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Collections. Vegetation sampling We observe and collect data on soil.

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Page 1: Collections. Vegetation sampling We observe and collect data on soil.

Collections

Page 2: Collections. Vegetation sampling We observe and collect data on soil.
Page 3: Collections. Vegetation sampling We observe and collect data on soil.
Page 4: Collections. Vegetation sampling We observe and collect data on soil.
Page 5: Collections. Vegetation sampling We observe and collect data on soil.

Vegetation sampling

Page 6: Collections. Vegetation sampling We observe and collect data on soil.
Page 7: Collections. Vegetation sampling We observe and collect data on soil.
Page 8: Collections. Vegetation sampling We observe and collect data on soil.

We observe and collect data on soil

Page 9: Collections. Vegetation sampling We observe and collect data on soil.

More soil. . .

Page 10: Collections. Vegetation sampling We observe and collect data on soil.

Once a plot is set up, the fun begins!

Page 11: Collections. Vegetation sampling We observe and collect data on soil.
Page 12: Collections. Vegetation sampling We observe and collect data on soil.
Page 13: Collections. Vegetation sampling We observe and collect data on soil.

Marl outcrop – Lake Waccamaw, Columbus Co, NC

Page 14: Collections. Vegetation sampling We observe and collect data on soil.

Fall line rock outcrop vegetation , with

Amphianthus pusillus and Diamorpha smallii

- Forty Acre Rock HP, Lancaster Co, SC

Page 15: Collections. Vegetation sampling We observe and collect data on soil.

Determining DBHDetermining DBHwith d-tapewith d-tape

Page 16: Collections. Vegetation sampling We observe and collect data on soil.

And more trees. . .

Page 17: Collections. Vegetation sampling We observe and collect data on soil.

It’s a plant id party!!

Page 18: Collections. Vegetation sampling We observe and collect data on soil.

VegBankVegBank ------

Data Model & XML Data Model & XML schemaschema

Page 19: Collections. Vegetation sampling We observe and collect data on soil.

Why an exchange Why an exchange standard?standard?

• Many research questions require Many research questions require lots of datalots of data

• Facilitate exchange !Facilitate exchange !• Write input/output just onceWrite input/output just once• Encourage others to participate Encourage others to participate

(eg US Forest Service)(eg US Forest Service)• Safe & documented long-term Safe & documented long-term

storage of plot datastorage of plot data

Page 20: Collections. Vegetation sampling We observe and collect data on soil.

www.vegbank.orgwww.vegbank.org

Page 21: Collections. Vegetation sampling We observe and collect data on soil.

T

Page 22: Collections. Vegetation sampling We observe and collect data on soil.

T

Page 23: Collections. Vegetation sampling We observe and collect data on soil.
Page 24: Collections. Vegetation sampling We observe and collect data on soil.

Key design featuresKey design features

• Many kinds of plots !!!Many kinds of plots !!!• Easy search Easy search • Easy citation and linkageEasy citation and linkage• Easy downloadEasy download• XML input and output optionsXML input and output options• Users can annotate plots and Users can annotate plots and

determinationsdeterminations• Support of taxon conceptsSupport of taxon concepts

Page 25: Collections. Vegetation sampling We observe and collect data on soil.

Biodiversity data structure

Taxonomic database

Plot/Inventory database

Occurrence database

Plot Observation/Collection Event

Specimen or Object

Bio-Taxon

Locality

Vegetation Type

Vegetation type database

Page 26: Collections. Vegetation sampling We observe and collect data on soil.

Project

PlotPlot

Observation

Taxon / Individual Observation

Taxon Interpretation

PlotInterpretation

Core Core elements of elements of VegBankVegBank

Page 27: Collections. Vegetation sampling We observe and collect data on soil.

VegBank VegBank consists of consists of three integrated three integrated

databasesdatabases

1.1. The Plot DatabaseThe Plot Database

2.2. The Plant DatabaseThe Plant Database

3.3. The Community DatabaseThe Community Database

Page 28: Collections. Vegetation sampling We observe and collect data on soil.

The VegBank ERDThe VegBank ERD

• Available at: Available at: http://vegbank.org/vegdocs/design/erd/vegbank_erd.pdf

• Click tables for data dictionary and Click tables for data dictionary and constrained vocabularyconstrained vocabulary

Page 29: Collections. Vegetation sampling We observe and collect data on soil.
Page 30: Collections. Vegetation sampling We observe and collect data on soil.

PlotPlot

• EmbargosEmbargos

• Named PlaceNamed Place

Page 31: Collections. Vegetation sampling We observe and collect data on soil.

ObservationObservation

• ProjectProject

• Disturbance ObsDisturbance Obs

• Soil Obs Soil Obs

• Soil taxonSoil taxon

• GraphicGraphic

• Observation Observation SynonymSynonym

Page 32: Collections. Vegetation sampling We observe and collect data on soil.

Taxon ObservationTaxon Observation

• Importance valuesImportance values

• Author nameAuthor name

Taxon InterpretationTaxon Interpretation

• Which taxonWhich taxon

• Who decided and whyWho decided and why

• Stem or collectiveStem or collective

• Voucher informationVoucher information

Page 33: Collections. Vegetation sampling We observe and collect data on soil.
Page 34: Collections. Vegetation sampling We observe and collect data on soil.

