Why model species distribution? Complements BHUs for conservation planning, helping develop irreplaceability ratings Supplements data for known distribution of species. Useful for discovering environmental factors that determine distribution. Particularly useful for extrapolating effects of environmental/climate change. Useful for estimating potential susceptibility of areas to alien invasives.

Species Envelope Source: Proteas of Southern Africa The areas in which Protea nitida is known to occur

Why use GARP? Implemented for many purposes in recent years, such as modelling invasive species (Peterson & Robins, 2003), infectious diseases, (Peterson & Shaw, 2003), and global warming (Thomas et al, 2004) Robust and powerful (Stockwell & Noble, 1992; Stockwell & Peters, 1999). Needs no absence data, and little a priori knowledge. Little independent testing of the algorithm has been done, and should be carried out (Peterjohn, 2001)

Test for difference between specialist and generalist species (H 0 : no difference; two sample t-test, df = 8)

The effects of the number of modelling points used of the effectiveness of GARP

The relationship between Type I and Type II errors (false positives and false negatives) in GARP- modelled distributions

Implications of Type I and Type II errors in alien invasive distribution modelling TYPE I ERROR (false positive) Predicts species presence in sites at which it may not be found. Overestimates range, increasing the risk priority of the species. This leads to inclusion of sites of little or no importance for conservation. May falsely skew conservation priorities toward elimination of plant species with low potential impact. TYPE II ERROR (false negative) Failure to predict environmental suitability in a site at which the species is known to occur. May therefore underestimate the overall susceptibility to invasion. Leads to exclusion of sites of possibly vital conservation value. Skews conservation priorities away from alien species with a potentially high invasive impact.

The incidence of Type II errors (false negatives) related to the number of modelling points used

Conclusions GARP-derived species layers have some potential use for conservation planning. There is little difference observed in the ability of the model to predict specialist and generalist species, although some tendencies to overestimate range for specialist species have been observed. The conservation objectives for a species should be borne in mind – in general it is better to err on the side of caution and choose a model that minimizes false negative (Type II) errors. Modelling for species at a finer scale may prove challenging, because obtaining environmental layers at the specified scale can be difficult and local environmental conditions may vary (micro-climate), and local the extent of field work required may be prohibitive.

Acknowledgements Richard Knight Tony Rebelo and the Protea Atlas Project The Beit Trust