Biological Heterogeneity in Aquatic Ecosystems

Downing, John A.

doi:10.1007/978-1-4612-3062-5_9

Cited by 51 publications

(45 citation statements)

References 59 publications

(64 reference statements)

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“…The locations and boundaries of plankton patches can be related to water masses efficiently, as was observed in this study. Because it is not feasible to collect enough plankton samples with conventional methodology, descriptions of plankton patchiness have been limited until now to statistical indices (see Downing 1991 andPinel-Alloul 1995 for comprehensive reviews). Now we can visualize the locations, boundaries, and internal densities of patches and determine how they are related to underlying mechanisms.…”

Section: Discussionmentioning

confidence: 99%

“…3) were computed with data from 13 dates between 11 October 1996 and 16 May 2000 (Table 1) when acoustic data were collected just prior (Ͻ15 min) to net sampling. Mean volume backscattering strength (MVBS) in depth increments sampled with plankton nets was calculated from volume backscattering strengths from 50 consecutive acoustic pulses at a vertical resolution of 10 acoustic samples (Taylor 1961;Downing 1991;PinelAlloul 1995). Means and variances of acoustic backscattering were computed from 50 evenly spaced acoustic pulses at 0.1-m increments in depths that contained Daphnia.…”

Section: Methodsmentioning

confidence: 99%

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Seasonal and diel patchiness of a Daphnia population: An acoustic analysis

Hembre

Megard

2003

Limnology & Oceanography

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Detailed information about the location and extent of zooplankton patches is fundamental to understand how abiotic and biotic forces interact to structure the spatial distribution of zooplankton. We mapped zooplankton patchiness in a Minnesota lake during spring, summer, and autumn with high-frequency (192-kHz) single-beam sonar. Conventional plankton samples of aggregations detected acoustically revealed that Daphnia pulicaria (mean body length 1.6 mm, mean target strength Ϫ120 dB) scattered most (ϳ63%) of the sound. Other taxa were smaller (Ͻ½ the length of D. pulicaria) and were usually less abundant and therefore scattered much less sound than D. pulicaria. Our acoustic estimates of Daphnia concentrations illustrate extreme patchiness, with concentrations varying by as much as four orders of magnitude over vertical distances of less than 1 m. Seasonal patterns of patchiness were related to predation by rainbow trout and to abiotic factors associated with stratification. Daphnia concentrations were highest from June to October in a deep-water ''refuge zone'' where oxygen concentrations were between 3 and 5 mg L Ϫ1 . These oxygen levels are suitable for Daphnia but are lower than those required by rainbow trout. Heterogeneity in Daphnia concentration along the lake's long axis was highest in May and June, when the population resided primarily in the oxic hypolimnion during the daytime. From July to October, as oxygen concentrations declined in the hypolimnion, the population became more metalimnetic and more uniformly distributed in the horizontal dimension. A diel study of the population in October indicated that the patchiness of population also changed dramatically between day and night. During the day the population aggregated densely in a thin layer (ϳ2 m thick) in the thermocline. After sunset the population dispersed into the epilimnion, where concentrations were ϳ100,000 m Ϫ3 less than they were during the day in the thermocline.Patchy spatial distributions and the low resolution of conventional sampling methods have impeded analyses of zooplankton populations. Zooplankton concentrations have been shown to vary by a factor of 1,000 within distances of meters horizontally or vertically, and the sampling resolution of conventional plankton nets and hoses is usually too coarse to identify the spatial limits of aggregations precisely (Coyle 2000). Variation in population density estimates due to sampling often cannot be distinguished from real changes of population density, and the effects of biological processes are difficult to distinguish from those of advective transport (Megard et al. 1997). Acoustic and optical plankton samplers developed during recent decades are major advances. They have very high sampling rates and spatial resolution, comparable to modern instruments (e.g., CTD profilers) used to measure environmental variables. Large numbers of plank-

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Seasonal and diel patchiness of a Daphnia population: An acoustic analysis

