Quantifying population declines based on presence-only records for red-list assessments

Area of Science:

• Ecology
• Conservation Biology
• Wildlife Management

Background:

• Accurate species trend estimates are crucial for effective conservation action.
• Imperfect species detection can lead to biased trend estimates, potentially overestimating declines.
• Biased population trends can negatively influence conservation policy and management decisions.

Purpose of the Study:

• To estimate nationwide population trends for 14 Swiss amphibian species using an occupancy-modeling framework.
• To compare population trend estimates that account for imperfect detection versus those that ignore it.
• To assess the impact of imperfect detection on conservation status assessments using IUCN Red List criteria.

Main Methods:

• Utilized an occupancy-modeling framework to estimate species detectability and population trends.
• Calculated nationwide population trends for 14 Swiss amphibian species.
• Applied IUCN Red List criteria to trend estimates derived with and without accounting for imperfect detection.

Main Results:

• Imperfect detection was observed in all 14 assessed amphibian species, with significant variation among species.
• Ignoring imperfect detection led to an overestimation of population declines for these species.
• Accounting for imperfect detection resulted in a lower IUCN Red List risk category for 5 of the 14 species.

Conclusions:

• Failing to account for imperfect species detectability can significantly impact conservation status assessments and management decisions.
• Occupancy modeling offers a flexible and effective framework for addressing observation bias in population trend estimation.
• Routine recording of non-observation and absence data is essential for improving the accuracy of conservation assessments.