Early modern nautical rutters (sailing directions) are the earliest Western documents that testify to the stable and regular lived experience of traversing the earth’s oceans on a global, planetary scale. Nautical rutters (and ship’s loogbooks) are technical documents that collect and analyse critical information for the successful accomplishment of oceanic navigation. This includes elements of strict nautical nature (courses, distances, and latitudes), as well as information on oceanography (currents and tides), meteorology (winds and storms), geography, geophysics (magnetic declination) and the natural world. Their unique value lies not only in the fact that they are exceptional historical repositories of information about the world on a planetary scale but, more importantly, that they document the emergence of global concepts about the earth. In fact, no earlier documents contain information about the earth on a comparable worldwide scale. Thus, their historical value is peerless. Using these exceptional, yet poorly known sources, the main objective of this project is to write a narrative of the scaling up of a scientific description of the earth in the sixteenth and seventeenth centuries, from the lived experience of travelling and observing the earth in long-distance sea voyages. As a preliminary task, a systematic search, identification and classification of the information contained in early modern Iberian rutters and ship’s logbooks will be performed. This will be followed by an extensive multidisciplinary study of their content aiming at radically improving our present knowledge of the historical process that led to the formation of global concepts about the earth.
Idea: CoralINT aims to deliver the ability to predict spatio-temporal change in biodiversity and the consequences of this change for ecosystem function. To achieve this aim, I will develop an Integrated Niche Theory linking three niche concepts: Grinnell’s niche (what a species needs), Elton’s niche (what a species does) and niche construction (how the species function changes the environment). The key to this integration lies in how species are sorted along each of the niche axes (environmental gradients, functional rates and niche construction rates). I will map the dynamic implications of different types of bivariate sorting to the development of positive and negative feedback loops. This new theory will allow predicting the indirect consequences of selection on one axis to change along the other two axes. I will test INT with environmental, compositional, and functional data extracted from 3D maps of coral reefs and its coral inhabitants. Ground breaking features: CoralINT sits at the interface between theory development and cutting-edge empirical data. I anticipate coralINT will produce 3D maps for a total area of >26,600 m2 with mm scale resolution, distributed among 100 sites along a 2,000 km latitudinal gradient. Within these maps we will follow >100,000 coral colonies through time, measuring and inferring structural and demographic rates across >200 species and environmental variation in space and time. Working at organismal and ecosystem scales will enable coralINT to develop mechanistic understanding of the processes connecting environmental, compositional and functional change. Objectives: develop a new Integrated Niche Theory; quantify the effects of the environment on corals’ distribution and functional rates; determine if function can be predicted from coral and reef structural traits; quantify the prevalence and evolutionary implications of coral niche construction. Feasibility:We have collected proof of concept data for each data type.
This is a project in Computational Complexity. The project aims to answer the following question: How hard is it to find a good algorithm for a given computational problem? This question can be asked in several different settings, depending on what one means by "algorithm" (what is the computational model?), "computational problem" (is it a decision problem? a search problem? a communication problem?), and by "good" (do we want an algorithm that uses little time? little memory? few logical gates?). This question has a deep connection with the problem of proving lower-bounds, and in almost every setting where the question has been answered, either the answer was discovered while attempting to prove lower-bounds, or obtaining the answer required the development of new lower-bound methods. It is also known that several variants of the above question are equivalent to fundamental open questions in cryptography, pseudorandomness, and learning theory. The goal of this project is to answer this question in various settings where the answer is unknown: in circuit complexity, communication complexity, data structures, and algebraic models of computation. For each of these settings, we will either provide explicit methods for finding efficient algorithms, or show that the problem of finding such efficient algorithms is NP-hard.