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Aerial stratification (polygons) and sampling locations (circles) for the Fall Midwater Trawl survey within the Sacramento-San Joaquin Delta, 1967–2012. Areas 2, 6, and 9 are not shown because they have not been consistently sampled and thus are not used by the California
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Investigating the effects of environmental, biological, and anthropogenic covariates on fish populations can aid interpretation of abundance and distribution patterns, contribute to understanding ecosystem functioning, and assist with management. Studies have documented declines in survey catch per unit effort (CPUE) of several fishes in the Sacram...
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Context 1
... de- sign such that sampling occurs at approximately the same location within predefined regional strata (17 areas excluding areas 2, 6, and 9 per the CDFW's protocol). Sampling inten- sity is related to water volume in each regional stratum such that samples are taken every 10,000 acre ft for areas 1-11 and every 20,000 acre ft for areas 12-17; Fig. 1). At each sampling location, a 12-min oblique tow is made from near bottom to the surface using a 3.7 m×3.7 m square midwater trawl with variable mesh in the body and a 1.3-cm stretch mesh cod end. Vessel speed over ground during tows can be variable since sampling procedures are designed to maintain a constant cable angle throughout ...
Context 2
... quantity intended to represent broader watershed-level hydrol- ogy in the absence of man-made facilities that affect flow. For each group, monthly inflow and outflow time series were assembled. Historical inflow included combined measure- ments from the Sacramento River, Yolo Bypass, and Eastern Delta (San Joaquin River and adjacent areas; Fig. 1), while historical outflow is a net quantity of inflow and an estimate of delta precipitation less total delta exports and diversions. All historical flow time series were based on DAYFLOW, which is a computer program designed to estimate daily average delta outflow (see http://www.water.ca.gov/dayflow/ for more details). Unimpaired ...
Context 3
... covariates indicated that all levels of month contained ade- quate nonzero CPUEs for inclusion in analyses. However, spatial data summaries showed that CPUEs were quite low in some areas, and the 5 % rule led to the inclusion of only areas 12-16 for delta smelt, 11-14 for longfin smelt, 12-16 for YOY striped bass, and 15-17 for threadfin shad (Fig. 1). (Fig. ...
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We utilized recently available data from the 20-mm Tow-Net and Spring Kodiak Trawl, together with other Interagency Ecological Program and regional monitoring programs, to provide a comprehensive description of the range and temporal and geographic distribution of delta smelt (Hypomesus transpacificus) by life stage within the San Francisco Estuary...
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... Black symbols represent variables with a significant effect on the counts of the functional fish grouping. Surprisingly, pelagic fishes were not correlated with turbidity as observed in other Delta studies (Feyrer et al., 2007(Feyrer et al., , 2017Latour, 2016). The lack of a relationship between the pelagic fishes functional group and turbidity could be explained by this group being composed of non-native Delta fishes (striped bass, threadfin shad, and American shad Alosa sapidissima; see Appendix S1: Figure S1), a true lack of a turbidity effect on pelagic fishes in the Delta, or other localized phenomena playing a stronger role during this study (e.g., local food availability). ...
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.
... Since salinity due to ocean salts decreases with distance up the main channel of the estuary, salinity can be used as a measure of distance along the channel in the reference frame of the fish. Also, like many fishes in the estuary (Latour 2016), larval longfin smelt are more abundant in turbid water than clear. Secchi depth measurements have been taken in every year of the SLS with only one missing value. ...
