Warming in the upper San Francisco Estuary: Patterns of water temperature change from 5 decades of data

2021 ◽  
Author(s):  
Samuel M. Bashevkin ◽  
Brian Mahardja ◽  
Larry R. Brown
Keyword(s):  
Water Temperature ◽  
Temperature Change ◽  
San Francisco ◽  
Generalized Additive Models ◽  
San Francisco Estuary ◽  
Additive Models ◽  
Spatiotemporal Variability ◽  
Northern Regions ◽  
Migration Corridor

Temperature is a key controlling variable from subcellular to ecosystem scales. Thus, climatic warming is expected to have broad impacts, especially in economically and ecologically valuable systems such as estuaries. The heavily managed upper San Francisco Estuary (SFE) supplies water to millions of people and is home to fish species of high conservation, commercial, and recreational interest. Despite a long monitoring record (> 50 years), we do not yet know how water temperatures have already changed or how trends vary spatially or seasonally. We fit generalized additive models on an integrated database of discrete water temperature observations to estimate long-term trends with spatio-seasonal variability. We found that water temperatures have increased 0.017 °C/year on average over the past 50 years. Rates of temperature change have varied over time, but warming was predominant. Temperature increases were most widespread in the late-fall to winter (November to February) and mid-spring (April to June), coinciding with the winter development of juvenile Chinook Salmon and spring spawning window of the endangered Delta Smelt. Warming was fastest in the northern regions, a key fish migration corridor with important tidal wetland habitat. However, no long-term temperature trends were detected in October and were only observed in some regions in May, July, and August. These results can help identify optimal areas for restoration or refugia to buffer the effects of a warming climate, and the methods can be leveraged to understand the spatiotemporal variability in climate warming patterns in other aquatic systems.

Seasonally variable relationships between surface water temperature and inflow in the upper San Francisco Estuary

2021 ◽  
Author(s):  
Samuel M. Bashevkin ◽  
Brian Mahardja
Keyword(s):  
Water Temperature ◽  
San Francisco ◽  
Negative Temperature ◽  
Weather Conditions ◽  
San Francisco Estuary ◽  
Environmental Drivers ◽  
Thermal Range ◽  
Additive Modeling ◽  
The Relationship

Water temperature and inflow are key environmental drivers in aquatic systems that are linked through a causal web of factors including climate, weather, water management, and their downstream linkages. However, we do not yet fully understand the relationship between inflow and water temperature, especially in complex managed systems such as estuaries. The San Francisco Estuary is the center of a critical water supply infrastructure and home to a deteriorating ecosystem with several declining fish species at the warm edge of their thermal range. We used generalized additive modeling of long-term monitoring data to evaluate the relationship between inflow and water temperature along with its spatio-seasonal variability. Most commonly, we found a negative temperature-inflow relationship in which water temperatures increased as inflow decreased, up to 2 °C from high to low-inflow years. However, the opposite (positive) relationship was observed in the winter months, and in the western (downstream) regions from July-September, up to -1.2 °C from high to low-inflow years. These results were upheld by models that included the long-term temperature trend or used salinity as a proxy for location. Upstream factors likely played the biggest role in the summer when local precipitation is negligible, while local precipitation and the related weather conditions may drive much of the winter pattern. Although further mechanistic studies are needed to infer the direct effect of dam releases on water temperatures, these results provide a broader understanding of the impacts of flood and drought dynamics for those tasked with managing estuarine ecosystems.

Environmental and geographical effects on fog occurrence

2021 ◽  
Author(s):  
Iva Hunova ◽  
Marek Brabec ◽  
Marek Malý ◽  
Alexandru Dumitrescu ◽  
Jan Geletič
Keyword(s):  
Air Pollution ◽  
Environmental Factors ◽  
Tensor Product ◽  
Generalized Additive Models ◽  
Additive Models ◽  
Low Rank ◽  
Seasonal Component ◽  
Explanatory Variables ◽  
The Individual

