Optimal foraging and community structure: implications for a guild of generalist grassland herbivores

A particular linear programming model is constructed to predict the diets of each of 14 species of generalist herbivores at the National Bison Range, Montana. The herbivores have body masses ranging over seven orders of magnitude and belonging to two major taxa: insects and mammals. The linear programming model has three feeding constraints: digestive capacity, feeding time and energy requirements. A foraging strategy that maximizes daily energy intake agrees very well with the observed diets. Body size appears to be an underlying determinant of the foraging parameters leading to diet selection. Species that possess digestive capacity and feeding time constraints which approach each other in magnitude have the most generalized diets. The degree that the linear programming models change their diet predictions with a given percent change in parameter values (sensitivity) may reflect the observed ability of the species to vary their diets. In particular, the species which show the most diet variability are those whose diets tend to be balanced between monocots and dicots. The community-ecological parameters of herbivore body-size ranges and species number can possibly be related to foraging behavior.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47765/1/442_2004_Article_BF00377109.pd

Impact of traffic-related air pollution on acute changes in cardiac autonomic modulation during rest and physical activity: a cross-over study

People are often exposed to traffic-related air pollution (TRAP) during physical activity (PA), but it is not clear if PA modifies the impact of TRAP on cardiac autonomic modulation. We conducted a panel study among 28 healthy adults in Barcelona, Spain to examine how PA may modify the impact of TRAP on cardiac autonomic regulation. Participants completed four 2-h exposure scenarios that included either rest or intermittent exercise in high- and low-traffic environments. Time- and frequency-domain measures of heart rate variability (HRV) were monitored during each exposure period along with continuous measures of TRAP. Linear mixed-effects models were used to estimate the impact of TRAP on HRV as well as potential effect modification by PA. Exposure to TRAP was associated with consistent decreases in HRV; however, exposure-response relationships were not always linear over the broad range of exposures. For example, each 10 μg/m(3) increase in black carbon was associated with a 23% (95% CI: -31, -13) decrease in high frequency power at the low-traffic site, whereas no association was observed at the high-traffic site. PA modified the impact of TRAP on HRV at the high-traffic site and tended to weaken inverse associations with measures reflecting parasympathetic modulation (P≤0.001). Evidence of effect modification at the low-traffic site was less consistent. The strength and direction of the relationship between TRAP and HRV may vary across exposure gradients. PA may modify the impact of TRAP on HRV, particularly at higher concentrations.This work was part of the European-wide project Transportation Air pollution and Physical ActivitieS (TAPAS): an integrated health risk assessment program of climate change and urban policies, which had partners in Barcelona, Basel, Copenhagen, Paris, Prague, and Warsaw. TAPAS was a 4-year project funded by the Coca-Cola Foundation, AGAUR, and CREAL (http://www.tapas-program.org/). CREAL is part of CIBERESP (http://www.ciberesp.es/), the Spanish Network for Epidemiology and Public Health Research. CREAL and its members are based at and supported by the Universitat Pompeu Fabra (http://www.upf.edu/en/)