United States

Department

of Agriculture

Forest Service

Rocky Mountain

Research Station

General Technical

Report RMRS-GTR-103

March 2003

Lichen Communities

Indicator Results from

Idaho: Baseline Sampling

Peter Neitlich

Paul Rogers

Roger Rosentreter
Cover illustration by Lucy Taylor, with permission from Bruce McCune

Neitlich, Peter; Rogers, Paul; Rosentreter, Roger. 2003. Lichen communities indicator results from

Idaho: baseline sampling. Gen. Tech. Rep. RMRS-GTR-103. Fort Collins, CO: U.S. Department of

Agriculture, Forest Service, Rocky Mountain Research Station. 14 p.

Abstract __________________________________________

Epiphytic lichen communities are included in the national Forest Health Monitoring (FHM) program

because they help us assess resource contamination, biodiversity, and sustainability in the context of

forest health. In 1996, field crews collected lichen samples on 141 field plots systematically located

across all forest ownership groups in Idaho. Results presented here are the baseline assessment of

the statewide field survey. Seventy-five epiphytic macrolichen species were reported from Idaho. Mean

species richness varied significantly from seven to 12 species per plot depending on ecoregion province

(p < 0.0001). Four lichen species are reported for the first time in Idaho. Major community gradients in

nonmetric multidimensional scaling (NMS) ordination are most strongly related to latitude, elevation,

percent forest cover, and lichen species richness. Ecoregion provinces occupy significantly

different subsections of n-dimensional species space in multi-response permutation procedures

(MRPP, p < 1 x 10–8).

Keywords: lichens, Forest Health Monitoring, forest inventory, Idaho, air quality, biodiversity

The Authors _____________________________________________

Peter Neitlich is a Plant Ecologist and has served as the national Lichen Indicator Advisor for the Forest Inventory

and Analysis program. He holds a B.S. degree in environmental studies from Yale University and an M.S. degree

in plant ecology from the University of Vermont. He holds a joint appointment as a plant ecologist with the National

Park Service in northwest Alaska.

Paul Rogers is an Ecologist in the Interior West Forest Inventory and Analysis program at the Rocky Mountain

Research Station, Forestry Sciences Laboratory, Ogden, UT. His primary responsibility is to report on Forest Health

Monitoring efforts in the Interior West. He holds a B.S. degree in geography from Utah State University and an M.S.

degree in geography from the University of Wisconsin-Madison.

Roger Rosentreter is the State Botanist for the Bureau of Land Management in Boise, ID. He earned a Ph.D.

degree in botany from the University of Montana. His duties include work on sagebrush ecosystems, rare plants,

and weeds in Idaho. He conducts several workshops and training sessions annually on plant and lichen

identification.

Acknowledgments _______________________________________

Peter Neitlich completed this work as a contractor to the FHM program, via funding from USDA Forest Service,

State and Private Forestry, Forest Health Protection and USDA Forest Service, Research, Forest Inventory and

Analysis. We thank Bruce McCune, Andrea Pipp, Susan Szewczak, Dayle Bennett, and Dave Atkins for advice and

technical assistance with Idaho lichen data collection. Special acknowledgement for outstanding effort goes out to

FHM field crew members Terry Briones, Peter Conklin, Linda Spillers, Sarah Hedrich, Ken Hehr, Brad Bolton, and

Dana Lambert. We appreciate the time and intelligence submitted by technical reviewers of this document.
Contents

Page

Introduction ....................................................................................................................................... 1

Previous Work in Idaho ..................................................................................................................... 1

Methods ............................................................................................................................................ 2

Lichen Community Sampling ......................................................................................................... 2

Data Sources ................................................................................................................................. 3

Quality Assurance .......................................................................................................................... 3

Results .............................................................................................................................................. 4

Biodiversity and Community Structure ........................................................................................... 4

Discussion: Epiphytic Lichen Status and Trends Relative to Forest Dynamics .............................. 11

Increase in Douglas-fir Stands and Stand Density ...................................................................... 11

Decline in Mature Larch ............................................................................................................... 11

Increase in Orange Lichens Due to Excess Nitrogen .................................................................. 11

Decline in Large Riparian Hardwoods ......................................................................................... 12

Further Research Needed............................................................................................................... 12

Air Quality .................................................................................................................................... 12

References ...................................................................................................................................... 13

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USDA Forest Service Gen. Tech. Rep. RMRS-GTR-103. 2003 1

Introduction ____________________

This publication assesses biodiversity and community structure of the Idaho lichen community by

using a statewide plot–based sample. Secondary goals

are to present basic lichen data analysis methods,

document quality assurance techniques, and make

some preliminary statements about air quality. Ultimately, a statewide inventory of lichen communities

can aid managers in resource decisionmaking and

lead to greater general ecosystem understanding by

the public.

The Forest Health Monitoring (FHM) program seeks

to assess the condition and trend of the forests of the

United States (NAPAP 1993; Riitters and others 1992).

FHM is linked with the national sampling grid established by the Environmental Monitoring and Assessment Program (EMAP) of the Environmental Protection Agency (Messer and others 1991) and now

maintained by the USDA Forest Service’s Forest Inventory and Analysis (FIA) program. Epiphytic lichen

community sampling was included in FHM to help

answer several key forest health assessment questions. These questions relate to contamination and

sustainability of forest resources, changes in biodiversity, and overall forest health.

Hundreds of papers worldwide (chronicled in the

series “Literature on air pollution and lichens” in the

Lichenologist) and dozens of review papers and books

(for example, Nash and Wirth 1988; Richardson 1992;

Seaward 1993; Smith and others 1993; van Dobben

1993) have documented the close relationship between lichen communities and air pollution, especially SO2 and acidifying or fertilizing nitrogen and

sulfur-based pollutants. In a comparison of biological

responses between nearby and remote areas surrounding a coal-fired power plant, lichens gave a much

clearer response (in terms of diversity, total abundance, and community composition) than either foliar

symptoms or tree growth (Muir and McCune 1988).

