When family matters: an analysis of Thelotremataceae (Lichenized Ascomycota: Ostropales) as...

ORI GIN AL PA PER

When family matters: an analysis of Thelotremataceae(Lichenized Ascomycota: Ostropales) as bioindicatorsof ecological continuity in tropical forests

Eimy Rivas Plata Æ Robert Lucking Æ H. Thorsten Lumbsch

Received: 10 April 2007 / Accepted: 24 October 2007 / Published online: 23 November 2007� Springer Science+Business Media B.V. 2007

Abstract We analysed patterns of habitat and microhabitat preferences of 19 families

(comprising 135 genera and 950 species) of crustose, corticolous lichens in Costa Rica

(Arthoniaceae, Arthopyreniaceae, Coenogoniaceae, Graphidaceae, Lecanoraceae, Letrou-

itiaceae, Monoblastiaceae, Pertusariaceae, Physciaceae, Pilocarpaceae, Porinaceae,

Pyrenulaceae, Ramalinaceae, Roccellaceae, Strigulaceae, Teloschistaceae, Thelenellaceae,

Thelotremataceae, Trypetheliaceae), in order to test whether Thelotremataceae are suitable

predictors of undisturbed tropical rain forest and can be used as bioindicators of ecological

continuity. The dataset consisted of 12,215 specimen samples and six environmental

parameters recorded for each sample (altitude, degree of seasonality, vegetation type,

disturbance level, substrate nature, light exposure), which were analysed by a multivariate

approach using principal component analysis (PCA). The analysis showed that three of the

19 families, Letrouitiaceae, Porinaceae, and Thelotremataceae, showed significant pref-

erences for undisturbed primary to old growth secondary forest, fully shaded to semi-

exposed microhabitats, and the bark of mature tree trunks, parameters assumed to be

correlated with ecological continuity of closed rain forest habitats. Thelotremataceae had

broader altitudinal range than Letrouitiaceae and Porinaceae and significantly higher genus

and species diversity (16 genera, 130 species) compared to Porinaceae (4 genera, 40

species) and Letrouitiaceae (1 genus, 5 species). Our results support the hypothesis that

Thelotremataceae perform best as predictors of undisturbed dry and lowland to montane

E. Rivas Plata � R. Lucking � H. T. LumbschDepartment of Botany, Field Museum of Natural History, 1400 South Lake Shore Drive,Chicago, IL 60605–2496, USA

R. Luckinge-mail: [email protected]

H. T. Lumbsche-mail: [email protected]

E. Rivas Plata (&)Ecology and Evolution Program, Biological Sciences Department, University of Illinois at Chicago,845 W Taylor Street, Chicago, IL 60607, USAe-mail: [email protected]

123

Biodivers Conserv (2008) 17:1319–1351DOI 10.1007/s10531-007-9289-9

rain forest and are the most suitable lichen bioindicators of ecological continuity in these

ecosystems. In contrast, Lecanoraceae, Pertusariaceae, Physciaceae, and Teloschistaceae,

were found to be predictors of disturbed and pioneer (micro-)habitats. We also found that,

among a variety of parameters tested, the Index of Ecological Continuity (IEC), adapted to

the use of Thelotremataceae in tropical forests, performs best in terms of predicting dis-

turbance levels and site history. A semi-taxonomic approach identifying morphotypes

rather than genera or species yielded the same results, making this method suitable for a

broader spectrum of potential users.

Keywords Crustose � Corticolous � Costa Rica � Lichen families

Tropical rain forests are the most diverse ecosystems on the planet, containing more than

half of all species (Terbourgh 1992; Phillips et al. 1994; Wilson 1999; Floren and Lin-

senmair 2005; Jablonski et al. 2006). They are not only valuable economic sources,

including ecotourism, food, pharmaceutical products, timber, protection of watersheds, and

carbon storage (Curran et al. 1999; Kremen et al. 2000; Pearce 2001; Dalton 2006), but are

living heritage and testimony to the evolution of life, in itself reason for their conservation

(Wilson 1984, 1999, 2002). Tropical rain forests continue to be deforested at alarming rates

(FAO 1981; Myers 1991; Skole and Tucker 1993; Achard et al. 2002; ITTO 2002), con-

tributing not only to regional and global climate change (Shukla et al. 1990; Still et al.

1999; Malhi and Grace 2000; Fearnside 2000, 2001; Lawton et al. 2001; Defries et al.

2002; Fearnside and Laurance 2004) but also the extinction of thousands of species (Lewin

1986; Raup 1986; Brook et al. 2006; Wright and Muller-Landau 2006). Tropical rain

forests are not only affected by clear-cutting, but also selective logging, slash-and-burn

agriculture, and fragmentation, being replaced by a mosaic of variously degraded forest

remnants, secondary vegetation, and partially recovering forest (Laurance et al. 2000;

Martin et al. 2004; Lamb et al. 2005).

Since the start of the conservation movement in the mid 20th century, increasing efforts

are being made to revert the effects of deforestation, by protecting remaining rain forest

and through reforestation and establishment of biological corridors (Uhl et al. 1988; Aide

et al. 2000; Margules and Pressey 2000; Barrow et al. 2002; Arroyo-Moya et al. 2005;

Lamb et al. 2005). However, conservation is expensive (Bonnie et al. 2000; Balmford and

Whitten 2003) and protective land use planning thus subject to economic decisions based

on financial resources, requiring selection among potentially available areas based on a

quality assessment. The Nature Conservancy was recently funded with $ 8 million by the

Moore Foundation to establish the ‘Osa Biological Corridor’, connecting several protected

areas on the Osa Pensinsula in southern Costa Rica, arguably the biologically richest

tropical rain forest in Central America (http://www.nature.org/pressroom/press/press1657.

html). Spending this money wisely depends on reliable assessment of the status of hitherto

unprotected forest remnants to be integrated into the prospective biological corridor.

One approach to assess the conservation status of forest remnants is the concept of

‘ecological continuity’ or, in more general terms, hemeroby or ‘naturalness’ (Rose 1974;

Norden and Appelquist 2001; Brentrup et al. 2002). Ecological continuity denotes the time

span a forest habitat requires to reach the successional stage of dynamic equilibrium: a

spatial-temporal mosaic of continuously changing patches (‘shifting mosaic’) representing

different successional stages, from young forest regrowth to mature forest (Heinselman

1973; Remmert 1991; Wu and Loucks 1995; Jentsch et al. 2002). Comprising the highest

diversity of mixed successional stages, the dynamic equilibrium supports higher species

1320 Biodivers Conserv (2008) 17:1319–1351

123

http://www.nature.org/pressroom/press/press1657.html

http://www.nature.org/pressroom/press/press1657.html

richness than younger and older successional stages (Connell 1978; Chesson 2000; Jentsch

et al. 2002; Wright 2002; Cunningham and Read 2003; Stokstad 2005); it is therefore the

‘preferred’ state of a forest ecosystem in terms of conservation. Mature forest patches are

the most critical components of this mosaic, since they require the entire time span to fully

develop. The temporal scale of ecological continuity has been suggested to be 200–500(-

1,000) years in temperate forests (Nilsson and Baranowski 1994; Gauslaa and Solhaug

1996; Hornberg et al. 1998), while examples such as the recovery of the Peten after the

Mayan deforestation (Rosenmeier et al. 2002), as well as age estimates based on tree

growth studies (Clark and Clark 2001; Laurance et al. 2004; Brienen 2005) indicate shorter

time spans of 100–500 years for tropical forests. Such time spans equal several human

generations, which has significant impact on conservation efforts, especially as clear-cut

and selective logging affect mature forest patches more than other components of the

mosaic.

Complete inventories of tropical rain forest stands to assess their ecological condition

are time- and resource-consuming and not feasible as routine implementations, although

Rapid Biological Inventories of plants and vertebrates (fm2.fieldmuseum.org/rbi) have

been successfully applied to establish protected areas, such as the Cordillera Azul National

Park in Peru (Alverson et al. 2001; http://www.fieldmuseum.org/cordilleraazul). Well-

studied Costa Rican rain forest stands harbour several thousand plant and vertebrate

species and a much higher number of invertebrates and fungi, such figures being the result

of several decades of study by hundreds of researchers (McDade et al. 1994; Kappelle

et al. 1996). Therefore, indirect methods such as remote sensing and bioindication by

surrogate species to assess the status of rain forest ecosystems have become popular

(Landres et al. 1988; Skole and Tucker 1993; Selva 1994, 1996, Ehrlich 1996; Faith and

Walker 1996a, 1996b; Cranston and Trueman 1997; De Leo and Levin 1997; Flather et al.

1997; Prendergast and Eversham 1997; Caro and O’Doherty 1999; Jonsson and Jonsell

1999; McCune 2000; Norden and Appelquist 2001; Sverdrup-Thygeson 2001; Whitfield

2001; Achard et al. 2002; Rose and Coppins 2002; Zedda 2004). Indicator species respond

to structural key factors that depend on ecological continuity, such as the diversity of

microhabitats for colonization, but also on the temporal component for successful dispersal

and establishment (Norden and Appelquist 2001).

Lichens have been successfully employed as bioindicators of environmental pollution

and ecosystem health in temperate regions (Hawksworth and Rose 1970, 1976; Nimis

1999; Insarov and Schroeter 2002; Nimis et al. 2002), including standardization using

models such as the Index of Atmospheric Purity (IAP; LeBlanc and De Sloover 1970) or

rigorous guidelines such as the German VDI 3957 for the use of lichens as bioindicators

(Bartholmess et al. 2004). Rose (1974) developed the Index of Ecological Continuity

(IEC), a measure of lichen species richness depending on ecological continuity, which was

later modified as ‘Revised’ (RIEC) and ‘New’ (NIEC) Index of Ecological Continuity

(Rose 1976, 1992; Selva 1994, 1996; Zedda 2004). The IEC or RIEC is a proportional

measure of species richness (n) relative to a predetermined ‘pool’ of 30 indicator species,

assuming that a maximum of 20 of these species occur at any given site (RIEC = 100

9 (n)/20). The use of this index and other measures of ecological continuity has been

criticised (Norden and Appelquist 2001), because of several reasons: (1) lack of stan-

dardization for comparison between geographical regions and different forest ecosystems;

(2) insufficient understanding of forest succession and its correlation with species richness;

(3) neglection of individual historical and ecogeographical factors influencing ecological

continuity for a given forest stand; (4) absence of solid ecological data for indicator

species; and (5) lack of quantitative methods of data sampling and analysis. Indicating

Biodivers Conserv (2008) 17:1319–1351 1321

123

http://www.fieldmuseum.org/cordilleraazul

ecological continuity thus requires careful selection of suitable bioindicators, knowledge of

their ecology, and a standardized, quantitative sampling approach. Suitable bioindicators of

ecological continuity increase in species richness and biodiversity with increasing eco-

logical continuity (reaching the dynamic equilibrium state), allow for easy quantitative

sampling, work across different forest ecosystems, and are widespread to be used in

different geographical regions. Also, a universal IEC index would ideally be independent

of ecogeographical constraints, in a similar manner as the IAP index.

Lichens are suitable bioindicators in tropical rain forests, since they form species-rich

communities on tree bark and leaves even in the forest understory, making them easily

accessible for observation and sampling (Sipman 1996; Gradstein et al. 1996; Lucking

2001). Rain forest lichen thalli are generally small (mostly less than 5 cm diam.) and

abundant, allowing for quantitative sampling with limited resources. Also, many species

are widely distributed. Lichens as bioindicators of environmental changes in the tropics

were used by Wolseley and her collaborators in Thailand (Wolseley and Aguirre-Hudson

1991, 1997a, 1997b; Wolseley et al. 1994; Wolseley 2002). In her study of montane

rainforests in Ecuador, Noske (2004) demonstrated the use of epiphytic lichens and bry-

ophytes as bioindicators of anthropogenic disturbances. In a more applied analysis, Peres

(2005) compared the lichen biota of three different forest management types in southern

Mexico and found that sustainable management conserved higher macrolichen diversity.

