ECOLOGY AND DIVERSITY OF THE LICHEN SYMBIOSIS: 

FOLLOWING ESTABLISHED PATTERNS, OR AN EXCEPTION TO THE RULE? 

 

By 

 

Klara Scharnagl 

 
 
 
 
 
 
 
 
 
 
 
 

A DISSERTATION 

 

Submitted to 

Michigan State University 

in partial fulfillment of the requirements 

for the degree of 

 

Plant Biology - Doctor of Philosophy 

Ecology, Evolutionary Biology and Behavior - Dual Major 

 

2019 

 
 
 
 
 
 

 
 
 

 
 

 
 

 

 

 

ABSTRACT 

ECOLOGY AND DIVERSITY OF THE LICHEN SYMBIOSIS: 

FOLLOWING ESTABLISHED PATTERNS, OR AN EXCEPTION TO THE RULE? 

By 

Klara Scharnagl 

 
Few phenomena of biodiversity have perplexed researchers as much as the latitudinal diversity gradient. 

Though many taxa have been shown to follow this pattern of high species richness in the tropics and lower 

species richness towards the poles, no consensus has yet been reached regarding the drivers of this global 

pattern. Symbiosis, a long term and physically intimate interaction between two organisms, is a prevalent 

biotic interaction across the tree of life, yet few studies of the latitudinal diversity gradient have looked at 

symbiotic organisms. One example of symbiosis is the lichen symbiosis, an association between a filamentous 

fungal partner and a photosynthetic partner of green algae or cyanobacteria. Little is known about the 

latitudinal diversity gradient of lichens, yet their terrestrial ubiquity and symbiotic nature could provide insight 

into the drivers of this global pattern.  

To assess whether lichenized fungi follow a latitudinal diversity gradient, I compiled a dataset from 

three repositories for digitized herbarium specimen data: the Consortium for North American Lichen 

Herbaria, the Global Biodiversity Information Facility, and the Institutos Nacionais de Ciencia e Tecnologia. 

The fully compiled and quality-controlled dataset contained over 900,000 datapoints representing over 8,000 

species. The raw species richness data revealed a peak in richness north of the equator outside of the tropics, 

however, this pattern mirrored the number of collections per latitudinal band. To correct for sampling effort 

biases in the digitized herbarium data, I rarefied species richness. I further corrected the rarefied species 

richness for land area, given the wide range of land area per latitudinal band in the Americas. This rarefied 

and land-area-corrected species richness data supports a latitudinal diversity gradient of lichenized fungi in the 

Americas. In a comparison to lichen checklist data at the country or state level, I revealed that tropical regions 

are underrepresented in the digitized herbarium data. 

 
 

To test the influence of sampling effort bias on the patterns revealed by the digitized herbarium data, 

I designed a field sampling approach directly targeted at the question of whether epiphytic lichens follow a 

latitudinal diversity gradient. This approach can help remove bias present in digitized herbarium data because 

they result from the compilation of many studies, each of which had its own taxonomic, regional, or 

ecological focus. To do so, I sampled from nine lowland forest sites across a 70-degree span of latitude in the 

Americas. At each site, I randomly chose ten plots, and sampled from ten trees within each plot for a total of 

nine hundred trees sampled. At each tree, I randomly chose a cardinal direction and placed a 20x40cm grid on 

the tree, collecting all lichens that fell within that grid. Thus, each site had the same amount of area surveyed 

for epiphytic lichen diversity. Lichens were identified to species in the lab. Data from systematic field 

sampling corroborate the latitudinal diversity gradient of (epiphytic) lichens. In a mixed effects model 

including tree and climate data, I found that this pattern is largely explained by host tree (substrate) diversity. 

With increasing land use change and impacts from climate change across the globe, it is increasingly 

important for us to set a baseline of patterns of diversity at large scales, as I did in my first two chapters, to 

then assess how these impacts are affecting the diversity of symbiotic organisms at different scales. For my 

third chapter, I applied my knowledge of lichen diversity to assess the impacts of three tropical forest 

restoration treatments on epiphytic lichens. The natural regeneration treatment had a small cohort of lichen 

species likely specialized to the high light and dry environment. The plantation and nucleation treatments had 

a mix of light and shade tolerant species and experienced higher competition from epiphytic bryophytes. The 

overall highest diversity of epiphytic lichens was found in the nucleation treatment, supporting this as the 

combination of the most cost-effective strategy that restores the greatest amount of tropical biodiversity.

 
 

 

 
 
 
 
 
Copyright by 
KLARA SCHARNAGL 
2019 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

 

 

 

To the North Carolina woods, 

And to Lynn Margulis, 
For your inspiration. 

Thank you. 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 
 
 
 
 

v 

ACKNOWLEDGEMENTS 

 

 

To my advisor, Alan Prather. Thank you for all of your guidance and wisdom, and thank you most of all for 

inviting me to join your lab even with all of my wild ideas. 

To my committee: Gary Mittelbach, Robert Lücking, Marjorie Weber, and Alan Fryday. Gary, thank you for 

all of your kind words and thoughtful feedback throughout this process, and for staying on my committee 

into retirement. Alan, thank you for all of the help with lichens and knowledge of lichen biology, thank you 

for help with herbarium specimens, and thank you also for staying on my committee into retirement. 

Marjorie, thank you for including me in your lab meetings, thank you for all of your feedback and help with 

my many questions, and thank you for your positivity and encouragement. Robert, thank you for being an 

important mentor in my life even before I began my PhD, thank you for all of your extensive feedback on 

methods and writing, thank you for all of the assistance with lichen identification for my dissertation as well 

as multiple side projects. 

To Douglas Schemske, thank you for serving on my committee during the formative years, thank you for all 

of the insight you provided as I planned my project. 

To Diane Ebert May, thank you for inviting me to join your amazing long-term alpine tundra project, and 

thank you for your mentorship and energy throughout my journey. Thank you for teaching me to look up. 

To my collaborators Karen Holl and Zak Zahawi, thank you so much for inviting me to work in your long-

term forest restoration plots, and thank you for all of your support and feedback. 

I would like to thank everyone at the Michigan State University Genomics Core for answering all of my 

questions and for helping me every step of the way in preparing my samples for Illumina sequencing. 

To Manuela Dal Forno, for taking the time to help me process and analyze a large sequence dataset, and for 

collaborating with me on the work investigating specificity within the lichen symbiosis. 

To Syrena Whitner, Robby Palazzolo, Drew Guthrie and Alex Blair, thank you for your assistance in the 

laboratory, for your independence and energy, and for your enthusiasm in learning about lichens. To Syrena, 

 

vi 

thank you for your dedication to working on specificity in the lichen symbiosis, and for your positive energy 

throughout. 

To Maren Friesen, thank you for connecting me with Alan Prather and encouraging me to apply to MSU. 

To Ekaphan (Bier) Kraichak, thank you for your friendship, your wonderful laugh, and for countless emails 

helping me through statistics and R. 

To Lynika Strozier, thank you for teaching me about lichen DNA extraction and PCR techniques, and thank 

you for your patience and your amazing attitude about life. 

To Eric von Wettberg, Suzanne Koptur, and Krish Jaychandran, my master’s thesis committee; thank you for 

your advice, enthusiasm, and for teaching me so much about science. 

To Toby Spribille, thank you for your mentorship, friendship, and inspiration. Thank you for inviting me to 

give a seminar, and thank you for your help with field work. 

To Matt von Konrat, Betsy Arnold, and Michelle Afkhami - thank you for your guidance, enthusiasm and 

support as I considered the next step in my career. 

To Nick Talbot, thank you for your shared enthusiasm in the lichen symbiosis, and for inviting me to the 

dream postdoc. 

To my parents, Gretchen and Robert Scharnagl, words cannot express my gratitude. Thank you for 

supporting me (mentally, spiritually, physically, and otherwise). Thank you for all of the brainstorming 

sessions and ideas, thank you for the questions. Thank you for believing in me. Thank you for the love. 

To Matthew Chansler, labmate, classmate, roommate, conference buddy, field assistant and best friend, thank 

you for all of your support, thank you for your perspective, thank you for being there for me. 

To Suzy Will-Wolf, Larry St Clair, Steve Leavitt, Joel Mercado Diaz, James Lendemer, Bruce McCune, and 

Erin Tripp, thank you for all of your support along my lichenological journey. 

To all of my former roommates and dear friends - Matthew Kolp, Kileigh Welshofer, Matthew Farr, Susan 

Gordon, and Erika LaPlante - thank you for all of the fun, thank you for the moral support, thank you for the 

long conversations about science, thanks for listening, and thank you for taking care of my cats while I 

traveled. 

 

vii 

To my friends - Nik McPhereson, Charlotte Soestini, Chrissy McTavish, Carina Baskett, Chase ONiell, 

Michael Foisy, Bruce Martin, Eleanor Ritter, Caroline Edwards, Bethany Moore, Joelyn de Lima, Kelsey 

Reider, Michael Britton, Erik Lokensgard, Emily Warschefsky, Geoff Zahn, Courtney Larson, Connie Rojas, 

and many many others - thank you for your friendship, and thank you so much for all of your acts of 

kindness, large and small. 

 

For access to, orientation to, and permits with field sites, we thank the Center for Tropical Forest Science, the 

Organization for Tropical Studies, the Aurora Research Institute, the US Forest Service, and the Florida Park 

Service. 

For their assistance with orientation to the field site, permitting, and navigating around Peru, we thank 

Roxana Arauco, Veronica Chavez, Cesar Flores, Kelsey Reider, and Eimy Rivas-Plata. For assistance with 

permits in Peru and agreement to house duplicate specimens, we thank Angel Ramirez and Dra. Magdalena 

Pavlich. For field assistance provided at Cocha Cashu, we thank Cesar Flores and Simona Clauschnitzer. 

For assistance with permits and agreement to house duplicate specimens, we thank Valencia Reyes Luis 

Renato. For field assistance in Ecuador and at Yasuni, we thank Ricardo Zambrano. 

For assistance with site access in Costa Rica, we thank Carlos de la Rosa. For permissions to use the Bosques 

plots, we thank Robin Chazdon. For orientation to the Bosques plots and field assistance, we thank Jeanette 

Paniagua, Bernal Paniagua, Enrique Salicetti, and Michelle Thompson. 

For permit assistance in Mexico, we thank Marusa Herrera Campos. For orientation at the Los Tuxtlas field 

station, we thank Rosamond Coates Lutes. 

We thank Emily Warschefsky for her field assistance at Fakahatchee Strand Preserve State Park, and we thank 

Matthew Chansler for his field assistance in Nantahala National Forest.  

For orientation to the Harvard Forest permits and site, we thank Audrey Barker-Plotkin. 

For orientation to and field assistance with the boreal site in British Columbia, we thank Toby Spribille. 

For assistance in preparing for the field at the Scotty Creek site, we thank Jennifer Baltzer and Katherine 

Standen. For orientation to the Scotty Creek site, we thank Katherine Standen and Jenna Rabley.  

 

viii 

To Anna Scharnagl, thank you for feedback and edits on many manuscripts, thank you for your collaboration, 

and thank you for your field assistance at Scotty Creek. 

For assistance in access to field sites, orientation to forest restoration plots, and identification of trees, thanks 

to Juan Abel Rosales, Hafet Rosales, and Leland Werden. Thanks to Chase Mendenhall and Andy Kulikowski 

for providing forest buffer data. 

 

Thanks to the following research funding sources: OTS and the Francis J. Bossuyt Memorial 

Fellowship, the Center for Tropical Forest Science – Forest Global Earth Observatory Research Grants 

Program, NSF grant DEB 14-56520, and the Michigan State University Ecology, Evolutionary Biology and 

Behavior Program, and the Paul Taylor funds. 

Thanks to the following funding sources: the Dr. Marie L Farr Graduate Fellowship, the Natural Sciences 

Dissertation Continuation and Completion Fellowships, and the Natural History Collections Internship. 

 

Thanks to the National Science Foundation Doctoral Dissertation Improvement Grant (NSF 17-01736), 

which made much of this work possible. 

 

 

A very special thanks the folks who began it all – to Thorsten Lumbsch, Todd Widhelm, and Matthew 

Nelsen, who introduced me to and inspired my passion for lichens at The Field Museum. To Rick Seavey and 

Jean Seavey, thank you for teaching me about lichens and for sharing your enthusiasm for lichens with me. 

Thank you also for serving as wonderful mentors and friends throughout. 

