Improving precision and reducing bias in biological surveys: estimating false-negative error rates

The use of presence/absence data in wildlife management and biological surveys is widespread. There is a growing interest in quantifying the sources of error associated with these data. We show that false-negative errors (failure to record a species when in fact it is present) can have a significant impact on statistical estimation of habitat models using simulated data. Then we introduce an extension of logistic modeling, the zero-inflated binomial (ZIB) model that permits the estimation of the rate of false-negative errors and the correction of estimates of the probability of occurrence for false-negative errors by using repeated. visits to the same site. Our simulations show that even relatively low rates of false negatives bias statistical estimates of habitat effects. The method with three repeated visits eliminates the bias, but estimates are relatively imprecise. Six repeated visits improve precision of estimates to levels comparable to that achieved with conventional statistics in the absence of false-negative errors In general, when error rates are less than or equal to50% greater efficiency is gained by adding more sites, whereas when error rates are >50% it is better to increase the number of repeated visits. We highlight the flexibility of the method with three case studies, clearly demonstrating the effect of false-negative errors for a range of commonly used survey methods.

Using tropical grasses to enhance the efficiency of nitrogen capture from dairy effluent

Five rates (0, 28.0, 65.4, 83.7 and 111.7 mm) of dairy effluent were applied through irrigation to tropical grass pasture during the wet season on the Atherton Tablelands in the Far North of Queensland, Australia. Irrigation water was applied to the treatments in inverse proportion to the effluent for equivalent total water application. Pastures were harvested on a three weekly basis, dry matter yield determined and sub samples analysed for N concentration (%), and Nitrogen yield (kg ha-1) calculated. Lysimeters installed in the high effluent treatment and the no effluent treatment measured leachate volume to 50 cm. Samples of leachate were analysed for nitrogen concentration and loss below 50 cm calculated. There was no significant difference in pasture yield and nitrogen yield among treatments. Loss of nitrogen through leachate was substantial in both the high effluent treatment and the zero effluent treatment.