Figure 1 - available via license: Creative Commons Attribution 4.0 International
Content may be subject to copyright.
Source publication
For nearly 50 years, the California Department of Fish and Wildlife has used a midwater trawl to intensively monitor fish populations in the San Francisco Estuary during the fall, sampling over 100 locations each month. The data collected have been useful for calculating indices of fish abundance, and for detecting and documenting the decline of th...
Contexts in source publication
Context 1
... sampled with the midwater trawl net used in the FMWT Survey (https://www.wildlife.ca.gov/ Conservation/Delta/Fall-Midwater-Trawl), which has mouth dimensions of 3.7 m by 3.7 m, and consists of nine sections of decreasing mesh size from 20-cm stretch mesh near the mouth to 1.3-cm stretch mesh at the cod end (Figure 1). We placed a cover with 0.25-cm woven mesh, similar to that of the Summer Townet (TNS) cod end (https://www.wildlife.ca.gov/ ...
Context 2
... surface tows, we affixed a constraining rope at the ends of the 30.5-m (100-ft) bridle to maintain net-mouth shape and bridle separation equivalent to deployment from a single boat (see Figure 1). This also ensured that the force of the two boats towing slightly away from one another did not change mouth dimensions or collapse the net. ...
Similar publications
Fifteen specimens of the big-scale sand smelt, Atherina boyeri were caught by a single trawl haul with a net mesh size of 3 mm on February 2017 from the Seyhan Dam Reservoir (South Anatolia, Adana/Turkey).In this study the big-scale sand smelt, A. boyeri, was recorded for the first time in the Seyhan Dam Reservoir. In addition, some morphometric an...
Citations
... Reference source not found.). We recognize that gear retention likely negatively affected spring and summer detection of age-0 Longfin Smelt (c.f., Mitchell et al. 2017Mitchell et al. , 2019 and that mesh size and additional debris and fish collected by the Bay Study OT likely improved summer detection relative to the MWT (Mitchell et al. 2017); however, no Longfin Smelt retention information is available for the MWT nor is any retention information available for Bay Study OT, so this analysis ignores selectivity effects, although the use of a 40 mm FL minimum length of inclusion in length and catch records did reduce the number of records where selectivity might have effected catches. Age class records were labeled by year-class year (the year when fish hatched and were detected as age-0 fish) to facilitate consistent predictions across subsequent calendar years as fish increment ages (i.e., to prevent jumps in predicted probability of catch from December to January). ...
... Reference source not found.). We recognize that gear retention likely negatively affected spring and summer detection of age-0 Longfin Smelt (c.f., Mitchell et al. 2017Mitchell et al. , 2019 and that mesh size and additional debris and fish collected by the Bay Study OT likely improved summer detection relative to the MWT (Mitchell et al. 2017); however, no Longfin Smelt retention information is available for the MWT nor is any retention information available for Bay Study OT, so this analysis ignores selectivity effects, although the use of a 40 mm FL minimum length of inclusion in length and catch records did reduce the number of records where selectivity might have effected catches. Age class records were labeled by year-class year (the year when fish hatched and were detected as age-0 fish) to facilitate consistent predictions across subsequent calendar years as fish increment ages (i.e., to prevent jumps in predicted probability of catch from December to January). ...
... The pattern of decreasing probability of capture in every region over the long-term Variation in regional probability of presence reflects events in life history as well as changes in behavior. The general pattern in the probability of presence curves for age-0 Longfin Smelt is explained to a large extent by recruitment to the gear, which likely occurs fully for some in their first fall and for most through the subsequent winter, based on retention of Delta Smelt and its similar but slightly thicker body shape at length compared to Longfin Smelt (Mitchell et al. 2017). There is also evidence that that Longfin Smelt in the SFE are anadromous and that beginning at age 0 but more commonly at age 1, they spend the summer months outside the SFE in the coastal ocean and in cool marine salinities in Central Bay (Error! ...
