Improving bald eagle nest monitoring with a second spring survey

Abstract

Failure to account for observation error can cause bias in estimators of variables important for wildlife management and conservation, such as abundance, occupancy, and species composition. Therefore, long‐term monitoring programs need to evaluate sources of bias to ensure that objectives of the program can be met. Although trend estimation is possible using biased estimators, population status, and management decisions can be sensitive to random and systematic heterogeneity in the observation process. For example, standard methods used to monitor reproductive attempts at bald eagle (Haliaeetus leucocephalus) nests fail to quantify observation error. We used bald eagle nest surveys from 3 national parks in Alaska, USA, to examine their ability to accurately estimate nesting attempts and hypothesized that our ability to perfectly observe nesting activity was related to the timing of the survey relative to peak nest attendance by eagles. We therefore, developed 3 scenarios that evaluated our ability to correctly identify nesting status metrics: peak nesting remained unchanged (observed variation scenario), reduced ability to predict peak nest attendance (high heterogeneity scenario), and peak nest attendance occurred earlier than the survey window (low detection scenario). Eagle nest attendance was consistently underestimated using naïve estimators, but productivity (predicted no. chicks/nesting attempt) was not affected by imperfect detection. All scenarios showed that using replicate observations to model imperfect detection corrected estimator bias for nest attendance and improved the estimator precision for both metrics. Our study demonstrates that imperfect observation of bald eagle nesting activity using standard methods results in estimator bias and reduced precision if not corrected. Further, our simulations show that changes in observation conditions can affect estimator bias and precision, which is an important consideration for long‐term monitoring programs. Therefore, formally modeling imperfect detection should be completed for monitoring programs designed to use nesting status to inform management or conservation decisions. © 2017 The Wildlife Society.

Nest use dynamics of an undisturbed population of bald eagles

“…We know this assumption was likely violated based on a previous analysis of our field methods (Wilson, Phillips, & Mangipane, 2017); and imperfect detection very likely affected our estimates. For example, transitions from the occupied state were not different from what is expected from a random process and is most likely a result of imperfect separation of the unoccupied and occupied states.…”

Direct and indirect effects of temperature and prey abundance on bald eagle reproductive dynamics

“…When this occurred, the new nests were added to the list as during the occupancy survey, but if no chicks were present, the occupancy state was assumed to be unknown because there was no way to know if the nest had been occupied but then failed prior to the second survey. We acknowledge that a single survey during each period likely resulted in state misclassification errors (i.e., Wilson et al 2017), although we expect these to be limited because bald eagles tend to have high nest attendance rates during the incubation period (Buehler 2000). Any errors would also most likely increase variation in our data, thereby decreasing our ability to detect covariate effects rather than leading to spurious results.…”