The Carolina Vegetation Survey

Robert K. PeetUniv. North Carolina at Chapel

Hill

In collaboration with

Thomas Wentworth (NCSU), Alan Weakley (NCBG), Mike Schafale (NC Heritage Program)

Carolina Vegetation Carolina Vegetation SurveySurvey

Multi-institutional collaborative study to Multi-institutional collaborative study to document and understand the natural document and understand the natural vegetation of the Carolinas.vegetation of the Carolinas.

High-quality, High-quality, quantitative quantitative records of records of natural natural vegetationvegetation

Why CVS?

• Description, classification, and analysis of Description, classification, and analysis of the natural vegetation of the Carolinasthe natural vegetation of the Carolinas

• Determine attributes of individual taxaDetermine attributes of individual taxa

• InventoryInventory

• Targets for restorationTargets for restoration

• Long-term monitoring – both natural and Long-term monitoring – both natural and modified landsmodified lands

• It’s funIt’s fun

Data collection and Data collection and analysis - an on-analysis - an on-going activitygoing activity

The NCVS ProtocolThe NCVS Protocol

• Consistent methodologyConsistent methodology• Appropriate for most vegetation typesAppropriate for most vegetation types• FGDC compliantFGDC compliant• Scale transgressiveScale transgressive• Flexible in intensity of use and commitment Flexible in intensity of use and commitment

of time (Levels 1-5)of time (Levels 1-5)• Easily resampleableEasily resampleable• Total floristicsTotal floristics• Tree population structureTree population structure• Major site variables, including soil Major site variables, including soil

attributesattributes

Plots contain Plots contain multiple multiple modules modules recorded at recorded at multiple scalesmultiple scales

The Pulse ApproachThe Pulse Approach• Based on community collaborationBased on community collaboration• Provides training & experienceProvides training & experience• Intense regional focus for one Intense regional focus for one

weekweek– ““Bootcamp for botanists”Bootcamp for botanists”– ““Botanical Woodstock”Botanical Woodstock”– ““Extreme botany”Extreme botany”

NCVS Report CardNCVS Report Card

• Pulses events: 19 years (1-2/yr)Pulses events: 19 years (1-2/yr)• Numerous affiliated projectsNumerous affiliated projects• Volunteer participants: > 600Volunteer participants: > 600• Total plots: > 6000Total plots: > 6000• Total species: > 3000Total species: > 3000• Total vegetation types: > 200Total vegetation types: > 200

Results: Species Results: Species

frequenciesfrequencies2628 of 4073 species, 4956 plots, 194331 2628 of 4073 species, 4956 plots, 194331

occurrencesoccurrencesOctave Range Count

0 0 1445

1 1 354

2 2-3 350

3 4-7 342

4 8-15 342

5 16-31 328

6 32-63 280

7 64-127 268

8 128-255 189

9 256-511 95

10 512-1023 53

11 1024-2047 25

12 >2047 1

Top 5 species in 4955 plots

• 63% 63% Acer rubrumAcer rubrum (Red Maple) (Red Maple)• 39%39% Smilax glaucaSmilax glauca (Whiteleaf Greenbrier) (Whiteleaf Greenbrier)• 38% 38% Smilax rotundifoliaSmilax rotundifolia (Common (Common

Greenbrier)Greenbrier)• 36%36% Nyssa sylvaticaNyssa sylvatica (Black Gum) (Black Gum)• 36%36% Quercus rubraQuercus rubra (Red Oak) (Red Oak)

Top 7 species: 652 Coastal Plain forest plots

• 48% 48% Toxicodendron radicansToxicodendron radicans (Poison-ivy) (Poison-ivy)• 44% 44% Acer rubrumAcer rubrum (Red Maple) (Red Maple)• 44% 44% Parthenocissus quinquefoliaParthenocissus quinquefolia

(Virginia-creeper)(Virginia-creeper)• 41% 41% Vitis rotundifoliaVitis rotundifolia (Muscadine) (Muscadine)• 41% 41% Liquidambar styracifluaLiquidambar styraciflua (Sweetgum) (Sweetgum)• 35% 35% Smilax rotundifoliaSmilax rotundifolia

(Common Greenbrier)(Common Greenbrier)• 34% 34% Smilax bona-noxSmilax bona-nox (Catbrier) (Catbrier)

(15 of the top 50 are vines)(15 of the top 50 are vines)

Who is missing?