Coincident changes in abundance and behavior pose a challenge for interpreting abundance data from monitoring programs. In the San Francisco Estuary, long-term monitoring documented the declines of many species including the anadromous Longfin Smelt (Spirinchus thaleichthys). We identified seasonal patterns in reginal presence of Longfin Smelt through its life cycle using monitoring data and generalized additive modelling. We then investigated the year-to-year variability in the seasonal patterns of presence using functional data analysis (FDA). FDA separated the variability due to population size from variability due to differences in timing of presence. We found that Longfin Smelt have consistent seasonal distribution patterns and that two trawl types were needed to accurately describe those patterns. After accounting for variability due to year-class strength, shifts in the timing of presence were evident in three regions. The most variable period for the upstream regions Suisun Bay and West Delta was for age-0 fish in summer and for the downstream region Central Bay was for age-0 fish in late fall. This manifested as a delay in the typical fall re-occupation of upstream regions that comprise the study area for another monitoring study (Fall Midwater Trawl). Thus, a portion of the recent reductions in Fall Midwater Trawl abundance of Longfin Smelt resulted from changes in behavior rather than a decline in abundance. The presence of multiple monitoring surveys allowed analysis of distribution from one data set to aid interpretation of patterns in abundance from another monitoring survey. This study highlights how identifying portions of the life cycle with the most and least variability in distribution can help inform the types of management strategies that will be most effective. It also illustrates an analytical method that can be used to address the problem of confounded effects of abundance and behavior on patterns in monitoring data.
... Although standardized protocols were used to sample during this study, issues of catchability are potentially a significant source of bias in our and other fish community analyses. Recent efforts in the San Francisco Estuary have demonstrated significant differences among fish species in their catchability using common surveying gears, and these differences can also be detected using the same gear types for similar fish species depending on fish life stage and the habitat types sampled (Huntsman et al., 2022;Huntsman, Feyrer, Young, Hobbs, et al., 2021;Mitchell et al., 2017;Mitchell & Baxter, 2021). We used gill nets during our sampling, which target active fishes and potentially bias our sampling toward fishes with active life-history traits (Feyrer & Healey, 2002). ...
Terminal channels were historically a common feature of tidal delta ecosystems but have become increasingly rare as landscapes have been modified. Tidal hydrodynamics are a defining feature in tidal terminal channel ecosystems from which native aquatic communities have evolved. However, few studies have explored the relationship between fish community structure and hydrodynamics in these tidal terminal channel ecosystems. We sampled fish communities throughout a network of terminal channels within the northeasternmost region of the San Francisco Estuary to determine the relationship between fish community structure and hydrodynamics within these environments. We collected two years (2017 and 2018) of fish community samples using gill nets and analyzed data using multivariate community analyses and count models. We found metrics of fish diversity and counts of native fishes to be greatest upstream (farthest from tidal influence) of the tidal excursion within terminal channels. Counts of non‐native fishes were less affected by this hydrodynamic feature of terminal channels and more tightly correlated to local habitat conditions (e.g., water temperature, depth). Our results suggest that channel hydrodynamics plays a role in structuring fish communities within terminal channels, particularly native fishes. These results indicate that hydrodynamics in tidal delta ecosystems may be able to be altered in ways that benefit native fishes without the cost of water pumping.
... A substantial amount of work has been done to account for observation error from differences in catchability and to provide measures of uncertainty (Walsh 1997;Royle 2004;MacKenzie and Royle 2005;Kéry and Royle 2016). Yet, work to estimate catchability in the estuary to date has either included a select few species (Perry et al. 2016;Mitchell et al. 2017;Mitchell et al. 2019;Huntsman et al. 2021aHuntsman et al. , 2021b or focused on occupancy rather than abundance (Mahardja et al. 2017;Peterson and Barajas 2018). ...
... Next, we assigned fish to a large (> 50 mm FL) or small size (≤ 50 mm FL) category. We adopted this size threshold because a gear efficiency study of the FMWT found that Delta Smelt (Hypomesus transpacificus) greater than approximately 50 mm were more likely to be retained in the cod end of the trawl (Mitchell et al. 2017). We only fit models when the species-size category was present in at least two gear types, because a catch-ratio cannot be made if the fish is present in only one gear. ...
