estimating regional extinction probabilities and reduction ...15299/datastrea… · keywords:...

415For. Snow Landsc. Res. 75, 3: 415–433 (2000)

Estimating regional extinction probabilities and reduction

in populations of rare epiphytic lichen-forming fungi

Christoph Scheidegger, Silvia Stofer, Michael Dietrich, Urs Groner, Christine Keller and Irene Roth

WSL Swiss Federal Research Institute, Zürcherstrasse 111, CH-8903 Birmensdorf, [email protected]; [email protected]; [email protected]; [email protected];[email protected]; [email protected]

Abstract

World-wide and regional Red List categories have recently been drawn up using quantitative criteria which describe the past, present and expected future viability of populations. A past reduction in national populations has probably been the most frequently used criterion in globaland regional Red Lists but detailed historical distribution data is lacking for many species, e.g.inconspicuous cryptogams.The projected or suspected decline in populations can then be a valuablealternative in the process of at-risk designation. We describe a method for assessing the futuredecline of a national population according to Red List criteria based on the size structure of local,independent populations. This method uses a spatially implicit, individual-based model of theextinction process of dispersal limited local populations of epiphytic lichen species such as L obaria

pulmonaria.A small tree harvest considerably increases the vulnerability of small populations anda harvest intensity considered sustainable in terms of tree harvesting inevitably leads to the extir-pation of even large L . pulmonaria populations. Estimating future decline in national populationsidentified 12 vulnerable and 1 endangered species. For another 81 species,A3 confirmed the threatcategory assigned by other Red List criteria.

Keywords: epiphytic lichens, L obaria pulmonaria, IUCN Red List criteria, small population biology, individual-based models

1 Introduction

World-wide and regional Red List categories have recently been drawn up using quantitativecriteria which describe the past, present and expected future viability of populations (IUCN1994). Red Lists have up to now evaluated the global populations of animals (BAILLIE andGROOMBRIDGE 1996) and plants (WALTER and G ILLETT 1997).A recent development, how-ever, allows the Red List criteria to be adapted to regional and national scales (GÄRDENFORS

1996; GÄRDENFORS et al. 1999). A past reduction in national populations has probably beenthe most frequently used criterion in global and regional Red Lists but recently the projectedor suspected decline in populations has also been proposed as a criterion (A3) in the processof at-risk designation (IUCN 2001).

Unfortunately, detailed historical distribution data is lacking for many species, e.g. incon-spicuous cryptogams. As long as their occurrence is correlated with characteristic habitattypes, an analysis of the past habitat distribution and quality may be used as a surrogate ofthe past population decline. In taxa such as epiphytic lichens, which depend on specific micro-habitats and structural elements (e.g. bark crevices) rather than on habitats such as forest associations, a reconstruction of the past area of occurrence and population size of currentlyrare and endangered species is often not possible. Furthermore, enigmatic species, such asMaronea constans and Usnea longissima, are critically endangered today despite the wide distribution of presumably suitable habitats and microhabitats. For these species, the only wayof estimating the future decline is by considering their present population structure.

416 Christoph Scheidegger et al.

In epiphytic lichens, two typical features make it easier to estimate the regional extinctionprobability and the extent of a future population reduction. First, rare epiphytic lichens areoften clustered in a habitat. It is not uncommon to find a tree densely covered with a rarelichen species, and neighbouring trees of seemingly the same habitat quality without thislichen. Often the lichen species lives on such a tree until the tree’s death or harvest, whichleads to the concerted death of all the individuals growing on it. The survival of all lichenindividuals on one such tree is therefore highly interconnected. Because the single mostimportant cause of death for epiphytic lichens is the death of their phorophyte host, all con-specific thalli inhabiting that phorophyte can,for practical purposes,be considered a functionalindividual (SCHEIDEGGER and GOWARD in print). This approach makes population studiesof epiphytic lichens relatively easy because the mortality of the lichen functional individualcan then be related to the mortality of the phorophyte.

The second feature which makes it easier to estimate regional extinction is that the localrarity of many epiphytic lichens cannot usually be explained by the small size or the low quality of the habitat. The long-term effects of large-scale catastrophic events on the lichenflora provide increasing evidence that low rates of dispersal and establishment limit the localoccurrence and population size. This applies especially to epiphytic lichens. Although someepiphytic species have a high dispersal potential which allows a rapid recolonisation of habitatse.g.after a fire (GARTY 1990;GARTY 1992;GORSHKOV et al. 1995;MISTRY 1998),many speciesin need of conservation are very sensitive to extended disturbance such as forest fire andclearcut logging (ROSE 1976; LESICA et al. 1991; ROSE 1992; GOWARD 1994; HAUGAN et al.1994). Such a species group, often referred to as old-growth dependent epiphytic lichens, areespecially likely to be threatened and a high percentage of this group is dispersal-limited undersuboptimal ecological conditions (GOWARD 1995; SCHEIDEGGER 1995). For this group of dispersal limited species especially, low populations may face an increased risk of becomingextinct due to stochastic processes rather than to habitat quality (G ILPIN 1987; GOODMAN

1987).The aim of this study was to describe a method for assessing the future decline of a national

population according to Red List criteria. This method uses a spatially implicit, individual-based model of the extinction process of dispersal limited local populations of epiphytic lichenspecies such as L obaria pulmonaria . Further, the study aimed to estimate the influence ofthree different tree harvest scenario on the Red List categories of the dispersal-limited,epiphytic lichen species of Switzerland.

2 Material and methods

2.1 Description of the survey

An intensive inventory of the epiphytic lichens of Switzerland was carried out from 1995 to1999. The sampling included a representative survey of all lichen species on 826 long-termecological observation plots located on the intersection points of the 1 x 1 km grid of the Swisscoordinate system.Additionally, an intensive mapping in 20 x 20 km squares with special ref-erence to rare and potentially threatened taxa has been carried out (for details, see D IETRICH

et al., this volume).The size of local populations was assessed for 160 pre-selected taxa whichwere considered potentially rare at the beginning of the study (Appendix A). Figure 1 showssome of the studied species. On each locality for the particular species selected the numberof trees was assessed and grouped into three size classes: one tree (size class 1), two to fivetrees (size class 2), and more than five trees (size class 3).The total local populations belongingto each size class were then calculated.

417For. Snow Landsc. Res. 75, 3 (2000)

Fig. 1. L obaria pulmonaria (a), Usnea longissima

(b), Sphaerophorus melanocarpus (c), Mycoblastus

sanguinarius (d), Heterodermia speciosa (e).

