Measuring and predicting abundance and dynamics of habitat for piping plovers on a large reservoir

Ecological Modelling
By: , and 



Measuring habitat and understanding habitat dynamics have become increasingly important for wildlife conservation. Using remotely-sensed data, we developed procedures to measure breeding habitat abundance for the federally listed piping plover (Charadrius melodus) at Lake Sakakawea, North Dakota, USA. We also developed a model to predict habitat abundance based on past and projected water levels, vegetation colonization rates, and topography. Previous studies define plover habitat as flat areas (<10% slope) with ≤30% obstruction of bare substrate. Compared to ground-based data, remotely-sensed habitat classifications (≤30/>30% bare-substrate obstruction) were 76% correct and omission and commission errors were equal. Due to water level fluctuations, habitat abundance varied markedly among years (1986–2009) ranging from 9 to 5195 ha. The proportion bare substrate declined with the number of years since a contour was inundated until 5 years (β = -0.65, SE = 0.05), then it stabilized near zero, and the decline varied by shoreline segment (5, 50, and 95 percentile were β = -0.19, SE = 0.05, β = -0.63, SE = 0.05, and β = -0.91, SE = 0.05, respectively). Years since inundated predicted habitat abundance well at shoreline segments (R2 = 0.77), but it predicted better for the whole lake (R2 = 0.86). The vastness and dynamics of plover habitat on Lake Sakakawea suggest that this is a key area for conservation of this species. Model-based habitat predictions can benefit resource conservation because they can (1) form the basis for a sampling stratification, (2) help allocate monitoring efforts among areas, and (3) help inform management through simulations or what-if scenarios.

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Additional publication details

Publication type Article
Publication Subtype Journal Article
Title Measuring and predicting abundance and dynamics of habitat for piping plovers on a large reservoir
Series title Ecological Modelling
DOI 10.1016/j.ecolmodel.2013.08.020
Volume 272
Year Published 2014
Language English
Publisher Elsevier
Contributing office(s) Northern Prairie Wildlife Research Center
Description 12 p.
Larger Work Type Article
Larger Work Subtype Journal Article
Larger Work Title Ecological Modelling
First page 16
Last page 27
Country United States
State North Dakota
Other Geospatial Lake Sakakawea
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