... Unless direct gear efficiency experiments have been conducted (see Mitchell et al. 2017Mitchell et al. , 2019Mitchell and Baxter 2021), studies that combine gear types must either include gear type in model structure to account for some variability in catch as a result of gear type (as fixed or often random effects) or assume equal catchability among gear types for each target species. Although this assumption may not be a critical flaw for some species with little differences in catchability among gear types, strong violations of this assumption can lead to significant bias in interpretations of spatial and temporal trends in population and community dynamics. ...
Fish monitoring gears rarely capture all available fish, an inherent bias in monitoring programs referred to as catchability. Catchability is a source of bias that can be affected by numerous aspects of gear deployment (e.g., deployment speed, mesh size, and avoidance behavior). Thus, care must be taken when multiple surveys—especially those using different sampling methods—are combined to answer spatio-temporal questions about population and community dynamics. We assessed relative catchability differences among four long-term fish monitoring surveys from the San Francisco Estuary: the Bay Study Otter Trawl (BSOT), the Bay Study Midwater Trawl (BSMT), the Fall Midwater Trawl (FMWT), and the Suisun Marsh Otter Trawl (SMOT). We used generalized additive models with a spatio-temporal smoother and survey as a fixed effect to predict gear-specific estimates of catch for 45 different fish species within large and small size classes. We used estimates of the fixed effect coefficients for each survey (e.g., BSOT) relative to the reference gear (FMWT) to develop relative measures of catchability among taxa, surveys, and fish-size classes, termed the catch-ratio. We found higher relative catchability of 27%, 22%, and 57% of fish species in large size classes from the FMWT than in the BSMT, BSOT, or SMOT, respectively. In the small size class, relative catchability was higher in the FMWT than the BSMT, BSOT, or SMOT for 50%, 18%, and 25% of fish species, respectively. As expected, relative catchability of demersal species was higher in the otter trawls (BSOT, SMOT) while relative catchability of pelagic species was higher in the midwater trawls (FMWT, BSMT). Our results demonstrate that catchability is a source of bias among monitoring efforts within the San Francisco Estuary, and assuming equal catchability among surveys, species, and size classes could result in significant bias when describing spatio-temporal patterns in catch if ignored.
... A substantial amount of work has been done to account for observation error from differences in catchability and to provide measures of uncertainty (Walsh 1997;Royle 2004;MacKenzie and Royle 2005;Kéry and Royle 2016). Yet, work to estimate catchability in the estuary to date has either included a select few species (Perry et al. 2016;Mitchell et al. 2017;Mitchell et al. 2019;Huntsman et al. 2021aHuntsman et al. , 2021b or focused on occupancy rather than abundance (Mahardja et al. 2017;Peterson and Barajas 2018). ...
... Next, we assigned fish to a large (> 50 mm FL) or small size (≤ 50 mm FL) category. We adopted this size threshold because a gear efficiency study of the FMWT found that Delta Smelt (Hypomesus transpacificus) greater than approximately 50 mm were more likely to be retained in the cod end of the trawl (Mitchell et al. 2017). We only fit models when the species-size category was present in at least two gear types, because a catch-ratio cannot be made if the fish is present in only one gear. ...
... Unless direct gear efficiency experiments have been conducted (see Mitchell et al. 2017Mitchell et al. , 2019Mitchell and Baxter 2021), studies that combine gear types must either include gear type in model structure to account for some variability in catch as a result of gear type (as fixed or often random effects) or assume equal catchability among gear types for each target species. Although this assumption may not be a critical flaw for some species with little differences in catchability among gear types, strong violations of this assumption can lead to significant bias in interpretations of spatial and temporal trends in population and community dynamics. ...