Lichens were one of the few components of terrestrial

ecosystems to show a clear relationship to gradients of

acidic deposition in the eastern United States (NAPAP

1991; Showman 1992). Much of the sensitivity of

epiphytic lichens to air quality apparently results

from their lack of a cuticle and their reliance on

atmospheric sources of nutrition. Although trees may

respond to moderate and chronic levels of airborne

pollutant deposition, multiple influences on tree growth

(e.g., variation in soil, moisture regime, canopy position, tree damage) make the responses of trees to

pollutants difficult to measure in the field. Lichen

communities not only provide a direct measure of air

pollution impacts upon lichens, but also suggest possible air pollution impacts on whole forest ecosystems

that are difficult to measure directly.

In addition to their utility as indicators of air quality, epiphytic lichens are an important component of

many forests. Lichens often comprise a large portion of

the diversity of total plant species in a forest. Lichens

have numerous functional roles in temperate forests,

including nutrient cycling (especially nitrogen fixation in moist forests) (Pike 1978) and as components of

food webs (Dawson and others 1987; Maser and others

1986; Rominger and Oldemeyer 1989; Servheen and

Lyon 1989).

Previous Work in Idaho __________

There have been numerous lichen studies in Idaho,

including several using lichens as biomonitors of air

pollution. Hoffman (1974) documented the influence

of a paper pulp mill on the epiphytic lichens in the

vicinity of Lewiston. Dillman (1996) studied the use of

Rhizoplaca melanophthalma as a biomonitor of phosphate pollution near Pocatello. Rope and Pearson

(1990) studied the use of lichens as air quality

biomonitors in the semiarid areas of Idaho. Rosentreter

(1990) correlated increasing lichen cover on desert

shrubs with increased dust and excess nitrogen in the

air. In Northern Idaho, McCune and Rosentreter (1998)

examined lichen species richness by forest cover types

over an elevational gradient. They found greater species richness in the moist low elevation forest cover

types than in the subalpine forest cover. There have

Lichen Communities Indicator

Results from Idaho: Baseline

Sampling

Peter Neitlich

Paul Rogers

Roger Rosentreter
2 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-103. 2003

also been several lichen inventory efforts in Idaho.

Schroeder and others (1973, 1975), Anderegg and others (1973) and Schroeder and Schroeder (1972) have

compiled a catalog of the lichens of Idaho as well as site

specific species lists.

Wildlife uses of lichen have received particular attention in Idaho. Rominger and others (1994) examined the impacts of timber harvesting on woodland

caribou habitat, of which epiphytic lichens were a

major forage component. Rosentreter and others (1997)

and Hayward and Rosentreter (1994) examined the

seasonal food habits of the northern flying squirrel in

the interior conifer forests of central Idaho, finding

that the epiphytic lichen Bryoria constituted a principal winter food source.

Atkins and others (1999) provide an overview of

forest resources, forest change, and forest health

issues generally in Idaho. Issues such as the changing

distribution of grand fir, western larch, and ponderosa

pine are likely to exert a great influence on future

lichen communities.

Methods _______________________

Lichen Community Sampling

The lichen community indicator is implemented in

two phases (fig. 1). In the calibration phase, a gradient model of lichen communities is constructed to

isolate and describe climatic and air quality gradients. In the application phase, this gradient model is

applied to calculate gradient scores for additional

plots. Scores for these plots are then used to describe

the regional condition and geographic variation in

Figure 1—Implementation of lichen communities as

an indicator in the Forest Health Monitoring program.

This figure presents a conceptual model of data flow

for lichen air quality scoring.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-103. 2003 3

lichen communities. Repeated sampling of these permanent plots allows for the documentation of changes

in the condition of lichen communities over time.

Lichen data from FHM sampling are archived in a

national database located in Las Vegas, Nevada.

There are a limited number of lichenologists and a

relatively large number of sample plots nationally.

Therefore, field procedures were designed for implementation by non-lichenologists for practical reasons

of staffing field crews. In FHM’s Interior West region, field crews have typically received between 2

and 3 days of intensive training in lichen community methods. To be certified, crews must attain the

required measurement quality objective (MQO) of

collecting 65 percent of an expert’s species capture on

the same plot. A crew must be certified to sample field

plots. The method has two parts that are performed

simultaneously:

(1) In each standard 0.94 acre (0.38 ha) FHM plot

(Tallent-Halsell 1994), the field crew searches for

macrolichens (relatively large leafy or pendulous lichens) on woody plants and collects a sample of each

lichen believed to be a distinct species. Macrolichens

are generally lichens that attain three dimensions and

are relatively easily removed from their substrates, as

opposed to the “flattened,” or two-dimensional, forms

that appear “painted on” to their respective substrates.

Tree and shrub bases below 1.64 ft (0.5 m) are excluded

from sampling to avoid distinct forest floor lichen

communities. Recently fallen lichen litter, either unattached or on branches, may be included as they

provide an excellent sample of forest canopy lichens.

This collection method represents the species diversity of woody substrate macrolichens in the plot as

fully as possible.

(2) The field crew estimates the abundance of each

species using a four-step scale: 1 = rare (<3 individuals

in plot); 2 = uncommon (4 to 10 individuals in plot);

3 = common (>10 individuals in plot but less than half

of the boles and branches have that species present);

and 4 = abundant (more than half of boles and branches

in the plot have the subject species present).

Field personnel only distinguish among species and

assign abundance estimates to each sample. Crews do

not have to identify samples; specimens are sent to

specialists for identification. Field methods are described in detail in Tallent-Halsell (1994). Quality

assurance procedures and results are described in

Cline (1995) and McCune and others (1997), and

methods have been closely scrutinized and documented

for repeatability (McCune and others 1997).

Analyses were designed to detect major community

gradients in the lichen species data and the significant

environmental variables strongly associated with these

gradients. Multivariate analyses including ordination

and multi-response permutation procedures were performed on the on-frame plot (see Data Sources below)

community matrix of 141 plots by 75 species using

PC-ORD (McCune and Mefford 1999, Mielke 1984).

Data Sources

This report summarizes results from a total of 155

plots, including 14 reference plots, as described below.