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2.2 Simulation of small population survival

For competitive species which usually colonise mature trees and live there until its harvest ordeath, an individual-based, spatially implicit stochastic simulation model was developed forL obaria pulmonaria in an upper montane mixed forest and used to estimate the local extinction probability for small populations (SCHEIDEGGER et al. 1998). The simulation (500runs) was carried out with Vortex, a stochastic simulation software of the extinction process(LACY 1993;LACY et al.1995).The stand contained 15 individuals of the preferred tree species,A cer pseudoplatanus. It is the limit set by the software Vortex for the maximum number ofpopulations which could be included in the metapopulation studied. The simulation startedwith a normal age distribution of the trees and the maximum tree age was set at 200 years(SCHEIDEGGER et al. 1998). Tree death and tree harvest (in scenarios 2 and 3) were includedin the simulation as catastrophic events which would lead to a complete destruction of thefunctional individual.After the death of the tree, a seedling of the same tree species replacedthe gap in the model and trees older than 20 years were considered as suitable substrates for L . pulmonaria. The natural mortality of the trees was 1% but tree harvest removed 50% (scenario 2) and 25% (scenario 3) of all trees after 40, 90, 130 and 180 years, irrespective of the presence or absence of L . pulmonaria on the harvested tree. A description of the parameters used in the simulation is given in SCHEIDEGGER et. al (1998). The probability forlocal extinction of small populations was simulated for the following three tree-harvestingscenarios: no harvest (scenario 1), sustainable harvest of the timber resource, i.e. single stemcutting after 40, 80, 120 and 180 years, with a rotation cycle of 90 years (scenario 2) and a 50%reduced harvest of the timber resource described for scenario 2 (scenario 3).

2.3 At-risk designation of the national population (criterion A3)

The total number of local populations in the study area formed the national population andeach local population was assigned to one of the three size classes. Because the distancesbetween local populations were always greater than 100 m, and in most cases more than 1 km,the local populations were considered independent.The death or harvest of single trees wereassumed to be the single most important catastrophic events for local epiphytic populations.The target species were considered to have limited dispersal potentials, similar to that of L .

pulmonaria. We assumed that no new subpopulation would arise during the observed periodand that the local extinction probability only depended on local population size and the management scenario. The binomial distribution was used to calculate the number of localpopulations that would become extinct during the next 100 years. If the cumulative distributionfunction indicated a probability ≥ 50% that ≤ 20% of the populations would survive over thenext 100 years, we considered the taxon to be critically endangered (CR). With expected survival rates ≤ 50%, the species were rated endangered (EN) and with expected survival rates≤ 70% , the species were rated as vulnerable (VU).

In some local populations the size class could not be determined. In such cases the pro-portion of populations belonging to the respective size classes were used rather than theobserved numbers.


3 Results

Local populations of L obaria pulmonaria consisting of only one functional individual at thebeginning of the simulation face a high probability that they will become extinct. Figure 2shows a rapid decrease in the survival probability during the simulated period of two hundredyears with an expected probability of survival for one local population of less than 30% .

Fig. 2. Survival probabilities of L obaria pulmonaria populations over 200 years. ◆ no harvest; ■ rotationcycle 90 years; 25% harvest after 40, 80, 120 and 180 years; 50% of mature trees are not harvested ▲rotation cycle 90 years; 50% harvest after 40 years, 50% harvest after 80 years. a: population consists of1 tree with L obaria at the beginning of the simulation. b: population consists of 4 trees with L obaria atthe beginning of the simulation. c: population consists of 10 trees with L obaria at the beginning of thesimulation. d: population consists of 15 trees with L obaria at the beginning of the simulation

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After one hundred years, which corresponds to the time period often considered in RedLists for long-lived organisms, the survival probability is 47% (Fig. 2a, Table 1). With highernumbers of functional individuals at the beginning of the simulation period, the probabilityconsiderably decreases that the local population will become extinct during the simulationperiod. Populations with four functional individuals at the beginning face a rather low extinction probability at the beginning of the simulation, but after about 80 years stochasticprocesses probably related to the natural death of L . pulmonaria-carrying trees led to a drastic decrease in the survival probability. After 200 years about 50% of the simulationsrevealed the extinction of the local population (Fig. 2b). The simulations starting with 10 functional individuals (Fig. 2c) and 15 functional individuals (Fig. 2d) can be regarded to berobust against the stochastic events considered in these simulations.

Table 1. Survival probabilities p over the next 100 years of populations restricted to 1, 4, or 8 trees underthree different forest harvest scenarios.

Scenario Population size1 tree (size class 1) 4 trees (size class 2) 8 trees (size class 3)

No harvest (Scenario 1) 0.47 0.85 0.95

Sustainable harvest (Scenario 2) 0.00 0.07 0.12

50% sustainble harvest (Scenario 3) 0.16 0.67 0.89

In scenario 2, all populations studied become extinct over the 200 year simulation period.Each tree harvest considerably reduced the survival probability of the population and the fourdifferent population sizes went extinct after 80, 140, 160 and 180 years, respectively. Scenario2 revealed a reduced survival probability compared to scenario 1,but the probability of survivalwas significantly higher than for scenario 3.

3.1 At-risk designation

The total number of local populations of each species and the proportion belonging to eachsize class, is given in Appendix A. Under scenario 1 the threat category CR is only reached byspecies where the national population is restricted to one single local populations of size class1, e.g. Parmelia reticulata (Fig. 3a). National populations face threat category EN if they consistof one population of size class 1 and 2 each, or where more than 90% of local populationsbelong to size class 1. An example is Sphaerophorus melanocarpus (Fig. 3b). The threat category VU is reached if the national population consists of at least 50% of size class 1, as isthe case with Heterodermia speciosa (Fig. 3c). Species with a higher percentage of larger localpopulations (e.g. Usnea longissima), face a low risk of being substantially reduced due to random processes, under the scenario without tree harvest (Fig. 3d).

The forest management scenario 3 with a low intensity of single-stem tree harvest increasedthe category of threatened species by one or even two categories, as shown for H. speciosa

in Figure 4a. Further more, species such as Usnea longissima (Fig. 4b) with up to six local populations of size class two qualify for VU, as do populations where a little less than 50% ofthe populations belong to size class 1.


Finally, scenario 2 assigns species with a contribution of about 30% from size class 1 populations to VU or a higher rank. Even species with a remarkably high number of localpopulations, such as L . pulmonaria, are ranked EN (Fig. 5a) and some species considered LCunder scenario 3, such as Mycoblastus sanguinarius, qualify for EN in this scenario (Fig. 5b).Species graded as VU or EN under scenario 1 are ranked CR throughout under scenario 2.

