The Index of Relative Importance (IRI) is a composite measure that reduces bias in descriptions of animal dietary data. The two papers introducing the IRI in 1971 had been cited a total of 214 times by the end of 2001 and proposed as a standard methodology. However, 180 of these citations concerned the description of the diets of fish, indicating that the IRI is not well known outside fisheries biology. This illustrates how the interests of researchers in a narrow range of taxa may restrict the application of a useful technique to particular groups of animals. Here we apply the IRI to dietary data from one mammal species, two bird species and two species of geckoes to illustrate its applicability to a wide range of taxa. We believe the approach should be considered seriously by terrestrial ecologists concerned about the biases inherent in single-index approaches to describing animal diets.

Fine particulate matter with an aerodynamic diameter of less than 2.5 µm (PM2.5) is highly variable in space and time. In this study, the dynamics of PM2.5 concentrations were mapped at high spatio-temporal resolutions using bicycle-based, mobile measures on a university campus. Significant diurnal and daily variations were revealed over the two-week survey, with the PM2.5 concentration peaking during the evening rush hours. A range of predictor variables that have been proven useful in estimating the pollution level was derived from Geographic Information System, high-resolution airborne images, and Light Detection and Ranging (LiDAR) datasets. Considering the complex interplay among landscape, wind, and air pollution, variables influencing the PM2.5 dynamics were quantified under a new wind wedge-based system that incorporates wind effects. Panel data analysis models identified eight natural and built environment variables as the most significant determinants of local-scale air quality (including four meteorological factors, distance to major roads, vegetation footprint, and building and vegetation height). The higher significance level of variables calculated using the wind wedge system as compared to the conventional circular buffer highlights the importance of incorporating the relative position of emission sources and receptors in modeling.

Seasonal migration is a behavioral response to predictable variation in environmental resources, risks, and conditions. In behaviorally plastic migrants, migration is a conditional strategy that depends, in part, on an individual’s informational state. The cognitive processes that underlie how facultative migrants understand and respond to their environment are not well understood. We compared perception of the present environment to memory and omniscience as competing cognitive mechanisms driving altitudinal migratory decisions in an endangered ungulate, the Sierra Nevada bighorn sheep (Ovis canadensis sierrae) using 1,298 animal years of data, encompassing 460 unique individuals. We built a suite of statistical models to partition variation in fall migratory status explained by cognitive predictors, while controlling for non-cognitive drivers. To approximate attribute memory, we included lagged attributes of the range an individual experienced in the previous year. We quantified perception by limiting an individual’s knowledge of migratory range to the area and attributes visible from its summer range, prior to migrating. Our results show that perception, in addition to the migratory propensity of an individual’s social group, and an individual’s migratory history are the best predictors of migration in our system. Our findings suggest that short-distance altitudinal migration is, in part, a response to an individual’s perception of conditions on alterative winter range. In long-distance partial migrants, exploration of migratory decision-making has been limited, but it is unlikely that migratory decisions would be based on sensory cues from a remote target range. Differing cognitive mechanisms underpinning short and long-distance migratory decisions will result in differing levels of behavioral plasticity in response to global climate change and anthropogenic disturbance, with important implications for management and conservation of migratory species.

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