The delimitation of biological species, i.e., deciding which individuals belong to the same species and whether and how many different species are represented in a data set, is key to the conservation of biodiversity. Much existing work uses only genetic data for species delimitation, but this can be misleading, because geographically distant groups of individuals can be genetically quite different even if they belong to the same species. This paper investigates the problem of testing whether two potentially separated groups of individuals can belong to a single species or not based on genetic and spatial data. A way to do this is via partial Mantel tests (PMTs), in which significance is traditionally assessed through permutations. By replacing these with jackknife and bootstrap, two new versions of PMT for species delimitation are introduced in this study, where their type-I-error rate and power are compared with permutation-based PMT on data generated by GSpace, a spatially-explicit genetic data simulator. Results suggest that bootstrap-based PMTs have unacceptable type-I-error, while jackknife-based ones are more conservative than permutation-based ones, but less powerful.