TY - JOUR
T1 - Indicators of site loss from a migration network
T2 - Anthropogenic factors influence waterfowl movement patterns at stopover sites
AU - Xu, Yanjie
AU - Kieboom, Mattias
AU - Van Lammeren, Ron J.A.
AU - Si, Yali
AU - De Boer, Willem F.
PY - 2021
Y1 - 2021
N2 - A network of connected wetlands supports migratory movements of waterfowl. These networks are rapidly changing due to intensive human activities around natural habitats. Quantifying how anthropogenic factors change waterfowl movements via a reduction of habitat availability and quality can facilitate a better understanding of the dynamics of these migration networks, and provide early-warning signals for network collapse. Using satellite tracking data for greater white-fronted geese (Anser albifrons) in the East Asian-Australasian Flyway, we tested how environmental factors (i.e., anthropogenic and ecological factors) influence geese movement patterns at stopover sites. We found that these factors, e.g., percentage of farmlands in the landscape, and proximity index of wetland patches, accurately predicted percentage of flying time and the median movement distance of tracked geese at stopover sites. Farmlands may increase energy consumptions in stopover sites because the geese flew more frequently, made longer movements, and switched their behaviour more frequently in landscapes with a higher proportion of farmlands. Goose movements were constrained in natural habitats, as a higher proportion of water and wetlands increased their movements, and thereby increased flying time and median movement distances. We suggest that using environmental factors monitored by remote sensing techniques to predict bird movement patterns is a powerful quantitative tool to measure quality of stopover sites. The changes in environmental factors in these stopover sites can be used as an indicator for the probability of losing a site from a migration network, and thereby generates insights for setting priorities in conservation planning of migratory birds.
AB - A network of connected wetlands supports migratory movements of waterfowl. These networks are rapidly changing due to intensive human activities around natural habitats. Quantifying how anthropogenic factors change waterfowl movements via a reduction of habitat availability and quality can facilitate a better understanding of the dynamics of these migration networks, and provide early-warning signals for network collapse. Using satellite tracking data for greater white-fronted geese (Anser albifrons) in the East Asian-Australasian Flyway, we tested how environmental factors (i.e., anthropogenic and ecological factors) influence geese movement patterns at stopover sites. We found that these factors, e.g., percentage of farmlands in the landscape, and proximity index of wetland patches, accurately predicted percentage of flying time and the median movement distance of tracked geese at stopover sites. Farmlands may increase energy consumptions in stopover sites because the geese flew more frequently, made longer movements, and switched their behaviour more frequently in landscapes with a higher proportion of farmlands. Goose movements were constrained in natural habitats, as a higher proportion of water and wetlands increased their movements, and thereby increased flying time and median movement distances. We suggest that using environmental factors monitored by remote sensing techniques to predict bird movement patterns is a powerful quantitative tool to measure quality of stopover sites. The changes in environmental factors in these stopover sites can be used as an indicator for the probability of losing a site from a migration network, and thereby generates insights for setting priorities in conservation planning of migratory birds.
KW - Animal movement
KW - Bird migration
KW - Habitat configuration
KW - Human activities
KW - Wetland
U2 - 10.1016/j.gecco.2020.e01435
DO - 10.1016/j.gecco.2020.e01435
M3 - Article
SN - 2351-9894
VL - 25
JO - Global Ecology and Conservation
JF - Global Ecology and Conservation
M1 - e01435
ER -