Regional and local spatial genetic structure of Siberian primrose populations in Northern Europe

Translocation of an arctic seashore plant reveals signs of maladaptation to altered climatic conditions

Ongoing anthropogenic climate change alters the local climatic conditions to which species may be adapted. Information on species' climatic requirements and their intraspecific variation is necessary for predicting the effects of climate change on biodiversity. We used a climatic gradient to test whether populations of two allopatric varieties of an arctic seashore herb (Primula nutans ssp. finmarchica) show adaptation to their local climates and how a future warmer climate may affect them. Our experimental set-up combined a reciprocal translocation within the distribution range of the species with an experiment testing the performance of the sampled populations in warmer climatic conditions south of their range. We monitored survival, size, and flowering over four growing seasons as measures of performance and, thus, proxies of fitness. We found that both varieties performed better in experimental gardens towards the north. Interestingly, highest up in the north, the southern variety outperformed the northern one. Supported by weather data, this suggests that the climatic optima of both varieties have moved at least partly outside their current range. Further warming would make the current environments of both varieties even less suitable. We conclude that Primula nutans ssp. finmarchica is already suffering from adaptational lag due to climate change, and that further warming may increase this maladaptation, especially for the northern variety. The study also highlights that it is not sufficient to run only reciprocal translocation experiments. Climate change is already shifting the optimum conditions for many species and adaptation needs also to be tested outside the current range of the focal taxon in order to include both historic conditions and future conditions.

Addressing potential local adaptation in species distribution models: implications for conservation under climate change

Species distribution models (SDMs) have been criticized for involving assumptions that ignore or categorize many ecologically relevant factors such as dispersal ability and biotic interactions. Another potential source of model error is the assumption that species are ecologically uniform in their climatic tolerances across their range. Typically, SDMs treat a species as a single entity, although populations of many species differ due to local adaptation or other genetic differentiation. Not taking local adaptation into account may lead to incorrect range prediction and therefore misplaced conservation efforts. A constraint is that we often do not know the degree to which populations are locally adapted. Lacking experimental evidence, we still can evaluate niche differentiation within a species' range to promote better conservation decisions. We explore possible conservation implications of making type I or type II errors in this context. For each of two species, we construct three separate Max-Ent models, one considering the species as a single population and two of disjunct populations. Principal component analyses and response curves indicate different climate characteristics in the current environments of the populations. Model projections into future climates indicate minimal overlap between areas predicted to be climatically suitable by the whole species vs. population-based models. We present a workflow for addressing uncertainty surrounding local adaptation in SDM application and illustrate the value of conducting population-based models to compare with whole-species models. These comparisons might result in more cautious management actions when alternative range outcomes are considered.