 
 
 
 
 
 
 
 

ix 

 
 

 

TABLE OF CONTENTS 

 
 
 
 

 

LIST OF TABLES………………………………………………………………………………………....xii 
 
LIST OF FIGURES……………………………………………………………………………………......xiii 
 
CHAPTER ONE: Digitized herbarium data support a latitudinal diversity gradient in New World lichens…1 
INTRODUCTION………………………………………………………………………………...1 
 
 
METHODS………………………………………………………………………………………..4 
Data……………………………………………………………………………………….4 
 
 
Do lichenized fungi follow a latitudinal diversity gradient?...........................................................4 
 
 
What are the likely environmental drivers of lichenized fungal richness across a latitudinal 
gradient?................................................................................................................................................6 
Do data from digitized herbarium collections show the same species richness patterns as 
other data sources such as regional checklists?...............................................................................6 
RESULTS………………………………………………………………………………….………7 
Do lichenized fungi follow a latitudinal diversity gradient?..........................................................7 
What are the likely environmental drivers of lichenized fungal richness across a latitudinal 
gradient?................................................................................................................................................7 
Do data from digitized herbarium collections show the same species richness patterns as 
other data sources such as regional checklists?...............................................................................7 
DISCUSSION……………………………………………………………………………………..8 
CONCLUSION…………………………………………………………………………………..11 
APPENDIX… ……………………………..…………………………………………………….12 
WORKS CITED………………………………………………………………………………….17 

 
 
 
 
 
CHAPTER TWO: Testing the latitudinal diversity gradient of New World epiphytic lichens using a 
systematic field sampling approach……………………………………………………………….………..25 
INTRODUCTION………………………………………………………………………………25 
 
 
METHODS………………………………………………………………………………………28 
Site Selection……………………………………………………………………………..28 
 
 
Field Sampling…………………………………………………………………………....28 
 
 
 
 
Lichen Identification……………………………………………………………………..29 
 
 
Analyses………………………………………………………………………………….30 
RESULTS……………………………………………………………………………………........32 
 
Latitudinal Patterns in Lichen Diversity…………………………………………………..32 
 
 
 
 
Drivers of Lichen Diversity……………………………………………………………....33 
 
 
A Preliminary Look within the Lichen Symbiosis………………………………………...33 
DISCUSSION…………………………………………………………………………………....34 
 
 
CONCLUSION………………………………………………………………………………….37 
APPENDIX.... ……………………………...…………………………………………………....38 
 
 
WORKS CITED…………………………………………………………………………………47 

 

x 

 
CHAPTER THREE: Lichen diversity across tropical forest restoration strategies………………………...53 
INTRODUCTION……………………………………………………………………………....53 
 
METHODS……………………………………………………………………………………...55 
 
 
 
Study Sites………………………………………………………………………………55 
Field Surveys of Lichens………………………………………………………………...56 
 
 
 
 
Analyses…………………………………………………………………………………57 
 
RESULTS………………………………………………………………………………………..58 
DISCUSSION…………………………………………………………………………………...60 
 
APPENDIX……………………………………………………………………………………..65 
 
 
WORKS CITED…………………………………………………………………………………76 
 

 

xi 

LIST OF TABLES 

 
 
 

Table 1.1 Comparison of Generalized Additive Models (GAMs) with a negative binomial distribution of the impact of 
latitude and climate data on rarefied species richness per unit area………………………………………………….13 
 
Table 1.S1 Pearson’s correlations between species richness or rarefied species richness (SR) of lichenized fungi and 
latitude, number of records, and environmental variables…………………………………………………………13,14 
 
Table 2.1 The nine sites used in this study; the type of long term research or protection status of the forest; the latitude 
and longitude; the country in which the site was located; and the method or dataset by which tree species were identified. 
……………………………………………………………………………………………………………………….39 
 
Table 2.2 Climate models for predicting lichen growth forms along a latitudinal gradient. Significance levels of each 
variable are reported from the generalized linear models and from the post-hoc analysis of deviance of the generalized 
linear models………………………………………………………………………………………………………39,40 
 
Table 2.S1 Coefficients of correlation and significance tests between latitude and measures of epiphytic lichen diversity. 
………………………………………………………………………………………………………………………40 
 
Table 3.1 IEC scores for Thelotremataceae, for combined Thelotremataceae, Porinaceae and Letrouitiaceae, and the 
ratio of lichen species in families indicating exposed or disturbed habitats to lichen species in families indicating forest 
continuity. Higher IEC scores mean more ecological continuity, whereas a higher indicator ratio means less continuity 
and more disturbance…………………………………………………………………………………………………66 

 

Table 3.S1 The number of morphospecies and number of individual lichens observed per lichenized fungal 
family………………………………………………………………………………………………………………66,67 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 

xii 

 
 

 

LIST OF FIGURES 

 
 
 

Figure 1.1 Rarefied species richness divided by log land area plotted against latitude. Extent of the tropics is marked by 
vertical dashed grey lines. One southern point (latitude = -60) was removed due to the small amount of land area and the 
fact that the log-area slope parameter changes between small and large values…………………………………………14 

Figure 1.2 (A, above) Plot of lichenized fungal species richness per country using all data (non-georeferenced) versus just 
georeferenced data from the Consortium of North American Lichen Herbaria (CNALH) database. (B, below) 
Lichenized fungal species richness per unit area based on lichen checklist data by country versus georeferenced data 
from CNALH………………………………………………………………………………………………………14,15 

 

 

Figure 1.3 Species richness per unit area of lichenized fungi according to country (and US state) checklist data plotted 
against latitude, as determined by country and US state centroids……………………………………………………....15 

Figure 1.S1 The observed species richness in the herbarium specimen data plotted against latitude. Extent of the tropics 
is marked by vertical dashed grey lines…………………………………………………………………………………16 

 

 

Figure 1.S2 Rarefied species richness in the herbarium specimen data plotted against latitude. Extent of the tropics is 
marked by vertical dashed grey lines…………………………………………………………………………………...16 
 
Figure 2.1 Sampling schematic. Nine sites (red circles) were sampled along a latitudinal gradient. Ten plots (green circles) 
were sampled at each site. Ten trees were sampled in each plot; a randomly selected focal tree (black rectangle), and its 
nine nearest neighbors (brown rectangles)……………………………………………………………………………..40 
 
Figure 2.2 Epiphytic lichen species richness per site from nine forest sites along a latitudinal gradient. Line is fit from 
generalized linear model with 95% confidence intervals……………………………………………………………......41 
 
Figure 2.3 Lichen beta diversity (dissimilarity) plotted against latitude…………………………………………………41 
 
Figure 2.4 (a) Left, The proportion of two-dimensional or crust-like growth forms (light blue) to three-dimensional 
growth forms (dark blue) across latitudes. (b) Right, The proportion of asexual (light green) reproductive modes to 
sexual reproductive (green) modes across latitudes……………………………………………………………………42 
 
Figure 2.S1 Epiphytic lichen species to genus ratio plotted against latitude……………………………………………42 
 
Figure 2.S2 The influence of face (cardinal direction) on lichen species richness per tree……………………………...43 
 
Figure 2.S3 Similarity of lichen species from one tree to another within a plot averaged across all plots within a site, 
plotted against latitude………………………………………………………………………………………………...43 
 
Figure 2.S4 Interaction network between mycobionts (8 species) and photobionts (5 ASVs) at the North Carolina site..44 
 
Figure 2.S5 Interaction network between mycobionts (7 species) and photobionts (3 ASVs) at the Harvard Forest site. 
………………………………………………………………………………………………………………………..44 
 
Figure 2.S6 Interaction network between mycobionts (4 species) and photobionts (7 ASVs) at the Scotty Creek site…44 
 

 

xiii 

Figure 2.S7 (A, above) Specificity index of mycobionts across our three northern sites. (B, below) Specificity index of 
photobionts across our three northern sites. Lines represent standard error…………………………………………..45 
 
Figure 2.S8 Differences in community composition of photobiont ASVs. Symbiont ID is provided as a combination of 
the highest BLAST hit from NCBI and a unique amplicon sequence variant (ASV) number. There is no overlap of ASVs 
across the three sites………………………………………………………………………………………………….46 

 

Figure 3.1 Lichen morphospecies richness per tree within each forest restoration treatment…………………………67 
 
Figure 3.2 Percent cover per tree of lichens (triangles) and bryophytes (circles)……………………………………...68 

Figure 3.3 Total lichen morphospecies richness at the 0.25 ha scale…………………………………………………69 

 

 

Figure 3.4 (a) Lichen morphospecies richness on each tree species across plots. (b) Lichen percent cover on each tree 
species across plots………………………………………………………………………………………………….70 

 

Figure 3.5 Effect of elevation (a) and surrounding forest cover at 100-150m (b) on lichen morphospecies richness at the 
0.25 ha level. Line of fit based on GLMER models………………………………………………………………….71 

 

Figure 3.6 (a) Ratio of lichens containing cyanobacteria to lichens containing green algal photobionts across treatments. 
(b) Ratio of three-dimensional macro lichens to two-dimensional crust lichens across treatments…………………..72 

Figure 3.S1 Ordination plot of lichen communities, colors represent treatments……………………………………73 

 

Figure 3.S2 Ordination plot of lichen communities, colors represent elevation……………………………………..74 

 

Figure 3.S3 Ordination plot of lichen communities, colors represent surrounding forest cover…………………….75 
 

 

 

xiv 

CHAPTER ONE: 
Digitized herbarium data support a latitudinal diversity gradient in New World lichens 
 

INTRODUCTION 

The latitudinal diversity gradient (LDG) is a pattern of increasing biological diversity from the poles to the 

equator. This phenomenon has been recognized since the time of Humboldt (1807), Darwin (1859) and 

Wallace (1878), and has been demonstrated across a number of taxa, both marine and terrestrial (Hillebrand 

2004). Over the 200 years that the LDG pattern has been researched, numerous hypotheses have been 

proposed to explain it (Pianka 1966, Fine 2015). These fall broadly into five categories: spatial or null 

mechanisms (e.g., Colwell & Lees 2000, but see Currie & Kerr 2008), mechanisms involving climate and 

metabolic energy balance (e.g., Hawkins et al. 2003), evolutionary or historical mechanisms (e.g., Mittelbach et 

al. 2007), time-integrated species-area effects (e.g., Fine & Ree 2006), and biotic mechanisms such as the 

biotic interactions hypothesis (e.g., Schemske et al. 2009, Smith et al. 2012). These mechanisms are not 

mutually exclusive, and to date no consensus has been reached regarding the driving mechanism of the LDG 

(Brown 2014, Schemske & Mittelbach 2017). More investigation of both taxonomic and ecological groups at 

broader geographic scales is needed to determine whether this lack of consensus would be resolved by 

investigating more organisms in more detail, or whether it is the case that each taxonomic group that follows 

the LDG might have its own particular underlying mechanisms. 

 

Studies establishing the latitudinal diversity gradient often involve a synthesis of data from a variety of 

sources, including species range maps, state or regional floras, checklists, museum or herbarium collections, 

observation data, georeferenced molecular data, direct field sampling, and reports from the literature (Qian & 

Ricklefs 2007, Archibald et al. 2010, Rolland et al. 2014, Visser et al. 2014). Some studies, to enhance the 

robustness of their underlying data, combine some of the data sources listed above. For example, Smith et al. 

(2016) used a combination of GBIF (Global Biodiversity Information Facility) and GenBank data to test the 

accuracy of taxonomic identification while investigating global patterns of Usnea longissima. Recently, 

digitization efforts have made the tremendous resource of herbarium specimen data available for the 

 

1 

investigation of broad-scale patterns of species richness such as the LDG (Holt et al. 2015, McLean et al. 

2016, James et al. 2018).  

 

The majority of studies on both the patterns and mechanisms of the LDG had a particular emphasis on 

plants and animals and a lack of data on fungi and other microorganisms. Taxa for which the LDG has been 

demonstrated include woody angiosperms (Barthlott et al. 2007, Kerkhoff et al. 2014), birds (Hawkins et al. 

2007), swallowtails, (Condamine et al. 2012), amphibians (Pyron & Wiens 2013) and marine bivalves 

(Jablonski et al. 2013), among others (Fischer 1960). Some possible exceptions include conifers (Fragnière et 

al. 2015) and mosses (Mateo et al. 2016). Within the fungi, foliar fungal endophytes (Arnold & Lutzoni 2007) 

and coprophilous (dung-loving) fungi (Richardson 2001) follow the LDG, while ectomycorrhizal fungi 

(Tedersoo & Nara 2010) and indoor fungal communities (Amend et al. 2010) are cited as exceptions. More 

work is needed on whether different fungal clades or functional groups follow the LDG and why.  

 

One particularly interesting system in which to investigate the latitudinal diversity gradient are lichenized 

fungi, a highly diverse and polyphyletic group defined by the nutritional habit in the form of symbioses with 

algae or cyanobacteria (Lücking et al. 2017, Lücking & Nelsen 2018). Lichens are a symbiotic association 

between a fungus and one or more photosynthetic partners, either green algae or cyanobacteria. Lichenized 

fungi are obligate symbionts, lending themselves to tests of biotic interactions hypotheses of the LDG. 

Lichens are ubiquitous, found in every terrestrial habitat on earth -- from tidelines to mountaintops, from 

deserts to rainforests, from under the ice in Antarctica to ground cover in savannas (Nash 2008). Their global 

distribution and symbiosis make them great candidates for LDG studies. 

 

Though lichenized fungi have been studied for centuries (Linnaeus 1767, Acharius 1799, Tuckerman 1882), 

the relationship between diversity and latitude has not yet been investigated in detail in lichens at a global 

scale. Prior studies of lichen diversity suggest that patterns of lichen diversity may differ depending on the 

geographic extent of the study, the spatial and the taxonomic scales investigated. For example, a U-shaped 

 

2 

pattern of diversity along the western coast of the United States was found using lichen herbarium collections 

data (Holt et al. 2015), while a reverse latitudinal pattern of diversity was found across North America using 

propagule sequence data from dust collected from door frames (Tripp et al. 2016). In a study across the 

Atlantic Forest of Brazil, LDG patterns varied by lineage: Trypetheliaceae and Graphidaceae followed more 

of a classic LDG, whereas species richness values peaked outside of the tropics for Lobariaceae and 

Parmeliaceae (Menezes et al. 2018).  

 

There are several reasons to hypothesize that lichenized fungi will not display LDG patterns. The first is their 

symbiotic nature. Within the lichen symbiosis, the photosynthetic partner provides carbohydrates to the 

fungal partner, which is usually dominant in biomass, leading to the characteristic slow growth in lichens, 

though this varies by species (Reiter et al. 2008). This symbiotic balance also leads lichens to perhaps prefer 

environmental conditions conducive to photosynthesis (Will-Wolf et al. 2004) - medium temperatures, ample 

light, and sufficient humidity - conditions which are not actually met in the hotter wetter climates of the 

tropics. Lichens also fill a variety of niches - growing on bark, leaves, soil, rocks, sand, and on many manmade 

materials as well (Ellis 2012). Lichens are poikilohydric, capable of enduring extremely stressful conditions in 

the desiccated stage (Nash 2008), enabling them to be the main colonizers of extreme habitats such as deserts 

and the rocky nunataks of Antarctica (Seymour et al. 2005, Raggio et al. 2016). Thus, in this study, we asked 

whether lichenized fungi follow a classic latitudinal gradient despite the ancient nature of the lichen symbiosis, 

its terrestrial ubiquity, and the photosynthesis requirements combined with the ability of many lichens to 

tolerate extreme environmental conditions. 

 

In this study, we consolidated and analyzed large-scale herbarium specimen data across North and South 

America to investigate latitudinal patterns of New World lichenized fungi. Specifically, we asked: (1) Do 

lichenized fungi follow a latitudinal diversity gradient? (2) What are the likely environmental drivers of 

lichenized fungal species richness across a latitudinal gradient? and (3) Do data from digitized herbarium 

collections show the same species richness patterns as other data sources such as regional checklists?  

