COVERater—A Free Application for Training Researchers to Accurately Estimate Species Cover in Terrestrial and Aquatic Ecosystems

摘要

Visual estimates of cover are widely used among ecologists, from describing vegetation communities to tracking and monitoring species' abundance. However, despite the known bias associated with visual estimates, no standardised training is available to improve these measurements. We developed a free online training tool, the COVERater, that effectively teaches users to visually estimate the percent cover of species in a variety of ecosystems (including alpine heath, arid lands, coral reefs, temperate reefs and wetlands). Prior to training, users with prior professional experience estimated species cover to an average inaccuracy of 5.2%, while users with no experience estimated cover to an average inaccuracy of 7.6%. COVERater training took an average of 31 min and 68 images, and reduced the estimate inaccuracy of users with no prior experience to 5.2%. There was no significant loss of estimate accuracy over 100 days following training. The COVERater can be used anywhere in the world, by data collectors of all experience levels, for projects spanning all spatial scales. By providing researchers with standardised training, our application can reduce variation in cover estimates that arise from human biases, allowing for comparable estimates across global collaborative projects and data syntheses. We encourage all relevant scientists to include COVERater training in their protocols to quantify cover with greater accuracy, improve the veracity of their results and make better inferences about our biosphere.