Geology topics

Mary Conner

Publications and source records attributed to Mary Conner.

4 recordsLinked to original sources

USGS2024

Beaver dam analogs did not improve beaver translocation outcomes in a desert river

Stream restoration programs employ beaver-related restoration techniques, including beaver translocations and installation of beaver dam analogs (BDA), to create complex in-stream habitat. We investigated whether BDA installations improved the probability of translocated beavers surviving and colonizing a section of a degraded desert river. We translocated beavers fitted with tracking devices to the Price River, Utah, United States, for 2 years before and after BDAs were installed. We monitored survival and site fidelity of beavers to estimate apparent survival ( φ ), using model selection to evaluate models with BDA, flow, and other factors hypothesized to relate to apparent survival. We found similar apparent survival 8 weeks post-release of pre-BDA ( φ = 0.50 ± 0.08 SE) and post-BDA beavers ( φ = 0.41 ± 0.06 SE). There were 15 predator-caused mortalities and 39 beavers emigrated out of the study site. Top models indicated apparent survival was negatively related to mean flow. Of the 70 BDAs constructed, beaver activity was detected on only two structures and the number of intact natural dams decreased due to monsoon floods. Our results suggest BDAs may not improve survival and site fidelity of translocated beavers in desert river systems. Instead, the dynamic flow of desert rivers and negative relationship between flow and apparent survival suggest the timing of release may be an important consideration for successful beaver translocation. Additional research is needed to understand how habitat, food availability, individual behavior, and resident conspecifics influence beaver translocation success.

Utah↗

USGS2020

Keeping it classy: Classification of live fish and ghost PIT tags detected with a mobile PIT tag interrogation system using an innovative analytical approach

The ability of passive integrated transponder (PIT) tag data to improve demographic parameter estimates has led to the rapid advancement of PIT tag systems. However, ghost tags create uncertainty about detected tag status (i.e., live fish or ghost tag) when using mobile interrogation systems. We developed a method to differentiate between live fish and ghost tags using a random forest classification model with a novel data input structure based on known fate PIT tag detections in the San Juan River (New Mexico, Colorado, and Utah, USA). We used our model to classify detected tags with an overall error rate of 6.8% (1.6% ghost tags error rate and 21.8% live fish error rate). The important variables for classification were related to distance moved and response to monsoonal flood flows; however, habitat variables did not appear to influence model accuracy. Our results and approach allow the use of mobile detection data with confidence and allow for greater accuracy in movement, distribution, and habitat use studies, potentially helping identify influential management actions that would improve our ability to conserve and recover endangered fish.

Canadian Journal of Fisheries and Aquatic Sciences↗

USGS2019

We ain’t afraid of no ghosts: Tracking habitat interactions and movement dynamics of ghost PIT tags under differing flow conditions in a sand bed river

The use of PIT tags has rapidly proliferated since their introduction, and new mobile detection methods have been developed. However, the presence of ghost tags (i.e., PIT tags left in the system after a fish dies) creates uncertainty about the status (live or dead) of tags detected. Herein, we describe our raft-based mobile PIT tag antenna system, which was used to evaluate the movements of “seeded tags” (i.e., PIT tags that we placed in the river as ghost tag analogs) and their interactions with habitat features. We deployed 5,000 seeded tags in the San Juan River, a large sand-bed river in the southwestern USA. Total distances moved by PIT tags ranged from 0.8 to 4,124 m, but 75% of movements were less than 100 m. Flow conditions causing the smallest to largest movements were (1) base flows, (2) spring runoff flows, (3) flash flood flows, and (4) a combination of spring runoff and flash flood flows. Based on Ivlev's electivity index, tags were more likely to be detected in riffles than in runs. These findings will help to classify mobile PIT tag detections as ghost tags or live fish, a critical data gap limiting the accurate estimation of demographic rates, population status metrics, and descriptions of the habitat use of fishes.

North American Journal of Fisheries Management↗

USGS2017

Quantifying long-term population growth rates of threatened bull trout: challenges, lessons learned, and opportunities

Temporal symmetry models (TSM) represent advances in the analytical application of mark–recapture data to population status assessments. For a population of char, we employed 10 years of active and passive mark–recapture data to quantify population growth rates using different data sources and analytical approaches. Estimates of adult population growth rate were 1.01 (95% confidence interval = 0.84–1.20) using a temporal symmetry model ( λ TSM ), 0.96 (0.68–1.34) based on logistic regressions of annual snorkel data ( λ A ), and 0.92 (0.77–1.11) from redd counts ( λ R ). Top-performing TSMs included an increasing time trend in recruitment ( f ) and changes in capture probability ( p ). There was only a 1% chance the population decreased ≥50%, and a 10% chance it decreased ≥30% ( λ MCMC ; based on Bayesian Markov chain Monte Carlo procedure). Size structure was stable; however, the adult population was dominated by small adults, and over the study period there was a decline in the contribution of large adults to total biomass. Juvenile condition decreased with increasing adult densities. Utilization of these different information sources provided a robust weight-of-evidence approach to identifying population status and potential mechanisms driving changes in population growth rates.

Oregon↗