Geology topics

Paul D. Scheerer

Publications and source records attributed to Paul D. Scheerer.

3 recordsLinked to original sources

USGS2023

A comprehensive multi-state conditional occupancy model for evaluating interactions of non-native and native species

A major challenge in ecology is disentangling interactions of non-native, potentially invasive species on native species. Conditional two-species occupancy models examine the effects of dominant species (e.g., non-native) on subordinate species (e.g., native) while considering the possibility that occupancy of one species may affect occupancy and/ or detection of the other. Although conditional two-species models are useful for evaluating the influence of one species on presence of another, it is possible that species interactions are density dependent. Therefore, we developed a novel two-species occupancy model that incorporates multiple abundance states (i.e., absent, present, abundant) of the native species. We showcase the utility of this model with a case study that incorporates random effects and covariates on both occupancy and detection to help disentangle species interactions given varying occupancy and detection in different abundance states. We use snorkel survey data from the Umpqua basin, Oregon, where it is hypothesized that smallmouth bass Micropterus dolomieu , a non-native piscivore, exclude Umpqua chub Oregonichthys kalawatseti , a small endemic minnow. From our two-species multi-state (2SMS) model, we concluded that average occupancy was low for both fishes, and that when non-native bass were present, overall native chub occupancy in the present (0.18 ± 0.05 SD) and abundant (0.19 ± 0.03) states was higher than when non-natives were absent (0.14 ± 0.02/ 0.08 ± 0.02), indicating the non-native was not excluding the native species. By incorporating a species interaction factor, we found a positive association (6.75 ± 5.54 SD) between native chub and non-native bass. The covariates strongly related to occupancy were elevation, algae, and land cover type (urban and shrub). Detection probability for both species (0.21–0.82) was most strongly related to the covariates day of year, water temperature, gravel substrate, and stream order/ magnitude. Incorporation of detection probability and covariates enabled interpretation of interactions between the two species that may have been missed without their inclusion in the modeling process. Our new 2SMS occupancy model can be used by scientists and managers with a broad range of survey and covariate data to disentangle species interactions problems to help them inform management decisions.

Frontiers in Ecology and Evolution↗

USGS2017

Distribution and abundance of Millicoma Dace in the Coos River Basin, Oregon

The Millicoma Dace Rhinichthys cataractae is a form of Longnose Dace endemic to the Coos River drainage in southwestern Oregon. Sparse species records in the Oregon State University Ichthyology Collection and database and infrequent recent encounters prompted surveys to assess the current status and distribution of the species. In 2014, we surveyed locations that had historically supported Millicoma Dace using backpack electrofishing to describe their current distribution and abundance at these locations. In 2015, we extended these surveys further upstream in the South Coos River basin, outside of the documented historical range. We used an N-mixture model to estimate abundance and capture probability for Millicoma Dace at each sampling location. We evaluated the effects of habitat covariates on both capture probability and abundance at each sample site. We found Millicoma Dace were widespread throughout their historical range and in the South Coos River sites outside of their documented historical range. We only found Millicoma Dace associated with native fishes; we did not collect any nonnative fish during our surveys. We collected Millicoma Dace exclusively from swift-water habitats, which were relatively uncommon in the basin, and found them typically associated with cobble or boulder substrates. Millicoma Dace were most abundant in the South Fork Coos and West Fork Millicoma River subbasins. We estimated capture probabilities for Millicoma Dace ranging from 9% when substrate was dominated by bedrock to 28% when substrate was dominated by cobble or gravel. Abundance estimates ranged from 1 to 560 dace per sampling location with a total estimated abundance (sum of site estimates) of over 3200 dace for the sites we sampled.

Oregon↗

USGS2015

An evaluation of the efficiency of minnow traps for estimating the abundance of minnows in desert spring systems

Desert springs are sensitive aquatic ecosystems that pose unique challenges to natural resource managers and researchers. Among the most important of these is the need to accurately quantify population parameters for resident fish, particularly when the species are of special conservation concern. We evaluated the efficiency of baited minnow traps for estimating the abundance of two at-risk species, Foskett Speckled Dace Rhinichthys osculus ssp. and Borax Lake Chub Gila boraxobius , in desert spring systems in southeastern Oregon. We evaluated alternative sample designs using simulation and found that capture–recapture designs with four capture occasions would maximize the accuracy of estimates and minimize fish handling. We implemented the design and estimated capture and recapture probabilities using the Huggins closed-capture estimator. Trap capture probabilities averaged 23% and 26% for Foskett Speckled Dace and Borax Lake Chub, respectively, but differed substantially among sample locations, through time, and nonlinearly with fish body size. Recapture probabilities for Foskett Speckled Dace were, on average, 1.6 times greater than (first) capture probabilities, suggesting “trap-happy” behavior. Comparison of population estimates from the Huggins model with the commonly used Lincoln–Petersen estimator indicated that the latter underestimated Foskett Speckled Dace and Borax Lake Chub population size by 48% and by 20%, respectively. These biases were due to variability in capture and recapture probabilities. Simulation of fish monitoring that included the range of capture and recapture probabilities observed indicated that variability in capture and recapture probabilities in time negatively affected the ability to detect annual decreases by up to 20% in fish population size. Failure to account for variability in capture and recapture probabilities can lead to poor quality data and study inferences. Therefore, we recommend that fishery researchers and managers employ sample designs and estimators that can account for this variability.

Oregon↗