oakwoods: Oak Woodlands in the Willamette Valley, Oregon, USA

In phytomosaic/ecole: ecole: School of Ecology Package

Description

Vascular plants in oak forests of the Willamette Valley from the PhD dissertation of John F. Thilenius at Oregon State University.

Usage

oakwoods

Format

A list of 5 data.frames:

- spe species abundance matrix: 47 observations of 103 vascular plant species. Abundances were relativized by species maximum. This is a subset of all species, where all singletons and doubletons were removed from the 'raw' matrix below.

- env environmental matrix: 47 observations of 30 environmental variables. Environmental variables, described in detail below, include topographic, geographic and soils variables, and indicators of stand history. We also provide some community summary variables, including species richness, groups derived from cluster analysis, and community types as originally designated by Thilenius.

- tra traits matrix: 103 vascular plant species scored for each of 6 traits. The traits are simply growth forms and are scored as binary 0/1 (no/yes).

- xy spatial matrix: 47 observations of 2 spatial coordinates.

- raw raw species abundances: 47 observations of 189 vascular plant species. The raw species abundances are before any modifications. The values are basal areas (ft^2^/acre) for trees and percentage cover for lower strata, based on 60, 0.2 m^2^ quadrats/stand. “Trace” was converted to 0.5%. A check on the field data sheet was converted to 0.2%. Be careful! Any use of these raw data must recognize that the columns representing the tree stratum differ in units from the lower strata; hence, use of a relativized matrix in spe.

Details

This documentation is nearly verbatim from PC-ORD (McCune and Mefford 2017).

Overview

In 1961 and 1962 John F. Thilenius sampled vascular plants in oak forests in the Willamette Valley for his Ph.D. at Oregon State University (Thilenius 1963, 1968). The data came from a fairly narrow range of habitats – all of the stands were closed forests dominated by Quercus garryana. This resulted in a data set with fairly low beta diversity. The environmental differences among the sites are rather modest. Much of the variation in species composition presumably is derived from the particular histories of each stand, such as episodes of grazing, logging, and fire. Of course we have limited information on those histories, so you will see that much of the variation in the plant communities is not readily explained by the measured environmental and historical variables. Nevertheless a definite environmental gradient emerges from the analysis.

The abstract from Thilenius (1968) is reproduced below:

“Quercus garryana forests, prominent at low elevations throughout the Willamette Valley, Oregon, have developed from oak savanna subsequent to settlement of the valley in the mid-nineteenth century. Interruption of the ground fires that were common in the pre-settlement environment probably caused the change. The understory of the oak forest is dominated by shrubs, and well-defined strata are present. Four plant communities occur: (1) Quercus garryana/Corylus cornuta var. californica/Polystichum munitum (most mesic); (2) Quercus garryana/Prunus avium/Symphoricarpos albus; (3) Quercus garryana/Amelanchier alnifolia; (4) Quercus garryana/Rhus diversiloba (most xeric). All are in seral condition because of their relatively recent development and because they have been disturbed throughout their existence by man's activities. The soils supporting the oak forest are generally deep and well drained and have developed profiles with illuvial horizons and acidic reaction. They are derived from sedimentary and basic igneous rocks and old valley-filling alluvium. Seven established soil series are present: Steiwer, Carlton, Peavine, Nekia, Dixonville, Olympic, and Amity. The Steiwer series and its catenary associate, Carlton, are the most common soils.”

Thilenius’ goals were to describe “the floristic composition, stand structure, physical environment, and successional status of plant communities where Quercus garryana is the major component of the overstory.” Although quantitative data were carefully recorded, Thilenius had few possibilities for multivariate analysis. His primary analyses were first arranging his data “according to similarities in species composition, importance ranks, and environmental attributes.” He then tabulated averages for species and environmental variables within the four groups. Here is an interesting challenge for modern community analysts: what can you add to his account (Thilenius 1968) based on a more sophisticated quantitative analysis of the data? I mentioned above that a single strong environmental gradient emerges from the analysis, but this is only hinted in Thilenius’ abstract. What is that gradient?