The management scenario has a significant influence on the number of species which qualify for each threat category. With scenario 1 only 19 species out of 160 species reach thehighest risk category CR, whereas under scenario 2 55 species qualify for CR, and under scenario 3, 36 species qualify for CR (Table 2).

Table 2. Number of species qualifying for the threat categories CR, EN, VU or LC for the Red List criteria, A3 and E , under three different tree harvesting scenarios: no tree harvest (scenario 1), 50% ofsustainable harvest (scenario 3) and sustainable harvest (scenario 2).

Category of criteria A3 and E management scenario 1 management scenario 3 management scenario 2A3 E A3 E A3 E

CR 19 19 36 26 55 38

EN 23 9 40 12 62 5

VU 41 2 47 2 30 7

LC 77 130 37 120 13 110

Fig. 3. Estimated probability of survival of 0% (RE), ≤ 20% (CR), ≤ 50% (EN) and ≤ 70% (VU) of the national populations of six rare species. Forest management scenario 1 (no tree harvest): CR:Parmelia reticulata (a), EN: Sphaerophorus melanocarpus (b),VU: Heterodermia speciosa (c), LC: Usnea

longissima (d).

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Fig. 4. Estimated probability of survival of 0% (RE), ≤ 20% (CR), ≤ 50% (EN) and ≤ 70% (VU) of thenational populations of rare species during the next 100 years. Forest management scenario 3 (50% ofsustainable harvest): EN: Heterodermia speciosa (a), Usnea longissima (b).

Fig. 5. Estimated probability of survival of 0% (RE), ≤ 20% (CR), ≤ 50% (EN) and ≤ 70% (VU) of thenational populations of rare species during the next 100 years. Forest management scenario 2 (100% sustainable harvest): EN: L obaria pulmonaria (a), Mycoblastus sanguinarius (b)

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4 Discussion

Typically, local populations of the epiphytic lichen species L obaria pulmonaria, consist of arelatively small number of trees. However, the abundance of the L . pulmonaria on the carriertrees is usually rather high, which leads to a highly clustered spatial population structure.Because diaspore production primarily depends on the biomass of L . pulmonaria, a local L .

pulmonaria population living on a large number of trees is more effective in dispersal and incolonising of trees than a population restricted to a few trees.With decreasing population size,the average age of trees colonised with L . pulmonaria therefore increases, which negativelyaffects the diaspore productivity of the next L . pulmonaria generation.

Under a scenario with no tree harvest, even local populations consisting of just four treesare reasonably stable over a planning period of 100 years, which is the usual time span considered in Red Lists for long-living organisms. However, this number does not considerthe maintenance of genetic diversity. Especially in heterothallic species this is of high relevance to maintain the potential of ascospore formation (ZOLLER et al. 1999). Even a smalltree harvest considerably increases the vulnerability of small populations and a harvest intensity considered sustainable in terms of tree harvesting inevitably leads to the extirpationof even large L . pulmonaria populations.

The validity of the model is restricted and an extrapolation to other species has to be considered with caution. The model was parameterised for lowland populations of L .

pulmonaria. Considering that no precise historical data are available on past local populationsizes, our field experience showing the decline of some local L . pulmonaria populations dur-ing the past twenty years is circumstantial evidence for the validity of the simulation. In a for-est near Berne, at least two local populations which consisted of one tree each have becomeextinct during our observation period. Even a rather large local population which consistedof 7 trees at the beginning of the observation period was reduced to three trees earlier thisyear. It has, however, since then been augmented with local material collected from a treewhich was killed by a windthrow.

It is evident that the model provides only very rough estimations of the future decline ofL . pulmonaria under different local climates and the precision for other lichen species is evenmore uncertain.Although many species such as Hypogymnia physodes are effective disperserswhich can easily colonise new habitats over larger distances and develop stable local popula-tions within one tree generation, there is now increasing evidence that other (often conser-vation-dependent) epiphytic lichens are poor dispersers. Recent experiments involving thetransplantation of diaspores and thallus fragments (ZOLLER et al. 2000) have shown that L .pulmonaria, Sticta fuliginosa and Parmotrema crinitum are dispersal limited in managedforests in Switzerland.These results are confirmed by an analysis using autologistic regressionmodels of the spatial patterns of local populations of L . pulmonaria in managed and virginboreal forests in Finland(GU et al. 2001). Many other epiphytic lichen species are also dispersal limited and for some of them, e.g. Usnea longissima, the dispersal limitation is evenmore pronounced than in L . pulmonaria. The extrapolation of the model to these specieswould therefore lead to a conservative estimation of the extinction risk and the at-risk desig-nation. Estimating declines in the national populations of dispersal limited epiphytic lichenscan, nevertheless, contribute to the at-risk designation in Red Lists. It is especially useful forassessing species where it has not been possible to determine past declines due to lack of historical data. In such cases, predicting future declines on the basis of evaluations of the current vulnerability of local populations can be a significant contribution to Red Lists. In the


recent Red List of epiphytic lichens of Switzerland (SCHEIDEGGER et al. in prep.), drawn upaccording to the recent IUCN guidelines (IUCN 2001), A3 appeared to be the strongest criterion for 13 species. It ranked 12 species under VU and 1 under EN. For another 81 species,A3 confirmed the rank assigned by several other Red List criteria.

Acknowledgements

We would like to thank Rita Ghosh for critical comments on the manuscript, Martin Frei for hisvaluable contribution to the field work, Peter Jakob and Nick Baumberger for help with the data-base Lichen and Jean-Claude Walser for discussing the individual-based model of the extinctionprocess.

5 References

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l.Appendix A. Number and size class distribution of local populations of 160 selected epiphytic lichen species. The threat category for the Red List criteria,A3 and E , is calculated for three tree-harvesting scenarios: no harvest (1), sustainable harvest (2) and 50% of the sustainable harvest (3).

