Satellite- versus temperature-derived green wave indices for predicting the timing of spring migration of avian herbivores. (November 2015)

• Record Type: Journal Article
• Authors: Shariati Najafabadi, Mitra; Darvishzadeh, Roshanak; Skidmore, Andrew K.; Kölzsch, Andrea; Vrieling, Anton; Nolet, Bart A.; Exo, Klaus-Michael; Meratnia, Nirvana; Havinga, Paul J.M.; Stahl, Julia; Toxopeus, Albertus G.
• Is Part Of: Ecological indicators. Volume 58(2015)
• Page Start: 322
• Page End: 331
• Publication Date: 2015-11
• Subjects: GWI index -- GDD jerk index -- Barnacle geese -- Stopover site -- Breeding site -- Mixed effect linear regression; Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2015.06.005
• Languages: English
• ISSNs: 1470-160X

Abstract

Highlights: The GWI and GDDjerk indices have significant relationships with goose migration timing. The GWI index accurately predicts arrival date of goose to breeding and stopovers. Unlike the GWI index, the GDDjerk index is highly sensitive to latitude. Abstract: According to the green wave hypothesis, herbivores follow the flush of spring growth of forage plants during their spring migration to northern breeding grounds. In this study we compared two green wave indices for predicting the timing of the spring migration of avian herbivores: the satellite-derived green wave index (GWI), and an index of the rate of acceleration in temperature (GDDjerk). The GWI was calculated from MODIS normalized difference vegetation index (NDVI) satellite imagery and GDDjerk from gridded temperature data using products from the global land data assimilation system (GLDAS). To predict the timing of arrival at stopover and breeding sites, we used four years (2008–2011) of tracking data from 12 GPS-tagged barnacle geese, a long-distance herbivorous migrant, wintering in the Netherlands, breeding in the Russian Arctic. The stopover and breeding sites for these birds were identified and the relations between date of arrival with the date of 50% GWI and date of peak GDDjerk at each site were analyzed using mixed effect linear regression. A cross-validation method was used to compare the predictive accuracy of the GWI and GDDjerk indices. Significant relationships were found between the arrival dates at the stopover and breeding sites for the dates of 50% GWI as well as the peak GDDjerk ( p < 0.01). The goose arrival dates at both stopover and breeding sites were predicted more accurately using GWI ( R 2 cv = 0.68, RMSD cv = 5.9 and R 2 cv = 0.71, RMSD cv = 3.9 for stopover and breeding sites, respectively) than GDDjerk. The GDDjerk returned a lower accuracy for prediction of goose arrival dates at stopover ( R 2 cv = 0.45, RMSD cv = 7.79) and breeding sites ( R 2 cv = 0.55, RMSD cv = 4.93). The positive correlation between the absolute residual values of the GDDjerk model and distance to the breeding sites showed that this index is highly sensitive to latitude. This study demonstrates that the satellite-derived green wave index (GWI) can accurately predict the timing of goose migration, irrespective of latitude and therefore is suggested as a reliable green wave index for predicting the timing of avian herbivores spring migration.