• Canada
• 2013-2022close
• 2017 close

Variations in sea level have a great environmental impact. They modulate coastal deposition, erosion and morphology, regulate heat and salt fluxes in estuaries, bays and ground waters, and control the dynamics of coastal ecosystems. Sea level variability has importance for coastal navigation, the building of coastal infrastructure, and the management of waste. The challenges of measuring, understanding and predicting sea level variations take particular relevance within the backdrop of global sea level rise, which might lead to the displacement of hundreds of millions of people by the end of this century. Sea level measurement relies primarily on the use of coastal tide gauges and satellite altimetry. Tide gauges provide sea levels at fine time resolutions (up to one second), but collect data only in coastal areas, and are irregularly distributed, with large gaps in the southern hemisphere and at high latitudes. Satellite altimetry, in contrast, has poor time resolution (ten days or longer), but provides near global coverage at moderate spatial resolutions (10-to-100 kilometres). Altimetric sea level products are problematic near the coast for reasons such as uncertainties in applying sea state bias corrections, errors in coastal tidal models, and large geoid gradients. The complicated shoreline geometry means that the raw altimeter data have to either undergo special transformations to provide more reliable measurements of sea level or be rejected. Developments in GPS measurements from buoys are now making it possible to determine sea surface heights with accuracy comparable to that of altimetry. In combination with coastal tide gauges, GPS buoys could be used as the nodes of a global sea level monitoring network extending beyond the coast. However, GPS buoys have several downsides. They are difficult and expensive to deploy, maintain, and recover, and, like conventional tide gauges, provide time series only at individual points in the ocean. This proposal focuses on the development of a unique system that overcomes these shortcomings. We propose a technology-led project to integrate Global Navigation Satellite Systems (GNSS i.e. encompassing GPS, GLONASS and, possibly, Galileo) technology with a state-of-the-art, unmanned surface vehicle: a Wave Glider. The glider farms the ocean wave field for propulsion, uses solar power to run on board equipment, and uses satellite communications for remote navigation and data transmission. A Wave Glider equipped with a high-accuracy GNSS receiver and data logger is effectively a fully autonomous, mobile, floating tide gauge. Missions and routes can be preprogrammed as well as changed remotely. Because the glider can be launched and retrieved from land or from a small boat, the costs associated with deployment, maintenance and recovery of the GNSS Wave Glider are comparatively small. GNSS Wave Glider technology promises a level of versatility well beyond that of existing ways of measuring sea levels. Potential applications of a GNSS Wave Glider include: 1) measurement of mean sea level and monitoring of sea level variations worldwide, 2) linking of offshore and onshore vertical datums, 3) calibration of satellite altimetry, notably in support of current efforts to reinterpret existing altimetric data near the coast, but also in remote and difficult to access areas, 4) determination of regional geoid variations, 5) ocean model improvement. The main thrust of this project is to integrate a state-of-the-art, geodetic-grade GNSS receiver and logging system with a Wave Glider recently acquired by NOC to create a mobile and autonomous GNSS-based tide gauge. By the end of the project, a demonstrator GNSS Wave Glider will be available for use by NOC and the UK marine community. The system performance will be validated against tide gauge data. Further tests will involve the use of the GNSS Wave Glider to calibrate sea surface heights and significant wave heights from Cryosat-2.

