Taxon:
Noctilio albiventris

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Scientific Name
Noctilio albiventris
Common Name
lesser bulldog bat
Taxa Group
mammal
Environment
terrestrial
Move Mode
fly

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  • Data package
    Data from: Seasonal shifts in tropical insect ephemerality drive bat foraging effort
    (2024-06-26) Kohles, Jenna E.; Page, Rachel A.; Wikelski, Martin; Dechmann, Dina K.N.
    Animal foraging is fundamentally shaped by food distribution and availability. However, the quantification of spatiotemporal food distribution is rare but crucial to explain variation in foraging behavior among species, populations, or individuals. Clumped but ephemeral food sources enable rapid energy intake but require increased effort to find, can generate variable foraging success, and force animals to forage more efficiently. We quantified seasonal shifts in the availability of such resources to test the proximate effects of food distribution on changes in movement patterns. The neotropical lesser bulldog bat (Noctilio albiventris) forages in a seasonal environment on emerging aquatic insects, whose numbers peak shortly after dusk. We GPS-tracked bats and quantified nocturnal insect distribution in their foraging area using floating camera traps across wet and dry seasons. Surprisingly, insects were 75% less abundant and swarms were 60% shorter lived (more ephemeral) in the wet season. As a result, wet season bats had to fly twice as far (total and maximum distance from roost distances) and 45% longer (duration) per night. Within foraging bouts, wet season bats spent less time in each insect patch and searched longer for subsequent patches, reflecting increased temporal ephemerality and decreased spatial predictability of insects. Our results highlight the tight link between foraging effort and spatiotemporal distribution of food, and the influence of constraints imposed by reproduction on behavioral flexibility and adaptations to the highly dynamic resource landscapes of mobile prey. Examining foraging behavior in light of spatiotemporal dynamics of resources can help predict how animals respond to shifts in food availability caused by escalating environmental changes.