• Rare speciesRare species• Weeds of fields and waste Weeds of fields and waste

placesplaces• Plants of marshes and wetlandsPlants of marshes and wetlands• Plants of special habitatsPlants of special habitats

Occurrences of Carolina MilkweedsOccurrences of Carolina Milkweeds**=rare, *=uncommon (Weakley 2006)**=rare, *=uncommon (Weakley 2006)

31 Asclepias amplexicaulis 1 ** Asclepias perennis

9 ** Asclepias cinerea 0 ** Asclepias purpurascens

1 ** Asclepias connivens 13 Asclepias quadrifolia

58 Asclepias exaltata 3 * Asclepias rubra

18 Asclepias humistrata 0 Asclepias syriaca

4 Asclepias incarnata 6 * Asclepias tomentosa

3 * Asclepias lanceolata 28 Asclepias tuberosa

27 * Asclepias longifolia 14 Asclepias variegata

13 * Asclepias michauxii 24 * Asclepias verticillata

1 ** Asclepias obovata 2 * Asclepias viridiflora

9 ** Asclepias pedicellata 0 ** Asclepias viridis

Longleaf Pine vegetationLongleaf Pine vegetation

Xeric barrens & Xeric barrens & Subxeric uplands:Subxeric uplands:

Longleaf – turkey Longleaf – turkey oak woodlands on oak woodlands on entisolsentisols

9 Types9 Types13 Types13 Types

Flatwoods:Flatwoods:

Longleaf Longleaf woodlands of woodlands of spodosolsspodosols

5 types5 types

Silty uplands: Silty uplands:

Longleaf Longleaf woodlands on woodlands on well-drained well-drained ultisolsultisols

12 types12 types

Savannas and Savannas and seeps:seeps:

Longleaf Longleaf woodlands on woodlands on moist alfisolsmoist alfisols

13 types13 types

Ecological Groups

Mountain Vegetation • Montane upland forests • Montane open upland vegetation • Montane alluvial wetland vegetation • Montane nonalluvial wetland vegetation

Piedmont Vegetation • Piedmont upland forests • Piedmont open upland vegetation • Piedmont alluvial wetland vegetation • Piedmont nonalluvial wetland vegetation

Coastal Plain Vegetation • Coastal Plain upland forests • Coastal Plain upland open & woodland vegetation • Coastal Plain alluvial wetland vegetation • Coastal Plain nonalluvial wetland vegetation

Coastal Fringe Vegetation • Maritime upland forests & shrublands • Maritime open upland vegetation • Maritime nontidal wetland vegetation • Tidal wetland vegetation http://

cvs.bio.unc.edu

Targets for ecological Targets for ecological restorationrestoration

Classic Restoration Classic Restoration strategystrategy• Document reference conditionsDocument reference conditions

• Derive restoration targetsDerive restoration targets

• Design site-specific restoration planDesign site-specific restoration plan

• Implement the planImplement the plan

• Monitor change and assess successMonitor change and assess success

• Employ adaptive managementEmploy adaptive management

““The EEP mission is to restore, The EEP mission is to restore, enhance, preserve and protect the enhance, preserve and protect the functions associated with wetlands, functions associated with wetlands, streams, and riparian areas, including streams, and riparian areas, including … restoration, maintenance and … restoration, maintenance and protection of water quality and protection of water quality and riparian habitats …”riparian habitats …”

North Carolina Ecosystem North Carolina Ecosystem Enhancement ProgramEnhancement Program

Biennial Budget FY 2005/06 and 2006-07

Cost by Category: Total $175,077,880

SummaryAdministration $ 9,477,939Restoration* $ 102,910,770HQ Preservation $ 57,984,804Project Development $ 4,704,366 *Includes Implementation and Biennial Total $ 175,077,880 Future Mitigation Projects

5%

59%

33%

3%Administration

Restoration

HQPreservation

ProjectDevelopment

Ecosystem Enhancement ProgramEcosystem Enhancement Program

Stream RestorationDurham, NC

Traditional EEP methodTraditional EEP method

• Consult brief habitat-based plant Consult brief habitat-based plant listslists

• Design a site-specific restoration Design a site-specific restoration planplan

• Implement the planImplement the plan

• Monitor survival of planted stems Monitor survival of planted stems 5 yrs5 yrs

• Replant if neededReplant if needed

EEP-CVS CollaborationEEP-CVS Collaboration• EEP wants to do a better job EEP wants to do a better job

creating natural ecosystems.creating natural ecosystems.

