• Assess the quantity, distribution, and condition of unplanted, high quality grassland communities in an 8-county area of Central Virginia
• Investigate and quantify relationships between geologic soil characteristics (chemical and physical) and local variations in plant assemblages
• Determine degree of indicator assemblage fidelity as it relates to physiographic characteristics
• Investigate relationships between exotic species prevalence and three factors: geologic soil class, native species richness, and native species diversity
• Identify threats and generate recommendations for the expansion of natural grasslands focused around these nodes of resilience, and the conservation of existing resources to help prevent further habitat and species loss.

We propose a 1 year study that includes:

1. Preliminary inventory of hypothesized high quality grassland remnants within an 8 county study area in Central Virginia, to include the counties of Madison, Greene, Albemarle, Orange, Louisa, Fluvanna, Buckingham, and Nelson.

2. Quantitative assessments of select examples of high quality grasslands from the preliminary inventory sites, to include the characterization of physiography, geology, soil chemical and physical attributes, vegetative cover, species richness, species diversity, and exotic species impact. Sample # will include a minimum of 35 plots (100 meter2)

3. Summary of the condition of each site that receives a sample plot

4. Report of findings including a short review of the historic record for supportive evidence of grasslands in the region (with matching funding, already secured)

5. Partnerships with public and private land owners and managers to gain access to sites for intensive study (already secured)

6. Matching funding and volunteer effort to increase the data set for the study: up to $14,750

• James River Association: $500 (secured 1/10/2021)
• Private Donors: $5,000 (secured 1/21/2021)
• CUH Staff Time and Materials Donation: $7,250 (committed, 2021)

COVID-19 Safety Protocols

• All survey participants must drive separately to survey sites. Because of the lack of the carpool option, all participants will be reimbursed for either drive time or on a per mile basis.
• Survey participants shall not share equipment, and will be responsible for being fully equipped for survey on each survey day. When equipment must be shared, hands and equipment must be sanitized with an ethanol based solution (minimum 70%)
• Survey personnel are not permitted to participate if they
• have a fever or respiratory symptoms or have been in contact with anyone these symptoms in the past 14 days;
• have tested positive for COVID-19 and have not yet been cleared to return to work by an authorized public health official; or
• have within the last 14 days returned from an area with reported community spread of COVID-19.
• Once at work, all participants shall remain a minimum of 6 feet apart
• If participants are within 50 feet of another participant, a mask must be worn at all times

Preliminary Inventory of potential study sites, Strategy

Staff will continue to conduct a cursory inventory of potential high quality survey sites using a combined method of field reconnaissance and analysis of aerial photography, geologic maps, historic maps, and LIDAR. The primary means of identifying high quality grassland sites involves driving hundreds of miles of backroad in the study area, often in an opportunistic manner. By that I mean any high quality grasslands discovered during outings, expeditions, or site visits to locations in the region, and found mostly by chance along roadsides and in powerline rights-of-way. We have a team of 5 individuals that have practiced and studied for about 5 years to hone their expertise around identifying mixes of indicator grassland species on the drive-by. When we see something, and if we have time, each individual typically gets out and does at least swift 2-3 minute walk through to affirm the indicator species, and assess for exotic species impact. We have identified hundreds of so-called “remnant” high quality grasslands in this way.

The other method is a bit more strategic, and the predictive model involves correlating grassland landcover in aerial imagery with geologic substrates that have tendencies to support higher-quality grasslands. When that combination is crossed with historic evidence, including place names, 19th century rights-of-way, old landscapes such as those found at battlefields, or areas that weren’t intensively plowed, the probability increases. We target those regions with specific volunteer-based recon efforts. During this project we will ramp up our recon efforts to maximize both the quantity and quality of the sample sites we conduct in 2021, and to ensure we accomplish sampling that is representative of the region as a whole, both geographically, and geologically.

Beginning in May 2021 we will conduct weekly expeditions to ground-truth hypothetical grassland sites in order to build an inventory from which to choose representative sample sites for intensive study described here-in.

Sample site selection strategy

With a growing inventory of high quality grassland sites we will have a large set to sample from in 2021. Choosing sites for our vegetative plot studies will depend on a number of factors, including accessibility, condition, and location.