 

3 

METHODS 

Data 

To assess latitudinal patterns of lichen diversity using collections data, we gathered data from the following 

repositories: the Consortium of North American Lichen Herbaria (CNALH), the Global Biodiversity 

Information Facility (GBIF), and the Institutos Nacionais de Ciência e Tecnologia in Brazil (INCT). The 

focus of these data repositories is on North American, global, and South American records, respectively. 

Since CNALH contains only lichen collection data, we simply used a bounding box search for the Americas; 

from 168W to 26W and from 72S to 83N. We used the same bounding box for GBIF and INCT; however, 

since these repositories contain more than just lichen data, we filtered by taxonomic group, using classes, 

orders, families, and genera that contain only lichenized fungi. The list comprised Lecanoromycetes, 

Arthoniomycetes, Lichinomycetes, Monoblastiales, Pyrenulales, Strigulales, Trypetheliales, Verrucariales, 

Lyrommataceae, Acantholichen, Cora, Corella, Dictyonema, Lichenomphalia and Multiclavula. Within each repository 

we filtered the search by specimen data only, excluding data based solely on observations with no 

accompanying specimen.  

 

The compilation from all three repositories resulted in a dataset containing 991,098 records. All data filtering 

and analyses were conducted in R (version 3.3.2, 2016-10-31). We removed records with incomplete or 

missing georeference data. We filtered out redundant records (the same records from multiple data sources, 

e.g. present in both GBIF and CNALH) using the ‘duplicated’ function in R and verified that this removal 

did not impact the number of species, only the number of records. The resulting filtered dataset contained 

712,798 records. 

 

Do lichenized fungi follow a latitudinal diversity gradient? 

To assess latitudinal patterns, we used the ‘floor’ function in R to divide the map into one-degree latitudinal 

bands. We converted our filtered dataset to a species-by-latitude matrix, with latitudinal bands as rows and 

species as columns. We created species ranges by filling in species presence values between the maximum and 

 

4 

minimum latitude for which a species was recorded. This approach assumes that a lack of records for a given 

species collected in an area that falls within the min and max distribution limits represent missing data rather 

than true absence. In addition, this approach allows only for interpolation rather than extrapolation of species 

distributions, meaning that missing data at the extremes of the distribution will not be captured. We used this 

interpolated species-by-latitude matrix for our analyses.  

 

We then binned the one-degree bands of our species-by-latitude matrix into 3-degree bands; three degrees 

being considered an intermediate amount of coverage compared to other LDG studies (Hawkins et al. 2003, 

Jablonski et al. 2013, Kerkhoff et al. 2014). By binning latitude into 3-degree bands, we mitigated the zero-

bias that may have resulted from latitudinal bands for which no lichen records exist. 

 

We first assessed the relationship between species richness and latitude using a Pearson’s correlation using the 

‘cor.test’ function in R. We also assessed the relationship between the number of species and the number of 

records using a Pearson’s correlation. Because there was a strong correlation between number of records and 

species richness (Table S1), we rarified our data to estimate the number of species per latitudinal band given 

equal sampling effort across bands. We ran a rarefaction analysis using the ‘vegan’ package in R with the 

default parameters in the function ‘rarefy.’ We used these rarefied species richness values for the remainder of 

our analyses unless otherwise noted. We used a Pearson’s correlation to assess the relationship between the 

rarefied species richness values and latitude. We also assessed the relationship between the rarefied number of 

species and the log land area. Rarefied species richness was significantly positively correlated with land area; 

because we were interested in comparing standardized species richness across latitudes, we calculated species 

richness per unit area for each 3-degree latitudinal band, and used these values in the remainder of our 

analyses. 

 

 

 

 

5 

What are the likely environmental drivers of lichenized fungal richness across a latitudinal gradient? 

We assessed the potential impact of the climatic variables of mean annual temperature, annual precipitation, 

annual temperature range, and precipitation of the driest quarter on rarefied species richness per unit area. We 

included the annual temperature range and precipitation of the driest quarter to investigate the impact of 

extremes in either temperature or precipitation on lichenized fungal richness. All bioclim data 

(https://www.worldclim.org/) were downloaded at the 2.5 minutes resolution using the ‘raster’ package in R. 

We placed rectangular polygons over the map at three-degree latitudinal intervals, extracted the bioclim data 

from within those polygons, and calculated the means for each of the climate variables. We first assessed 

relationships between each of our five climatic factors individually with rarefied species richness using 

Pearson’s correlation, with a Bonferroni adjustment. Due to the nonlinear nature of the relationships in the 

data, we then assessed the impacts of the climatic variables using generalized additive models with a negative 

binomial distribution. Poisson is the typical distribution for count data such as species richness; however, our 

data were overdispersed using this method. 

 

Do data from digitized herbarium collections show the same species richness patterns as other data sources such as regional 

checklists? 

We compared country checklist data compiled by Feuerer (2013) and total and georeferenced data from 

CNALH. We used just CNALH data to compare full lichen lists at the country level, rather than searching 

the other databases by orders, families, and genera. For this comparison, we downloaded data from the 

Consortium of North American Lichen Herbaria by country for all North, Central and South American 

countries. CNALH data were assigned to latitude by using state centroids for U.S. states and country 

centroids elsewhere. We used a Pearson’s correlation to assess the relationship between the CNALH non-

georeferenced and georeferenced datasets. We then calculated species richness per unit area for the CNALH 

and checklist data, and ran a Pearson’s correlation to determine the similarity in patterns of species richness 

from the two data sources. Finally, we used a generalized additive model with a negative binomial distribution 

to assess the impact of latitude on species richness per unit area from the checklist data. 

 

6 

RESULTS 

Do lichenized fungi follow a latitudinal diversity gradient? 

New World lichen species richness shows a pronounced and significant (0.0024) latitudinal diversity gradient, 

with rarefied richness declining with increasing latitude in both hemispheres (Figure 1; observed species 

richness plotted in Figure S1). The peak in values is within the tropics, north of the equator.  

 

What are the likely environmental drivers of lichenized fungal richness across a latitudinal gradient? 

Using model comparison of GAMs of our climate predictor variables, the best model, based on R-squared 

values, was the model that included the full set of bioclim variables (mean annual temperature, annual 

precipitation, annual temperature range, and precipitation in the driest quarter) as well as latitude (Table 1). 

This model explained up to 73% of the variation in the rarefied species richness of lichenized fungi across a 

latitudinal gradient. The generalized additive model that included the means of temperature and precipitation 

in addition to latitude explained 69% of the variance in rarefied species richness of lichenized fungi. None of 

the smooth terms in the generalized additive models were significant. 

 

Do data from digitized herbarium collections show the same species richness patterns as other data sources such as regional 

checklists? 

Comparison of the checklist, total and georeferenced datasets revealed that species richness values were 

consistently lowered when non-georeferenced specimens were removed from the dataset. However, the non-

georeferenced and georeferenced CNALH collections data were highly correlated (Figure 2A, Pearson’s 

correlation coefficient = 0.945, t = 23.095, p<<0.0001). Species richness per unit area from the country 

checklist data had a much weaker but significant correlation with species richness per unit area from the 

georeferenced collections data (Figure 2B, Pearson’s correlation coefficient = 0.4003, t = 3.495, p = 0.001), 

and actually had higher species richness than either non-georeferenced or georeferenced collections data for 

some countries (Argentina, Venezuela, Cuba, Panama, Guyana, Colombia, Uruguay and Nicaragua). Checklist 

data had higher species richness than just the georeferenced collections data for Costa Rica. 

 

7 

Latitude of the centroid was not a significant predictor of species richness per unit area from the country 

checklist data in the generalized additive model (Chi-squared=1.647, p=0.554, model R-squared=0.0523). 

Thus, the checklist data alone do not support a latitudinal diversity gradient of lichenized fungi (Figure 3).  

 

DISCUSSION 

This is the first study to assess a pattern of lichenized fungal richness across both hemispheres in the 

Americas. We compiled a large data set encompassing all lichenized fungi across two continents, as well as 

associated bioclimatic data. We found strong support for a latitudinal diversity gradient: rarified richness of 

lichenized fungi per area was highest near the equator (Figure 1). Including bioclimatic data revealed both 

temperature and precipitation as having strong predictive power of lichenized fungal diversity. These climatic 

correlations are similar to those found for other taxonomic groups that follow the latitudinal diversity 

gradient (Fischer 1960).  

 

Lichenized fungal rarefied species richness was significantly correlated with both mean annual temperature 

and land area (Table S1). Mean annual temperature itself is correlated with latitude and is a main component 

of the climate and energy hypotheses of the LDG (Belmaker & Jetz 2015), and we would expect a greater 

area to support a greater number of species (Connor & McCoy 1979). Notably, the model that explains the 

greatest amount of variation in the rarefied species richness per unit area of lichenized fungi is the one that 

includes all of the climate variables we considered, in addition to latitude. Studies of lichenized fungal richness 

along other environmental gradients such as altitudinal gradients, frequently reveal a hump-shaped pattern of 

richness from low to high altitude, however the pattern often changes above the treeline (Grytnes et al. 2006, 

Baniya et al. 2010). This reveals a complex of interacting drivers including substrate and microclimatic factors 

(Nascimbene & Marini 2015). Extreme environmental conditions, such as steep seasonal swings in 

temperature or extreme periods of dry, may not explain lichenized fungal richness on their own, but may 

nevertheless play a role in driving lichenized fungal richness along a latitudinal gradient. Lichens are able to 

tolerate extreme conditions, including salinity (Delmail et al. 2013), freezing temperatures (Kappen et al. 

 

8 

1996), dryness (Kranner et al. 2008), and even the extremes of the vacuum of space (Brandt et al. 2015). The 

current consensus is that the LDG is driven by a number of interacting ecological and evolutionary factors 

(Jablonski et al. 2017), which should be incorporated into future investigations of the lichen LDG. 

 

The raw species richness from the three data repositories was strongly and significantly correlated with 

number of records, with a high peak north of the equator, indicating a bias for collecting outside of the 

tropics. A potential temperate bias in lichen collection and digitization efforts is supported by the number of 

resources available for North American lichenized fungi (Brodo et al. 2001, Nash et al. 2007), while the 

number of resources available for lichenized fungi in the New World tropics remain fairly decentralized, with 

species lists, reports of new records, and keys spread across individual papers. A northern temperate 

collecting bias is prevalent in other groups of fungal symbionts, including arbuscular mycorrhizal fungi (Öpik 

et al. 2010) and Trichomycete gut fungi (Lichtwardt 2012), supporting the need for further sampling in the 

tropics as we continue to investigate global biogeographical patterns in these groups. As evidenced by the 

checklists having higher species richness than collections data in many tropical countries, there is also a need 

for more digitization of herbarium collections data. Furthermore, as indicated by the non-georeferenced data 

from CNALH having higher species richness values than the georeferenced data, there is a need for more 

georeferencing of specimen data. A previously cited exception to the LDG, ichneumonid wasps (Sime & 

Brower 1998), resulted from a lack of data in the tropics (Veijalainen et al. 2012), rather than an actual lack of 

species. We therefore stress the importance of further tropical sampling, and digitization of data from these 

tropical collections. 

 

Herbarium collections are critical resources in studies of taxonomy (Bebber et al. 2010), phenology (Robbirt 

et al. 2011), and biogeography (Wollan et al. 2008). Herbarium collections are nevertheless underutilized; as of 

2013, less than 2% of herbarium specimens worldwide had been used in these studies (Lavoie 2013). Studies 

of potential collection bias in herbarium collections reveal that these can be overcome with the incorporation 

of field data or expert consultation (Loiselle et al. 2008), emphasizing the usefulness of these resources even 

 

9 

when biases exist. While inclusion of non-georeferenced collections data in our analyses increased the number 

of lichenized fungal species per latitudinal band, non-georeferenced and georeferenced data followed the 

same pattern. However, discrepancies found between the country checklist data and the georeferenced 

collections data warn that some collections data may be incomplete. Considering the countries for which 

checklist data had a higher species richness than either non-georeferenced or georeferenced collections data, 

the tropics and southern hemisphere are likely still underrepresented in digital repositories of specimen data.  

 

In meta-analyses of the generality of the latitudinal diversity gradient across taxa, the LDG was shown to be a 

pervasive pattern, though weaker than expected in slope for some taxa (Hillebrand 2004, Kinlock et al. 2017). 

These meta-analyses included studies of latitudinal ranges from as small as 10 degrees to global spans. 

Previous work on the latitudinal diversity gradient in lichenized fungi outside of the tropics had revealed 

patterns incongruent with the classic pattern followed by many taxa that peak in richness in the tropics (Holt 

et al. 2015, Tripp et al. 2016). These more geographically restricted studies indicate that at smaller scales other 

drivers of lichen diversity may be important and should be explored more 

 

Previous studies addressing a temperate-tropical LDG in lichens and including the tropics, were limited to 

one of the hemispheres and used either only checklist data (Lücking et al. 2011; north of the equator) or a 

limited set of taxa (Menezes et al. 2018; south of the equator). These studies of lichen diversity which 

incorporate or focus on the tropics show species richness increasing towards the equator (Lücking et al. 

2011), though this depends on the taxonomic group (eg. Menezes et al. 2011: Graphidaceae versus 

Parmeliaceae). We emphasize here the importance of including both hemispheres, particularly including the 

tropics, when investigating a latitudinal diversity gradient. 

 

With each new survey, lichenologists are finding undescribed species and high species richness of lichenized 

fungi in both tropical (Lücking et al. 2014a) and extratropical (Dillman et al. 2012, Fryday & Øvstedal 2012) 

environments. Tropical lichen floras are not as developed as temperate lichens in terms of taxonomic 

 

10 

revisions and determination of cryptic species (Lücking et al. 2014b), which suggests that the collections data 

used in this study may not only be influenced by a collecting bias, but by a taxonomic bias as well. However, 

we did not directly test for taxonomic biases in the current study. Lichenized fungi, and fungi more generally, 

lag behind other taxonomic groups in terms of digitized data availability (eg. plants, Allen et al. 2019). We 

suggest the need for more collecting of lichens, taxonomic work on lichens, and digitization of lichen 

specimen data, especially in the tropics, such that we can continue to investigate these large-scale questions of 

diversity and distributions with greater and greater precision.  