Hembre

Megard

2003

Limnology & Oceanography

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“…This distinction is, however, not as sharp as may appear at first glance, and meanings essentially depend on the choice of approach (Downing 1991, Naeem & Colwell 1991, Shashak & Brand 1991. From a statistical viewpoint, however, 'heterogeneity', when applied to the distribution of the values taken by a random variable, is the opposlte of 'homogeneity', which refers to sameness and similarity.…”

Section: Introductionmentioning

confidence: 98%

Characterisation of space-time variability in stratified and mixed coastal waters (Baie des Chaleurs, Québec, Canada):application of fractal theory

Seuront¹,

Lagadeuc²

1997

Mar. Ecol. Prog. Ser.

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The vanability of in vivo fluorescence, temperature and salinity in the vertically stratifled and well-mixed waters of the Baie des Chaleurs (Quebec, Canada) was investigated as a continuous function of scale by applying the concept of fractal dimension to variogram analysis. Widely applied to the description of spatial heterogeneity, fractal dimension appears here to be a helpful descriptive tool in discnrninating between homogeneity and heterogeneity In time series of both physical and biologlcal parameters. In stratified waters, the structuration of in v~v o fluorescence, temperature and salin~ty remains the same over time, in spite of mixing induced by the rise of a strong wind, and is shown to be associated with the global structure of the water column. In mixed waters, the situation is more complex, giving rise to specific behaviour of in vivo fluorescence and salinity. In both cases, the differences observed between the fractal dimensions can be explained in terms of different ranges of scales perceived in pattern variability and thus, in the complexity of the pattern structure. Wc also suggest that the departure from strict selfsimilarity which seems to be associated with the vertical structure of the residual circulation is an indicator of the transitional zone between different levels of system organisation.

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“…Recent emphasis on the importance of patchiness in ecological interactions (Pickett & White 1985) has focussed on the large amounts of variability within and among patches of habitat, often at small spatial scales (e.g. Downing 1991, Lohse 1993, Chapman 1994, Chapman et al 1995, Farnsworth & Ellison 1996, Thompson et al 1996, Underwood 1996a, Underwood & Chapman 1996, 1998a. Such patterns have mostly been described for the larger components of fauna on intertidal rocky shores or of benthos in soft-sediments (e.g.…”

Section: Introductionmentioning

confidence: 99%

Comparison of patterns of spatial variation of microgastropods between 2 contrasting intertidal habitats

Olabarria¹,

Chapman²

2001

Mar. Ecol. Prog. Ser.

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Small-scale spatial variation in the distribution of the macrofauna of marine intertidal shores has long been recognized, but there have been few quantitative studies about the scales of patchy distribution of the microbenthos on rocky shores. Patchiness has important implications for comparative and descriptive studies of distribution and abundance because it confounds comparisons of abundance at the largest spatial scales unless the smaller scales are appropriately incorporated into the sampling designs. Spatial variation in the distribution of a number of species of intertidal microgastropods across 2 different habitats (sediment and coralline turf) in Botany Bay, Australia, is described using a nested, hierarchical sampling design. Significant variation was detected mainly at small scales, ranging from less than 1 to 10 m. Moreover, the species showed different patterns of variation depending on the type of habitat and the time of sampling. There was no relation between these patterns and the taxonomic relations of the species. These data illustrate the scales of variability that must be considered when planning long-term or baseline investigations of microbenthos to assure that the study adequately represents different habitats and that subsequent ecological inferences are valid.

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Biological Heterogeneity in Aquatic Ecosystems

Cited by 51 publications

References 59 publications

Seasonal and diel patchiness of a Daphnia population: An acoustic analysis

Seasonal and diel patchiness of a Daphnia population: An acoustic analysis

Characterisation of space-time variability in stratified and mixed coastal waters (Baie des Chaleurs, Québec, Canada):application of fractal theory

Comparison of patterns of spatial variation of microgastropods between 2 contrasting intertidal habitats

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