that the goals of a deep drilling project can be reached. Meticulous preparation, including the collection of site-specific information from pilot studies may serve to construct a strategy for collecting primary and secondary data that can then be evaluated against scientific objectives, budget, logistic requirements, and the available time. Accurate subsampling and data interpretation requires a full tracking record of the core. Moreover, sediment subsampling should be coordinated and samples should, whenever possible, be taken from the same sample depth to aid data integration. Data analyses should be hierarchically structured. As studies from long records are very laborious and time-consuming, the first target should be to produce low/medium resolution data. Only then, high-resolution analyses are to be conducted. Though many new methods and analyses (e.g., analysis of isotopes in organic materials, high throughput image analyses and high throughput DNA sequencing, low-concentration biomarker analyses, studies of ancient amino acids and ancient DNA, molecular dating) are of high potential for integrating diverse datasets, their weaknesses in terms of resolution, quality of data, and practicability have to be considered. Whereas the physical linkage of primary information obtained from sediment cores is, in most cases, straightforward due to the chronological constraints on the data, integrating secondary data and/or interpretations into a consistent representation of the natural history of ancient lakes remains challenging. Moreover, in most previous deep drilling projects, geological and biological data were linked empirically. However, recent statistical developments enable a better mathematical integration of diverse of datasets and the testing of hypotheses based on specific null models. For future deep drilling campaigns we expect to see more explicit attempts to statistically link geological and biological histories aided by methodological advances in data generation (e.g., automated methods of fossil retrieval, visualization and identification) and data analyses (e.g., a better integration of uncertainties in age-depth calculations). Interdisciplinary projects should integrate earth and life scientists, statisticians, and modelers in the planning phase, to establish clear communication strategies, to align interests, and to discuss
that the goals of a deep drilling project can be reached. Meticulous preparation, including the collection of site-specific information from pilot studies may serve to construct a strategy for collecting primary and secondary data that can then be evaluated against scientific objectives, budget, logistic requirements, and the available time. Accurate subsampling and data interpretation requires a full tracking record of the core. Moreover, sediment subsampling should be coordinated and samples should, whenever possible, be taken from the same sample depth to aid data integration. Data analyses should be hierarchically structured. As studies from long records are very laborious and time-consuming, the first target should be to produce low/medium resolution data. Only then, high-resolution analyses are to be conducted. Though many new methods and analyses (e.g., analysis of isotopes in organic materials, high throughput image analyses and high throughput DNA sequencing, low-concentration biomarker analyses, studies of ancient amino acids and ancient DNA, molecular dating) are of high potential for integrating diverse datasets, their weaknesses in terms of resolution, quality of data, and practicability have to be considered. Whereas the physical linkage of primary information obtained from sediment cores is, in most cases, straightforward due to the chronological constraints on the data, integrating secondary data and/or interpretations into a consistent representation of the natural history of ancient lakes remains challenging. Moreover, in most previous deep drilling projects, geological and biological data were linked empirically. However, recent statistical developments enable a better mathematical integration of diverse of datasets and the testing of hypotheses based on specific null models. For future deep drilling campaigns we expect to see more explicit attempts to statistically link geological and biological histories aided by methodological advances in data generation (e.g., automated methods of fossil retrieval, visualization and identification) and data analyses (e.g., a better integration of uncertainties in age-depth calculations). Interdisciplinary projects should integrate earth and life scientists, statisticians, and modelers in the planning phase, to establish clear communication strategies, to align interests, and to discuss
Author_accepted_manuscript_Wilke_GPC.docx