A General Framework for Setting Quantitative Population Objectives for Wildlife Conservation

Kristen E Dybala ,Rodd Kelsey,Thomas Gardali,Stefan Lorenzato,Ronald Melcer ,Neil Clipperton,Nathaniel E Seavy ,Joseph G Silveira ,Gregory H Golet ,Gregory S Yarris

doi:10.15447/sfews.2017v15iss1art8

Abstract

Author(s): Dybala, Kristen E.; Clipperton, Neil; Gardali, Thomas; Golet, Gregory H.; Kelsey, Rodd; Lorenzato, Stefan; Melcer, Jr., Ronald; Seavy, Nathaniel; Silveira, Joseph G.; Yarris, Gregory S. | Abstract: Quantitative population objectives are necessary to successfully achieve conservation goals of secure or robust wildlife populations. However, existing methods for setting quantitative population objectives commonly require extensive species-specific population viability data, which are often unavailable or are based on estimates of historical population sizes, which may no longer represent feasible objectives. Conservation practitioners require an alternative, science-based method for setting long-term quantitative population objectives. We reviewed conservation biology literature to develop a general conceptual framework that represents conservation biology principles and identifies key milestones a population would be expected to pass in the process of becoming a recovered or robust population. We then synthesized recent research to propose general hypotheses for the orders of magnitude at which most populations would be expected to reach each milestone. The framework is structured as a hierarchy of four population sizes, ranging from very small populations at increased risk of inbreeding depression and extirpation (l 1,000 adults) to large populations with minimized risk of extirpation (g 50,000 adults), along with additional modifiers describing steeply declining and resilient populations. We also discuss the temporal and geographic scales at which this framework should be applied. To illustrate the application of this framework to conservation planning, we outline our use of the framework to set long-term population objectives for a multi-species regional conservation plan, and discuss additional considerations in applying this framework to other systems. This general framework provides a transparent, science-based method by which conservation practitioners and stakeholders can agree on long-term population objectives of an appropriate magnitude, particularly when the alternative approaches are not feasible. With initial population objectives determined, long-term conservation planning and implementation can get underway, while further refinement of the objectives still remains possible as the population’s response to conservation effort is monitored and new data become available.

Highlights

Conservation objectives are the specific, measurable changes that are necessary to achieve broad and visionary conservation goals (CMP 2013), such as improving ecological integrity (LCC 2014); enhancing ecosystem function, services, or resilience (UNEP 2010); and achieving recovered, secure, or robust wildlife populations (Rich et al 2004; NOAA 2012)
Generating clear and scientifically defensible conservation objectives is a critical component of successful conservation planning and implementation (Margules and Pressey 2000; Villard and Jonsson 2009)
When the conservation goal is to achieve recovered, secure, or robust wildlife populations, conservation objectives often take the form of a target population size

Summary

Introduction

Conservation objectives are the specific, measurable changes that are necessary to achieve broad and visionary conservation goals (CMP 2013), such as improving ecological integrity (LCC 2014); enhancing ecosystem function, services, or resilience (UNEP 2010); and achieving recovered, secure, or robust wildlife populations (Rich et al 2004; NOAA 2012). When the conservation goal is to achieve recovered, secure, or robust wildlife populations, conservation objectives often take the form of a target population size. To establish these population objectives, one recommended approach is to estimate the minimum viable population (MVP) size (Himes Boor 2014; Doak et al 2015), defined as the smallest population size at which the population has a high probability of persisting for a desired length of time (Morris and Doak 2002). Few recovery plans for at-risk species have used population viability analyses to set recovery

Objectives

Findings

Conclusion