Interannual fluctuations in primary production: Direct physical effects and the trohic cascade at Castle Lake, California

Jassby, Alan D.; Powell, Thomas M.; Goldman, Charles R.

doi:10.4319/lo.1990.35.5.1021

Cited by 77 publications

(85 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In designing tests for these ideas, we have favored an experimental approach (Carpenter 1988a;Carpenter and Kitchell 1988;Carpenter et al 199 1). Paleolimnological reconstructions (Kitchell and Carpenter 198 7;Leavitt et al 1989;Carpenter and Leavitt 199 l), longterm records (Mills et al 1987;Jassby et al 1990), and multilake comparative studies (Mills and Schiavone 1982;Pace 19 84;Carpenter et al 199 1) have also provided valuable evidence. Since DeMelo et al restrict their scope to experiments, we will not address other research approaches in our comment.…”

Section: Commentmentioning

confidence: 99%

Trophic cascade and biomanipulation: Interface of research and management‐A reply to the comment by DeMelo et al

Carpenter

Kitchell

1992

Limnology & Oceanography

View full text Add to dashboard Cite

Section: Commentmentioning

confidence: 99%

Trophic cascade and biomanipulation: Interface of research and management‐A reply to the comment by DeMelo et al

Carpenter

Kitchell

1992

Limnology & Oceanography

View full text Add to dashboard Cite

“…For example, in Castle Lake, California, much of the primary production variability observed in June and July was attributed to the ENSO, with the role of ENSO expressed via its impact on winter snowfall and spring rain, which determined the timing of ice out and the intensity of spring hydraulic flushing (Jassby et al 1990). A clear distinction between the ENSO and PDO is complicated, because these phenomena are spatially and temporally related (Mantua et al 1997).…”

mentioning

confidence: 99%

“…In western North American marine and lacustrine ecosystems, the El Niño-Southern Oscillation (ENSO) (Strub et al 1985;Goldman et al 1989;Jassby et al 1990) and the Pacific Decadal Oscillation (PDO) (Mantua et al 1997;McGowan et al 1998) are large-scale meteorological phenomena that can influence thermal structure and biotic community dynamics. For example, in Castle Lake, California, much of the primary production variability observed in June and July was attributed to the ENSO, with the role of ENSO expressed via its impact on winter snowfall and spring rain, which determined the timing of ice out and the intensity of spring hydraulic flushing (Jassby et al 1990).…”

mentioning

confidence: 99%

Effects of climatic variability on the thermal properties of Lake Washington

Arhonditsis

Brett

DeGasperi

et al. 2004

Limnology & Oceanography

106

View full text Add to dashboard Cite

We conducted a statistical analysis of a long-term record of intra-and interannual temperature fluctuations in Lake Washington, Washington. Lake Washington has experienced a warming trend, with overall increases of 1.5 (0.045ЊC yr Ϫ1 ) and 0.9ЊC (0.026ЊC yr Ϫ1), respectively, for temperature data weighted over the surface (0-10 m) and entire lake volume. This warming trend was greatest for the period from April to September and was smallest and nonsignificant for November-February. A principal-components analysis of the long-term mean monthly temperature time series identified two independent modes of interannual variability. The first mode represented the months of the year when the lake warms and is warmest (e.g., March-October) and explained 54% of the variability in the overall time series. The second mode represented the months when the lake cools and is coldest (November-February) and explained 24% of the variability. The March-October mode was positively correlated with interannual variability in air temperatures and the Pacific Decadal Oscillation (PDO), multivariate r 2 ϭ 0.65. The November-February mode was positively correlated with air temperature, PDO, relative humidity, solar radiation, and wind speed (r 2 ϭ 0.83). A heat budget model indicated that long-term trends had a secondary role and interannual variability dominated, with exceptions being net long-wave atmospheric radiation and surface-emitted radiation, for which the long-term trend explained ϳ25% and 53% of the total variance, respectively. An increase in incoming long-wave radiation fluxes was mainly associated with the increase in minimum daily temperatures (0.06ЊC yr Ϫ1 , r 2 ϭ 0.47), especially during the March-October mode, when the linear trend accounted for 85% of the variability.Climatic and large-scale oceanic fluctuations are increasingly recognized as important regulatory factors that are capable of influencing the structural properties of both terrestrial and aquatic ecosystems (Aebischer et al. 1990;Adrian et al. 1995; George and Taylor 1995;Post et al. 1997;Beamish et al. 1999). Generally, the thermal properties of aquatic ecosystems are more directly governed by these broad-scale phenomena than are the thermal properties of terrestrial ecosystems, with lakes appearing to be particularly sensitive to the ecological impacts of climatic forcing (Hostetler and Small 1999;Gerten and Adrian 2001). There is clear evidence of a strong relationship between climatic conditions (e.g., air temperature and wind patterns) and lake thermal structure (e.g., onset of stratification, thermocline depth, mean epilimnetic temperature, turnover date, and duration of ice cover) for northern temperate lakes (Schindler et al.

show abstract

“…Shapiro and Wright 1984;Carpenter et al 1987), by following the cascading effects of food-web disruption that result from either natural events (e.g. summer fish kills- vanni et al 1990) or accidental introductions of exotic species (see Kitchell et al 1988), and analysis of long-term records to elucidate mechanisms of biotic and abiotic control of lake community structure or productivity (Mills and Forney 1988;Jassby et al 1990). …”

mentioning

confidence: 99%

Trophic interactions and direct physical effects control phytoplankton biomass and production in an estuary

1992

View full text Add to dashboard Cite

The recent invasion of San Francisco Bay by the suspension-feeding clam Putamocorbula amurensis has provided an opportunity to document the ecological consequences of a major biological disturbance. Previous work over the last two decades has shown that phytoplankton biomass in the upper estuary is low (2-3 mg Chl a m-3) during seasonal periods of high river flow and short residence time, and it is usually high (peak > 30 mg Chl a m-3) during the summer-autumn seasons of low river flow and long residence time. However since P. amurensis became widespread and abundant in 1987, the summer phytoplankton biomass maximum has disappeared, presumably because of increased grazing pressure by this newly introduced species. For the period 1977-l 990, mean estimated primary production was only 39 g C mm2 yr-' during years when bivalve suspension feeders were abundant (>2,000 mm2), compared to 106 g C m-2 yr-' when bivalves were absent or present in low numbers. These observations support the hypothesis that seasonal and interannual fluctuations in estuarine phytoplankton biomass and primary production can be regulated jointly by direct physical effects (e.g. river-driven transport) and trophic interactions (episodes of enhanced grazing pressure by immigrant populations of benthic suspension feeders).

show abstract

Interannual fluctuations in primary production: Direct physical effects and the trohic cascade at Castle Lake, California

Cited by 77 publications

References 44 publications

Trophic cascade and biomanipulation: Interface of research and management‐A reply to the comment by DeMelo et al

Trophic cascade and biomanipulation: Interface of research and management‐A reply to the comment by DeMelo et al

Effects of climatic variability on the thermal properties of Lake Washington

Trophic interactions and direct physical effects control phytoplankton biomass and production in an estuary

Contact Info

Product

Resources

About