California’s imperiled herpetofauna illustrate the importance of standardized methods for classifying extinction risk

Authors: MOTHES, CAITLIN - University Of Miami; CLEMENTS, STEPHANIE - University Of Miami; HEWAVITHANA, DISHANE - University Of Miami; HOWELL, HUNTER - University Of Miami; David, Aaron; SEARCY, CHRISTOPHER - University Of Miami; LEVENTHAL, NICOLE - University Of Miami

Submitted to: Conservation Biology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/19/2019
Publication Date: 10/4/2019
Citation: Mothes, C., Clements, S., Hewavithana, D., Howell, H., David, A.S., Searcy, C., Leventhal, N. 2019. California’s imperiled herpetofauna illustrate the importance of standardized methods for classifying extinction risk. Conservation Biology. 34(3):754-761. https://doi.org/10.1111/cobi.13421.
DOI: https://doi.org/10.1111/cobi.13421

Interpretive Summary: Imperiled species lists are important tools to combat biodiversity loss because they assess extinction threat and aid in conservation prioritization for policy decisions. Standardized classification methods that use quantifiable risk metrics are critical for evaluating extinction threats because they increase objectivity, consistency, and transparency of listing decisions. Yet, in the United States, neither federal nor state agencies use standardized methods for listing species for legal protection, which could put listing decisions at odds with the magnitude of the risk. Here, we use a recently developed set of quantitative risk metrics with classification tree analyses to evaluate state and federal listing decisions for imperiled herpetofauna in California. We find that federally-listed herpetofauna in California score significantly higher on the risk metric spectrum than those not federally-listed, but that state-listed species do not score any higher than those not state-listed. Classification trees detect state endemism as the most important predictor of listing status at the state level, and distribution trend (the proportion of a species’ range that has been lost over time) as the most important predictor at the federal level. Using the imperiled herpetofauna of California as a case study, we emphasize the need for governing bodies to adopt standardized methods for assessing conservation risk that utilize quantitative criteria. We demonstrate how such methods allow decision-makers to identify the criteria that are inherently most important in determining listing status and produce an unbiased comparison of conservation threat across all species to promote consistency and effectiveness of the listing process.

Technical Abstract: Imperiled species lists are important tools to combat biodiversity loss because they assess extinction threat and aid in conservation prioritization for policy decisions. Standardized classification methods that use quantifiable risk metrics are critical for evaluating extinction threats because they increase objectivity, consistency, and transparency of listing decisions. Yet, in the United States, neither federal nor state agencies use standardized methods for listing species for legal protection, which could put listing decisions at odds with the magnitude of the risk. Here, we use a recently developed set of quantitative risk metrics with classification tree analyses to evaluate state and federal listing decisions for imperiled herpetofauna in California. We find that federally-listed herpetofauna in California score significantly higher on the risk metric spectrum than those not federally-listed, but that state-listed species do not score any higher than those not state-listed. Classification trees detect state endemism as the most important predictor of listing status at the state level, and distribution trend (the proportion of a species’ range that has been lost over time) as the most important predictor at the federal level. Using the imperiled herpetofauna of California as a case study, we emphasize the need for governing bodies to adopt standardized methods for assessing conservation risk that utilize quantitative criteria. We demonstrate how such methods allow decision-makers to identify the criteria that are inherently most important in determining listing status and produce an unbiased comparison of conservation threat across all species to promote consistency and effectiveness of the listing process.