The dominant group of lichens in tropical rain forests are crustose microlichens, a

highly diverse assemblage that lacks detailed taxonomic and ecological studies, among

them the families Graphidaceae and Thelotremataceae (Wirth and Hale 1963, 1978; Hale

1974, 1978, 1981; Staiger 2002; Frisch et al. 2006). Hale (1974, 1978, 1981), in his

fieldwork in Central America, the Caribbean, and Sri Lanka, was the first to observe that

Thelotremataceae were diverse in undisturbed tropical rain forests but rare or absent in

strongly disturbed forests, as well as secondary and anthropogenic vegetation. He also

noticed that Thelotremataceae often colonize the trunks of large, mature trees, but are less

commonly found on young trees or on thin branches and twigs, observations that were

confirmed in recent studies in Venezuela, Cameroon, Tanzania and Brazil (Komposch and

Hafellner 1999, 2000; Kalb 2004; Frisch et al. 2006, Caceres et al. 2007a, 2007b). In the

present study, we test this hypothesis using a large dataset of 12,215 samples, gathered in

Costa Rica during the TICOLICHEN biodiversity inventory in 2002–2006 (Chaves et al.

2004; Lucking et al. 2004, 2007). The study is divided into two parts: In the first part, the

dataset was analysed with regard to six environmental parameters denoting habitat and

microhabitat preferences of 19 selected crustose corticolous microlichen families,

assuming that suitable indicators of ecological continuity show significant preferences for

closed, undisturbed (to partly disturbed or old growth secondary) forest, shaded micro-

habitats, and mature trees. In the second part, we tested the performance of

Thelotremataceae with respect to predicting forest disturbance levels, using richness

parameters, IEC, and related measures based on species, genus, and morphotype diversity.

Material and methods

We analysed a large dataset of specimens gathered at 115 different sites during the TI-

COLICHEN biodiversity inventory in Costa Rica (Lucking et al. 2004), collected between

2002 and 2006. The total number of specimens was close to 30,000, of which we selected

12,215 samples representing crustose, corticolous lichens belonging to the 19 most dom-

inant lichen families in this group in terms of abundance and genus and species diversity


123

(Table 1). Crustose lichens were selected since the diversity and abundance of foliose and

fruticose macrolichens is comparatively low in tropical dry, moist, and lowland rain forest

habitats, especially in shaded conditions (Sipman and Harris 1989; Komposch and Ha-

fellner 2000). We tested and confirmed this observation by analysing the entire dataset of

nearly 30,000 samples first (data to be published elsewhere).

For each sample, we determined six environmental parameters (Table 2): (1) altitude,

(2) degree of seasonality, (3) vegetation type, (4) disturbance level, (5) substrate nature,

and (6) light exposure. Parameters (1)-(4) were site specific habitat parameters and

determined by consultation of vegetation maps and pertinent literature (Holdridge 1967;

Holdridge et al. 1971; Herrera 1985; Gomez 1986), as well as field observations and data

provided by the Costa Rican MINAE and SINAC (www. sinaccr.net). Parameters (5) and

(6) were sample specific microhabitat parameters and determined in the field using pre-

determined categories (Lucking 1997). Light exposure was estimated in five categories,

supported by semi-quantitative measurements using a fish-eye lens for hemispheric pho-

tographies mounted on a NIKON Coolpix 5400 digital camera.

Data were analysed in two ways: (1) Samples were categorized according to family and

parameter values and compared for significant differences across families using one-way

ANOVA and Scheffe post-hoc comparison. (2) The entire data matrix was subjected to

principal component analysis (PCA based on correlation matrix), to visualize the differ-

ential ordination of samples according to families (and genera of Thelotremataceae) in the

hyperspace defined by the six environmental parameters. All samples were analysed

simultaneously to result in a consistent ordination pattern, but families (and genera of

Thelotremataceae) were displayed individually to allow for easier comparison.

Table 1 Families of crustose,corticolous lichens analysed forthis study, indicating number ofgenera and species

Family Number ofgenera

Number ofspecies

Number ofsamples

Arthoniaceae 6 &50 927

Arthopyreniaceae 3 &10 89

Coenogoniaceae 1 &50 207

Graphidaceae 18 &200 3,275

Lecanoraceae 6 &40 741

Letrouitiaceae 1 &5 109

Monoblastiaceae 4 &35 152

Pertusariaceae 3 &25 626

Physciaceae 12 &50 689

Pilocarpaceae 16 &70 862

Porinaceae 4 &40 624

Pyrenulaceae 6 &65 925

Ramalinaceae 11 &50 680

Roccellaceae 13 &50 533

Strigulaceae 2 &10 64

Teloschistaceae 1 &10 87

Thelenellaceae 2 &10 35

Thelotremataceae 16 &130 1,129

Trypetheliaceae 10 &50 471

Total 135 &950 12,225


123

In a subsequent approach, we analysed the 115 sampling sites for richness parameters of

Thelotremataceae and their correlation with observed disturbance categories. We excluded

25 sites lacking sufficient sampling effort, i.e. that were represented by a low number of

samples relative to the expected lichen species richness in the corresponding site class,

retaining 90 sites in the analysis. For each site, we determined the richness of species,

genera and morphotypes of Thelotremataceae. We defined 24 different morphotypes based

on apothecial and thallus morphology that can be readily determined using a hand lens,

without the aid of a compound microscope or chemical analysis (Fig. 1; Table 3). Modern

revisions of crustose lichens, in particular Graphidaceae and Thelotremataceae (Staiger

2002; Frisch et al. 2006; Lucking et al. 2007), demonstrate that groups of closely related

species share similar morphological traits and differ mainly in anatomical and chemical

characters. Specifically within a monophyletic lineage, the morphotype concept is thus a

good predictor of groups of related species and genera, and a good approximator to genus

and species richness, with the advantage of a significantly reduced effort in time and

resources with respect to identification work.

Since richness parameters are not only dependent on site quality but also site size, we

calculated a set of transformed richness values by dividing the number of species,

genera, and morphotypes, by the log-transformed number of samples for each site (as an

approximator for site size). Log-transformation is appropriate since richness parameters,

especially species richness, correlate with area in logarithmic fashion (Scheiner et al.

2000; Sagar et al. 2003; Scheiner 2003, 2004). In addition, we calculated relative

richness values based on species, genera, and morphotypes, as follows: the 115 sites

Table 2 Definition and coding of six environmental parameters used for the multivariate analysis ofcrustose lichen habitat and microhabitat ecology in Costa Rica

Category Code Category Code

Altitude Disturbance

sea level 1 undisturbed forest 1

0–200 m (lowland) 2 partly disturbed forest (selective logging) 2

200–500 m (submontane) 3 old growth secondary forest ([25 years) 3

500–1,000 m (lower montane) 4 young secondary forest (\25 years) 4

1,000–1,500 m (montane) 5 anthropogenic vegetation (plantations, gardens) 5

1,500–2,000 m (montane) 6 Substrate

2,000–2,500 m (upper montane) 7 trunk ([ 10 cm dbh) base (0–1 m) 1

2,500–3,000 m (upper montane) 8 lower trunk (1–5 m) or stem (\10 cm dbh) base 2

3,000–3,500 m (subparamo) 9 upper trunk ([5 m) or lower stem 3

Seasonality upper stem, branch ([2 cm), liana, stilt root 4

no dry season 1 twig (\2 cm) 5

slight dry season (\1 month) 2 wood (fence posts lacking bark) 6

distinct dry season (1–3 months) 3 Exposure

strong dry season (3–5 months) 4 fully shaded (0–2% diffuse site factor) 1

extended dry season ([5 months) 5 shaded (2–5 % diffuse site factor) 2

Vegetation semi-exposed (5–13% diffuse site factor) 3

Closed forest 1 exposed (13–35 % diffuse site factor) 4

Savanna (mixed forest and grassland) 2 fully exposed (35–100% diffuse site factor) 5

Grassland or shrub (including paramo) 3


123

Fig. 1 Morphotypes in Thelotremataceae (see also Table 3). The cruentodiscoid, gyrotremoid, andrhodostromoid type are pigmented (yellow to red or pink pigments). For further explanation see text


123

Table 3 Morphotypes of corticolous Thelotremataceae (see also Fig. 1)

Morphotype Apothecia and reproductivestructures

Thallus Genera

Chroodiscoid Open with recurved lobules smooth, ± shiny Acanthotrema, Chapsa

Leprocarpoid Open with erect lobules mealy, ± matt Chapsa

Cruentodiscoid Open with erect lobules discpigmented

smooth, ± shiny Chapsa

Gyrotremoid Open with recurved lobules,disc pigmented, withconcentric rings

smooth, ± shiny Gyrotrema

Reimnitzioid Open with erect lobules rough, with crystals Reimnitzia

Glaucescentoid Open with erect lobules rough, with crystals ‘‘Leucodecton’’ (glaucescens)

Leucodectonoid Closed with tiny pore rough, with crystals Leucodecton

Leptotremoid Immersed with small pore rough, with crystals Leptotrema

Myriotremoid Immersed with small pore smooth, ± shiny Myriotrema,‘‘Thelotrema’’glaucopallensgroup

Glaucophaenoid Prominent with wide pore, insection with pale walls

smooth, ± shiny Myriotrema

Annulotremoid Prominent with wide pore,pore with inner ring

smooth, ± shiny Myriotrema, Thelotrema

Thelotremoid Prominent with wide pore,pore with inner ‘‘mouth’’

smooth, ± shiny Thelotrema

Ampliotremoid Prominent with wide pore, insection with black walls

smooth, ± shiny Ampliotrema, Ocellularia

Ocellularioid Prominent with wide pore,pore with ‘‘finger’’(columella), in section withblack walls

smooth, ± shiny Ocellularia

Praestantoid Large and prominent withsmall pore, pore with‘‘finger’’ (columella), insection with black walls

smooth, ± shiny Ocellularia (praestans group)

Rhodostromoid Large and prominent withsmall pore, pore with‘‘finger’’ (columella), insection with black wallsand pigment

smooth, ± shiny Ocellularia (rhodostroma group)

Teniotremoid Immersed with small poreand black margin, porewith ‘‘finger’’ (columella),in section with black walls

smooth, ± shiny ‘‘Thelotrema’’clandestinumgroup

Melanotremoid Prominent with wide poreand black margin, porefilled with broad ‘‘stump’’(columella), in section withblack walls

smooth, ± shiny Melanotrema, Ocellularia,‘‘Thelotrema’’clandestinumgroup

Pallidostegoboloid Prominent with wide pore,pore filled with irregularstructures, in section withpale walls

smooth, ± shiny Stegobolus (wrightii group)


123

were classified according to main environmental parameters (altitude, seasonality) into

six categories: (1) dry (semi-deciduous) forest (0–500 m), (2) moist (evergreen) forest

(500–1,500 m), (3) lowland rain forest (including submontane; 0–500 m), (4) lower

montane rain forest (500–1,000 m), (5) montane rain forest (1,000–2,000 m), and (6)

upper montane rain forest (including subparamo; 2,000–3,500 m). For each category, we

determined the total number of species, genera, and morphotypes. For species, we also

calculated the total number divided by the log-transformed number of sites included in

each category (since total species richness is logarithmically correlated with site num-

ber). Individual site richness values were then divided by the total numbers for each

category.

Based on the original IEC and revised RIEC indices (Rose 1974, 1976; Selva 1994,

1996; Zedda 2004), we calculated IEC indices for Thelotremataceae as follows:

IEC ¼ 100� n/Nmax;

where n = number of species, genera, or morphotypes, per site and Nmax = maximum

expected number of species, genera, or morphotypes, per site. Settings for Nmax were

derived from the data and adjusted with respect to site category and whether relating to

species, genus, or morphotype data (Table 4). The values for IEC range between 0 and

100% and were divided into five classes, using either as an approximated exponential or a

linear scale (Table 4). The highest IEC percentage thereby corresponded to the lowest

disturbance level, and vice versa.

