Scale dependence in the species‐discharge relationship for fishes of the southeastern U.S.A.

1. Species‐discharge relationships (SDR) are aquatic analogues of species‐area relationships, and are increasingly used in both basic research and conservation planning. SDR studies are often limited, however, by two shortcomings. First, they do not determine whether reported SDRs, which normally use complete drainage basins as sampling units, are scale dependent. Second, they do not account for the effects of habitat diversity within or among samples. 2. We addressed both problems by using discrete fish zones as sampling units in a SDR analysis. To do so, we first tested for longitudinal zonation in three rivers in the southeastern U.S.A. In each river, we detected successive ‘lower’, ‘middle’, and ‘upper’ fish zones, which were characterized by distinct fish assemblages with predictable habitat requirements. Because our analyses combined fish data from multiple sources, we also used rarefaction and Monte Carlo simulation to ensure that our zonation results were robust to spurious sampling effects. 3. Next, we estimated the average discharge within each zone, and plotted these estimates against the respective species richness within each zone (log₁₀ data). This revealed a significant, linear SDR (r² = 0.83; P < 0.01). Notably, this zonal SDR fit the empirical data better than a comparable SDR that did not discriminate among longitudinal zones. We therefore conclude that the southeastern fish SDR is scale dependent, and that accounting for within‐basin habitat diversity is an important step in explaining the high diversity of southeastern fishes. 4. We then discuss how our zonal SDR can be used to improve conservation planning. Specifically, we show how the slope of the SDR can be used to forecast potential extinction rates, and how the zonal data can be used to identify species of greatest concern.     

Analysis of Time-Varying Biological Data Using Rainflow Cycle Counting

A wide range of biological investigations lead to time-history data. The characterization of such data can be difficult particularly in the presence of signal noise or superimposed signals. Several methods are described which can be brought to bear including FFT, thresholding, peak counting, and range counting. However, each of these approaches has significant disadvantages. In this paper we describe a novel method, known as rainflow cycle counting, for characterizing time varying biological time-history data in terms of spiking or oscillation amplitude and frequency. Rainflow counting is a straightforward algorithm for identifying complete cycles in the data and determining their amplitudes. The approach is simple, reliable, easily lends itself to automation, and robust even in the presence of superimposed signals or background noise. After describing the method, its use and behavior are demonstrated on three sample histories of intracellular calcium concentration in chondrocytes exposed to fluid shear stress. The method is also applied to a more challenging data set that has had an artificial random error included. The results demonstrate that the rainflow counting algorithm identifies signal oscillations and appropriately determines their amplitudes even when superimposed or distorted by background noise. These attractive properties make rainflow counting a powerful approach for quantifying and characterizing biological time histories.     

The role of ant nest-mounds in maintaining small-scale patchiness in dry grasslands in Central Germany

Nest-mounds of Lasius flavus, Lasius alienus and Formica rufibarbis are mainly on north-facing slopes with a markedly patchy distribution at Gimritz, northwest of Halle (Saale). Nest-mound soils had higher sodium and potassium levels but lower phosphorus and nitrogen levels than soils away from mounds. Moisture content was lower but soil pH was significantly higher in nest-mound soils. However, there was no difference in the relative abundance of plants of alkaline or acid soils growing on mounds compared to plants off mounds and no significant difference between the numbers of nitrophilous plants on and off mounds. Fewer plant species (35 spp.) in total occurred on mounds than off mounds (42 spp.). Plant species richness and total plant cover was significantly less on the nest-mounds than off the mounds. Similarly, the mean number of grass (1.39 spp dm−2) and forb species (1.13 spp dm−2) on mounds was lower than the mean number of grass (1.99 spp dm−2) and forb species (1.91 spp dm−2) off mounds. Some shrubs and forbs had higher occurrence and cover on the mounds, although only in Calluna vulgaris, Thymus serpyllum and Cerastium arvense was this difference particularly marked. Ant nest-mounds may favour plant species that cannot compete with tall grasses on unmanaged, set-aside meadows. This revised version was published online in November 2006 with corrections to the Cover Date.