Interactions between trypanosomes and tsetse flies

African trypanosomes are insect-borne parasites that cause sleeping sickness in humans and nagana in domesticated animals. Successful transmission is the outcome of crosstalk between the trypanosome and its insect vector, the tsetse fly. This enables the parasite to undergo successive rounds of differentiation, proliferation and migration, culminating in the infection of a new mammalian host. Several stage- and species-specific parasite surface molecules have been identified and there are new insights into their regulation in the fly. Tsetse flies are often refractory to infection with trypanosomes. While many environmental and physiological factors are known to influence infection, our detailed understanding of tsetse-trypanosome relationships is still in its infancy. Recent studies have identified a number of tsetse genes that show altered expression patterns in response to microbial infections, some of which have also been implicated in modulating trypanosome transmission.

Matrix models for quantifying competitive intransitivity from species abundance data

In a network of competing species, a competitive intransitivity occurs when the ranking of competitive abilities does not follow a linear hierarchy (A > B > C but C > A). A variety of mathematical models suggests that intransitive networks can prevent or slow down competitive exclusion and maintain biodiversity by enhancing species coexistence. However, it has been difficult to assess empirically the relative importance of intransitive competition because a large number of pairwise species competition experiments are needed to construct a competition matrix that is used to parameterize existing models. Here we introduce a statistical framework for evaluating the contribution of intransitivity to community structure using species abundance matrices that are commonly generated from replicated sampling of species assemblages. We provide metrics and analytical methods for using abundance matrices to estimate species competition and patch transition matrices by using reverse-engineering and a colonization-competition model. These matrices provide complementary metrics to estimate the degree of intransitivity in the competition network of the sampled communities. Benchmark tests reveal that the proposed methods could successfully detect intransitive competition networks, even in the absence of direct measures of pairwise competitive strength. To illustrate the approach, we analyzed patterns of abundance and biomass of five species of necrophagous Diptera and eight species of their hymenopteran parasitoids that co-occur in beech forests in Germany. We found evidence for a strong competitive hierarchy within communities of flies and parasitoids. However, for parasitoids, there was a tendency towards increasing intransitivity in higher weight classes, which represented larger resource patches. These tests provide novel methods for empirically estimating the degree of intransitivity in competitive networks from observational datasets. They can be applied to experimental measures of pairwise species interactions, as well as to spatio-temporal samples of assemblages in homogenous environments or environmental gradients.