Supplemental urban and industrial plots (not yet

established) will provide a final data component in

future analysis (see Methods, fig. 1). All data, as well

as further information concerning the Lichen Communities Indicator, may be accessed online at: http://

www.wmrs.edu/lichen/

On-frame plots—Lichen community data were

collected by field crews on 141 on-frame permanent

plots in 1996. “On-frame” plots are located on a formal

sampling framework, according to standard sampling

protocols for the EMAP hexagonal grid (Messer and

others 1991). The strict sampling criteria applied to

the on-frame data allow regional estimates of lichen

community parameters. On-frame data can be used

for assessment of regional status and trends because

they comprise an unbiased sample (Messer and others

1991). In contrast, off-frame data, while useful in

building a gradient model, cannot be used to answer

such questions as, “Is lichen diversity in Idaho decreasing through time?”

Reference plots—In 1996, a reference location in

Cache County, Utah, was sampled twice by each of

seven crew members for a total of 14 reference plot

data files. The purpose of these reference plots was to

establish consistency between crews and to assess

changes in crew performance over the season. These

plots are for quality assurance assessment only and

are not included in the Idaho dataset analysis.

Quality Assurance

Quality assurance for the 1996 Idaho dataset included reference plots and “hot” checks, but not “cold”

checks (i.e., independent audits by specialists, either

with or without crew knowledge). Although data were

not kept of “hot” checks, an experienced trainer independently sampled plots, checked for procedural compliance, and answered sampling questions. Each reference plot (located near Logan, Utah, close to Idaho) was

sampled twice by each crew member. Although expert

plot scores were not available for this year, the high

score of eight species was consistent with expert scores

from other years in Logan Canyon and was used for

calculation of the measurement quality objective

(MQO). Crews improved in species capture by 9 percent
4 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-103. 2003

over the season (table 1), starting the season with 68

percent of expert scores and ending at 73 percent.

Between-crew variability represented by the coefficient

of variation (CV=[standard deviation/mean]*100) for

the two measurements was 9 percent and 28 percent

for the first and second visits, respectively. It appears

that the rise in the CV in the second visit occurred as

some crews gained skill over the season while others

did not. The mean CV over all reference plots was 19

percent. A high rate of attainment of MQOs was

achieved (93 percent overall) for reference plots, which

lends good credibility to the on-frame dataset.

Results ________________________

Biodiversity and Community Structure

Seventy-five macrolichen species were found on FHM

plots in Idaho in 1996 (table 2, table 3). The five most

common lichen species in Idaho’s forests were Letharia

vulpina(70 percent plot frequency), Bryoria fuscescens

(60 percent), Hypogymnia imshaugii (56 percent),

Melanelia exasperatula(59 percent), and Parmeliopsis

ambigua (48 percent) (table 3). Four species, Hypogymnia austerodes, Hypogymnia bitteri, Ramalina dilacerata, and Usnea hirta are reported in Idaho for the

first time. General distributions of plots per species

richness class are shown in table 4. Most FHM plots

(68 percent) in Idaho had six to 15 species collected.

The mean species richness per plot was 9.2 species

(table 2) and species richness varied significantly by

ecoregion province (Bailey and others 1994) (F = 9.8,

p < 0.0001 in a one-way ANOVA), from 12.2 in the

oceanically influenced Northern Rocky Mountain Province to 7.1 in the dry Intermountain Semi-Desert

Province (table 5) (fig. 2). Patterns in species richness

across the State may be attributed largely to moisture

and temperature regimes accompanying each

ecoregion’s physical geography.

A variety of preliminary community analyses via

nonmetric multidimensional scaling ordination (NMS)

(Kruskal 1964) were tested. For these trials, plots and

species with two or fewer occurrences and those for

which key secondary measurements (e.g., basal area

Table 1—Summary of QA reference plots, Idaho, 1996 (located at a training site near Logan, Utah). “S” is mean species richness

followed in parentheses by the standard deviation. Bias represents the signed mean deviation from the expert score. The

Measurement Quality Objective (MQO) represented 65 percent of eight species, or five species.

Improvement from CV between Crews

N S (SD) % of experta Bias 1st to 2nd sampling crewsb achieving MQO

- - - - - - - - - - - - - - - - - - - Percent- - - - - - - - - - - - - - - - - -

All 14 5.6 (1.2) 71 –2.4 9 19 93

Sample 1 (June) 7 5.4 (0.5) 68 –2.6 — 9 100

Sample 2 (August) 7 5.9 (1.7) 73 –2.2 — 28 86

a

As expert scores were not available, the high species count of eight was used. This was consistent with true expert scores in this same location

for other years. b

Coefficient of variation. See text for calculation.

Table 2—Alpha with standard deviation (SD), beta, and

gamma diversity of epiphytic lichens in 141 onframe plots in Idaho. Alpha diversity (α) is

mean species richness per plot. Beta diversity

(β) is gamma/alpha and is a rough estimate of

“community turnover.” Gamma diversity (γ) is

the total number of species found on all plots.

Plot type Number α (SD) β γ

On Frame 141 9.2 (4.3) 8.2 75
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-103. 2003 5

Table 3—Epiphytic macrolichen species found on 141 on-frame plots in Idaho, 1996. Matrix contents: 141 plots by 75 species.

Percent frequency = number of occurrences/total number of plots. Relative abundance = sum total abundance/total

possible abundance sum for all plots. Status was assessed using percent frequency values as follows: 0–1 = uncommon;

2–10 = occasional; 11–25 = common; >25 = abundant. Axis 1 and Axis 2 r2 values are correlations of species with

ordination axes (see fig. 3 for ordination). Only r 2 values > 0.04 are shown. Indicator values: *= p < 0.05; **= p < 0.01 (see

table 7 for explanation of ecoregion province codes and/or Bailey and others [1994] for province and section information).

Ecological distribution notes classify the lichens in one of five categories: oceanic influence, moist interior, widespread,

boreal, and continental. These reflect a gradient from moist to dry sites.

