Temporal degradation of data limits biodiversity research. Issue 17 (27th July 2017)

• Record Type: Journal Article
• Authors: Tessarolo, Geiziane; Ladle, Richard; Rangel, Thiago; Hortal, Joaquin
• Is Part Of: Ecology and evolution. Volume 7:Issue 17(2017:Sep.)
• Page Start: 6863
• Page End: 6870
• Publication Date: 2017-07-27
• Subjects: biodiversity data -- data degradation -- data quality -- maps of ignorance -- species distribution models -- temporal decay; Ecology -- Periodicals; Evolution -- Periodicals; 577.05
• DOI: 10.1002/ece3.3259
• Languages: English
• ISSNs: 2045-7758

Abstract

Abstract: Spatial and/or temporal biases in biodiversity data can directly influence the utility, comparability, and reliability of ecological and evolutionary studies. While the effects of biased spatial coverage of biodiversity data are relatively well known, temporal variation in data quality (i.e., the congruence between recorded and actual information) has received much less attention. Here, we develop a conceptual framework for understanding the influence of time on biodiversity data quality based on three main processes: (1) the natural dynamics of ecological systems—such as species turnover or local extinction; (2) periodic taxonomic revisions, and; (3) the loss of physical and metadata due to inefficient curation, accidents, or funding shortfalls. Temporal decay in data quality driven by these three processes has fundamental consequences for the usage and comparability of data collected in different time periods. Data decay can be partly ameliorated by adopting standard protocols for generation, storage, and sharing data and metadata. However, some data degradation is unavoidable due to natural variations in ecological systems. Consequently, changes in biodiversity data quality over time need be carefully assessed and, if possible, taken into account when analyzing aging datasets. Abstract : Biodiversity data have both spatial and temporal dimensions. However, concerns on data quality have been mainly focused on spatial coverage. Here, we discuss how the passage of time can affect biodiversity data quality, and why it can have fundamental consequences for the comparability of data collected in different time periods.