 

CONCLUSION 

Lichens are an ideal system for investigating the pattern and process of the LDG due to their terrestrial 

ubiquity, their niche breadth, and the fact that lichens are themselves biotic interactions. This is the first study 

of the latitudinal diversity gradient of lichenized fungi to encompass data from both the Northern and 

Southern hemispheres. We consolidated data from both the northern and southern hemispheres, controlling 

for collection effort and area. Rarefied species richness from herbarium collections data reveal a classic 

latitudinal diversity gradient in lichenized fungi. This gradient is predicted by climatic factors of temperature 

and precipitation, possibly supporting climate and energy hypotheses of the LDG. Potential taxonomic and 

geographic biases in the collections data will be improved with increased collecting and research of lichenized 

fungi in the tropics.  

 

 
 
 
 
 
 
 
 
 
 
 
 

 

11 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

APPENDIX 

12 

CHAPTER ONE TABLES AND FIGURES 
 
Table 1.1 Comparison of Generalized Additive Models (GAMs) with a negative binomial distribution of the impact of 
latitude and climate data on rarefied species richness per unit area. 

Model 

Variables 

R-squared(adj.) 

Latitude, Mean Annual Temperature, Mean 
Annual Precipitation, Annual Temperature 
Range, Precipitation in the Driest Quarter 

Latitude, Mean Annual Temperature, Mean 
Annual Precipitation 

Mean Annual Temperature, Mean Annual 
Precipitation, Annual Temperature Range, 
Precipitation in the Driest Quarter 

Mean Annual Temperature, Mean Annual 
Precipitation 

Lat_Climate 

Lat_Means 

Climate 

Means 

Latitude 

Latitude 

0.733 

0.695 

0.667 

0.198 

0.119 

 
Table 1.S1 Pearson’s correlations between species richness or rarefied species richness (SR) of lichenized fungi and 
latitude, number of records, and environmental variables. 

Variables 

Correlation 
Coefficient 

t-test 

p-value 

Bonferroni adjusted 
p-value 

Species Richness X 
|Latitude| 

-0.2659 

-1.851 

0.071 

0.142 

Species Richness X 
Number of Records 

0.8083 

9.211 

<<0.00001*** 

0.00002*** 

Rarefied Species 
Richness X 
|Latitude| 

Rarefied Species 
Richness X Land 
Area (log) 

Rarefied Species 
Richness X Mean 
Annual Temperature 

Rarefied Species 
Richness X Annual 
Precipitation 

Rarefied Species 
Richness X Annual 
Temperature Range 

 

 

-0.4935 

-3.81 

0.0004*** 

0.0024** 

0.7171 

6.9028 

<<0.00001*** 

0.00006*** 

0.4141 

3.0516 

0.0038** 

0.0228* 

0.2722 

1.8978 

0.064 

0.384 

0.089 

0.5994 

0.552 

1.00 

13 

Table 1.S1 (cont’d) 

Rarefied Species 
Richness X 
Precipitation in 
Driest Quarter 

-0.043 

-0.2887 

0.774 

1.00 

 
Figure 1.1 Rarefied species richness divided by log land area plotted against latitude. Extent of the tropics is marked by 
vertical dashed grey lines. One southern point (latitude = -60) was removed due to the small amount of land area and the 
fact that the log-area slope parameter changes between small and large values. 
 

Figure 1.2 (A, above) Plot of lichenized fungal species richness per country using all data (non-georeferenced) versus 
just georeferenced data from the Consortium of North American Lichen Herbaria (CNALH) database. (B, below) 
Lichenized fungal species richness per unit area based on lichen checklist data by country versus georeferenced data 
from CNALH. 
 
 

 

 
 
 
 
 
 
 
 
 
 
 
 

 

14 

Figure 1.2 (cont’d) 
 

 
Figure 1.3 Species richness per unit area of lichenized fungi according to country (and US state) checklist data plotted 
against latitude, as determined by country and US state centroids.  
 

 

 
 
 
 
 
 
 
 
 
 

 

 

15 

Figure 1.S1 The observed species richness in the herbarium specimen data plotted against latitude. Extent of the tropics 
is marked by vertical dashed grey lines. 
 

 
Figure 1.S2 Rarefied species richness in the herbarium specimen data plotted against latitude. Extent of the tropics is 
marked by vertical dashed grey lines. 
 

 

 
 
 
 
 
 
 

 

 

16 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

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Morphology, Distribution, Functional Ecology of Plants 203(1): 34-46 
 
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Robbirt KM, Davy AJ, Hutchings MJ, Roberts DL (2011) Validation of biological collections as a source of phenological 
data for use in climate change studies: a case study with orchid Ohprys sphegodes. Journal of Ecology 99: 235-241 
 
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Seymour FA, Crittenden PD & Dyer PS (2005) Sex in the extremes: lichen-forming fungi. Mycologist 19(2): 51-58 
 
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from butterflies. Journal of Animal Ecology 67: 367-399 
 
Smith BT, Bryson RW, Houston DD, Klicka J (2012) An asymmetry in niche conservatism contributes to the latitudinal 
species diversity gradient in New World vertebrates. Ecology Letters 15: 1318-1325 
 
Smith BE, Johnston MK, Lücking R (2016) From GenBank to GBIF: Phylogeny-based predictive niche modeling tests 
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doi:10.1371/journal.pone.0151232 
 
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Phytologist 185: 351-354 
 
Tripp EA, Lendemer JC, Barberán A, Dunn RR, Fierer N (2016) Biodiversity gradients in obligate symbiotic organisms: 
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Cassino, Boston, MA. 
 
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parasitoid wasp diversity in tropical forests. Proceedings of the Royal Society B 279: 4694-4698 
 
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diversity gradient for grasses. Global Ecology and Biogeography 23(1): 61-75 
 
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HERBARIUM COLLECTIONS CITATIONS 
Arthoniomycetes. GBIF.org (29th January 2018) GBIF Occurrence Download https://doi.org/10.15468/dl.6ivn6l 
 
Lecanoromycetes. GBIF.org (29th January 2018) GBIF Occurrence Download https://doi.org/10.15468/dl.hcd8mq 
 
Lichinomycetes. GBIF.org (29th January 2018) GBIF Occurrence Download https://doi.org/10.15468/dl.j0wlti 
 
Pyrenulales. GBIF.org (30th January 2018) GBIF Occurrence Download https://doi.org/10.15468/dl.5dag7d 
 
Trypetheliales. GBIF.org (30th January 2018) GBIF Occurrence Download https://doi.org/10.15468/dl.v8oxqz 

 

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Verrucariales.  GBIF.org (30th January 2018) GBIF Occurrence Download https://doi.org/10.15468/dl.iqarzp 
 
Cora. GBIF.org (30th January 2018) GBIF Occurrence Download https://doi.org/10.15468/dl.wdoowq 
 
Dictyonema. GBIF.org (30th January 2018) GBIF Occurrence Download https://doi.org/10.15468/dl.ninfk0 
 
Lichenomphalia. GBIF.org (30th January 2018) GBIF Occurrence Download https://doi.org/10.15468/dl.gb62lg 
 
Racodium. GBIF.org (30th January 2018) GBIF Occurrence Download https://doi.org/10.15468/dl.45ft61 
 
Consortium of North American Lichen Herbaria (CNALH). 2018. http//:lichenportal.org/portal/index.php. Accessed 
on February 5. 
 
Lecanoromycetes (INCT) Arizona State University Lichen Herbarium (ASU-Lichen), Herbário Irina Delanova Gemtchújnicov 
(BOTU), United States National Fungus Collections (BPI), Herbário da Fundação Universidade Federal de Mato Grosso do Sul 
(CGMS), Farlow Herbarium, Harvard University (FH), Herbario da Universidade Estadual de Feira de Santana (HUEFS), Bernard 
Lowy Mycological Herbarium (LSUM), Herbário do Museu da Pontifícia Universidade Católica do Rio Grande do Sul (MPUC), 
Botanical Collections (NHM-London-BOT), Herbário do Museu Nacional - Criptogamos (R-Criptogamos), Herbário Dom Bento 
José Pickel (SPSF), NMNH Extant Specimen and Observation Records (US-Fungi), Wisconsin State Herbarium (WIS) available at 
speciesLink network (http://inct.splink.org.br) in 2018, Feb 05. 
 
Arthoniomycetes (INCT) Arizona State University Lichen Herbarium (ASU-Lichen), Herbário Irina Delanova Gemtchújnicov 
(BOTU), Herbário da Fundação Universidade Federal de Mato Grosso do Sul (CGMS), Herbário do Museu da Pontifícia Universidade 
Católica do Rio Grande do Sul (MPUC), Herbário do Museu Nacional - Criptogamos (R-Criptogamos), Wisconsin State Herbarium 
(WIS) available at speciesLink network (http://inct.splink.org.br) in 2018, Feb 06. 
 
Pyrenulales (INCT) Arizona State University Lichen Herbarium (ASU-Lichen), Herbário Irina Delanova Gemtchújnicov (BOTU), 
Herbário da Fundação Universidade Federal de Mato Grosso do Sul (CGMS), Coleção de Fungos INPA (INPA-Fungos), Herbário 
ISE (ISE), Herbário do Museu da Pontifícia Universidade Católica do Rio Grande do Sul (MPUC), Herbário Pe. Camille Torrand 
(URM), Wisconsin State Herbarium (WIS) available at speciesLink network (http://inct.splink.org.br) in 2018, Feb 06. 
 
Strigulales (INCT) Arizona State University Lichen Herbarium (ASU-Lichen), Herbário Irina Delanova Gemtchújnicov (BOTU), 
Herbário ISE (ISE), Herbário Pe. Camille Torrand (URM), Wisconsin State Herbarium (WIS) available at speciesLink 
network(http://inct.splink.org.br) in 2018, Feb 06. 
 
Trypetheliales (INCT) Arizona State University Lichen Herbarium (ASU-Lichen), Herbário Irina Delanova Gemtchújnicov 
(BOTU), Herbário da Fundação Universidade Federal de Mato Grosso do Sul (CGMS), Herbário ISE (ISE), The New York 
Botanical Garden - Brazilian records (NY), Herbário Pe. Camille Torrand (URM), NMNH Extant Specimen and Observation Records 
(US-Fungi), Wisconsin State Herbarium (WIS) available at speciesLink network (http://inct.splink.org.br) in 2018, Feb 06. 
 
Dictyonema (INCT) Arizona State University Lichen Herbarium (ASU-Lichen), Herbário da Universidade Federal de Minas Gerais 
(BHCB), Herbário Irina Delanova Gemtchújnicov (BOTU), Herbário do Centro de Pesquisas do Cacau (CEPEC), Herbário Leopoldo 
Krieger(CESJ), Herbário da Fundação Universidade Federal de Mato Grosso do Sul (CGMS), Royal Botanic Garden Edinburgh 
Herbarium (E), Herbário do Departamento de Botânica da Universidade Federal de Santa Catarina (FLOR), Geneva Herbaria 
Catalogue with species Brazil (G), Herbário Alarich Rudolf Holger Schultz (HAS), Herbário do Museu de Ciências Naturais da PUC-
Minas (HPUC-MG), Liquenoteca do Herbário da Universidade de Caxias do Sul (HUCS-Liquenoteca), Herbário 
Unisanta(HUSC), Herbário do Instituto de Ciências Naturais (ICN), Coleção de Fungos INPA (INPA-Fungos), Herbário do Parque 
da Ciência Newton Freire Maia (IRAI), Herbário ISE (ISE), Herbário Joinvillea (JOI), Herbário do Museu Botânico Municipal 
(MBM), Herbário do Museu da Pontifícia Universidade Católica do Rio Grande do Sul (MPUC), Botanical Collections (NHM-

 

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London-BOT), Herbário do Museu Nacional - Criptogamos (R-Criptogamos), Herbário de fungos de São José do Rio Preto (SJRP-
Fungi), Maria Eneyda Pacheco Kauffmann Fidalgo (SP-Fungi), Herbário da Universidade de Brasília (UB), Herbário UFP - Geraldo 
Mariz (UFP), Herbário da Universidade Federal do Paraná (UPCB), Wisconsin State Herbarium (WIS) available at speciesLink 
network (http://inct.splink.org.br) in 2018, Feb 06. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

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CHAPTER TWO: 
Testing the latitudinal diversity gradient of New World epiphytic lichens using a systematic field sampling 
approach 
 
INTRODUCTION 

Symbiosis, the intimate association of two dissimilar organisms over space and time, is a biotic interaction 

that is critical across taxonomic groups, yet frequently gets a minimal treatment in studies of ecology, 

evolution, and biogeographical patterns, such as the latitudinal diversity gradient (Scharnagl 2019). The 

latitudinal diversity gradient (LDG) is a global pattern of increasing richness with decreasing latitude. The 

richness and diversity of many taxa peak within the tropics around the equator; this pattern has been 

demonstrated for plants (Kerkhoff et al. 2014) and animals (amphibians, Pyron & Wiens 2013; birds, 

Hawkins et al. 2007), and ranging from the terrestrial (Rolland et al. 2014) to the marine (Jablonski et al. 2013, 

Floeter et al. 2004). Of the few symbiotic associations that have been investigated, we find support for a 

LDG in both stony corals (Spano et al. 2016) and in arbuscular mycorrhizal fungi (Davison et al. 2015). In 

this study, we propose to expand upon our current understanding of the biogeography of symbioses through 

the investigation of the latitudinal diversity gradient of lichens. 