Methane is a powerful long-lived greenhouse gas that is second only to carbon dioxide in its radiative forcing potential. Understanding the Earth's methane cycle at regional scales is a necessary step for evaluating the effectiveness of methane emission reduction schemes, detecting changes in biological sources and sinks of methane that are influenced by climate, and predicting and perhaps mitigating future methane emissions. The growth rate of atmospheric methane has slowed since the 1990s but it continues to show considerable year-to-year variability that cannot be adequately explained. Some of the variability is caused by the influence of weather on systems in which methane is produced biologically. When an anomalous increase in atmospheric methane is detected in the northern hemisphere that links to warm weather conditions, typically wetlands and peatlands are thought to be the cause. However, small lakes and ponds commonly are overlooked as potential major sources of methane emissions. Lakes historically have been regarded as minor emitters of methane because diffusive fluxes during summer months are negligible. This notion has persisted until recently even though measurements beginning in the 1990s have consistently shown that significant amounts of methane are emitted from northern lakes during spring and autumn. In the winter time the ice cover isolates lake water from the atmosphere and the water column become poor in oxygen and stratified. Methane production increases in bottom sediment and the gas spreads through the water column with some methane-rich bubbles rising upwards and becoming trapped in the ice cover as it thickens downward in late winter. In spring when the ice melts the gas is released. Through changes in temperature and the influence of wind the lake water column mixes and deeper accumulations of methane are lost to the atmosphere. In summer the water column stratifies again and methane accumulates once more in the bottom sediments. When the water column become thermally unstable in the autumn and eventually overturns the deep methane is once again released although a greater proportion of it appears to be consumed by bacteria in the autumn. Lakes differ in the chemistry of their water as well as the geometry of their basins. Thus it is difficult to be certain that all lakes will behave in this way but for many it seems likely. The proposed study will measure the build-up of methane in lakes during spring and autumn across a range of ecological zones in North America. The focus will be on spring build-up and emissions because that gas is the least likely to be influenced by methane-consuming bacteria. However, detailed measurements of methane emissions will also be made in the autumn at a subset of lakes. The measurements will then be scaled to a regional level using remote sensing data providing a 'bottom-up' estimate of spring and autumn methane fluxes. Those results will be compared to a 'top-down' estimate determined using a Met Office dispersion model that back-calculates the path of air masses for which the concentration of atmospheric methane has been measured at global monitoring stations in order to determine how much methane had to be added to the air during its passage through a region. Comparing estimates by these two approaches will provide independent assessments of the potential impact of seasonal methane fluxes from northern lakes. In addition measurements of the light and heavy versions of carbon and hydrogen atoms in methane (C, H) and water (H) will be measured to evaluate their potential use as tracer for uniquely identifying methane released by lakes at different latitudes. If successful the proposed study has the potential to yield a step-change in our perception of the methane cycle by demonstrating conclusively that a second major weather-sensitive source of biological methane contributes to year-to-year shifts in the growth rate of atmospheric methane.

The shift from hunting and gathering to an agricultural way of life was one of the most profound events in the history of our species and one which continues to impact our existence today. Understanding this process is key to understanding the origins and rise of human civilization. Despite decades of study, however, fundamental questions regarding why, where and how it occurred remain largely unanswered. Such a fundamental change in human existence could not have been possible without the domestication of selected animals and plants. The dog is crucial in this story since it was not only the first ever domestic animal, but also the only animal to be domesticated by hunter-gatherers several thousand years before the appearance of farmers. The bones and teeth of early domestic dogs and their wild wolf ancestors hold important clues to our understanding of how, where and when humans and wild animals began the relationship we still depend upon today. These remains have been recovered from as early as 15,000 years ago in numerous archaeological sites across Eurasia suggesting that dogs were either domesticated independently on several occasions across the Old World, or that dogs were domesticated just once and subsequently spreading with late Stone Age hunter gatherers across the Eurasian continent and into North America. There are also those who suggest that wolves were involved in an earlier, failed domestication experiment by Ice Age Palaeolithic hunters about 32,000 years ago. Despite the fact that we generally know the timing and locations of the domestication of all the other farmyard animals, we still know very little for certain about the origins of our most iconic domestic animal. New scientific techniques that include the combination of genetics and statistical analyses of the shapes of ancient bones and teeth are beginning to provide unique insights into the biology of the domestication process itself, as well as new ways of tracking the spread of humans and their domestic animals around the globe. By employing these techniques we will be able to observe the variation that existed in early wolf populations at different levels of biological organization, identify diagnostic signatures that pinpoint which ancestral wolf populations were involved in early dog domestication, reveal the shape (and possibly the genetic) signatures specifically linked to the domestication process and track those signatures through time and space. We have used this combined approach successfully in our previous research enabling us to definitively unravel the complex story of pig domestication in both Europe and the Far East. We have shown that pigs were domesticated multiple times and in multiple places across Eurasia, and the fine-scale resolution of the data we have generated has also allowed us to reveal the migration routes pigs took with early farmers across Europe and into the Pacific. By applying this successful research model to ancient dogs and wolves, we will gain much deeper insight into the fundamental questions that still surround the story of dog domestication.