Microplastics in Indonesian Megafauna Habitats ray egested material confirmed plastic ingestion, the consequences of which might include exposure to toxic plastic additives and adhered persistent organic pollutants. Communicating this information to communities who stand to benefit from healthy megafauna populations might help local governments as they work toward reducing plastics in the marine environment.

This research describes the breeding ecology, behaviour and substrate preferences of the Australian Fairy Tern, Sternula nereis nereis, in four colonies around Perth, Western Australia between 2018 and 2020. Extensive field observations, supported by a bird banding study and sunrise to sunset video recording were used at colony and roosting sites to determine the processes of mating, colony formation, egg-laying and incubation periods, post-hatching care and breeding success (fledglings per pair). At a colony in North Fremantle, the median nest spacing was 0.71m (mean± s.e.= 0.89±0.05m), which increased over time. Birds establishing nests within a week of the first eggs being laid selected sites with significantly higher percentage beach shell cover (73.5±4.5%) than those laying later in the season (58.2±7.9%) and on average, birds selected sites with higher shell cover (64.9±2.8%, n=114) than a random sample of sites within the colony (53.7±4.4%, n=44). Incubation periods ranged from 17 to 26 days (n=86, mean=21±0.17 days). Incubation shift duration was highly variable, with both sexes contributing, almost equally to the care of the brood (mean=1.27±6.11h). Chicks fledged 21–23 (mean=22±0.21, n=10) days following hatching, with all banded juveniles leaving the colony site within 8 days of fledgling. The information gained from this research helps inform conservation strategies for this vulnerable species, where management interventions are frequently necessary to prevent population decline.

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The ability to simulate graphs with given properties is important for the analysis of social networks. Sequential importance sampling has been shown to be particularly effective in estimating the number of graphs adhering to fixed marginals and in estimating the null distribution of graph statistics. This paper describes the networksis package for R and how its simulate and simulate_sis functions can be used to address both of these tasks as well as generate initial graphs for Markov chain Monte Carlo simulations.