Ecoregion

province and/or

Relative Axis 1 Axis 2 section indicator Ecological

Species % freq abundance (%) Status r r values distribution notes

Ahtiana sphaerosporella 1 0.9 Uncommon Moist interior

Alectoria imshaugii 12 8.9 Common 0.12 Moist interior

Alectoria sarmentosa 31 26.2 Abundant 0.42 **M333, *M333D Oceanic influence

Bryoria capillaris 13 11.7 Common 0.18 *M333, *M333A Oceanic influence

Bryoria fremontii 16 13.1 Common Moist interior;

 open sites

Bryoria furcellata 1 0.5 Uncommon Oceanic influence

Bryoria fuscescens 60 46.8 Abundant 0.05 Widespread

Bryoria pseudofuscescens 16 14.5 Common 0.11 0.05 *331 Moist interior

Bryoria simplicior 1 0.2 Uncommon Moist interior

Candelaria concolor 4 2.5 Occasional Widespread;

 excess N indicator

Cetraria canadensis 9 6.6 Occasional 0.08 Moist interior

Cetraria chlorophylla 30 22.7 Abundant 0.37 **M333, *M333A Widespread

Cetraria merrillii 9 5.3 Occasional *331 Continental

Cetraria orbata 21 17.4 Common 0.17 *M333 Oceanic influence

Cetraria pallidula 1 0.5 Uncommon Moist interior

Cetraria pinastri 1 0.2 Uncommon Widespread; boreal

Cetraria platyphylla 29 23.8 Abundant 0.18 0.04 Continental

Cladonia sp. 9 5.7 Occasional 0.10 Widespread

Cladonia chlorophaea 1 0.7 Uncommon Widespread

Esslingeriana idahoensis 9 6.0 Occasional 0.10 Moist interior;

 predominantly

 M333

Evernia prunastri 13 8.0 Common 0.08 Oceanic influence;

 predominantly

 M333

Hypocenomyce scalaris 1 0.2 Uncommon Widespread

Hypogymnia apinnata 1 0.5 Uncommon Oceanic influence

Hypogymnia austerodes 4 2.0 Occasional Boreal; new

 record for Idaho;

 M332 only

Hypogymnia bitteri 1 0.5 Uncommon Boreal; new

 record for Idaho

Hypogymnia enteromorpha 1 1.2 Uncommon Oceanic influence

Hypogymnia imshaugii 56 47.3 Abundant 0.27 0.18 Moist interior

Hypogymnia inactiva 2 2.0 Occasional Oceanic influence;

 M333 only

Hypogymnia metaphysodes 12 9.8 Common *331 Oceanic influence

Hypogymnia occidentalis 12 11.2 Common 0.19 Oceanic influence;

 predominantly

 M333

Hypogymnia physodes 21 18.6 Common 0.27 *M333 Widespread

Hypogymnia rugosa 1 0.5 Uncommon Oceanic influence

Hypogymnia tubulosa 13 11.5 Common 0.16 *M333 Widespread;

 predominantly

 M333

Letharia columbiana 30 23.0 Abundant n0.12 0.08 Continental

(con.)
6 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-103. 2003

Letharia vulpina 70 55.1 Abundant 0.17 *331 Continental

Lobaria pulmonaria 6 5.5 Occasional 0.14 Oceanic influence;

 predominantly

 M333

Melanelia elegantula 6 4.8 Occasional n0.04 Continental

Melanelia exasperatula 59 45.4 Abundant n0.07 Continental

Melanelia glabra 2 1.1 Occasional n0.11 **342 Continental;

 342 only

Melanelia multispora 15 11.2 Common Oceanic influence

Melanelia subaurifera 4 3.0 Occasional n0.05 *342 Widespread

Melanelia subelegantula 10 7.6 Occasional Continental

Melanelia subolivacea 15 11.5 Common n0.06 Continental

Nephroma helveticum 1 0.4 Uncommon Oceanic influence

Nephroma parile 1 0.7 Uncommon Oceanic influence

Nephroma resupinatum 4 2.5 Occasional n0.05 Oceanic influence

Nodobryoria abbreviata 30 22.9 Abundant 0.27 **331, *331A Continental;

 coniferous forest

Nodobryoria oregana 1 1.1 Uncommon Moist interior

Parmelia hygrophila 19 15.2 Common 0.16 Oceanic influence

Parmelia sulcata 26 20.7 Abundant 0.14 Widespread

Parmeliopsis ambigua 48 35.1 Abundant 0.15 Widespread

Parmeliopsis hyperopta 13 10.1 Common 0.09 Oceanic influence

Peltigera collina 1 1.2 Uncommon Oceanic influence;

 epiphyte

Physcia adscendens 11 7.6 Common n0.06 n0.11 *342D Widespread;

 excess N

 indicator

Physcia aipolia 4 1.6 Widespread

Physcia biziana 2 0.9 n0.04 Widespread; on

 hardwoods

Physcia callosa 1 0.2 Uncommon Moist interior; rare

Physcia dimidiata 3 2.0 Occasional n0.07 n0.10 Continental; mostly

 on juniper

Physcia tenella 2 1.1 Occasional n0.04 n0.09 Widespread;

 excess N

 indicator

Physconia detersaa 1 0.9 Uncommon Widespread;

 apparently

 uncommon in

 Idaho

Physconia distorta 1 0.4 Uncommon Currently not

 classified

Platismatia glauca 33 29.3 Abundant 0.58 **M333, **M333A Moist interior;

 predominantly

 M333, moist

 areas

Platismatia stenophylla 2 2.0 Occasional Oceanic influence;

 M333 only

Pseudocyphellaria anthraspis 1 0.9 Uncommon Oceanic influence;

 M332 only in

 these data

c.f. Punctelia rudecta 1 0.4 Uncommon Needs further study

Ramalina dilacerata 1 0.5 Uncommon Widespread; on

 hardwoods; new

 record for Idaho

Ramalina farinacea 1 0.5 Uncommon Moist interior; on

 hardwoods

Usnea sp. 1 0.7 Uncommon Widespread

Usnea hirta 1 0.2 Uncommon Continental; new

 record for Idaho

Table 3 (Con.)

Ecoregion

province and/or

Relative Axis 1 Axis 2 section indicator Ecological

Species % freq abundance (%) Status r r values distribution notes

(con.)
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-103. 2003 7

Usnea lapponica 26 18.6 Abundant n0.04 **M331 Continental;

 southern Rocky

 Mountains

Usnea plicata agg.b 3 2.5 Occasional Continental

Usnea scabrata 1 0.7 Uncommon Oceanic

Usnea subfloridana 6 4.8 Occasional Oceanic

Xanthoria fallaxc 22 14.7 Common n0.24 n0.23 **342 Widespread;

 excess N

 indicator

Xanthoria polycarpad 19 13.5 Common n0.18 Widespread; excess

 N indicator

a This taxon has now been divided into several others including Physconia enteroxantha, P. isidiigera and P. perisidiosa. b Recent taxonomic changes may place this aggregate within the Usnea filipendula group. c It is likely that these records may have included specimens of this species as well as X. fulva and X. oregana. d It is likely that these records may have included specimens of this species as well as X. hasseana and/or X. montana. n This value represents a negative relationship.