 
Lichens are cryptic but ubiquitous terrestrial composite organisms (Nash 2008), which comprise symbiotic 

associations between a mycobiont (fungal partner), photobiont (photosynthetic partner; green algae and/or 

cyanobacteria), and as has been more recently discovered, a possible third partner as well (Cyphobasidiales 

yeast; Spribille et al. 2016). Beyond the primary symbionts, lichens contain additional algae, fungi, and 

bacteria; each lichen thallus is a microcosmic ecosystem (Eymann et al. 2017). Though lichens can be found 

from the poles to the equator, from tidelines to mountaintops, they vary in terms of their habitat and 

substrate preferences (Smith et al. 2009, Cornelissen et al. 2007). The lichen symbiosis is relatively ancient, 

and lichenized fungi are a polyphyletic group in which lichenization likely evolved multiple times 

independently (Gargas et al. 1995, Honegger 2018, Lücking & Nelsen 2018). 

 
Despite the prevalence of the latitudinal diversity gradient across taxa, no consensus has been reached 

regarding what drives the latitudinal diversity gradient (Schemske & Mittelbach 2017, Palmer 1994). In 

 

25 

general, the hypotheses for the LDG can be placed into three main categories: historical, ecological, and 

evolutionary (for a thorough review, see Mittelbach et al. 2007). Historical hypotheses relate to time and area; 

at different points in earth’s history, more of the earth’s surface experienced a tropical climate, enabling more 

species to diversify within a tropical environment (Fine & Ree 2006). One example of this is the tropics-as-

museum hypothesis, in which the ranges of formerly widespread and diverse taxa were reduced into the 

contemporary latitudinal bands of the tropics as the earth’s climate shifted. Another, related historical 

hypothesis is that of tropical niche conservatism, which emphasizes the importance of temperature, 

proposing that there may be a physiological hurdle to overcome if species are to move from the tropics to 

extra-tropical regions. Ecological hypotheses also consider climate, and include the species-energy hypothesis, 

which connects climate and energy with primary productivity. Higher primary productivity leads to a higher 

carrying capacity for more individuals, which can lead to higher species richness (Wright 1983). Another 

ecological hypothesis, proposed by Pianka (1966), proposes that tropical environments contain higher 

heterogeneity or complexity of physical/spatial factors, which in turn leads to a higher number of available 

habitats for species in the tropics. Evolutionary hypotheses discuss the differences in diversification rates 

between tropical and extratropical regions: for example, speciation rates may be equal in both regions but 

there are higher extinction rates in extra-tropical regions due to extreme climatic conditions (Mittelbach 

2012). Though there is ample support for the latitudinal diversity gradient in different taxonomic groups, and 

its correlation with climate (temperature), no single proposed hypothesis has been able to match the species 

accumulation rate in the tropics (Antonelli & Sanmartin 2011): when species richness is plotted based upon 

models proposed in the LDG hypotheses, the predicted curve falls short of the curve of observed species 

richness increase with decreasing latitude (Currie, Mittelbach et al. 2004). One hypothesis that attempts to 

account for this discrepancy in species accumulation rates is the biotic interactions hypothesis. 

 
Wallace (1878), Dobzhansky (1950) and Fischer (1960) each proposed the idea that in the tropics, organisms 

were freed from the abiotic constraints of the higher latitudes. Temperate regions experience extreme and 

unpredictable fluctuations in temperature and other climatic events not experienced in the tropics, tending to 

lead towards, as Dobzhansky postulated, “a few generalists.” In the tropics, however, species are freed from 

 

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this constraint, and the importance of biotic interactions increases. Schemske et al. (2009) expanded upon this 

idea; demonstrating that many species interactions, including parasitism, mutualisms, herbivory, predation and 

other indicators such as sexual selection, often showed a greater prevalence and importance in the tropics. 

However, many areas of species interactions require further research. The importance of species interactions 

would ideally be measured by looking at the proportion of fitness due to biotic interactions (Schemske 2009). 

Since this is often difficult, alternative measures discussed in Schemske et al. (2009) include looking at the 

frequency of interactions (eg. the richness of species involved in biotic interactions), the expression of 

interactions (eg. possessing traits involved in biotic interactions such as plants using chemical defenses against 

herbivory), and the strength of interactions (eg. the specificity or generality of species interactions). 

 
Although the latitudinal diversity gradient has been demonstrated for most plant and animal groups, fungal 

patterns of diversity along a latitudinal gradient vary strongly by group. For example, while pathogenic fungi 

follow the LDG (Peay et al. 2016), indoor fungi follow an inverse pattern (Amend et al. 2010), and 

ectomycorrhizal fungi actually have a bimodal pattern (Tedersoo & Nara 2010). Previous studies that have 

investigated diversity of lichenized fungi (the mycobionts in the lichen symbiosis) across latitudes have also 

revealed a variety of patterns. In a study using herbarium collections data along a gradient in the Western 

continental United States, Holt et al. (2015) found a U-shaped pattern of diversity. Lichen richness was high 

in the southwestern USA, dipped down at mid-latitudes, and peaked again in the Pacific Northwest. In a 

study using a molecular dataset of lichen propagules collected in dust samples from door and window frames 

from across the USA, Tripp et al. (2016) found an inverse latitudinal gradient, with lichen species richness 

increasing with increasing latitude. In a study of patterns of lichen richness in the Brazilian Atlantic Forest, 

Menezes et al. (2018) found an overall latitudinal diversity gradient of lichens supported, though the patterns 

did vary when assessed by lineage (at the fungal family level). In a recent study of lichen richness based on 

herbarium specimen data across both hemispheres in the Americas, Scharnagl (Chapter One 2019) expanded 

the latitudinal range investigated for a lichen LDG, and demonstrated that lichens do indeed follow a 

latitudinal diversity gradient. However, multiple potential gaps in the herbarium collections data were 

identified, revealing the need for more data and other approaches in order to verify this lichen LDG.  

 

27 

 
The majority of LDG studies are based upon a compilation of data sources, including herbarium specimen 

data, observation databases, and reviews of the literature (Scharnagl Chapter One 2019). While these 

approaches enable the researcher to study a larger area or have a more comprehensive taxon sampling, these 

data are based upon multiple studies; multiple researchers and multiple approaches. In this study we set out to 

determine how a field approach, using a systematic sampling design and a single primary researcher, 

investigating the latitudinal diversity gradient of lichens compares to studies based upon the aforementioned 

larger datasets. Using data collected from nine sites along a 70-degree New World latitudinal gradient, we 

asked (1) what are the patterns of lichen richness, diversity, beta diversity, and functional diversity along a 

latitudinal gradient, and (2) what are potential drivers of lichen richness along a latitudinal gradient? 

 
METHODS 

Site Selection 

Given the habitat and substrate versatility of lichens, we narrowed our sampling to focus on epiphytic lichens 

in (relatively) lowland forest habitats. Epiphytic lichens are those that grow on the bark of living trees. A total 

of nine sites were selected along a New World latitudinal gradient from approximately 12 degrees south to 61 

degrees north (Table 1). Sites that included long term forest research plots (eg. RainFor, ForestGEO/CTFS, 

Bosques) were targeted. Where these were not available, sites were selected based upon level of protection 

(forests under long term protection, eg. State Preserve, Biological Station or National Forest) in addition to 

accessibility. Sites were also selected based upon maximal coverage along a latitudinal gradient. Based upon 

these selection criteria, sites were relatively evenly spaced latitudinally but varied a good deal longitudinally 

(Figure 1). Tree data and local climate data was obtained for the majority of sites. In three of the sites, trees 

were identified by the researcher or a field assistant. 

 
Field Sampling 

At each site we surveyed and sampled epiphytic lichens from 100 individual trees, for a total of 900 trees 

across nine sites (Figure 1). At most sites we sampled trees greater than 5cm diameter breast height (DBH); 

however, at some sites, such as the Scotty Creek site in the boreal, we had to amend this approach. Most of 

 

28 

the long term forest sites were laid out in plots or grids; we used these to select which trees to sample from 

using a random number generator. At sites without plots or grids, we used a map of the site and trails with a 

grid overlay to randomly select trees for sampling. Once a tree was selected using the random number 

generator, we sampled from that tree and its nine closest neighbors for clusters of ten, before using the 

random number generator to sample from a different part of the forest plot. GPS coordinates were recorded 

for each cluster of ten trees. 

 
Each tree species was either identified in the field, or its tag number was recorded to be matched with a tree 

database following field work. At each tree, we measured DBH and used a random number generator to 

choose whether to sample from the N, NE, E, SE, S, SW, W or NW side of the tree. Once a side was 

selected, we placed a 20 x 40cm open plastic grid over the trunk at 1.5 m above ground. The grid was 

photographed as a reference, then all lichens within the grid were collected. Lichens were collected using a 

field knife and stored in paper packets. 

 
Lichen Identification 

Lichen samples were first sorted into individual paper packets - one packet per lichen species. Packets were 

labeled with site information, then lichens were sorted by morphological characteristics. These include thallus 

type (crustose, foliose, fruticose, squamulose, leprose), reproductive structures (sexual: apothecia, perithecia, 

lirellae, asexual: isidia, soredia), and where easily identifiable, photobiont (green algae, cyanobacteria). From 

these categories, lichen samples were further sorted into similar morpho-groups. Lichens were then keyed out 

using dichotomous keys (Lendemer et al. 2013, Sipman 2005, Brodo et al. 2001). For some lichen 

identification, spot tests using iodine, bleach, or potassium hydroxide were necessary, and for some, spore 

characteristics were also obtained. Tropical lichen sample identification was provided by Robert Lücking at 

the Berlin Botanic Garden. Lichens that could not be identified to the species level were assigned to a 

morphospecies. Some lichens were recorded as indeterminable morphospecies either due to old or sterile 

thalli, and were excluded from further analyses. The final lichen dataset contained: collection numbers, lichen 

species identification and higher taxonomic classifications, site information including name and geographic 

 

29 

coordinates, lichen morphological descriptions including growth form and reproductive mode, notes on any 

spore characteristics or spot tests, and tree data including tree species identification, tree tag numbers and 

DBH. Lichen voucher specimens are housed at the Michigan State University Herbarium. 

 
Analyses 

All statistics were conducted in R (R Core Team 2019). To assess three measures of diversity (richness, 

Simpson’s diversity, and beta diversity), we used a species by site presence/absence matrix in the vegan 

package (Oksanen et al. 2019) using functions ‘specnumber,’ ‘diversity,’ and ‘betadiver,’ respectively. Richness 

was assessed at the site level. To determine dissimilarity and evenness within a site, beta diversity and 

Simpson’s diversity were calculated at the plot level, then the mean value was calculated for each site. Each of 

the relationships between diversity and latitude were assessed using a generalized linear model with a negative 

binomial distribution. Analyses were conducted using the MASS package (Venables & Ripley 2002). 

 
As lichen specimens were identified they were assigned to a variety of growth forms and reproductive modes. 

Growth form refers to the vegetative body of the lichen, the thallus (Brodo et al. 2001). The growth form 

categories assigned in this dataset included: crustose (flat, crust-like), foliose (three-dimensional, leaf-like), 

fruticose (long and three-dimensional, sometimes pendulous), leprose (loose association, almost fluffy-

looking), squamulose (thallus composed of many small scales), and filamentous (thallus composed of thin 

filaments, often closely appressed to the substrate). To compare across latitudes, we lumped growth forms 

into two categories: two-dimensional and three-dimensional. Two-dimensional refers to the crustose growth 

form. Three-dimensional consisted of foliose, fruticose and squamulose. Leprose and filamentous growth 

forms were rare within the dataset, and were excluded from this analysis. We then calculated the ratio of two-

dimensional to three-dimensional growth form categories for each site.  

 
In this study, reproductive mode refers to the reproductive structures visibly apparent on the lichen thallus. 

These can include spore-producing structures such as apothecia, perithecia, and lirellae, or asexual propagules 

such as soredia and isidia. As with growth form, we lumped reproductive mode into two categories: sexual 

(spore-producing) and asexual (propagules composed of fungal hyphae and algal cells). Lichens that exhibited 

 

30 

both sexual and asexual reproductive modes on the same thallus were counted in both categories; these 

represented less than 0.05% of the dataset. Sterile lichens, those for which no reproductive structures were 

identified on the thallus, were excluded from this analysis. We then calculated the ratio of these reproductive 

mode categories for each site. The relationship between each ratio (growth form, reproductive mode) and 

latitude was assessed using a generalized linear model with a negative binomial distribution. 

 
Tree species richness, the number of host tree species from which lichens were collected, was calculated per 

site using the specnumber function in the vegan package in R. We calculated the species richness of lichens 

per individual tree, and assessed the impact of face on lichen species richness using a generalized linear mixed 

effects model with plot as a random variable using the lme4 package (Bates et al. 2015). We calculated the 

mean and standard deviation of DBH per site. We downloaded bioclim data at the 10 minute resolution (Fick 

& Hijmans 2017) using the raster package (Hijmans 2019) and extracted climate data for each of our nine 

sites. We used a generalized linear mixed model to assess the potential drivers of latitude, tree species 

richness, mean DBH, variance in DBH, temperature of the coldest quarter, and precipitation of the driest 

quarter on lichen species richness. We chose climate data from the coldest and driest quarters as representing 

potential constraints on photosynthesis. We also assessed the impact of different climate variables (mean 

annual temperature, annual precipitation, temperature seasonality, precipitation seasonality, temperature in the 

coldest quarter, temperature in the warmest quarter, precipitation in the driest quarter, and precipitation in the 

wettest quarter) on the ratio of two-dimensional to three-dimensional growth forms, using generalized linear 

models with a negative binomial distribution using the MASS package. A post-hoc analysis of deviance test 

was conducted for each of the variables in the models using the Anova function. 