Accessibility varies from one region and county to another, and depends greatly on whether or not the grassland remnant is on private land, public land, or in the public right-of-way along state roads. We have established great relationships with property owners and government agencies (i.e., parks, VDOT, etc.), and so we do not foresee access being an issue. With the exception of 2 or 3 study sites, all will be a short walking distance from a primary road.

The condition of each of our potential study sites will inform prioritization for this study. Many sites are impacted during the growing season by land managers, and when that impact makes them impossible to assess quantitatively we will forego an assessment. We are seeing a wide spectrum of grassland “health”, with diversity and exotic species impact varying from site to site even in what are perceived to be old-growth, high quality sites. All grasslands that will be studied during this project in 2021 will focus on those that are hypothesized to be high quality. At many of these sites rare species have already been confirmed. Another force that creates variety in condition is substrate. We see grasslands across the full spectrum of geology, from ultramafic to acidic, and upland to wetland. Despite some grasslands being more diverse than others naturally, we intend to sample across the spectrum to gain a better understanding of variety in the region – In other words, hypothesized diversity will not be the only deciding factor in choosing study sites. Some sites have rare or uncommon species, and those will be given priority for study when accessible.

Location is a factor in selecting study sites. Preliminary inventories of grassland remnants will produce varied level of density on the regional scale, depending historic land-use and physiography. For example, we know that the density of high quality grasslands is elevated in eastern Fluvanna and Buckingham counties when compared to Nelson and Albemarle counties. We intend to sample in a representative manner, while including even regions that have very few surviving remnant grasslands.

Additional Plot Data

While we do have specific targets for the total number of sites we will sample, we plan to augment the sample size in two ways. First, we will conduct an undetermined number of volunteer-based sample plots. We have done this in year’s past, simply because we truly love doing this type of work. Secondly, we will add data from all our past sample plots, as well as any new ones that are accomplished during other funded or contracted work involving Piedmont grasslands in 2021. At the end of the study we should have an enormous data set that we can look at and learn from, and the totality of the work will speak volumes about the quantity, quality, and distribution of grasslands in the 8 county study area.

Data set from grasslands in all states of health, from pastures and lawns, to high quality savannas.

Data Collection Protocols

Vegetative Sample Plots

Center for Urban Habitats (CUH) samples natural plant communities using the Relevé Method, following standard procedures employed by the Virginia Department of Conservation and Recreation’s (DCR) Natural Heritage Program (VANHP). The Relevé sample method is a multidimensional method of quantifying natural plant communities. This procedure was developed by plant ecologist, Josias BraunBlanquet, in the 20th century and it continues to this day to be one of the most detailed and comprehensive approaches recognized in the field of ecology. The Relevé method is widely employed by Natural Heritage programs throughout the United States, as it results in an exhaustive description of a given unique ecological community. It relies upon thorough multi-variate data collection within a sample plot of sufficient size to accurately represent the community being sampled (in the subject area of this proposal, the grassland types, that size is 100 square meters). During a Relevé survey, a sample plot is established within a unique ecological plant community (natural and/or anthropogenic). The Relevé approach focuses on quantifying vegetative content and structure as well as a number of physical factors such as geology, topography, soil drainage, and soil chemistry. The approach operates under the premise that all layers of a natural plant community, from the highest reaches of the canopy to below the ground surface, contribute to influencing the plant communities’ relationships to the land and to other communities. Certain species of flora have unique growing requirements, and thus they serve as “indicator species” that allow us to hypothesize about geologic conditions, land-use history, and plant community diagnosis and variation. We rely heavily on indicator species for the initial determination of possible “high quality” grassland. When several of these indicator species occur together, the probability and classification confidence level increases, for both the community type, and the quality or ecological health. For this reason, indicator species are important for the classification and naming of all natural plant communities, and for determining whether further investigation is warranted to support education or conservation. They are also among the primary influencing factors when determining where and how many plots should be executed on a given tract of land.

Field technician, Olivia Lewis, proceeds along a transect line in a grassland sample plot in Albemarle County, VA.

Plot Size

All assessments will be treated with 100 square meter sample plots with a standard 5m x 20m configuration when the community size and shape allow, and other shape configurations when necessary to remain entirely within the community being sampled and at least 1 meter away from the edges of the community being sampled. We are choosing this rectilinear configuration because the vast majority of the grasslands that will be the subject of this study will be in long, narrow corridors. There may be some study sites that will command other dimensions, and we will address those on a case-by-case basis. But in all situations, the total square footage will remain 100m2, and the maximum short side will not exceed 5 meters.

