Group size effects on foraging and vigilance in migratory Tibetan antelope

Large group sizes have been hypothesized to decrease predation risk and increase food competition. We investigated group size effects on vigilance and foraging behaviour during the migratory period in female Tibetan antelope Pantholops hodgsoni, in the Kekexili Nature Reserve of Qinghai Province, China. During June to August, adult female antelope and yearling females gather in large migratory groups and cross the Qinghai-Tibet highway to calving grounds within the Nature Reserve and return to Qumalai county after calving. Large groups of antelope aggregate in the migratory corridor where they compete for limited food resources and attract the attention of mammalian and avian predators and scavengers. We restricted our sampling to groups of less than 30 antelopes and thus limit our inference accordingly. Focal-animal sampling was used to record the behaviour of the free-ranging antelope except for those with lambs. Tibetan antelope spent more time foraging in larger groups but frequency of foraging bouts was not affected by group size. Conversely, the time spent vigilant and frequency of vigilance bouts decreased with increased group size. We suggest that these results are best explained by competition for food and risk of predation. (C) 2007 Elsevier B.V. All rights reserved.

Rensch's rule in large herbivorous mammals derived from metabolic scaling

Rensch’s rule, which states that the magnitude of sexual size dimorphism tends to increase with increasing body size, has evolved independently in three lineages of large herbivorous mammals: bovids (antelopes), cervids (deer), and macropodids (kangaroos). This pattern can be explained by a model that combines allometry,life-history theory, and energetics. The key features are thatfemale group size increases with increasing body size and that males have evolved under sexual selection to grow large enough to control these groups of females. The model predicts relationships among body size and female group size, male and female age at first breeding,death and growth rates, and energy allocation of males to produce body mass and weapons. Model predictions are well supported by data for these megaherbivores. The model suggests hypotheses for why some other sexually dimorphic taxa, such as primates and pinnipeds(seals and sea lions), do or do not conform to Rensh’s rule.

Oregon's pronghorn antelope.

Mode of access: Internet.

A new antelope from the Pleistocene of Rancho La Brea,

Mode of access: Internet.

Prevalence and associations of Trypanosoma spp. and Sodalis glossinidius with intrinsic factors of tsetse flies

Trypanosomiasis has been identified as a neglected tropical disease in both humans and animals in many regions of sub-Saharan Africa. Whilst assessments of the biology of trypanosomes, vectors, vertebrate hosts and the environment have provided useful information about life cycles, transmission, and pathogenesis of the parasites that could be used for treatment and control, less information is available about the effects of interactions among multiple intrinsic factors on trypanosome presence in tsetse flies from different sites. It is known that multiple species of tsetse flies can transmit trypanosomes but differences in their vector competence has normally been studied in relation to individual factors in isolation, such as: intrinsic factors of the flies (e.g. age, sex); habitat characteristics; presence of endosymbionts (e.g. Wigglesworthia glossinidia, Sodalis glossinidius); feeding pattern; host communities that the flies feed on; and which species of trypanosomes are transmitted. The purpose of this study was to take a more integrated approach to investigate trypanosome prevalence in tsetse flies. In chapter 2, techniques were optimised for using the Polymerase Chain Reaction (PCR) to identify species of trypanosomes (Trypanosoma vivax, T. congolense, T. brucei, T. simiae, and T. godfreyi) present in four species of tsetse flies (Glossina austeni, G. brevipalpis, G. longipennis and G. pallidipes) from two regions of eastern Kenya (the Shimba Hills and Nguruman). Based on universal primers targeting the internal transcribed spacer 1 region (ITS-1), T. vivax was the predominant pathogenic species detected in flies, both singly and in combination with other species of trypanosomes. Using Generalised Linear Models (GLMs) and likelihood ratio tests to choose the best-fitting models, presence of T. vivax was significantly associated with an interaction between subpopulation (a combination between collection sites and species of Glossina) and sex of the flies (X2 = 7.52, df = 21, P-value = 0.0061); prevalence in females overall was higher than in males but this was not consistent across subpopulations. Similarly, T. congolense was significantly associated only with subpopulation (X2 = 18.77, df = 1, P-value = 0.0046); prevalence was higher overall in the Shimba Hills than in Nguruman but this pattern varied by species of tsetse fly. When associations were analysed in individual species of tsetse flies, there were no consistent associations between trypanosome prevalence and any single factor (site, sex, age) and different combinations of interactions were found to be significant for each. The results thus demonstrated complex interactions between vectors and trypanosome prevalence related to both the distribution and intrinsic factors of tsetse flies. The potential influence of the presence of S. glossinidius on trypanosome presence in tsetse flies was studied in chapter 3. A high number of Sodalis positive flies was found in the Shimba Hills, while there were only two positive flies from Nguruman. Presence or absence of Sodalis was significantly associated with subpopulation while trypanosome presence showed a significant association with age (X2 = 4.65, df = 14, P-value = 0.0310) and an interaction between subpopulation and sex (X2 = 18.94, df = 10, P-value = 0.0043). However, the specific associations that were significant varied across species of trypanosomes, with T. congolense and T. brucei but not T. vivax showing significant interactions involving Sodalis. Although it has previously been concluded that presence of Sodalis increases susceptibility to trypanosomes, the results presented here suggest a more complicated relationship, which may be biased by differences in the distribution and intrinsic factors of tsetse flies, as well as which trypanosome species are considered. In chapter 4 trypanosome status was studied in relation to blood meal sources, feeding status and feeding patterns of G. pallidipes (which was the predominant fly species collected for this study) as determined by sequencing the mitochondrial cytochrome B gene using DNA extracted from abdomen samples. African buffalo and African elephants were the main sources of blood meals but antelopes, warthogs, humans, giraffes and hyenas were also identified. Feeding on multiple hosts was common in flies sampled from the Shimba Hills but most flies from Nguruman had fed on single host species. Based on Multiple Correspondence Analysis (MCA), host-feeding patterns showed a correlation with site of sample collection and Sodalis status, while trypanosome status was correlated with sex and age of the flies, suggesting that recent host-feeding patterns from blood meal analysis cannot predict trypanosome status. In conclusion, the complexity of interactions found suggests that strategies of tsetse fly control should be specific to particular epidemic areas. Future studies should include laboratory experiments that use local colonies of tsetse flies, local strains of trypanosomes and local S. glossinidius under controlled environmental conditions to tease out the factors that affect vector competence and the relative influence of external environmental factors on the dynamics of these interactions.