Diverging trends and drivers of Arctic flower production in Greenland over space and time

The Arctic is warming at an alarming rate. While changes in plant community composition and phenology have been extensively reported, the effects of climate change on reproduction remain poorly understood. We quantified multidecadal changes in flower density for nine tundra plant species at a low- and a high-Arctic site in Greenland. We found substantial changes in flower density over time, but the temporal trends and drivers of flower density differed both between species and sites. Total flower density increased over time at the low-Arctic site, whereas the high-Arctic site showed no directional change. Within and between sites, the direction and rate of change differed among species, with varying effects of summer temperature, the temperature of the previous autumn and the timing of snowmelt. Finally, all species showed a strong trade-off in flower densities between successive years, suggesting an effective cost of reproduction. Overall, our results reveal region- and taxon-specific variation in the sensitivity and responses of co-occurring species to shared climatic drivers, and a clear cost of reproductive investment among Arctic plants. The ultimate effects of further changes in climate may thus be decoupled between species and across space, with critical knock-on effects on plant species dynamics, food web structure and overall ecosystem functioning

Outlier SNPs detect weak regional structure against a background of genetic homogeneity in the Eastern Rock Lobster, Sagmariasus verreauxi

Genetic differentiation is characteristically weak in marine species making assessments of population connectivity and structure difficult. However, the advent of genomic methods has increased genetic resolution, enabling studies to detect weak, but significant population differentiation within marine species. With an increasing number of studies employing high resolution genome-wide techniques, we are realising that the connectivity of marine populations is often complex and quantifying this complexity can provide an understanding of the processes shaping marine species genetic structure and to inform long-term, sustainable management strategies. This study aims to assess the genetic structure, connectivity, and local adaptation of the Eastern Rock Lobster (Sagmariasus verreauxi), which has a maximum pelagic larval duration of 12 months and inhabits both subtropical and temperate environments. We used 645 neutral and 15 outlier SNPs to genotype lobsters collected from the only two known breeding populations and a third episodic population—encompassing S. verreauxi's known range. Through examination of the neutral SNP panel, we detected genetic homogeneity across the three regions, which extended across the Tasman Sea encompassing both Australian and New Zealand populations. We discuss differences in neutral genetic signature of S. verreauxi and a closely related, co-distributed rock lobster, Jasus edwardsii, determining a regional pattern of genetic disparity between the species, which have largely similar life histories. Examination of the outlier SNP panel detected weak genetic differentiation between the three regions. Outlier SNPs showed promise in assigning individuals to their sampling origin and may prove useful as a management tool for species exhibiting genetic homogeneity

Understanding 'it depends' in ecology : a guide to hypothesising, visualising and interpreting statistical interactions

Ecologists routinely use statistical models to detect and explain interactions among ecological drivers, with a goal to evaluate whether an effect of interest changes in sign or magnitude in different contexts. Two fundamental properties of interactions are often overlooked during the process of hypothesising, visualising and interpreting interactions between drivers: the measurement scale - whether a response is analysed on an additive or multiplicative scale, such as a ratio or logarithmic scale; and the symmetry - whether dependencies are considered in both directions. Overlooking these properties can lead to one or more of three inferential errors: misinterpretation of (i) the detection and magnitude (Type-D error), and (ii) the sign of effect modification (Type-S error); and (iii) misidentification of the underlying processes (Type-A error). We illustrate each of these errors with a broad range of ecological questions applied to empirical and simulated data sets. We demonstrate how meta-analysis, a widely used approach that seeks explicitly to characterise context dependence, is especially prone to all three errors. Based on these insights, we propose guidelines to improve hypothesis generation, testing, visualisation and interpretation of interactions in ecology.Peer reviewe

Climate change reshuffles northern species within their niches

Climate change is a pervasive threat to biodiversity. While range shifts are a known consequence of climate warming contributing to regional community change, less is known about how species' positions shift within their climatic niches. Furthermore, whether the relative importance of different climatic variables prompting such shifts varies with changing climate remains unclear. Here we analysed four decades of data for 1,478 species of birds, mammals, butterflies, moths, plants and phytoplankton along a 1,200 km high latitudinal gradient. The relative importance of climatic drivers varied non-uniformly with progressing climate change. While species turnover among decades was limited, the relative position of species within their climatic niche shifted substantially. A greater proportion of species responded to climatic change at higher latitudes, where changes were stronger. These diverging climate imprints restructure a full biome, making it difficult to generalize biodiversity responses and raising concerns about ecosystem integrity in the face of accelerating climate change.The authors analyse four decades of distribution data for various taxonomic groups to understand the shift of species within their climatic niches and the changing influences of different climate factors. The diverse and diverging climate imprints raise concerns about future ecosystem integrity

BioTIME:a database of biodiversity time series for the Anthropocene

Abstract Motivation: The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community‐led open‐source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene. Main types of variables included: The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record. Spatial location and grain: BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km² (158 cm²) to 100 km² (1,000,000,000,000 cm²). Time period and grain: BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year. Major taxa and level of measurement: BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates. Software format: .csv and .SQL