Over the past 3.5 million years, there have been several intervals when climate conditions were warmer than during the preindustrial Holocene. Although past intervals of warming were forced differently than future anthropogenic change, such periods can provide insights into potential future climate impacts and ecosystem feedbacks, especially over centennial-to-millennial timescales that are often not covered by climate model simulations. Our observation-based synthesis of the understanding of past intervals with temperatures within the range of projected future warming suggests that there is a low risk of runaway greenhouse gas feedbacks for global warming of no more than 2 °C. However, substantial regional environmental impacts can occur. A global average warming of 1-2 °C with strong polar amplification has, in the past, been accompanied by significant shifts in climate zones and the spatial distribution of land and ocean ecosystems. Sustained warming at this level has also led to substantial reductions of the Greenland and Antarctic ice sheets, with sea-level increases of at least several metres on millennial timescales. Comparison of palaeo observations with climate model results suggests that, due to the lack of certain feedback processes, model-based climate projections may underestimate long-term warming in response to future radiative forcing by as much as a factor of two, and thus may also underestimate centennial-to-millennial-scale sea-level rise.

Abstract. Shell fluxes of planktonic Foraminifera species vary intra-annually in a pattern that appears to follow the seasonal cycle. However, the variation in the timing and prominence of seasonal flux maxima in space and among species remains poorly constrained. Thus, although changing seasonality may result in a flux-weighted temperature offset of more than 5° C within a species, this effect is often ignored in the interpretation of Foraminifera-based paleoceanographic records. To address this issue we present an analysis of the intra-annual pattern of shell flux variability in 37 globally distributed time series. The existence of a seasonal component in flux variability was objectively characterised using periodic regression. This analysis yielded estimates of the number, timing and prominence of seasonal flux maxima. Over 80% of the flux series across all species showed a statistically significant periodic component, indicating that a considerable part of the intra-annual flux variability is predictable. Temperature appears to be a powerful predictor of flux seasonality, but its effect differs among species. Three different modes of seasonality are distinguishable. Tropical and subtropical species (Globigerinoides ruber (white and pink varieties), Neogloboquadrina dutertrei, Globigerinoides sacculifer, Orbulina universa, Globigerinella siphonifera, Pulleniatina obliquiloculata, Globorotalia menardii, Globoturborotalita rubescens, Globoturborotalita tenella and Globigerinoides conglobatus) appear to have a less predictable flux pattern, with random peak timing in warm waters. In colder waters, seasonality is more prevalent: peak fluxes occur shortly after summer temperature maxima and peak prominence increases. This tendency is stronger in species with a narrower temperature range, implying that warm-adapted species find it increasingly difficult to reproduce outside their optimum temperature range and that, with decreasing mean temperature, their flux is progressively more focussed in the warm season. The second group includes the temperate to cold-water species Globigerina bulloides, Globigerinita glutinata, Turborotalita quinqueloba, Neogloboquadrina incompta, Neogloboquadrina pachyderma, Globorotalia scitula, Globigerinella calida, Globigerina falconensis, Globorotalia theyeri and Globigerinita uvula. These species show a highly predictable seasonal pattern, with one to two peaks a year, which occur earlier in warmer waters. Peak prominence in this group is independent of temperature. The earlier-when-warmer pattern in this group is related to the timing of productivity maxima. Finally, the deep-dwelling Globorotalia truncatulinoides and Globorotalia inflata show a regular and pronounced peak in winter and spring. The remarkably low flux outside the main pulse may indicate a long reproductive cycle of these species. Overall, our analysis indicates that the seasonality of planktonic Foraminifera shell flux is predictable and reveals the existence of distinct modes of phenology among species. We evaluate the effect of changing seasonality on paleoceanographic reconstructions and find that, irrespective of the seasonality mode, the actual magnitude of environmental change will be underestimated. The observed constraints on flux seasonality can serve as the basis for predictive modelling of flux pattern. As long as the diversity of species seasonality is accounted for in such models, the results can be used to improve reconstructions of the magnitude of environmental change in paleoceanographic records.

To understand ecosystem responses to anthropogenic global change, a prevailing framework is the definition of threshold levels of pressure, above which response magnitudes and their variances increase disproportionately. However, we lack systematic quantitative evidence as to whether empirical data allow definition of such thresholds. Here, we summarize 36 meta-analyses measuring more than 4,600 global change impacts on natural communities. We find that threshold transgressions were rarely detectable, either within or across meta-analyses. Instead, ecological responses were characterized mostly by progressively increasing magnitude and variance when pressure increased. Sensitivity analyses with modelled data revealed that minor variances in the response are sufficient to preclude the detection of thresholds from data, even if they are present. The simulations reinforced our contention that global change biology needs to abandon the general expectation that system properties allow defining thresholds as a way to manage nature under global change. Rather, highly variable responses, even under weak pressures, suggest that 'safe-operating spaces' are unlikely to be quantifiable.

The high sequence divergence within the small subunit ribosomal RNA gene (SSU rDNA) of foraminifera makes it difficult to establish the homology of individual nucleotides across taxa. Alignment-based approaches so far relied on time-consuming manual alignments and discarded up to 50% of the sequenced nucleotides prior to phylogenetic inference. Here, we investigate the potential of the multiple analysis approach to infer a molecular phylogeny of all modern planktonic foraminiferal taxa by using a matrix of 146 new and 153 previously published SSU rDNA sequences. Our multiple analysis approach is based on eleven different automated alignments, analysed separately under the maximum likelihood criterion. The high degree of congruence between the phylogenies derived from our novel approach, traditional manually homologized culled alignments and the fossil record indicates that poorly resolved nucleotide homology does not represent the most significant obstacle when exploring the phylogenetic structure of the SSU rDNA in planktonic foraminifera. We show that approaches designed to extract phylogenetically valuable signals from complete sequences show more promise to resolve the backbone of the planktonic foraminifer tree than attempts to establish strictly homologous base calls in a manual alignment.