Foraminifer counts in core JM01-1199, and review of radiocarbon ages in the Norwegian-Barents Sea-Svalbard margin

We compare six high-resolution Holocene, sediment cores along a S-N transect on the Norwegian-Svalbard continental margin from ca 60°N to 77.4°N, northern North Atlantic. Planktonic foraminifera in the cores were investigated to show the changes in upper surface and subsurface water mass distribution and properties, including summer sea-surface temperatures (SST). The cores are located below the axis of the Norwegian Current and the West Spitsbergen Current, which today transport warm Atlantic Water to the Arctic. Sediment accumulation rates are generally high at all the core sites, allowing for a temporal resolution of 10-102 years. SST is reconstructed using different types of transfer functions, resulting in very similar SST trends, with deviations of no more than +- 1.0/1.5 °C. A transfer function based on the maximum likelihood statistical approach is found to be most relevant. The reconstruction documents an abrupt change in planktonic foraminiferal faunal composition and an associated warming at the Younger Dryas-Preboreal transition. The earliest part of the Holocene was characterized by large temperature variability, including the Preboreal Oscillations and the 8.2 k event. In general, the early Holocene was characterized by SSTs similar to those of today in the south and warmer than today in the north, and a smaller S-N temperature gradient (0.23 °C/°N) compared to the present temperature gradient (0.46 °C/°N). The southern proxy records (60-69°N) were more strongly influenced by slightly cooler subsurface water probably due to the seasonality of the orbital forcing and increased stratification due to freshening. The northern records (72-77.4°N) display a millennial-scale change associated with reduced insolation and a gradual weakening of the North Atlantic thermohaline circulation (THC). The observed northwards amplification of the early Holocene warming is comparable to the pattern of recent global warming and future climate modelling, which predicts greater warming at higher latitudes. The overall trend during mid and late Holocene was a cooling in the north, stable or weak warming in the south, and a maximum S-N SST gradient of ca 0.7 °C/°N at 5000 cal. years BP. Superimposed on this trend were several abrupt temperature shifts. Four of these shifts, dated to 9000-8000, 5500-3000 and 1000 and ~400 cal. years BP, appear to be global, as they correlate with periods of global climate change. In general, there is a good correlation between the northern North Atlantic temperature records and climate records from Norway and Svalbard.

Distribution models for mountain plant species: The value of elevation

The climatic conditions of mountain habitats are greatly influenced by topography. Large differences in microclimate occur with small changes in elevation, and this complex interaction is an important determinant of mountain plant distributions. In spite of this, elevation is not often considered as a relevant predictor in species distribution models (SDMs) for mountain plants. Here, we evaluated the importance of including elevation as a predictor in SDMs for mountain plant species. We generated two sets of SDMs for each of 73 plant species that occur in the Pacific Northwest of North America; one set of models included elevation as a predictor variable and the other set did not. AUC scores indicated that omitting elevation as a predictor resulted in a negligible reduction of model performance. However, further analysis revealed that the omission of elevation resulted in large over-predictions of species' niche breadths-this effect was most pronounced for species that occupy the highest elevations. In addition, the inclusion of elevation as a predictor constrained the effects of other predictors that superficially affected the outcome of the models generated without elevation. Our results demonstrate that the inclusion of elevation as a predictor variable improves the quality of SDMs for high-elevation plant species. Because of the negligible AUC score penalty for over-predicting niche breadth, our results support the notion that AUC scores alone should not be used as a measure of model quality. More generally, our results illustrate the importance of selecting biologically relevant predictor variables when constructing SDMs.