PLoS ONE (Jan 2016)

On the Challenge of Interpreting Census Data: Insights from a Study of an Endangered Pinniped.

  • Fritz Trillmich,
  • Kristine Meise,
  • Stephanie Kalberer,
  • Birte Mueller,
  • Paolo Piedrahita,
  • Ulrich Pörschmann,
  • Jochen B W Wolf,
  • Oliver Krüger

DOI
https://doi.org/10.1371/journal.pone.0154588
Journal volume & issue
Vol. 11, no. 5
p. e0154588

Abstract

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Population monitoring is vital for conservation and management. However, simple counts of animals can be misleading and this problem is exacerbated in seals (pinnipeds) where individuals spend much time foraging away from colonies. We analyzed a 13-year-series of census data of Galapagos sea lions (Zalophus wollebaeki) from the colony of Caamaño, an islet in the center of the Galapagos archipelago where a large proportion of animals was individually marked. Based on regular resighting efforts during the cold, reproductive (cold-R; August to January) and the warm, non-reproductive (warm-nR; February to May) season, we document changes in numbers for different sex and age classes. During the cold-R season the number of adults increased as the number of newborn pups increased. Numbers were larger in the morning and evening than around mid-day and not significantly influenced by tide levels. More adults frequented the colony during the warm-nR season than the cold-R season. Raw counts suggested a decline in numbers over the 13 years, but Lincoln-Petersen (LP-) estimates (assuming a closed population) did not support that conclusion. Raw counts and LP estimates were not significantly correlated, demonstrating the overwhelming importance of variability in attendance patterns of individuals. The probability of observing a given adult in the colony varied between 16% (mean for cold-R season) and 23% (warm-nR season) and may be much less for independent 2 to 4 year olds. Dependent juveniles (up to the age of about 2 years) are observed much more frequently ashore (35% during the cold-R and 50% during the warm-nR seasons). Simple counts underestimate real population size by a factor of 4-6 and may lead to erroneous conclusions about trends in population size.