Taxon Local Percentage of local Expected number of local populations Probability of 20, 50, 80 Category of criteria A3 and Epopu- populations belonging of size classes 1, 2 and 3 going extinct when and 100% reduction of the for management scenarioslations to size class the national population reduction is number of local populations

30% 50% 80% 1 2 31 2 3 1 2 3 1 2 3 1 2 3 20 50 80 100 A3 E A3 E A3 E

A gonimia allobata

(Stizenb.) P.James 40 50% 40% 10% 12 0 0 20 0 0 20 12 0 0.35 <0.001 <0.001 <0.001 LC LC VU LC EN LC A lectoria sarmentosa

(Ach.) Ach. 34 29% 0% 71% 10 0 1 10 0 7 10 0 18 <0.01 <0.001 <0.001 <0.001 LC LC LC LC VU LCA naptychia ciliaris

(L.) Körber ex Massal. 124 55% 30% 15% 38 0 0 62 0 0 68 32 0 0.36 <0.001 <0.001 <0.001 LC LC VU LC EN LCA naptychia crinalis

(Schleich.) Vezda 23 0% 43% 57% 0 7 0 0 10 2 0 10 9 <0.1 <0.001 <0.001 <0.001 LC LC LC LC LC LCA rthonia cinnabarina

(DC.) Wallr. 91 29% 57% 14% 26 2 0 26 20 0 26 47 0 <0.001 <0.001 <0.001 <0.001 LC LC LC LC VU LCA rthonia leucopellaea

(Ach.) Almq. 29 21% 41% 41% 6 3 0 6 9 0 6 12 6 <0.1 <0.01 <0.001 <0.001 LC LC LC LC VU LCA rthonia reniformis

(Pers.) Nyl. 1 100% 0% 0% 1 0 0 1 0 0 1 0 0 0.53 0.53 0.53 0.53 CR CR CR CR CR CRBacidia fraxinea Lonnr. 1 100% 0% 0% 1 0 0 1 0 0 1 0 0 0.53 0.53 0.53 0.53 CR CR CR CR CR CRBacidia rosella (Pers.) De Not. 4 100% 0% 0% 2 0 0 2 0 0 4 0 0 0.73 0.73 <0.1 <0.1 EN LC EN EN CR CRBactrospora dryina

(Ach.) Massal. 102 8% 38% 54% 8 23 0 8 39 4 8 39 35 <0.001 <0.001 <0.001 <0.001 LC LC LC LC LC LCBiatoridium delitescens

(Arnold) Haf. 1 100% 0% 0% 1 0 0 1 0 0 1 0 0 0.53 0.53 0.53 0.53 CR CR CR CR CR CRBryoria bicolor

(Ehrh.) Brodo & D.Hawksw. 35 71% 14% 14% 11 0 0 18 0 0 25 3 0 0.86 <0.1 <0.001 <0.001 VU LC EN LC EN LCBryoria capillaris

(Ach.) Brodo & D.Hawksw. 174 26% 31% 42% 46 7 0 46 41 0 46 54 40 <0.001 <0.001 <0.001 <0.001 LC LC LC LC VU LCBryoria fuscescens (Gyelnik) Brodo & D.Hawksw. 175 45% 20% 35% 53 0 0 79 9 0 79 35 26 <0.01 <0.001 <0.001 <0.001 LC LC VU LC EN LCBryoria implexa

(Hoffm.) Brodo & D.Hawksw. 131 38% 30% 32% 40 0 0 50 16 0 50 39 16 <0.001 <0.001 <0.001 <0.001 LC LC VU LC VU LCBryoria subcana

(Nyl.) Brodo & D. Hawksw. 2 0% 0% 100% 0 0 1 0 0 1 0 0 2 0.21 0.21 <0.1 <0.1 LC LC LC LC LC LC

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Appendix A continued.

Buellia alboatra (Hoffm.) Th.Fr. 12 92% 0% 8% 4 0 0 6 0 0 10 0 0 0.92 0.58 <0.01 <0.001 EN LC EN LC CR VUBuellia disciformis (Fr.) Mudd 111 47% 30% 23% 34 0 0 52 4 0 52 33 4 <0.1 <0.001 <0.001 <0.001 LC LC VU LC EN LCBuellia erubescens Arnold 34 18% 18% 68% 6 5 0 6 6 5 6 6 16 <0.1 <0.001 <0.001 <0.001 LC LC LC LC LC LCBuellia triphragmia

(Nyl.) Arnold 1 100% 0% 0% 1 0 0 1 0 0 1 0 0 0.53 0.53 0.53 0.53 CR CR CR CR CR CRCalicium adaequatum Nyl. 5 100% 0% 0% 2 0 0 3 0 0 4 0 0 0.85 0.56 0.23 <0.1 EN LC CR EN CR CRCaloplaca lucifuga Thor 41 56% 44% 0% 13 0 0 21 0 0 23 10 0 0.45 <0.001 <0.001 <0.001 LC LC VU LC EN LC Candelariella lutella

(Vain.) Räsänen 1 100% 0% 0% 1 0 0 1 0 0 1 0 0 0.53 0.53 0.53 0.53 CR CR CR CR CR CRCetraria laureri Krempelh. 30 33% 67% 0% 9 0 0 10 5 0 10 14 0 <0.1 <0.01 <0.001 <0.001 LC LC VU LC EN LCCetraria oakesiana Tuck. 15 100% 0% 0% 5 0 0 8 0 0 12 0 0 0.96 0.59 <0.1 <0.001 EN LC CR LC CR CRCetraria sepincola (Ehrh.) Ach. 11 18% 55% 36% 2 2 0 2 4 0 2 6 1 0.18 <0.1 <0.001 <0.001 LC LC LC LC VU LCCetrelia cetrarioides (Del.ex Duby) W.Culb. & C.Culb. 169 38% 33% 30% 51 0 0 64 21 0 64 55 17 <0.001 <0.001 <0.001 <0.001 LC LC VU LC VU LCCetrelia chicitae

(W. Culb.) W. Culb. & C. Culb. 1 100% 0% 0% 1 0 0 1 0 0 1 0 0 0.53 0.53 0.53 0.53 CR CR CR CR CR CRCetrelia olivetorum

(Nyl.) W.Culb. & C.Culb. 30 43% 43% 13% 9 0 0 13 2 0 13 11 0 0.19 <0.001 <0.001 <0.001 LC LC VU LC EN LCChaenotheca brachypoda

(Ach.) Tibell 29 41% 52% 7% 9 0 0 12 3 0 12 12 0 0.11 <0.001 <0.001 <0.001 LC LC VU LC EN LCChaenotheca chlorella

(Ach.) Müll.Arg.. 16 100% 0% 0% 5 0 0 8 0 0 13 0 0 0.98 0.69 <0.1 <0.001 EN LC CR LC CR CRChaenotheca chrysocephala

