Developing a wintering waterfowl community baseline for environmental monitoring of Narragansett Bay, Rhode Island [version 3; peer review: 1 approved, 2 approved with reservations]

• Published in: F1000 research Vol. 4; p. 40
• Main Authors: Kreakie, Betty J, Winiarski, Kristopher, McKinney, Richard
• Format: Journal Article
• Language: English
• Published: F1000 Research Ltd 2015
• Subjects: Community Ecology & Biodiversity; Marine & Freshwater Ecology; Population Ecology; Theoretical Ecology; Baseline Data; Community; Environmental Monitoring; Narragansett Bay; Nonmetric Multidimensional Scaling; Waterfowl
• ISSN: 2046-1402; 2046-1402
• DOI: 10.12688/f1000research.6080.3

In 2004, the Atlantic Ecology Division of the US Environmental Protection Agency's Office of Research and Development began an annual winter waterfowl survey of Rhode Island's Narragansett Bay. Herein, we explore the survey data gathered from 2004 to 2011 in order to establish a benchmark understanding of our waterfowl communities and to establish a statistical framework for future environmental monitoring. The abundance and diversity of wintering waterfowl were relatively stable during the initial years of this survey, except in 2010 when there was a large spike in abundance and a reciprocal fall in diversity. There was no significant change in ranked abundance of most waterfowl species, with only Bufflehead ( Bucephala albeola) and Hooded Merganser ( Lophodytes cucllatus) showing a slight yet significant upward trend during the course of our survey period. Nonmetric multidimensional scaling (NMDS) was used to examine the community structure of wintering waterfowl. The results of the NMDS indicate that there is a spatial structure to the waterfowl communities of Narragansett Bay and this structure has remained relatively stable since the survey began. Our NMDS analysis helps to solidify what is known anecdotally about the bay's waterfowl ecology, and provides a formalized benchmark for long-term monitoring of Narragansett Bay's waterfowl communities. Birds, including waterfowl, are preferred bioindicators and we propose using our multivariate approach to monitor the future health of the bay. While this research focuses on a specific area of New England, these methods can be easily applied to novel areas of concern and provide a straightforward nonparametric approach to community-level monitoring. The methods provide a statistic test to examine potential drivers of community turnover and well-suited visualization tools.