What We (Don't) Know About Global Plant Diversity
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Utah State University DigitalCommons@USU Ecology Center Publications Ecology Center 8-8-2019 What We (Don’t) Know About Global Plant Diversity William K. Cornwell University of New South Wales William D. Pearse Utah State University Rhiannon L. Dalrymple University of New South Wales Amy E. Zanne George Washington University Follow this and additional works at: https://digitalcommons.usu.edu/eco_pubs Part of the Ecology and Evolutionary Biology Commons Recommended Citation Cornwell, W.K., Pearse, W.D., Dalrymple, R.L. and Zanne, A.E. (2019), What we (don't) know about global plant diversity. Ecography, 42: 1819-1831. doi:10.1111/ecog.04481 This Article is brought to you for free and open access by the Ecology Center at DigitalCommons@USU. It has been accepted for inclusion in Ecology Center Publications by an authorized administrator of DigitalCommons@USU. For more information, please contact [email protected]. What we (don’t) know about global plant diversity William K. Cornwell1, William D. Pearse2, Rhiannon L. Dalrymple1, and Amy E. Zanne3 1 Evolution & Ecology Research Centre, School of Biological, Earth and Environmental Sciences, UNSW Sydney, Australia 2 Department of Biology & Ecology Center, Utah State University, Logan, UT, USA 3 Department of Biological Sciences, George Washington University, Washington, DC, USA Corresponding author email: [email protected] ORCiD ids and emails: William K. Cornwell: 0000-0003-4080-4073, [email protected] William D. Pearse: 0000-0002-6241-3164, [email protected] Rhiannon L. Dalrymple: 0000-0002-2660-1424, [email protected] Amy E. Zanne: 0000-0001-6379-9452, [email protected] 1 Abstract 2 The era of big biodiversity data has led to rapid, exciting advances in the theoretical and applied biological, ecological 3 and conservation sciences. While large genetic, geographic and trait databases are available, these are neither complete 4 nor random samples of the globe. Gaps and biases in these databases reduce our inferential and predictive power, and 5 this incompleteness is even more worrisome because we are ignorant of both its kind and magnitude. We performed a 6 comprehensive examination of the taxonomic and spatial sampling in the most complete current databases for plant 7 genes, locations, and functional traits. To do this, we downloaded data from The Plant List (taxonomy), the Global 8 Biodiversity Information Facility (locations), TRY (traits) and GenBank (genes). Only 17.7% of the world’s described 9 and accepted land plant species feature in all three databases, meaning that more than 82% of known plant biodiversity 10 lacks representation in at least one database. Species coverage is highest for location data and lowest for genetic data. 11 Bryophytes and orchids stand out taxonomically and the equatorial region stands out spatially as poorly represented in 12 all databases. We have highlighted a number of clades and regions about which we know little functionally, spatially 13 and genetically, on which we should set research targets. The scientific community should recognize and reward the 14 significant value, both for biodiversity science and conservation, of filling in these gaps in our knowledge of the plant 15 tree of life. 16 Keywords: Bias, functional trait, genetic, knowledge gaps, macro-ecology, spatial, taxonomic 17 Introduction 18 In perhaps the first plant trait database, Theophrastus of Eresus (371–287 BC), a student of Plato and Aristotle, assembled 19 and published a complete list of the woody and herbaceous plants growing in his garden (Theophrastus 1916). Since then 20 the nature and scale of plant databases have changed, but the goal of organized, accessible information about the world’s 21 plants remains the same. For the first time, after more than 2000 years of research, global versions of Theophrastus’ list 22 are now on the horizon. 23 24 Global biological databases have two goals: (1) provide the best global snapshots of biodiversity available at a given 25 time, and (2) organize their underlying data to facilitate their intersection with other datasets to address research 26 questions. From decades of hard work and accumulated knowledge, we know more now than we ever have about 27 biodiversity. The hurdles stopping us from attaining our goal of available, comprehensive global plant databases remain 28 daunting but also increasingly surmountable. In this effort, we believe it is worthwhile, periodically, to take stock of 29 what information we have and what we still lack. Here we ask: how much do we know about global plant diversity, and 30 what and where are the most conspicuous blank pages in our encyclopedia of plant life? 31 32 There are four primary classes of global biological data: taxonomic, geographic, genetic, and trait. Together they provide 33 the most complete picture currently available of where and how