AG Micropaleontology - Paleoceanography

Metal and growth anomalies in foraminiferal shells as proxy for industrial pollution: a case study from the Eastern Mediterranean

Prof. Michal Kucera, Dr. Raphael Morard, Dr. Michael Siccha

1.4.2020 - 31.3.2024

The recent years have been witnessing a considerable growth of industrial facilities along the coastal areas of Israel. Some of these have major economical and national importance yet their operation can introduce a wide range of chemicals, such as heavy metals, that might contaminate the coastal area and impact local ecosystems and our health. Efforts to mitigate these effects and to establish more sustainable practices are contingent on the knowledge of baseline concentrations of potential pollutants and our ability to monitor their presence and biological impacts at small scales temporally and spatially, detecting their presence even at low concentrations, before they are damaging and considered as pollution. Direct monitoring of water chemistry is logistically difficult and analytically expensive and the response time of the ecosystem is often too long to observe concomitant reaction, especially where the pollutants are released intermittently. Instead, a biological system simultaneously recording pollution levels and biotic response through time is required. In this proposal, we suggest to use geochemical signatures and growth patterns of benthic foraminiferal shells as proxies for the footprint of the extent and the effects of heavy metal injection in marine environments. The shells of foraminifera grow by sequential addition of chambers, providing a temporally resolved record of pollution levels. This is because the shells are precipitated by a mechanism that involves direct seawater vacuolization and the heavy metal concentration in the precipitated mineral thus reflects the chemical composition of the ambient water. Under optimal conditions, the growth of foraminiferal shells is strictly geometrical, but stress induces irregularities, which are preserved in the pattern of chamber addition. Thus foraminifera act as “living data loggers”, recording simultaneously pollution levels and biotic response. Taken together with their high diversity and occurrence in all marine habitats, this makes them an ideal candidate for monitoring of historical and ongoing pollution and its impacts. In this study, we will explore this potential by identifying species most suitable for monitoring heavy metal concentrations and constraining how the recorded levels of pollution correlate with growth irregularity. We will combine field and laboratory experiments to calibrate metal concentrations in seawater and foraminiferal calcite and detect pollution levels affecting growth. The result of this study will be a broadly applicable and quantitatively calibrated recorder of heavy metal concentrations and their biotic impact in coastal waters, allowing reconstructions of pollution history and detection of short-term pollutant injections without the need for a costly continuous direct monitoring of water properties.

Microfossils and data science: a new approach to infer the impact of global climate on plankton macroecology

Dr. Flavia Boscolo-Galazzo

1.9.2022 - 31.8.2024

One of the most pressing scientific challenges today is understanding the fate of our oceans and marine ecosystems under on-going climate change. Unfortunately, anthropogenic stressors act at a rate and magnitude that exceed recent natural variability, making the use of decadal ecological data and time-series insufficient for predictions of future behavior of marine ecosystems. MICRO2MACRO will reconstruct snapshots of marine pelagic ecosystems between 54 and 32 million years ago (Eocene and early Oligocene), when climate and environmental conditions approximate what we will start to experience in the next century and beyond. Using the microfossil record of planktonic foraminifera (PF), the most complete of any Cenozoic eukaryote, the project will generate the first methodologically controlled (hence reproducible) early Cenozoic global dataset of ecology, abundance, species composition, diversity and biogeography (macroecology) of these prolific pelagic calcifiers. Benefiting from the mole of data generated over the last 15 years, I will apply novel tools in data-science technology to compile ocean temperature and chemistry datasets for the studied time intervals and compare them against the new PF dataset generated with this project. This study will combine the most advanced knowledge in several disciplines (micropaleontology, informatics, statistical ecology) to test for links between time-specific climate (eg, sea surface temperatures) and ecosystem (eg, species composition, dominant ecology) configurations, and understand how plankton biogeography was shaped in a warmer world. Hence, MICRO2MACRO will highlight future ecological and evolutionary analogues if the current climate trajectory remains interrupted and we are to hit climate conditions similar to those in the Eocene and Oligocene.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme Marie Sklodowska-Curie IF under grant agreement No 101019438

From the last Interglacial to the Anthropocene - Modeling a complete glacial cycle

Dr. Lukas Jonkers

1.10.2019 - 31.8.2026

The goal of the PALMOD project (palmod.de) is simulating a full glacial cycle in transient mode and with comprehensive Earth System Models (ESMs) which allow full interactions between the physical and biogeochemical components of the Earth system, including ice sheets. The ultimate aim is to assess possible future climate trajectories beyond this century during the next millennia with sophisticated ESMs that can realistically simulate both the climate trajectory and variability of the last glacial cycle.

Within this project we use the extensive marine and terrestrial paleoclimate syntheses to characterise the dynamics of climate change across the past 130,000 years as recorded by proxy records. The goal is to provide benchmarks for the transient simulations carried out during the previous and upcoming phases of PalMod and to derive constraints for future predictions that consider uncertainty in both the data and the models. The temporal focus is on the key time periods for which simulations are available: the glacial inception and termination and marine isotope stage 3. All three periods are characterised by abrupt climate change. However, the nature and cause of this variability remains poorly constrained, hindering evaluation of transient climate simulations.

These poor constraints are partly due to the inherently uncertain nature of paleodata that often restricts the hypotheses that data-data and model-data comparison studies can successfully address. Many of these uncertainties are multifactorial and difficult to quantify over large data compilations as they relate to the fabric of the samples themselves (e.g. sedimentation rate, bioturbation, preservation). In contrast to these intrinsic uncertainties, extrinsic errors, such as the dating (measurement and calibration) and reconstruction errors (modeling of modern proxy-climate relationships), can be more easily estimated. While these uncertainties were included in PalMod’s data compilations, and tools were developed to quantify these uncertainties, they have been often omitted in subsequent comparative studies. This work package aims to address and incorporate these uncertainties in several ways and whilst doing so lay the foundation to evaluate simulations in PalMod.

Furthermore, data-model comparison is often ambiguous as differences often cannot be clearly attributed to specific climatic processes. Uncertainty-based model-data comparisons across multiple parameters (temperature, isotopes) and including novel approaches (species ecology) could both reduce the effect of reconstruction uncertainty and identify the reasons for differences in spatio-temporal variability between reconstructions and simulations. A multi-parameter approach is best possible in marine archives, where multiple parameters are co-registered. Comparing multiple dimensions will shed light on processes responsible for mismatch also in cases where simulations or proxies show little difference along one parameter. This approach will allow us to identify robust results of climate models and assess the effect of coupling. The inclusion of the terrestrial data during the second half of this project will foster a more complete evaluation of the simulations and further our understanding of the land-ocean dynamics during periods of abrupt climate change.