(Turner ex Ach.) Th.Fr. 293 28% 41% 31% 83 5 0 83 64 0 83 120 32 <0.001 <0.001 <0.001 <0.001 LC LC LC LC VU LC Chaenotheca gracilenta (Ach.) Mattsson & Middelborg 24 46% 54% 0% 8 0 0 11 1 0 11 9 0 0.16 <0.001 <0.001 <0.001 LC LC VU LC EN LCChaenotheca hispidula

(Ach.) Zahlbr. 19 100% 0% 0% 6 0 0 10 0 0 16 0 0 0.98 0.60 <0.01 <0.001 EN LC CR LC CR CRChaenotheca laevigata Nádv. 7 100% 0% 0% 3 0 0 4 0 0 6 0 0 0.82 0.57 <0.1 <0.1 EN LC CR EN CR CRChaenotheca phaeocephala

(Turner) Th.Fr. 28 89% 11% 0% 9 0 0 14 0 0 23 0 0 0.97 0.46 <0.001 <0.001 VU LC EN LC CR LCChaenotheca subroscida

(Eitner) Zahlbr. 14 0% 50% 50% 0 5 0 0 7 0 0 7 5 <0.1 <0.001 <0.001 <0.001 LC LC LC LC LC LCCheiromycina flabelliformis

B. Sutton 1 100% 0% 0% 1 0 0 1 0 0 1 0 0 0.53 0.53 0.53 0.53 CR CR CR CR CR CR

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30% 50% 80% 1 2 31 2 3 1 2 3 1 2 3 1 2 3 20 50 80 100 A3 E A3 E A3 E

Chromatochlamys muscorum

(Fr.) Mayrhofer & Poelt 1 100% 0% 0% 1 0 0 1 0 0 1 0 0 0.53 0.53 0.53 0.53 CR CR CR CR CR CRChrysothrix candelaris

(L.) Laundon 265 33% 45% 22% 80 0 0 88 45 0 88 119 5 <0.001 <0.001 <0.001 <0.001 LC LC LC LC VU LCCliostomum corrugatum

(Ach.) Fr. 23 52% 35% 17% 7 0 0 12 0 0 12 7 0 0.47 <0.001 <0.001 <0.001 LC LC VU LC EN LCCliostomum pallens

(Kullh.) S.Ekman 1 0% 100% 0% 0 1 0 0 1 0 0 1 0 0.33 0.33 0.33 0.33 LC EN LC EN LC ENCollema fasciculare

(L.) Weber ex Wigg. 4 50% 0% 50% 2 0 0 2 0 0 2 0 2 0.28 0.28 <0.01 <0.01 LC LC EN LC EN LCCollema flaccidum (Ach.) Ach. 97 55% 36% 9% 30 0 0 49 0 0 53 25 0 0.35 <0.001 <0.001 <0.001 LC LC VU LC EN LCCollema fragrans (Sm.) Ach. 3 67% 33% 0% 1 0 0 2 0 0 2 1 0 0.78 0.28 0.28 <0.1 VU LC EN EN EN ENCollema furfuraceum

(Arnold) Du Rietz 4 100% 0% 0% 2 0 0 2 0 0 4 0 0 0.73 0.73 <0.1 <0.1 EN LC EN EN CR CRCollema ligerinum (Hy) Harm. 2 0% 100% 0% 0 1 0 0 1 0 0 2 0 0.55 0.55 0.11 0.11 EN VU EN VU EN VUCollema nigrescens

(Hudson) DC. 48 75% 19% 8% 15 0 0 24 0 0 36 3 0 0.94 <0.1 <0.001 <0.001 VU LC EN LC CR LCCollema occultatum Bagl. 1 100% 0% 0% 1 0 0 1 0 0 1 0 0 0.53 0.53 0.53 0.53 CR CR CR CR CR CRCyphelium inquinans

(Sm.) Trevisan 9 56% 22% 22% 3 0 0 5 0 0 5 2 1 0.56 <0.1 <0.001 <0.001 VU LC VU LC EN LCCyphelium karelicum

(Vainio) Räsänen 27 56% 44% 0% 9 0 0 14 0 0 15 7 0 0.39 <0.01 <0.001 <0.001 LC LC VU LC EN LCCyphelium lucidum

(Th.Fr.) Th.Fr. 6 100% 0% 0% 2 0 0 3 0 0 5 0 0 0.92 0.71 0.14 <0.1 EN LC CR EN CR CR Cyphelium pinicola Tibell 1 0% 100% 0% 0 1 0 0 1 0 0 1 0 0.33 0.33 0.33 0.33 LC EN LC EN LC ENCyphelium trachylioides (Nyl.ex Branth & Rostr.) Erichsen 1 100% 0% 0% 1 0 0 1 0 0 1 0 0 0.53 0.53 0.53 0.53 CR CR CR CR CR CRDimerella lutea

(Dickson) Trevisan 7 71% 29% 0% 3 0 0 4 0 0 5 1 0 0.56 0.23 <0.1 <0.01 VU LC EN LC CR VUEopyrenula leucoplaca

(Wallr.) R .Harris 18 67% 33% 0% 6 0 0 9 0 0 12 3 0 0.69 0.11 <0.001 <0.001 VU LC EN LC EN LC

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Evernia divaricata (L.) Ach. 216 28% 34% 38% 60 5 0 60 48 0 60 74 39 <0.001 <0.001 <0.001 <0.001 LC LC LC LC VU LCEvernia mesomorpha Nyl. 25 48% 32% 24% 8 0 0 12 1 0 12 8 0 0.26 <0.001 <0.001 <0.001 LC LC VU LC EN LCFellhanera sp. 1 7 57% 0% 57% 3 0 0 4 0 0 4 0 2 0.36 <0.1 <0.001 <0.001 LC LC VU LC EN LCFellhaneropsis vezdae (Coppins & P. James) Sérus. & Coppins 16 31% 31% 31% 5 0 0 5 3 0 5 5 3 <0.1 <0.1 <0.001 <0.001 LC LC LC LC VU LCGraphis elegans

(Borrer ex Sm.) Ach. 5 60% 60% 0% 2 0 0 3 0 0 3 1 0 0.54 0.15 0.15 <0.01 VU LC EN LC CR LCGyalecta flotowii Körber 13 38% 38% 23% 4 0 0 5 2 0 5 5 1 0.23 <0.1 <0.001 <0.001 LC LC VU LC EN LCGyalecta truncigena

