Downloads provided by UsageCounts
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>AbstractTheories suggest that food webs might consist of groups of species forming ‘blocks’, ‘compartments’ or ‘guilds’. We consider ecological networks – subsets of complete food webs – involving species at adjacent trophic levels. Reciprocal specializations occur when (say) a pollinator (or group of pollinators) specializes on a particular flower species (or group of such species) and vice versa. Such specializations tend to group species into guilds. We characterize the level of reciprocal specialization for both antagonistic interactions – particularly parasitoids and their hosts – and mutualistic ones – such as insects and the flowers that they pollinate. We also examine whether trophic patterns might be ‘palimpsests’– that is, there might be reciprocal specialization within taxonomically related species within a network, but these might be obscured when these relationships are combined. Reciprocal specializations are rare in all these systems when tested against the most conservative null model.
Food Chain, food web, nestedness, null model, Food web, trophic level, Models, Biological, host-parasitoid, specialization, Mutualism, Ecological network, Animals, Null models, Ecosystem
Food Chain, food web, nestedness, null model, Food web, trophic level, Models, Biological, host-parasitoid, specialization, Mutualism, Ecological network, Animals, Null models, Ecosystem
| 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). | 41 | |
| 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. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
| views | 382 | |
| downloads | 28 |

Views provided by UsageCounts
Downloads provided by UsageCounts