Diagram of sample plot size, proportion, and target locations for soil samples and inventory transect path.

Semi-permanent Datum

In order to facilitate long term monitoring and resampling in the future, all plots will be marked (when permitted) in their northwest corner with an 8” steel spike driven into the ground and tagged with an aluminum plot label to convey date, project name, and plot number. Quantitative vegetation sampling will be conducted during the growing season between April 30, 2021 and October 30, 2021.

Physiographic Data

Within each sample plot specific physiographic data will be recorded on a standardized Field Form. This form captures general metadata and physiographic characteristics, including plot number, plot name, project name, date, county, state, recorder and surveyor names, ecoregion (Omernik, Level IV), plot elevation range, estimated community elevation range, latitude and longitude for the plot location, plot size and dimensions, plot bearing, estimated natural plant community size, plot location description, and geologic formation. General sketches, portraying a plan view and section, will be executed in the field to provide additional contextual information not captured in the form. Detailed plot-based physiographic data will be collected, including rock and mineral types present, ground surface cover materials and abundance, slope, angle of incline, aspect, landform, topographic position, evidence of disturbance, soil drainage class, soil moisture regime, soil sample notes, tree core notes (if applicable), and a field narrative covering all important aspects of the site and observations.

Environmental Data

A standard set of environmental data will be measured or estimated at each plot. The following is an overview of the data classes:

Land slope, angle of incline, and aspect will be measured to the nearest percent and degree.

Slope Classes
0-3% (level or nearly so)
3-8% (gentle/undulating)
8-16% (sloping/rolling)
16-30% (moderate/hilly)
30-65% (steep)
65-75% (very steep)
75+% (extremely steep)

Aspect Classes
north (337.5°-22.5°)
northeast (22.5°-67.5°)
East (67.5°-112.5°)
southeast (112.5°-157.5°)
south (157.5°-202.5°)
southwest (202.5°-247.5°)
west (247.5°-292.5°)
northwest (292.5°-337.5°)

Elevation will be determined to the nearest 10 feet using a combination of GIS data and high resolution aerial imagery.

Ground Cover will be estimated as a percentage of the total plot surface area, with amounts being adjusted such that the total equals 100%.

SURFACE COVER (Excluding flora, total = 100%) Bedrock_______% Organic matter_______% Boulders _______ % Cobbles/Gravel_______% Decaying Wood_______ % Mineral Soil/Sand_______% Water_______% Other_______%

Landform will be documented as being associated with one or more of the following:

Landform
□ ridge / interfluve
□ saddle / gap
□ slope bench/ ledge / step
□ side slope
□ fan piedmont
□ cove
□ ravine
□ cliff / escarpment / face
□ seep / swale / non- alluvial bottom
□ bedrock outcrop
□ alluvial flat / alluvial terrace / floodplain
□ boulderfield / talus / debris slide
□ floodplain levee
□ hill / knob / monadnock
□ channel shelf / stream margin / bar
□ rolling / dissected upland
□ OTHER:

Topographic position will be noted for each sample plot, and typically includes one of the following:

Topographic Position
□ undulating / flat plain
□ crest / interfluve
□ upper slope
□ middle slope
□ lower slope
□ toe slope
□ plain/level/bottom
□ basin/depression

Soil drainage class and soil moisture regime will be assessed using a fixed range of standard options:

SOIL DRAINAGE CLASS
□ rapidly drained
□ well drained
□ moderately well drained
□ somewhat poorly drained
□ poorly drained
□ very poorly drained

SOIL MOISTURE REGIME
□ Xeric
□ Dry-mesic
□ Mesic
□ Wet-mesic
□ Sub-hydric
□ Hydric

Bedrock geology will be hypothesized to the greatest precision possible and recorded by using a locally segregated geological map when available, and general USGS geological map at other times. Field techs will inspect freshly broken rock and mineral samples that are available at the ground surface in order to detect site-level variation that may differ from the local trend (a frequent occurrence). Rock and mineral identifications are done in the field and rely heavily on prior knowledge of the geologic substrate in the region. Identifications will sometimes require confirmation using multivariate objective analysis with lab samples (macroscopic views and mineral type/abundance key).

