An approach to practical persistence

 A basic problem in community ecology is determining whether a community of interacting species will survive in the long term. A criterion ensuring this is that of permanence (or uniform persistence), which is based on the idea that species densities for large time are above minimum non-zero levels. There are various mathematical techniques for investigating permanence, but they do not yield an estimate for the minimum levels, and these may lie below minimum viability levels in the biological sense of ‘Practical Persistence’. Here we study a technique for obtaining explicit expressions for the minimum levels when one species is ‘slow’. This is illustrated for a predator–prey problem governed by difference equations, and we note that the technique is applicable even when the dynamics is chaotic.. Received: 7 April 1997 / Revised version: 25 March 1998     

Improved Histology for the Chick-Quail Chimera

A simple modification of nuclear staining after acid hydrolysis has been made which provides easy identification of quail nuclear markings in a chick-quail chimera. This method also improves the histologic detail normally seen with hematoxylin and eosin when compared to the more commonly used Feulgen reaction. Embryonic tissues can be fixed in Zenker's or Helly's solution and the sections obtained are hydrolyzed in acid (3.5 N HCl at 37 C for 40-50 min). After acid hydrolysis the sections are stained with hematoxylin and eosin rather than Schiff reagent and fast green. The interphase nuclei of chick cells show homogeneous or mottled purplish blue staining, while quail nuclei contain a dark blue spot. This staining corresponds to the reddish purple staining of the quail's heterochromatin seen adjacent to the nucleolus in the standard Feulgen stain. This new technique facilitates identification of quail cell types in the chick host and provides superior histology of the chick tissues by demonstrating cytoplasmic detail.     

Use of lamplit roads by foraging bats in southern England

Roads illuminated by white streetlamps attracted three times more foraging bats (mostly Pipistrellus pipistrellus ) than did roads lit by orange streetlamps or unlit roads (3.2, 1.2 and 0.7 bat passes/km, respectively). More insects flew around white lamps than around orange lamps (mean 0.67 and 0.083 insects per lamp, respectively). The mean number of bat passes recorded in any 1-km section of road was positively correlated to the number of white streetlamps along the section, and also, independently, to the amount of trees and hedgerows. Bat activity was not related to the number of houses along the road, ambient temperature or cloud cover. The attractive effect of the lamps on the bats was diminished in windy weather.     

Relationship of aerobic and anaerobic parameters with 400 m front crawl swimming performance

The aims of the present study were to investigate the relationship of aerobic and anaerobic parameters with 400 m performance, and establish which variable better explains long distance performance in swimming. Twenty-two swimmers (19.1±1.5 years, height 173.9±10.0 cm, body mass 71.2±10.2 kg; 76.6±5.3% of 400 m world record) underwent a lactate minimum test to determine lactate minimum speed (LMS) (i.e., aerobic capacity index). Moreover, the swimmers performed a 400 m maximal effort to determine mean speed (S400m), peak oxygen uptake (V.O2PEAK) and total anaerobic contribution (C_ANA). The C_ANA was assumed as the sum of alactic and lactic contributions. Physiological parameters of 400 m were determined using the backward extrapolation technique (V.O2PEAK and alactic contributions of C_ANA) and blood lactate concentration analysis (lactic anaerobic contributions of C_ANA). The Pearson correlation test and backward multiple regression analysis were used to verify the possible correlations between the physiological indices (predictor factors) and S400m (independent variable) (p < 0.05). Values are presented as mean ± standard deviation. Significant correlations were observed between S400m (1.4±0.1 m·s^-1) and LMS (1.3±0.1 m·s^-1; r = 0.80), V.O2PEAK (4.5±3.9 L·min^-1; r = 0.72) and C_ANA (4.7±1.5 L·O₂; r= 0.44). The best model constructed using multiple regression analysis demonstrated that LMS and V.O2PEAK explained 85% of the 400 m performance variance. When backward multiple regression analysis was performed, C_ANA lost significance. Thus, the results demonstrated that both aerobic parameters (capacity and power) can be used to predict 400 m swimming performance.