thumbnail

A Bayesian network approach to predicting nest presence of thefederally-threatened piping plover (Charadrius melodus)using barrier island features

Ecological Modelling

By:
, , , , , , ,
DOI: /10.1016/j.ecolmodel.2014.01.005

Links

Abstract

Sea-level rise and human development pose significant threats to shorebirds, particularly for species that utilize barrier island habitat. The piping plover (Charadrius melodus) is a federally-listed shorebird that nests on barrier islands and rapidly responds to changes in its physical environment, making it an excellent species with which to model how shorebird species may respond to habitat change related to sea-level rise and human development. The uncertainty and complexity in predicting sea-level rise, the responses of barrier island habitats to sea-level rise, and the responses of species to sea-level rise and human development necessitate a modelling approach that can link species to the physical habitat features that will be altered by changes in sea level and human development. We used a Bayesian network framework to develop a model that links piping plover nest presence to the physical features of their nesting habitat on a barrier island that is impacted by sea-level rise and human development, using three years of data (1999, 2002, and 2008) from Assateague Island National Seashore in Maryland. Our model performance results showed that we were able to successfully predict nest presence given a wide range of physical conditions within the model’s dataset. We found that model predictions were more successful when the range of physical conditions included in model development was varied rather than when those physical conditions were narrow. We also found that all model predictions had fewer false negatives (nests predicted to be absent when they were actually present in the dataset) than false positives (nests predicted to be present when they were actually absent in the dataset), indicating that our model correctly predicted nest presence better than nest absence. These results indicated that our approach of using a Bayesian network to link specific physical features to nest presence will be useful for modelling impacts of sea-level rise- or human-related habitat change on barrier islands. We recommend that potential users of this method utilize multiple years of data that represent a wide range of physical conditions in model development, because the model performed less well when constructed using a narrow range of physical conditions. Further, given that there will always be some uncertainty in predictions of future physical habitat conditions related to sea-level rise and/or human development, predictive models will perform best when developed using multiple, varied years of data input.

Geospatial Extents

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
A Bayesian network approach to predicting nest presence of thefederally-threatened piping plover (Charadrius melodus)using barrier island features
Series title:
Ecological Modelling
DOI:
/10.1016/j.ecolmodel.2014.01.005
Volume
276
Year Published:
2014
Language:
English
Publisher:
Elsevier
Contributing office(s):
Woods Hole Coastal and Marine Science Center
Description:
13 p.
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
First page:
38
Last page:
50
Country:
United States
State:
Maryl