Table 3 (Con.)

Ecoregion

province and/or

Relative Axis 1 Axis 2 section indicator Ecological

Species % freq abundance (%) Status r r values distribution notes

Table 4—Number of plots by species richness

classes, 1996, Idaho.

Lichen species Number Percent

richness class of plots of plots

0 (0 spp.) 2 5

1 (1–5 spp.) 32 32

2 (6–15 spp.) 97 68

3 (>15 spp.) 9 5

Table 5—Lichen species richness with standard deviation (SD) according to Bailey’s Ecoregion Provinces (Bailey and others 1994),

with highly associated lichen species at province levels, Idaho, 1996. Associated species were determined with Indicator

Species Analysis (Dufrene and Legendre 1997). Indicator values: *= p < 0.05; **= p < 0.01. Gamma diversity (total species

number) was 75 and is not presented by province because of unequal sample sizes.

Ecoregion province N Species richness (SD) Highly associated species

331. Palouse Dry Steppe 6 11.8 (4.4) Nodobryoria abbreviata**, Bryoria

pseudofuscescens*, Cetraria merrellii*,

Hypogymnia metaphysodes*, Letharia vulpina*

M331. Southern Rocky Mountain 12 7.3 (2.4) Physcia adscendens*, Usnea lapponica**

Steppe-Open Woodland-Coniferous

Forest-Alpine Meadow

M332. Middle Rocky Mountain 71 8.1 (4.1)

Steppe-Coniferous Forest-Alpine

Meadow

M333. Northern Rocky Mountain 37 12.2 (3.3) Alectoria sarmentosa**, Bryoria capillaris*,

Forest-Steppe-Coniferous Forest- Cetraria chlorophylla**, C. orbata*,

Alpine Meadow Hypogymnia physodes*, H. tubulosa**,

Platismatia glauca**

342. Intermountain Semi-Desert 15 7.1 (4.0) Melanelia glabra**, Melanelia subaurifera*,

Xanthoria fallax**

Total for State 141 9.2 (4.3)
8 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-103. 2003

Figure 2—FHM lichen species richness for 141 on-frame plots in Bailey’s Ecoregion

Provinces, Idaho, 1996. Major cities with populations of over 18,000 are shown. Boundaries

from Bailey and others 1994.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-103. 2003 9

live trees, basal area conifers) were absent were excluded from the starting community matrix (141 plots x

75 species) resulting in a reduced community matrix of

135 plots x 57 species. The ordination explaining the

greatest amount of variance (79 percent) yielded a

three-dimensional solution with an extremely strong

correlation of two of the three primary community

gradients with species, latitude, elevation, species

richness, and longitude. A two-dimensional solution

explaining 70 percent of the variance was chosen for

increased interpretability, better correlations of environmental variables, and elimination of strong species

and environmental variable correlation along more

than one axis (table 6). Forty-eight percent of the

variance was explained by Axis 1 and 22 percent

explained by Axis 2 (coefficients of determination for

the correlations between ordination distances and

distances in the original n-dimensional space [r2] were

0.48 and 0.22 for Axis 1 and 2 respectively). Plots

clustered strongly in species space by ecoregion province (fig. 3) and provinces maintained strongly distinct subsections of n-dimensional species space in

multi-response permutation procedures (p < 1x10–8)

Figure 3—Ordination of a reduced community matrix of 135 Idaho plots by 57 species with nonmetric

multidimensional scaling (NMS, Kruskal 1964). Vectors from centroid are proportional to strength of correlation

(table 6). Vector values: LAT = Latitude; S = Species richness; LONG = longitude; % FOR = percent of plot

forested; ELEV = elevation. Ecoregion province designations follow Bailey and others (1994).

Table 6—Correlations of moderately to highly correlated

environmental variables in 1996 on-frame Idaho

dataset with two ordination axes in NMS ordination (McCune and Mefford 1999). Environmental

variable values where r2

 > 0.04 are shown.

Axis 1 Axis 2

Variable r2 r

2

Latitude 0.72

Longitude 0.29 0.11

Elevation *0.45

Species richness 0.45

Basal area (Total) 0.12 0.04

Basal area hardwoods *0.05

Basal area live hardwoods *0.05

Basal area conifers 0.12 0.07

Basal area live conifers 0.10 0.08

Percent of subplots forested 0.18

* This value represents a negative relationship.

LAT

LONG

S

ELEV

% FOR

nms

Axis 1

Axis 2

ECOREGION PROVINCE

M331-Southern Rocky Mountains

M332-Middle Rocky Mountains

M333-Northern Rocky Mountains

342-Intermountain Semi-Desert

331-Great Plains-Palouse Dry Steppe
10 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-103. 2003

(Mielke 1984). This statistic is complemented additionally by the high beta diversity (8.2) found in the

original unreduced community matrix (141 plots),

suggesting that there is more than one distinct lichen

community present in the dataset. Northern Rocky

Mountain province plots appeared to cluster more

tightly than any other province’s plots in both two- and

three-dimensional solutions. Mean values for basic

environmental attributes are shown by ecoregion provinces in table 7.

Axis 1 explained 79 percent of the variance in the

original data matrix; it was strongly associated with

subregional climates with the northern Rocky Mountain plots defining the positive end of this gradient

(fig. 3). Latitude, longitude, and species richness were

strongly positively correlated with Axis 1, while elevation was strongly negatively correlated (table 6). Species richness was higher in the oceanically influenced,

lower elevation mountains of northern Idaho (Northern Rocky Mountain Province). Richness was lower in

the higher and drier central and southern mountain

regions (Middle and Southern Rocky Mountain Provinces). Species such as Alectoria sarmentosa,

Platismatia glauca, Cetraria chlorophylla, and several Hypogymnia species were strongly correlated

with Axis 1, and most of these were strongly associated

indicator species for the Northern Rocky Mountain

Province (table 3). These and several other species

occurred exclusively or primarily in the wet conifer

forests of northern Idaho. Species such as Xanthoria

fallax and Letharia columbiana were negatively correlated with Axis 1 and were associated with the drier

Intermountain Semi-Desert and/or Southern and

Middle Rocky Mountain Provinces. A species cluster

including such taxa as Melanelia elegantula, M.

subolivacea, M. exasperatula, Physcia dimidiata, and

Physcia adscendens joined the latter two species on

the dry end of this gradient. The negative correlation

of elevation with the primary climatic axis relates

mainly to the lower mean elevation status of northern

Rocky Mountain plots (3600 ft/1097 m) than of other

regions (5300–7200 ft/1615–2194 m). It should be

stressed that in interpreting broad patterns in species

richness across the State, primary correlation is expected to relate to climate rather than air quality.