 
As a first look into the within-lichen patterns of diversity, we selected a subset of lichen individuals within the 

family Parmeliaceae from three of our northern sites. Total genomic DNA was extracted directly from each 

sample using the REDExtract-N-Amp kit (Sigma-Aldrich). After being soaked in acetone, our selected small 

fragments of lichen thalli were allowed to air dry. Twenty μL of extraction buffer was added to each sample, 

and the sample was then ground in the extraction buffer using a micropestle. Samples were then warmed to 

 

31 

95°C for twelve minutes, and brought back to room temperature. Twenty μL of dilution buffer were then 

added to each sample. Samples were centrifuged for 5 minutes, which brought all of the solids to the bottom 

of the tube. The elution was then used to create a 1:20 dilution using nuclease-free water. This 1:20 dilution 

was then used for PCR. We used specifically designed primers for algae within Trebouxiophyceae (Piercey-

Normore & DePriest 2001) for the internal transcribed spacer (ITS) region. Each 20.8 μL of reaction mixture 

included 10 μLof REDExtract-N-Amp PCR Reaction Mix (Sigma-Aldrich), 8.5 μL PCR-grade water, 0.5 μL 

each of forward and reverse primers, and 1.3 μL of [1:20] extracted DNA solution. Microtubes were then 

placed in a BioRad T100 thermocycler and the following cycling reaction was run: 94°C for 5 min, 94°C for 

30 sec, 45°C for 30 sec, 72°C for 2 min, 44 cycles at [94°C for 30 sec, 45°C for 30 sec, 72°C for 2 min], 72°C 

for 5 minutes, then kept at 4°C until retrieved. DNA bands were detected using ethidium bromide on a 0.7% 

agarose gel; all positive products yielded a single band. PCR products were normalized and submitted for 

sequencing on the Illumina MiSeq platform within the Michigan State University Genomics Core. Sequences 

were assembled, trimmed and BLASTed using Qiime2 and GENEious Prime. Patterns of specificity between 

lichenized fungi and their algal photobionts were analyzed using the bipartite package in R (Dormann et al. 

2008). 

 
RESULTS 

Latitudinal Patterns in Lichen Diversity 

As latitude increases, species richness of epiphytic lichens across our nine sampled sites decreases (Figure 2). 

Lichen species richness across nine sites from 12 degrees south to 61 degrees north in the Americas follows a 

latitudinal diversity gradient (for all measures of correlation between latitude and diversity, see Table S1). 

Simpson’s diversity of lichens does not follow a latitudinal pattern; a diversity measure that includes both 

richness and evenness of lichens does not significantly change along a latitudinal gradient. Latitude is 

significantly correlated with beta diversity along two axes; as latitude increases, the number of species shared 

among plots within a site increases, whereas the number of species not shared among plots within a site 

decreases (Figure 3). The ratio of lichen species to genera decreases with increasing latitude (Figure S1). 

 

 

32 

The ratio between two-dimensional, crust-like growth forms and three-dimensional growth forms 

significantly changes along a latitudinal diversity gradient (Figure 4a, estimate= -0.0515, p<<0.0001). As 

latitude increases, crust-like growth forms are replaced by more three-dimensional growth forms including 

foliose, fruticose, and squamulose. The ratio between sexual and asexual reproductive modes did not 

significantly change along a latitudinal gradient (Figure 4b, estimate= -0.0043, p=0.69). The ratio of two-

dimensional to three-dimensional growth forms was driven by climatic variables. The climate extremes model 

was the best fit, but only precipitation variables had a significant association with growth form ratios (Table 

2). 

 
Drivers of Lichen Diversity 

In the full GLMM, only tree species diversity was a significant predictor (Chi-squared=3.76, p=0.033) of 

lichen species richness along a latitudinal gradient; mean and variance of DBH, climate variables, and latitude 

were not significant predictors of lichen richness. The face of the tree from which the lichens were collected 

had no significant impact upon lichen species richness at any latitude (AIC=3152, all p-values for the 

different faces >0.3, See Supp Fig2). 

 
A Preliminary Look within the Lichen Symbiosis 

Our sequencing approach yielded five algal amplicon sequence variants (ASVs) from across eight lichen 

species at the North Carolina site (Figure S4), three ASVs from across seven lichen species at the Harvard 

Forest site (Figure S5), and seven ASVs from across four lichen species at the Scotty Creek site (Figure S6). 

The mean specificity index of photobionts increases with increasing latitude across our three examined sites; 

however, latitude is not a significant predictor of photobiont specificity (F=0.614, p=0.557, Figure S7A). The 

mean specificity index of mycobionts does not follow a latitudinal pattern and latitude is also not a significant 

predictor of mycobiont specificity (F=0.123, p=0.73, Figure S7B). We found no overlap in photobiont ASVs 

among our three sites (Figure S8). 

 
 

 

 

33 

DISCUSSION 

New World epiphytic lichenized fungi follow a latitudinal diversity gradient, with the highest species richness 

at and around the equator, and decreasing species richness with increasing latitude. The pattern revealed here 

by the systematic field sampling approach corroborates the latitudinal diversity gradient of lichens revealed 

from herbarium collections data (Scharnagl Chapter One 2019). Beta diversity of lichenized fungi also 

followed a latitudinal gradient, with lichens within plots becoming more similar to one another with 

increasing latitude. This latitudinal gradient in beta diversity has been observed in other groups as well, 

including vascular plants (Qian & Ricklefs 2007) and mammals (Qian et al. 2009). Interestingly, beta diversity 

between trees within a single plot did not follow a latitudinal pattern. Rather, as one moves from one tree to 

another within a plot, similarity remains low until we get to our two boreal forest sites (Figure S3). Schemske 

et al. (2009) proposed that the richness of organisms engaged in tight biotic interactions could be used as a 

proxy for the frequency of biotic interactions at different latitudes. The patterns of lichen diversity found in 

this study support the Biotic Interactions Hypothesis in terms of frequency of biotic interactions.  

 
Lichen species richness generally increased with increasing host tree species richness, and tree species richness 

was the sole significant driver in the full model assessing drivers of lichen richness across our nine sites. Host 

specificity, even host genotype, has been implicated as an important driver in other epiphytic (Zytynska et al. 

2011) and endophytic (Hoffman & Arnold 2008) groups, often interacting with other factors such as locality. 

In one group of lichenized fungi, Resl et al. (2018) found multiple transitions from specialist to generalist and 

back again in terms of substrate types (eg. soil, rock, bark, wood), though overall more transitions from 

generalist to specialist. In a study in the Brazilian Atlantic rainforest, the specificity of epiphytic lichen 

communities was somewhat influenced by bark characteristics and microclimate, but the largest factor 

seemed to be stochastic effects of lichen dispersal, suggesting less emphasis on substrate specificity within a 

substrate type, such as the bark of trees (Cáceres et al. 2007). Further investigation is needed into the 

relationship between lichen richness, tree richness, and lichen substrate specificity in order to determine the 

role of tree richness in driving lichen richness along a latitudinal gradient. 

 

 

34 

The ratio of two-dimensional to three-dimensional growth forms of lichens followed a latitudinal gradient 

across the nine sampled sites. Similar patterns in epiphytic lichens have been found across other gradients, 

such as elevational gradients; the percentage of crustose lichens decreases with increasing altitude, while the 

percentage of fruticose and vegetative lichens increases (Dietrich & Scheidegger 1997). The same pattern may 

also prevail at the scale of vertical gradients along a single tree (Scharnagl, unpublished data). These patterns are 

likely a result of environmental gradients in moisture availability or aridity (and other parameters (Matos et al. 

2015)), as growth form has been associated with water uptake ability (Rundel 1978). Across multiple studies, 

both lichen richness and the diversity of lichen growth forms are driven primarily by light intensity and 

moisture availability (Harris 1971, Brodo 1961). The latitudinal gradient in growth form ration in our study 

supports climatic stability hypotheses of the LDG. The tropics have a relatively stable climate (Gates 1962) 

and have been less impacted by extreme events such as glaciation events compared to northern latitudes 

(Dynesius & Jansson 2000). The hypothesis of climatic stability states that the more stable climate in the 

tropics supports higher species richness through greater specialization and narrower niches. The converse of 

that being that the lower stability and higher variability of extratropical climates would support lower species 

richness (Pianka 1966). The ratio of lichen growth forms is best explained by the climate extremes model, 

supporting the idea that fewer species better adapted to higher climate variability may dominate outside of the 

tropics. The importance of species tolerance to climatic extremes at northern latitudes, and narrower tropical 

niches as an enforcing factor of isolation and diversification, is further discussed in Janzen’s (1967) idea of 

mountain passes being higher in the tropics (Sheldon et al. 2018). Another symbiotic group, the stony corals, 

have a latitudinal gradient driven by a combination of history and climatic stability; more transitions from 

temperate to tropical have taken place than the reverse (Spano et al. 2016). Likewise, arbuscular mycorrhizal 

fungi follow the “sun worshipper hypothesis,” in which the higher light availability and less extreme climate 

in the tropics leads to higher incidence and specificity of arbuscular mycorrhizal plants, thus driving 

arbuscular mycorrhizal diversity (Veresoglou et al. 2019). 

 

 

35 

The ratio between sexual and asexual reproductive modes did not vary along a latitudinal gradient, though 

these have been shown to be influenced by factors such as moving from forested to non-forested habitats or 

length of time following a disturbance such as fire (Nelson et al. 2015). 

 
In our preliminary look into biotic interactions within the lichens themselves, we do not find evidence for a 

latitudinal pattern of specificity across three sites from either the mycobiont (fungal partner) or photobiont 

perspective. Specificity and selectivity of the mycobionts to the photobionts is driven largely by abiotic factors 

(Leavitt et al. 2015), though there is evidence for both photobiont-mediated (climate drivers, Peksa & Skaloud 

2011) and mycobiont-mediated (lineage-driven, Yahr et al. 2004) guilds. Evidence from corals in the Indian 

Ocean suggest that partnerships within this symbiosis are also driven by abiotic factors (LaJeunesse et al. 

2010). Partner switching may in fact be a mechanism by which these symbiotic organisms overcome 

physiological hurdles, eg. transitions from tropical to temperate environments. Mycobiont and photobiont 

specificity were not aligned at any of our sites. It is possible that this is an artefact of a small sample size or 

that mycobiont and photobiont specificity are driven by different factors in these northern latitudes, though 

other studies have found high levels of reciprocal specificity in lichens even at intercontinental scales (Otalora 

et al. 2010). We did find complete turnover of photobiont ASVs across our three sites, suggesting localized 

(locally adapted?) pools of available partners. We are interested to see whether these localized pools become 

narrower or broader in a tropical environment. 

 
We find some support for a historical hypothesis of the LDG in lichens based upon a higher species:genus 

ratio in the tropics and a lower species:genus ratio with increasing latitude (Figure S1). Tropical lichens may 

have had more opportunities for speciation by isolation (Janzen 1967) before coming together again, leading 

to many closely related lichen species being found close together spatially in the tropics (Lücking & Matzer 

2001).  

 
As in other groups (Schemske & Mittelbach 2017), the LDG of lichens is likely driven by multiple interacting 

factors, including geological history, gradients in light, temperature and moisture availability, and substrate 

diversity. It is important to note here that these patterns and drivers are based on epiphytic lichen diversity. 

 

36 

Trees are a relatively new substrate for lichens evolutionarily speaking, and it is likely that lichens specialized 

to other substrates, such as saxicolous lichens (lichens growing on rocks) that tend to dominate in extreme 

environments such as arctic and alpine tundra (Wang et al. 2017), may follow a different pattern. 

 
CONCLUSION 

Systematic field sampling of one hundred individual trees across ten plots at each of nine sites spread across a 

70-degree latitudinal gradient in the Americas supports a latitudinal gradient of species richness, beta diversity, 

and growth form ratio of lichenized fungi. Notably, Simpson’s diversity and reproductive mode ratio do not 

follow a latitudinal gradient. The latitudinal gradient of lichen species richness is significantly driven by tree 

species richness, but not by tree size or face. This study provides further support that lichenized fungi do 

indeed follow a latitudinal diversity gradient and explores some of the underlying mechanisms of history, 

climate, and biotic interactions.  

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

37 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

APPENDIX 

38 

CHAPTER TWO TABLES AND FIGURES 
 
Table 2.1 The nine sites used in this study; the type of long term research or protection status of the forest; the latitude 
and longitude; the country in which the site was located; and the method or dataset by which tree species were identified. 

Site 

Forest Type 

Cocha Cashu  Biological Station & 

Long term research plots 

Latitude 
 

-11.8 S 
 

Longitude  Country  Tree Species Identification 

-71 W 

Peru 

RAINFOR 

Biological Station & 
Long term research plots 

0.9 N 
 

-76 W 

Ecuador  ForestGEO 

Yasuni 

La Selva 

Biological Station & 
Long term research plots 

Los Tuxtlas 

Biological Station 

Fakahatchee 

State Preserve 

Nantahala 

National Forest 

Harvard 
Forest 

Biological Station & 
Long term research plots 

BC Boreal 

Public Forest 

Scotty Creek  Biological Station & 

Long term research plots 

10 N 
 

18N 
 

26 N 
 

35 N 
 

42 N 
 

52 N 
 

61 N 
 

-84 W 

Costa 
Rica 

Bosques 

-95 W 

Mexico  Not obtained 

-81 W 

USA 

Identified by Klara 
Scharnagl 

-83 W 

USA 

Identified by Matthew 
Chansler 

-72W 

USA 

ForestGEO 

-119 W 

Canada 

Identified by Toby Spribille 
& Klara Scharnagl 

-121 W 

Canada 

ForestGEO 

 
Table 2.2 Climate models for predicting lichen growth forms along a latitudinal gradient. Significance levels of each 
variable are reported from the generalized linear models and from the post-hoc analysis of deviance of the generalized 
linear models. 

Model 

Variables  
(estimate & significance) 

AIC 

R-squared 

Climate Means 

Mean Annual Temperature (0.0118 ***/***) 
Annual Precipitation (0.0001 ns/ns) 

46.441 

0.574 

Climate Seasonality 

Temperature Seasonality (-0.0021 ***/***) 
Precipitation Seasonality (0.0372 **/***) 

37.399 

0.862 

 
 
 

 

39 

Table 2.2 (cont’d) 

Climate Extremes  Temp Coldest Quarter (-0.0001 ns/**) 
Temp Warmest Quarter (0.0708 ns/ns) 
Precip Driest Quarter (0.0036 **/***) 
Precip Wettest Quarter (-0.0047 ***/***) 

37.872 

0.928 

 
Table 2.S1 Coefficients of correlation and significance tests between latitude and measures of epiphytic lichen diversity. 

