Ecosphere (Feb 2023)

Estimating recruitment rate and population dynamics at a migratory stopover site using an integrated population model

  • Anna M. Tucker,
  • Conor P. McGowan,
  • Bryan L. Nuse,
  • James E. Lyons,
  • Clinton T. Moore,
  • David R. Smith,
  • John A. Sweka,
  • Kristen A. Anstead,
  • Audrey DeRose‐Wilson,
  • Nigel A. Clark

DOI
https://doi.org/10.1002/ecs2.4439
Journal volume & issue
Vol. 14, no. 2
pp. n/a – n/a

Abstract

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Abstract Consideration of the full annual cycle population dynamics can provide useful insight for conservation efforts, but collecting data needed to estimate demographic parameters is often logistically difficult. For species that breed in remote areas, monitoring is often conducted during migratory stopover or at nonbreeding sites, and the recruitment rate of new breeding adults can be difficult to estimate directly. Here, we present an integrated population model that uses mark‐resight and count data to estimate survival probability, population growth rate, and recruitment rate for an Arctic‐breeding shorebird of conservation concern, the red knot (Calidris canutus rufa), from data collected during spring stopover in Delaware Bay, USA, from 2005 to 2018. At this site, red knots feed primarily on the eggs of spawning horseshoe crabs (Limulus polyphemus), a legally harvested species. We used this model to estimate the relationship between horseshoe crab abundance and red knot demographics, which informed a recent revision to the framework used to establish horseshoe crab harvest regulations. Our analysis indicates that the red knot population was most likely stable from 2005 to 2018 (average λ = 1.03, 95% credible interval [CRI]: 0.961, 1.15) despite low recruitment rates (average ρ = 0.088, 95% CRI: 0.012, 0.18). Adult survival probability was positively associated with horseshoe crab abundance in the same year (β = 0.35, 95% CRI: 0.09, 0.63), but we found no effect of horseshoe crab abundance two years previously on recruitment of new adults (β = −0.08, 95% CRI: −0.41, 0.38). Our approach demonstrates the utility of integrated population models for understanding population dynamics, even when data are only available from migratory stopover monitoring.

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