Variation in freshwater flow into estuaries can profoundly alter abundance of estuarine organisms through a variety of mechanisms. In the San Francisco Estuary, California, an annual abundance index of juvenile longfin smelt Spirinchus thaleichthys has varied by ~ 100-fold over the range of flow, and over the last five decades the index has declined by over 100-fold. The unknown mechanisms for variation with flow may include removal of larvae by freshwater diversions during low-flow periods. Using data from larval trawl surveys during January–March 2009–2020, we estimated larval population size, its response to freshwater flow, and losses of larvae to freshwater diversions. Population size was estimated by a Bayesian hierarchical model linking a process model, with salinity and water clarity as covariates, to an observation model representing catch by a negative binomial distribution. Population size averaged across surveys within years—an index of the number of larvae produced—decreased over the study period from ~ 10 ⁹ to 10 ⁸ larvae. Population size was unrelated to freshwater flow in the year of hatching but positively related to the subsequent juvenile abundance index. Thus, the mechanisms underlying the strong variability in the annual abundance index of longfin smelt with freshwater flow are constrained to occur after March. Estimated proportional losses to water diversions accumulated over the period of vulnerability averaged 1.5% of the population, too low to measurably influence population dynamics.
... 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.
... This trend toward decreasing turbidity and decreasing catch of Delta Smelt over time has led some researchers to speculate whether changes in turbidity might be responsible for a change in catchability. In particular, the question is whether Delta Smelt avoid sampling gear more effectively-particularly that of the Fall Midwater Trawl (FMWT) surveywhen Secchi depths are high, because of an increased field of visibility compared to when water is more turbid (Latour 2016). ...
... The declining pattern of Delta Smelt abundance has been questioned https://doi.org/10.15447/sfews.2021v19iss3art6 because of (1) the inability of monitoring surveys to distinguish between effects of declining abundance, and (2) changes in catchability from changing environmental conditions and/or habitat use Latour 2016), often with a specific focus on the apparent decline in turbidity measured during surveys such as the FWMT. ...
... A few studies provide insight into separating catchability from availability for Delta Smelt. Applying zero-inflated negative binomial models to the FWMT to separate true zeros from false zeros, Latour (2016) found that as water clarity increased (larger Secchi depth), catch declined, and the probability of false zeros increased. This suggests that decreasing turbidity negatively affects catchability. ...
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.
... Further, the predictive capability of models could be improved by consistently recording additional variables that influence CPUE, other than seasonal climate. For example, fish abundance could be affected by fishing pressure, whereas catchability could be affected by turbidity, water temperature and time of day (Vašek et al., 2009;Latour, 2016;Weyl et al., 2021). Other possible methods to obtain CPUE data should also be examined, including random stratified survey design and combining catch data from various sources, including fishery-dependent data (Paukert et al., 2017;Camp et al., 2020). ...
A South African inland fisheries policy will depend on a reliable long-term supply of social-ecological data covering freshwater fisheries at a broad geographic scale. Approaches to systematic planning of research and monitoring are demonstrated herein, based on a fishery-independent gillnet dataset covering 44 dams, and geographic information system maps of monthly and annual climate variables, human land use, and road access in a 5 km zone around 442 dams. Generalised linear mixed models were used to determine the covariates of gillnet catch per unit effort. Such covariates are required for a model-based process to select a subset of state-owned dams for a long-term fishery survey programme. The models indicated a monthly climate influence on catch per unit effort and climatic drivers of fish species distributions. However, unexplained variation is overwhelming and precludes a model-based survey design process. Non-hierarchical clustering of 442 dams was then done based on annual climate and human land use variables around dams. The resulting clusters of dams with shared climate and land use characteristics indicates the types of dams that should be selected for monitoring to represent the full range of climate and land use characteristics. Surrounding land use could indicate the socioeconomic characteristics of fisheries, for example, dams that may support subsistence-based communities that require increased research effort. Finally, although primary catchments could be useful for organising national-scale management, land use cover in the 5 km zone around dams varied widely within the respective primary catchments. Beyond these proposed approaches to plan research, this study also reveals various data deficiencies and recommends additional future studies on other possible methods for systematic research planning.
... If catchability were inaccurately assumed to be constant, the decrease in catch would 54 be interpreted as a decrease in population size, which would introduce a negative bias to the 55 estimates of population size. Where an environmental factor affects both catchability and 56 availability, additional studies are necessary to separate the two effects on catch, but 57 abundance estimates are possible in this situation using N-mixture models (Royle 2004 Midwater Trawl survey, when Secchi depths are high because of an increased field of visibility 72 compared to when water is more turbid (Latour 2016). 73 The IEP has been monitoring fish and water quality in the estuary for over 50 years. ...
