Behavioral Traits and Airport Type Affect Mammal Incidents with U.S. Civil Aircraft

Wildlife incidents with aircraft cost the United States (U.S.) civil aviation industry >US$1.4 billion in estimated damages and loss of revenue from 1990 to 2009. Although terrestrial mammals represented only 2.3 % of wildlife incidents, damage to aircraft occurred in 59 % of mammal incidents. We examined mammal incidents (excluding bats) at all airports in the Federal Aviation Administration (FAA) National Wildlife Strike Database from 1990 to 2010 to characterize these incidents by airport type: Part-139 certified (certificated) and general aviation (GA). We also calculated relative hazard scores for species most frequently involved in incidents. We found certificated airports had more than twice as many incidents as GA airports. Incidents were most frequent in October (n = 215 of 1,764 total) at certificated airports and November (n = 111 of 741 total) at GA airports. Most (63.2 %) incidents at all airports (n = 1,523) occurred at night but the greatest incident rate occurred at dusk (177.3 incidents/hr). More incidents with damage (n = 1,594) occurred at GA airports (38.6 %) than certificated airports (19.0 %). Artiodactyla (even-toed ungulates) incidents incurred greatest (92.4 %) damage costs (n = 326; US$51.8 million) overall and mule deer (Odocoileus hemionus) was the most hazardous species. Overall, relative hazard score increased with increasing log body mass. Frequency of incidents was influenced by species relative seasonal abundance and behavior. We recommend airport wildlife officials evaluate the risks mammal species pose to aircraft based on the hazard information we provide and consider prioritizing management strategies that emphasize reducing their occurrence on airport property.     

Bayesian analysis of Jolly-Seber type models

We propose the use of finite mixtures of continuous distributions in modelling the process by which new individuals, that arrive in groups, become part of a wildlife population. We demonstrate this approach using a data set of migrating semipalmated sandpipers (Calidris pussila) for which we extend existing stopover models to allow for individuals to have different behaviour in terms of their stopover duration at the site. We demonstrate the use of reversible jump MCMC methods to derive posterior distributions for the model parameters and the models, simultaneously. The algorithm moves between models with different numbers of arrival groups as well as between models with different numbers of behavioural groups. The approach is shown to provide new ecological insights about the stopover behaviour of semipalmated sandpipers but is generally applicable to any population in which animals arrive in groups and potentially exhibit heterogeneity in terms of one or more other processes.     

Examining Trajectories of Change for Prosperous Forest Landscapes in Cambodia

Environmental Management - Tropical forest landscapes are undergoing rapid transition. Rural development aspirations are rising, and land use change is contributing to deforestation, degradation,...