The time is ripe for a comprehensive mission to explore and document Earth's species. This calls for a campaign to educate and inspire the next generation of professional and citizen species explorers, investments in cyber-infrastructure and collections to meet the unique needs of the producers and consumers of taxonomic information, and the formation and coordination of a multi-institutional, international, transdisciplinary community of researchers, scholars and engineers with the shared objective of creating a comprehensive inventory of species and detailed map of the biosphere. We conclude that an ambitious goal to describe 10 million species in less than 50 years is attainable based on the strength of 250 years of progress, worldwide collections, existing experts, technological innovation and collaborative teamwork. Existing digitization projects are overcoming obstacles of the past, facilitating collaboration and mobilizing literature, data, images and specimens through cyber technologies. Charting the biosphere is enormously complex, yet necessary expertise can be found through partnerships with engineers, information scientists, sociologists, ecologists, climate scientists, conservation biologists, industrial project managers and taxon specialists, from agrostologists to zoophytologists. Benefits to society of the proposed mission would be profound, immediate and enduring, from detection of early responses of flora and fauna to climate change to opening access to evolutionary designs for solutions to countless practical problems. The impacts on the biodiversity, environmental and evolutionary sciences would be transformative, from ecosystem models calibrated in detail to comprehensive understanding of the origin and evolution of life over its 3.8 billion year history. The resultant cyber-enabled taxonomy, or cybertaxonomy, would open access to biodiversity data to developing nations, assure access to reliable data about species, and change how scientists and citizens alike access, use and think about biological diversity information.

Understanding the factors that drive the evolution of pathogenic fungi is central to revealing the mechanisms of virulence and host preference, as well as developing effective disease control measures. Prerequisite to these pursuits is the accurate delimitation of species boundaries. Colletotrichum gloeosporioides s.l. is a species complex of plant pathogens and endophytic fungi for which reliable species recognition has only recently become possible through a multi-locus phylogenetic approach. By adopting an intensive regional sampling strategy encompassing multiple hosts within and beyond agricultural zones associated with cranberry ( Vaccinium macrocarpon Aiton), we have integrated North America strains of Colletotrichum gloeosporioides s.l. from these habitats into a broader phylogenetic framework. We delimit species on the basis of genealogical concordance phylogenetic species recognition (GCPSR) and quantitatively assess the monophyly of delimited species at each of four nuclear loci and in the combined data set with the genealogical sorting index ( gsi ). Our analysis resolved two principal lineages within the species complex. Strains isolated from cranberry and sympatric host plants are distributed across both of these lineages and belong to seven distinct species or terminal clades. Strains isolated from V. macrocarpon in commercial cranberry beds belong to four species, three of which are described here as new. Another species, C. rhexiae Ellis & Everh., is epitypified. Intensive regional sampling has revealed a combination of factors, including the host species from which a strain has been isolated, the host organ of origin, and the habitat of the host species, as useful indicators of species identity in the sampled regions. We have identified three broadly distributed temperate species, C. fructivorum , C. rhexiae , and C. nupharicola , that could be useful for understanding the microevolutionary forces that may lead to species divergence in this important complex of endophytes and plant pathogens.

Topological heterogeneity among gene trees is widely observed in phylogenomic analyses and some of this variation is likely caused by systematic error in gene tree estimation. Systematic error can be mitigated by improving models of sequence evolution to account for all evolutionary processes relevant to each gene or identifying those genes whose evolution best conforms to existing models. However, the best method for identifying such genes is not well established. Here, we ask if filtering genes according to their clock-likeness or posterior predictive effect size (PPES, an inference-based measure of model violation) improves phylogenetic reliability and congruence. We compared these approaches to each other, and to the common practice of filtering based on rate of evolution, using two different metrics. First, we compared gene-tree topologies to accepted reference topologies. Second, we examined topological similarity among gene trees in filtered sets. Our results suggest that filtering genes based on clock-likeness and PPES can yield a collection of genes with more reliable phylogenetic signal. For the two exemplar data sets we explored, from yeast and amniotes, clock-likeness and PPES outperformed rate-based filtering in both congruence and reliability.

Developing a comprehensive and reliable taxonomy for the Colletotrichum gloeosporioides species complex will require adopting data standards on the basis of an understanding of how methodological choices impact morphological evaluations and phylogenetic inference. We explored the impact of methodological choices in a morphological and molecular evaluation of Colletotrichum species associated with banana in Brazil. The choice of alignment filtering algorithm has a significant impact on topological inference and the retention of phylogenetically informative sites. Similarly, the choice of phylogenetic marker affects the delimitation of species boundaries, particularly if low phylogenetic signal is confounded with strong discordance, and inference of the species tree from multiple-gene trees. According to both phylogenetic informativeness profiling and Bayesian concordance analyses, the most informative loci are DNA lyase (APN2), intergenic spacer (IGS) between DNA lyase and the mating-type locus MAT1-2-1 (APN2/MAT-IGS), calmodulin (CAL), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), glutamine synthetase (GS), β-tubulin (TUB2), and a new marker, the intergenic spacer between GAPDH and an hypothetical protein (GAP2-IGS). Cornmeal agar minimizes the variance in conidial dimensions compared with potato dextrose agar and synthetic nutrient-poor agar, such that species are more readily distinguishable based on phenotypic differences. We apply these insights to investigate the diversity of Colletotrichum species associated with banana anthracnose in Brazil and report C. musae, C. tropicale, C. theobromicola, and C. siamense in association with banana anthracnose. One lineage did not cluster with any previously described species and is described here as C. chrysophilum.

Fungus-farming ants cultivate multiple lineages of fungi for food, but, because fungal cultivar relationships are largely unresolved, the history of fungus-ant coevolution remains poorly known. We designed probes targeting >2000 gene regions to generate a dated evolutionary tree for 475 fungi and combined it with a similarly generated tree for 276 ants. We found that fungus-ant agriculture originated ~66 million years ago when the end-of-Cretaceous asteroid impact temporarily interrupted photosynthesis, causing global mass extinctions but favoring the proliferation of fungi. Subsequently, ~27 million years ago, one ancestral fungal cultivar population became domesticated, i.e., obligately mutualistic, when seasonally dry habitats expanded in South America, likely isolating the cultivar population from its free-living, wet forest–dwelling conspecifics. By revealing these and other major transitions in fungus-ant coevolution, our results clarify the historical processes that shaped a model system for nonhuman agriculture.