Fisheries Research 76 (2005) 252–265 The effect of methodological options on geostatistical modelling of animal distribution: A case study with Liocarcinus depurator (Crustacea: Brachyura) trawl survey data M.M. Rufino a,b,c,∗ , F. Maynou b , P. Abell´ o a,b,c,d , L. Gil de Sola d , A.B. Yule c a CRIPSul, IPIMAR, Avenida 5 de Outubro, s/n 8700-305 Olh˜ ao, Portugal b Institut de Ci` encies del Mar—CMIMA (CSIC), Passeig Mar´ ıtim de la Barceloneta 37-49, 08003 Barcelona, Spain c School of Ocean Sciences, University of Wales–Bangor, Gwynedd LL59 5EY, UK d Instituto Espa ˜ nol de Oceanograf´ ıa, Centro Oceanogr´ afico de M ´ alaga, Muelle Pesquero s/n, Apdo. 285, 29640 Fuengirola (M´ alaga), Spain Received 14 September 2004; received in revised form 17 June 2005; accepted 24 June 2005 Abstract Geostatistical methods have been applied to the problem of accurately mapping animal densities derived from trawl surveys. Sample data are often sparse, highly skewed in distribution and quite unlike the examples used to investigate the adequacy of the methodological options available. We analysed the data from a trawl survey of the portunid crab Liocarcinus depurator using two approaches: (a) removal of outliers and (b) logarithmic transformation of the densities. Within each approach we compared a range of options for both the estimation of the underlying spatial structure (variogram) and modelling of crab density through kriging. The results indicated that log-transformation produced the least robust and most unrealistic assessment of L. depurator spatial distribution. Removing outliers gave consistent estimates, regardless of small changes in methodology except when inappropriate spatial models were applied (exponential and Gaussian models did not fit the variogram well). Differences in the number of lags used to build the variogram or the number of outliers removed from the data had more effect on the spatial model parameters than did most of the procedural alterations. Density estimates from kriging highlighted the difference between the two approaches. For example, estimates of the coefficient of variation were most unrealistic from the log-transformation approach but were roughly half that of the original sample when the spatial model was fitted with data without outliers. In general, the failure of the methods to reflect the original sample were related to the assumptions underlying the methods. Thus, the log-transformation approach produces a peculiar distribution of densities, with zero densities creating considerable departure from log-normality. The resulting parameter and density estimates were thus erratic and unrealistic. Removal of outliers helped uncover the spatial structure in the crab population and led to very realistic parameter and density estimates. However, the lack of symmetry in the distribution led to unrealistic (negative) minimum density estimates when kriging forced a symmetrical distribution on the data. ∗ Corresponding author. E-mail address: mrufino@icm.csic.es (M.M. Rufino). 0165-7836/$ – see front matter © 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.fishres.2005.06.014