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Finite study areas and vital rates: sampling effects on estimates of spotted owl survival and population trends
Author(s) -
ZIMMERMAN GUTHRIE S.,
GUTIÉRREZ R.J.,
LAHAYE WILLIAM S.
Publication year - 2007
Publication title -
journal of applied ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.503
H-Index - 181
eISSN - 1365-2664
pISSN - 0021-8901
DOI - 10.1111/j.1365-2664.2007.01343.x
Subject(s) - juvenile , vital rates , population , wildlife , geography , mark and recapture , estimator , population size , sample size determination , range (aeronautics) , endangered species , sampling (signal processing) , statistics , demography , ecology , biology , population growth , mathematics , physics , materials science , sociology , composite material , detector , optics
Summary1 Evaluating the status of endangered wildlife depends upon well‐designed field studies. Finances and logistics often constrain field studies to finite (limited‐sized) areas where inductive inferences are needed to extrapolate results to populations. Although available quantitative techniques for analysing data are robust to many aspects of field investigations, few investigators assess the influence of their study area size on estimators of population parameters and subsequent inferences derived from those estimators. 2 We used mark–recapture to monitor an entire population of spotted owls Strix occidentalis in the San Bernardino Mountains of southern California (2140 km 2 ) for which we knew the approximate true rate of survival. We defined hypothetical study areas of varying size by subsampling the population in increments of five territories; we then estimated apparent survival and emigration for non‐juvenile and juvenile owls within each of these sample study areas to assess the influence of study area size on estimators of survival and population trends. 3 Estimated survival rates of juvenile spotted owls increased approximately fourfold from the smallest sample area to the largest ( min = 0·08, SÊ = 0·03; max = 0·33, SÊ = 0·03). In contrast, estimates of apparent survival for non‐juvenile owls did not vary with study area size (range non‐juvenile = 0·80–0·82, SÊ = 0·01–0·03). 4 Juvenile emigration was extremely high in the smallest study area ( juvenile = 0·77, SÊ = 0·09) and remained above 10% until > 62% of our study area (approximately 900 km 2 ) was encompassed by a sample study area. Non‐juvenile owls had low annual emigration probabilities from all sample study area sizes (range non‐juvenile = 0·00–0·02). 5 Although estimates of λ (finite population growth rate) increased gradually from 0·828 to 0·903 as the subsample increased from 20 to 143 territories, these estimates were similar to the ‘true’ value. 6 Synthesis and applications. We provide direct estimates of the bias that sampling limited study areas has on emigration and mark–recapture estimators of survival. Our results demonstrate that permanent emigration from limited study areas can lead to underestimates of survival and population growth rates. In addition, our approach illustrates a technique for using multistate models to assess study design and estimator assumptions.