By Julia K. Parrish, William M. Hamner
Colleges of fish, flocks of birds, and swarms of bugs are examples of three-d aggregation. masking either invertebrate and vertebrate species, the authors examine this pervasive organic phenomenon via quite a few disciplines, from physics to arithmetic to biology. the 1st part is dedicated to many of the tools, as a rule optical and acoustic, used to assemble three-d info through the years. the second one part makes a speciality of analytical tools used to quantify development, workforce kinetics, and interindividual interactions in the team. The part on behavioral ecology and evolution offers with the capabilities of aggregative habit from the perspective of an inherently egocentric person member. the ultimate part makes use of types to explain how workforce dynamics on the person point creates emergent development on the point of the gang.
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2. The system for measuring the three-dimension distribution of chlorophyll-a using fluorescence imaging. Depicted here is an experimental setup that consists of a light source and a camera. image is collected. This procedure is continued in sequence until a given volume is mapped out. A system of equations can be used to describe the forward model, which can then be inverted to determine the three-dimensional distribution of chlorophyll-a in a way similar to the optical serial microscopy mentioned above.
Osborn (Ch. 3) reviews optical triangulation methods extensively. g. g. fluorescence imaging). At present, these technologies have yet to be applied to track an individual, or group of individuals, as they move through space and time. An interesting result of my broad review of these many approaches to three-dimensional mensuration is that almost none of them meet our specific goal of simultaneous good resolution in both time and space. It is also clear that one of the problems in applying the above techniques to sensing individual animals and animal aggregations is the often prohibitive cost.
An additional complication occurs in sonar imaging that is not typically present in the light optical case. 5 mm @ 1 MHz), the reflection of sound can be considered equivalent to the superposition of a random distribution of time delayed wave forms. This leads to a special kind of multiplicative noise called speckle (Goodman 1986). For fully developed speckle, the SNR is 1. Clearly, this results in very noisy images. Jaffe (1991) has proposed an approximate classification of sonar imaging systems, relative to increasing complexity (Fig.
Animal Groups in Three Dimensions: How Species Aggregate by Julia K. Parrish, William M. Hamner