Does marine geospatial/environmental variation affect genetic variation? A meta-analysis
Genetic information is important to inform management and conservation. However, few studies have tested the relationship between genetic variation and geospatial/environmental variation across marine species. Here, I test two genetics-based ideas in evolutionary theory using data from 55 New Zealand coastal marine taxa. The Core-Periphery Hypothesis (CPH) states that populations at the centre of a species’ distribution exhibit greater genetic variability than populations at the periphery (the ‘normal’ model). Variants of this model include the ‘ramped north’ (greatest variation in the north), the ‘ramped south’ (greatest variation in the south), and the ‘abundant edge’ (greatest variation at the distributional edges, least variation at the centre). The Seascape Genetics Test (SGT) null hypothesis predicts no association between genetic variation and environmental variation. I conducted a meta-analysis of published/unpublished material on population genetic connectivity and diversity and marine environmental data to test both hypotheses. To assess the CPH, genetic data were fitted to four models (Normal, Ramped North, Ramped South, Abundant Edge). I also conducted a descriptive analysis between the genetic outcomes of the CPH and abundance records for a subset of species. The SGT involved GLM analyses using eleven geospatial/environmental variables and species-specific FST-ΦST (genetic distance) estimates plus a smaller subset of genetic diversity data. The CPH results showed that 55 of 249 tests (evaluating on average 2.9 ± 1.3 genetic indices in each of the 84 studies) fitted at least one of the four models: Ramped North (10%), Ramped South (8%), Normal (2%) and Abundant Edge (2.4%). Species-specific abundance records followed the same patterns detected by the CPH. These results indicate that edge populations (Ramped North, Ramped South, Abundant Edge) exhibit greater genetic variability than central populations amongst marine taxa from New Zealand, but that most taxa do not conform to any model (~78% of all tests were not statistically significant). For the seascape genetics multi-species analysis (comprising 498 individual tests), the FST-ΦST estimates (genetic distance estimates between pairs of populations) were mostly affected by four factors related to sea surface temperature. For genetic diversity indices the most significant predictors were latitude and longitude. Whilst different factors (e.g., physical oceanography, food availability, life-history traits and harvesting), either acting alone or acting synergistically, are likely to be important in explaining patterns of genetic diversity in New Zealand’s marine coastal species, my results indicate that variables including SST and to a lesser extent the geospatial variables (latitude and longitude) explain much of the variation in the genetic indices tested here.