Soil Data

Soil samples are collected from each sample plot. Samples are gathered from a minimum of five locations within each survey plot to ensure the samples represent the soil variety and any anomalies that are present. These small sub-samples were combined into a single 3 cup sample. Each soil sample is taken by first removing the leaf litter and any rocks or organic material that lay on the surface. With natural soil exposed, the sample is taken using a trowel to a maximum depth of 5 inches, with care to take equal amounts from the upper and lower portions of the soil column. This depth is standard when assessing soil characteristics that impact natural vegetation. All samples are packed, sealed, and labeled in transparent plastic bags in the field, and transported to our lab where they are dried for two days. They are then packaged and mailed to Brookside Laboratories, Inc., in New Bremen, Ohio for processing. We use this laboratory for all our soil analyses because Virginia’s primary entity for tracking species and natural communities (Virginia DCR-DNH) also uses that laboratory. This allows our data to be directly comparable.

At the laboratory soil samples are oven-dried, sieved, and analyzed for pH, phosphorus, soluble sulfur, exchangeable cations (calcium, magnesium, potassium, and sodium in parts-per-million), extractable micronutrients (boron, iron, manganese, copper, zinc, aluminum, in parts-per-million), total exchange capacity, total base saturation, percent organic matter, and percentages of clay, sand, and silt. Chemical extractions are carried out using the Mehlich III method (Mehlich, A. 1953). Percent organic matter is determined by loss-on-ignition. Physical analysis are determined using the Bouyoucos hydrometer method (Bouyoucos. 1936).

The test results include numbers for 25 chemical and physical characteristic data points. These combine to create powerful objective information that is independent of the vegetative and physiographic data collected in the field, and the addition of the soil data is invaluable for supporting the natural community classification process and an understanding of local variability in grassland assemblages.

Vegetative Data

We utilize a separate Vegetative Stratum Form in all study areas. One or more of these forms is used per vertical layer of the natural community. Six potential layers (aligned with the DCR-VANHP data collection protocols) are assessed for their species variety, frequency, relative frequency, vegetative cover, and minimum and maximum d.b.h. (diameter at breast height: 4.5’ above ground). Other information captured on this form includes whether the species is exotic-invasive or native, whether or not the observation was inside or outside the sample plot, and whether or not the identification of the species is in question.

Plots are placed in stands of vegetation that are optimally representative of the community type being sampled, and far enough away from interfaces with other community types and/or changes in stand succession. All vascular plant species present are recorded and each species’ total cover, defined as the percentage of the ground covered by each species’ collective vertical projection, is estimated across the entire plot. Vegetative cover is assigned to each species using a nine-point scale:

1 = trace (< 0.1%), 2 = a few (<1%), 3 = 1-2%, 4 = 2-5%, 5 = 5-10%, 6 = 10-25%, 7 = 25-50%, 8 = 50-75%, 9 = 75-100%

In addition to documenting the presence of species and the abundance of each within the plot, the structure of the flora is quantified by measuring the size of trees, shrubs, and vines, and determining how they are distributed in three dimensions. The diameter at breast height (~4.5 feet) of each woody species above 20” tall will be measured within each layer of the canopy. Stems > 1inch are measured to the nearest tenth of an inch (.1). In order to assign a tree to a specific elevation stratum zone, we determine the height of that tree using a digital clinometer and the following double-tangent formula:

(Tan ∠ to tree top x distance to tree) + (Tan ∠ to tree base x distance to tree) = Tree Height

A clinometer is not used when a tree falls clearly within an already determined, and well-referenced, strata zone, but is instead employed to define the upper and lower limits of all strata listed below, and to resolve trees that are occurring closest to the interface of one of the six layers. Each species will be defined within one or more of the following layers:

□ Herb layer (H): < 20 inches
□ Shrub layer (S): 20 inches to 20 feet
□ Tree layer 1 (T1): 20 feet to 33 feet
□ Tree layer 2 (T2): 33 feet to 66 feet
□ Tree layer 3 (T3): 66 feet to 115 feet
□ Tree layer 4 (T4): > 115 feet

Definitions

The data collected will allow us to quantify three critical characteristics of natural community health: Species Richness, Diversity, and Exotic Species Importance.