Fish monitoring gears rarely capture all available fish, an inherent bias in monitoring programs referred to as catchability. Catchability is a source of bias that can be affected by numerous aspects of gear deployment (e.g., deployment speed, mesh size, and avoidance behavior). Thus, care must be taken when multiple surveys—especially those using different sampling methods—are combined to answer spatio-temporal questions about population and community dynamics. We assessed relative catchability differences among four long-term fish monitoring surveys from the San Francisco Estuary: the Bay Study Otter Trawl (BSOT), the Bay Study Midwater Trawl (BSMT), the Fall Midwater Trawl (FMWT), and the Suisun Marsh Otter Trawl (SMOT). We used generalized additive models with a spatio-temporal smoother and survey as a fixed effect to predict gear-specific estimates of catch for 45 different fish species within large and small size classes. We used estimates of the fixed effect coefficients for each survey (e.g., BSOT) relative to the reference gear (FMWT) to develop relative measures of catchability among taxa, surveys, and fish-size classes, termed the catch-ratio. We found higher relative catchability of 27%, 22%, and 57% of fish species in large size classes from the FMWT than in the BSMT, BSOT, or SMOT, respectively. In the small size class, relative catchability was higher in the FMWT than the BSMT, BSOT, or SMOT for 50%, 18%, and 25% of fish species, respectively. As expected, relative catchability of demersal species was higher in the otter trawls (BSOT, SMOT) while relative catchability of pelagic species was higher in the midwater trawls (FMWT, BSMT). Our results demonstrate that catchability is a source of bias among monitoring efforts within the San Francisco Estuary, and assuming equal catchability among surveys, species, and size classes could result in significant bias when describing spatio-temporal patterns in catch if ignored.
... Over the years, additional monitoring programs that rely on trawl surveys have been initiated by different management agencies to monitor fishes for different objectives. Although fish catch data from these surveys have long been used to inform policy and management decision making, it was not until relatively recent that the effect of the observation process on inferences regarding the distribution and relative abundance of fishes in the Bay-Delta was considered (Goertler et al., 2020;Latour 2016;Mahardja et al., 2017Mahardja et al., , 2021Mitchell et al., 2017Mitchell et al., , 2019Newman 2008;Peterson & Barajas, 2018;Polansky et al., 2019;Thomson et al., 2010). Overall, this collection of work has demonstrated that fish capture efficiency varies markedly across species, time, location, and monitoring program within the Bay-Delta. ...
... The SKT and EDSM were both initiated with the aim of monitoring the distribution and relative abundance of Delta Smelt to inform policy and management decision making in the Bay-Delta. It is clear that monitoring data collected in the Bay-Delta are complicated by the observation process and that capture efficiency can vary considerably (Goertler et al., 2020;Latour, 2016;Mahardja et al., 2017Mahardja et al., , 2021Mitchell et al., 2017Mitchell et al., , 2019Newman, 2008;Peterson & Barajas, 2018;Polansky et al., 2019;Thomson et al., 2010;this study). Although trends in occupancy and relative abundance of fishes in the raw catch data for a few species and monitoring programs (with different sampling extents and resolutions) in the Bay-Delta appear unbiased when compared to estimates from multistate occupancy models (Peterson & Barajas, 2018), there are at least two primary reasons why not separating the ecological and observation process is problematic with respect to the goals of SKT, EDSM, and management in the Bay-Delta. ...
Occupancy models are often used to analyze long-term monitoring data to better understand how and why species redistribute across dynamic landscapes while accounting for incomplete capture. However, this approach requires replicate detection/non-detection data at a sample unit and many long-term monitoring programs lack temporal replicate surveys. In such cases, it has been suggested that surveying subunits within a larger sample unit may be an efficient substitution (i.e., space-for-time substitution). Still, the efficacy of fitting occupancy models using a space-for-time substitution has not been fully explored and is likely context dependent. Herein, we fit occupancy models to Delta Smelt (Hypomesus transpacificus) and Longfin Smelt (Spirinchus thaleichthys) catch data collected by two different monitoring programs that use the same sampling gear in the San Francisco Bay-Delta, USA. We demonstrate how our inferences concerning the distribution of these species changes when using a space-for-time substitution. Specifically, we found the probability that a sample unit was occupied was much greater when using a space-for-time substitution, presumably due to the change in the spatial scale of our inferences. Furthermore, we observed that as the spatial scale of our inferences increased, our ability to detect environmental effects on system dynamics was obscured, which we suspect is related to the tradeoffs associated with spatial grain and extent. Overall, our findings highlight the importance of considering how the unique characteristics of monitoring programs influences inferences, which has broad implications for how to appropriately leverage existing long-term monitoring data to understand the distribution of species.