... 84 A few studies provide insight into separating catchability from availability for Delta Smelt. 85 Applying zero-inflated negative binomial models to the FWMT to separate true zeros from false 86 zeros, Latour (2016) found that as water clarity increased (larger Secchi depth), catch declined 87 and the probability of false zeros increased. This suggests that decreasing turbidity negatively 88 affects catchability. ...
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 that is 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 due to an effect of changing water clarity on catchability.
... Delta Smelt may be able to avoid capture to a greater extent when the water is clear, which would result in a negative estimate for 1 (Latour 2016). Increased water clarity may also result in a change in the vertical or lateral distribution of Delta Smelt, which could also affect sampling efficiency because the SKT samples the top 2 m of the water column, and typically well away from the shorelines. ...
... These latter models resulted in high densities in the most inland regions, which often had clear water (high Secchi depth) and low catch. As a result, the model could improve the fit to the SKT data by predicting a negative relationship between sampling efficiency and Secchi depth as estimated for juveniles captured in the FMWT surveys (Latour 2016). However, the improvement in fit was relatively Table 2). ...
... But in a relative sense this implies the model has over-estimated the expected abundance in the South Delta by about 65%, leading to the conclusion that entrainment has also been potentially overestimated by this amount (if one also ignores over-estimation of abundance in western regions for the purpose of this argument). However, catch rates vary widely across the different stations sampled in a region within surveys, likely as a result of extensive variation in fish density and, perhaps, catchability (Latour 2016). High sampling variance (e.g., a 10:1 varianceto-mean ratio in water year 2002) leads to a relatively small reduction in the likelihood of the data by estimating an expected value of 4.5 rather than 2.7 fish per tow. ...
There has been considerable debate about effects of entrainment of endangered Delta Smelt (Hypomesus transpacificus) at water export facilities located in the Sacramento–San Joaquin River Delta. In this paper we use a behavior-driven movement model (BMM) to simulate the movement of adult Delta Smelt, which, in conjunction with a population dynamics model, estimates the proportion of the population that is lost to entrainment, i.e., proportional entrainment loss (PEL). Parameters of the population model are estimated by maximum likelihood by comparing predictions to data from Fall Midwater Trawl (FMWT) and Spring Kodiak Trawl (SKT) surveys, as well as to daily salvage estimates. Our objectives are to evaluate different movement behavior hypotheses, to rank estimates of PEL based on how well predictions fit the data, and to sharpen our understanding of the data to inform future research and monitoring decisions. We applied the modeling framework to data from water year 2002—a year when salvage was high—and tested 30 combinations of six behavior and five population dynamics models. More complex process and observation assumptions in the population model led to much improved fits in most cases, but did not appreciably influence PEL predictions, which were largely determined by movement predictions from the BMMs. Estimates of PEL varied considerably among behaviors (2% to 40%). The model with the highest predictive capability explained 98% of the variation in FMWT data across regions, 70% of the variation in SKT data across regions and surveys, and 28% and 43% of the daily variation in salvage at federal and state fish screening facilities, respectively. The PEL estimate from this model was 35%, more than double the original estimate from Kimmerer (2008) of 15%. While PEL estimates provided in this study should be considered preliminary, our framework for testing combined behavior-driven movement models and population dynamics models is an improvement compared to earlier efforts.
... Delta Smelt may be able to avoid capture to a greater extent when the water is clear, which would result in a negative estimate for 1 (Latour 2016). Increased water clarity may also result in a change in the vertical or lateral distribution of Delta Smelt, which could also affect sampling efficiency because the SKT samples the top 2 m of the water column, and typically well away from the shorelines. ...
... These latter models resulted in high densities in the most inland regions, which often had clear water (high Secchi depth) and low catch. As a result, the model could improve the fit to the SKT data by predicting a negative relationship between sampling efficiency and Secchi depth as estimated for juveniles captured in the FMWT surveys (Latour 2016). However, the improvement in fit was relatively Table 2). ...