<p>Fog is a very complex phenomenon (Gultepe et al., 2007). In some areas it can contribute substantially to hydrological and chemical inputs and is therefore of high environmental relevance (Blas et al., 2010). Fog formation is affected by numerous factors, such as meteorology, air pollution, terrain (geomorphology), and land-use.</p><p>In our earlier studies we addressed the role of meteorology and air pollution on fog occurrence (Hůnová et al., 2018) and long-term trends in fog occurrence in Central Europe (Hůnová et al., 2020). This study builds on earlier model identification of year-to-year and seasonal components in fog occurrence and brings an analysis of the deformation of the above components due to the individual explanatory variables. The aim of this study was to indicate the geographical and environmental factors affecting the fog occurrence.</p><p>       We have examined the data on fog occurrence from 56 meteorological stations of various types from Romania reflecting different environments and geographical areas. We used long-term records from the 1981–2017 period. </p><p>       We considered both the individual explanatory variables and their interactions. With respect to geographical factors, we accounted for the altitude and landform. With respect to environmental factors,   we accounted for proximity of large water bodies, and proximity of forests. Geographical data from Copernicus pan-European (e.g. CORINE land cover, high resolution layers) and local (e.g. Urban Atlas) projects were used. Elevation data from EU-DEM v1.1 were source for morphometric analysis (Copernicus, 2020).</p><p>        We applied a generalized additive model, GAM (Wood, 2017; Hastie & Tibshirani, 1990) to address nonlinear trend shapes in a formalized and unified way. In particular, we employed penalized spline approach with cross-validated penalty coefficient estimation. To explore possible deformations of annual and seasonal components with various covariates of interest, we used (penalized) tensor product splines to model (two-way) interactions parsimoniously, Wood (2006).</p><p>       The fog occurrence showed significant decrease over the period under review. In general the selected explanatory variables significantly affected the fog occurrence and their effect was non-linear. Our results indicated that, the geographical and environmental variables affected primarily the seasonal component of the model. Of the factors which were accounted for, it was mainly the altitude showing the clear effect on seasonal component deformation (Hůnová et al., in press).</p><p>      </p><p> </p><p>References:</p><p>Blas, M, Polkowska, Z., Sobik, M., et al. (2010). Atmos. Res. 95, 455–469.</p><p>Copernicus Land Monitoring Service (2020). Accessed online at: https://land.copernicus.eu/.</p><p>Gultepe, I., Tardif, R., Michaelidis, S.C., Cermak, J., Bott, A. et al. (2007). Pure Appl Geophys, 164, 1121-1159.</p><p>Hastie, T.J., Tibshirani, R.J. (1990). Generalized Additive Models. Boca Raton, Chapman & Hall/CRC.</p><p>Hůnová, I., Brabec, M., Malý, M., Dumitrescu, A., Geletič, J. (in press) Sci. Total Environ. 144359.</p><p>Hůnová, I., Brabec, M., Malý, M., Valeriánová, A. (2018) Sci. Total Environ. 636, 1490–1499.</p><p>Hůnová, I., Brabec, M., Malý, M., Valeriánová, A. (2020) Sci. Total Environ. 711, 135018.</p><p>Wood, S.N. (2006) Low rank scale invariant tensor product smooths for generalized additive mixed models. Biometrics 62(4):1025-1036</p><p>Wood, S.N. (2017). Generalized Additive Models: An Introduction with R (2nd ed). Boca Raton, Chapman & Hall/CRC.</p><p> </p>

Evidence for temperature-dependent shifts in spawning times of anadromous alewife (Alosa pseudoharengus) and blueback herring (Alosa aestivalis)

2020 ◽  
Vol 77 (4) ◽  
pp. 741-751 ◽  
Author(s):  
Steven M. Lombardo ◽  
Jeffrey A. Buckel ◽  
Ernie F. Hain ◽  
Emily H. Griffith ◽  
Holly White
Keyword(s):  
Generalized Additive Models ◽  
Additive Models ◽  
Alosa Pseudoharengus ◽  
Spawning Habitat ◽  
Temperature Dependent ◽  
Blueback Herring ◽  
River Herring ◽  
Alosa Aestivalis ◽  
Timing Of Spawning

We analyzed four decades of presence–absence data from a fishery-independent survey to characterize the long-term phenology of river herring (alewife, Alosa pseudoharengus; and blueback herring, Alosa aestivalis) spawning migrations in their southern distribution. We used logistic generalized additive models to characterize the average ingress, peak, and egress timing of spawning. In the 2010s, alewife arrived to spawning habitat 16 days earlier and egressed 27 days earlier (peak 12 days earlier) relative to the 1970s. Blueback herring arrived 5 days earlier and egressed 23 days earlier (peak 13 days earlier) in the 2010s relative to the 1980s. The changes in ingress and egress timing have shortened the occurrence in spawning systems by 11 days for alewife over four decades and 18 days for blueback herring over three decades. We found that the rate of vernal warming was faster during 2001–2016 relative to 1973–1988 and is the most parsimonious explanation for changes in spawning phenology. The influence of a shortened spawning season on river herring population dynamics warrants further investigation.

scholarly journals The value of long-term monitoring of the San Francisco Estuary for Delta Smelt and Longfin Smelt

2021 ◽  
pp. 148-171
Author(s):  
Trishelle L. Tempel ◽  
Timothy D. Malinich ◽  
Jillian Burns ◽  
Arthur Barros ◽  
Christina E. Burdi ◽  
...  
Keyword(s):  
San Francisco ◽  
San Francisco Estuary ◽  
Delta Smelt ◽  
Long Term Monitoring ◽  
Term Monitoring ◽  
Longfin Smelt

scholarly journals Use of the SmeltCam as an Efficient Fish Sampling Alternative Within the San Francisco Estuary

2020 ◽  
Vol 19 (2) ◽  
Author(s):  
Brock Huntsman ◽  
◽  
Federick Feyrer ◽  
Matthew Young ◽  
◽  
...  
Keyword(s):  
San Francisco ◽  
Biological Data ◽  
San Francisco Estuary ◽  
Sampling Efficiency ◽  
Modeling Framework ◽  
Retention Efficiency ◽  
Handling Stress ◽  
Delta Smelt ◽  
Northern Anchovy

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.

Long-term Bioaccumulation Monitoring with Transplanted Bivalves in the San Francisco Estuary

1999 ◽  
Vol 38 (3) ◽  
pp. 170-181 ◽  
Author(s):  
Andrew J. Gunther ◽  
Jay A. Davis ◽  
Dane D. Hardin ◽  
Jordan Gold ◽  
David Bell ◽  
...  
Keyword(s):  
San Francisco ◽  
San Francisco Estuary
Sign in / Sign up

Export Citation Format

Share Document