Correlation between Latitude and: 

Correlation Coefficient 

t-value 

p-value 

Species Richness 

Simpson’s Diversity 

Similarity 

Dissimilarity 

-0.802 

-0.416 

0.678 

-0.583 

-3.554 

-1.212 

2.44 

0.009 

0.265 

0.044 

-1.901 

0.01 

 
 
 
Figure 2.1 Sampling schematic. Nine sites (red circles) were sampled along a latitudinal gradient. Ten plots (green 
circles) were sampled at each site. Ten trees were sampled in each plot; a randomly selected focal tree (black rectangle), 
and its nine nearest neighbors (brown rectangles). 
 

 

 

 

 

 

 

 

40 

Figure 2.2 Epiphytic lichen species richness per site from nine forest sites along a latitudinal gradient. Line is fit from 
generalized linear model with 95% confidence intervals. 

 
 
Figure 2.3 Lichen beta diversity (dissimilarity) plotted against latitude. 

 

 

 

 

 

41 

Figure 2.4 (a) Left, The proportion of two-dimensional or crust-like growth forms (light blue) to three-dimensional 
growth forms (dark blue) across latitudes. (b) Right, The proportion of asexual (light green) reproductive modes to 
sexual reproductive (green) modes across latitudes. 

 
 
 
Figure 2.S1 Epiphytic lichen species to genus ratio plotted against latitude. 

 

 
 
 

 

 

42 

Figure 2.S2 The influence of face (cardinal direction) on lichen species richness per tree. 

 

 

Figure 2.S3 Similarity of lichen species from one tree to another within a plot averaged across all plots within a site, 
plotted against latitude. 

 
 

 

 

43 

Figure 2.S4 Interaction network between mycobionts (8 species) and photobionts (5 ASVs) at the North Carolina site. 

 
Figure 2.S5 Interaction network between mycobionts (7 species) and photobionts (3 ASVs) at the Harvard Forest site. 

 
Figure 2.S6 Interaction network between mycobionts (4 species) and photobionts (7 ASVs) at the Scotty Creek site. 

 
 

 

44 

 

 

 

Figure 2.S7 (A, above) Specificity index of mycobionts across our three northern sites. (B, below) Specificity index of 
photobionts across our three northern sites. Lines represent standard error. 
 

 

 
 
 
 
 
 
 

 

 

 

45 

Figure 2.S8 Differences in community composition of photobiont ASVs. Symbiont ID is provided as a combination of 
the highest BLAST hit from NCBI and a unique amplicon sequence variant (ASV) number. There is no overlap of ASVs 
across the three sites. 
 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

 

46 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

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52 

CHAPTER THREE: 
Lichen diversity across tropical forest restoration strategies 
 
INTRODUCTION 

Tropical forests are global biodiversity hotspots and important sources of natural products (Myers et al. 

2000), yet over half of the world’s tropical forests have been converted to other land uses (Lewis et al. 2015). 

Tropical landscapes that were once dominated by primary tropical forests (Gibson et al. 2011) now exist as 

patchworks of secondary forests and other land uses (Zahawi et al. 2015), mainly agricultural (Henders et al. 

2015). Conversion to other land uses is not only leading to irrevocable biodiversity loss, it is also leading to 

dramatic shifts in the global carbon budget (Norris 2016). It is therefore critical to work on restoring these 

tropical forest ecosystems, and to understand the many dynamics involved in different tropical forest 

restoration strategies. 

 

The primary push in tropical reforestation has been for natural regeneration; however, this strategy is slow 

(Chazdon & Guariguata 2016), and may contain long term costs that lead to abandonment or disturbance of 

this forest restoration strategy (Zahawi et al. 2014). Tropical reforestation is challenging due to the initial costs 

involved in more active strategies such as tree plantations (Holl et al. 2011). In addition, most tropical 

reforestation is taking place on land that had been used for agriculture, which alters the seed bank (Reid et al. 

2015), soil nutrient composition, and even the mycorrhizal communities (Holste et al. 2016), which may 

inhibit recruitment and growth of tropical trees.  

 

Tropical forests are biodiversity hotspots for a multitude of organisms, and the symbiotic associations 

between fungi and a photosynthetic partner (green algae or cyanobacteria) known as lichens are no exception 

(Aptroot & Sipman 1997). Lichens are terrestrially ubiquitous organisms (Nash 2008), occurring from 

tidelines to mountaintops, from lush tropical forests to the arctic tundra, yet biodiversity of lichenized fungi 

seems to peak in the tropics (Scharnagl Chapter One & Chapter Two, Lücking & Matzer 2001). While our 

understanding of tropical lichen diversity is on the rise (Lücking et al. 2009) and we continue to discover and 

 

53 

describe new tropical species (Lücking et al. 2014), our understanding of the ecology and the impact of 

deforestation on these composite organisms lags behind. 

 

The photosynthetic requirements of lichens makes them sensitive to microclimatic gradients in light and 

moisture availability (Ellis et al. 2012, Fryday 2001). Lichens are poikilohydric, obtaining moisture and 

nutrients directly from the air, which makes them sensitive to subtle changes in these conditions. Lichens 

have long been used as indicators of air quality (Munzi et al. 2014), but more recently have been used as 

indicators of climate change (Aptroot 2009), biodiversity (Jovan 2008), and ecosystem disturbance (Leavitt & 

St. Clair 2015, Stoffer et al. 2006). A few studies have proposed the use of lichens as indicators of disturbance 

in tropical forest ecosystems (Benitez et al. 2012, Andersson & Gradstein 2005, Wolseley 1994). Rivas Plata et 

al. (2008) took the idea of lichens as indicators beyond total lichen richness, and rigorously assessed the use of 

corticolous (growing on the bark of trees) tropical lichen families as either indicators of disturbed/exposed 

forest habitat, or as indicators of more intact/continuous forest habitat. Of the three families 

(Thelotremataceae, Porinaceae, Letrouitiaceae) found to be indicators of ecological continuity of tropical 

rainforest habitats (preference for undisturbed primary and older secondary forest, shaded to somewhat 

exposed microhabitats, and mature trees), Rivas Plata et al. (2008) chose Thelotremataceae alone to be used in 

their IEC analyses, as it had a wider altitudinal range and larger number of genera and species compared to 

the other two families. Within their analyses, Rivas Plata et al. (2008) also identified lichenized fungal families 

that were indicators of more disturbed or pioneer habitats; these included Lecanoraceae, Pertusariaceae, 

Physciaceae, and Teloschistaceae. 

 

In this study, we quantified lichen colonization in a long-term restoration study established in southern Costa 

Rica to test three forest restoration strategies: the active strategies of plantation-style planting and the 

nucleation or “island” style tree planting, and the passive strategy of natural regeneration. Within the 

framework of this study we addressed the following questions: (1) What is the impact of different restoration 

strategies on tropical lichen diversity and community composition?; and (2) Can lichens be used as indicators 

 

54 

of ecological continuity within each of these restoration strategy treatments? We censused lichens in the three 

restoration strategies to address these questions. 

 

METHODS 

Study Sites 

This study was conducted using twelve forest restoration sites located within a ~100 km2 area in southern 

Costa Rica between the Las Cruces Biological Station (8° 47’ N, 82° 57’ W) and the town of Agua Buena (8° 

44’ N, 82° 55’ W). This area is comprised of hilly terrain between 1060 to 1430 m asl, with annual 

precipitation of 3000-4000mm and mean annual temperature of 21℃. The native ecosystem is tropical 

premontane rainforest (Holdridge et al. 1971), but the majority of forest was cleared for coffee growing 

between 1960 and 1980 (Zahawi et al. 2015). The current landscape is highly fragmented into mixed-use 

agricultural fields, pastures, forest patches and riparian corridors. 

 

The forest restoration sites were established in 2004-2006 on post-agricultural lands that had been farmed for 

18 or more years (Holl et al. 2011). Each site contained three 0.25-ha (50x50 m) randomly assigned treatment 

plots. Each plot was assigned one of three restoration strategies: (1) natural regeneration, (2) applied 

nucleation or tree “islands,” and (3) tree plantations. Natural regeneration plots were fenced to prevent 

livestock grazing but were otherwise left alone. Island plots contained six patches; two large islands (12x12 m, 

25 seedlings planted), two medium islands (8x8 m, 13 seedlings planted), and two small islands (4x4 m, 5 

seedlings planted). Plantation plots contained 313 seedlings planted throughout the 50x50 m area. Within the 

two active restoration strategies of island and plantation, seedlings were separated by 2.8 m from one another. 

Seedlings of the following tree species were planted in the island and plantation treatments: Erythrina 

poeppigiana (Fabaceae), Inga edulis (Fabaceae), Terminalia amazonia (Combretaceae), and Vochysia guatemalensis 

(Vochysiaceae). Plots within a site were separated by at least 5 m, and sites were separated by at least 0.7 km.  

 

 

 

55 

Field Surveys of Lichens 

We conducted our lichen survey during the dry season in early 2019. We focused on two planted native 

species: Terminalia amazonia (J.F. Gmel.) Exell (Combretaceae), and Vochysia guatemalensis Donn. Sm. 

(Vochysiaceae), and three recruit species: Cecropia obtusifolia Bertol. (Urticaceae), Miconia schlimii Triana 

(Melastomataceae) and Heliocarpus appendiculatus Turcz. (Malvaceae). These were chosen as they were well 

distributed across treatments and sites, though, particularly in the natural regeneration treatment, not all 

species were found. 

 

Within each treatment plot, a maximum of five individual trees per tree species were surveyed, and this 

method was replicated across the twelve sites. For each survey, the lower trunk of each tree, from the ground 

up to 1.8 m, was visually surveyed for epiphytic lichens. The diameter at breast height (DBH) was measured 

and recorded for each tree. The percent cover of lichens, bryophytes, and other [pooled cover of algae, non-

lichenized fungi, vascular epiphytes, bare bark] were visually estimated and recorded for each tree. Each 

lichen in the field was assigned to a tentative morphospecies and a description was recorded; some were 

photographed for later identification.  

 

Lichens were identified to genus or morphospecies based upon field notes descriptions and photographs 

using a combination of tropical lichen guides (fieldguides.fieldmuseum.org), tropical lichen keys (Sipman 

2005), and a reference collection from a previous study in these plots [collected by K. Scharnagl, and 

identified with the help of Robert Lücking; voucher specimens from this study are housed in the Michigan 

State University Herbarium]. About half of all the morphospecies identified could be assigned to a family. 

Lichen community composition and indicator species were analyzed based upon these morphospecies 

identifications.  

 

 

 

 

56 

Analyses 

All analyses were conducted in R (R Core Team 2019). Morphospecies richness was assessed using the 

specnumber function in the vegan package (Oksanen et al. 2019). Drivers of richness at both the tree and 

treatment level were analyzed using generalized linear mixed effects models using a poisson distribution, with 

site as a random variable, in the lme4 package (Bates et al. 2015). The significance of each of these effects was 

analyzed using the Anova function, which performs a Type II Wald Chi-squared test, in the car package (Fox 

& Weisberg 2011). 

 

Lichen morphospecies were assigned to different functional groups based on photobiont (cyanobacteria or 

green algae), growth form (two-dimensional crust-like or three-dimensional macrolichens), and reproductive 

mode (asexual or sexual). Asexual lichens were those that produced fragments including soredia, isidia, and 

phyllidia. Sexual lichens were those that produced spore-bearing structures including apothecia, perithecia, 

and lirellae. Some functional diversity was recorded as indeterminable based upon what was observed in the 

field. For example, many lichens observed contained neither sexual or asexual reproductive structures and 

were therefore recorded as “N/A”. We calculated the ratio of each functional group per treatment. For each 

functional group, the ratio was calculated as rare/dominant (eg. cyanobacteria/green algae, 

macrolichens/crusts, asexual/sexual). Effect of treatment was assessed using analysis of variance (ANOVA) 

and differences among treatments were assessed using a Tukey test (TukeyHSD in R). 

 

Lichen community composition was assessed using a non-metric multidimensional scaling (NMDS) 

ordination. We further assessed drivers of lichen community similarity and dispersion using the adonis 

(permutational multivariate analysis of variance) function in the vegan package; permutational multivariate 

analysis of variance enables us to assess drivers using a community or dissimilarity matrix as the response 

variable. 

 

We used the Index of Ecological Continuity (IEC) equation provided in Rivas Plata et al. (2008), as follows: 

 

57 

IEC = 100 x n/Nmax, 

with n = the number of morphospecies detected in a given treatment, and Nmax = the maximum number of 

morphospecies across all treatments/sites. IEC was determined for each treatment: plantation, island, and 

natural regeneration. To test the efficacy of Thelotremataceae alone as an indicator of ecological continuity as 

found in Rivas Plata et al. (2008), we first ran this equation for just morphospecies within Thelotremataceae. 

We then ran the equation for morphospecies within Thelotremataceae, Letrouitiaceae, and Porinaceae 

combined, to see how all three families performed as indicators within our forest restoration sites. Finally, we 

calculated the ratio of indicators of disturbed and exposed habitats (members of the Lecanoraceae, 

Pertusariaceae and Physciaceae families) to indicators of more continuous tropical forest habitats (members 

of the Thelotremataceae, Letrouitiaceae, and Porinaceae families) for each treatment. 

 

RESULTS 

In total, we surveyed 527 individual trees across 12 sites, observing 3093 lichen individuals that represent 

approximately 369 morphospecies (Table S1). Morphospecies richness per tree was highest in the natural 

regeneration treatment (Figure 1). Lichen percent cover per tree was also highest in the natural regeneration 

treatment, and followed an inverse pattern to bryophyte percent cover per tree (Figure 2).  Total 

morphospecies richness at the 0.25 ha scale was lowest in the natural regeneration treatment, and highest in 

the island treatment (Figure 3). Both lichen morphospecies richness and percent lichen cover were highest on 

the naturally recruiting species Heliocarpus appendiculatus and Cecropia obtusifolia (Figure 4a-b). 

