer.com.ezproxy.proxy.library.oregonstate.edu/chapter/10.1007/978-1- 4612-5046-3_8.

Nasr, H. M., and F. Selles. 1995. “Seedling Emergence as Influenced by Aggregate Size, Bulk Density, and Penetration Resistance of the Seedbed.” Soil and Tillage Research 34 (1): 61–76. doi:10.1016/0167-1987(94)00451- J.

NRCS 2016. What Is Soil? | NRCS Soils. 2016. Accessed March 3. http://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/edu/?cid=nrcs142p2_054280.

Soil Survey Staff. Gridded Soil Survey Geographic (gSSURGO) Database for the Conterminous United States. United States Department of Agriculture, Natural Resources Conservation Service. Available online at https://gdg.sc.egov.usda.gov/. November 16, 2015 (FY2016 official release).

St. Clair Bradley John, Francis F. Kilkenny, Richard C. Johnson, Nancy L. Shaw, and George Weaver. 2013. “Genetic Variation in Adaptive Traits and Seed Transfer Zones for Pseudoroegneria Spicata (bluebunch Wheatgrass) in the Northwestern United States.” Evolutionary Applications 6 (6): 933–48. doi:10.1111/eva.12077.

Ullah Alizai Hamid, and Lloyd Hulbert. 1969. “Effects of soil texture on evaporative loss and available water”, Soil Science.

Westfall, R. D. 1992. “Developing Seed Transfer Zones.” In Handbook of Quantitative Forest Genetics, edited by Lauren Fins, Sharon T. Friedman, and Janet V. Brotschol, 313–98. Forestry Sciences 39. Springer Netherlands. http://link.springer.com.ezproxy.proxy.library.oregonstate.edu/chapter/10.1007/978-94-015-7987-2_9.