(Ach.) Hepp 76 57% 39% 4% 23 0 0 38 0 0 43 18 0 0.54 <0.001 <0.001 <0.001 VU LC VU LC EN LCGyalecta ulmi (Sw.) Zahlbr. 19 68% 32% 0% 6 0 0 10 0 0 13 3 0 0.78 <0.1 <0.001 <0.001 VU LC EN LC EN LCHeterodermia obscurata

(Nyl.) Trevisan 3 33% 67% 0% 1 0 0 1 1 0 1 2 0 0.53 0.29 0.29 <0.1 VU LC VU LC EN VUHeterodermia speciosa

(Wulfen) Trevisan 9 78% 0% 22% 3 0 0 5 0 0 7 0 1 0.82 0.28 <0.01 <0.001 VU LC EN LC EN LCHypocenomyce caradocensis

(Leigthon ex Nyl.) P.James & G.Schneider 12 67% 33% 0% 4 0 0 6 0 0 8 2 0 0.70 0.19 <0.01 <0.001 VU LC EN LC EN LCHypocenomyce friesii

(Ach.) P.James & G.Schneider 3 100% 0% 0% 1 0 0 2 0 0 3 0 0 0.90 0.54 0.15 0.15 EN VU CR CR CR CRHypocenomyce scalaris

(Ach. ex Lilj.) Choisy 123 35% 44% 21% 37 0 0 43 19 0 43 54 2 <0.001 <0.001 <0.001 <0.001 LC LC LC LC VU LCHypogymnia vittata (Ach.) Parr. 53 36% 42% 23% 16 0 0 19 8 0 19 22 2 <0.01 <0.001 <0.001 <0.001 LC LC VU LC VU LCL ecanactis abietina

(Ach.) Körber 38 26% 18% 55% 10 2 0 10 7 2 10 7 14 <0.01 <0.001 <0.001 <0.001 LC LC LC LC VU LCL ecanora allophana Nyl. 125 40% 46% 14% 38 0 0 50 13 0 50 50 0 <0.001 <0.001 <0.001 <0.001 LC LC VU LC EN LCL eptogium burnetiae Dodge 2 50% 0% 50% 1 0 0 1 0 0 1 0 1 0.53 0.53 <0.1 <0.1 EN LC EN LC EN VUL eptogium cyanescens

(Rabenh.) Körber 9 78% 22% 0% 3 0 0 5 0 0 7 1 0 0.82 0.28 <0.1 <0.01 VU LC EN LC CR VUL eptogium hildenbrandii

(Garov.) Nyl. 12 75% 25% 0% 4 0 0 6 0 0 9 1 0 0.80 0.32 <0.01 <0.001 VU LC EN LC CR LCL eptogium saturninum

(Dickson) Nyl. 143 59% 27% 15% 43 0 0 72 0 0 84 31 0 0.67 <0.001 <0.001 <0.001 VU LC VU LC EN LCL etharia vulpina (L.) Hue 78 22% 44% 35% 17 7 0 17 22 0 17 34 12 <0.001 <0.001 <0.001 <0.001 LC LC LC LC VU LC

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L obaria amplissima

(Scop.) Forss. 7 43% 43% 14% 3 0 0 3 1 0 3 3 0 0.15 0.15 0.15 <0.001 LC LC VU LC EN LCL obaria pulmonaria

(L.) Hoffm. 146 29% 39% 32% 42 2 0 42 31 0 42 57 18 <0.001 <0.001 <0.001 <0.001 LC LC LC LC VU LCL obaria scrobiculata

(Scop.) DC. 4 75% 25% 0% 1 0 0 1 0 0 2 0 0 0.78 0.78 0.28 <0.1 EN LC CR EN CR ENL opadium disciforme

(Flotow) Kullhem 24 21% 79% 0% 5 3 0 5 7 0 5 15 0 <0.1 <0.1 <0.001 <0.001 LC LC LC LC VU LCMenegazz ia terebrata

(Hoffm.) Massal. 94 33% 31% 36% 29 0 0 31 16 0 31 29 16 <0.001 <0.001 <0.001 <0.001 LC LC LC LC VU LCMicarea adnata Coppins 8 50% 50% 0% 3 0 0 4 0 0 4 3 0 0.36 <0.1 <0.1 <0.001 LC LC VU LC EN LCMycobilimbia sphaeroides

(Dickson) V.Wirth 14 79% 21% 0% 5 0 0 7 0 0 11 1 0 0.79 0.35 <0.001 <0.001 VU LC EN LC CR LCMycoblastus affinis

(Schaerer) Schauer 31 68% 0% 32% 10 0 0 16 0 0 21 0 4 0.76 <0.1 <0.001 <0.001 VU LC EN LC EN LCMycoblastus caesius

(Coppins & P.James) Tønsb. 1 100% 0% 0% 1 0 0 1 0 0 1 0 0 0.53 0.53 0.53 0.53 CR CR CR CR CR CRMycoblastus sanguinarius

(L.) Norman 17 35% 65% 0% 6 0 0 6 3 0 6 8 0 <0.1 <0.1 <0.01 <0.001 LC LC LC LC EN LCNephroma bellum

(Sprengel) Tuck. 48 56% 21% 21% 15 0 0 24 0 0 27 10 2 0.47 <0.001 <0.001 <0.001 LC LC VU LC EN LCNephroma laevigatum Ach. 4 100% 0% 0% 2 0 0 2 0 0 4 0 0 0.73 0.73 <0.1 <0.1 EN LC EN EN CR CRNephroma parile (Ach.) Ach. 59 64% 25% 10% 18 0 0 30 0 0 38 10 0 0.80 <0.001 <0.001 <0.001 VU LC EN LC EN LCNephroma resupinatum

(L.) Ach. 59 51% 29% 19% 18 0 0 30 0 0 30 17 1 0.28 <0.001 <0.001 <0.001 LC LC VU LC EN LCOchrolechia pallescens

(L.) Massal. 22 41% 59% 0% 7 0 0 9 2 0 9 9 0 0.12 <0.01 <0.01 <0.001 LC LC VU LC EN LCOchrolechia szatalaensis Vers. 58 74% 21% 7% 18 0 0 29 0 0 43 4 0 0.95 <0.1 <0.001 <0.001 VU LC EN LC CR LCOpegrapha ochrocheila Nyl. 1 100% 0% 0% 1 0 0 1 0 0 1 0 0 0.53 0.53 0.53 0.53 CR CR CR CR CR CRPachyphiale fagicola

(Hepp) Zwackh. 17 53% 53% 0% 6 0 0 9 0 0 9 5 0 0.32 <0.01 <0.01 <0.001 LC LC VU LC EN LC

