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Todd Dubreuil

Publications and source records attributed to Todd Dubreuil.

5 recordsLinked to original sources

Technical note: A low-cost approach to monitoring relative streamflow dynamics in small headwater streams using time lapse imagery and a deep learning model

Despite their ubiquity and importance as freshwater habitat, small headwater streams are under-monitored by existing stream gage networks. To address this gap, we describe a low-cost, non-contact, and low-effort method that enables organizations to monitor relative streamflow dynamics in small headwater streams. The method uses a camera to capture repeat images of the stream from a fixed position. A person then annotates pairs of images, in each case indicating which image has more apparent streamflow or indicating equal flow if no difference is discernible. A deep learning modeling framework called streamflow rank estimation (SRE) is then trained on the annotated image pairs and applied to rank all images from highest to lowest apparent streamflow. From this result a relative hydrograph can be derived. We found that our modeled relative hydrograph dynamics matched the observed hydrograph dynamics well for 11 cameras at 8 streamflow sites in western Massachusetts. Higher performance was observed during the annotation period (median Kendall's Tau rank correlation of 0.75, with a range of 0.6–0.83) than after it (median Kendall's Tau of 0.59, with range 0.34–0.74). We found that annotation performance was generally consistent across the 11 camera sites and 2 individual annotators and was positively correlated with streamflow variability at a site. A scaling simulation determined that model performance improvements were limited after 1000 annotation pairs. Our model's estimates of relative flow, while not equivalent to absolute flow, may still be useful for many applications, such as ecological modeling and calculating event-based hydrological statistics (e.g., the number of out-of-bank floods). We anticipate that this method will be a valuable tool to extend existing stream monitoring networks and provide new insights on dynamic headwater systems.

Massachusetts

A low-cost approach to monitoring streamflow dynamics in small, headwater streams using timelapse imagery and a deep learning model

Despite their ubiquity and importance as freshwater habitat, small headwater streams are under monitored by existing stream gage networks. To address this gap, we describe a low-cost, non-contact, and low-effort method that enables organizations to monitor streamflow dynamics in small headwater streams. The method uses a camera to capture repeat images of the stream from a fixed position. A person then annotates pairs of images, in each case indicating which image has more apparent streamflow or indicating equal flow if no difference is discernible. A deep learning modelling framework called Streamflow Rank Estimation (SRE) is then trained on the annotated image pairs and applied to rank all images from highest to lowest apparent streamflow. From this result a relative hydrograph can be derived. We found that our modelled relative hydrograph dynamics matched the observed hydrograph dynamics well for 11 cameras at 8 streamflow sites in western Massachusetts. Higher performance was observed during the annotation period (median Kendall’s Tau rank correlation 0.75 with range 0.6–0.83) than after it (median Kendall’s Tau 0.59 with range 0.34 – 0.74). We found that annotation performance was generally consistent across the eleven camera sites and two individual annotators and was positively correlated with streamflow variability at a site. A scaling simulation determined that model performance improvements were limited after 1,000 annotation pairs. Our model’s estimates of relative flow, while not equivalent to absolute flow, may still be useful for many applications, such as ecological modelling and calculating event-based hydrological statistics (e.g., the number of out-of-bank floods). We anticipate this method will be a valuable tool to extend existing stream monitoring networks and provide new insights on dynamic headwater systems.

EGUSphere

Negative growth in body mass of trout and salmon in a small stream network

In species inhabiting stressful environments, some individuals experience negative growth in body mass during their lives, potentially influencing survival, reproduction, populations, and ecosystems. Using data from a long-term (1997–2015) study of brook trout ( Salvelinus fontinalis ), brown trout ( Salmo trutta ), and juvenile Atlantic salmon ( Salmo salar ) in Massachusetts, USA, we analyzed the frequency, causes, and consequences of seasonal mass loss. Negative growth occurred in 14.8% of observations (3573 instances), with the highest prevalence during summer (June–September). Species differed markedly: 42.5% of juvenile Atlantic salmon, 24.9% of brook trout, but only 7.7% of brown trout exhibited negative growth. The likelihood of mass loss increased with size, age, and low stream flows, particularly in summer. Brook trout in the small or isolated tributaries exhibited less summer mass loss than those in the larger streams. Other factors, including temperature and population density, had minimal or inconsistent effects. Individuals experiencing negative growth, especially brook trout in summer and autumn, were less likely to be re-encountered. As we observed no association of mass loss with movement, this suggests a potential survival cost of negative body mass growth.