• CVS provides improved reference CVS provides improved reference data, target design, data, target design, monitoring, and monitoring, and data management data management and analysisand analysis

Target generation Target generation

• Simple goalSimple goal – Deliver composition – Deliver composition goal based on the vegetation type goal based on the vegetation type most appropriate for the site and most appropriate for the site and region.region.

• Sophisticated goalSophisticated goal – Automated – Automated system that uses site information system that uses site information and reference plot data to predict and reference plot data to predict vegetation composition.vegetation composition.

Longleaf pine – feasibility study

• Few longleaf pine sites remain in “original” condition.

• Restoration targets must be extrapolated from a limited number of reference stands.

Dataset:

-188 plots across fall-line sandhills of NC, SC, & GA

- All sites contained near-natural, fire-maintained groundlayer vegetation

- Soil attributes included for both the A and B horizon: sand, silt, clay, Ca, Mg, K, P, S, Mn, Na, Cu, Zn, Fe, BD, pH, organic content, CEC, BS.

Step 1. Classification.

Developed a classification of the major vegetation types of the ecoregion.

Used cluster analysis with a matrix of 188 plots x 619 species.

Vegetation types were seen to be differentiated with respect to soil texture, moisture, nutrient status, & geography.

Step 2. Build model.

- Forward selection with linear discriminant analysis identified predictor variables.

- Critical variables were Latitude, Manganese, Phosphorus, Clay, Longitude.

- 75% of plots correctly identified to vegetation series. Typically 75% of plots within a series were correctly classified to community type.

Step 3. Select species.

1.Generate a list of all species in type (species pool) with frequency, mean cover values, and mean richness.

2.Randomly order the list

3.Compare species frequency to random number between 0 & 1, and if the random number is less than the proportion of plots the species is selected. Continue until the number in list of selected species equals the number predicted.

Summary of overall strategy:

• Identify biogeographic region and obtain predictive models.

• Select pool of candidate species for a specific site based on range information.

• Divide restoration site into environmentally homogenous areas, stratifying by topography and soil.

• Use models to select species number and composition.

Monitoring – CVS Monitoring – CVS methodsmethods

• Trade off between detail and time.Trade off between detail and time.

• EEP protocol seamlessly integrates EEP protocol seamlessly integrates with CVS methods by allowing a with CVS methods by allowing a series of sampling levels.series of sampling levels.

• MS-Access data-entry tool to assure MS-Access data-entry tool to assure standardize data, easy assimilation, standardize data, easy assimilation, and automated quality control.and automated quality control.

• Backend database used for reports Backend database used for reports and analysisand analysis

Reports & AnalysisReports & Analysis

• Datasheets for monitoringDatasheets for monitoring

• Survival & growth of planted stemsSurvival & growth of planted stems

• Direction of compositional changeDirection of compositional change

• Rate of changeRate of change

• Problems needing attention, such Problems needing attention, such as exotic species as exotic species

Information Information Infrastrustructure and Infrastrustructure and

Biodiversity Databases Biodiversity Databases

“ … ecology is a science of contingent generalizations, where future trends depend (much more than in the physical sciences) on past history and on the environmental and biological setting.”

Robert May 1986

Major new data sourcesMajor new data sources

• Site data: climate, soils, topography, etc.

• Taxon attribute data: identification, phylogeny, distribution, life-history, functional attributes, etc.

• Occurrence data: attributes of individuals (e.g., size, age, growth rate) and taxa (e.g., cover, biomass) that occur or co-occur at a site.

Biodiversity Biodiversity data structuredata structure

Taxonomic database

Observation database

Occurrence database

Observation/Collection Event

Specimen or Object

Bio-Taxon

Locality

Observation or Community Type

Observation type database

VegBankVegBank

• VegBankVegBank is a public archive for vegetation is a public archive for vegetation plot observations (plot observations (http://vegbank.org).

• VegBankVegBank is expected to function for is expected to function for vegetation plot data in a manner vegetation plot data in a manner analogous to analogous to GenBankGenBank. .