Richness: “Richness” refers to the total number of species within a given area. Many natural plant communities have naturally low species richness (such as the forested heath habitats in the study area). In the Piedmont, forests tend to have fewer plant species than open-space grassland types such as prairies, savannas, and woodlands. There are a great number of reasons for this, but one worth noting here is that pre-Columbian native landscapes in the region were blanketed by as much grassland as forest. Enormous contiguous grasslands had thousands of years of robust, full sun, species development. One may surmise that the competition for space, nutrients, water, and light there-in resulted in enormous division of species within each Genera (in fact, this bears fruit in Solidago, Dichanthelium, Desmodium and many others). Time compounds this affect, and each taxa of plant fills every little niche of the grassland landscape, both spatially and temporally, with a well-suited species. Species richness is a very important data point for comparing natural communities across the land. In combination with abundance and seasonal change, one may use richness to begin to understand biological health and the potential of a site, regardless of the condition it is in.

Diversity: “Diversity” is calculated by combining richness and abundance (% cover for each species), and is a reflection of variety in species, dominance, and evenness. The formula we use (see below) produces an index number that may be used to compare across different plant community types. This number has proven critical for tracking change during restoration projects, but also for comparing relative health in natural communities across the region. The “Diversity” number ranges from 0-5. The closer to 5 the number is, the more diverse the community is. Some communities have naturally low diversity. Tracking Diversity through time by repeating quantitative data collection at sample plot locations has tremendous benefit, as it sheds light on gradual changes that are happening that may go un-noticed in a qualitative view of things.

There are several popular ways to calculate Diversity. We have adopted a common calculation method in field ecology, as it has proven to have benefit for comparing restoration sites and natural communities of similar types and sizes across local landscapes:

Shannon-Weiner Diversity Index:

Exotic Species Importance: We have adopted what is referred to as the “Exotic Species Importance Value (IV)”, as devised by Gary Fleming at the Virginia Department of Conservation and Recreation’s Natural Heritage Program. This index number has proven valuable in creating goals, targets, and measures in restoration projects. It is a quantitative way of measuring and tracking non-native plant species impact across time. This formula combines non-native species richness (# of species) and abundance (% cover) and expresses each as a relative percentage of the total population (including native species). The final number is expressed as a value on a scale of 0-1, with “0” meaning a complete absence of non-native species, and “1” meaning 100% non-native species, and 100% non-native ground cover.

Exotic Species Importance Value Index (IV) = Relative Exotic Richness + Relative Exotic Abundance / 2

The Project Manager, Devin Floyd (Executive Director, Center for Urban Habitats) will be responsible for overseeing and coordinating all aspects of the project, including hiring, accounting, scheduling, survey implementation, lab work, research, and reporting. The project manager will partake in field and lab portions of the project. All staff will report to the project manager during this 1 year survey effort.

The planning team will consist of all project staff, and together they will coordinate survey and lab workdays, and review safety protocols, and brush up on survey methods periodically. During the broader “Inventory” phase of the project where the objective is to locate potential high quality native grasslands (using indicator species), specific CUH staff will be responsible for locating and reporting to the GIS staff member, Matt Smith. The lead staff for identifying those sites are Devin Floyd, Drew Chaney, and Ezra Staengl. On occasions other CUH staff may report rare species in grasslands, and/or intact natural grassland communities.

The majority of data entry and related research will be accomplished by Drew Chaney (CUH Field Botanist), Ezra Staengl (CUH Field Botanist), David Bellangue (Senior Intern, Virginia Tech), Evie Sackett (Intern, Yale University), Jacob Obernesser (Intern, Virginia Tech), and Devin Floyd (CUH, Project Director / Co-P.I.)

On the day of vegetative plot surveys, the survey team (a minimum of two individuals) will commute to the survey site, convene, organize, and hike (if necessary) to the 100 square meter sample plot location. The team will work together to locate the optimum representative sample location, lay out 100m2 sample plots, and prepare data collections sheets.

Each survey member will be encouraged to take photographs throughout the day, with the understanding that any image captured will be curated in the CUH database and may be shared in a public venue (including VNPS).