... The placement of fish within the path of the net does not consider water depth. Little research has been done on the vertical distribution of Delta Smelt in the water column, but there is some evidence to suggest that youngest life stages are evenly distributed throughout the water column (Rockriver 2004) and juvenile to adult life stages are more surface oriented (Souza 2002;Hobbs et al. 2006;Mitchell et al. 2017). Based on some of these studies, Polansky et al. (2019) estimated that life stages captured by the FMWT occupied depths of 0.5 m to 4.5 m. ...
In fisheries monitoring, catch is assumed to be a product of fishing intensity, catchability, and availability, where availability is defined as the number or biomass of fish present and catchability refers to the relationship between catch rate and the true population. Ecological monitoring programs use catch per unit of effort (CPUE) to standardize catch and monitor changes in fish populations; however, CPUE is proportional to the portion of the population that is vulnerable to the type of gear used in sampling, which is not necessarily the entire population. Programs often deal with this problem by assuming that catchability is constant, but if catchability is not constant, it is not possible to separate the effects of catchability and population size using monitoring data alone. This study uses individual-based simulation to separate the effects of changing environmental conditions on catchability and availability in environmental monitoring data. The simulation combines a module for sampling conditions with a module for individual fish behavior to estimate the proportion of available fish that would escape from the sample. The method is applied to the case study of the well monitored fish species Delta Smelt (Hypomesus transpacificus) in the San Francisco Estuary, where it has been hypothesized that changing water clarity may affect catchability for long-term monitoring studies. Results of this study indicate that given constraints on Delta Smelt swimming ability, it is unlikely that the apparent declines in Delta Smelt abundance are the result of changing water clarity affecting catchability.
... Similarly, in NS habitat the Platform captured > 3 times the number of individuals and 4 more taxa than the beach seine with half the samples performed. This pattern suggests that because the Platform can collect more individuals in the same amount of time relative to the trawl or seine, it may be more effective at detecting species that are in low abundance such as threatened or endangered species and non-native species that have recently invaded (Mitchell et al., 2017). Greater fish numbers and taxa were observed in NS than OW habitats, either by separate methods or by Platform alone. ...
We performed a preliminary evaluation of a mobile sampling platform with adjustable push net and live box (Platform) against two common methods for sampling small-bodied fish (i.e., 10–100 mm) in two distinct lentic habitats. Nearshore (NS) littoral habitat was sampled by Platform and beach seine, and open water (OW) pelagic habitat by Platform and Kodiak trawl. Our goal was to evaluate the Platform’s ability to describe fish assemblage structure across habitat types in contrast to common techniques restricted to single habitat types that are less comparable due to gear-specific bias. Platform sample speed had a significant positive effect on recapture efficiency of both nearly neutrally buoyant objects and marked fish. Marked fish recapture efficiencies were similar for Platform in NS and OW, indicating similar efficiency across habitat types. Platform capture efficiency was similar to beach seine and greater than Kodiak trawl. With similar sampling time, the Platform collected more individuals and taxa in NS relative to beach seine and in OW relative to Kodiak trawl. Greater taxa detection by the Platform suggests that it may be effective at detecting species that are numerically rare in specific habitats when compared to these methods. Fish CPUE was significantly greater NS regardless of technique. However, by using the Platform, there is greater confidence that this difference was reliable and not a gear selectivity artifact. Overall, this preliminary study demonstrates the Platform's potential to collect standardized data across NS and OW habitats, track ontogenetic habitat shifts, and detect differences in small-bodied fish taxa richness, relative abundance, and density between NS and OW habitats. Continued experimentation beyond a single reservoir and fish size range is required before consensus can be established regarding the utility of this new push net design.