• Primary data will be deposited for Primary data will be deposited for reference, novel synthesis, and reanalysis.reference, novel synthesis, and reanalysis.

• The database architecture is generalizable The database architecture is generalizable to most types of species co-occurrence to most types of species co-occurrence data.data.

www.vegbank.orgwww.vegbank.org

OpportunitiesOpportunities

• Theoretical community ecologyTheoretical community ecology. Which taxa . Which taxa occur together, and where, and following occur together, and where, and following what rules?what rules?

• Remote sensingRemote sensing. What is really on the . What is really on the ground?ground?

• MonitoringMonitoring. What changes are really taking . What changes are really taking place in the vegetation?place in the vegetation?

• RestorationRestoration. What should be our . What should be our restoration targets?restoration targets?

• Vegetation & species modelingVegetation & species modeling. Where . Where should we expect species & communities to should we expect species & communities to occur after environmental changes?occur after environmental changes?

• Accurate identification and Accurate identification and labelling of organisms is a critical labelling of organisms is a critical part of collecting, recording and part of collecting, recording and reporting biological data. reporting biological data.

• Increasingly, research in Increasingly, research in biodiversity and ecology is based biodiversity and ecology is based on the integration (and re-use) of on the integration (and re-use) of multiple datasets.multiple datasets.

Biodiversity informatics Biodiversity informatics depends on accurate and depends on accurate and

precise taxonomyprecise taxonomy

Taxonomic database Taxonomic database challenge:challenge:

Standardizing organisms and Standardizing organisms and communitiescommunities

The problem:The problem: Integration of data potentially Integration of data potentially

representing different times, places, representing different times, places, investigators and taxonomic standards.investigators and taxonomic standards.

The traditional solution:The traditional solution: A standard list of organisms / A standard list of organisms /

communities.communities.

Standard lists are available for Standard lists are available for TaxaTaxa

Representative examples for higher plants in Representative examples for higher plants in North America / USNorth America / US

USDA PlantsUSDA Plants http://plants.usda.gov http://plants.usda.gov ITISITIS http://www.itis.usda.gov http://www.itis.usda.gov NatureServeNatureServeBONAP BONAP Flora North AmericaFlora North America

These are intended to be checklists wherein the taxa These are intended to be checklists wherein the taxa recognized perfectly partition all plants. The lists can recognized perfectly partition all plants. The lists can be dynamic.be dynamic.

Name ReferenceConcept

Taxonomic theoryTaxonomic theory

A taxon concept represents a unique A taxon concept represents a unique combination of a combination of a namename and a and a reference. reference.

Report -- Report -- namename sec sec referencereference..

.

USDA Plants & ITIS

Abies lasiocarpa

var. lasiocarpa

var. arizonica

One concept ofAbies lasiocarpa

Flora North America

Abies lasiocarpa

Abies bifolia

A narrow concept of Abies lasiocarpa

Partnership with USDA plants to provide plant concepts for data integration

Relationships among Relationships among conceptsconcepts

allow comparisons and allow comparisons and conversionsconversions

• Congruent, equal (=)Congruent, equal (=)• Includes (>)Includes (>)• Included in (<)Included in (<)• Overlaps (><)Overlaps (><)• Disjunct (|)Disjunct (|)• and others …and others …

High-elevation fir trees of western US

AZ NM CO WY MT AB eBC wBC WA OR

var. arizonica

Abies lasiocarpa

Distribution

USDA & ITIS

Flora North America

Abies bifolia Abies lasiocarpa

A. lasiocarpa sec USDA > A. lasiocarpa sec FNA

A. lasiocarpa sec USDA > A. bifolia sec FNA

A. lasiocarpa v. lasiocarpa sec USDA > A. lasiocarpa sec FNA

A. lasiocarpa v. lasiocarpa sec USDA | A. bifolia sec FNA

A. lasiocarpa v. arizonica sec USDA < A. bifolia sec FNA

var. lasiocarpa

Andropogon virginicusAndropogon virginicus complex in the complex in the CarolinasCarolinas

9 elemental units; 17 base concepts; 25 9 elemental units; 17 base concepts; 25 namesnames

Demonstration ProjectsConcept relationships of Southeastern US

plants treated in different floras.

