Demographic Characteristics of Extinction in a Small, Insular Population of House Sparrows in Northern Norway

• Published in: Conservation Biology
• Main Authors: RINGSBY, THOR HARALD, SÆTHER, BERNT‐ERIK, JENSEN, HENRIK, ENGEN, STEINAR
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2006
• Subjects: Norway; Northern Norway
• Online Access: http://dx.doi.org/10.1111/j.1523-1739.2006.00568.x; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fj.1523-1739.2006.00568.x; http://onlinelibrary.wiley.com/wol1/doi/10.1111/j.1523-1739.2006.00568.x/fullpdf

Abstract: In conservation ecology there is an urgent need for indicators that can be used to predict the risk of extinction of populations. Identifying extinction‐prone populations has been difficult because few data sets on the demographic characteristics of the final stage to extinction are available and because of problems in separating out stochastic effects from changes in the expected dynamics. We documented the demographic changes that occurred during the period prior to extinction of a small island population of House Sparrows ( Passer domesticus ) after the end of permanent human settlement. A mark‐recapture analysis revealed that this decline to extinction was mainly due to increased mortality after closure of the last farm that resulted in a negative long‐term‐specific growth rate. No change occurred in either the structural composition (breeding sex ratio and age distribution) of the population or in female recruitment. No male, however, recruits were produced on the island after the farm closure. Based on a simple, stochastic, density‐dependent model we constructed a population prediction interval (PPI) to estimate the time to extinction. The 95% PPI slightly overestimated the time to extinction with large uncertainty in predictions, especially due to the influence of demographic stochasticity and parameter drift. Our results strongly emphasize the importance of access to data on temporal variation that can be used to parameterize simple population models that allow estimation of critical parameters for credible prediction of time to extinction.