Learning where and when: Large ungulate migrations occur across continents and inspire curiosity about how these animals know when to leave and where to go. Jesmer et al. took advantage of regional extinctions and reintroductions of several North American ungulate species to determine the role of learning in migrations (see the Perspective by Festa-Bianchet). Reintroduced populations of bighorn sheep and moose did not migrate as historical herds had. However, after several decades, newly established herds were better able to track the emergence of vegetation in the environment and were increasingly migratory. Thus, newly introduced animals learned about their environment and shared the information through social exchange. Science , this issue p. 1023 ; see also p. 972

The green wave hypothesis (GWH) states that migrating animals should track or ‘surf’ high-quality forage at the leading edge of spring green-up. To index such high-quality forage, recent work proposed the instantaneous rate of green-up (IRG), i.e. rate of change in the normalized difference vegetation index over time. Despite this important advancement, no study has tested the assumption that herbivores select habitat patches at peak IRG. We evaluated this assumption using step selection functions parametrized with movement data during the green-up period from two populations each of bighorn sheep, mule deer, elk, moose and bison, totalling 463 individuals monitored 1–3 years from 2004 to 2014. Accounting for variables that typically influence habitat selection for each species, we found seven of 10 populations selected patches exhibiting high IRG—supporting the GWH. Nonetheless, large herbivores selected for the leading edge, trailing edge and crest of the IRG wave, indicating that other mechanisms (e.g. ruminant physiology) or measurement error inherent with satellite data affect selection for IRG. Our evaluation indicates that IRG is a useful tool for linking herbivore movement with plant phenology, paving the way for significant advancements in understanding how animals track resource quality that varies both spatially and temporally.

Newly emerging plants provide the best forage for herbivores. To exploit this fleeting resource, migrating herbivores align their movements to surf the wave of spring green-up. With new technology to track migrating animals, the Green Wave Hypothesis has steadily gained empirical support across a diversity of migratory taxa. This hypothesis assumes the green wave is controlled by variation in climate, weather, and topography, and its progression dictates the timing, pace, and extent of migrations. However, aggregate grazers that are also capable of engineering grassland ecosystems make some of the world’s most impressive migrations, and it is unclear how the green wave determines their movements. Here we show that Yellowstone’s bison ( Bison bison ) do not choreograph their migratory movements to the wave of spring green-up. Instead, bison modify the green wave as they migrate and graze. While most bison surfed during early spring, they eventually slowed and let the green wave pass them by. However, small-scale experiments indicated that feedback from grazing sustained forage quality. Most importantly, a 6-fold decadal shift in bison density revealed that intense grazing caused grasslands to green up faster, more intensely, and for a longer duration. Our finding broadens our understanding of the ways in which animal movements underpin the foraging benefit of migration. The widely accepted Green Wave Hypothesis needs to be revised to include large aggregate grazers that not only move to find forage, but also engineer plant phenology through grazing, thereby shaping their own migratory movements.

Understanding the relationship between foraging ecology and the presence of human-dominated landscapes is important, particularly for American black