Axis 2 explained 22 percent of the variance in the

species by plots matrix. This axis was most strongly

correlated with percentage of subplots forested and

mean basal area of live conifers, and was most negatively correlated with mean basal area of live hardwoods (table 6). Provinces with a high mean percentage forested (96–98 percent for 3 northern provinces)

also had the highest mean basal area of conifers,

therefore these two variables were closely related.

Species strongly positively associated with this axis

were conifer forest dwellers (e.g., Hypogymnia

imshaugii, Letharia vulpina, Nodobryoria abbreviata),

while those negatively associated tended to occur on

hardwoods or conifer woodlands in nitrogen-enriched

areas (e.g., Xanthoria fallax, X. polycarpa, Physcia

spp.) As forest cover and basal area were lowest in the

dry southern regions, many of the species most strongly

negatively correlated with Axis 2 also had negative

correlations with Axis 1.

The correlation of hardwood basal area with Axis 2

was based on a very limited set of plots with hardwoods

present (table 7). The hardwood correlation was likely

to have been reduced further because the few plots

Table 7—Environmental attributes of 135 FHM plots for which secondary data exist, Idaho, 1996. Standard deviation of the mean

is provided in parentheses after the mean value. Ecoregion province designations follow Bailey and others (1994).

Ecoregion Province

M333. Northern M331. Southern

Rocky Mountain Rocky Mountain

M332. Middle forest- steppeRocky Mountain steppe- open

steppe- coniferous woodland342. Inter- coniferous forest- coniferous

331. Palouse mountain forest-alpine alpine forest-alpine

Variable dry steppe semi-desert meadow meadow meadow

N 5 15 66 37 12

Mean elevation 5300 (1315) 5960 (884) 6381 (1473) 3659 (1070) 7108 (931)

Mean basal area (ft2/ac) 12 (7) 11 (7) 18 (11) 21 (11) 15 (11)

Mean basal area hardwoods (ft2

/ac) 0.2 (0.4) 2.4 (6.0) 0.5 (1.3) 1.1 (2.9) 0.6 (1.4)

Mean basal area live hardwoods (ft2/ac) 0.2 (0.4) 2.2 (5.5) 0.4 (1.3) 1.1 (2.8) 0.5 (1.2)

Mean basal area conifers (ft2/ac) 12 (8) 8 (7) 18 (11) 20 (11) 14 (12)

Mean basal area live conifers (ft2

/ac) 12 (7) 8 (7) 16 (10) 17 (10) 12 (10)

Mean % of plot forested 98 (4) 86 (27) 98 (11) 96 (14) 85 (25)
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-103. 2003 11

containing hardwoods in the northern Rockies differed

both in tree and lichen species from the hardwood plots

in southern areas. As the hardwood lichen flora is

dramatically different from that of conifers, analysis of

these trends would require targeted sampling of hardwoods. Analysis of hardwoods separately within northern and southern provinces would also be likely to give

a stronger signal. For the construction of a gradient

model, it is likely that the semi-desert province will be

grouped with other Great Basin provinces, while the

montane provinces will be grouped with others in

Montana and eastern Oregon.

Ecoregional analysis provided several insights into

the floristics of Idaho’s lichens. Two ecoregion provinces stood out prominently in hosting a large number

of indicator species strongly associated with that province (table 5). The Northern Rocky Mountain Province

hosted seven indicator species, all of which represented common species west of the Cascade crest in

the Pacific Northwest. The Palouse Dry Steppe Province also hosted seven indicator species dominant in

eastern Oregon and Washington including Nodobryoria

abbreviata, Letharia vulpina, and Cetraria merrillii.

Because of the small number of plots in this province,

however, the high indicator values in these cases

should be treated with caution—these species occurred reliably in the few plots in this particular

province but most of these species are widespread

throughout at least one to two other provinces. The

Southern and Middle Rocky Mountain Provinces

tended to be more transitional in species composition

between the Northern Rockies and the Semi-Desert.

Letharia columbiana and L. vulpina, which overlap in

much of their range, showed divergent distribution in

Idaho. Letharia columbiana occurred predominantly

in drier forests, while L. vulpina proved widespread.

Discussion: Epiphytic Lichen Status

and Trends Relative to Forest

Dynamics ______________________

Increase in Douglas-fir Stands and Stand

Density

The Boise National Forest has documented a major shift in forest cover from mature open growth

ponderosa pine to denser, smaller diameter Douglasfir (O’Laughlin 1994), which impacts the distribution of lichen communities. This shift is attributed

to forest harvesting practices and fire suppression.

Historic ratios of approximately 80:20 percent ponderosa pine to Douglas-fir have changed to a ratio of

20:80 percent cover of the forested portions of the

landscape (O’Laughlin 1994).

Decline in Mature Larch

Western larch (Larix occidentalis) may support a

unique population of lichen species in central and

north Idaho (McCune and Rosentreter 1998; Rosso

and Rosentreter 1999). This tree can live 600 years

and is affected less by insects and disease than other

conifer species. Larch is associated with the upper

range of moisture in the State of Idaho and has fireresistant characteristics. Harvest practices, lack of

natural fires, and artificial regeneration of other tree

species have caused a decline in mature larch in Idaho

and Montana. This tree is held sacred to the Native

Americans who collect forage lichens from its branches

to be cooked and added to their pemican for winter

sustenance (Turner 1977). This tree species supports

large populations of forage lichens and produces large

amounts of biomass that are utilized by wildlife (Rosso

and Rosentreter 1999). Larch decline may contribute

to a decline in the abundance of the forage lichens in

the northern part of the state. Collaboration between

FHM and other forest surveys (for example, Forest

Inventory and Analysis) should yield ample information on larch population trends and lichen diversity.