Each of the three richness parameters and the IEC were tested for correlation with

observed disturbance categories for each site (see Table 2) using the Spearman rank

correlation. In addition, disturbance categories predicted from IEC indices based on

Thelotremataceae richness (Table 4) were compared to observed disturbance categories

using Spearman rank correlation.

Statistical analyses were performed using PC-ORD 5.03 (McCune and Mefford 1999;

McCune et al. 2002) and STATISTICATM 6.0.

Table 3 continued

Morphotype Apothecia and reproductivestructures

Thallus Genera

Stegoboloid Prominent with wide pore,pore filled with irregularstructures, in section withblack walls

smooth, ± shiny Stegobolus

Redingerioid Immersed with linear slit, slitfilled with irregularstructures, in section withblack walls

smooth, ± shiny Redingeria, Stegobolus

Isidiotremoid Apothecia lacking, with isidia smooth, ± shiny Myriotrema, Ocellularia

Schizotremoid Apothecia lacking, withschizidia

smooth, ± shiny Stegobolus

Sorediotremoid Apothecia lacking, withsoralia

smooth, ± shiny Myriotrema, Ocellularia


123

Tab

le4

Set

tin

gs

for

Nm

ax

per

site

for

the

calc

ula

tio

no

fth

eIE

Cin

dic

esb

ased

on

Th

elo

trem

atac

eae

and

div

isio

no

fIE

Cv

alu

esin

tofi

ve

dis

turb

ance

clas

ses

Sit

eca

tegory

Dis

turb

ance

cate

gory

IEC

clas

s(e

xponen

tial

)S

pec

ies

Gen

era

Morp

hoty

pes

IEC

clas

s(l

inea

r)S

pec

ies

Gen

era

Morp

hoty

pes

Dry

fore

st(0

–5

00

m)

Nm

ax

–1

07

10

–1

07

10

1[

70

–10

0%

8–

10

5–

78

–1

0[

80

–10

0%

8–

10

6–

78

–1

0

2[

50

–70

%6

–7

46

–7

[6

0–

80

%6

–7

56

–7

3[

30

–50

%4

–5

34

–5

[4

0–

60

%4

–5

3–

44

–5

4[

10

–30

%2

–3

1–

22

–3

[2

0–

40

%2

–3

22

–3

50

–1

0%

0–

10

0–

10

–2

0%

0–

10

–1

0–

1

Mo

ist

fore

st(5

00

–1

,500

m)

Nm

ax

–1

07

10

–1

07

10

1[

70

–10

0%

8–

10

5–

78

–1

0[

80

–10

0%

8–

10

6–

78

–1

0

2[

50

–70

%6

–7

46

–7

[6

0–

80

%6

–7

56

–7

3[

30

–50

%4

–5

34

–5

[4

0–

60

%4

–5

3–

44

–5

4[

10

–30

%2

–3

1–

22

–3

[2

0–

40

%2

–3

22

–3

50

–1

0%

0–

10

0–

10

–2

0%

0–

10

–1

0–

1

Lo

wla

nd

rain

fore

st(0

–5

00

m)

Nm

ax

–2

01

01

2–

20

10

12

1[

70

–10

0%

15

–20

8–

10

9–

12

[8

0–

10

0%

15

–20

8–

10

11

–15

2[

50

–70

%1

1–

14

6–

77

–8

[6

0–

80

%1

1–

14

6–

78

–1

0

3[

30

–50

%7

–1

04

–5

4–

6[

40

–60

%7

–1

04

–5

5–

7

4[

10

–30

%3

–6

2–

32

–3

[2

0–

40

%3

–6

2–

32

–4

50

–1

0%

0–

20

–1

0–

10

–2

0%

0–

20

–1

0–

1

Lo

wer

mo

nta

ne

(50

0–1

,000

m)

Nm

ax

–1

57

10

–1

57

10

1[

70

–10

0%

11

–15

5–

78

–1

0[

80

–10

0%

15

–20

6–

78

–1

0

2[

50

–70

%8

–1

04

6–

7[

60

–8

0%

11

–14

56

–7

3[

30

–50

%5

–7

34

–5

[4

0–

60

%7

–1

03

–4

4–

5

4[

10

–30

%2

–4

1–

22

–3

[2

0–

40

%3

–6

22

–3

50

–1

0%

0–

10

0–

10

–2

0%

0–

20

–1

0–

1


123

Ta

ble

4co

nti

nu

ed

Sit

eca

tegory

Dis

turb

ance

cate

gory

IEC

clas

s(e

xponen

tial

)S

pec

ies

Gen

era

Morp

hoty

pes

IEC

clas

s(l

inea

r)S

pec

ies

Gen

era

Morp

hoty

pes

Mo

nta

ne

(1,0

00–

2,0

00

m)

Nm

ax

–1

57

10

–1

57

10

1[

70

–10

0%

11

–15

5–

78

–1

0[

80

–10

0%

11

–15

6–

78

–1

0

2[

50

–70

%8

–1

04

6–

7[

60

–80

%8

–1

05

6–

7

3[

30

–50

%5

–7

34

–5

[4

0–

60

%5

–7

3–

44

–5

4[

10

–30

%2

–4

1–

22

–3

[2

0–

40

%2

–4

22

–3

50

–1

0%

0–

10

0–

10

–2

0%

0–

10

–1

0–

1

Up

per

mo

nta

ne

(2,0

00–

3,5

00

m)

Nm

ax

–1

05

7–

10

57

1[

70

–10

0%

8–

10

4–

55

–7

[8

0–

10

0%

8–

10

56

–7

2[

50

–70

%6

–7

34

[6

0–

80

%6

–7

45

3[

30

–50

%4

–5

23

[4

0–

60

%4

–5

33

–4

4[

10

–30

%2

–3

11

–2

[2

0–

40

%2

–3

22

50

–1

0%

0–

10

00

–2

0%

0–

10

–1

0–

1

Set

Nm

ax

val

ues

are

bas

edo

na

com

bin

atio

no

fm

axim

um

nu

mb

ero

fsp

ecie

s,g

ener

a,o

rm

orp

ho

typ

esp

ersi

teca

teg

ory

(gam

ma-

div

ersi

ty)

and

per

site

(alp

ha-

div

ersi

ty)

ob

serv

ed.

Fo

rlo

wla

nd

rain

fore

stsi

tes,

thes

eco

rres

po

nd

toN

max

defi

ned

for

tem

per

ate

fore

sts

inth

eo

rig

inal

IEC

(Ro

se1

97

4,

19

76;

Sel

va

19

94,

19

96;

Zed

da

20

04);

for

oth

ersi

tes,

val

ues

for

Nm

ax

are

low

ersi

nce

expec

ted

Thel

otr

emat

acea

ediv

ersi

tyis

low

er


123

Results

Comparison of 19 families comprising tropical crustose lichens

Significant differences across families were found for all six environmental parameters.

Altitude divided the 19 families in four groups (Fig. 2): Group A included Pertusariaceae

Fig. 2 Column plot showing variation of altitude, seasonality, and vegetation categories according to lichenfamily. Groups A, B, C, and D are significantly different based on Scheffe post-hoc comparison. Indicatedare means and standard deviation. Altitude: 1 = sea level, 2 = 0–200 m, 3 = 200–500 m, 4 = 500–1,000 m,5 = 1,000–1,500 m, 6 = 1,500–2,000 m, 7 = 2,000–2,500 m, 8 = 2,500–3,000 m. Seasonality: 1 = no dryseason, 2 = slight dry season, 3 = distinct dry season, 4 = strong dry season, 5 = extended dry season.Vegetation: 1 = closed forest, 2 = savanna


123

with preferential altitude of 1,000–2,000 m (montane), while group B (and transition to C)

comprised Arthopyreniaceae, Coenogoniaceae, Lecanoraceae, Ramalinaceae, and Thele-

nellaceae (preferential altitude 500–1,500 m: lower montane). Graphidaceae, Physciaceae,

Pilocarpaceae, Pyrenulaceae, Teloschistaceae, Thelotremataceae, and Trypetheliaceae,

form a third group C (with transition to D), with preferential altitudes of 200–1,000 m

(submontane to lower montane), and the fourth group D (0–500 m: lowland to submon-

tane) includes Arthoniaceae, Letrouitiaceae, Monoblastiaceae, Porinaceae, Roccellaceae,

and Strigulaceae.

Seasonality showed a similar pattern, with four groups (Fig. 2). Group A (with tran-

sition to B) included three families (Teloschistaceae, Physciaceae, Letrouitiaceae) with

preference for habitats with distinct to extended dry season. Group B (with transition to C)

comprised families with preference for rainforest with distinct dry season: Arthoniaceae,

Lecanoraceae, Monoblastiaceae, Porinaceae, Pyrenulaceae, Roccellaceae, and Trypethe-

liaceae. Group C (with transition to D) unites families with preference for rainforest with

slight (to distinct) dry season, including Arthopyreniaceae, Graphidaceae, Pertusariaceae,

Ramalinaceae, Strigulaceae, and Thelotremataceae, while three families belong to group D

(preference for rainforest with slight dry season): Coenogoniaceae, Pilocarpaceae, and

Thelenellaceae.

Except for Pertusariaceae, Lecanoraceae, and Trypetheliaceae (tendency towards

savanna vegetation), all families show a preference for closed forest vegetation (Fig. 2).

However, significant preferences for different disturbance levels were found (Fig. 3).

Arthoniaceae, Arthopyreniaceae, Coenogoniaceae, Graphidaceae, Lecanoraceae, Monob-

lastiaceae, Pertusariaceae, Physciaceae, Teloschistaceae, Thelenellaceae, and

Trypetheliaceae (group A including transition to B) showed preferences for secondary

forest and secondary vegetation, while five further families (Pilocarpaceae, Pyrenulaceae,

Ramalinaceae, Roccellaceae, Strigulaceae) were most commonly found in old growth

secondary forest. Only three families exhibited preferences for undisturbed to partly dis-

turbed primary and old growth secondary forest: Letrouitiaceae, Porinaceae, and

Thelotremataceae.

Analysis of substrate nature preferences revealed three groups (Fig. 3): Lecanoraceae,

Pertusariaceae, Physciaceae, and Teloschistaceae are more commonly found on trunks and

stems of young trees, as well as branches, twigs, and lianas, while Letrouitiaceae, Porin-

aceae, Pyrenulaceae, Ramalinaceae, Roccellaceae, Strigulaceae, Thelenellaceae, and

Thelotremataceae, are more characteristic of trunks of mature and old trees. The remaining

families (Arthoniaceae, Arthopyreniaceae, Coenogoniaceae, Monoblastiaceae, Pilocarpa-

ceae, and Trypetheliaceae) are intermediate in this respect. Light exposure preferences

across families revealed four groups (Fig. 3). Group A (with transition to B) included

families with preference for exposed microhabitats (Arthopyreniaceae, Lecanoraceae,

Physciaceae, Teloschistaceae, Trypetheliaceae), while families united in group B (with

transition to C) showed preferences for semi-exposed to exposed microhabitats (Arthon-

iaceae, Monoblastiaceae, Pertusariaceae, Thelenellaceae). Group C (with transition to D)

included families characteristic of semi-exposed microhabitats (Pilocarpaceae, Pyrenula-

ceae, Ramalinaceae), while the remaining families of group D preferred shaded to semi-

exposed microhabitats: Coenogoniaceae, Letrouitiaceae, Porinaceae, Roccellaceae, Stri-

gulaceae, and Thelotremataceae.

