Abstract

The shift from single species conservation initiatives to multiple-species conservation plans has not been accompanied by parallel changes in methods to evaluate the success of these efforts, nor to provide managers critical information to employ adaptive management strategies. Layering single species approaches for monitoring multiple-species conservation plans is inefficient and may lead to management strategies that have unintended detrimental impacts on target and nontarget organisms. Alternative approaches, such as ecosystem monitoring, can also fail to provide adequate protection for listed species and so may not fulfill regulatory requirements. We propose a hybrid approach that employs conceptual and spatial data in an iterative process to create niche models for species and species associations within natural communities. Niche models are composed of testable hypotheses linking species occurrences to environmental parameters over multiple scales. During an initial data gathering period these hypotheses are evaluated, accepted or rejected, and modified as indicated by new data. Once niche models are corroborated, the focus of monitoring shifts to a greater emphasis on identified anthropogenic and natural environmental drivers of species occurrence and abundance. The focus on environmental drivers supplies managers with direct information as to how, when, and where to employ adaptive management strategies when natural variance in those drivers is compromised by anthropogenic stressors. We provide a specific example on the conceptualization, development, and implementation of our hybrid approach from a new Multiple-species Habitat Conservation Plan for the Coachella Valley, in the Colorado desert of southern California.

Full Text
Paper version not known

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 call

Disclaimer: 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.