Improving biodiversity knowledge with dataset synergy: A case study of non-native plants in Colorado

Abstract

Species lists are important tools for managing biodiversity, including controlling nonnative species, but they are either incomplete or lacking for many areas. Our objective was to illustrate how the synergy of disparate data sets can increase knowledge of species distributions while minimizing further field expenditures. We compared five different data types (two species lists, weed surveys, vegetation plots, and weed maps) of nonnative plant locations at the county level from 45 data sets covering Colorado. Species lists captured the highest number of species, but they missed many of the noxious weeds recorded by weed-mapping data. The number of species recorded per county increased by 30% on average with data synergy even in the most intensively surveyed areas. Each data type also followed the same pattern of survey intensity, leaving some areas in the state consistently unsurveyed or undersurveyed. On average, there was a 44% increase in species recorded per county with all data types included. Overall, inclusion of more data types greatly increased knowledge of the nonnative species in Colorado. Therefore, harnessing the synergy of disparate data sets seems to be a cost-effective first step to increase knowledge of species richness (presence) in an area.