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DIAGNOSING A SHOREBIRD LOCAL POPULATION DECLINE WITH A STAGE‐STRUCTURED POPULATION MODEL
Author(s) -
Hitchcock Christine L.,
Gratto-Trevor Cheri
Publication year - 1997
Publication title -
ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.144
H-Index - 294
eISSN - 1939-9170
pISSN - 0012-9658
DOI - 10.1890/0012-9658(1997)078[0522:daslpd]2.0.co;2
Subject(s) - survivorship curve , population , vital rates , fecundity , demography , juvenile , population model , population decline , population growth , ecology , biology , sociology
The breeding population of Semipalmated Sandpipers at La Pérouse Bay, Churchill, Manitoba declined sharply during the 1980s. Using demographic information collected during eight summers of field work we built a stochastic matrix population model. The model successfully reconstructed the observed decline in the population during the course of the study. The predictions of the model agreed with the observed population level in 1993, 5 yr after the study was completed. Sensitivity analysis showed that the population trend was most sensitive to changes in adult survivorship and to immigration of adults onto the site. We ran simulations to consider five possible reasons for the decline: (1) low adult survivorship, (2) low fecundity, (3) delayed recruitment into the population, (4) low juvenile survivorship, and (5) insufficient immigration. For biologically reasonable values of these parameters, only adult survivorship and immigration rates could account for the observed decline, although juvenile survival also had some impact. These simulations also illustrate that sensitivity is a complex function of the demographic variables, and in particular, sensitivity to adult survival varies across the range of adult survival values that we considered. In addition, we used the model to explore the influence of annual variability in demographic parameters. It is known that the general effect of annual variation is to depress population trends. We showed that the sensitivity of the model to annual variability in survival is tied to the sensitivity of the model to changes in mean values of survival. With the empirical parameter values from this local population, we found that, when survival is high enough to promote stability of the population, the population is highly sensitive to the level of survival, and also to the amount of annual variability in survival. By contrast, the model is not very sensitive to fecundity and is correspondingly insensitive to annual variation in fecundity.