Local adaptation along an environmental cline in a species with an inversion polymorphism.

Polymorphic inversions are ubiquitous across the animal kingdom and are frequently associated with clines in inversion frequencies across environmental gradients. Such clines are thought to result from selection favouring local adaptation; however, empirical tests are scarce. The seaweed fly Coelopa frigida has an α/ß inversion polymorphism, and previous work demonstrated that the α inversion frequency declines from the North Sea to the Baltic Sea and is correlated with changes in tidal range, salinity, algal composition and wrackbed stability. Here, we explicitly test the hypothesis that populations of C. frigida along this cline are locally adapted by conducting a reciprocal transplant experiment of four populations along this cline to quantify survival. We found that survival varied significantly across treatments and detected a significant Location x Substrate interaction, indicating local adaptation. Survival models showed that flies from locations at both extremes had highest survival on their native substrates, demonstrating that local adaptation is present at the extremes of the cline. Survival at the two intermediate locations was, however, not elevated at the native substrates, suggesting that gene flow in intermediate habitats may override selection. Together, our results support the notion that population extremes of species with polymorphic inversions are often locally adapted, even when spatially close, consistent with the growing view that inversions can have direct and strong effects on the fitness of species.

BAS: balanced acceptance sampling of natural resources.

To design an efficient survey or monitoring program for a natural resource it is important to consider the spatial distribution of the resource. Generally, sample designs that are spatially balanced are more efficient than designs which are not. A spatially balanced design selects a sample that is evenly distributed over the extent of the resource. In this article we present a new spatially balanced design that can be used to select a sample from discrete and continuous populations in multi-dimensional space. The design, which we call balanced acceptance sampling, utilizes the Halton sequence to assure spatial diversity of selected locations. Targeted inclusion probabilities are achieved by acceptance sampling. The BAS design is conceptually simpler than competing spatially balanced designs, executes faster, and achieves better spatial balance as measured by a number of quantities. The algorithm has been programed in an R package freely available for download.