Physical Determinants of Phytoplankton Production, Algal Stoichiometry, and Vertical Nutrient Fluxes

Jäger, Christoph G.; Diehl, Sebastian; Emans, Maximilian

doi:10.1086/650728

Cited by 42 publications

(26 citation statements)

References 52 publications

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“…During spring 2013 at Tiefer See, this scenario likely resulted in elevated concentrations of nutrients (Si and P, Fig. 4) that offset nutrient limitation for algal production, an occurrence commonly reported in deep lakes (Jäger et al 2010;Peeters et al 2013). In addition to high nutrient availability, the diatoms benefited from the rapid onset of stratification that increased the intensity of incident light.…”

Section: Discussionmentioning

confidence: 94%

Effects of spring warming and mixing duration on diatom deposition in deep Tiefer See, NE Germany

et al. 2016

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Monitoring during three meteorologically different spring seasons in 2012, 2013, and 2014 revealed that temperature increase in spring, which influences spring lake mixing duration, markedly affected nutrient availability and diatom deposition in a sediment trap close to the bottom of deep Tiefer See, NE Germany. Deposition of Stephanodiscus taxa and small Cyclotella taxa was much higher after late ice out and a deep, short lake mixing period in spring 2013, compared to that after gradual warming and lengthy lake mixing periods in spring 2012 and 2014, when only brief or marginal ice cover occurred. Availability of dissolved Si and P was 33% and 20% higher, respectively, in 2013 compared to 2014. The observed relation between high (low) diatom deposition and short (lengthy) mixing duration in spring was applied to varved sediments deposited between AD 1924 and 2008. Low detrital Si content in trapped material and a sediment core enabled use of µXRF-counts of Si as a proxy for diatom silica. The spring mixing duration for 1951-2008 was derived from FLake-model calculations. The spring warming duration related to lake mixing was approximated from air temperatures for 1924-2008 using the dates when daily mean air temperature exceeded 5°C (start) and 10°C (end). Diatom silica deposition showed a significant (p<0.0001) inverse linear relationship with the modeled spring mixing duration (R² = 0.36) and the spring warming duration (R² = 0.28). In both cases, the relationship is strengthened when data from the period of low diatom production (1987)(1988)(1989)(1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005) is excluded (R² = 0.59 and R² = 0.35). Part of this low diatom production is related to external nutrient supply that favored growth of cyanobacteria at the expense of diatoms. This approach shows that diatom Si deposition was strongly influenced by the availability of light and nutrients, related to the duration of lake mixing and warming in spring, during most of the studied period. The remaining unexplained variability, however, indicates that additional factors influence Si deposition. Further tests in other deep, temperate lakes are necessary to verify if this relation is a common feature and consequently, if diatom Si can be used as a proxy for spring mixing duration in such lakes.

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Section: Discussionmentioning

confidence: 94%

Effects of spring warming and mixing duration on diatom deposition in deep Tiefer See, NE Germany

et al. 2016

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“…Such systems are typically characterized by opposing vertical resource gradients (with light availability decreasing and nutrient availability increasing with depth), setting up a smooth, continuous gradient of spatially varying selection for light versus nutrient use capacities. As an illustration, we use the so-called fixed stoichiometry version of a phytoplankton model by Jäger et al (2010), where nutrients from algae that have settled out of the water column are recycled in the bottom sediment. The equations that describe the ecological dynamics are reproduced in appendix E together with the details of how the evolutionary dynamics were implemented.…”

Section: Example 2: Sinking Algae In a Water Columnmentioning

confidence: 99%

Determining Selection across Heterogeneous Landscapes: A Perturbation-Based Method and Its Application to Modeling Evolution in Space

Wickman

Diehl

Blasius

et al. 2017

The American Naturalist

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Online enhancements: appendixes.abstract: Spatial structure can decisively influence the way evolutionary processes unfold. To date, several methods have been used to study evolution in spatial systems, including population genetics, quantitative genetics, moment-closure approximations, and individualbased models. Here we extend the study of spatial evolutionary dynamics to eco-evolutionary models based on reaction-diffusion equations and adaptive dynamics. Specifically, we derive expressions for the strength of directional and stabilizing/disruptive selection that apply both in continuous space and to metacommunities with symmetrical dispersal between patches. For directional selection on a quantitative trait, this yields a way to integrate local directional selection across space and determine whether the trait value will increase or decrease. The robustness of this prediction is validated against quantitative genetics. For stabilizing/disruptive selection, we show that spatial heterogeneity always contributes to disruptive selection and hence always promotes evolutionary branching. The expression for directional selection is numerically very efficient and hence lends itself to simulation studies of evolutionary community assembly. We illustrate the application and utility of the expressions for this purpose with two examples of the evolution of resource utilization. Finally, we outline the domain of applicability of reaction-diffusion equations as a modeling framework and discuss their limitations.

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“…These cases will require numerical solution of the full model, possibly with the addition of sinking or buoyancy (as in Huisman and Sommeijer, 2002a,b;Huisman et al, 2004;Jäger et al, 2010;Ryabov et al, 2010).…”

Section: Assumptions Limitations and Extensionsmentioning

confidence: 99%

The vertical distribution of phytoplankton in stratified water columns

Mellard

Yoshiyama

Litchman

et al. 2011

Journal of Theoretical Biology

105

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Physical Determinants of Phytoplankton Production, Algal Stoichiometry, and Vertical Nutrient Fluxes

Cited by 42 publications

References 52 publications

Effects of spring warming and mixing duration on diatom deposition in deep Tiefer See, NE Germany

Effects of spring warming and mixing duration on diatom deposition in deep Tiefer See, NE Germany

Determining Selection across Heterogeneous Landscapes: A Perturbation-Based Method and Its Application to Modeling Evolution in Space

The vertical distribution of phytoplankton in stratified water columns

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