Nutrient compensatory foraging in a free-living social insect

The geometric framework model predicts that animal foraging decisions are influenced by their dietary history, with animals targeting a combination of essential nutrients through compensatory foraging. We provide experimental confirmation of nutrient-specific compensatory foraging in a natural, free-living population of social insects by supplementing their diet with sources of protein- or carbohydrate-rich food. Colonies of the ant Iridomyrmex suchieri were provided with feeders containing food rich in either carbohydrate or protein for 6 days, and were then provided with a feeder containing the same or different diet. The patterns of recruitment were consistent with the geometric framework: while feeders with a carbohydrate diet typically attracted more workers than did feeders with protein diet, the difference in recruitment between the two nutrients was smaller if the colonies had had prior access to carbohydrate than protein. Further, fewer ants visited feeders if the colony had had prior access to protein than to carbohydrates, suggesting that the larvae play a role in worker foraging behaviour.     

Efficient Delineation of Nested Depression Hierarchy in Digital Elevation Models for Hydrological Analysis Using Level‐Set Method

In terrain analysis and hydrological modeling, surface depressions (or sinks) in a digital elevation model (DEM) are commonly treated as artifacts and thus filled and removed to create a depressionless DEM. Various algorithms have been developed to identify and fill depressions in DEMs during the past decades. However, few studies have attempted to delineate and quantify the nested hierarchy of actual depressions, which can provide crucial information for characterizing surface hydrologic connectivity and simulating the fill‐merge‐spill hydrological process. In this paper, we present an innovative and efficient algorithm for delineating and quantifying nested depressions in DEMs using the level‐set method based on graph theory. The proposed level‐set method emulates water level decreasing from the spill point along the depression boundary to the lowest point at the bottom of a depression. By tracing the dynamic topological changes (i.e., depression splitting/merging) within a compound depression, the level‐set method can construct topological graphs and derive geometric properties of the nested depressions. The experimental results of two fine‐resolution Light Detection and Ranging‐derived DEMs show that the raster‐based level‐set algorithm is much more efficient (~150 times faster) than the vector‐based contour tree method. The proposed level‐set algorithm has great potential for being applied to large‐scale ecohydrological analysis and watershed modeling.     

Testing the importance of accurate meteorological input fields and parameterizations in atmospheric transport modelling using dream - validation against ETEX-1

A tracer model, the DREAM, which is based on a combination of a near-range Lagrangian model and a long-range Eulerian model, has been developed. The meteorological meso-scale model, MM5V1, is implemented as a meteorological driver for the tracer model. The model system is used for studying transport and dispersion of air pollutants caused by a single but strong source as, e.g. an accidental release from a nuclear power plant. The model system including the coupling of the Lagrangian model with the Eulerian model are described. Various simple and comprehensive parameterizations of the mixing height, the vertical dispersion, and different meterological input data have been implemented in the combined tracer model, and the model results have been validated against measurements from the ETEX-1 release. Several different statistical parameters have been used to estimate the differences between the parameterizations and meterological input data in order to find the best performing solution.