Abstract
Monitoring population trends of threatened species requires standardized techniques that can be applied over broad areas and repeated through time. Sun bears Helarctos malayanus are a forest dependent tropical bear found throughout most of Southeast Asia. Previous estimates of global population trends have relied on expert opinion and cannot be systematically replicated. We combined data from 1,463 camera traps within 31 field sites across sun bear range to model the relationship between photo catch rates of sun bears and tree cover. Sun bears were detected in all levels of tree cover above 20%, and the probability of presence was positively associated with the amount of tree cover within a 6-km2 buffer of the camera traps. We used the relationship between catch rates and tree cover across space to infer temporal trends in sun bear abundance in response to tree cover loss at country and global-scales. Our model-based projections based on this “space for time” substitution suggested that sun bear population declines associated with tree cover loss between 2000–2014 in mainland southeast Asia were ~9%, with declines highest in Cambodia and lowest in Myanmar. During the same period, sun bear populations in insular southeast Asia (Malaysia, Indonesia and Brunei) were projected to have declined at a much higher rate (22%). Cast forward over 30-years, from the year 2000, by assuming a constant rate of change in tree cover, we projected population declines in the insular region that surpassed 50%, meeting the IUCN criteria for endangered if sun bears were listed on the population level. Although this approach requires several assumptions, most notably that trends in abundance across space can be used to infer temporal trends, population projections using remotely sensed tree cover data may serve as a useful alternative (or supplement) to expert opinion. The advantages of this approach is that it is objective, data-driven, repeatable, and it requires that all assumptions be clearly stated.
Highlights
Management and conservation of species and sub-populations threatened with extinction requires accurate and reproducible estimates of population trend
We used the relationship between tree cover and relative density of sun bears across space to project population change due to habitat loss. Using this “space for time” substitution, by assuming that the drivers of the spatial gradient between sun bears and % tree cover drive temporal changes [35], we provide a standardized proximate measure of sun bear population change through time based on deforestation data, at least until better data become available
Relationship between sun bear detections at camera traps and % tree cover
Summary
Management and conservation of species and sub-populations threatened with extinction requires accurate and reproducible estimates of population trend. Measuring changes in the global status of a species usually requires data collected over broad spatial and temporal scales. When management resources are limited, monitoring programs tend to be restricted in scope, with data collected within a single study area over short periods, and with limited ability to extrapolate to other areas. Of the > 5000 mammalian species categorized by the International Union for the Conservation of Nature (IUCN) Red List of Threatened Species, > 800 are classed as data deficient (status unknown), and 25% are threatened with extinction. International collaborators combine data from multiple study sites to monitor populations on regional and global scales [4,5,6,7]. Population change is sometimes measured indirectly, using a proxy measure, such as change in habitat extent [8,9,10]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