 

At the individual tree level, treatment (Chi-squared=14.65, df=4, p=0.0007), DBH (Chi-squared=9.29, df=1, 

p=0.0023), and tree species (Chi-squared=548.11, df=4, p<0.0001) all had significant effects on lichen 

morphospecies richness. Elevation (Chi-squared=0.645, df=1, p=0.422) and surrounding forest cover (Chi-

squared=0.325, df=1, p=0.57) were not significant predictors of lichen morphospecies richness at the 

individual tree level (Figure 5a). Elevation (Chi-squared=4.84, df=1, p=0.027), surrounding forest cover (Chi-

 

58 

squared=54.21, df=1, p<0.0001), and treatment (Chi-squared=4848.4, df=2, p<0.0001) were all significant 

predictors of lichen species richness at the 0.25 ha level (Figure 5b). 

 

We found substantial overlap in lichen communities among sites. We found a significant influence of both 

treatment (adonis(treatment) F=2.13, R2=0.114, p=0.001, Figure S1) and elevation (adonis(tree species) 

F=2.80, R2=0.075, p=0.001, Figure S2), and no significant effect of surrounding forest cover 

(adonis(surrounding forest cover) F=1.14, R2=0.031, p=0.281, Figure S3) on lichen community composition. 

 

There was a significant effect (F=32.92, df=2, p<0.001) of treatment on the ratio between lichens containing 

cyanobacteria and lichens containing green algae (more common). The tukey’s test revealed a significant 

difference among all three treatments (Figure 6a); natural regeneration had significantly more lichens 

containing cyanobacteria than either islands or plantations, and islands had significantly more lichens 

containing cyanobacteria than plantations (p<0.05). Treatment also had a significant effect (F=12.96, df=2, 

p<0.0001) on the ratio between macro lichens and crust lichens. The natural regeneration treatment had 

significantly more macro lichens than both the island and plantation treatments, and the island and plantation 

treatments were not significantly different from one another (Figure 6b). There were no significant 

differences among treatments on the ratio between lichens with asexual modes of reproduction to lichens 

with sexual modes of reproduction. 

 

The IEC score based on Thelotremataceae alone was the same for island and natural regeneration treatments 

(Table 1), and lowest in the plantation treatment. The IEC score based on the three families 

Thelotremataceae, Letrouitiaceae, and Porinaceae, was highest in the plantation, followed by the island, and 

lowest in the natural regeneration. For these two assessments, a higher IEC score corresponds to a higher 

score for ecological continuity. The ratio of families indicating disturbed or exposed environments 

(Lecanoraceae, Pertusariaceae, Physciaceae) to families indicating forest continuity (Thelotremataceae, 

Letrouitiaceae, Porinaceae) was highest in the plantation treatment, followed by the island treatment, and 

 

59 

lowest in the natural regeneration treatment. In this assessment, a higher ratio is indicative of a more exposed 

or disturbed habitat, and a lower ratio (fewer morphospecies representing disturbed habitats relative to 

morphospecies representing continuous or undisturbed habitat) is indicative of more ecological continuity. 

 

DISCUSSION 

Our lichen survey across twelve sites in southern Costa Rica yielded approximately 369 lichen morphospecies. 

This likely represents a conservative estimate of lichen richness, as there are many cryptic lichen species in the 

tropics, which may have been lumped under a single morphospecies in our surveys (Cáceres et al. 2008, 

Emmerer & Hafellner 2004). Forest restoration treatment (nucleation, plantation, or natural regeneration) was 

a significant predictor of lichen morphospecies richness at both the tree and 0.25-ha levels, and of lichen 

community composition. Other studies have found forest stand structure, as replicated by our forest 

restoration strategies, to be the strongest influence on lichen diversity (Moning et al. 2009), even more than 

other predictor variables such as climate. 

 

The highest overall morphospecies richness was found in the active restoration strategy of nucleation, 

followed by the active restoration strategy of plantations, and then by the passive restoration strategy of 

natural regeneration. Though there was overlap of lichen communities across sites and treatments, we found 

the greatest spread in our ordination of the island treatment communities, and treatment overall had a 

significant effect on lichen community composition. The island or nucleation strategy may have the most 

heterogeneous microclimatic landscape compared to the plantation or natural regeneration strategies, which 

could lead to more heterogeneous lichen communities and therefore overall higher morphospecies richness in 

the island treatments. A similar pattern was observed for other groups in these treatments; both arthropod 

(Cole et al. 2016) and vascular epiphyte (Reid et al. 2016) diversity were higher in the islands than in the other 

treatments. 

 

 

60 

At the level of the individual tree we found a different pattern, with the highest lichen morphospecies 

richness per tree in the natural regeneration, followed by the nucleation, then the plantation. Lichen cover per 

tree followed the same pattern, which was the inverse of the pattern of bryophyte cover per tree. Bryophytes 

are more shade tolerant whereas lichens may have the competitive advantage on substrates exposed to higher 

UV radiation and aridity (Ranius et al. 2008). Thus we find the highest lichen cover and lowest bryophyte 

cover on trees in the natural regeneration treatment, where many trees are surrounded by lower vegetation, 

their trunks exposed on all sides to high levels of light and wind. In both the island and plantation interiors, 

there is much higher shade, and we find lower lichen cover and higher bryophyte cover per tree. While we 

find the highest lichen morphospecies richness and cover per individual tree in the natural regeneration 

treatment, we also find the lowest overall species richness in this treatment, suggesting that there may be a 

species pool specialized to this more gap-like environment.  

 

We found the highest morphospecies richness and lichen cover per tree on the naturally recruiting species 

Heliocarpus appendiculatus and Cecropia obtusifolia. Species such as Cecropia are known pioneers, and have a large 

leaf area ratio and high growth rate (Pompa & Bongers 1988). While we found both H. appendiculatus and C. 

obtusifolia across our treatments, they were often the only trees found in the natural regeneration plots, where 

lichen cover and richness were generally high, which may explain the overall high richness and cover reported 

for these species. Epiphytic lichen composition and richness is also known to be driven by bark 

characteristics, including pH and texture (Lamit et al. 2015, Cácares et al. 2007). It is therefore possible that 

the naturally recruiting species H. appendiculatus and C. obtusifolia have more favorable bark characteristics for 

lichen growth than the planted species. In addition, their strategy of fast growth often led to higher DBH 

measurements than those recorded for the other tree species, and we found DBH to be a significant predictor 

of lichen species richness at the individual tree level. Other research has shown that both the mean and 

variance of DBH predict lichen species richness at multiple scales, including across a latitudinal gradient 

(Scharnagl Chapter Two), supporting a species-area interaction for lichens (He & Legendre 1996).  

 

 

61 

We did not find a significant effect of surrounding forest cover, at either a short distance of 100-150m or a 

wider distance of 500-550m, on lichen morphospecies richness per tree. Likewise, a study on seedling recruits 

across the three treatments found a weak effect of surrounding forest cover, compared to the effects of 

treatment and elevation (Holl et al. 2017). We did find a significant effect of surrounding forest cover at the 

100-150m distance on lichen morphospecies richness at the 0.25-ha scale. Interestingly, there was a negative 

slope in this relationship; increasing surrounding forest cover led to a slight decrease in lichen morphospecies 

richness. This is the opposite trend of that found for vascular epiphytes in these plots, where vascular 

epiphyte richness increased with increasing surrounding forest cover (Reid et al. 2016). In addition, 

surrounding forest cover did not predict lichen community composition. These patterns may be driven by 

dispersal modes of lichens and the ability of lichen propagules to travel on the wind; this enables many lichen 

species to disperse over long distances (Gjerde et al. 2015, Muñoz et al. 2004). Lichen community 

composition and succession are in fact more limited by establishment parameters than by dispersal (Ronnås 

et al. 2017, Werth et al. 2006). We suggest that more data is needed on the establishment criteria of tropical 

lichens before we can understand the role of surrounding forest cover on lichen recruitment into these plots.  

 

Elevation was a significant predictor of both lichen morphospecies richness and community composition at 

the 0.25 ha level. Overall, as elevation increased, lichen morphospecies richness decreased, which is again 

opposite to that found for vascular epiphytes (Reid et al. 2016). It is possible that lichens and vascular 

epiphytes respond to different environmental drivers along an elevational gradient, or even that there is direct 

competition between these two epiphytic groups. Studies in temperate regions found increasing lichen 

richness with increasing elevation (Bässler et al. 2016, Bruun et al. 2006), and it is unclear whether our results 

are representative of total lichen richness along an elevation gradient, or whether there is an interaction 

between elevation and forest restoration impacting the observed pattern. 

 

We found the highest ratio of cyanolichens to lichens containing green algal photobionts per plot in the 

natural regeneration treatment, followed by the island treatment, then the plantations. In a study of lichen 

 

62 

functional traits as ecological indicators, Benitez et al. (2018) found cyanolichens to be an indicator of more 

continuous forest. However, they also found certain macrolichens such as fruticose and foliose species with 

narrow lobes to be more abundant in disturbed forest habitats. As such, it is difficult to use the ratios we 

found in our plots as indicators of forest disturbance or continuity. However, if we consider the 

microclimates experienced by lichens in the different treatments to fall along a gradient from highest light and 

variability of moisture and temperature in the natural regeneration treatments (Zahawi & Augspurger 2006) to 

lowest light and variability in the plantation (Holl et al. 2011), we find parallels to patterns of lichen diversity 

across larger ecological gradients. In a study on the latitudinal diversity gradient of lichens in the Americas, 

Scharnagl (Chapter Two, 2019) found a higher ratio of macro lichens to crusts with increasing latitude, which 

coincides with increasing variability in temperature and precipitation. We found no significant differences in 

the ratios of asexual to sexual reproductive modes along an environmental gradient.  

 

New species of lichens are continually being discovered and described (Lumbsch et al. 2011), both in the 

tropics and in the temperate regions (Fryday & Hertel 2014, Fryday & Ovstedal 2012). There is therefore 

much work to be done to understand both the diversity and the ecology of tropical lichen communities. As 

revealed in this study, there are multiple interacting factors affecting the recruitment patterns of tropical 

lichen communities, and these tropical forest restoration plots provide an ideal setting in which to investigate 

these dynamics. We aim to continue to monitor these plots for lichen succession as fast growing recruits or 

microhabitat specialists are replaced or joined by other species. 

 

Our preliminary indicator measurements support that the plantation is a more open/”disturbed” habitat type 

whereas islands and natural regeneration more closely mimic continuous forest, but we suggest that more data 

is needed to make use of the lichen indicators proposed by Rivas Plata et al. (2008). Our indicator analyses 

support the island treatment as an intermediate between potential microclimatic extremes of the natural 

regeneration and plantation treatments. Islands, with their multiple edges and interiors and more 

heterogeneous microclimates, are likely the most suitable environments for supporting the widest array of 

 

63 

lichen niches and therefore the highest overall morphospecies richness. As we continue to monitor these 

tropical forest restoration strategies over time, we propose that lichens may become increasingly important as 

indicators of both ecological continuity and forest health (McCune 2000) within these plots. 

 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

64 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

APPENDIX 

65 

CHAPTER THREE TABLES AND FIGURES 
 
Table 3.1 IEC scores for Thelotremataceae, for combined Thelotremataceae, Porinaceae and Letrouitiaceae, and the 
ratio of lichen species in families indicating exposed or disturbed habitats to lichen species in families indicating forest 
continuity. Higher IEC scores mean more ecological continuity, whereas a higher indicator ratio means less continuity 
and more disturbance. 

Treatment 

Island 

Plantation 

Natural Regeneration 

Thelotremataceae EIC 

Combined EIC 

Indicator Ratios 

80 

60 

80 

68.75 

75 

25 

0.36 

0.42 

0.25 

 
Table 3.S1 The number of morphospecies and number of individual lichens observed per lichenized fungal family.  

Family 

Arthoniaceae 

Arthopyreniaceae 

Caliciaceae 

Coccocarpiaceae 

Coenogoniaceae 

Collemataceae 

Crocyniaceae 

Graphidaceae 

Hygrophoraceae 

Lecanoraceae 

Letrouitiaceae 

Lobariaceae 

Malmideaceae 

Monoblastiaceae 

Opegraphaceae 

Parmeliaceae 

Peltigeraceae 

Pertusariaceae 

Physciaceae 

Pilocarpaceae 

 

 

Number of Species 

Number of Samples 

19 

1 

1 

1 

20 

25 

1 

65 

2 

1 

1 

6 

12 

2 

2 

5 

1 

1 

4 

3 

379 

2 

1 

3 

163 

155 

2 

290 

7 

1 

1 

27 

130 

14 

2 

17 

5 

5 

51 

15 

66 

Table 3.S1 (cont’d) 

Porinaceae 

Pyrenulaceae 

Ramalinaceae 

Roccellaceae 

Stictidaceae 

Thelotremataceae 

Trypetheliaceae 

Unassigned 

10 

8 

5 

7 

1 

5 

2 

158 

102 

113 

58 

32 

1 

27 

3 

1487 

 
 
Figure 3.1 Lichen morphospecies richness per tree within each forest restoration treatment. 
 

 
 
 
 
 

 

 

67 

Figure 3.2 Percent cover per tree of lichens (triangles) and bryophytes (circles). 
 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

 

68 

Figure 3.3 Total lichen morphospecies richness at the 0.25 ha scale. 
 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

 

69 

Figure 3.4 (a) Lichen morphospecies richness on each tree species across plots. (b) Lichen percent cover on each tree 
species across plots. 
 
(a) 

 
(b) 

 
 
 
 
 
 
 

 

 

 

70 

Figure 3.5 Effect of elevation (a) and surrounding forest cover at 100-150m (b) on lichen morphospecies richness at the 
0.25 ha level. Line of fit based on GLMER models. 
 
(a) 

 
(b) 

 
 
 
 
 
 
 
 
 
 

 

 

 

71 

Figure 3.6 (a) Ratio of lichens containing cyanobacteria to lichens containing green algal photobionts across treatments. 
(b) Ratio of three-dimensional macro lichens to two-dimensional crust lichens across treatments. 
 
(a) 

 
 
(b) 

 
 
 
 
 
 

 

 

 

72 

Figure 3.S1 Ordination plot of lichen communities, colors represent treatments. 
 

 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

73 

Figure 3.S2 Ordination plot of lichen communities, colors represent elevation. 
 

 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

74 

Figure 3.S3 Ordination plot of lichen communities, colors represent surrounding forest cover. 
 

 

 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 

75 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

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76 

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