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Project Details | |
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Project DescriptionOver the last 600 ka, Earth’s climate is dominated by changes in the orbital geometry (eccentricity) causing glacial-interglacial cycles with a frequency of approximately 100 ka. These cycles are asymmetrical meaning long glacial periods are followed by rapid warmings. During these transitions – also referred to as deglaciations – the global climate is rapidly changing on a multi-millennial-scale which makes these time periods ideal to study potential adaptation to environmental change. Marine plankton are of fundamental importance when it comes to the understanding of the pace and impacts that climate change will have on this planet. There are not only several feedback mechanisms which highlight the ability of marine plankton to contribute to global climate, but marine plankton are also very good indicators for climate change itself. They often have short live cycles and show a high evolutionary divergence; thus, it appears that plankton dynamics may be tightly coupled to environmental change. Also, marine plankton – by its definition – is free floating, so environmental change might be recorded by plankton distribution changes and shifts in their geographical range. A basic goal of the present PhD project is to benefit from the vast amount of plankton assemblage data that have been published in environmental data archives such as PANGAEA and NCEI and to utilize these data to better understand the variability in natural time scales. In particular, this PhD project aims to spatially and temporarily investigate the rates of adaptation of marine plankton to environmental change. For that, assemblage as well as morphological data extracted from the fossil record will be analysed. | Duration:1.2.2019-31.01.2022 Problem statementUnderstanding the response of marine ecosystems to climate change requires knowledge of processes that operate over long time scales. Over the last decades, abundant data have been generated on the change in the composition of marine microplankton assemblages across the last deglaciation. These data were used to reconstruct various aspects of the ocean and climate system during this climatic upheaval; however, their potential to evaluate biotic response to climatic forcing has been rarely explored. Objective of first manuscriptYasuhara et al. (2020) showed a compositional shift (latitudinal diversity gradient - LDG) in planktonic foraminifera from low to mid latitudes during the last deglaciation by analysing global census data (ForCenS, MARGO). Since they only looked at two time slices (LGM, pre-industrial), they were not able to analyse the timing of this shift in more detail. However, they assume that this shift probably started after the onset of the postglacial warming around 15 ka ago. Here, we use a data set of planktonic foraminifera records (see description below) to analyse the timing and the nature of this transition.
Working Area North Atlantic Ocean Data setWe compiled records of plankton response to the last deglaciation covering the entire North Atlantic Ocean. The records comprise assemblage composition data of marine zooplankton (planktonic foraminifera; n = 25) and phytoplankton (coccolithophores and dinoflagellate cysts; n = 5 and 6, respectively) covering the last 24 ka with a resolution of at least 1 ka. The comparability of the data is ensured as follows: For all sites, which are included in the PALMOD 130k marine palaeoclimate data synthesis V1.0 (Jonkers et al., 2020), the provided revised age models are used. For all other sites, which are not included in this synthesis, the same approach was used to revise the published age models to ensure the comparability of all analysed sites.
References Jonkers, L., Cartapanis, O., Langner, M., McKay, N., Mulitza, S., Strack, A., & Kucera, M. (2020). Integrating palaeoclimate time series with rich metadata for uncertainty modelling: strategy and documentation of the PalMod 130k marine palaeoclimate data synthesis. Earth System Science Data, 12(2), 1053–1081. doi:10.5194/essd-12-1053-2020 Yasuhara, M., Wei, C.-L., Kucera, M., Costello, M. J., Tittensor, D. P., Kiessling, W., … Kubota, Y. (2020). Past and future decline of tropical pelagic biodiversity. Proceedings of the National Academy of Sciences, 117(23), 12891–12896. doi:10.1073/pnas.1916923117 |
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Preliminary results of first manuscript | |
| We used the records of the planktonic foraminifera data set to first determine the shape of the major compositional change in each record by principle components analyses. The mean global response of the plankton to the deglaciation was then evaluated by an Empirical Orthogonal Function (EOF) analysis of the main biotic trends across all sites. We find that the dominant response of the zooplankton consists of synchronous unidirectional shifts initiated between 16-17 ka BP, and progressing into the Holocene. When regressed on the global ocean temperature and CO2 trends, we can see a proportionate response to the forcing during the last glacial maximum, the deglaciation and the early Holocene. In contrast, the late Holocene is characterised by continued compositional change, which does not appear related to environmental forcing. We speculate that this decoupling indicates the existence of a multi-millennial delay in community change following the climatic forcing. |
Figure explanation: The different rows of this plot correspond to changes in different community metrics (1. richness, 2. gains, 3. losses) calculated for each individual site. The first column shows the data as density plots and the second column shows the same data as box plots separated by the specific plankton groups. The third column shows the change of the specific community metric in a geographical context. | Overview of site-specific community metrics of North Atlantic Ocean data set We calculated changes in community metrics (richness, gains and losses) for each record of the North Atlantic Ocean data set for the last 24 ka. This overview plot shows consistent change in the flora/fauna such as increasing number of species at mid latitudes and decreasing number at low latitudes. Furthermore, the change in species gains is most prominent at mid latitudes whereas most species losses during the last deglaciation occur at low latitudes. This change could reflect species moving, but could also imply formation of new communities (i.e. with different composition than found anywhere). Methods: Richness change: Species richness (# of species) for each sample at each site. The site-specific change is then calculated as the slope of the linear model. Gains/losses change: Species gains and losses (in percent) as the proportion of species either gained or lost relative to the total number of species observed across both time periods (always compared to the oldest sample in the record). Note: the species gains/losses take actual species identity into account, it’s not only the change in # of species. The site-specific change is then again calculated as the slope of the linear model. NOTE: A negative slope (red colour in geographical maps) in e.g. richness change means that the number of species increased from the LGM to recent times. It’s kind of counter-intuitive, but it’s because of the x-axis (time). However, for a better intelligibility, this can be easily changed. |
| Gridded Hovmoller plots for richness [# and %], Shannon and Inverse Simpson diversity expressed as residuals from LGM mean
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