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The SISAL database
(2018)
Stable isotope records from speleothems provide information on past climate changes, most particularly information that can be used to reconstruct past changes in precipitation and atmospheric circulation. These records are increasingly being used to provide "out-of-sample" evaluations of isotope-enabled climate models. SISAL (Speleothem Isotope Synthesis and Analysis) is an international working group of the Past Global Changes (PAGES) project. The working group aims to provide a comprehensive compilation of speleothem isotope records for climate reconstruction and model evaluation. The SISAL database contains data for individual speleothems, grouped by cave system. Stable isotopes of oxygen and carbon (delta O-18, delta C-13) measurements are referenced by distance from the top or bottom of the speleothem. Additional tables provide information on dating, including information on the dates used to construct the original age model and sufficient information to assess the quality of each data set and to erect a standardized chronology across different speleothems. The metadata table provides location information, information on the full range of measurements carried out on each speleothem and information on the cave system that is relevant to the interpretation of the records, as well as citations for both publications and archived data.
Although quantitative isotope data from speleothems has been used to evaluate isotope-enabled model simulations, currently no consensus exists regarding the most appropriate methodology through which to achieve this. A number of modelling groups will be running isotope-enabled palaeoclimate simulations in the framework of the Coupled Model Intercomparison Project Phase 6, so it is timely to evaluate different approaches to using the speleothem data for data–model comparisons. Here, we illustrate this using 456 globally distributed speleothem δ18O records from an updated version of the Speleothem Isotopes Synthesis and Analysis (SISAL) database and palaeoclimate simulations generated using the ECHAM5-wiso isotope-enabled atmospheric circulation model. We show that the SISAL records reproduce the first-order spatial patterns of isotopic variability in the modern day, strongly supporting the application of this dataset for evaluating model-derived isotope variability into the past. However, the discontinuous nature of many speleothem records complicates the process of procuring large numbers of records if data–model comparisons are made using the traditional approach of comparing anomalies between a control period and a given palaeoclimate experiment. To circumvent this issue, we illustrate techniques through which the absolute isotope values during any time period could be used for model evaluation. Specifically, we show that speleothem isotope records allow an assessment of a model's ability to simulate spatial isotopic trends. Our analyses provide a protocol for using speleothem isotope data for model evaluation, including screening the observations to take into account the impact of speleothem mineralogy on δ18O values, the optimum period for the modern observational baseline and the selection of an appropriate time window for creating means of the isotope data for palaeo-time-slices.
Environmental monitoring involves the quantification of microscopic cells and particles such as algae, plant cells, pollen, or fungal spores. Traditional methods using conventional microscopy require expert knowledge, are time-intensive and not well-suited for automated high throughput. Multispectral imaging flow cytometry (MIFC) allows measurement of up to 5000 particles per second from a fluid suspension and can simultaneously capture up to 12 images of every single particle for brightfield and different spectral ranges, with up to 60x magnification. The high throughput of MIFC has high potential for increasing the amount and accuracy of environmental monitoring, such as for plant-pollinator interactions, fossil samples, air, water or food quality that currently rely on manual microscopic methods. Automated recognition of particles and cells is also possible, when MIFC is combined with deep-learning computational techniques. Furthermore, various fluorescence dyes can be used to stain specific parts of the cell to highlight physiological and chemical features including: vitality of pollen or algae, allergen content of individual pollen, surface chemical composition (carbohydrate coating) of cells, DNA- or enzyme-activity staining. Here, we outline the great potential for MIFC in environmental research for a variety of research fields and focal organisms. In addition, we provide best practice recommendations.