Foraging behavior and energetics of Great Egrets and Snowy Egrets at interior rivers and weirs

Abstract

Wading birds may use different foraging methods and prey capture techniques in particular habitats or under specific conditions. We measured foraging behavior and its energetic costs for Great Egrets (Ardea alba) and Snowy Egrets (Egretta thula) at two weirs (small overflow dams that raise water levels in a stream or river) and in two naturally flowing rivers in Kansas in May and June 2000 and 2005. We observed 99 randomly selected birds (38 Great Egrets and 61 Snowy Egrets) for 1513 min, and noted strike rate, prey capture rate, capture efficiency, prey size, and social interactions. In addition, 30 of these birds were observed for 504 min to estimate ambulation velocities and foraging energetics. Both species had higher strike rates and prey capture rates in rivers, but caught larger fish at weirs. Capture efficiency was higher for Snowy Egrets at weirs, but did not differ between microhabitats for Great Egrets. Snowy Egrets had higher rates of conspecific aggression at weirs than in rivers, but little aggression was documented for Great Egrets. Established algorithms suggest that, while foraging in rivers, Snowy Egrets had similar costs for changes in velocity. Changes in ambulation velocity for Great Egrets were greater at weirs than rivers. For both species, the percentage of time spent standing was twice as high at weirs as in rivers. Both species also used low-cost foraging strategies at weirs that yielded larger fish, so net energetic gains at weirs were higher than in rivers. Weirs appear to be more important to Snowy Egrets than to Great Egrets. Estimates of energy gains and expenses provide valuable predictive power for understanding egret behavior. SINOPSIS. Conducta de forrajeo y gasto energético de Ardea alba y Egretta thula en ríos del interior y en paraderasMedimos la conducta de forrajeo y el costo energético en individuos de Garza Real (Ardea alba) y Garza Blanca (Egretta thula), en dos paraderas o canales de ríos y dos ríos en Wichita, Kansas. El estudio se llevó a cabo en mayo y junio de 2002 y 2005. Observamos al azar 99 aves seleccionadas (38 de Garza Real y 61 Garza Blanca) por un total de 1513 minutos, y las siguientes variables fueron comparadas entre especies y microhabitats: tasa de acometidas, tasa de captura de presas, eficiencia de captura, tamaño de la presa e interacciones sociales. Un subconjunto de aves fue observada por 450 minutos y utilizadas para estimar la velocidad de desplazamiento y el presupuesto energético de forrajeo. Pusimos a prueba la hipótesis que las garzas adaptan los componentes de su forrajeo a las condiciones locales. Si correcto, los patrones de alimentación para ambas especies debio variar entre microhabitats. Ambas especies, exhibieron una tasa mas altas de acometidas y captura de presas en rios, pero capturaron peces de mayor tamano en canales. El muestreo de presas en ambos microhabitats mostró que los peces en canales eran mas grandes que los de rios. La Garza Blanca mostró una tasa más alta de agresión conespecifica en canales que en ríos. Se documento ...

The contrasting feeding ecology of great egrets and roseate spoonbills in limnetic and estuarine colonies

“…Using isotopes we could not exclude the possibility that periphyton, phytoplankton or C 3 macrophyte consumers, or consumers of vegetable organic matter, such as the small fish A. eigenmanniorum and J. multidentata, which include vegetation in their diets (Corrêa et al, 2010;Fischer et al, 2011), are food sources. The great egret is a visual predator that uses the sitand-wait technique (Kushlan & Hancock, 2005;Maccarone & Brzorad, 2007). Fish were three times more important than insects in the diet of egrets in the estuary, and insects were the predominant prey in freshwater.…”

“…The great egret, Ardea alba Linnaeus, 1753, hereafter egret, is widespread in Americas and the Old World, using a range of brackish and freshwater habitats for feeding (McCrimmon et al, 2001;Kushlan & Hancock, 2005). Egrets usually capture prey such as fish, crustaceans, amphibians, reptiles, and insects by detecting them visually and capturing a single prey with a rapid downward or lateral stroke (Beltzer & Quiroga, 2007;Maccarone & Brzorad, 2007;Post, 2008). In estuarine areas of North Carolina (USA), egrets forage and respond opportunistically to local prey availability (Post, 2008), foraging mainly during the daytime (Rojas et al, 1999).…”

Effect of Water Level and Time of day on Black-Crowned Night-Heron (Nycticorax nycticorax) Foraging Behavior at an Artificial Weir: 2013–2014

“…Fish lengths and identification were determined for 90% of successful strikes. The relationship between fish length and weight was established from a sample of >100 Red Shiners (Cyprinella lutrensis) and Sand Shiners (Notropis ludibundus) collected near the study site (Maccarone and Brzorad 2007). Both species are common in local waters and comprised a large proportion of captured fish both years.…”

A Telemetry-based Study of Snowy Egret (Egretta thula) Nest-activity Patterns, Food-provisioning Rates and Foraging Energetics

“…Prey size was estimated by comparing prey length to the length of a Snowy Egret bill (7.9 cm) (Bayer 1985;Brzorad et al 2004). A length weight regression (R 2 > 0.90) previously established by measuring a random sample of 113 fish collected at this site (Maccarone and Brzorad 2007) was used to convert body lengths into weights. Petersen and Ward (1999) determined the energy value of Sand Shiners (Notropis stramineus) to be 6703 J/g wet weight, which was used to estimate the energy content of fish.…”

“…Petersen and Ward (1999) determined the energy value of Sand Shiners (Notropis stramineus) to be 6703 J/g wet weight, which was used to estimate the energy content of fish. This species often comprises the majority of fish captured by egrets in this area (Maccarone and Brzorad 2007). Although body lengths of Leopard Frogs (Rana pipiens) were estimated as with fish, frog body weights were determined with a different regression model (Hatai 2005).…”