After a listing of the files and variables contained in the files, three example procedures are given. The first demonstrates modification of the raw data into a form suitable for analysis. The second is an ordination with nonmetric multidimensional scaling. The third compares groups of sample units, as defined by landform.

Methods from Thilenius (1968)

“Investigations were confined to closed-canopy stands 4 ha or more in area where Quercus garryana was the major component of the overstory. Basal area, frequency, and density of overstory trees were determined on twenty 0.004-ha circular plots spaced at 9-m intervals in four rows parallel to the slope contour. Density was recorded in four classes: saplings (< 10 cm dbh); poles (11-40 cm dbh); mature (41-100 cm dbh) and relict (> 100 cm dbh). The maximum height of trees on each plot was measured with an optical rangefinder.”

“Frequency and percentage crown coverage of shrub and herbaceous species were recorded on sixty 0.2 m2 quadrats spaced at 3-m intervals in four rows coincident with the rows of 0.004-ha plots. Very low crown coverage was recorded as trace and arbitrarily assigned a value of 0.5% for calculation purposes. Above trace, the intervals were 1% and 5%. Coverage greater than 5

Coding for variables in the second matrix

Topographic and geographic variables

Elev,m = elevation above sea level in meters.
LatAppx = approximate latitude, decimal degrees, based on automated conversion of Township/Range/Section, using the program TRS2LL.exe.
LongAppx = approximate longitude, decimal degrees, based on automated conversion of Township/Range/Section, using the program TRS2LL.exe.
SlopeDeg = slope in degrees (originally recorded in percentages)
AspClass = aspect class, 1=SW, 2=S or W, 3=SE or NW, 4=N or E, 5=NE.
AspDeg = aspect in degrees E of N
PDIR = Potential annual direct incident radiation, MJ/cm2/yr, calculated according to McCune and Keon (2002) Eq. 3.
HeatLoad = Heat load index, calculated according to McCune and Keon (2002)
Landform: 1=valley bottom, 2=draw or slope of draw, 3=slope, 4=ridge
TopoClas = Topographic position class: adapted from scales used by Whittaker & Kessell (Kessell 1979)

Soil variables

Drainage: 1=poor, 2=moderate, 3=good, 4=well
Soil series: 1=Steiwer, 2=Peavine, 3=Dixonville, 4=Nekia, 5=Carlton, 6=Olympia, 7=Amity
SoilGrp: 1=sedimentary, 2=basic igneous, 3=alluvial
A-horiz = thickness of A horizon, cm
B1-horiz = thickness of B1 horizon, cm
B2-horiz = thickness of B2 horizon, cm
B3-horiz = thickness of B3 horizon, cm (if profile truncated, e.g. “44+ inches”, add 20 inches)
B-horiz = sum of B1+B2+B3, cm

Indicators of stand history

GrazCurr = signs of current grazing recorded on field data sheet (0=no,1=yes)
GrazCurrC = same as above but provided as text-based categorical variable (ungrazed, grazed)
GrazPast = signs of past grazing recorded on field data sheet (0=no, 1=yes, must be 1 if GrazCurr=1)
GrazPastC = same as above but provided as text-based categorical variable (ungrazedpast, grazedpast)
NotLogged = NPL recorded under “Influences” on data sheet. I guessed this means “no past logging”, i.e. no signs of past logging (0=logged, 1=not logged)
NotLoggedC = same as above but provided as text-based categorical variable (logged, notlogged)
Que>60cm = number of Quercus garryana recorded in the 60 cm (24 inch) size class and larger (no stands had large Pseudotsuga; one stand (Stand05) had a large Acer macrophyllum and one stand (Stand07) had two large Arbutus menziesii).
LogQ>60 = log of (x+1) where x is the number of Quercus garryana recorded in the 60 cm (24 inch) size class and larger (i.e. x = “LogQ>60”).
TreeHtM = maximum height of Quercus garryana in meters.

Community summary variables derived from the species matrix

SppRich = species richness, calculated from OakRaw.wk1, counting each species x layer combination as a separate species.
ThilType = vegetation types from Thilenius (1968)
- 1 = Quercus/Corylus/Polystichum
- 2 = Quercus/Prunus/Symphoricarpos
- 3 = Quercus/Amelanchier/Symphoricarpos
- 4 = Quercus/Rhus
FlxB-.25 = community types defined at the 4-group level from hierarchical cluster analysis, Flexible beta method, Sørensen distance, beta= -0.25.