... In the San Francisco Estuary, a variety of trawls are used to collect data on many species of management interest, including Chinook Salmon (Oncorhynchus tshawytscha) and four fish species that experienced decreases in population size during the Pelagic Organism Decline (POD; Baxter et al. 2007;, Delta Smelt (Hypomesus transpacificus), Longfin Smelt (Spirinchus thaleichthys), Threadfin Shad (Dorosoma petenense), and Striped Bass (Morone saxatilis). However, despite the importance of these trawls in the estuary's monitoring networkand how their efficiencies potentially affect the resulting data sets-local published gear efficiency evaluations are few (e.g., Newman 2008;Mitchell et al. 2017 USFWS 2008). In the San Francisco Estuary, selectivity analyses have focused largely on Delta Smelt and the open water trawling of the FMWT Survey (Newman 2008;Mitchell et al. 2017), though other trawl nets have also been studied (Mahardja et al. 2017;. ...
... However, despite the importance of these trawls in the estuary's monitoring networkand how their efficiencies potentially affect the resulting data sets-local published gear efficiency evaluations are few (e.g., Newman 2008;Mitchell et al. 2017 USFWS 2008). In the San Francisco Estuary, selectivity analyses have focused largely on Delta Smelt and the open water trawling of the FMWT Survey (Newman 2008;Mitchell et al. 2017), though other trawl nets have also been studied (Mahardja et al. 2017;. This is because the FMWT Survey has provided valuable trend data on the endangered Delta Smelt USFWS 2008;Latour 2016) despite the fact that the survey was originally designed to monitor age-0 Striped Bass (Stevens 1977;Stevens and Miller 1983). ...
... This is because the FMWT Survey has provided valuable trend data on the endangered Delta Smelt USFWS 2008;Latour 2016) despite the fact that the survey was originally designed to monitor age-0 Striped Bass (Stevens 1977;Stevens and Miller 1983). In particular, a FMWT covered codend study was conducted in 2014-2015 to improve our understanding of the trawl's ability to catch Delta Smelt, and to help separate gear selectivity effects from underlying population trends in the data (Mitchell et al. 2017). ...
The Fall Midwater Trawl Survey has provided data on aquatic organisms in the San Francisco Estuary for over five decades. In 2014–2015, a study was conducted to investigate and quantify the efficiency of this trawl for catching the endangered fish species Delta Smelt (Hypomesus transpacificus). In an analysis based on that study, we calculated retention probability—the probability that a Delta Smelt is retained in the cod end of the trawl—as a function of fish length and fit a selectivity curve reflecting the relationship between size and retention. Here we return to the same gear efficiency study and further utilize the data set by (1) fitting selectivity curves for three additional pelagic fish species: Threadfin Shad (Dorosoma petenense), American Shad (Alosa sapidissima), and Mississippi Silverside (Menidia beryllina), (2) refitting the selectivity curve for Delta Smelt to incorporate between-haul variability, and (3) calculating the lengths of 50% and 95% retention in order to characterize and compare the resulting selectivity curves. We also present retention data on age-0 Striped Bass (Morone saxatilis), all of which were retained in the cod end. We found that Threadfin Shad, American Shad, and Delta Smelt are 95% retained at 45, 49, and 61 mm fork length, respectively. Because data were limited for Mississippi Silverside, American Shad, and age-0 Striped Bass, we used body shape, in conjunction with retention data, to develop hypotheses about selectivity based on whether each species’ body shape resembles that of Threadfin Shad, which are more deep-bodied and laterally compressed, or Delta Smelt, which are more fusiform. We also found that retention-at-length was more variable for Delta Smelt than for Threadfin Shad, potentially because length is a good predictor of retention in deep-bodied, laterally compressed fish whereas maximum girth is a better predictor of retention in fusiform fish.