Massachusetts

Survival and density of a dominant fish species across a gradient of urbanization in North Carolina tidal creeks

Development in the southeastern U.S. coastal plain generates the need for a better understanding of how demographics (survival and abundance) of estuarine nekton respond to urbanization. Apparent survival and density of the dominant Atlantic coast salt marsh fish, Fundulus heteroclitus, were estimated in four North Carolina tidal creeks using a model simultaneously fitted to mark-resight and mark-recapture data. Rates of weekly loss (mortality plus emigration) were high (~10%). Sampling for tagged fish within- and outside of study creeks showed high site fidelity to each creek, suggesting that loss largely result from mortality rather than emigration. Estimated rates of apparent survival were lowest in the creek with the least instream- and watershed-level impacts relative to creeks with greater impacts; this was also the creek with direct (non-culvert) access downstream to a larger waterbody, suggesting that enhanced access by predators and/or greater rates of permanent emigration may have contributed to loss there. There was a positive relationship between minnow trap catch-per-unit-effort (CPUE) and density; CPUE was used to index density so that the relationship between it and habitat and urbanization effects could be examined in two additional (six total) study creeks. Highest CPUE estimates occurred early in each growing season and were associated with creeks possessing characteristics most representative of undisturbed salt marsh mosaics: high percentages of marsh coverage instream and downstream and greatest percentages of marsh edge. Given generally limited movement outside of creeks, differences in abundance among creeks likely result from different levels of recruitment that are related to salt marsh availability. Natural resource planners should prioritize preservation of salt marsh habitats to maintain abundance levels of this trophically important species.

North Carolina

Estimating movement and survival rates of a small saltwater fish using autonomous antenna receiver arrays and passive integrated transponder tags

We evaluated the performance of small (12.5 mm long) passive integrated transponder (PIT) tags and custom detection antennas for obtaining fine-scale movement and demographic data of mummichog Fundulus heteroclitus in a salt marsh creek. Apparent survival and detection probability were estimated using a Cormack Jolly Seber (CJS) model fitted to detection data collected by an array of 3 vertical antennas from November 2010 to March 2011 and by a single horizontal antenna from April to August 2011. Movement of mummichogs was monitored during the period when the array of vertical antennas was used. Antenna performance was examined in situ using tags placed in wooden dowels (drones) and in live mummichogs. Of the 44 tagged fish, 42 were resighted over the 9 mo monitoring period. The in situ detection probabilities of the drone and live mummichogs were high (~80-100%) when the ambient water depth was less than ~0.8 m. Upstream and downstream movement of mummichogs was related to hourly water depth and direction of tidal current in a way that maximized time periods over which mummichogs utilized the intertidal vegetated marsh. Apparent survival was lower during periods of colder water temperatures in December 2010 and early January 2011 (median estimate of daily apparent survival = 0.979) than during other periods of the study (median estimate of daily apparent survival = 0.992). During late fall and winter, temperature had a positive effect on the CJS detection probability of a tagged mummichog, likely due to greater fish activity over warmer periods. During the spring and summer, this pattern reversed possibly due to mummichogs having reduced activity during the hottest periods. This study demonstrates the utility of PIT tags and continuously operating autonomous detection systems for tracking fish at fine temporal scales, and improving estimates of demographic parameters in salt marsh creeks that are difficult or impractical to sample with active fishing gear.

Marine Ecology Progress Series