The variance spectra of phytoplankton, krill and water temperature in the Antarctic Ocean south of Africa

Weber, L. H.; El‐Sayed, Sayed Z.; Hampton, Ian

doi:10.1016/0198-0149(86)90039-7

Cited by 120 publications

(74 citation statements)

References 20 publications

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“…Phytoplankton patchiness has been analysed using variance spectra and typically shown to follow a power-law form but with higher variance at the larger wavelengths (e.g. Denman & Platt 1976;Gower et al 1980;Weber et al 1986). We can therefore infer that cluster-size distributions would exhibit a power-law scaling but with a positive slope.…”

Section: Resultsmentioning

confidence: 99%

Cluster size distributions: signatures of self–organization in spatial ecologies

Pascual

Roy

Guichard

et al. 2002

Phil. Trans. R. Soc. Lond. B

106

112

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Three different lattice-based models for antagonistic ecological interactions, both nonlinear and stochastic, exhibit similar power-law scalings in the geometry of clusters. Specifically, cluster size distributions and perimeter-area curves follow power-law scalings. In the coexistence regime, these patterns are robust: their exponents, and therefore the associated Korcak exponent characterizing patchiness, depend only weakly on the parameters of the systems. These distributions, in particular the values of their exponents, are close to those reported in the literature for systems associated with self-organized criticality (SOC) such as forest-fire models; however, the typical assumptions of SOC need not apply. Our results demonstrate that power-law scalings in cluster size distributions are not restricted to systems for antagonistic interactions in which a clear separation of time-scales holds. The patterns are characteristic of processes of growth and inhibition in space, such as those in predator-prey and disturbance-recovery dynamics. Inversions of these patterns, that is, scalings with a positive slope as described for plankton distributions, would therefore require spatial forcing by environmental variability.

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Section: Resultsmentioning

confidence: 99%

Cluster size distributions: signatures of self–organization in spatial ecologies

Pascual

Roy

Guichard

et al. 2002

Phil. Trans. R. Soc. Lond. B

106

112

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“…This would explain the range of positive and negative krill-food relationships reported in the literature at different scales (e.g. Weber et al 1986. Overall, the relative importance of top-down and bottom-up controls varies both with scale of observation and with local predator densities.…”

Section: Overall Perspectivementioning

confidence: 61%

“…Hardy & Gunther 1935, Weber & El-Sayed 1985, Weber et al 1986, Lawson et al 2008, they have arrived at a variety of conclusions. Both positive and negative relationships between phytoplankton and krill have been found, with the former interpreted as the krill aggregating in good feeding grounds and the latter implying that krill have grazed down their food (Weber et al 1986). The sign of this relationship has been suggested to depend partly on the scale of analysis, and various positive, negative and dome-shaped relationships have been found across a wide range of scales (e.g.…”

Section: Introductionmentioning

confidence: 99%

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Role of krill versus bottom-up factors in controlling phytoplankton biomass in the northern Antarctic waters of South Georgia

Whitehouse

Atkinson²,

Ward³

et al. 2009

Mar. Ecol. Prog. Ser.

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The extent to which Antarctic phytoplankton stocks are controlled by 'bottom-up' and/or 'top-down' factors is highly variable. Here we consider data collected at South Georgia during 3 summer surveys that recorded substantial hydrographic variability. A suite of bottom-up and top-down controlling factors were measured simultaneously at the mesoscale. Sea surface temperature varied by > 2°C, macronutrients ranged from near-winter concentrations to near-depleted, while mean densities of a major grazer, krill Euphausia superba, varied between near-zero and > 400 g wet mass m -2 . A general linear model was used to identify the main factors implicated in the observed differences in phytoplankton biomass. Despite east-to-west and on-to off-shelf temperature gradients, temperature per se was not implicated in phytoplankton variability. Also, while there was an abundance of NO 3 -N in surface waters, NH 4 -N was the key nutrient throughout. A domed relationship between phytoplankton and krill peaked between 2 and 4 mg chlorophyll a m -3 and 6 and 30 g krill m -2 . The positive side of this dome was represented by the west off-shelf region downstream of South Georgia. Here, an ample supply of micro-and macronutrients promoted high primary production, and low densities of krill presumably had little grazing effect. This positive relationship between krill and phytoplankton biomasses was interpreted as krill accumulating in areas of good feeding conditions. The negative side of the dome was typified by the east off-shelf region, where macronutrients remained high, primary production rates were low, and krill densities were very high. The grazing rates calculated here suggested that krill affect their food stocks severely, and the negative krill-phytoplankton relationship in this region may reflect locally high krill densities driving down their food supply.