organisms make a living across the globe and how they 34 have evolved through time, with taxonomy providing the link between the other three types of primarily species-level 35 information. Each of these data types is complex in its own way. Two classes, taxonomic, and trait, require taxon-based 36 specialized knowledge—botanists are required to build and curate such datasets [e.g., The Angiosperm Phylogeny Website 37 http://www. mobot.org/MOBOT/research/APweb/, The Plant List http://www.theplantlist.org/, The State of the World’s 38 Plants Report RBG Kew (Willis 2017) , and TRY (Kattge et al. 2011)]. In contrast, data within genetic and geographic 39 databases share similar structure and curation protocols across all organisms, and as such, data for plants, animals, and 40 microbes can be usefully kept in one place. General databases for all organisms exist for genes (GenBank; Benson et al. 41 2013), phylogenetic relationships based on those genes (The Open Tree of Life; Hinchliff et al. 2015) and spatial 42 observations (GBIF; http://gbif. org/). Here, using The Plant List as our taxonomic backbone, we explore the data available 43 in GenBank, GBIF, and TRY, as these are the most complete current databases with fundamental, disaggregated data which 44 has been collected about global plants (König et al. 2019). 45 46 These three databases (GenBank, GBIF, and TRY) were assembled from numerous research projects with diverse 47 original goals and data availability; this diversity, while valid within each effort, creates global-scale biases in terms of 2 48 which species feature in a particular database and which do not, which in turn effects the usability of data (Beck et al. 49 2013, 2014, Hinchliff and Smith 2014, Gratton et al. 2017). The globally uneven distribution of research funding may 50 play a role in creating biases in data collection by limiting researchers’ efforts to certain geographical regions or taxa 51 (particularly to species of commercial or cultural value). Furthermore, biodiversity is not evenly distributed across the 52 globe. For instance, the high alpha and beta-diversity and commonness of rare species in many tropical ecosystems 53 means that the sampling effort required to capture some percentage of the species present during a sampling trip at low 54 latitudes is much more intensive than at high latitudes. Global patterns in biodiversity, combined with patchy sampling 55 effort, has left us with gaps in biodiversity data. Finally, non-random gaps within a given database can intersect with 56 gaps in other databases in surprising ways, reducing the number of species about which we have a comprehensive 57 understanding. The nature and source of gaps in each kind of information, and the interactions and consequences of 58 these shortfalls have been clearly conceptually defined (Hortal et al. 2015). There have been some recent assessments of 59 the current gaps in data, including outlines of gaps in phylogenetic data for fungi (Nilsson et al. 2016) and across the tree 60 of life (Hinchliff et al. 2015), and in spatial data for birds (Team eBird, July 2014) and plants (Meyer et al. 2016, Stropp 61 et al. 2016). However, the relative size and overlap of gaps in these data types, and taxonomic and spatial biases in their 62 intersection has never been defined. Thus, our main aim is to examine these biases, gaps, and overlaps of gaps in plants 63 across multiple data sources, starting with the most basic definition of species coverage: presence or absence. 64 65 Such data paucity matters. Lack of data is a major impediment to conservation: we cannot save a species if we do not 66 know where it is or what it needs to live. Data are crucial to identifying conservation crises (Rodrigues et al. 2006, 67 Cardoso et al. 2011, Keith 2015). For example, high-resolution remote-sensing deforestation maps (Hansen et al. 2013), 68 when combined with even small amounts of location data, can identify rare species at risk of extinction and worthy of 69 conservation efforts. A great deal of resources are allocated to conservation actions for some broadly-covered species 70 (i.e., species for which we have taxonomic, genetic, spatial, and trait data) that are at risk; in contrast, poorly-covered 71 species may be going extinct before conservation biologists are able to interrogate a geographic database to determine 72 where they are found or a trait database to determine its form or characteristics should they go looking for them. It is our 73 hope that an assessment of gaps in plant data across geographic space and the extant branches of the plant phylogeny 74 will spur the sharing and/or further collection of data where they are most sorely needed. 75 76 By isolating the key spatial and taxonomic knowledge gaps in plant data and the intersections between them, we hope to 77 increase our chances of filling in the most important missing pages in the book of plant life as efficiently as possible.