PCA ordination of the 12,215 specimen samples with respect to six environmental

parameters resulted in 68% cumulative variance explained on the first three axes and 50%

on the first and second axis (first axis eigenvalue = 1.74 or 29% variance, second axis

eigenvalue = 1.28 or 21% variance). The first axis correlated with the parameters light


123

exposure and disturbance level and more weakly so with substrate nature and vegetation

type, while the second axis correlated strongly with altitude and negatively with of

seasonality (Fig. 4). Nine families showed indifference relative to the six measured

environmental parameters, being scattered across the hyperdimensional environmental

Fig. 3 Column plot showing variation of disturbance, substrate, and exposure categories according tolichen family. Groups A, B, C, and D are significantly different based on Scheffe post-hoc comparison.Indicated are means and standard deviation. Disturbance: 1 = undisturbed forest, 2 = partly disturbed forest(selective logging), 3 = old growth secondary forest, 4 = young secondary forest, 5 = anthropogenicvegetation. Substrate: 1 = trunk base, 2 = lower trunk, stem base, 3 = upper trunk or lower stem, 4 = upperstem, branch, liana, stilt root. Exposure: 1 = fully shaded, 2 = shaded, 3 = semi-exposed, 4 = exposed


123

Fig. 4 PCA ordination of 12,215 specimen samples based on six environmental parameters; pointsindicating samples belonging six selected lichen families (all other sample points hidden)


123

space: Arthoniaceae, Arthopyreniaceae (not shown), Graphidaceae (Fig. 4), Monoblasti-

aceae, Pyrenulaceae, Ramalinaceae, Strigulaceae, Thelenellaceae, and Trypetheliaceae

(not shown). Coenogoniaceae (Fig. 4) showed a tendency towards lowland and montane

habitats lacking a distinct to extended dry season. Four families exhibited a shift towards

exposed and disturbed (micro-)habitats, with slightly different behaviour regarding altitude

and seasonality: Lecanoraceae (Fig. 4) and Physciaceae (not shown) were indifferent with

regard to the latter, while Pertusariaceae (not shown) preferred montane and Teloschist-

aceae (not shown) dry habitats. Two families, Pilocarpaceae and Roccellaceae (not shown),

showed slight preferences towards shaded and undisturbed (micro-)habitats, while the

remaining three families exhibited a strong preference towards shaded and undisturbed

(micro-)habitats, with preference of lowland and drier habitats in Letrouitiaceae (Fig. 4),

slight preference of lowland (and drier) habitats in Porinaceae (Fig. 4) and altitudinal and

seasonality indifference in Thelotremataceae (Fig. 4).

Comparison of Thelotremataceae genera

Among Thelotremataceae, with a total of 1,129 samples, significant differences between

genera were found for altitude, degree of seasonality, vegetation type, disturbance level,

and exposure, while all genera agreed in substrate preferences towards the bark of mature

trees, mostly the lower and upper trunk (Fig. 5). Altitude revealed two opposing groups A

(1,000–1,500 m: Thelotrema) and C (0–500 m: Chapsa, Gyrotrema, Leucodecton), with

the remaining genera in between (Acanthotrema, Ampliotrema, Leptotrema, Myriotrema,Ocellularia, Stegobolus). Differences in seasonality were not as distinct but similarly

showed three groups, with Leucodecton showing preferences towards habitats with distinct

to strong dry season and Thelotrema exhibiting tendencies towards habitats with no or a

slight dry season only. All genera prefer closed forest, with only Thelotrema showing a

tendency towards savanna or paramo shrub. Leucodecton was the only genus with pref-

erences towards secondary vegetation, while the remaining genera either preferred

undisturbed to partly disturbed forest (Acanthotrema, Ampliotrema, Gyrotrema, Stegobo-lus) or partly disturbed to old growth secondary forest (Chapsa, Leptotrema, Myriotrema,Ocellularia, Thelotrema). In accordance, slight differences were found with regard to light

exposure, with Leucodecton, Ampliotrema, Myriotrema, and Thelotrema, preferring semi-

exposed and the remaining genera (Acanthotrema, Chapsa, Gyrotrema, Leptotrema,Ocellularia, and Stegobolus) shaded microhabitats.

Nine genera, comprising 80% of all Thelotremataceae samples, show strong preference

for shaded and undisturbed (micro-)habitats, with indifference regarding altitude and

seasonality, thus following the general pattern of the family. These are Acanthotrema,Ampliotrema, Chapsa (Fig. 6), Leptotrema, Myriotrema (not shown), Ocellularia (Fig. 6),

Reimnitzia, and Stegobolus (Fig. 6). Five further genera also show strong preference for

shaded and undisturbed (micro-)habitats, but with distinct preferences towards lowland

habitats in Gyrotrema (Fig. 6), and montane habitats in Fibrillithecis, Melanotrema,Redingeria (not shown), and Thelotrema (Fig. 6). The Thelotrema clandestinum group

shows a montane distribution with indifference regarding exposure and disturbance

(Fig. 6), whereas Leucodecton (Fig. 6) prefers shaded and undisturbed (micro-)habitats in

lowland forests and more exposed and disturbed (micro-)habitats in montane forests. Thus,

only two of the 16 genera are indifferent with respect to exposure and disturbance.

Morphotype data (not shown) gave similar results, with the exception of the cruento-

discoid morphotype tending towards exposed and disturbed lowland (micro-)habitats, the


123

isidiotremoid morphotype showing a montane distribution with indifference regarding

exposure and disturbance (similar to that of the Thelotrema clandestinum group), and the

tenuitremoid morphotype preferring montane shaded and undisturbed (micro-)habitats

(similar to Thelotrema).

Fig. 5 Column plot showing variation of altitude, seasonality, vegetation, disturbance, substrate, andexposure categories according to 10 selected genera of the lichen family Thelotremataceae. Groups A, B,and C are significantly different based on Scheffe post-hoc comparison. Indicated are means standarddeviation. Altitude: 1 = sea level, 2 = 0–200 m, 3 = 200–500 m, 4 = 500–1,000 m, 5 = 1,000–1,500 m,6 = 1,500–2,000 m, 7 = 2,000–2,500 m, 8 = 2,500–3,000 m. Seasonality: 1 = no dry season, 2 = slight dryseason, 3 = distinct dry season, 4 = strong dry season, 5 = extended dry season. Vegetation: 1 = closedforest, 2 = savanna. Disturbance: 1 = undisturbed forest, 2 = partly disturbed forest (selective logging),3 = old growth secondary forest, 4 = young secondary forest, 5 = anthropogenic vegetation. Substrate:1 = trunk base, 2 = lower trunk, stem base, 3 = upper trunk or lower stem, 4 = upper stem, branch, liana,stilt root, 5 = twig. Exposure: 1 = fully shaded, 2 = shaded, 3 = semi-exposed, 4 = exposed


123

Fig. 6 PCA ordination of 12,215 specimen samples based on six environmental parameters; pointsindicating samples belonging to six selected genera of the lichen family Thelotremataceae (all other samplepoints hidden)


123

Thelotremataceae as predictors of disturbance

Analysis of Thelotremataceae richness parameters of the 115 sites resulted in strong and

highly significant (P \ 0.001) negative correlations with observed disturbance categories,

with Spearman correlation coefficients ranging between -0.69 and -0.80 (not shown).

Excluding the 25 sites with insufficient sampling effort, Spearman correlation coefficients

increased to -0.80 to -0.84, with minor differences between individual parameters

(Table 5). Equally strong negative correlations (-0.83 to -0.84) were found for richness

(Fig. 7), richness divided by log-transformed sample number, and IEC (Fig. 7), while

richness divided by total richness per site category, as well as species per genus quotient,

showed slightly weaker correlations (-0.80 to -0.82). In all cases, species, genus, and

morphotype data performed equally well.

Richness parameters and IEC performed differently depending on site category. Very

strong and highly significant negative correlations (-0.88 to -0.99) were observed for dry

forest, lowland rain forest, and montane sites (Table 5), with all parameters performing

similarly well. In dry forest sites, species data performed better than genus and morphotype

data, whereas in lowland rainforest sites it was genus data and in montane sites it was

morphotype data, but the differences were very minor (1–2% points). Upper montane sites

showed a similar pattern but with weaker negative correlations (-0.60 to -0.61). Moist

forest and lower montane sites behaved erratically, with mostly weak negative correlations

lacking statistical significance, except for genus data in the case of lower montane sites

(Table 5).

We observed very strong and highly significant positive correlations between predicted

(based on IEC) and observed disturbance categories for all sites together and for dry,

lowland rain forest, and montane sites, ranging between +0.82 and +1.00 (Tables 5 and 6).

Upper montane sites showed slightly weaker correlations (+0.61 to +0.78), while those for

moist forest and lower montane sites were generally weak, although mostly significant.

Best overall performance was found for species data in combination with exponentially

defined IEC categories, but individual differences were apparent: dry forest sites did not

differ markedly with respect to exponentially or linearly defined categories (except for

genus data), while exponentially defined categories gave stronger correlations for species

(and morphotype) data in dry forest, lowland rain forests, and montane sites, and for genus

data in montane rain forests (Table 5). In contrast, linearly defined categories gave better

results based on genus data overall and in dry, moist, lowland rain forest, lower montane,

and upper montane sites, and based on morphotype data in dry forest, lower montane,

montane, and upper montane sites.

In terms of accuracy with respect to prediction of disturbance categories, species,

genus, and morphotype data performed better in combination with exponentially defined

categories (Fig. 8). Thus, while correlations were partially stronger for genus and mor-

photype data in combination with linearly defined categories, predictive accuracy was

lower. In particular, observed disturbance categories 2, 3, and 4, tended to be underes-

timated as categories 3, 4, and 5, especially for species data (Fig. 8). For species data

and exponentially defined IEC categories, prediction was accurate for disturbance cate-

gories 1, 2, and 5, whereas slight deviations were observed for categories 3 and 4,

respectively (Table 6). In category 3, one sites was wrongly predicted as category 5,

whereas in category 4, almost half of the sites were wrongly predicted as category 5.

Also, one out of 46 sites in category 5 was wrongly predicted as category 2. Except for

this site and another in category 4, inaccurate predictions resulted in underestimations of


123

Tab

le5

Lin

ear

rank

corr

elat

ion

(rS

pearm

an)

bet

wee

nri

chnes

spar

amet

ers,

IEC

index

,an

dpre

dic

ted

dis

turb

ance

cate

gori

esbas

edo

nth

efa

mil

yT

hel

otr

emat

acea

ew

ith

obse

rved

dis

turb

ance

cate

gori

es(s

eeal

soF

ig.

7).

