Breeding Biology of Red-winged Blackbirds (Agelaius phoeniceus) in Stormwater Retention Ponds on the College at Brockport Campus

Red-winged Blackbirds (Agelaius phoeniceus) often breed in stormwater retention ponds. I studied the breeding biology of the species in seven small retention ponds at the College at Brockport, to evaluate their breeding success in a created habitat relative to data from studies in natural habitats. I also determined how habitat characteristics affect the breeding biology of Red-winged Blackbirds. The College at Brockport population had harem sizes with up to four females per male. There was a significant positive relationship between pond area and the number of male territories. I found 47 nests, at least four of which wer second nestings; average clutch size was 3.7 eggs. The nesting season began with the first clutch on 26 April 2017 with peak hatching dates from 27 May until 2 June and peak fledging dates from 7 June until 16 June. The nesting season ended when the last nest fledged, which was around 22 July 2017. Apparent nest success was 78.3%, with predation rates of 10.0%. In studies from similar habitats, apparent nest success was often much lower, ranging from 3.0 to 71.0% with predation rates ranging from 30.0% up to 97.0% in some areas. There was no significant difference between successful and unsuccessful nests in distance from nest to pond edge or open water, water depth, vegetation height, and density between. Based on my results the retention ponds provide good breeding habitat for Red-winged Blackbirds but stormwater ponds should be managed properly for wildlife use. Management practices such as discouraging invasive species, reducing overabundance of emergent vegetation, and occasional dredging would benefit wildlife use of the retention ponds.

Author dc:creator

• Butler, Abigail

Advisor dc:contributor.advisor

• Norment, Christopher

Language dc:language.iso

en_US

Handle dc:identifier.uri

http://hdl.handle.net/20.500.12648/6717

OAI identifier oai:identifier

oai:soar.suny.edu:20.500.12648/6717