Strata & Strata & CoverCover

• Stratum methodStratum method

• Stratum typeStratum type

• StratumStratum

• Cover methodCover method

• Cover IndexCover Index

Page 35: Collections. Vegetation sampling We observe and collect data on soil.

InterpretatioInterpretationncontinued continued

PlantsPlants

• Tax Tax InterpretationInterpretation

• Taxon AltTaxon Alt

CommunitiesCommunities

• ClassClass

• InterpretationInterpretation

Page 36: Collections. Vegetation sampling We observe and collect data on soil.

Problematic taxa of ecological datasets

• Carex sp.• Crustose lichen• Hairy sedge #6.• Sporobolus sp. #1• Picea glauca – engelmannii complex• Potentilla simplex or P. canadensis• Carya ovata sec. Gleason 1952

Page 37: Collections. Vegetation sampling We observe and collect data on soil.

PartyParty• Project Project Contr.Contr.

• Obs Contr.Obs Contr.

• RoleRole

Page 38: Collections. Vegetation sampling We observe and collect data on soil.

ReferencReferenceses

Page 39: Collections. Vegetation sampling We observe and collect data on soil.

UtilitiesUtilities• User definedUser defined

• NotesNotes

• RevisionsRevisions

Page 40: Collections. Vegetation sampling We observe and collect data on soil.
Page 41: Collections. Vegetation sampling We observe and collect data on soil.

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.

Page 42: Collections. Vegetation sampling We observe and collect data on soil.

Standardized taxon lists Standardized taxon lists failfail

to allow dataset integrationto allow dataset integration

The reasons include:The reasons include:

• Taxonomic concepts are not defined (just Taxonomic concepts are not defined (just lists), lists),

• Relationships among concepts are not Relationships among concepts are not defineddefined

• The user cannot reconstruct the database as The user cannot reconstruct the database as viewed at an arbitrary time in the past, viewed at an arbitrary time in the past,

• Multiple party perspectives on taxonomic Multiple party perspectives on taxonomic concepts and names cannot be supported or concepts and names cannot be supported or reconciled.reconciled.

Page 43: Collections. Vegetation sampling We observe and collect data on soil.

Abies lasiocarpa

Abies bifolia

Abies lasiocarpa

sec.sec. Little Littlesec.sec. USDA PLANTS USDA PLANTS

sec.sec. Flora North America Flora North America

Three concepts of subalpine fir

Splitting one species into two illustrates the ambiguity often associated with scientific names.

Page 44: Collections. Vegetation sampling We observe and collect data on soil.

USDA Plants & ITIS

Abies lasiocarpa

var. lasiocarpa

var. arizonica

One concept ofAbies lasiocarpa

Page 45: Collections. Vegetation sampling We observe and collect data on soil.

Flora North America

Abies lasiocarpa

Abies bifolia

A narrow concept of Abies lasiocarpa

Partnership with USDA plants to provide plant concepts for data integration

Page 46: Collections. Vegetation sampling We observe and collect data on soil.

High-elevation fir trees of High-elevation fir trees of western North Americawestern North America

AZ NM CO WY MT AB eBC wBC WA OR

Abies lasiocarpa

var. arizonica

Abies lasiocarpa var. lasiocarpa

DistributionDistribution

USDA - ITISUSDA - ITIS

Flora North AmericaFlora North America

Abies bifolia Abies lasiocarpa

Minimal conceptsMinimal concepts

A B C

Page 47: Collections. Vegetation sampling We observe and collect data on soil.

Andropogon virginicusAndropogon virginicus complex in the complex in the CarolinasCarolinas

9 elemental units; 17 base concepts, 27 scientific names9 elemental units; 17 base concepts, 27 scientific names

Page 48: Collections. Vegetation sampling We observe and collect data on soil.

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 …

Page 49: Collections. Vegetation sampling We observe and collect data on soil.

Party PerspectiveParty Perspective

The Party Perspective on a concept includes:The Party Perspective on a concept includes:

• Status – Standard, Nonstandard, Status – Standard, Nonstandard, UndeterminedUndetermined

• Correlation with other concepts – Correlation with other concepts – Equal, Greater, Lesser, Overlap, Equal, Greater, Lesser, Overlap,

Undetermined.Undetermined.

• Start & Stop dates for tracking changesStart & Stop dates for tracking changes

Page 50: Collections. Vegetation sampling We observe and collect data on soil.

Intended functionalityIntended functionality

• Organisms are labeled by reference to Organisms are labeled by reference to concept (name-reference combination),concept (name-reference combination),

• Party perspectives on concepts and names Party perspectives on concepts and names can be dynamic, but remain perfectly can be dynamic, but remain perfectly archived,archived,

• User can select which party perspective to User can select which party perspective to follow,follow,

• Different names systems are supported,Different names systems are supported,

• Enhanced stability in recognized concepts Enhanced stability in recognized concepts by separating name assignment and rank by separating name assignment and rank from concept.from concept.


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