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“…In aquatic environments, efforts to quantify scale-dependent pattern and process have traditionally focused on populations of particles or organisms that drift with water motion (e.g., Platt and Denman 1975;Powell et al 1975;Horwood 1978). Parallel examinations of mobile organism distributions are not as common (e.g., Horwood and Cushing 1978) but are increasing in number (e.g., Weber et al 1986;Schneider 1994a;Horne and Schneider 1997). Explicit treatment of scale is rapidly becoming standard practice (e.g., Giller et al 1994;Schneider 1994b;Peterson and Parker 1998) when quantifying distribution patterns and the relevance of biological and physical processes.…”

Section: Introductionmentioning

confidence: 99%

Comparative examination of scale-explicit biological and physical processes: recruitment of Pacific hake (<i>Merluccius productus</i>)

Horne¹,

Smith²,

Schneider³

1999

Journal canadien des sciences halieutiques et aquatiques

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Abstract:The creation, maintenance, and destruction of aquatic organism distributions result from biological and physical processes that operate at different spatial and temporal scales. Rate diagrams plot and contour ratios of process rates as a function of spatial and temporal scale to summarize the relative importance of demographics, growth, and kinematics. We demonstrate the utility of this approach by examining physical and biological processes that influence the distribution and survival of larval and juvenile Pacific hake (Merluccius productus) in the California Current region. Processes that influence changes in hake biomass switch from mortality and drift among larvae to somatic growth and active locomotion among juveniles. Comparison of hake rate diagrams with those of capelin (Mallotus villosus) and Atlantic cod (Gadus morhua) show that dominant processes differ across scales, across life history stages, and across species.Résumé : La création, le maintien et la disparition des aires de répartition des organismes aquatiques résultent de processus biologiques et physiques qui agissent à des échelles spatiales et temporelles différentes. Des diagrammes de taux et des rapports d'isolignes des taux des processus en fonction de l'échelle spatiale et temporelle sont présentés pour résumer l'importance relative des facteurs liés à la démographie, à la croissance et à la cinématique. Nous démontrons l'utilité de cette approche de par un examen des processus physiques et biologiques qui influent sur la répartition et la survie des larves et des juvéniles du merlu du Pacifique (Merluccius productus) dans la région du courant de Californie. Les processus qui influent sur la variation de la biomasse du merlu vont de la mortalité et de la dérive chez les larves à la croissance somatique et au déplacement actif chez les juvéniles. La comparaison des diagrammes du merlu avec ceux du capelan (Mallotus villosus) et de la morue franche (Gadus morhua) montre que les processus dominants varient selon l'échelle, l'étape du cycle vital et l'espèce.[Traduit par la Rédaction] Horne et al. 179

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The variance spectra of phytoplankton, krill and water temperature in the Antarctic Ocean south of Africa

Cited by 120 publications

References 20 publications

Cluster size distributions: signatures of self–organization in spatial ecologies

Cluster size distributions: signatures of self–organization in spatial ecologies

Role of krill versus bottom-up factors in controlling phytoplankton biomass in the northern Antarctic waters of South Georgia

Comparative examination of scale-explicit biological and physical processes: recruitment of Pacific hake (<i>Merluccius productus</i>)

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