Ab

sen

ceo

fsi

gn

ifica

nt

P-l

evel

sw

ith

stro

ng

corr

elat

ion

sin

low

eran

du

pp

erm

on

tane

rain

fore

star

ed

ue

tolo

wsi

ten

um

ber

s(4

–7

)

Sit

ese

lect

ion

:A

ll(9

0)

Dry

(7)

Mo

ist

(13

)L

ow

lan

d(2

6)

Lo

wer

(6)

Mo

nta

ne

(27

)U

pp

er(1

1)

r Spearm

an

Pr S

pearm

an

Pr S

pearm

an

Pr S

pearm

an

Pr S

pearm

an

Pr S

pearm

an

Pr S

pearm

an

P

Ric

hn

ess

Sp

ecie

s-

0.8

4*

**

-0

.97

**

*-

0.3

9–

-0

.90

**

*-

0.5

9–

-0

.98

**

*-

0.6

1*

Gen

era

-0

.84

**

*-

0.9

6*

**

-0

.39

–-

0.9

1*

**

-0

.81

*-

0.9

7*

**

-0

.61

*

Mo

rph

oty

pes

-0

.84

**

*-

0.9

6*

**

-0

.39

–-

0.9

0*

**

-0

.59

–-

0.9

9*

**

-0

.61

*

Ric

hn

ess

div

ided

by

log

-tra

nsf

orm

edsa

mp

len

um

ber

Sp

ecie

s-

0.8

3*

**

-0

.96

**

*-

0.4

1–

-0

.88

**

*-

0.5

9–

-0

.99

**

*-

0.6

1*

Gen

era

-0

.84

**

*-

0.9

6*

**

-0

.41

–-

0.8

8*

**

-0

.80

–-

0.9

7*

**

-0

.61

*

Mo

rph

oty

pes

-0

.84

**

*-

0.9

6*

**

-0

.41

–-

0.8

8*

**

-0

.59

–-

0.9

9*

**

-0

.61

*

Ric

hn

ess

div

ided

by

tota

lri

chn

ess

for

site

clas

s,in

clu

din

gco

rrec

tio

nfo

rsp

ecie

sb

ylo

g-t

ran

sfo

rmed

site

nu

mb

er

Sp

ecie

s-

0.8

0*

**

-0

.97

**

*-

0.3

9–

-0

.90

**

*-

0.5

9–

-0

.98

**

*-

0.6

1*

Sp

ecie

s(c

orr

ecte

d)

-0

.82

**

*-

0.9

7*

**

-0

.39

–-

0.9

0*

**

-0

.59

–-

0.9

8*

**

-0

.61

*

Gen

era

-0

.81

**

*-

0.9

6*

**

-0

.39

–-

0.9

1*

**

-0

.81

*-

0.9

7*

**

-0

.61

*

Mo

rph

oty

pes

-0

.81

**

*-

0.9

6*

**

-0

.39

–-

0.9

0*

**

-0

.59

–-

0.9

9*

**

-0

.61

*

Sp

ecie

sp

erg

enu

sq

uo

tien

t

Qu

oti

ent

-0

.81

**

*-

0.7

4–

-0

.39

–-

0.8

7*

**

-0

.28

–-

0.9

6*

**

-0

.60

–

IEC

calc

ula

ted

as1

00

9(n

)/N

max

Sp

ecie

s-

0.8

4*

**

-0

.97

**

*-

0.3

9–

-0

.90

**

*-

0.5

9–

-0

.98

**

*-

0.6

1*

Gen

era

-0

.84

**

*-

0.9

6*

**

-0

.39

–-

0.9

1*

**

-0

.81

*-

0.9

7*

**

-0

.61

*

Mo

rph

oty

pes

-0

.84

**

*-

0.9

6*

**

-0

.39

–-

0.9

0*

**

-0

.59

–-

0.9

9*

**

-0

.61

*

Pre

dic

ted

(bas

edon

IEC

)vs.

obse

rved

dis

turb

ance

cate

gory

(exponen

tial

lydefi

ned

cate

gori

es)

Sp

ecie

s+

0.8

7*

**

+1

.00

**

*+

0.5

7*

+0

.93

**

*+

0.4

9–

+0

.92

**

*+

0.7

8*

Gen

era

+0

.82

**

*+

0.9

1*

+0

.39

–+

0.8

3*

**

+0

.81

*+

0.9

7*

**

+0

.61

*

Mo

rph

oty

pes

+0

.85

**

*+

0.9

9*

**

+0

.57

*+

0.9

2*

**

+0

.49

–+

0.9

1*

**

+0

.61

*


123

Ta

ble

5co

nti

nu

ed

Sit

ese

lect

ion

:A

ll(9

0)

Dry

(7)

Mo

ist

(13

)L

ow

lan

d(2

6)

Lo

wer

(6)

Mo

nta

ne

(27

)U

pp

er(1

1)

r Spearm

an

Pr S

pearm

an

Pr S

pearm

an

Pr S

pearm

an

Pr S

pearm

an

Pr S

pearm

an

Pr S

pearm

an

P

Pre

dic

ted

(bas

edon

IEC

)vs.

obse

rved

dis

turb

ance

cate

gory

(lin

earl

ydefi

ned

cate

gori

es)

Sp

ecie

s+

0.8

2*

**

+0

.99

**

*+

0.5

7*

+0

.87

**

*+

0.5

6–

+0

.82

**

*+

0.7

8*

Gen

era

+0

.85

**

*+

0.9

9*

**

+0

.57

*+

0.8

9*

**

+0

.90

*+

0.9

0*

**

+0

.78

*

Mo

rph

oty

pes

+0

.85

**

*+

1.0

0*

**

+0

.57

*+

0.8

8*

**

+0

.72

–+

0.9

2*

**

+0

.78

*

*S

ign

ifica

nt

**

*H

igh

lysi

gn

ifica

nt


123

disturbance categories, i.e. sites were predicted as more strongly disturbed than observed

in the field (Table 6).

Discussion

This study is the first to analyse a large dataset of tropical crustose, corticolous microli-

chens in terms of their habitat and microhabitat preferences. In addition to the large

number of samples analysed, the study covers 19 families of crustose, corticolous, tropical

lichens, with a total of 135 genera and approximately 950 species, corresponding to

Fig. 7 Boxplots showing correlation between species, genus, and morphotype richness and observeddisturbance category, as well as between IEC based on species, genera, and morphotypes and observeddisturbance category. Indicated are means, standard deviation, and min/max


123

Fig. 8 Boxplots showing correlation between predicted category based on species, genera, andmorphotypes and observed disturbance category, using either exponential or linear scaling. Indicated aremeans, standard deviation, and min/max

Table 6 Observed versus predicted disturbance categories derived from IEC based on species data andexponential scaling of transformation of IEC values into five classes

Observed category Number of sites analysed Predicted category

1 2 3 4 5

1. Undisturbed 8 7 1 – – –

2. Partly disturbed 11 – 9 2 – –

3. Old growth secondary 6 – – 4 1 1

4. Young secondary 19 – – 1 9 9

5. Anthropogenic 46 – 1 – – 45

Total 90 7 11 7 10 55


123

roughly 90% of crustose, corticolous lichen species occurring in Costa Rica. The formation

of different lichen communities under different light levels, and their stratification from the

shaded rain forest understory to the exposed canopy (Cornelissen and Ter Steege 1989;

Montfoort and Ek 1990; Lucking 1998, 1999; Komposch and Hafellner 2000, 2003; Holz

and Gradstein 2005) is the principal explanation for changes in lichen diversity and species

composition in partly disturbed and secondary forests and secondary and anthropogenic

vegetation (Lucking 1997). Accordingly, in our PCA ordination of the specimen data, the

two parameters light exposure and disturbance level were highly redundant. Disturbances

such as selective logging that change the canopy structure alter light regimes in the

understory (Chazdon and Fetcher 1984; Smith et al. 1992; Turton 1992; Clark et al. 1996;

Sterck 1997; Sterck et al. 1999), but also reduce tree fall gap dynamics (Hartshorn 1978;

Denslow 1987; McDade et al 1994), which initially leads to higher light levels and

extensive gaps in the understory, but eventually to stands with a more uniformly shaded

understory under a closed canopy composed of demographically more homogeneous,

younger trees. Initial disturbance thus favors lichen communities adapted to higher light

levels, while subsequent phases developing into old growth secondary forest favor com-

munities adapted to low light levels. As a result, lichens of different communities will have

difficulties to coexist, and lichens characteristic of mature tree trunks will disappear.

Abundance, diversity and species composition of such lichens are therefore a good pre-

dictors of ecological continuity, reflecting the recent disturbance history of a given forest

plot.

In the present study, three out of 19 families showed (micro-)habitat preferences that

meet the requirements of potential indicators of ecological continuity: Letrouitiaceae,

Porinaceae, and Thelotremataceae. All other families are either indifferent with respect to

the analysed environmental parameters or show a reverted tendency: Lecanoraceae,

Pertusariaceae, Physciaceae, and Teloschistaceae are more characteristic of exposed, dis-

turbed habitats, a behaviour also observed in other studies (Komposch and Hafellner 2000,

2003; Caceres et al. 2007a). The taxonomic diversity of Letrouitiaceae and Porinaceae is

significantly lower compared to Thelotremataceae (Letrouitiaceae one genus: Letrouitia;

Porinaceae one dominant rain forest genus: Porina), and their preferred altitudinal range is

narrower. Thus, quantitative models working with index values based on genus and species

richness will not perform well. This leaves Thelotremataceae as the best bioindicator of

ecological continuity in tropical rain forests, supporting observations made by Hale (1974,

1978, 1981) and our initial hypothesis. Indeed, our analysis of different richness param-

eters and indices based on Thelotremataceae show strong and highly significant

correlations with disturbance level, provided that data are based on sufficient sampling

effort.

Richness parameters (species, genus, and morphotype number) and IEC correlate

equally well with observed disturbance categories, due to the fact that richness and IEC

are directly proportional as long as observed values for n are not greater than Nmax. The

advantage of the IEC is that Nmax can be adjusted to allow for comparison between

different forest ecotypes, as shown here for dry forest, lowland rain forest, and montane

rain forest habitats. The subjective determination of Nmax is one of the elements of the

IEC that is to be criticised (Norden and Appelquist 2001), but the alternative calculation

of derived richness parameters relativized by total sample, total species, or total site

number, as tested here, did not give improved results and instead even performed worse

than the IEC. A remarkable finding is the strong correlation of species and genus

richness data, based on taxonomic identifications by experienced workers or specialists,

with morphotype data, the latter based on simple morphological assessment. The


123

performance of morphotype data did not differ from that of species data, thus allowing

for developing an index that works with morphotypes rather than taxa, being suitable for

a much wider group of potential users. In addition, rapid assessments in the field are

feasible. Also, morphotype data are not susceptible to taxonomic changes and yet better

predictors of systematic relationships than previously assumed (Staiger 2002; Frisch

et al. 2006). Apart from their ecological traits, Thelotremataceae are suitable for this

approach: with a few exceptions, they are readily separated as a group from most other

crustose lichen families that occur in the same habitats (except for a few Graphidaceae

and rare Gomphillaceae, Gyalectaceae, and Stictidaceae), and they exhibit sufficient

morphological variation.

Deviations from the overall pattern of observed versus predicted disturbance cate-

gories were found in the moist and lower montane rain forest. The moist forest sites

showed rather accurate predictions except for one site, the Leonelo Oviedo Ecological

Reserve on the campus of the University of Costa Rica in the capital San Jose (Di

Stefano et al. 1996; http://www.biologia.ucr.ac.cr/estaciones.html#LO). Structurally and

historically, the site classifies as category 3 (old growth secondary forest), but the

presence of only one Thelotremataceae predicts category 5. This is most probably due to

the fact that the vast majority of the surrounding, heavily populated Central Valley is

completely deforested (Sanchez-Azofeita et al. 2001). Thus, recolonization by Thelotr-

emataceae (and other lichens typical of closed forest) is difficult, if not impossible, even

if the ecological conditions would support their growth. Another case is a pasture at

Volcan Tenorio National Park, a lower montane rain forest site, bordered by living

fences of planted, young trees surrounding pasture grazed by cows. Such landscapes are

common in Costa Rica and exhibit low Thelotremataceae diversity, with 0–1(-2) genera

and species. However, the mentioned site supported no less than nine species in four

genera, predicting a category 2 (partly disturbed primary forest). Volcan Tenorio forms

part of an ecologically unique region characterized by constant cloud cover and drizzling

rain to below 1,000 altitude, which even for exposed vegetation results in conditions that

support unusually high lichen diversity. These outliers are the reason for the low cor-

relations observed for moist and lower montane rain forest and point out two conditions

which relativize the usefulness of richness values and IEC: (1) spatial isolation and

fragmentation which significantly affect dispersal from source sites, and (2) specific

ecological conditions that deviate from overall patterns of observed ecotypes. In such

cases, predictions of disturbance levels might not work, but the combination of observed

structure and IEC will give insight into particular geographical, historical, or ecological

conditions.

Data on Thelotremataceae richness and site disturbance levels are available from a

few other studies, particularly Hale (1974, 1978, 1981) in Panama, Dominica, and Sri

Lanka, but also Komposch and Hafellner (2000, 2003) in Venezuela and Caceres et al.

