| Summary: | Symbiosis, the intimate relationship between unrelated organisms, is a widespread complex trait that allows for exploitation of ecological niches and has the potential to drive evolutionary change. The lichen symbiosis is an obligate mutualism of fungi, photosynthesizers, and bacteria, with polyphyly of lichenization exhibited by each group. Despite the long history of lichenology, many key features of lichens have only recently been discovered, leading to questions about past assumptions. In addition, lichenology has sometimes lacked comparison with non-lichen-forming fungi in a phylogenetic context. Here, we present a framework through which to examine the complexities of the lichen symbiosis, and then employ the framework to explore two aspects of lichen biology. We evaluated the claim that 8% of the world is covered in lichens and found this was unsubstantiated. We then used a MaxEnt model to predict northern North American occurrence of Cladonia rangiferina to test its viability as a method to estimate global lichen coverage. Our model predicted C. rangiferina could cover 35% of northern North America, demonstrating that MaxEnt may form the starting point for a more integrated model. At the other end of the biological scale, we designed and validated a method to estimate lichen-forming fungal genome size. We then measured the fungal genomes of 25 lichens (23 not currently included in the Fungal Genome Size Database) spanning 2 classes and 10 orders of lichen-forming fungi and 3 independent origins of lichenization, and compared them to non-lichen-forming taxa in a phylogenetic context. We found that all lichens have relatively small genomes for eukaryotes (mean of 0.028 pg), and that they are comparable to their nearest non-lichen-forming relatives. In all, we demonstrate the applicability of employing a multi-perspective framework to the study of complex biological entities, the value of evaluating uncertain claims, and the utility of comparing fundamental traits across phylogeny. Finally, we suggest ...
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