Abstract Climate change is altering the phenology of food resources, and migratory birds may respond by adjusting migration timing to track shifting food availability (i.e. their phenological sensitivity). The ability to adjust migration timing can vary among species according to traits such as ecological guild, body size and migration distance. Stopover sites are critical components of migration, allowing birds to refuel and acquire updated environmental information. However, empirical evidence on how stopover use enhances phenological sensitivity to shifting spring green‐up remains lacking. In this study, we investigated how stopover frequency influences the phenological sensitivity of migratory waterfowl at breeding areas. We hypothesized that individuals using more stopover sites would better align their migration timing with shifts in vegetation green‐up. We reconstructed 220 spring migration paths from five East Asian migratory waterfowl species using high‐resolution tracking data collected from 2015 to 2023. Spring vegetation green‐up was derived from remote sensing data. We then fitted linear mixed models to test how stopover frequency influences the change of arrival timing at breeding sites. Individuals using a greater number of stopover sites showed closer alignment between their migration timing and local spring vegetation green‐up at breeding areas. More frequent stopover use was associated with stronger phenological sensitivity, suggesting greater behavioural plasticity in tracking shifting resources. Loss of stopover habitat may therefore limit their capacity to respond to changing resource phenology, underscoring the importance of stopover conservation for promoting resilience to climate change.
The forage maturation hypothesis predicts that herbivores should select plants at intermediate growth stages because they strike a balance between biomass and nutritional quality. Methods for identifying this key stage of plant phenology commonly rely on satellite-based greenness indices and their derivatives. By combining such indices with fine-scale movement data, ecologists have uncovered many novel behaviours and life-history strategies, including 'green-wave surfing' by herbivores. Yet, few studies have evaluated the degree to which greenness indices accurately reflect variation in forage characteristics or their selection by herbivores in forested habitats. We studied relationships among remotely sensed greenness indices, on-the-ground measures of forage biomass and quality and resource selection by white-tailed deer (Odocoileus virginianus), elk (Cervus canadensis) and moose (Alces alces) in the coniferous forests of northern Idaho, USA. We hypothesized that remote-sensing methods for measuring the green wave (i.e. the phenological progression of understory food plants) are not useful in coniferous forests because variation in greenness is driven mainly by conifers. We also hypothesized that patterns of forage selection by large herbivores are not detectable in the forest using greenness indices. We tested predictions derived from these hypotheses using on-the-ground measures of forage biomass and quality and more than 10 years of movement data from GPS collars. Remotely sensed greenness indices explained <2.5% of variation in forage biomass (adjusted R2 < 0.024), which was more readily predicted by variation in tree canopy cover, topography and climate (total biomass: adjusted R2 = 0.313; high-quality biomass: adjusted R2 = 0.174). Moreover, with only one exception (elk selected pixels where the instantaneous rate of green-up was near its peak), greenness indices were among the least useful predictors of selection by large herbivores. Indeed, although all three species selected forage biomass, elk and moose simultaneously avoided greener pixels. Our results indicate that greenness indices are of limited value for predicting variation in forage resources or their selection by large herbivores in forested environments. Despite their intuitive appeal and ease of accessibility, such indices cannot always be substituted for on-the-ground measurements of plant traits that directly influence nutrient intake by herbivores.
