A regionally coherent ecological fingerprint of climate change, evidenced from natural history collections

Climate change has dramatic impacts on ecological systems, affecting a range of ecological factors including phenology, species abundance, diversity, and distribution. The breadth of climate change impacts on ecological systems leads to the occurrence of fingerprints of climate change. However, climate fingerprints are usually identified across broad geographical scales and are potentially influenced by publication biases. In this study, we used natural history collections spanning over 250 years, to quantify a range of ecological responses to climate change, including phenology, abundance, diversity, and distributions, across a range of taxa, including vertebrates, invertebrates, plants, and fungi, within a single region, Central Norway. We tested the hypotheses that ecological responses to climate change are apparent and coherent at a regional scale, that longer time series show stronger trends over time and in relation to temperature, and that ecological responses change in trajectory at the same time as shifts in temperature. We identified a clear regional coherence in climate signal, with decreasing abundances of limnic zooplankton (on average by 7691 individuals m-3 °C-1) and boreal forest breeding birds (on average by 1.94 territories km-2 °C-1), and earlier plant flowering phenology (on average 2 days °C-1) for every degree of temperature increase. In contrast, regional-scale species distributions and species diversity were largely stable. Surprisingly, the effect size of ecological response did not increase with study duration, and shifts in responses did not occur at the same time as shifts in temperature. This may be as the long-term studies include both periods of warming and temperature stability, and that ecological responses lag behind warming. Our findings demonstrate a regional climate fingerprint across a long timescale. We contend that natural history collections provide a unique window on a broad spectrum of ecological responses at timescales beyond most ecological monitoring programs. Natural history collections are thus an essential source for long-term ecological research.

Spatiotemporal monitoring of the rare northern dragonhead (Dracocephalum ruyschiana, Lamiaceae) - SNP genotyping and environmental niche modeling herbarium specimens

The species we have studied the spatiotemporal genetic change in the northern dragonhead, a plant species that has experienced a drastic population decline and habitat loss in Europe. We have added a temporal perspective to the monitoring of northern dragonhead in Norway by genotyping herbarium specimens up to 200 years old. We have also assessed whether northern dragonhead has achieved its potential distribution in Norway. To obtain the genotype data from 130 herbarium specimens collected from 1820 to 2008, mainly from Norway (83) but also beyond (47), we applied a microfluidic array consisting of 96 SNP markers. To assess temporal genetic change, we compared our new genotype data with existing data from modern samples. We used sample metadata and observational records to model the species' environmental niche and potential distribution in Norway. Our results show that the SNP array successfully genotyped all included herbarium specimens. Hence, with the appropriate design procedures, the SNP array technology appears highly promising for genotyping old herbarium specimens. The captured genetic diversity correlates negatively with distance from Norway. The historical‐modern comparisons reveal similar genetic structure and diversity across space and limited genetic change through time in Norway, providing no signs of any regional bottleneck (i.e., spatiotemporal stasis). The regional areas in Norway have remained genetically divergent, however, both from each other and more so from populations outside of Norway, rendering continued protection of the species in Norway relevant. The ENM results suggest that northern dragonhead has not fully achieved its potential distribution in Norway and corroborate that the species is anchored in warmer and drier habitats.

Contrasting spatial, temporal and environmental patterns in observation and specimen based species occurrence data

Species occurrence data records the location and time of an encounter with a species, and is valuable for many aspects of ecological and evolutionary analyses. A key distinction within species occurrence data is between (1) collected and preserved specimens that can be taxonomically validated (i.e., natural history collections), and (2) observations, which are more error prone but richer in terms of number and spread of observations. In this study we analyse the distribution in temporal, spatial, taxonomic and environmental coverage of specimen- and observation based species occurrence data for land plants in Norway, a region with strong climatic and human population density gradients. Of 4.8 million species occurrence records, the majority (78%) were observations. However, there was a greater species richness in the specimen record (N = 4691) than in the observation record (N = 3193) and most species were recorded more as specimens than observations. Specimen data was on average older, and collected later during the year. Both record types were highly influenced by a small number of prolific contributors. The species most highly represented in the observation data set were widespread or invasive, while in the specimen records, taxonomically challenging species were overrepresented. Species occurrence records were unevenly spatially distributed. Both specimen and observation records were concentrated in regions of Norway with high human population density and with high temperatures and precipitation, but in different regions within Norway. Observation and specimen records thus differ in taxonomic, temporal, spatial and environmental coverage for a well-sampled group and study region, potentially influencing the ecological inferences made from studies utilizing species occurrence data. The distribution of observation data dominates the dataset, so inferences of species diversity and distributions do not correspond to the evolutionary or physiological knowledge of species, which is based on specimen data. We make recommendations for users of biodiversity data, and collectors to better exploit the complementary strengths of these distinct biodiversity data types.