Quiz 17: Species Interactions and Community Structure
Kirk Winemiller described the feeding relationships between the species of fresh water. The food web gave a very complex structure. As a measure to reduce the complexity of the food web, he included the strong tropic links and thereby excluded the weakest tropic links from the structure. The criteria by which he determined whether a link is weak or strong are on the base of the percentage of consumption. If a species on a higher tropic level consumed less than 1% of the diet species, then it was considered as a weak interaction and thus, excluded from the web. However, still the webs gave a very complex appearance. Robert Paine was another ecologist who studied the food web relationships of various ecosystems. He suggested that some species have a very strong influence on the community. The interaction by such species was considered as the strong interactions. He also suggested that the identification of strong interactions in a food web or a community by any ecologist would enable them to understand the effect and influence of the species on the community. More precisely, the elimination or alteration of a strong link would lead to more significant effects on any community than the elimination of the weaker interactions. Paine's criteria for determination of a "strong link" were as follows: • Degree of influence of a link on the community. • Quantity of energy flow. The criteria for determination of the "strong link" by Paine differed from that of Winemiller because Winemiller only determined the "strong interaction" on base of energy flow. Winemiller determined the energy flow by on base of the percentage of diet being consumed. On the other hand, Paine considered the effect of a species on the community and energy flow for determination of a "strong link".
Two given populations can be called statistically different if their confidence level does not overlap. If the confidence levels of any two populations overlap, it shows that they would not be statistically very different. Thus, it can be concluded that the statistical difference of any two populations depends on the confidence intervals. The confidence interval for a true population µ can be calculated by the following formula: Where, = True population mean = Sample mean = Standard Error t = Value of students t The standard error can be calculated the following formula: Where, = standard Error s = Sample Standard Deviation n = Sample Size Thus, we see that if the sample size would be larger, the standard error would be lesser. Standard error is directly proportional to the confidence interval. More the standard error, larger would be the confidence interval and smaller the standard error, smaller would be the confidence interval. The smaller confidence intervals lead to a larger statistical difference between populations as the chances of their over lap of 95% is very less. Hence, larger sample size reduces the standard error that in turn limits the size of confidence interval there by increasing the chances to detect more statistical differences between populations.
A keystone species is the species that has an influence of a high proportion on any community. The influence is relative to the abundance of that species. Some of the specific influences of a key stone species can be as follows: • It may control the population of one or more species. • It may reduce some invader species from affecting the community. • Its removal may drastically affect the population of the other species of the community. • Removal of key stone species would severely reduce the diversity of the community. One classic example of key stone species is the sea star, Pisaster in the intertidal community of Mukkaw Bay. Paine conducted experiments on two different communities and two different species of sea star, in his research work on key stone species. One of the study sites was intertidal zone of Mukkaw Bay in North America. Another study site was intertidal zone in the west coast of New Zealand. The similarities between these two study sites were as follows: • Both the intertidal zones comprised for rocky shores. • The top predator in both the communities was sea star. • The invertebrates involved in both the studies were sea stars, limpets, barnacles, chitons, and mussels. The differences between these two communities were as follows: • The top level predator or the keystone species in Mukkaw Bay was Pisaster whereas that in New Zealand west coast was Stichaster. • The most prominent competitors for space in Mukkaw Bay were the mussel Mytilus californianus and Pollicipes polymerus. On the other hand, the most dominant competitor for space in the west coast study area of New Zealand was Durvillea Antarctica. • The mussels in the Mukkaw Bay did not face any strong competition from algal species; whereas, in the west coast of New Zealand, the mussels had to face the challenge of competition with algal species for space Paine conducted the experiments in both the study areas to understand the role and effect of keystone species in the respective communities. But there were significant differences in the experimental design. These differences were as follows: • In the first experiment Paine removed only a single species ( Pisaster) that is the key stone species from the study plot. • On contrary, from the second study plot he removed two species. One was the keystone species (Stichaster) and other was the strong competitor of space that was brown algae. • The competitive exclusion was given more importance in the second experiment. As the design of the experiments was different, the results obtained were also drastically different. The first study site showed a dominance of the two species of mussel ( M. californianus ) and gooseneck ( P. polymerus ); they competitively excluded many species from the community as, the requirement of space was the main constraint. The second study site showed the dominance of mussel ( Perna ), and it excluded nearly all the flora and fauna. However, both the studies showed a substantial support in favour of the keystone species hypothesis; that states that key stone species increases species diversity.
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