... But in a relative sense this implies the model has over-estimated the expected abundance in the South Delta by about 65%, leading to the conclusion that entrainment has also been potentially overestimated by this amount (if one also ignores over-estimation of abundance in western regions for the purpose of this argument). However, catch rates vary widely across the different stations sampled in a region within surveys, likely as a result of extensive variation in fish density and, perhaps, catchability (Latour 2016). High sampling variance (e.g., a 10:1 varianceto-mean ratio in water year 2002) leads to a relatively small reduction in the likelihood of the data by estimating an expected value of 4.5 rather than 2.7 fish per tow. ...
There has been considerable debate about effects of entrainment of endangered Delta Smelt (Hypomesus transpacificus) at water export facilities located in the Sacramento–San Joaquin River Delta. In this paper we use a behavior-driven movement model (BMM) to simulate the movement of adult Delta Smelt, which, in conjunction with a population dynamics model, estimates the proportion of the population that is lost to entrainment, i.e., proportional entrainment loss (PEL). Parameters of the population model are estimated by maximum likelihood by comparing predictions to data from Fall Midwater Trawl (FMWT) and Spring Kodiak Trawl (SKT) surveys, as well as to daily salvage estimates. Our objectives are to evaluate different movement behavior hypotheses, to rank estimates of PEL based on how well predictions fit the data, and to sharpen our understanding of the data to inform future research and monitoring decisions. We applied the modeling framework to data from water year 2002—a year when salvage was high—and tested 30 combinations of six behavior and five population dynamics models. More complex process and observation assumptions in the population model led to much improved fits in most cases, but did not appreciably influence PEL predictions, which were largely determined by movement predictions from the BMMs. Estimates of PEL varied considerably among behaviors (2% to 40%). The model with the highest predictive capability explained 98% of the variation in FMWT data across regions, 70% of the variation in SKT data across regions and surveys, and 28% and 43% of the daily variation in salvage at federal and state fish screening facilities, respectively. The PEL estimate from this model was 35%, more than double the original estimate from Kimmerer (2008) of 15%. While PEL estimates provided in this study should be considered preliminary, our framework for testing combined behavior-driven movement models and population dynamics models is an improvement compared to earlier efforts.
... The me thods for these surveys have been documented previously (Moyle et al. 1992, USFWS 2004, Bennett 2005. The varying strengths and weaknesses of several of these surveys as population assessment tools for delta smelt have been described by Bennett (2005) and sampling biases in the surveys for delta smelt and other species have been explored by Latour (2016). We used data from these publicly available fish surveys, delineating life stages as depicted in Table 1, to assess the distribution in local densities of delta smelt. ...
Habitat restoration efforts in the upper San Francisco Estuary, including the Sacramento-San Joaquin Delta, California, move forward, despite a paucity of information on the environmental requirements of many targeted species. The endemic delta smelt Hypomesus transpacificus , protected under the federal Endangered Species Act, is a primary focus of those efforts despite uncertainties regarding many aspects of its relationship with the estuary’s physical and biotic resources. Here we use time-series data from 4 trawl surveys and data on environmental attributes collected from throughout the delta smelt’s distribution to identify ranges of conditions acceptable to delta smelt for each of 5 environmental attributes: water-body type, temperature, turbidity, salinity, and prey availability. Low turbidity and elevated water temperatures render a large portion of the estuary seasonally unsuitable for delta smelt. Within areas in which water quality is suitable, patterns of delta smelt occurrences indicate that habitat is found in subregions where channels of intermediate depth adjoin shallow water. In certain subregions, conditions are inadequate for at least one of the environmental attributes for periods up to several months. We suggest a habitat-restoration strategy that can achieve adequate habitat conditions for delta smelt regardless of through-Delta flow levels, and which can be carried out at a number of locations, but not necessarily the same locations, during each life stage.
... 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). 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.