(2007a, 2007b) in northeastern Brazil. In all cases, Spearman rank correlations show

strong, significant negative correlations between Thelotremataceae species richness and

disturbance category and positive correlations between observed and predicted distur-

bance category, when IEC is calculated for each site applying the same settings as in this

paper (Table 7). However, accuracy of predictions varies, as do maximum species

numbers per site. In Panama and Sri Lanka, Hale (1974) found up to 44 species per site,

twice as many as in the present study for Costa Rican sites. This is in part due to the fact

that Hale extensively sampled canopy species, which may account for more than 50% of

species richness at a given site (based on our observations on Hale’s collected material at

US). Komposch and Hafellner (2000) found 69 species of Thelotremataceae at a single


123

http://www.biologia.ucr.ac.cr/estaciones.html#LO

site in Venezuela, out of a total of 250 lichen species; however, most of these were from

the upper trunk and inner canopy region, and only seven species were sampled at the

trunk base. Extensive canopy sampling was not done in the present study and is also not

feasible for the purpose of monitoring; accordingly, reducing Hale’s numbers by 50% (at

sites with extensive canopy sampling) yields figures similar to those found in the present

study. Also, sample sites were much more narrowly defined in the present study, to

maintain closely adnate sites with different disturbance history separate, which also

accounts for lower per site richness compared to Hale (1974, 1978, 1981). Yet, even

without correction for canopy samples and site definition, prediction of disturbance

categories is rather accurate based on Hale’s data, with only three out of 12 sites

predicting a lower disturbance level than observed.

The numbers reported by Hale (1978) for Dominica range between 1 and 21, very

similar to the present study. However, predictions are not as accurate, especially in

observed category 2 (13 sites), with four sites predicted as category 3 and 5 sites as

category 4 when using the settings given in this paper. These underestimations can be

explained by three reasons. Firstly, several of the sites were only briefly sampled, recov-

ering only part of the entire species richness. Secondly, the studied mountain ranges on

Dominica are rather low, reaching little less than 1,200 m altitude, which causes a mass

elevation effect that lowers altitudinal zones (Hastenrath 1968; Grubb 1971). As a con-

sequence, forest in a range of 800–1,200 m, in Costa Rica considered lower montane to

montane, on Dominica ecologically behaves like an upper montane rain forest (elfin for-

est), which requires a correction of Nmax. For example, a category 2 site at 1,200 m had six

species, which would result in a predicted category 3 if considered a montane site, but

category 2 (as observed) if considered an upper montane site due to the mass elevation

effect. Thirdly, Dominica, as an island ecosystem, was mostly colonized by long-distance

dispersal, which results in lower species richness than expected in similar mainland forest

ecotypes. In northeastern Brazil, ten sites of observed category 2 (partly disturbed) are

consistently underestimated as categories 3, 4, and 5. The Atlantic rain forest, especially its

northeastern part, is highly fragmented into small, partly disturbed rain forest remnants

isolated by large agricultural and urban areas (Whitmore 1990; Silva Filho et al. 1998),

which possibly affects diversity of species dependent on undisturbed primary forest beyond

Table 7 Thelotremataceae species richness and observed versus predicted disturbance categories (appyingsettings as in present paper) based on raw data from studies in Panama, Dominica, Sri Lanka, Venezuela,and northeastern Brazil (Hale 1974, 1978, 1981; Komposch and Hafellner 2000; Caceres et al. 2007a,2007b)

Study Numberof sites

Max. speciesrichness per site

Species richness vs.observed disturbance

Predicted vs.obs. disturbance

Costa Rica (this paper) 90 19 -0.84** +0.87**

Panama (Hale 1974) 12 34CAN -0.81* +0.90**

Dominica (Hale 1978) 28 21CAN -0.81** +0.76**

Sri Lanka (Hale 1981) 15 44CAN -0.75** +0.74**

Venezuela (Komposchand Hafellner 2000)

1 69CAN – –

NE Brazil (Caceres et al. 2007a) 23 15 -0.80** + 0.67**

* = Significant (P \ 0.05), ** = Highly significant (P \ 0.001)CAN = Denotes that extensive upper trunk and canopy sampling took place


123

the observed disturbance level, due to difficulties in dispersal and paucicity of undisturbed

source areas. Also, part of the sites represents the dry Caatinga, to which the Nmax setting

of dry forest (10 species) was applied, but which might have much lower genuine species

richness.

These data support the strong negative correlation between Thelotremataceae species

richness and disturbance level across a wide geographical range in the tropics and across

a wide range of forest ecotypes, but also emphasize that, for accurate prediction of

disturbance levels, both a uniform and standardized sampling protocol and adjustment of

the IEC to forest ecotype and to particular geographical and ecological conditions are

required, taking into account phenomena such as the mass elevation effect and island

biogeography. While this sounds complex, the only parameter that needs to be adjusted

is Nmax, and for this purpose, quantitative ecological data are required for a wider

geographic range.

Based on these findings, we formulate recommendations for the use lichens as bioin-

dicators of ecological continuity in tropical forest ecosystems: (a) The selected organisms

must exhibit a monotonous, negative relationship with disturbance level. For crustose

corticolous lichens (dominant in lowland rain forest), three families meet this requirement:

Letrouitiaceae, Porinaceae, and Thelotremataceae. (b) The selected organisms must have

sufficiently high taxonomic diversity at genus and species level. Among the three afore-

mentioned families, only Thelotremataceae meet this condition. (c) Abundance and

diversity should be high across a wide geographic range and across different forest eco-

types. Thelotremataceae show a wide range regarding altitude and seasonality, but work

best in dry to wet lowland to montane forest ecosystems. For more extreme forest ecotypes

and other ecosystems, other lichen groups are more feasible. (d) For studies of relative

comparison between sites, determination of simple richness values (number of species,

genera, morphotypes) suffice, but comparison with other studies and standardization of

findings is strongly limited. Instead, a standardized, adjustable IEC should be used. (e)

Alternative indices, relativizing richness values against total number of samples, taxa, or

sites, do not perform better, and partly worse, than the IEC. The IEC, a richness measure

relative to total expected site richness, is the simplest and best approach to calculate a

standardized, comparable index. (f) The most critical element of the IEC is the setting of

Nmax, which has to be adjusted to forest ecotype, including a number of ecological

parameters such as precipitation regime and physiognomy, rather than simply altitude

(mass elevation effect). Tree species composition, on the other hand, does not seem to

affect the behaviour of Thelotremataceae richness, as shown by comparison of data from

different parts of the Neotropics and those of Sri Lanka, which all share similar rain forest

physiognomies but different tree species, genera, and even families. (g) Besides species

and genus data, morphotype data are a viable alternative to calculate the IEC. The effort in

time and resources is roughly 5–10% of the effort when identifying species, and direct

assessments in the field are possible, which surpasses the disadvantage of inaccurate

taxonomic treatment, especially as morphotype data perform as well as species data in the

prediction of disturbance levels. (h) A standardized sampling protocol is required. Based

on our experiences in Costa Rica (Lucking et al. 2004, 2007), as well as in southern and

northeastern Brazil (Marcelli 1992; Caceres et al. 2007c), Venezuela (Komposch and

Hafellner 2000) and on published sampling protocols (Gradstein et al. 1996; Sipman

1996), including those using lichens as bioindicators of atmospheric pollution (Kirschbaum

and Wirth 1997; Nimis et al. 2002; Bartholmess et al. 2004), we propose a preliminary

protocol to be tested by further studies (Box 1).


123

Acknowledgements This study was made possible by grants from the NSF to The Field Museum (DEB0206125; PI R. Lucking/DEB 0516116; PI H. T. Lumbsch, CoPI R. Lucking). Most of the Thelotremataceaematerial and other crustose lichens analysed in this study were collected by R. Lucking, J. L. Chaves, and H.J. M. Sipman, but collections and field data were also contributed by A. Aptroot, W. R. Buck, E. Fletes, M.Grube, I. Lopez, E. Navarro, M. P. Nelsen, M. T. Trest, L. Umana, and S. Will-Wolf. We thank INBio andthe Costa Rican MINAE and SINAC for assistance with working and collection permits.

References

Achard F, Eva H, Stibig HJ, Mayaux P, Gallego J, Richards T, Malingreau JP (2002) Determination ofdeforestation rates of the world’s humid tropical forests. Science 297:999–1002

Aide TM, Zimmermann JK, Pascarella JB, Rivera L, Marcano-Vega H (2000) Forest regeneration in achronosequence of tropical abandoned pastures: implications for restoration ecology. Restor Ecol8:328–338

Alverson WS, Rodrıguez LO, Moskovits DK (eds) (2001) Rapid biological inventories 02: Peru: BiaboCordillera Azul. The Field museum, Chicago

Arroyo-Mora JP, Sanchez-Azofeifa GA, Rivard B, Calvo JC, Janzen DH (2005) Dynamics in landscapestructure and composition for the Chorotega region, Costa Rica, from 1960 to 2000. Agric EcosysEnviron 106:27–39

Balmford A, Whitten T (2003) Who should pay for tropical conservation, and how could the costs be met?Oryx 37:238–250

Barrow E, Timmer D, White S, Maginnis S (2002) Forest Landscape Restoration: Building Assets forPeople and Nature – Experience from East Africa. World Conservation Union (IUCN), Cambridge

Bartholmess H, Erhardt W, Frahm JP, Franzen-Reuter I, John V, Kirschbaum U, Turk R, Windisch U, WirthV (2004) Biologische Messverfahren zur Ermittlung und Beurteilung der Wirkung von Luftverun-reinigungen auf Flechten (Bioindikation). Kartierung der Diversitat epiphytischer Flechten alsIndikator fur die Luftgute. VDI 3957, Part 13. Verein Deutscher Ingenieure (VDI), Dusseldorf

Bonnie R, Schwartzman S, Oppenheimer M, Bloomfield J (2000) Counting the costs of deforestation.Science 288:1763–1764

Brentrup F, Kusters J, Lammel J, Kuhlmann H (2002) Life cycle impact assessment of land use based on thehemeroby concept . Int J Life Cycle Assess 7:339–348

Brienen RJW (2005) Tree rings in the tropics: a study on growth and ages of Bolivian rain forest trees.Tekst. Proefschrift, Universiteit Utrecht

Box 1 Suggested sampling protocol to assess disturbance levels of tropical forest sites based on Index ofEcological continuity (IEC) using Thelotremataceae species, genus, or morphotype richness

1. Identify the forest remnant(s) or fragment(s) to be studied.

2. Establish a transect of 500 m length.

3. Select 50 trees each 10 m along the transect.

4. For each tree, (a) either collect a sample of each presumed Thelotremataceae thallus from ground level to2 m height all around the trunk, for subsequent identification to morphotype, genus, or species level, or(b) record the presence of different Thelotremataceae morphotypes as defined here from ground level to2 m height all around the trunk directly in the field, preferably supported by digital images for subsequentconfirmation.

5. For IEC assessment, for each site calculate the IEC as follows:

IEC = 100 9 n/Nmax,

with n = number of species, genera, or morphotypes, detected at a give site and Nmax = maximum numberof species, genera, or morphotypes. Settings for Nmax should be used as in the present paper (Table 4),until further quantitative data for other regions allow for adjustment if required.

6. For prediction of disturbance categories based on IEC, define categories as appropriate; for most regions,the five categories as defined here (Table 4) will work well. Divide IEC into categories using anapproximately exponential scale, with narrow species richness ranges in high disturbance categories andbroad species richness ranges in low disturbance categories.