Once the sample plot is established, the project manager will assign roles related to specific data collection activities in the vegetative plot. Interns and staff will be assigned various duties related to collecting all vegetative data as described in the Methodology section of this proposal.

Once the data is collected, the survey team convenes to organize the field forms and data sheets, and the project manager assures completion and quality, and fields questions and concerns. The data sheets are compiled and stored for data entry on a lab workday.

All field techs present on the survey days are required to also partake in the lab workday that follows. During lab days, all techs (including interns and CUH staff) are responsible for researching the remaining unidentified species (represented in samples and/or photographs) and labeling/uploading personal images taken during work hours (images are uploaded to the project folder). CUH lab techs, Drew and Ezra, are responsible for organizing, curating, and processing all plant samples that were collected on the survey day. New county records are pressed and processed following rigorous herbaria protocols and the vouchers are submitted to VA state herbaria and/or the DCR for consideration.

Data entry will be accomplished by CUH staff (Drew Chaney, Ezra Staengl, Devin Floyd) as well as any intern Evie, Jacob, and David.

Final synthesis will be a group effort, and the final review and reporting will be handled by the project manager, Devin Floyd.

Staff will work closely with DCR’s Natural Heritage Division during this project when needed, for natural community review, plant identifications, methodologies for field data and analysis, and sample and data curation. The point of contact will be Gary Fleming.

Data will be reviewed, assessed, and analyzed by the project manager, in coordination with Dr. J. Leighton Reid at Virginia Tech and PhD candidate analyst, Jordan Coscia with the VTECH Department of Plant and Environmental Sciences. The results of our assessment will be included in a regional study being conducted by Jordan related to natural grasslands of the Piedmont.

CUH staff will be responsible for advancing our mission throughout the life of the project, particularly as it relates to education. To accomplish this staff will generate blog posts, photographs, and other means of communication throughout the project.

2021 May. Hiring Window
2021 June. Planning/Scheduling, Materials Procurement
2021 July 1 – December 1. Native Grassland Inventory Window:
2021 September 1. Inventory window half-way point review of inventory progress and consideration of new priority sites for late season study
2021 July 15 – October 15. Native Grassland Sample Plot Window
2021 September 1. Half-way point for vegetative plots, all staff progress review, budget review, and feedback on new priority sites identified during ongoing regional inventory.
2021 July 1 – December 1. Laboratory activity to follow each inventory and survey effort.
2021 December – 2022 March. Review and research window.
2022 April – June 2022 Synthesis and report period
2022 June. Survey report due one year after grant award.
2022 August. Presentation of findings to VNPS, via oral presentation and/or a poster.
2022 December 1. Report for Publication due to VNPS 6 months following project completion.

The data collected during the survey will be analyzed to better understand the probability of each sight being an intact, pre-settlement, remnant grassland. Many variables will be considered, including heliophyte abundance, whether soils have been plowed, C-value (conservatism), cover-weighted Floristic Quality Index (FQI), species richness, and exotic species impact information. These vegetative data variables will be compared to dozens of environmental, physiographic, and soil variables within each plot across the study area to identify correlation trends between the variables. The data set produced during the survey project window will be compared to data collected in prior years at other locations in the Piedmont region to provide some context for quality, character, and regional trends in species composition and hypothesized age. The concept of “self-assembly” is important for this assessment, as some groupings of species require centuries of sunny conditions and stable natural disturbance regimes to self-assemble. We will assess and report closely on relationships between rare species and geo-physiographic patterns, as well as trends observed between the exotic species data and the species richness and diversity data. Ultimately we hope to devise an effective method for determining how old a remnant grassland is.

We hope to identify threats to grasslands that are related to modern human activity, but also to historic land use, soil chemical and physical variables, and relative abundance of exotic invasive species. With all of these relationships considered, we will report the results (including rare and unusual finds) to the DCR, the VNPS, and partner organizations.

All project staff will be given a project evaluation form. This form will include a 1-10 ranking scale for broad categories of the project, including general expectations, safety, quality, efficacy in project management, professionalism, educational quality, methodology, efficacy and relevance, work value vs. payment, staff behavior, work environment, support, and equity and inclusion.

