Public support for sustainable commercial harvesting of wildlife: An Australian case study

This paper surveys a sample of 204 members of the Australian public to determine their attitude to the sustainable commercial harvesting of wildlife generally, and considers their specific support for the sustainable commercial harvesting of each of 24 Australian native species. The general attitude of the sample to wildlife harvesting is related to their attitude to nature conservation. The relationship between respondents’ support for the sustainable commercial harvesting of each of the species and their degree of endangerment based on IUCN Red List rankings is established and found to be an inverse one. Support for the commercial sustainable use of each of the species is compared with the willingness of respondents to pay for their conservation. Support for sustainable commercial harvesting of species is found to be inversely related to the willingness of respondents to pay is for a particular species’ conservation. In turn, this willingness to pay is found to rise with the degree of endangerment of species. While the likeability of a species has some influence on whether there is support or not for its commercial harvesting, it does not seem to be the predominant influence— the degree of endangerment of a species appears to be the major influence here. Even so, this does not imply majority support for the harvest of all species that are not threatened; rather, majority support for harvest was observed only for some species known to be abundant. None of the species that appear in the Red List have majority support for harvesting. Implications are outlined of the results for the policy of promoting wildlife conservation by means of sustainable use.

The critical power function is dependent on the duration of the predictive exercise tests chosen

The linear relationship between work accomplished (W-lim) and time to exhaustion (t(lim)) can be described by the equation: W-lim = a + CP.t(lim). Critical power (CP) is the slope of this line and is thought to represent a maximum rate of ATP synthesis without exhaustion, presumably an inherent characteristic of the aerobic energy system. The present investigation determined whether the choice of predictive tests would elicit significant differences in the estimated CP. Ten female physical education students completed, in random order and on consecutive days, five art-out predictive tests at preselected constant-power outputs. Predictive tests were performed on an electrically-braked cycle ergometer and power loadings were individually chosen so as to induce fatigue within approximately 1-10 mins. CP was derived by fitting the linear W-lim-t(lim) regression and calculated three ways: 1) using the first, third and fifth W-lim-t(lim) coordinates (I-135), 2) using coordinates from the three highest power outputs (I-123; mean t(lim) = 68-193 s) and 3) using coordinates from the lowest power outputs (I-345; mean t(lim) = 193-485 s). Repeated measures ANOVA revealed that CPI123 (201.0 +/- 37.9W) > CPI135 (176.1 +/- 27.6W) > CPI345 (164.0 +/- 22.8W) (P < 0.05). When the three sets of data were used to fit the hyperbolic Power-t(lim) regression, statistically significant differences between each CP were also found (P < 0.05). The shorter the predictive trials, the greater the slope of the W-lim-t(lim) regression; possibly because of the greater influence of 'aerobic inertia' on these trials. This may explain why CP has failed to represent a maximal, sustainable work rate. The present findings suggest that if CP is to represent the highest power output that an individual can maintain for a very long time without fatigue then CP should be calculated over a range of predictive tests in which the influence of aerobic inertia is minimised.