Increase in Orange Lichens Due to Excess

Nitrogen

The increase of orange lichens (Xanthoria spp. and

others) on desert shrubs and elsewhere (Kauppi 1980),

due to excess nitrogen is documented in Idaho

(Rosentreter 1990) and may be affecting forests and

woodlands near sources of nitrogen pollution. From

FHM plot data observed here, nitrophilous species

such as Xanthoria fallax and X. polycarpa (sensu lato)

were highly associated with the Intermountain SemiDesert Province. This association is due in part to the

naturally high deposition of soil nitrogen via dust in

semi-arid areas, although the extent to which anthropogenic sources have contributed to an increase of

these taxa is unknown. While a small group of lichen

taxa are known to respond positively to nitrogen

enrichment, a much larger group exhibits deleterious

effects including dieback, deformities, cancer-like

growths, and dissociation of the algal and fungal

partners of the lichen (Kauppi 1980).

A prominent anthropogenic source of nitrogen in

Idaho is livestock; specifically concentrated dairy

farming in the southern part of the State. Idaho’s

dairy industry has expanded rapidly in recent years.

While the total number of dairies has decreased,

average size and overall dairy production have increased (Mitchell and Beddoes 1999). This trend may

be linked to a broader pattern of increasing atmospheric and terrestrial nitrogen levels in the western

U.S. (LeJeune and Seastedt 2001). Elevated nitrogen
12 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-103. 2003

pollution is likely to continue and lichen community

monitoring may be able to detect and track its areas of

impact.

Decline in Large Riparian Hardwoods

Due to forest conversion, streamside disturbance,

regulated stream flows from dams, splash dams for

logs, and road building along the stream channels,

riparian areas with large hardwoods have declined in

the State (USDA 1997). These hardwoods, most prominently aspen and cottonwood, support a diverse and

occasionally rare lichen flora (Hutchinson and McCune

2001). Since no plots occurred in riparian areas, gradient model plots or Evaluation Monitoring (a subsection of FHM) studies will examine several such areas

in assessing trends in diversity in riparian areas. The

Table 8—Characteristics of some common macrolichen genera growing on trees in Idaho.

Genus Appearance Indicator value and functional roles

Alectoria Yellow, hair-like Pollution-sensitive; strong indicator of wet-montane climate.

Bryoria Brown, hair-like Pollution-sensitive; forage lichen; many uses by animals. Some

species strong climate indicators.

Candelaria Yellow, very small foliose Pollution and dust tolerant, mainly on hardwoods.

Cetraria Greenish, broad-lobed foliose Generally intermediate in pollution sensitivity and in climate

indication.

Cladonia Grey-green stalks or cups with small frills Forest floor, tree bases, and rotting wood. Intermediate to

sensitive to air pollution; most common in wetter climates.

Hypogymnia Grey or brown, foliose, hollow lobes Mainly on conifers, some species pollution tolerant.

Letharia Yellow to chartreuse shrubby Widespread in continental conifer forests; somewhat pollution

sensitive.

Melanelia Brown to olive, foliose, medium size Nearly ubiquitous; some species pollution tolerant; on both

hardwoods and conifers.

Nephroma Brown, foliose, small A nitrogen-fixing lichen with oceanic affinities, pollution-sensitive.

Parmelia Grey, foliose, medium size, black below Widespread, pollution tolerant, on both hardwoods and

conifers.

Parmeliopsis Grey or green-gray narrow lobed foliose Mid to upper elevation conifers; intermediate in pollution

sensitivity.

Phaeophyscia Small, cryptic, gray or brownish, foliose Usually on hardwoods; most species pollution tolerant.

Physcia Small, white, foliose Some species nitrogen-loving; some species almost restricted

to hardwoods.

Physconia Small, frosty-coated, foliose, often Usually on hardwoods; pollution tolerant, nitrogen-loving.

 forming neat rosettes; brown,

 gray or white

Platismatia White, foliose, large On conifers in wet climates, pollution-tolerant to intermediate.

Usnea Greenish fruticose, tufted or hanging, Abundant in the mountains, somewhat pollution sensitive but

 branches have a central cord persisting in polluted areas as dwarf, compact forms.

Xanthoria Orange or yellow, foliose Widespread but more abundant in areas of elevated nitrogen,

somewhat pollution tolerant.

results of these special studies can complement regional gradient models and on-frame plots by specifically targeting less common regional habitats that

may significantly contribute to overall diversity.

Further Research Needed ________

Air Quality

Some common macrolichen genera growing on trees

in Idaho are presented in table 8. Based on the pollution sensitivity of species in these genera in the Pacific

Northwest (McCune and Geiser 1997) and Colorado

(McCune and others 1998), we have listed their likely

indicator values in Idaho, but further research will

determine their actual value as indicators here.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-103. 2003 13

Hayward, G. D.; Rosentreter, R. 1994. Lichens as nesting material

for northern flying squirrels in the Northern Rocky Mountains.

Journal of Mammalogy. 75(3): 663–673.

Hoffman, G. R. 1974. The influence of a paper pulp mill on the

ecological distribution of epiphytic cryptogams in the vicinity of

Lewiston, Idaho and Clarkson, Washington. Environmental Pollution. 7: 283–301.

Hutchinson, J. L.; McCune, B. 2001. Riparian lichens of northern

Idaho. Tech. Bull. 01-12. Boise, ID: U.S. Department of the

Interior, Idaho Bureau of Land Management. 139 p.

Kauppi, M. 1980. The influence of nitrogen-rich pollution components on lichens. Oulu, Finland: ACTA Universitatis Ouluensis,

Seris A Scientiaererum Naturalium No. 101, Biologica No. 9.

Kruskal, J. B. 1964. Nonmetric multidimensional scaling: a numerical method. Psychometrika. 29: 115–129.

LeJeune, K. D.; Seastedt, T. R. 2001. Centaurea species: the forb

that won the West. Conservation Biology. 15(6): 1568–1574.

