Variations in animal populations and community structure are inherently scale dependent. For Hudson zooplankton interesting scales of variation include the temporal scales of diel and tidal cycles as well as seasonal and interannual variation. These temporal scales might be measured in hours (diel and tidal), weeks (seasonal), and years (interannual). Some interesting spatial scales of variation include relatively small-scales that encompass replicate samples as well as the "patchiness" of zooplankton. These occur at scales of hundreds to thousands of liters. At the opposite end of the spectrum is the distribution and river-wide abundance of zooplankton along the north-south axis of the river (a length of >250 km).
Specific questions often dictate the scale of sampling and variance analysis. For example, studies of predation on zooplankton by fish need to consider the mean and variance of zooplankton at the foraging scale of the fish. If zooplankton are aggregated in space, fish might successfully forage from aggregation to aggregation if they have a means of detecting concentrated patches of zooplankton. The population consequences of such behavior for both zooplankton and fish require some means of "scaling-up" foraging interactions to assess their consequences for the respective populations. These types of scale-dependent and scale-translation issues are important problems in zooplankton research specifically, in ecological research generally, and represent an exciting frontier of research. Most zooplankton studies focus on samples taken at a single or a few stations. Whole-system estimates of abundance based on sampling across spatial and temporal scales are rarely made but are needed to effectively assess the possible ecosystem consequences of zooplankton dynamics. Here, we describe variation of zooplankton at several scales and an example of "scaling-up" to estimate riverwide abundances from temporal and spatial data.
At the scale of replicate samples (approximately 100-1,000 liters), the logarithm of the mean of a set of replicate samples is related to the logarithm of the variance, and the slope of this relationship is in the range of 1.4 to 1.9 (Pace, Findlay, and Lints, 1991). Variance is predictable, therefore, given an estimate of mean abundance. Sampling can be adjusted to achieve a desired precision. This is an important advantage in hypothesis testing as both the consequences ofvarying statistical significance level and power canbe assessed as a function of expected differences in density and sample size (see Cyr et al., 1992 for an example).
Tides are a significant feature of the Hudson and may influence zooplankton variation at the scale of hours as the tide ebbs, slackens, and then floods. Tidal magnitude also varies over the monthly cycle ofspringand neap tides. Significant variation associated with tidal dynamics has been observed in the Hudson (Pace, Findlay, and Lints, 1992). In estuar-ine systems plankton exploit tides for migration as well as maintenance of position in the estuary (e.g., Christy and Morgan, 1998). A study of larval transport in the Hudson estuary (Kunze, 1995) showed that the ability of swimming larvae (for example, a gastropod, Littorina, and a barnacle, Balanus) to maintain depth was highly dependent not only on their swimming capabilities but also the degree of tidal mixing. At the George Washington Bridge (river km (RKM) 19), larvae were mixed throughout the water column during mid-ebb and mid-flood of a spring tide. At the Verrazano Narrows (in NewYork Harbor), waters were less mixed because of greater salinity stratification. Here, larvae were able to regulate their depth in the water column, potentially reducing their loss from the estuary.
At seasonal time scales zooplankton exhibit consistent seasonal variation within the Hudson. Figure 16.2 illustrates the dynamics of rotifers, copepods, and cladocerans at a single station located near Kingston, NewYork (RKM 152), for two years: one prior to the establishment of large populations of the zebra mussel (1991) and a postzebra mussel year (1999). Zooplankton are typically at low levels during winter and early spring when low temperatures reduce population growth and high inputs of fresh water result in short water residence times and increased advective losses. As temperature increases during spring, zooplankton become more abundant. For example, in 1991 rotifer abundances increased from about 10 l-1 in April to 1,000 l-1 by June and densities greater than 100 l-1 were sustained until late November. Rotifer dynamics were similar in 1999, but overall abundance was reduced due to zebra mussels (see next section). Copepods, principally cyclopoids, are persistentlyabundant with occasional summer increases to greater than 10 l-1 (Fig. 16.2). Clado-cerans undergo a consistent seasonal cycle that features rapid increase to high densities in spring, sharp mid-summer decline, and moderate populations (1-10 l-1) in late summer and fall. This is
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