Seasonal space use and habitat selection in magpie geese: implications for reducing human‐wildlife conflicts

Abstract

Negative interactions between waterbirds and people are increasing. Waterbirds feeding on agricultural crops cause significant losses to farmers worldwide, but so far most research to address these conflicts has been conducted on migratory species in the temperate northern hemisphere. We investigated the space use and habitat selection of the magpie goose (Anseranas semipalmata), a taxonomically distinct waterbird endemic to Australia and southern Papua New Guinea. In tropical northern Australia, magpie geese are protected but are increasingly persecuted by farmers to protect crops during the late dry–early wet season (~Sep–Jan), a bottleneck of natural resources for waterbirds in the monsoonal tropics. Using satellite telemetry of 38 geese spread across 3 seasons (2016–2017, 2017–2018, 2018–2019), we evaluated daily and seasonal space use, individual site fidelity, and habitat selection to determine the extent of use of agricultural fields by geese, and the spatiotemporal scales at which management should be undertaken. Geese used relatively small daily areas (x̄ = 8.2 km2) consistently throughout the late dry–early wet season, and repeatedly used agricultural fields, forested bushlands, and local wetlands. Geese used comparatively large seasonal areas (x̄ = 219.5 km2) encompassing several agricultural areas, and had a low mean overlap between successive weekly core activity areas, indicating that site fidelity rapidly weakened over time. These results suggest that farm‐scale (<30 ha) management of geese is unlikely to be effective because hazed individuals are likely to be replaced soon afterwards. Instead, our findings suggest that goose management should be coordinated strategically at the local (~1,000 ha), or regional (~100,000 ha) scale. Farm‐level management would likely be more effective if implemented in conjunction with the creation of regional sanctuaries where geese could rest and potentially feed undisturbed away from farms. Our findings can be used by wildlife managers for optimizing the location of such sanctuaries and highlight the necessity for management to be adaptive given the opportunistic nature of the species.

Using dietary metabarcoding analyses to characterise waterbirds–agriculture interactions

“…Irrespective of the type of sampling location (farm or reserve), most geese consumed at least some foods likely to have been of agricultural origin, except for individuals hunted on one reserve located furthest away from agricultural fields (25 km compared to <2 km for all other sites). This exception, along with the spatiotemporal variation in dietary composition and absence of a relationship with individual body condition, is consistent with evidence that geese forage opportunistically (Frith & Davies, 1961; Whitehead, 1991), and within a limited daily activity area (Corriveau, Klaassen, Garnett, Kaestli, Christian, et al, 2022). Our results suggest that resource availability and abundance are likely to be the most influential drivers of food resources consumed, and that geese are attracted to a wide variety of resources within agricultural landscapes.…”

“…However, given the observed spatial variation in dietary composition, such temporal variation in diet choice could also result from geese changing their movements over time. Magpie geese generally move across short distances between September and January (median daily activity area = 0.6 km 2 ), but also occasionally range over larger areas (≤1,486 km 2 ) (Corriveau, Klaassen, Garnett, Kaestli, Christian, et al, 2022). The size of areas used by geese could be influenced by regional disturbances (e.g.…”

Dublin Hareport: The movement ecology and airfield interactions of resident, airside hares, at an international airport

“…As an increasing number of species and populations are required to live within anthropogenically modified landscapes, the potential for human‐wildlife conflict arises. These conflicts can range from the spread of zoonotic diseases (Dias et al., 2020) to the destruction of crops (Corriveau et al., 2022) and the occurrence of wildlife‐vehicle collisions (Serieys et al., 2021). Hence, acquiring high quality wildlife movement data within anthropogenically modified landscapes, with the goal of mitigating impacts and conflicts, is a central objective for wildlife managers (Dias et al., 2020).…”