Maser, C.; Maser, Z.; Witt, J. W.; Hunt, G. 1986. The northern flying

squirrel: a mycophagist in southwestern Oregon. Canadian Journal of Zoology. 64: 2086–2089.

McCune, B.; Dey, J.; Peck, J.; Cassell, D.; Heiman, K.; Will-Wolf, S.;

Neitlich, P. 1997. Repeatability of community data: species richness versus gradient scores in large-scale lichen studies. Bryologist.

100: 40–46.

McCune, B.; Geiser, L. 1997. Macrolichens of the Pacific Northwest.

Corvallis: Oregon State University Press. 386 p.

McCune, B.; Mefford, M. J. 1999. PC-ORD: Multivariate analysis of

ecological data, version 4. Manual. Gleneden Beach, OR: Software Design. 237 p.

McCune, B.; Rogers, P.; Ruchty, A.; Ryan, B. 1998. Lichen communities for Forest Health Monitoring in Colorado, USA. A report to

the U.S. Department of Agriculture, Forest Service, National

Forest Health Monitoring Program, Research Triangle Park, NC

Report on file at: Oregon State University, Department of Botany

and Plant Pathology. Corvallis, OR. 30 p.

McCune, B.; Rosentreter, R. 1998. Macrolichens from Priest River

Experimental Forest, Idaho. Evansia. 15(1): 37–42.

Messer, J. J.; Linthurst, R. A.; Overton, W. S. 1991. An EPA program

for monitoring ecological status and trends. Environmental Monitoring and Assessment. 17: 67–78.

Mielke, P. W., Jr. 1984. Meteorological applications of permutation

techniques based on distance functions. In: Krishnaiah, P. R.;

Sen, P. K., eds. Handbook of statistics. Vol. 4. Elsevier Science

Publishers: 813–830.

Mitchell, M. C.; Beddoes, J. C. 1999. Idaho dairy nutrient management. In: 1999 American Society of Agricultural Engineers

annual international meeting proceedings; 1999 July 19–21;

Toronto, Ontario, Canada. Paper No. 994079.

Muir, P. S.; McCune, B. 1988. Lichens, tree growth, and foliar

symptoms of air pollution: are the stories consistent? Journal of

Environmental Quality. 17: 361–370.

NAPAP (National Acid Precipitation Assessment Program). 1991.

Acidic deposition: state of science and technology reports. Volumes

I–IV. Washington, DC: United States Government Printing Office.

NAPAP. 1993. National Acid Precipitation Assessment Program

1992 report to Congress. Washington, DC: U.S. Government

Printing Office.

Nash, T. H.; Wirth, V., eds. 1988. Lichens, bryophytes and air

quality. Bibliotheca Lichenologica. 30: 1–297.

O’Laughlin, J. 1994. Assessing forest health conditions in Idaho with

forest inventory data. Journal of Sustainable Forestry. 2: 221–247.

Pike, L. H. 1978. The importance of epiphytic lichens in mineral

cycling. Bryologist. 81: 247–257.

Richardson, D. H. S. 1992. Pollution monitoring with lichens.

Naturalists’ Handbooks 19. Slough, England: Richmond Publishing Co., Ltd. 76 p.

Riiters, K. H.; Law, B. E.; Kucera, R. C.; Gallant, A. L.; DeVelice, R. L.;

Palmer, C. J. 1992. A selection of forest condition indicators for

monitoring. Environmental Monitoring and Assessment. 20: 21–33.

Rominger, E. M.; Allen-Johnson, L.; Oldemeyer, J. L. 1994. Arboreal

lichen in uncut and partially cut subalpine fir stands in woodland

caribou habitat, northern Idaho and southeastern British Columbia. Forest Ecology and Management. 70: 195–202.

Rominger, E. M.; Oldemeyer, J. L. 1989. Early-winter habitat of

woodland caribou, Selkirk Mountains, British Columbia. Journal

of Wildlife Management. 53: 238-243.

Rope, S. K.; Pearson, L. C. 1990. Lichens as air pollution biomonitors

in a semiarid environment in Idaho. Bryologist. 93(1): 50–61.

Air pollution impacts on lichens have been documented from a variety of sources in Idaho (Dillman

1996; Hoffman 1974; Rope and Pearson 1990). Pollution is likely to be having effects in the Boise and

Pocatello area, but determination of the nature and

severity of these effects awaits a gradient model. As

in other western States (e.g., Colorado) (McCune and

others 1998) pollution is likely to have the greatest

influence at low- to mid-elevations, where the climate

is driest and lichen flora are naturally species-poor.

Low species richness near Boise (western Intermountain Semi-Desert and southern Middle Rocky Mountain Provinces) should not necessarily be attributed to

pollution. Pollution impact on lichens has been documented in Lewiston (Hoffman 1974) and is likely to

produce patterns different from those farther south,

as diversity is naturally higher in this wetter zone.

The main research needed to place these findings in

perspective is regional gradient modeling (fig. 1). Examples of gradient analysis from other regions of the

country may be viewed online at: http://www.wmrs.edu/

lichen/. By sampling intensively around urban and

industrial areas and known clean air sites, we will be

able to model the changes in lichen communities from

clean air to polluted air in a variety of ecoregions and

elevations. An air quality scoring system is the key

product of the gradient model. The gradient model can

be applied to individual plot locations to give us a

better picture of air quality impacts on State lichen

communities specifically, and Idaho forests generally.

With a gradient model in place, we will be able to

assess air quality trends after the second cycle of

lichen sampling is completed in 2005.

References _____________________

Anderegg, D. E.; Schroeder, G. L.; Schroeder, N. E. 1973. Further

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implications. Rep. 99-4. Missoula, MT: U.S. Department of Agriculture, Forest Service, Northern Region, Forest Health Protection. 44 p.

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subregions of the United States. Washington, DC: U.S. Department

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14 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-103. 2003

Rosentreter, R. 1990. Indicator value of lichen cover on desert

shrubs. In: McArthur, E. D.; Romney, E. M.; Smith, S. D.; Tueller,

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1973. Seventy lichen species previously unreported from Idaho.

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unreported from Idaho. Bryologist. 75: 101–102.

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the lichens of Idaho. Bryologist. 78: 32–43.

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nitrogen and acidity. Netherlands: Utrecht University. 214 p.

(Dissertation).

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