123

Brook BW, Bradshaw CJA, Koh LP, Sodhi NS (2006) Momentum drives the crash: mass extinction in thetropics. Biotropica 38:302–305

Caceres MES, Lucking R, Rambold G (2007a) Corticolous microlichens in northeastern Brazil: Habitatdifferentiation between coastal Mata Atlantica, Caatinga and Brejos de Altitude. The Bryologist (inpress)

Caceres MES, Lucking R, Rambold G (2007b) Phorophyte specificity and environmental parameters asdeterminants for species composition, richness and area cover in corticolous crustose lichen com-munities in the Atlantic rainforest of northeastern Brazil. Mycological Progress (in press)

Caceres MES, Lucking R, Rambold G (2007c) Efficiency of sampling methods for accurate estimation ofspecies richness: Corticolous microlichens in the Atlantic rainforest of northeastern Brazil. Ecotropica(in press)

Caro TM, O’Doherty G (1999) On the use of surrogate species in conservation biology. Conserv Biol13:805–814

Chaves JL, Lucking R, Sipman HJM, Umana L, Navarro E (2004) A first assessment of the ticolichenbiodiversity inventory in Costa Rica: the genus Dictyonema (Polyporales: Atheliaceae). Bryologist107:242–249

Chazdon RL, Fetcher N (1984) Light environments of tropical forests. In: Medina E, Mooney HA, Vasquez-Yanes C (eds) Physiological Ecology of Plants of the Wet Tropics. W. Junk, The Hague, pp. 27–36

Chesson P (2000) Mechanisms of maintenance of species diversity. Ann Rev Ecol Sys 31:343–366Clark DA, Clark DB (2001) Getting to the canopy: Tree height growth in a neotropical rain forest. Ecology

82:1460–1472Clark DB, Clark DA, Rich PM, Weiss WB, Oberbauer SB (1996) Landscape-scale evalu-ation of understory

light and canopy structure: methods and application in a neotropical low-land rain forest. Can J For Res26:747–757

Connell JH (1978) Diversity in tropical rain forests and coral reefs. Science 199:1302–1310Cornelissen JHC, Ter Steege H (1989) Distribution and ecology of epiphytic bryophytes and lichens in dry

evergreen forest of Guyana. J Trop Ecol 5:131–150Cranston PS, Trueman JWH (1997) ‘Indicator’ organism groups in invertebrate biodiversity assessment.

Mem Mus Vic 562:267–274Cunningham S, Read J (2003) Comparison of temperate and tropical rainforest tree species: growth

responses to temperature. J Biogeogr 30:143–153Curran LM, Caniago I, Paoli GD, Astiani D, Kusneti M, Leighton M, Nirarita CE, Haeruman H (1999)

Impact of El Nino and logging on canopy tree recruitment in Borneo. Science 286:2184–2188Dalton R (2006) Biodiversity: Cashing in on the rich coast. Nature 442:567–569DeLeo GA, Levin S (1997) The multifaceted aspects of ecosystem integrity. Conserv Ecol 1:3Defries RS, Houghton RA, Hansen MC, Field CB, Skole D, Townshend J (2002) Carbon emissions from

tropical deforestation and regrowth based on satellite observations for the 1980s and 90s. Proc NatlAcad Sci USA 99:14256–14261

Denslow JS (1987) Tropical rainforest gaps and tree species diversity. Ann Rev Ecol Sys 18:431–451Di Stefano JF, Ielsen VN, Hoomans J, Fournier LA (1996) Regeneracion de la vegetacion arborea en una

pequena reserva forestal urbana del premontano humedo, Costa Rica. Rev Biol Trop 44:575–580Ehrlich PR (1996) Conservation in temperate forests: what do we need to know and do? For Ecol Manage

851:9–19Ehrlich PR, Ehrlich AH (1981) Extinction: the causes and consequences of the dissappearance of species.

Random House, New YorkFaith DP, Walker PA (1996a) Environmental diversity: on the best-possible use of surrogate data for

assessing the relative biodiversity of sets of areas. Biodivers Conserv 54:399–415Faith DP, Walker PA (1996b) How do indicator groups provide information about the relative biodiversity

of different sets of areas?: on hotspots, complementarity and pattern-based approaches. Biodivers Lett31:18–25

FAO (1981) Los Recursos Forestales de la America Tropical. Proyecto de Evaluacion de los RecursosForestales Tropicales. FAO, Rome

Fearnside PM (2000) Global warming and tropical land-use change: Greenhouse gas emissions from bio-mass burning, decomposition and soils in forest conversion, shifting cultivation and secondaryvegetation. Clim Change 46:115–145

Fearnside PM (2001) Saving tropical forests as a global warming countermeasure: An issue that divides theenvironmental movement. Ecol Econ 39:167–184

Fearnside PM, Laurance WF (2004) Tropical deforestation and greenhouse gas emissions. Ecol Appl14:982–986


123

Flather CH, Wilson KR, Dean DJ, McComb WC (1997) Identifying gaps in conservation networks: Ofindicators and uncertainty in geographic-based analyses. Ecol Appl 72:531–542

Floren A, Linsenmair KE (2005) The importance of primary tropical rain forest for species diversity: aninvestigation using arboreal ants as an example. Ecosystems 8:559–567

Frisch A, Kalb K, Grube M (2006) Contributions towards a new systematics of the lichen family The-lotremataceae. Bibl Lichenol 92:1–556

Gauslaa Y, Solhaug K-A (1996) Differences in the susceptibility to light stress between epiphytic lichens ofancient and young boreal forest stands. Funct Ecol 10:344–354

Gomez LD (1986) Vegetacion de Costa Rica. In: Gomez LD (ed) Vegetacion y Clima de Costa Rica, vol 1.Editorial Universidad Estatal a Distancia, San Jose (Costa Rica)

Gradstein SR, Hietz P, Lucking R, Lucking A, Sipman HJM, Vester HFM, Wolf JHD, Gardette E (1996)How to sample the epiphytic diversity of tropical rain forests. Ecotropica 2:59–72

Grubb PJ (1971) Interpretation of the ‘‘Massenerhebung’’ effect on tropical mountains. Nature 229:44–45Hale ME Jr (1974) Morden-Smithsonian expedition to Dominica: the lichens (Thelotremataceae). Smith

Contrib Bot 16:1–46Hale ME Jr (1978) A revision of the lichen family Thelotremataceae in Panama. Smith Contrib Bot 38:1–60Hale ME Jr (1981) A revision of the lichen family Thelotremataceae in Sri Lanka. Bull Br Mus 8:227–332Hartshorn GS (1978) Treefalls and tropical forest dynamics. In: Tomlinson PB, Zimmerman MH (eds)

Tropical Trees as Living Systems. Cambridge University Press, Cambridge, UK, pp 617–638Hastenrath S (1968) Certain aspects of the three-dimensional distribution of climate and vegetation belts in

the mountains of Central America and southern Mexico. In: Troll C (ed) Colloquim Goegraphicum,Band 9. Geoecology of the Mountainous Regions in the Tropical Americas. Proceedings of theUNESCO Mexico Symposium 1966, pp 122–130

Hawksworth D, Rose F (1970) Qualitative scale for estimating sulphur dioxide air pollution in England andWales using epiphytic lichens. Nature 227:145–148

Hawksworth DL, Rose F (1976) Lichens as Pollution Monitors. Edward Arnold, LondonHeinselman ML (1973) Fire in the virgin forests of the Boundary Waters Canoe Area, Minnesota. Quat Res

3:329–382Herrera W (1985) Clima de Costa Rica. In: Gomez LD (ed) Vegetacion y Clima de Costa Rica, vol 2.

Editorial Universidad Estatal a Distancia, San Jose, Costa RicaHoldridge LR (1967) Life Zone Ecology. Tropical Science Center, San Jose (Costa Rica)Holdridge LR, Grenke WC, Hatheway WH, Liang T, Tosi JA Jr (1971) Forest environments in tropical life

zones: a pilot study. Oxford, Pergamon PressHolz I, Gradstein SR (2005) Cryptogamic epiphytes in primary and recovering upper montane oak forests of

Costa Rica – species richness, community composition and ecology. Plant Ecol 178:89–109Hornberg GO, Zackrisson U, Segerstrom U, Svensson BW, Ohlson M and Bradshaw RHW (1998) Boreal

swamp forests biodiversity ‘hotspots’ in an impoverished forest landscape. Bioscience 48:795–802Insarov GE, Schroeter B (2002) Lichen monitoring and climate change. In: Nimis PL, Scheidegger C,

Wolseley PA (eds) Monitoring with Lichens – Monitoring Lichens, NATO Science Series, IV, vol 7.Kluwer, Dordrecht, pp 183–201

ITTO (2002) Guidelines for the restoration, management and rehabilitation of degraded and secondarytropical forest. International Tropical Timber Organization, Yokohama

Jablonski D, Roy K, Valentine JW (2006) Out of the tropics: evolutionary dynamics of the latitudinaldiversity gradient. Science 314:102–106

Jentsch A, Beierkuhnlein C, White S (2002) Scale, the dynamic stability of forest ecosystems, and thepersistence of biodiversity. Silva fenn 36:393–400

Jonsson B-G, Jonsell M (1999) Exploring potential biodiversity indicators in boreal forests. BiodiversConserv 8:1417–1433

Kalb K (2004) New or otherwise interesting lichens II. Bibl Lichenol 88:301–329Kappelle M, Geuze T, Leal ME, Cleff AM (1996) Successional age and forest structure in a Costa Rican

upper montane Quercus forest. J Trop Ecol 12:681—698Komposch H, Hafellner J (1999) List of lichenized fungi so far observed in the tropical lowland rain forest

plot Surumoni (Venezuela, Estado Amazonas). Fritschiana 19:1–10Komposch H, Hafellner J (2000) Diversity and vertical distribution of lichens in a Venezuelan tropical

lowland rain forest. Selbyana 21:11–24Komposch H, Hafellner J (2003) Species composition of lichen dominated corticolous communities: a

lowland rain forest canopy compared to an adjacent shrubland in Venezuela. Bibl Lichenol 86:351–367Kirschbaum U, Wirth V (1997) Flechten erkennen, Luftgute bestimmen. Ulmer, StuttgartKremen C, Niles JO, Dalton MG, Daily GC, Ehrlich PR, Fay JP, Grewal D, Guillery RRP (2000) Economic

incentives for rain forest conservation across scales. Science 288:1828–1832


123

Lamb D, Erskine PD, Parrotta JA (2005) Restoration of degraded tropical forest landscapes. Science310:1628–1632

Landres P, Verner BJ, Thomas JW (1988) Ecological uses of vertebrate indicator species: a critique.Conserv Biol 2:316–328

Laurance WF, Nascimento HEM, Laurance SG, Condit R, D’Angelo S, Andrade A (2004) Inferred lon-gevity of Amazonian rainforest trees based on a long-term demographic study. For Ecol Manage190:131–143

Laurance WF, Delamonica P, Laurance SG, Vasconcelos HL, Lovejoy TE (2000) Rainforest fragmentationkills big trees. Nature 404:836

Lawton RO, Nair US, Pielke RA, Welch RM (2001) Climatic impact of tropical lowland deforestation onnearby montane cloud forests. Science 294:584–587

LeBlanc F, De Sloover J (1970) Relation between industrialization and the distribution and growth ofepiphytic lichens and mosses in Montreal. Can J Bot 48:1485–1496

Lewin R (1986) Mass extinctions select different victims. Science 231:219–220Lucking R (1997) The use of foliicolous lichens as bioindicators in the tropics, with special reference to the

microclimate. Abstr Bot 21(1):99–116Lucking R (1998) Ecology of foliicolous lichens at the ‘Botarrama’ trail (Costa Rica), a neotropical rain-

forest site. Part II. Patterns of diversity and area cover, and their dependence on microclimate andphorophyte species. Ecotropica 4:1–24

Lucking R (1999) Ecology of foliicolous lichens at the ‘Botarrama’ trail (Costa Rica), a neotropical rain-forest. IV. Species associations, their salient features and their dependence on environmental variables.Lichenologist 31:269–289

Lucking R (2001) Lichens on leaves in tropical rainforests: life in. a permanently ephemerous environment.Diss Bot 346:41–77

Lucking R, Sipman HJM, Umana-Tenorio L (2004). TICOLICHEN—the Costa Rican lichen biodiversityinventory as a model for lichen inventories in the tropics. In: Randlane T, Saag A (eds) The 5th IALSymposium. Lichens in Focus. Tartu University Press, Tartu, 32 pp

Lucking R, Chaves JL, Sipman HJM, Umana L, Aptroot A (2007) A first assessment of the Ticolichenbiodiversity inventory in Costa Rica: The genus Graphis (Ascomycota: Ostropales: Graphidaceae).Fieldiana (in press).

