PHYTOPLANKTON, LIGHT, AND NUTRIENTS IN A GRADIENT OF MIXING DEPTHS: THEORY

By S. Diehl. 2002

200 citations recorded by the source corpus.

Subfields: Ecology, Environmental Chemistry, Oceanography

View Paper: https://www.semanticscholar.org/paper/d10c8fbaf88e92dac05a3bb1433e7e421cb6ed28

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Citations in the corpus

Light supply, plankton biomass, and seston stoichiometry in a gradient of lake mixing depths (2006, methodology): “Discussion Our model extends similar strategic ecosystem models by Huisman and Weissing (1995) and Diehl (2002) to include flexible algal nutrient stoichiometry.”
Performance of sinking and nonsinking phytoplankton taxa in a gradient of mixing depths (2003, methodology): “depend on the specific choice of parameters (Diehl 2002). where the filamentous diatom Melosira italica usually vanishes during summer stratification due to high sedimentation losses, Lund (1971) achieved its persistence in this period by artificial mixing.”
A biodiversity‐inspired approach to aquatic ecosystem modeling (2007, methodology): “The plankton model is loosely based on concepts from DEB theory (Kooijman 2000) and qualitatively resembles previous approaches (Huisman and Weissing 1995; Diehl 2002).”
Effects of thermocline deepening on lake plankton communities (2011, methodology): “Theoretical investigations into the effect of lake thermal stratification on phytoplankton communities have been espe- cially fruitful (e.g., Huisman and Weissing 1995; Klausmeier and Litchman 2001; Diehl 2002) and have provided predictions for the occurrence of plankton blooms, among others.”
Artificial mixing to control cyanobacterial blooms: a review (2015, background): “Models simulating the total biomass per unit surface area as a function of mixing depth (Lorenzen and Mitchell 1973; Oskam 1978; Huisman and Weissing 1995; Diehl 2002) show that with increasing mixing depth the biomass initially will increase, until a mixing depth where nutrient limitation is replac”
Spatio-temporal behaviour of the deep chlorophyll maximum in Mediterranean Sea: Development of a stochastic model for picophytoplankton dynamics (2012, background): “…a series of theoretical studies based on model systems (Radach and Maier-Reimer, 1975; Varela et al., 1992; Huisman and Weissing, 1995; Klausmeier and Litchman, 2001; Diehl, 2002; Hodges and Rudnick, 2004; Beckmann and Hense, 2007; Klausmeier et al., 2007; Mei et al., 2009; Bougaran et al., 2010).”
Climate change and Australian marine life (2007, background): “…because they fundamentally affect the supply of nutrients (from below) and light (from above), and sinking losses of phytoplankton (Mitchell & Holm-Hansen 1991, Huisman & Weissing 1995, Diehl 2002) and because consumer biomass is positively related to the productivity of their food (Grover 1997).”
Water color affects the stratification, surface temperature, heat content, and mean epilimnetic irradiance of small lakes (2006, background): “, light, nutrients, or sinking rate) for algal production (Diehl 2002; Diehl et al. 2002; Ptacnik et al. 2003).”
Stoichiometrically Explicit Food Webs: Feedbacks between Resource Supply, Elemental Constraints, and Species Diversity (2009, background): “(c) Variation in producer stoichiometry in aquatic systems can also be driven, in part, by light:nutrients supplied to them (e.g., one to three regressions derived from data from Sterner et al. 1997; four stems from data of Diehl 2002, 2005).”
Influence of water‐column depth and mixing on phytoplankton biomass, community composition, and nutrients (2008, background): “The latter occurs because turbulent mixing disperses phytoplankton in the water column and therefore partly counteracts sedimentation; overall, sinking losses should thus be most severe for fast-sinking algae in shallow and weakly mixed water columns (Diehl 2002; Huisman et al. 2002).”