Decision-Making in Group Foragers With Incomplete Information: Test of Individual-Based Model in Geese

Abstract

One important challenge of spatial ecology is to generate models linking individual behavior to population‐level phenomena. Although animals often face great uncertainty regarding foraging patch quality, earlier models explaining the aggregation of animals have rarely specified how stable outcomes are achieved through individual decisions, especially under realistic assumptions for incompletely informed foragers. We developed a new foraging model that assumed a realistic decision‐making rule for incompletely informed group foragers, and we tested its performance against existing models with different assumptions by comparing how well they reproduce the patterns observed in foraging White‐fronted Geese (Anser albifrons). The assumptions in each of the four compared models were: (1) incompletely informed foraging with benefits of group foraging, which uses the expected gain rates for making decisions on diet choice, patch departure, and flock joining; (2) incompletely informed foraging without benefits of group foraging, which uses the expected gain rates to determine the timing of patch departure but selects a new patch randomly; (3) completely informed foraging without benefits of group foraging, which simply selects the most profitable patches; and (4) completely informed foraging with benefits of group foraging, which selects the most profitable patches, considering benefits from the presence of conspecifics. The model that assumed incompletely informed foragers with benefits of group foraging was best in agreement with the observed patterns in all of the five spatial distribution and fat deposition parameters. The models that assumed no benefits of group foraging could not reproduce the observed seasonal variation in flock sizes, whereas the models with completely informed foragers overestimated the flock size as well as usage by the geese of alternative food and the fields near the roost. These results supported the idea that the geese can be assumed to use the expected gain rates for decision‐making on diet choice, patch departure, and flock joining. Further, the incompletely informed foragers showed greater disparity in foraging performance among individuals. We discuss the necessity of assuming, when appropriate, that foragers have incomplete information on patch quality in models explaining spatial distribution and foraging success. We also make some references to the applicability of the presented model in other studies.

Modeling marine protected areas for threatened eiders in a climatically changing Bering Sea

“…For species that typically aggregate in large flocks, such as Spectacled Eiders in winter, attraction to conspecifics is undoubtedly an important aspect of habitat selection (Amano et al 2006). We addressed this issue partly by restricting some analyses to locations where eiders were modeled to survive winter ( Table 3), assuming that individuals could easily locate large flocks that concentrate in viable habitat.…”

“…Rather, our intent was to estimate the fraction of the overall region in which eiders could survive regardless of how they located those areas, and to identify factors affecting the viability of those locations. The benefits of conspecific attraction are often linked to rates of prey depletion (Beauchamp et al 1997, Amano et al 2006), a factor that we also did not consider. Our once-per-season icebreaker cruises into this otherwise inaccessible area did not allow monitoring of progressive prey depletion over winter.…”

How do foragers decide when to leave a patch? A test of alternative models under natural and experimental conditions

“…; Amano et al . ; but see Nolet, Klaassen & Mooij ). For example, Bayesian updating models explained foraging behaviour better than other models, including a prescient forager model, in red knots ( Calidris canutus ) (van Gils et al .…”

The Future for Research on Waterbirds in Rice Fields

“…Placing data collection on foraging behavior in a broader theoretical context would also provide important insights (e.g. Amano et al 2006aAmano et al , 2006bLourenço et al 2010), especially if linked directly to measures of body condition or survival.…”