Characterization of extrasolar terrestrial planets from diurnal photometric variability

The detection of massive planets orbiting nearby stars has become almost routine, but current techniques are as yet unable to detect terrestrial planets with masses comparable to the Earth's. Future space-based observatories to detect Earth-like planets are being planned. Terrestrial planets orbiting in the habitable zones of stars-where planetary surface conditions are compatible with the presence of liquid water-are of enormous interest because they might have global environments similar to Earth's and even harbor life. The light scattered by such a planet will vary in intensity and colour as the planet rotates; the resulting light curve will contain information about the planet's properties. Here we report a model that predicts features that should be discernible in light curves obtained by low-precision photometry. For extrasolar planets similar to Earth we expect daily flux variations up to hundreds of percent, depending sensitively on ice and cloud cover. Qualitative changes in surface or climate generate significant changes in the predicted light curves. This work suggests that the meteorological variability and the rotation period of an Earth-like planet could be derived from photometric observations. Other properties such as the composition of the surface (e.g., ocean versus land fraction), climate indicators (for example ice and cloud cover), and perhaps even signatures of Earth-like plant life could be constrained or possibly, with further study, even uniquely determined.Comment: Published in Nature. 9 pages including 3 figure

Colorful Niches of Phytoplankton Shaped by the Spatial Connectivity in a Large River Ecosystem: A Riverscape Perspective

Large rivers represent a significant component of inland waters and are considered sentinels and integrators of terrestrial and atmospheric processes. They represent hotspots for the transport and processing of organic and inorganic material from the surrounding landscape, which ultimately impacts the bio-optical properties and food webs of the rivers. In large rivers, hydraulic connectivity operates as a major forcing variable to structure the functioning of the riverscape, and–despite increasing interest in large-river studies–riverscape structural properties, such as the underwater spectral regime, and their impact on autotrophic ecological processes remain poorly studied. Here we used the St. Lawrence River to identify the mechanisms structuring the underwater spectral environment and their consequences on pico- and nanophytoplankton communities, which are good biological tracers of environmental changes. Our results, obtained from a 450 km sampling transect, demonstrate that tributaries exert a profound impact on the receiving river’s photosynthetic potential. This occurs mainly through injection of chromophoric dissolved organic matter (CDOM) and non-algal material (tripton). CDOM and tripton in the water column selectively absorbed wavelengths in a gradient from blue to red, and the resulting underwater light climate was in turn a strong driver of the phytoplankton community structure (prokaryote/eukaryote relative and absolute abundances) at scales of many kilometers from the tributary confluence. Our results conclusively demonstrate the proximal impact of watershed properties on underwater spectral composition in a highly dynamic river environment characterized by unique structuring properties such as high directional connectivity, numerous sources and forms of carbon, and a rapidly varying hydrodynamic regime. We surmise that the underwater spectral composition represents a key integrating and structural property of large, heterogeneous river ecosystems and a promising tool to study autotrophic functional properties. It confirms the usefulness of using the riverscape approach to study large-river ecosystems and initiate comparison along latitudinal gradients

Advances in remote sensing of great lakes algal blooms

Many regions of the Great Lakes now see recurring cyanobacterial harmful algal blooms (cyanoHABs), with documented repercussions for ecosystem services, public health, and ecosystem integrity. Early detection and comprehensive monitoring of cyanoHABs are fundamental to their effective management and mitigation of detrimental impacts. Satellite remote sensing has provided the means by which algal blooms in the Great Lakes can be observed with unprecedented frequency and spatial coverage. Algorithms have been developed and validated; fully automated data processing streams have been rendered operational; and stakeholders have been engaged in order to develop user-friendly end products. Such products have been integral in providing near-real-time monitoring of bloom conditions, documenting spatiotemporal trends, improving understanding of environmental drivers of blooms, and guiding nutrient management actions. In this chapter we present background information on remote sensing of algal blooms, document the current state of knowledge with a focus on Lake Erie, and discuss remote sensing products available to the Great Lakes community