1. Natural Community data for all sample plots
2. Master list of species for each community type
3. Collection of Photographs produced during the Survey Effort. Images will be captured, of species, communities, and staff working shots, throughout the project. Images are curated in CUH’s database, as well as in a sharable on-line folder (Google Drive). Each image is labeled with species, date, and photographer name.
4. List of Voucher Specimens. New county occurrences of plant species will be sampled for submission and consideration by the VBA, DCR, and a state herbarium. We will maintain an inventory of those samples and supply that list to the VNPS at the end of the project.
5. Map of all Grassland Inventory Sites and Sample Plot Locations in the study region.
6. Final Report. The report will review the goals and objectives of the study and describe the methodology, findings, and conclusions. The primary issue being addressed by the study, and indeed the report, is to better understand the quality, quantity, and distribution of native grasslands in the Central Virginia Piedmont Region. The report will quantify both quality and quantity by synthesizing a great number of data classes, include those in the soil data, physiographic and environmental data, and vegetative data. We will review any trends or correlations that emerge. During this study we hypothesize that we will find

• Trends that suggest local and regional sub-variants of prairies and savannas as well as moderately strong correlation between dominant native species, bedrock type, and residual mineral soil.
• Direct relationships between degree of site disturbance and/or proximity to modern human disturbance, and condition as quantified with diversity, richness, and exotic species importance data.
• Associations between the degree of invasion by exotic species and prevalence of liberal native species (weedy, early pioneer generalists) vs. conservative assemblages (fire adapted, less common, need older stable soils) of native grassland species
• Higher quantities of high quality (diverse with few exotic species) grasslands over landscapes with soils that are naturally nutrient-poor and/or shallow, rocky, well-drained, and dry.
• Lower species richness, yet lower exotic species abundance, in communities over natural residual soils that have lower base saturation and acidic pH
• Higher native species richness in basic/nutrient rich settings, and especially those with shallow rocky soils and fewest exotic invasive species.
• More rare/uncommon species over mafic or ultramafic bedrock substrates, and especially those with shallow, rocky soils.
• Preponderance of grassland remnants in the eastern half of the study area (east of the southwest mountains line) due to the reduction in local physiographic relief and an increase in soils that are not productive for agriculture.
• Fewer occurrences of well-preserved grasslands in the intensive agricultural areas of the western half of the study area.
• Variety of grassland types including acidic, mid-spectrum, and basic variants of barren, prairie, savanna, and woodland, as well as wet and dry variants of prairie and savanna.
• High species fidelity for indicator species when comparing grasslands from different geologies

Grantor: Virginia Native Plant Society

Study Sites Access and Maintenance, Public: Albemarle County Parks and Recreation, Virginia Department of Transportation, Albemarle County Service Authority

Study Sites Access and Maintenance, Private: More than 20 private property owners in the study region

Analysis, Publishing, Technical Support: School of Plant and Environmental Sciences, Virginia Tech

Flora and Natural Communities Advisor: Gary Fleming, Plant Ecologist, Department of Conservation and Recreation

Matching Donors: James River Association, Polis-Schutz Family Fund, J. Hackworth Fund

This is the beginning of a long term research initiative of Center for Urban Habitats. While the near-term scope is focused on an initial 8-county area, the long-term strategy is to study the broader Piedmont region, from the Fall Line to the Blue Ridge, and from the Hudson River to Alabama. We’ve already begun significant inventory efforts, but this funding will allow us to begin understanding quantity, quality, distribution, and the risks that grasslands face in the Central Virginia Piedmont through quantitative assessments.

We have been working on the project since the beginning of 2020, and we plan to sustain the research indefinitely as part of our ongoing core operations. The growing list of partners and institutions engaged in similar activity help assure the validity and longevity of the study, and indeed the broader grasslands conservation movement. We believe that grasslands are a critical part of the natural and cultural heritage of the Piedmont region, and many of the endemic varieties may be considered our crown jewel ecosystems. To support the ongoing effort we will apply for grants from a variety of organizations (including VNPS), but also continue to build a robust donor base to support the project. CUH staff will also continue to dedicate a great deal of volunteer time to the project annually. The combination of grants, donors, and volunteer commitment ensure the longevity and impact. We consider this 2021 VNPS grant to be a critical catalyst at the very beginning of an initiative that will grow to be a research and education program that will have a widespread impact on environmental education and conservation.

Helianthus dominated prairie remnant in the south end of our 2021 study area.