Here we present an objective, repeatable approach to delineating species when populations are divergent and highly structured geographically using the Californian trapdoor spider species complex Aptostichus atomarius Simon as a model system. This system is particularly difficult because under strict criteria of geographical concordance coupled with estimates of genetic divergence, an unrealistic number of population lineages would qualify as species (20 to 60). Our novel phylogeographic approach, which is generally applicable but particularly relevant to highly structured systems, uses genealogical exclusivity to establish a topological framework to examine lineages for genetic and ecological exchangeability in an effort to delimit cohesion species. Both qualitative assessments of habitat and niche-based distribution modeling are employed to evaluate selective regime and ecological interchangeability among genetic lineages; adaptive divergence among populations is weighted more heavily than simple geographical concordance. Based on these analyses we conclude that five cohesion species should be recognized, three of which are new to science.

Species exhibiting morphological homogeneity and strong population structuring present challenging taxonomic problems: morphology-based approaches infer few species, whereas genetic approaches often indicate more. Morphologically cryptic, yet genetically divergent species groups require alternative approaches to delimiting species that assess adaptive divergence and ecological interchangeability of lineages. We apply such an approach to Promyrmekiaphila, a small genus (three nominal taxa) of trapdoor spiders endemic to northern California to define cohesion species (lineages that are genetically exchangeable and ecologically interchangeable). Genetic exchangeability is evaluated using standard phylogeographical techniques (e.g. nested clade analysis); ecological interchangeability is assessed using two GIS-based approaches. First, climatic values are extracted from layer data for each locality point and utilized in a principal components analysis followed by MANOVA. Second, niche-based distribution models of genetically divergent lineages are created using a maximum-entropy modelling approach; the amount of overlap among lineages is calculated and evaluated against a probability distribution of null overlap. Lineages that have significant amounts of predicted overlap are considered ecologically interchangeable. Based on a synthetic evaluation of ecological interchangeability, geographical concordance, and morphological differentiation, we conclude that Promyrmekiaphila comprises six cohesion species, five of which are cryptic (i.e. undetectable by conventional means).

One of the primary goals of any systematic, taxonomic or biodiversity study is the characterization of species distributions. While museum collection data are important for ascertaining distributional ranges, they are often biased or incomplete. The Genetic Algorithm for Rule-set Prediction (GARP) is an ecological niche modelling method based on a genetic algorithm that has been argued to provide an accurate assessment of the spatial distribution of organisms that have dispersal capabilities. The primary objective of this study is to evaluate the accuracy of a GARP model to predict the spatial distribution of a non-invasive, non-vagile invertebrate whose full distributional range was unknown. A GARP predictive model based on seven environmental parameters and 42 locations known from historical museum records for species of the trapdoor spider genus Promyrmekiaphila was produced and subsequently used as a guide for ground truthing the model. The GARP model was neither a significant nor an accurate predictor of spider localities and was outperformed by more simplistic BIOCLIM and GLM models. The isolated nature of Promyrmekiaphila populations mandates that environmental layers and their respective resolutions are carefully chosen for model production. Our results strongly indicate that, for modelling the spatial distribution of low vagility organisms, one should employ a modelling method whose results are more conducive to interpretation than models produced by a 'black box' algorithm such as GARP.

Background: Species that are widespread throughout historically glaciated and currently nonglaciated areas provide excellent opportunities to investigate the role of Pleistocene climatic change on the distribution of North American biodiversity. Many studies indicate that northern animal populations exhibit low levels of genetic diversity over geographically widespread areas whereas southern populations exhibit relatively high levels. Recently, paleoclimatic data have been combined with niche-based distribution modeling to locate possible refugia during the Last Glacial Maximum. Using phylogeographic, population, and paleoclimatic data, we show that the distribution and mitochondrial data for the millipede genus Narceus are consistent with classical examples of Pleistocene refugia and subsequent post-glacial population expansion seen in other organismal groups.

The mygalomorph spider genus Promyrmekiaphila comprises two species known from northern and central California. The type species, P. clathrata (Simon), is considered a senior synonym of P. gertschi Schenkel and P. zebra (Chamberlin & Ivie); male and female exemplar specimens are described. A new species, Promyrmekiaphila winnemem, from Shasta and Tehama Counties in northern California, is described.

This paper addresses the issues raised by McNyset and Blackburn (2006) in their response to Stockman et al . (2006). Re-evaluation of our published GARP analyses by McNyset and Blackburn showed that a much improved ecological niche model is obtained for predicting the distribution of the trapdoor spider genus Promyrmekiaphila in central/northern California. The improved niche model results in a substantially reduced omission error rate and a predictive model comparable to models obtained using other methods (GLM and BIOCLIM). However, the improved GARP models have a high commission error rate (> 0.75); consequently, the inferences regarding difficulties in modelling non-vagile taxa drawn by Stockman et al . remain valid. Finally, we discuss other relatively minor criticisms of our study raised by McNyset and Blackburn and issues related to the peer review of our original paper. KeywordsAraneae, Desktop GARP, niche modelling, predicting species occurrences, Promyrmekiaphila . McNyset and Blackburn (2006) reassessed the data and analyses reported in our paper (Stockman et al ., 2006). Their use of Desktop GARP (DG, Scachetti-Pereira, 2002) with our data produces a more accurate niche model, particularly with respect to omission rate, than the one we obtained. The primary criticism raised by McNyset and Blackburn (2006) resides with our mistaken use of many single-specimen models summed to form a single predictive model. Secondary criticisms include use of categorical layer data (soil and vegetation class), model comparison, use of layer data at too fine a resolution, and use of multiple species to generate single models. The improvements found in their DG models are largely attributed to the use of all 42 of our data points to generate a summed predictive model. While we do not necessarily agree with all of the points raised by McNyset and Blackburn we are concerned with the discrepancy between our original analysis and the one they provide. We report here a reanalysis of our data set (Stockman et al ., 2006) for DG, address the later concerns raised by McNyset and Blackburn, discuss ground-truthing of our models, and make some final concluding remarks. This paper is intended to serve as both a response to McNyset and Blackburn (2006) and as a correction to Stockman et al . (2006). Our original conclusion that non-vagile organisms present a special class of problems for predictive niche modelling is not only retained in light of the corrected model, but is further strengthened.We would like to state upfront explicitly that the DG predictive models we report here are consistent with those of McNyset and Blackburn. We trace the discrepancy to a data input mistake, rather than 'ignorance' , at one of the earlier stages in our analysis. We were likewise able to generate DG models for Promyrmekiaphila distributions that were much improved with respect to omission rate. The intent of our original paper was not to evaluate the DG software package nor was it intended as an evaluation of the GARP algorithm; in fac...

d-novl is a Monte Carlo program designed to generate a null expectation of overlap between two niche-based distribution models. The user may choose between two growth algorithms: the separated algorithm grows a random number of disjointed growth areas, whereas the number of islands algorithm allows the user to input the desired number of growth areas. The latter algorithm can also be used to grow a single growth area. The resulting probability distribution of expected overlap values can be exported into a spreadsheet for further analysis. d-novl is freely available for Mac and Windows platforms at http://www.mygalomorphae.org.

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