Using Generalised Dissimilarity Models and many small samples to improve the efficiency of regional and landscape scale invertebrate sampling

Abstract

It is rarely cost-effective to survey invertebrates for use in systematic conservation planning activities. The efficiency of sampling methods needs to be improved, and this is especially important at landscape and regional scales. We investigated two methods that could be used to improve regional scale sampling efficiency using a case study of ants, beetles, flies, bugs, spiders and wasps from the semi-arid Pilbara region of Western Australia. First, Generalised Dissimilarity Models (GDMs) were used to divide the region into landscapes with relatively homogeneous communities and environmental conditions. We found that some of these landscapes were large, and a low sampling density could be employed in these areas due to the low spatial turnover in species. Other landscapes were 1-2 orders of magnitude smaller, and a higher sampling density should be employed to capture the high species turnover and unique species in these areas. Variation of sampling density based on landscape dimensions could vastly improve survey efficiency. Second, we investigated whether one large sample or five small samples were a more efficient method to estimate the species composition of each landscape. We found that five small samples captured a higher proportion of landscape scale species richness for a fixed sampling effort, and was therefore a more efficient method to determine the species composition of the landscape. Combining five small samples also resulted in less sample variability than one large sample, which increases statistical power to detect changes. We concluded that GDM was an effective method to increase sampling efficiency, because it allowed sampling density to vary according to the spatial turnover in species. Using many small samples is a more efficient method to capture the species composition of landscapes than a single large sample with an equivalent sample size. Disciplines Medicine and Health Sciences | Social and Behavioral Sciences Publication DetailsAshcroft, M. B., Gollan, J. R., Faith, D. P., Carter, G. A., Lassau, S. A., Ginn, S. G., Bulbert, M. W. & Cassis, G. (2010). Using Generalised Dissimilarity Models and many small samples to improve the efficiency of regional and landscape scale invertebrate sampling. Ecological Informatics, 5 (2), 124-132. Efficient invertebrate sampling 2Abstract It is rarely cost-effective to survey invertebrates for use in systematic conservation planning activities. The efficiency of sampling methods needs to be improved, and this is especially important at landscape and regional scales. We investigated two methods that could be used to improve regional scale sampling efficiency using a case study of ants, beetles, flies, bugs, spiders and wasps from the semi-arid Pilbara region of Western Australia. First, Generalised Dissimilarity Models (GDMs) were used to divide the region into landscapes with relatively homogeneous communities and environmental conditions. We found that some of these landscapes were large, and a low sampling density could be employed in thes...

Predictions of beta diversity for reef macroalgae across southeastern Australia

“…In community modelling, GDM has become a popular approach for analysing and predicting patterns of species turnover (mainly in terrestrial systems) (see, e.g., Ferrier et al 2002, Allnutt et al 2008, Growns 2009, Marsh et al 2010, Ashcroft et al 2010, Overton et al 2009) but has rarely been compared with alternate modelling approaches for community data. For the first time we have been able to assess the congruence of predictions generated from a GDM approach to a quite different and novel approach, GFM, at a regional scale for an area that has globally been identified as important for algal diversity (Kerswell 2006).…”

“…While the methods are technically different, the predictive outputs i.e., mapped beta diversity of GDM and GFM are highly suitable as subjects for comparison. The GDM approach is now used in terrestrial ecological community modelling and biodiversity assessment (Ferrier et al 2007), conservation planning , Marsh et al 2010, regional scale survey design (Ashcroft et al 2010), river classification (Leathwick et al 2010) and marine environmental classification (Leathwick et al 2009). GFM in contrast is a novel approach that has so far been applied for community modelling and biodiversity assessment to the continental shelves around Australia ) and the Gulf of Maine and the Gulf of Mexico as part of the Census of Marine Life (CoML) project (unpublished).…”

A conservation assessment of the terrestrial invertebrate fauna of Mkambati Nature Reserve in the Pondoland Centre of Endemism

“…It must be recognised, however, that the survey represents a limited data set in terms of temporal variation and sampling effort, and the estimated species richness is higher than that sampled. Increasing the number of samples collected at each site, as well as the number of sites sampled (Ashcroft et al 2010), and resampling to capture temporal change would increase the number of species. Increasing sampling effort in invertebrate surveys increases the time and cost of processing and identifying the material (Ward & Larivière 2004), and these limitations have to be weighed up against the urgent need for data for areas such as those in global biodiversity hotspots.…”

Modelling beta diversity of aquatic macroinvertebrates in High Andean wetlands

“…This approach is an extension of matrix regression and is specifically designed to accommodate the nonlinearity commonly found in largescale ecological datasets. The GDM method has been used for terrestrial ecological community modelling and biodiversity assessment (Ferrier et al, 2007), conservation planning (Ferrier, 2002;Marsh et al, 2010), regional scale survey design (Ashcroft et al, 2010;Leaper et al, 2011;Laidlaw et al, 2015), and river (Leathwick et al, 2011) and marine environmental classifications (Lasram et al, 2015).…”