Determining Decision Thresholds and Evaluating Indicators when Conservation Status is Measured as a Continuum

• Published in: Conservation biology 2014-12, Vol.28 (6), p.1626-1635
• Main Authors: CONNORS, B. M, COOPER, A. B
• Format: Article
• Language: English
• Subjects: Animal, plant and microbial ecology; Animals; Applied ecology; Aquatic Organisms - physiology; Biodiversity; Biological and medical sciences; Biomass; British Columbia; característica operante del receptor (ROC); clasificación de amenazas; classification error; Conservation; Conservation biology; Conservation of Natural Resources - methods; conservation status; Conservation, protection and management of environment and wildlife; Contributed Papers; Decision Making; Depopulation; detritivores; Ecosystem; Endangered Species; Environmental conservation; error de clasificación; estado de conservación; false negative; False negative errors; false positive; False positive errors; falso negativo; falso positivo; Fundamental and applied biological sciences. Psychology; General aspects; incertidumbre; indicador; indicator; Indicator organisms; Marine ecosystems; Oncorhynchus nerka; Pacific Ocean; Parks, reserves, wildlife conservation. Endangered species: population survey and restocking; Population characteristics; Population dynamics; receiver operating characteristic (ROC); Reproducibility of Results; ROC Curve; Salmon; Salmon - physiology; signal detection theory; teoría de detección de señales; threat classification; uncertainty; Wildlife conservation
• ISSN: 0888-8892; 1523-1739
• DOI: 10.1111/cobi.12364

Categorization of the status of populations, species, and ecosystems underpins most conservation activities. Status is often based on how a system's current indicator value (e.g., change in abundance) relates to some threshold of conservation concern. Receiver operating characteristic (ROC) curves can be used to quantify the statistical reliability of indicators of conservation status and evaluate trade‐offs between correct (true positive) and incorrect (false positive) classifications across a range of decision thresholds. However, ROC curves assume a discrete, binary relationship between an indicator and the conservation status it is meant to track, which is a simplification of the more realistic continuum of conservation status, and may limit the applicability of ROC curves in conservation science. We describe a modified ROC curve that treats conservation status as a continuum rather than a discrete state. We explored the influence of this continuum and typical sources of variation in abundance that can lead to classification errors (i.e., random variation and measurement error) on the true and false positive rates corresponding to varying decision thresholds and the reliability of change in abundance as an indicator of conservation status, respectively. We applied our modified ROC approach to an indicator of endangerment in Pacific salmon (Oncorhynchus nerka) (i.e., percent decline in geometric mean abundance) and an indicator of marine ecosystem structure and function (i.e., detritivore biomass). Failure to treat conservation status as a continuum when choosing thresholds for indicators resulted in the misidentification of trade‐offs between true and false positive rates and the overestimation of an indicator's reliability. We argue for treating conservation status as a continuum when ROC curves are used to evaluate decision thresholds in indicators for the assessment of conservation status.