Defining optimal sampling effort for large-scale monitoring of invasive alien plants: a Bayesian method for estimating abundance and distribution
Date
2011
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
1. Monitoring the abundance and spatial structure of invasive alien plant populations is important
for designing and measuring the efficacy of long-term management strategies. However, methods
for monitoring over large areas with minimum sampling effort, but with sufficient accuracy, are
lacking. Although sophisticated sampling techniques are available for increasing sampling efficiency,
they are often difficult to implement for large-scale monitoring, thus necessitating a robust
yet practical method.
2. We explored this problem over a large area (c.20 000 km2), using ad hoc presence–absence
records routinely collected over 4 years in Kruger National Park (KNP), South Africa. Using a
Bayesianmethod designed to solve the pseudo-absence (or false-negative) dilemma, we estimated the
abundance and spatial structure of all invasive alien plants inKNP. Five sampling schemes, with different
spatially weighted sampling efforts, were assessed and the optimal sampling effort estimated.
3. Although most taxa have very few records (50% of the species have only one record), the more
abundant species showed a log-normal species-abundance distribution, with the 29 most abundant
taxa being represented by an estimated total of 2Æ22 million individuals, with most exhibiting positive
spatial autocorrelation.
4. Estimations from all sampling schemes approached the real situation with increasing sampling
effort. An equal-weighted (uniform) sampling scheme performed best for abundance estimation
(optimal efforts of 68 records per km2), but showed no advantage in detecting spatial autocorrelation
(247 records per km2 required). With increasing sampling effort, the accuracy of abundance
estimation followed an exponential form, whereas the accuracy of distribution estimation showed
diverse forms. Overall, a power law relationship between taxon density (as well as the spatial autocorrelation)
and the optimal sampling effort was determined.
5. Synthesis and applications. The use of Bayesian methods to estimate optimal sampling effort indicates
that for large-scale monitoring, reliable and accurate schemes are feasible. These methods can
be used to determine optimal schemes in areas of different sizes and situations. In a large area like
KNP, the uniform equal-weighted sampling scheme performs optimally for monitoring abundance
and distribution of invasive alien plants, and is recommended as a protocol for large-scale monitoring
in other protected areas as well.
Description
Keywords
abundance estimation, Bayesian estimation, protected areas, pseudo-absence
Citation
Hui, C., Foxcroft, L.C., Richardson, D.M. & MacFadyen, S. (2011) Defining optimal sampling effort for large-scale monitoring of invasive alien plants: a Bayesian method for estimating abundance and distribution. Journal of Applied Ecology, 48: 768-776.