List of species codes

Note: because woody species may occur in more than one stratum, a suffix (-s, -t) is used to indicate a given species in the shrub or tree stratum.

Abgr‑s Abies grandis SHRUB Abgr-t Abies grandis Acar Actea arguta Acgld Acer glabrum var. douglasii Acma‑s Acer macrophyllum shrub Acma-t Acer macrophyllum Acmi Achillea millefolium Adbi Adenocaulon bicolor Agha Agrostis hallii Agre Agropyron repens AGRO Agrostis sp? Agse Agrostis semiverticullata (subsecundum) Agte Agrostis tenuis Aica Aira caryophyllea ALL Allium sp. Alpr Alopecurus pratensis Amal‑s Amelanchier alnifolia shrub Amal-t Amelanchier alnifolia Apan Apocynum androsaemifolium Aqfo Aquilegia formosa Arel Arrhenatherum elatius Arme‑s Arbutus menziesii SHRUB Arme-t Arbutus menziesii Avfa Avena fatua Beaq Berberis aquifolium Brpu Brodiaea pulchella Brco Bromus commutatus Brla Bromus laevipes Brri Bromus rigidus Brse Bromus secalinus Brst Bromus sterilis Brvu Bromus vulgeris Caqu Camassia quamash CAR Carex sp. Cato Calochortus tolmiei Cear Cerastium arenses Ceum Centaurium umbellatum Ceve Ceanothus velutinus Cipa Circaea pacifica Civu Cirsium vulgare Coco‑s Corylus cornuta shrub Coco-t Corylus cornuta Cogr Collomia grandiflora Conu‑S Cornus nuttallii SHRUB Conu-t Cornus nuttallii CORY Corylus sp. Cost Corallorhiza striata Crca Crepis capillaris Crdo‑t Crataegus douglasii Crdo‑s Crataegus douglasii Crox Crataegus oxyacantha Cyec Cynosurus echinatus Cyfo Cystopteris fragilis Cygr Cynoglossum grande Daca Danthonia californica Dacar Daucus carota Dagl Dactylus glomerata Deel Deschampsia elongata Diar Dianthus armeria Doel Downingia elegans Drar Drysopterus arguta Drar Dryopteris arguta Elgl Elymus glaucus Erla Eriophyllum lanatum Erog Erythronium oregonum Eucr Euphorbia crenulata Feca Festuca californica Fede Festuca dertonenses Feel Festuca elatior var. arendmaceae Feme Festuca megalura Feoc Festuca occidentalis Feru Festuca rubra Frbr Fragaria bracteata (vesca) Frcu Fragaria cuneifolia Frla‑s Fraxinus latifolia shrub Frla-t Fraxinus latifolia Frvi Fragaria virginiana GAL Galium sp. Gema Geum macrophyllum Geog Geranium oreganum (incisum) Gepu Geranium pusillum Haob Habenaria orbiculata Haun Habenaria unalacensis Hehe Hedera helix Hemi Heuchera micrantha Hodi Holodiscus discolor Hola Holcus lanatus Hyoc Hydrophyllum occidentale Hype Hypericum perforatum Hyra Hypochaeris radicata Irte Iris tenax JUNC Juncus sp. Kocr Koeleria cristata Laco Lapsana comunis Lapo Lathyrus polyphyllus Lasa Lathyrus sativus (Pisum sativum) Liap Ligusticum apiifolium Libu Lithophragma bulbifera Lico Lilium columbianum Lide-t Libocedrus deccurens Lide‑s Libocedrus deccurens LILI Lilium sp. Loci Lonicera ciliosa Lope Lolium perenne LOT Lotus sp. Lotr Lomatium triternatum Lumu Luzula multiflora Maex Madia exigua MAL Malvaceae sp. Maor Marah oreganus Mebu Melica bulbosa Mila Microseris laciniata Mope Montia perfoliata Mosi Montia sibirica Nepa Nemophylla parviflora ONGR Onagraceae sp. Osce‑t Osmaronia cerasiformis tree Osce-s Osmaronia cerasiformis Osch Osmorhiza chilensis Osnu Osmorhiza nuda (chilensis) Phca Physocarpus capitatus Phle Philadelphus lewisii Phpr Phleum pratense Phvi Phoradendron villosum Pipo‑s Pinus ponderosa Pipo Pinus ponderosa Plla Plantago lanceolata Poco Poa compressa Pogl Potentilla glandulosa Pogr Potentilla gracilus Pogr Potentilla gracilis Pomu Polystichum munitum Popr Poa pratensis Povu Polypodium vulgare Prav‑s Prunus avium shrub Prav-t Prunus avium Prde-t Prunus virginiana var. demissa Prde‑s Prunus virginiana var. demissa shrub Prvu Prunella vulgeris Psme‑s Pseudotsuga menziesii shrub Psme-t Pseudotsuga menziesii Ptan Pterospora andromedia Ptaq Pteridium aquilinum var. lanuginosum Pyco‑s Pyrus communis shrub Pyco Pyrus communis Pyfu‑s Pyrus fusca SHRUB Pyfu-t Pyrus fusca Quga-s Quercus garryana shrub Quga Quercus garryana Raoc Ranunculus occidentalis Rhdi Rhus diversiloba Rhpu‑s Rhamnus purshiana shrub Rhpu Rhamnus purshiana Risa Ribes sanguinius Rodu Rosa??? Roeg Rosa eglanteria Rogy Rosa gymnocarpa Ronu Rosa nutkana Ropi Rosa pisocarpa Ropi Rosa pisocarpa Ruac Rumex acetosella Rula Rubus laciniatus Rule Rubus leucodermus Rupa Rubus parvifloris Rupr Rubus procerus Ruur Rubus ursinus S‑2 Carex sp2. S‑1 Carex sp1. Sacr Sanicula crassicaulis Sado Satureja douglasii Sagr Sanicula graveolens Seja Senecio jacobaea Siho Silene hookeri Smra Smilacina racemosa Smse Smilacina sessilifolia Syal Symphoricarpus albus Taas Taeniatherum asperum Taof Taraxacum officinale Tegr Tellima grandiflora Thoc Thalictrum occidentale Toar Torilis arvensis Trca Trisetum canescens TRIF Trifolium sp Trla Trientalis latifolia Trov Trillium ovatum Trpr Trifolium procumbens V1 Vicia sp. Valo Valerianella locusta Viam Vicia americana Viel Viburnum ellipticum Vinu Viola nuttallii VIOL Viola sp Zice Zygadenus venosus

