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The Ecology of "Crowding"

Authors: Albert O. Bush; Albert O. Bush; Jeffrey M. Lotz;

The Ecology of "Crowding"

Abstract

There are 2 elements that make ‘‘crowding’’ interesting— mechanism (causality) and manifestation (effect). In our companion paper, Larry Roberts addresses mechanisms. Here, we focus on manifestation. As ecologists, it is difficult to get too excited about Clark Read’s paper on the ‘‘crowding effect’’ in cestodes, at least initially. The paper acknowledges clearly that the phenomenon has been observed repeatedly, is mostly a discussion of appropriate techniques, and concludes with a brief overture to causality. Recalling a popular television commercial from several years ago, ‘‘Where’s the beef?’’ The answer lies in the implication of crowding. Simply stated, crowding means too many of something. In the case of worms in the gut of a host, it is obvious that there exists a finite number of individuals that can physically fit into a gut. Crowding is a common phenomenon, certainly not restricted to tapeworms in the small intestine of a rat. It is very, very common in managed systems where the intent is to get the ‘‘biggest bang for the buck.’’ For example, gardeners know that too many plants in a prescribed area will result in a poor crop; so too do aquaculturists raising fishes, crustaceans, or shellfish. Under such artificial conditions, the remedy for alleviating crowding is simple, at least in theory. Either reduce (thin) the target population or artificially enhance the environment. The latter may be accomplished by supplemental feeding, removing toxic wastes, and so forth. Trivial observations perhaps but ‘‘crowding’’ is overwhelmingly common, at least where humans have intervened. But, what of the ecology of crowding in a natural context? We consider crowding as being important ecologically in 2 contexts—first as it relates to predator–prey relationships and second as it relates to the much-maligned idea of competition. In a food web, crowding will always impact most severely on the prey population. If there are too many predators, e.g., the predators are crowded, more prey will be taken simply because there are more things to eat them. Similarly, if there are too many prey, predators will find and, perhaps, capture them more easily. However, our focus here is not on predator–prey relationships, rather it is on crowding as it might relate to parasites in a host. At the time Clark Read’s paper was published, ecology was more qualitative natural history than the quantitative science we know today. If predator–prey interactions could not account for the observed patterns on the distribution and abundance of organisms, then surely the answer must lie in competition. It is perhaps for that reason, that competition was apparently so pervasive that Read ignored manifestation in his paper. Why emphasize what was so readily obvious? Basically, competition takes 2 forms: interference and exploitation. With interference competition, organisms may impact on others in a direct fashion, for example, releasing toxins.

Country
United States
Keywords

Life Sciences, Animals, Cestoda, Marine Biology, History, 20th Century, Cestode Infections, Host-Parasite Interactions

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    citations
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    37
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    Average
    influence
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    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
37
Average
Top 10%
Top 10%
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