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Pachyphiale ophiospora Lettau 2 100% 0% 0% 1 0 0 1 0 0 2 0 0 0.78 0.78 0.28 0.28 EN EN CR CR CR CRPannaria conoplea (Ach.) Bory 27 67% 26% 7% 9 0 0 14 0 0 18 4 0 0.69 <0.1 <0.001 <0.001 VU LC EN LC EN LCParmelia acetabulum

(Necker) Duby 147 54% 29% 17% 45 0 0 74 0 0 80 38 0 0.32 <0.001 <0.001 <0.001 LC LC VU LC EN LCParmelia flaventior Stirton 57 60% 26% 14% 18 0 0 29 0 0 34 12 0 0.57 <0.001 <0.001 <0.001 VU LC EN LC EN LCParmelia laevigata (Sm.) Ach. 14 57% 29% 14% 5 0 0 7 0 0 8 4 0 0.43 <0.1 <0.01 <0.001 LC LC EN LC EN LCParmelia minarum Vainio 1 100% 0% 0% 1 0 0 1 0 0 1 0 0 0.53 0.53 0.53 0.53 CR CR CR CR CR CRParmelia reticulata Taylor 1 100% 0% 0% 1 0 0 1 0 0 1 0 0 0.53 0.53 0.53 0.53 CR CR CR CR CR CRParmelia septentrionalis

(Lynge) Ahti 3 0% 0% 100% 0 0 1 0 0 2 0 0 3 0.30 <0.1 <0.01 <0.01 LC LC LC LC LC LCParmelia sinuosa (Sm.) Ach. 24 75% 25% 0% 8 0 0 12 0 0 18 2 0 0.83 0.18 <0.001 <0.001 VU LC EN LC CR LCParmelia submontana

Nàdv. ex Hale 87 47% 46% 7% 27 0 0 41 3 0 41 29 0 <0.1 <0.001 <0.001 <0.001 LC LC VU LC EN LCParmelia taylorensis Mitch. 18 78% 0% 28% 6 0 0 9 0 0 14 0 1 0.85 0.28 <0.001 <0.001 VU LC EN LC EN LCParmeliella triptophylla

(Ach.) Müll.Arg.. 97 41% 45% 13% 30 0 0 40 9 0 40 38 0 <0.01 <0.001 <0.001 <0.001 LC LC VU LC EN LCParmotrema arnoldii

(Du Rietz) Hale 30 87% 13% 0% 9 0 0 15 0 0 24 0 0 0.98 0.39 <0.001 <0.001 VU LC EN LC CR LCParmotrema chinense

(Osbeck) Hale & Ahti 70 69% 23% 7% 21 0 0 35 0 0 48 8 0 0.92 <0.01 <0.001 <0.001 VU LC EN LC EN LCParmotrema crinitum

(Ach.) Choisy 23 43% 43% 13% 7 0 0 10 2 0 10 9 0 0.23 <0.01 <0.01 <0.001 LC LC VU LC EN LCParmotrema stuppeum

(Taylor) Hale 12 0% 100% 0% 0 4 0 0 6 0 0 10 0 0.60 0.17 <0.001 <0.001 VU LC VU LC VU LCPeltigera collina

(Ach.) Schrader 72 49% 46% 6% 22 0 0 35 1 0 35 23 0 0.16 <0.001 <0.001 <0.001 LC LC VU LC EN LCPertusaria alpina Hepp ex Ahles 14 0% 50% 50% 0 5 0 0 7 0 0 7 5 <0.1 <0.001 <0.001 <0.001 LC LC LC LC LC LCPertusaria coccodes (Ach.) Nyl. 146 69% 29% 2% 44 0 0 73 0 0 101 16 0 0.98 <0.001 <0.001 <0.001 VU LC EN LC EN LCPertusaria constricta Erichsen 27 33% 33% 33% 9 0 0 9 5 0 9 9 4 <0.01 <0.01 <0.001 <0.001 LC LC LC LC VU LCPertusaria coronata

(Ach.) Th.Fr. 109 57% 26% 17% 33 0 0 55 0 0 62 26 0 0.54 <0.001 <0.001 <0.001 VU LC VU LC EN LCPertusaria flavida

(DC.) Laundon 16 100% 0% 0% 5 0 0 8 0 0 13 0 0 0.98 0.69 <0.1 <0.001 EN LC CR LC CR CRPertusaria leioplaca DC. 124 40% 43% 17% 38 0 0 50 12 0 50 50 0 <0.001 <0.001 <0.001 <0.001 LC LC VU LC EN LCPertusaria ophthalmiza

(Nyl.) Nyl. 14 79% 0% 29% 5 0 0 7 0 0 11 0 1 0.79 0.35 <0.001 <0.001 VU LC EN LC EN LC

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Pertusaria pertusa

(Weigel) Tuck. 15 20% 67% 20% 3 2 0 3 5 0 3 9 0 0.13 <0.1 <0.01 <0.001 LC LC VU LC VU LCPertusaria pupillaris (Nyl.) Th.Fr. 53 60% 40% 0% 16 0 0 27 0 0 32 11 0 0.70 <0.001 <0.001 <0.001 VU LC EN LC EN LCPertusaria sommerfeltii

(Sommerf.) Fr. 2 100% 0% 0% 1 0 0 1 0 0 2 0 0 0.78 0.78 0.28 0.28 EN EN CR CR CR CRPhaeophyscia ciliata

(Hoffm.) Moberg 44 27% 45% 27% 12 2 0 12 10 0 12 20 4 <0.001 <0.001 <0.001 <0.001 LC LC LC LC VU LCPhaeophyscia hirsuta

(Mereschk.) Moberg 21 81% 10% 10% 7 0 0 11 0 0 17 0 0 0.89 0.24 <0.001 <0.001 VU LC EN LC CR LCPhaeophyscia hispidula

(Ach.) Moberg 1 100% 0% 0% 1 0 0 1 0 0 1 0 0 0.53 0.53 0.53 0.53 CR CR CR CR CR CRPhaeophyscia insignis

(Mereschk.) Moberg 8 38% 25% 38% 3 0 0 3 1 0 3 2 2 0.15 0.15 <0.001 <0.001 LC LC VU LC EN LCPhaeophyscia poeltii