Based on > 50,000 mapped concepts

When reporting the identity of When reporting the identity of organisms in publications, data, or on organisms in publications, data, or on specimens, provide the full scientific specimens, provide the full scientific name of each kind of organism and name of each kind of organism and the reference that provided the the reference that provided the taxonomic concept.taxonomic concept.

e.g.,e.g., Abies lasiocarpa sec. Abies lasiocarpa sec. Flora North Flora North America 1997.America 1997.

Best practice: Report Best practice: Report taxa by reference to taxa by reference to conceptsconcepts

Lessons forLessons for HorticulturalistsHorticulturalists

• Which taxa to recommend for restoration Which taxa to recommend for restoration planting ? – CVS descriptions and toolsplanting ? – CVS descriptions and tools

• Determine how well plantings have Determine how well plantings have worked ?worked ?– CVS monitoring– CVS monitoring

• What to grow in anticipation of the What to grow in anticipation of the market ?market ?– CVS descriptions & EEP predictions– CVS descriptions & EEP predictions

• How to document identifications ?How to document identifications ?– NCU concepts– NCU concepts

• What are the natural conditions under What are the natural conditions under which a taxon typically grows ? which a taxon typically grows ? – CVS database– CVS database

Case study:Case study:

Diversity and invasibility Diversity and invasibility of southern Appalachian of southern Appalachian plant communities.plant communities.

Little Tennessee River - Little Tennessee River - FloodplainFloodplain

Nolichucky River - UplandsNolichucky River - Uplands

Nolichucky River – Nolichucky River – Bedrock Scour BarBedrock Scour Bar

New River - Scoured IslandNew River - Scoured Island

Montane riparian habitats

NativeNative

ExoticExotic

UplandUpland(1090 plots)(1090 plots)

Riparian Riparian (121 plots)(121 plots)

31.12

0.20 (268 plots with exotics)

55.66

7.98 (110 plots with exotics)

Mean Species Richness

Kruskal-Wallis: Native Richness Kruskal-Wallis: Native Richness ΧΧ22 = 353.2, df = 1, P < 0.0001 = 353.2, df = 1, P < 0.0001

Exotic Richness Exotic Richness ΧΧ22 = 127.7, df = 1, P < 0.0001= 127.7, df = 1, P < 0.0001

Community saturation at small Community saturation at small scales?scales?

Does the degree to which immigration or Does the degree to which immigration or extinction processes affect communities extinction processes affect communities vary with scale?vary with scale?

Relationship between Native and Relationship between Native and Exotic Species Richness at a Large Exotic Species Richness at a Large

ScaleScale

Relationship between Native and Relationship between Native and Exotic Species Richness at a Local Exotic Species Richness at a Local

ScaleScale

Case Study – The lower Roanoke River

Roanoke basin

IA

IB

IIA

IIB

IIC

IIDi

IIDii

IIE

IIF

IIG

IIIA

IIIB

IIIC

IIIDi

IIIDii

IIIE

IIIF

IIIHi

IIIHii

V

IVB

IVA

VIA

VIB

VIC

VID

VIIAi

VIIAii

VIIB

VIIC

VIII

IX

X

IIH

I. Upland Oak Forest

II. Mixed Mesic Forest

III. Alluvial Hardwood Forest

IV. Forested Peatland

VI. Blackwater Swamp Forest

VII. Brownwater Swamp Forest

VIII. Sand and Mud Bar VegetationIX. Freshwater Marsh VegetationX. Floating Aquatic Vegetation

COMMUNITY TYPE VEGETATION CLASS

IIIG

V. Non-riverine Swamp Forest

Pre-settlement floodplain surface: -82 cm

DarkerGley

Financial Support

• US Forest Service – Savannah River Site; Clean Air Program; National Forests in NC

• The Nature Conservancy • NC Heritage Trust Fund• NC Agricultural Research Service • Syngenta• National Park Service • National Science Foundation• NC-DENR – Ecosystem Enhancement

Program

Why CVS?

• Description, classification, and analysis of Description, classification, and analysis of the natural vegetation of the Carolinasthe natural vegetation of the Carolinas

• Determine attributes of individual taxaDetermine attributes of individual taxa

• InventoryInventory

• Targets for restorationTargets for restoration

• Long-term monitoring – both natural and Long-term monitoring – both natural and modified landsmodified lands

• It’s fun, and you are invited !!It’s fun, and you are invited !!