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Conservation challenges of a sink: the viability of an isolated population of the Snowy Plover

Published online by Cambridge University Press:  06 February 2014

LUKE J. EBERHART-PHILLIPS*
Affiliation:
Present Address: Department of Animal Behaviour, Universität Bielefeld, Morgenbreede 45, 33615 Bielefeld, Germany.
MARK A. COLWELL
Affiliation:
Department of Wildlife, Humboldt State University, 1 Harpst Street, Arcata, CA 95521, USA.
*
*Author for correspondence; email: luke.eberhart@uni-bielefeld.de
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Summary

Source-sink dynamics are easily overlooked when formulating recovery objectives for threatened species. This could lead to unrealistic criteria imposed on sink populations, which in turn might restrict an entire metapopulation from being delisted. Therefore, an understanding of the viability of subpopulations within the context of a metapopulation is needed to develop appropriate recovery objectives. Consequently, we used 11 years of mark-recapture, productivity, and movement data to analyse the viability of a small, geographically isolated population of the Snowy Plover Charadrius nivosus, a shorebird listed as threatened under the U.S. Endangered Species Act. Simulations confirmed that the focal population in northern California is a sink that relies upon immigrants from neighbouring populations. Furthermore, these source populations will increase within the next 50 years and are likely to achieve the delisting requirements. However, the northern California population is unlikely to reach the delisting criteria given the current vital rate estimations. Management scenarios demonstrated that lethal predator removal and reducing human disturbance facilitate population recovery and may partially alleviate the reliance upon immigration. However, the use of nest exclosures reduced population growth because they are known to compromise adult survival. These results highlight the importance of maintaining viable source populations and re-evaluating the recovery objectives of metapopulations with active sinks.

Information

Type
Research Articles
Copyright
Copyright © BirdLife International 2013 
Figure 0

Figure 1. Map of Snowy Plover distribution along the Pacific Coast of the United States with the delineation of the two populations used in the stochastic model. NCA is the northern California focal population and PAC is a source population consisting of surrounding recovery units contributing immigrants to northern California.

Figure 1

Figure 2. Sequence of life-history events and probabilities (P) used by VORTEX to model population growth of Snowy Plovers in northern California (NCA) in the context of the Pacific Coast population (PAC), where ϕi is the survival of age class i and ψj, k is the movement between population j and population k.

Figure 2

Figure 3. Comparison of observed and predicted population projections for (a) northern California and (b) the Pacific Coast between 2001 and 2011 using the 2001 initial population sizes and the baseline vital rates. Baseline model population projections for (c) northern California and (d) the Pacific Coast. Error bars represent the 95% confidence interval of the average population size of 1,000 iterations.

Figure 3

Figure 4. Elasticity of the stochastic growth rate of the northern California population for 21 model components specific to northern California (NCA), the Pacific Coast (PAC), or globally affecting both populations simultaneously (immigration, emigration, the winter cold weather catastrophe, and inbreeding). Total productivity represents a perturbation of both the broods per male and fledglings per brood distributions. All perturbations were made in the direction that would hypothetically favour growth in northern California.

Figure 4

Figure 5. Population projections for northern California under four management approaches addressing either predation or human disturbance: (a) lethal predator removal, (b) the use of nest exclosures, (c) fencing, and (d) fencing with three levels of hypothetical reductions in mortality related to vehicle strike. Error bars represent the 95% confidence interval of the average population size of 1,000 iterations.

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