(Frey) Nimis 10 50% 0% 50% 3 0 0 5 0 0 5 0 3 0.56 <0.1 <0.001 <0.001 VU LC VU LC EN LCPhlyctis agelaea (Ach.) Flotow 49 53% 27% 20% 15 0 0 25 0 0 26 13 1 0.39 <0.001 <0.001 <0.001 LC LC VU LC EN LCPhyscia clementei (Turner) Maas Geest. 7 71% 29% 0% 3 0 0 4 0 0 5 1 0 0.56 0.23 <0.1 <0.01 VU LC EN LC CR VUPhyscia vitii Nádv. 10 30% 30% 30% 3 0 0 3 2 0 3 3 2 0.15 0.15 <0.001 <0.001 LC LC VU LC VU LCRamalina fastigiata (Pers.) Ach. 52 50% 38% 12% 16 0 0 26 0 0 26 16 0 0.25 <0.001 <0.001 <0.001 LC LC VU LC EN LCRamalina fraxinea (L.) Ach. 77 51% 34% 17% 24 0 0 39 0 0 39 23 0 0.18 <0.001 <0.001 <0.001 LC LC VU LC EN LCRamalina obtusata (Arnold) Bitter 74 65% 28% 7% 23 0 0 37 0 0 48 12 0 0.80 <0.001 <0.001 <0.001 VU LC EN LC EN LCRamalina roesleri

(Hochst. ex Schaerer) Hue 8 0% 100% 0% 0 3 0 0 4 0 0 7 0 0.52 0.25 <0.01 <0.001 VU LC VU LC VU LCRamalina sinensis Jatta 2 100% 0% 0% 1 0 0 1 0 0 2 0 0 0.78 0.78 0.28 0.28 EN EN CR CR CR CRRamalina thrausta (Ach.) Nyl. 21 24% 76% 0% 5 2 0 5 6 0 5 12 0 <0.1 <0.1 <0.001 <0.001 LC LC LC LC VU LCRinodina ventricosa

Hinteregger & Giralt 1 0% 100% 0% 0 1 0 0 1 0 0 1 0 0.33 0.33 0.33 0.33 LC EN LC EN LC EN

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Schismatomma decolorans

(Turn. & Borrer ex Sm.) Clauz. & Vezda 28 71% 29% 0% 9 0 0 14 0 0 20 3 0 0.83 <0.1 <0.001 <0.001 VU LC EN LC CR LCSchismatomma graphidioides

(Leighton) Zahlbr. 1 100% 0% 0% 1 0 0 1 0 0 1 0 0 0.53 0.53 0.53 0.53 CR CR CR CR CR CRSchismatomma pericleum

(Ach.) Branth & Rostrup 120 29% 55% 16% 35 1 0 35 25 0 35 61 0 <0.001 <0.001 <0.001 <0.001 LC LC LC LC VU LCSclerophora nivea

(Hoffm.) Tibell 17 76% 18% 6% 6 0 0 9 0 0 13 1 0 0.78 0.19 <0.001 <0.001 VU LC EN LC CR LCScoliciosporum schadeanum

(Erichs.) Vezda 1 100% 0% 0% 1 0 0 1 0 0 1 0 0 0.53 0.53 0.53 0.53 CR CR CR CR CR CRSphaerophorus globosus

(Hudson) Vainio 17 35% 35% 35% 6 0 0 6 3 0 6 6 2 <0.1 <0.1 <0.001 <0.001 LC LC LC LC VU LCSphaerophorus melanocarpus

(Sw.) DC. 2 100% 0% 0% 1 0 0 1 0 0 2 0 0 0.78 0.78 0.28 0.28 EN EN CR CR CR CRSticta limbata (Sm.) Ach. 2 100% 0% 0% 1 0 0 1 0 0 2 0 0 0.78 0.78 0.28 0.28 EN EN CR CR CR CRSticta sylvatica (Huds.) Ach. 24 63% 38% 0% 8 0 0 12 0 0 15 5 0 0.59 <0.1 <0.001 <0.001 VU LC EN LC EN LCStrigula mediterranea Etayo 1 100% 0% 0% 1 0 0 1 0 0 1 0 0 0.53 0.53 0.53 0.53 CR CR CR CR CR CRTephromela atra (Hudson) Haf. 43 88% 12% 0% 13 0 0 22 0 0 35 0 0 0.99 0.33 <0.001 <0.001 VU LC EN LC CR LCThelenella modesta (Nyl.) Nyl. 2 100% 0% 0% 1 0 0 1 0 0 2 0 0 0.78 0.78 0.28 0.28 EN EN CR CR CR CRThelopsis rubella Nyl. 10 100% 0% 0% 3 0 0 5 0 0 8 0 0 0.96 0.69 <0.1 <0.01 EN LC CR VU CR CRThelotrema lepadinum

(Ach.) Ach. 52 17% 37% 46% 9 7 0 9 17 0 9 19 14 <0.01 <0.001 <0.001 <0.001 LC LC LC LC LC LCUsnea cavernosa Tuck. 51 35% 22% 43% 16 0 0 18 8 0 18 11 12 <0.01 <0.001 <0.001 <0.001 LC LC LC LC VU LCUsnea ceratina Ach. 41 34% 56% 12% 13 0 0 14 7 0 14 19 0 <0.01 <0.001 <0.001 <0.001 LC LC LC LC EN LCUsnea cornuta Körber 1 100% 0% 0% 1 0 0 1 0 0 1 0 0 0.53 0.53 0.53 0.53 CR CR CR CR CR CRUsnea florida

(L.) Weber ex Wigg. 7 0% 100% 0% 0 3 0 0 4 0 0 6 0 0.42 0.17 <0.01 <0.001 LC LC LC LC LC LCUsnea fulvoreagens

(Räsänen) Räsänen 16 0% 100% 0% 0 5 0 0 8 0 0 13 0 0.65 0.12 <0.001 <0.001 VU LC VU LC VU LCUsnea glabrata (Ach.) Vainio 11 36% 64% 0% 4 0 0 4 2 0 4 5 0 <0.1 <0.1 <0.1 <0.001 LC LC LC LC EN LCUsnea longissima Ach. 7 43% 14% 43% 3 0 0 3 1 0 3 1 2 0.15 0.15 <0.01 <0.001 LC LC VU LC VU LCUsnea wasmuthii Räsänen 9 100% 0% 0% 3 0 0 5 0 0 8 0 0 0.94 0.57 <0.1 <0.01 EN LC CR EN CR CRVaricellaria rhodocarpa

(Körber) Th.Fr. 4 0% 0% 100% 0 0 2 0 0 2 0 0 4 <0.1 <0.1 <0.001 <0.001 LC LC LC LC LC LC

estimating regional extinction probabilities and reduction ...15299/datastrea… · keywords:...

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