Malhi Y, Grace J (2000) Tropical forests and atmospheric carbon dioxide. Trends Ecol Evol 15:332–337Marcelli MP (1992) Ecologia liquenica nos manguezais do sul-sudeste Brasileiro. Bibl Lichenol 47(i–vii):1–

288Margules CR, Pressey RL (2000) Systematic conservation planning. Nature 405:243–253Martin PH, Sherman RE, Fahey TJ (2004) Forty years of tropical forest recovery from agriculture: structure

and floristics of secondary and old-growth riparian forests in the Dominican Republic. Biotropica36:297–317

McCune B (2000) Lichen communities as indicators of forest health. Bryologist 103:353–356McCune B, Grace JB, Urban DL (2002) Analysis of ecological communities. MjM Software, Gleneden

Beach, OregonMcCune B, Mefford MJ (1999) PC-ORD. Multivariate Analysis of Ecological Data, version 4.0. MjM

Software, Gleneden Beach, Oregon, USAMcDade LA, Bawa KS, Hespenheide HA, Hartshorn GS (eds) (1994) La Selva: ecology and natural history

of a neotropical rain forest. University of Chicago Press, ChicagoMontfoort D, Ek R (1990) Vertical distribution and ecology of epiphytic bryophytes and lichens in a

lowland rainforest in French Guiana. Herbarium, Institute of Systematic Botany, UtrechtMyers N (1991) Trees by the billions: a blueprint for ecology. Int Wildl 21:12–15Nilsson S-G, Baranowski R (1994) Indikatorer pa jattetradskontinuitet—Svenska forekomster av knappare

som ar beroende av grova, levande trad. Entomol Tidskr 115:81–97Nimis PL (1999) Linee guida per la bioindicazione degli effetti dell’inquinamento tramite la biodiversita dei

licheni epifiti. In: Piccini C, Salvati S (eds) Atti Workshop Biomonitoraggio Qualita dell’Aria sulterritorio Nazionale, pp 267–277. ANPA, Ser. Atti, 2

Nimis PL, Scheidegger C, Wolseley PA (eds) (2002) Monitoring with Lichens—Monitoring Lichens.NATO Science Series. IV. Earth and Environmental Sciences, 7. Kluwer Academic Publishers,Dordrecht, The Netherlands

Norden B, Appelquist T (2001) Conceptual problems of Ecological Continuity and its bioindicators. Bio-divers Conserv 10:779–791

Noske NM (2004) Effekte anthropogener Storung auf die Diversitat kryptogamischer Epiphyten (Flechten,Moose) in einem Bergregenwald in Sudecuador. Ph.D. Thesis, Mathematisch-NaturwissenschaftlicheFakultat, Georg-August-Universitat zu Gottingen.


123

Pearce D (2001) How valuable are the tropical forests? Demonstrating and capturing economic value as ameans of addressing the causes of deforestation. Conseil d’Analyse Economique, Seminaire Economiede L’Environnement et du Developpement Durable, Paris

Peres REP (2005) Impacto del Manejo Forestal en los Macrolıquenes Cortıcolas de Pinus patula (Schl. &Cham) an la Sierra de Juarez, Oaxaca. PhD Thesis, Universidad Autonoma del Estado de Morelos,Cuernavaca, Mexico

Phillips OL, Hall P, Gentry AH, Sawyer SA, Vazquez R (1994) Dynamics and species richness of tropicalrain forests. Proc Natl Acad Sci USA 91: 2805–2809

Prendergast JR, Eversham BC (1997) Species richness covariance in higher taxa: empirical tests of thebiodiversity indicator concept. Ecography 20:210–216

Raup DM (1986) Biological extinction in earth history. Science 231:1528–1533Remmert H (1991) The mosaic-cycle concept of ecosystems—an overview. In: Remmert H (ed) The

Mosaic-cycle Concept of Ecosystems. Springer, Berlin, pp 1–21Rose F (1974) The epiphytes of oak. In: Morris MG, Perring FH (eds) The British oak: its history and natural

history. Classey Faringdon, UK, pp 250–273Rose F (1976) Lichenological indicators of age and ecological continuity in Woodlands. In: Brown DH,

Hawksworth DL, Bailey RH (eds) Lichenology: progress and problems. Academic Press, London, pp279–307

Rose F (1992) Temperate forest management: its effects on bryophyte and lichen floras and habitats. In:Bates JW, Farmer AM (eds) Bryophytes and lichens in a changing enviroment. Oxford ScientificPublications, Oxford, pp 211–233

Rose F, Coppins S (2002) Site assessment of epiphytic habitats using lichen indices. In: Nimis PL et al (eds)Monitoring with lichens – Monitoring lichens NATO science series, IV, vol 7. Kluwer, Dordrecht, pp434–348

Rosenmeier MF, Hodell DA, Brenner M, Curtis JH, Martin JB, Anselmetti FS, Ariztegui D, Guilderson TP(2002) Influence of vegetation change on watershed hydrology: implications for paleoclimatic inter-pretation of lacustrine d 18 O records. J Paleolimnol 27:117–131

Sagar R, Raghubanshi AS, Singh JS (2003) Asymptotic models of species-area curve for measuringdiversity of dry tropical forest tree species. Curr Sci 84:1555–1560

Sanchez-Azofeifa GA, Harris RC, Skole DL (2001) Deforestation in Costa Rica: A quantitative analysisusing remote sensing imagery. Biotropica 33:378–384

Scheiner SM (2003) Six types of species-area curves. Glob Ecol Biogeogr 12:441–447Scheiner SM (2004) A melange of curves – further dialogue about species-area relationships. Glob Ecol

Biogeogr 13:479–484Scheiner SM, Cox SB, Willig M, Mittelbach GG, Osenberg C, Kaspari M (2000) Species richness, species-

area curves and Simpson’s paradox. Evol Ecol Res 2: 791–802Selva SB (1994) Lichen diversity and stand continuity in the northern hardwoods and spruce-fir forests of

northern New England and western New Brunswick. Bryologist 97:424–429Selva SB (1996) Using lichens to assess ecological continuity in northeastern forests. In: Byrd M (ed)

Eastern old-growth forests – prospects for rediscovery and recovery. Island Press,Washington, DC, pp35–48

Shukla J, Shukla J, Nobre C, Sellers P (1990) Amazon deforestation and climate change. J Sci 247:1322–1325

Silva Filho AA, Toniolo ER, Gabınio M, Oliveira SFS (1998) Mapeamento da cobertura florestal nativalenhosa do estado de Pernambuco (Documento de Campo FAO no. 17). PNDU, FAO, IBAMA,Governo de Pernambuco

Sipman HJM (1996) Corticolous lichens. In: Gradstein SR, Hietz P, Lucking R, Lucking A, Sipman HJM,Vester HFM, Wolf JHD, Gardette E (eds) How to sample the epiphytic diversity of tropical rainforests, pp 66–67. Ecotropica 2: 59–72

Sipman HJM, Harris RC (1989) Lichens. In Lieth H, Werger MJA (eds) Tropical rain forest ecosystemsbiogeographical and ecological studies (Ecosystems of the World 14B). Elsevier, Amsterdam, pp 303–309

Skole D, Tucker C (1993) Tropical deforestation and habitat fragmentation in the Amazon: satellite datafrom 1978 to 1988. Science 260:1905–1910

Smith AP, Hogan KP, Idol JR (1992) Spatial and temporal patterns of light and canopy structure in lowlandtropical moist forest. Biotropica 24:503–511

Staiger B (2002) Die Flechtenfamilie Graphidaceae. Studien in Richtung einer naturlicheren Gliederung.Bibl Lichenol 85:1–526


123

Sterck FJ (1997) Trees and Light: Tree Development and Morphology in relation to light availability in atropical rain forest in French Guiana. PhD Thesis, Wageningen Agricultural University, Ponser &Looijen, Wageningen

Sterck FJ, Clark DB, Clark DA, Bongers F (1999) Light fluctuations, crown traits, and response delays fortree saplings in a Costa Rican lowland rain forest. J Trop Ecol 5:83–95

Still CJ, Foster PN, Schneider SH (1999) Simulating the effect of climate change on tropical montane cloudforests. Nature 398:608–610

Stokstad E (2005) Learning to adapt. Science 309:688–690Sverdrup-Thygeson A (2001) Can ‘continuity indicator species’ predict species richness or red-listed species

of saproxylic beetles? Biodivers Conserv 10:815–832Terbourgh J (1992) Maintenance of diversity in tropical forests. Biotropica 24:283–292Turton SM (1992) Understory light environments in a northeast Australian rain forest before and after a

tropical cyclone. J Trop Ecol 8:241–252Uhl C, Buschbacher R, Serrao EAS (1988) Abandoned pastures in Eastern Amazonia. I. Patterns of plant

succession. J Ecol 6:663–681Whitfield J (2001) Vital signs. Nature 411:989–990Whitmore TC (1990) An introduction to tropical rainforests. Clarendon Press, OxfordWilson EO (1984) Biophilia. Harvard University Press, CambridgeWilson EO (1999) The diversity of life. W. W. Norton & Co., New YorkWilson EO (2002) The future of life. Knopf, New YorkWirth M, Hale ME Jr (1963) The lichen family Graphidaceae in Mexico. Contrib US Natl Herb 36:63–119Wirth M, Hale ME Jr (1978) Morden-Smithsonian expedition to Dominica: the lichens (Graphidaceae).

Smith Contrib Bot 40:1–64Wolseley PA (2002) Using corticolous lichens of tropical forests to assess environmental changes. In: Nimis

PL, Scheidegger C, Wolseley PA (eds) Monitoring with Lichens – Monitoring Lichens, Nato ScienceSeries IV Earth and Environmental Sciences. Kluwer Academic Publishers, Dordrecht, pp 1–2

Wolseley PA, Aguirre-Hudson B (1991) Lichens as indicators of environmental change in the tropicalforests of Thailand. Glob Ecol Biogeogr Lett 1:170–175

Wolseley PA, Aguirre-Hudson B (1997a) The ecology and distribution of lichens in tropical deciduous andevergreen forests of northern Thailand. J Biogeogr 24:327–343

Wolseley PA, Aguirre-Hudson B (1997b) Fire in tropical dry forests: corticolous lichens as indicators ofrecent ecological changes in Thailand. J Biogeogr 24:345–362

Wolseley PA, Moncrieff C, Aguirre-Hudson B (1994) Lichens as indicators of environ-mental stability andchange in the tropical forests of Thailand. Glob Ecol Biogeogr Lett 4:116–123

Wright SJ (2002) Plant diversity in tropical forests: a review of mechanisms of species coexistence. Oec-ologia 130:1–14

Wright SJ, Muller-Landau HC (2006) The future of tropical forest species. Biotropica 38:287–301Wu J, Loucks OL (1995) From balance of nature to hierarchical patch dynamics: a paradigm shift in

ecology. Q Rev Biol 70:439–466Zedda L (2002) The epiphytic lichens on Quercus in Sardinia (Italy) and their value as ecological indicators.

Englera 24:1–468


123

When family matters: an analysis of Thelotremataceae (Lichenized Ascomycota: Ostropales) as...

Documents

Transcript of When family matters: an analysis of Thelotremataceae (Lichenized Ascomycota: Ostropales) as...