... Retention probability-the probability that an organism is retained by the sampling gear, conditional on it being available to the gear-is a component of detection efficiency commonly estimated for trawling gear deployed in the estuary. Paired gear studies have already been conducted within the estuary to estimate gear retention probability for Delta Smelt (Mitchell et al. 2017 and used to provide a less biased index of abundance throughout the estuary (Polansky et al. 2019). However, no such assessment has been performed for the SmeltCam, which is important if it is to be used as a viable alternative to conventional trawling surveys. ...
... Gear-specific retention efficiency (p) was constrained as a function of turbidity for the SmeltCam because of its presumed effect on video processing (DeCelles et al. 2017). The retention efficiency of the closed cod end was modeled as a function of the log-transformed total number of fish (plus 1 due to zeros) captured in the sample, because this is known to increase the sampling efficiency of trawl surveys because it blocks the mesh from which smaller fish may escape (Mitchell et al. 2017;Peterson and Barajas 2018). The latent state abundance parameter was also constrained by fixed tide effects ( i ; ebb, flood, high slack, low slack) and site effects (Napa River vs. San Pablo Bay), with the intercept ( N ) representing the ebb tide within the Napa River. ...
... We included a negative covariate effect (-1.0) for the SmeltCam simulation, which was the assumed effect of turbidity on SmeltCam retention efficiency. A positive effect also was included for the trawl retention efficiency simulation (1.0), an assumed effect of fish density on the retention efficiency of the trawling gear (Mitchell et al. 2017). A second simulation scenario included a range of sample sizes (or sites) to determine whether our sample size of 52 tows was sufficient to produce unbiased results of gear efficiency and how many tows (n = 25, 52, 88, 150) would be needed to Table 1 Model priors and posterior parameter estimates fit to the integrated binomial N-mixture model with SmeltCam and midwater trawl sampling gears in the San Francisco Estuary, California. ...
Resource managers often rely on long-term monitoring surveys to detect trends in biological data. However, no survey gear is 100% efficient, and many sources of bias can be responsible for detecting or not detecting biological trends. The SmeltCam is an imaging apparatus developed as a potential sampling alternative to long-term trawling gear surveys within the San Francisco Estuary, California, to reduce handling stress on sensitive species like the Delta Smelt (Hypomesus transpacificus). Although believed to be a reliable alternative to closed cod-end trawling surveys, no formal test of sampling efficiency has been implemented using the SmeltCam. We used a paired deployment of the SmeltCam and a conventional closed cod-end trawl within the Napa River and San Pablo Bay, a Bayesian binomial N-mixture model, and data simulations to determine the sampling efficiency of both deployed gear types to capture a Delta Smelt surrogate (Northern Anchovy, Engraulis mordax) and to test potential bias in our modeling framework. We found that retention efficiency—a component of detection efficiency that estimates the probability a fish is retained by the gear, conditional on gear contact—was slightly higher using the SmeltCam (mean = 0.58) than the conventional trawl (mean = 0.47, Probability SmeltCam retention efficiency > trawl retention efficiency = 94%). We also found turbidity did not affect the SmeltCam’s retention efficiency, although total fish density during an individual tow improved the trawl’s retention efficiency. Simulations also showed the binomial model was accurate when model assumptions were met. Collectively, our results suggest the SmeltCam to be a reliable alternative to sampling with conventional trawling gear, but future tests are needed to confirm whether the SmeltCam is as reliable when applied to taxa other than Northern Anchovy over a greater range of conditions.
... The STNS and FMWT were implemented to sample Striped Bass not Delta Smelt (Stevens 1977b), so these surveys possibly misrepresent the relative abundance of Delta Smelt compared to Striped Bass (e.g., Mitchell et al. 2017). To evaluate whether the long-term trawl surveys mischaracterize the relative abundance of Delta Smelt, we summarized the extensive published literature on Bay−Delta fish assemblages (Table 5). ...
