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Applied Informatics for Studies of Vegetation Alliances: A Case Study Michael Jennings U.S. Geological Survey / University of Idaho [email protected]
Applied Informatics for Studies of Vegetation Alliances:
A Case Study
Michael Jennings
U.S. Geological Survey /University of Idaho
Vegetation Alliance
A vegetation classification unit containing one or more associations, and defined by a characteristic range of species composition, habitat conditions, physiognomy, and diagnostic species, typically at least one of which is found in the uppermost or dominant stratum of the vegetation.
(ESA Vegetation Panel 2004, www.esa.org/vegweb)
Quercus Garryana Forest and Woodland AlliancesPseudotsuga Menziesii - Quercus Garryana Woodland AlliancePinus Ponderosa - Quercus Garryana Woodland Alliance
Portions of Washington and Oregon, USA
Structural problems that limit work on the ecology of vegetation alliances:
the quantity of field samples needed, data that are interoperable (e.g., species
composition, climate, morphological traits), the quantitative descriptions.
The purpose of this study is to examine:
The processes needed for integrating field plot and other data from multiple sources.
Methods for assigning plot data to an accepted alliance.
Study Area
A Field Plot Dataset from Multiple Sources: The sources Univariate outliers Standardizing species names Assigning plots to alliances Multivariate outliers Testing for null Reducing dimensionality and visualizing the data Using the plot data set with climate and
productivity modeled data.
British Columbia
Washington
Oregon
39,131 Vegetation Field Plots from 11 Sources
The Data:
SourcesField Plots Sources
Field Plots
Hanford Site 30 USFS Eastside Forests 6,108Abies Grandis Data Cntr. 251 USFS Habitat Studies 2,213
Idaho Conservation Data Cntr. 137 USFS Nevada 1,256Montana Natural Heritage Prgm. 81 USFS Wyoming 376Montana Riparian Assn. 1,914 USFS California 289Orchard Training Area 396 USFS Region 6 8,547Oregon Natural Heritage Prgm. 330 USFS Research 308Oregon State U. Research 136 USFS Westside Forests 10,354Private Land Plots 2,725 Yakima Training Center 383USFS Forest Inventory & Assessment 3,297 TOTAL 39,131
Sources and amounts of field plots.
Univariate OutliersVariable Logical Consistency
canopy cover between 1 and 100coordinates to within the study areaspatial precision of 1 km or betterfour-digit years between 1940 and 2000elevation between 0 and 4,000 mslope aspect values between 0 and 360ºslope gradient values between 0 and 90ºplot size equivalent to 20 m2
All Taxonomic Entities
Process 1 Process 2
Binomials
Have synonyms?
Synonyms standardized to a single name
Unique binomial
yes no
Trinomials
Are synonymous with a unique binomial from Process 1?
Relabeled to unique
binomial
Relabeled to synonymous
unique binomial
yes no
Standardizing species names
Assigning Plots to Alliances
Query Parameters: dominant species identity and canopy cover associated species and canopy covers geographic range elevation range ground slope gradient ground slope aspect
Assigning Plots to AlliancesA query example:
SELECT DISTINCT …..FROM …..WHERE (((DomSp_New.AllianceKey)="A1000") And ((DomSp)="ALSI3") And ((([Basic plot info 18].[Can_Cov 1])>DomSp_New!SpCov_L)) And ((([Basic plot info 18].[Can_Cov 2])<DomSp_New!SpCov_H)) And ((([ELEVATIO]*3.048))>1200) And (([Basic plot info 18].LON)<-119));
Outliers of the Artemisia Arbuscula Alliance Plots
Axis 1
Axi
s 2
Mantel Test*
Evaluates correlation and significance of correlation between distance matrices.Used here to test the null hypothesis that the classified plot members of an alliance have no more floristic similarity than would randomly selected sets of plot records
* Mantel 1967, Sokal 1979, McCune & Grace 2002
OutlierAnalysis
OutliersRemoved
PlotSet 2
RemoveSet 2 from
all plots
Non-Set 2Plot List
RandomSample
Selection
Random Set ofPlots
Mantel TestSorensenDistance
PlotSet 1
12 3
4 5 6
78
9
Data flow of the multivariate outlier analysis and the Mantel test
Mantel Test
Survival Criteria: p < 0.1 r < 0.3
Results: 7 alliance plot sets had p > 0.1 1 set had r > 0.3 (Abies Lasiocarpa Krummholz ) 49 sets survived 8,919 field plots remained
Nonmetric Multidimentional ScalingOrdination
Classified plots were grouped by general types: forest / woodland shrub herbaceous
Criteria: Sorenson distance measure three dimensions 100 maximum iterations
Used to examine the floristic relationship of the plots within and among alliances.
NMS Results
Axis 1Axis 2
Axis 3
A total of 1,494 field plots comprising 20 shrub alliances.Artemisia Tridentada Shrub Alliance (all vars.) plots are shown in black, n=494. All other plots are shown in red.
NMS ResultsForest and Woodland Alliances
7
2
1 3
8
6
17
4
10
11
12
13
9
5 15
16
1814
19
20
Techniques for Classifying and Understanding Vegetation
The remote sensing and information technology that used in solving problems such as biodiversity loss can only be as good as our knowledge of plant community ecology on the ground.
A focus on measures of vegetation alliances is a good place to begin.
13
711
9
12
10
18
321
17
19
4
6
8
14
5
162015
Mean Similarity Among and Variability Within Shrubland Alliance Field Plots With and Without Dominant Species
3
4
5 6
12
8 9
10
11
12
13
14
17
7
191516
18
20
1. CAME 8. ROWO 15. ARTR-2. PHEM 9. ALIN LECI3. VADE 10. RUPA 16. ARTR4. SAPL 11. ALVI 17. AMAL5. COSE 12. ABLA-ACGL 18. ARUV6. SAGE 13. SYAL 19. PUTR7. PRVI 14. PEFL 20. ARAR
Dominant and Subdominant Species
Subdominant Species Only
Alliance Acronyms