Source

Bruce McCune collected this dataset for PC-ORD (McCune and Mefford 2017). The original raw data cards from Thilenius study in 1963 (data collected in 1961 and 1962) were obtained from John Thilenius via Bob Frenkel. Thanks to John Thilenius for granting permission to distribute his data. Bill Daly did the initial data entry. Bibit Traut added more variables and resolved numerous nomenclatural questions regarding the species codes used by Thilenius.

References

Kessell, S. R. 1979. Gradient Modeling: Resource and Fire Management. Springer-Verlag, New York. 432 pp.

McCune, B. and D. Keon. 2002. Equations for potential annual direct incident radiation and heat load. Journal of Vegetation Science 13:603-606.

McCune, B., and M. J. Mefford. 2017. PC-ORD. Multivariate Analysis of Ecological Data. Version 7. MjM Software Design, Gleneden Beach, OR.

Thilenius, J. F. 1963. Synecology of the white-oak (Quercus garryana Douglas) woodlands of the Willamette Valley, Oregon. PhD Dissertation. Oregon State University, Department of Botany and Plant Pathology, Corvallis. 151 pages.

Thilenius, J. F. 1968. The Quercus garryana forests of the Willamette Valley, Oregon. Ecology 49:1124-1133.

Examples

# split into two data.frames
data(oakwoods)
spe <- oakwoods$spe
env <- oakwoods$env
tra <- oakwoods$tra
raw <- oakwoods$raw

phytomosaic/ecole documentation built on Jan. 2, 2022, 11:24 p.m.