A framework for modeling the impacts of adaptive search intensity on the efficiency of abundance surveys

When planning abundance surveys, the impact of search intensity on the quality of the density estimates is rarely considered. We constructed a time-budget modeling framework for abundance surveys using principles from optimal foraging theory. We link search intensity to the number of sample units surveyed, searcher detection probability, the number of detections made, and the precision of the estimated population density. This framework allowed us to determine how a searcher should behave to produce optimized density estimates. Using data collected from quadrat and removal surveys of zebra mussels (Dreissena polymorpha) in central Minnesota, we applied this framework to evaluate potential improvements. We found that by tuning searcher behavior, density estimates from removal surveys of zebra mussels could be improved by up to 60% in some cases, without changing the overall survey time. Our framework also predicts a critical population density where the best survey method switches from removal surveys at low densities to quadrat surveys at high densities, consistent with past empirical work. In addition, we provide simulation tools to apply this form of analysis to a number of other commonly used survey designs. Our results provide insights into how to improve the performance of many survey methods in high-density environments by either tuning searcher behavior or decoupling the estimation of population density and detection probability.

A Comparison of Systematic Quadrat and Capture-Mark-Recapture Sampling Designs for Assessing Freshwater Mussel Populations

Our study objective was to compare the relative effectiveness and efficiency of quadrat and capture-mark-recapture (CMR) sampling designs for monitoring mussels. We collected data on a recently reintroduced population of federally endangered Epioblasma capsaeformis and two nonlisted, naturally occurring species—Actinonaias pectorosa and Medionidus conradicus—in the Upper Clinch River, Virginia, over two years using systematic quadrat and CMR sampling. Both sampling approaches produced similar estimates of abundance; however, precision of estimates varied between approaches, years, and among species, and further, quadrat sampling efficiency of mussels detectable on the substrate surface varied among species. CMR modeling revealed that capture probabilities for all three study species varied by time and were positively associated with shell length, that E. capsaeformis detection was influenced by sex, and that year-to-year apparent survival was high (>96%) for reintroduced E. capsaeformis. We recommend that monitoring projects use systematic quadrat sampling when the objective is to estimate and detect trends in abundance for species of moderate to high densities (>0.2/m2), whereas a CMR component should be incorporated when objectives include assessing reintroduced populations, obtaining reliable estimates of survival and recruitment, or producing unbiased population estimates for species of low to moderate densities (≤0.2/m2).

A semi-arid river in distress: Contributing factors and recovery solutions for three imperiled freshwater mussels (Family Unionidae) endemic to the Rio Grande basin in North America

Freshwater resources in arid and semi-arid regions are in extreme demand, which creates conflicts between needs of humans and aquatic ecosystems. The Rio Grande basin in the southwestern United States and northern Mexico exemplifies this issue, as much of its aquatic biodiversity is in peril as a result of human activities. Unionid mussels have been disproportionately impacted, though the specific factors responsible for their decline remain largely unknown. This is problematic because the Rio Grande basin harbors one federally endangered unionid mussel (Popenaias popeii, Texas Hornshell) plus two other mussel species (Potamilus metnecktayi, Salina Mucket; and Truncilla cognata, Mexican Fawnsfoot), which are also being considered for listing under the U.S. Endangered Species Act. To date, surveys for these species have not corrected for variability in detection so current range estimates may be inaccurate. Using single occupancy-modeling to estimate detection and occupancy at 115 sites along ~800 river kilometers of the Rio Grande in Texas, we found that detection probabilities were relatively high, indicating that our survey design was efficient. In contrast, the estimated occupancy was low, indicating that our focal species were likely rare within the Rio Grande drainage. In general, the predicted occupancy of our focal species was low throughout their respective ranges, indicating possible range declines. A comparison of currently occupied ranges to presumptive ranges underscores this point. The best-approximating models indicated that occupancy was influenced by habitat, water quantity and quality, and proximity to large-scale human activities, such as dams and major urban centers. We also discuss a series of conservation options that may not only improve the long-term prognosis of our focal species but also other aquatic taxa.