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Tim Ellis

Publications and source records attributed to Tim Ellis.

3 recordsLinked to original sources

Measurement of fish steroids in water--a review.

Measurement of fish steroids in water provides a non-invasive alternative to measurement in blood samples, offering the following advantages: zero or minimal intervention (i.e. no anaesthetic, bleeding or handling stress); results not being biased by sampling stress; repeat measurements on the same fish; the possibility of making non-lethal measurements on small and/or rare fish; integrating the response of many (or of single) fish; and allowing concurrent monitoring of behaviour or physiology. The procedure is relatively new and, although applications are still fairly limited, there are several themes and potential problem areas that are worthy of review.

Animals↗

Atmospheric nitrogen deposition promotes carbon loss from peat bogs.

Peat bogs have historically represented exceptional carbon (C) sinks because of their extremely low decomposition rates and consequent accumulation of plant remnants as peat. Among the factors favoring that peat accumulation, a major role is played by the chemical quality of plant litter itself, which is poor in nutrients and characterized by polyphenols with a strong inhibitory effect on microbial breakdown. Because bogs receive their nutrient supply solely from atmospheric deposition, the global increase of atmospheric nitrogen (N) inputs as a consequence of human activities could potentially alter the litter chemistry with important, but still unknown, effects on their C balance. Here we present data showing the decomposition rates of recently formed litter peat samples collected in nine European countries under a natural gradient of atmospheric N deposition from approximately 0.2 to 2 g.m(-2).yr(-1). We found that enhanced decomposition rates for material accumulated under higher atmospheric N supplies resulted in higher carbon dioxide (CO2) emissions and dissolved organic carbon release. The increased N availability favored microbial decomposition (i) by removing N constraints on microbial metabolism and (ii) through a chemical amelioration of litter peat quality with a positive feedback on microbial enzymatic activity. Although some uncertainty remains about whether decay-resistant Sphagnum will continue to dominate litter peat, our data indicate that, even without such changes, increased N deposition poses a serious risk to our valuable peatland C sinks.

Atmosphere↗

Learning semantic scene models from observing activity in visual surveillance.

This paper considers the problem of automatically learning an activity-based semantic scene model from a stream of video data. A scene model is proposed that labels regions according to an identifiable activity in each region, such as entry/exit zones, junctions, paths, and stop zones. We present several unsupervised methods that learn these scene elements and present results that show the efficiency of our approach. Finally, we describe how the models can be used to support the interpretation of moving objects in a visual surveillance environment.

Algorithms↗