A method for measuring the relative information content of data from different monitoring protocols

Abstract

Summary1. Species monitoring is an essential component of assessing conservation status, predicting effects of habitat change and establishing management and conservation priorities. The pervasive access to the Internet has led to the development of several extensive monitoring projects that engage massive networks of volunteers who provide observations following relatively unstructured protocols. However, the value of these data is largely unknown. 2. We develop a novel cross-data validation method for measuring the value of survey data from one source (e.g. an Internet checklist program) relative to a second, benchmark data source. The method fits a model to the data of interest and validates the model using benchmark data, allowing us to isolate the training data's information content from its biases. We also define a data efficiency ratio to quantify the relative efficiency of the data sources. 3. We apply our cross-data validation method to quantify the value of data collected in eBirda western hemisphere, year-round citizen science bird checklist project -relative to data from the highly standardized North American Breeding Bird Survey (BBS). The results show that eBird data contain information similar in quality to that in BBS data, while the information per BBS datum is higher. 4. We suggest that these methods have more general use in evaluating the suitability of sources of data for addressing specific questions for taxa of interest.

Investigating the Feasibility of Geo-Tagged Photographs as Sources of Land Cover Input Data

“…Data collection protocols for VGI are either non-existent or not strictly enforced, e.g., with OSM data. In contrast, many citizen science projects in the area of biodiversity monitoring and conservation have well-defined data collection protocols that require user training and/or strong interaction with experts in the field [52]. In a sense, trying to cover this gap, the World Wide Web Consortium (W3C) and the Open Geospatial Consortium (OGC) have jointly published a draft document [53] on the best practices that should be followed when publishing spatial data on the web but there is still generally a lack of protocols in VGI.…”

Identifying Reliable Opportunistic Data for Species Distribution Modeling: A Benchmark Data Optimization Approach

“…In addition, opportunistic data typically consists of species presence locations, without information on species absences [8,26]. Munson et al [27] also found that the eBird opportunistic data had more uncertainty than the professionally collected North American Breeding Bird Survey (BBS) data. Due to these and other issues, many still consider opportunistic data to be low quality and unreliable for research and conservation planning purposes [9].…”

“…Furthermore, the sheer quantity and spatial extent of opportunistic data can provide researchers and policy makers with information on ecological trends that may otherwise go unnoticed due to the relative scarcity of professionally collected data [4,10]. Studies demonstrating the similar predictive results of models built on opportunistic data versus professional data further justify the use of opportunistic data [27]. A study conducted by Bried and Siepielski [10] also indicated that their presence-only opportunistic datasets contained identical patterns to that of presence-absence systematic datasets.…”

Virtual birding : extending birdwatching to review acoustic recordings

“…For many systems, the interesting and desirable information often lies within the uncommon data. The protocol for describing observations by participants is an important factor in measuring data quality (Munson et al, 2010). Munson et al also infer that the more unstructured the protocol, the higher the volume of data required to ensure a useful level of quality.…”

“…Long-term monitoring, in a variety of geographic locations, gathers data about faunal activity and composition changes (Munson et al, 2010). The essential information to be monitored includes the presence, distribution, and abundance of faunal species.…”