Leveraging Delta Smelt Monitoring for Detecting Juvenile Chinook Salmon in the San Francisco Estuary

Abstract

Monitoring is an essential component in ecosystem management, and leveraging existing data sources for multiple species of interest can be one effective way to enhance information for management agencies. Here, we analyzed juvenile Chinook Salmon (Oncorhynchus tshawytscha) bycatch data that has been collected by the recently established Enhanced Delta Smelt Monitoring program (EDSM), a survey designed to estimate the abundance and distribution of the San Francisco Estuary’s (estuary) endangered Delta Smelt (Hypomesus transpacificus). Two key aspects of the EDSM program distinguish it from other fish surveys in the estuary: a stratified random sampling design and the spatial scale of its sampling effort. We integrated the EDSM data set with other existing surveys in the estuary, and used an occupancy model to assess differences in the probability of detecting Delta Smelt across gear types. We saw no large-scale differences in size selectivity, and while detection probability varied among gear types, cumulative detection probability for EDSM was comparable to other surveys because of the program’s use of replicate tows. Based on our occupancy model and sampling effort in the estuary during spring of 2017 and 2018, we highlighted under-sampled regions that saw improvements in monitoring coverage from EDSM. Our analysis also revealed that each sampling method has its own benefits and constraints. Although the use of random sites with replicates, as conducted by EDSM, can provide more statistically robust abundance estimates relative to traditional methods, the use of fixed stations and simple methods such as beach seining may provide a more cost-effective way to monitor salmon occurrence in certain regions of the estuary. Leveraging the strengths of each survey’s method can enable stronger inferences on salmon abundance and distribution. Careful consideration of these trade-offs is crucial as the management agencies of the estuary continue to adapt and improve their monitoring programs.

Space‐for‐time is not necessarily a substitution when monitoring the distribution of pelagic fishes in the San Francisco 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.…”

“…Admittedly, it is not clear to us how occupancy dynamics at the scale of an entire subregion will help inform real-time management decision making for these species in the Bay-Delta. We treated subregions as sample units for the spatial replicate analyses because these delineations are used by managers in the Bay-Delta for planning purposes, this approach provided the number of replicate surveys needed based on the fixed locations of the SKT survey stations, and this scale of inference is being used for other species, in particular Chinook Salmon (Oncorhynchus tshawytscha), in the Bay-Delta (Mahardja et al, 2021). If this scale of inference is deemed suitable for informing management decision making for Delta Smelt and Longfin Smelt, it is worth noting that how stations are selected for surveys matters.…”

“…Additionally, occupancy analyses of these historical data would benefit from more integrated analyses that leverage data from the multiple monitoring programs while treating the different sampling gears as different detection methods directly in the model (Nichols et al, 2008). To our knowledge, Mahardja et al (2021) were the first to try this in the Bay-Delta when analyzing Chinook Salmon detection/nondetection data at the spatial scale of a subregion. Our results suggest this approach requires more careful consideration to identify a smaller spatial scale when the objective is to relate occupancy probability to environmental covariates.…”

“…Given the above findings, it is clear that the data collected by fish monitoring programs in the Bay-Delta need to be corrected for incomplete capture to properly inform decision making. Like many monitoring programs across the world (Budy et al, 2015;Duarte et al, 2021;Kéry et al, 2010;Sadoti et al, 2013;Van Strien et al, 2013;Whitlock et al, 2020; and many more), occupancy models are increasingly being used to accomplish this for fishes in the Bay-Delta despite sampling designs not explicitly considering occupancy models when many of these monitoring programs were established (Goertler et al, 2020;Mahardja et al, 2017Mahardja et al, , 2021Peterson & Barajas, 2018). However, one of the long-term monitoring programs used to monitor the distribution and relative abundance of Delta Smelt (Hypomesus transpacificus) in the Bay-Delta, the Spring Kodiak Trawl (SKT), lacks temporal replicate surveys (Newman et al, 2017).…”

“…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.…”