最適採食戦略 : 食物獲得の行動生態学

本稿は行動生態学で発達した最適採食理論を人間の食物獲得活動へ適用した研究のレヴューである。最適採食理論に基づく食物獲得活動の研究では,利用可能な戦略(行動)の中でどのような戦略が進化するかを予測する最適化分析が用いられる。ここでは最適採食モデルとして,食餌幅,パッチ選択とパッチ内時間のモデル,およびこれら古典モデルの仮定を緩和することによって修正されたモデルとして中心点採食,資源の変動や食物分配とリスクの関係,複数の「通貨」を取り入れた線形計画法と無差別曲線分析などがあつかわれる。現在までのところ,最適採食モデルの人間行動への適用事例ではモデルの予測と実際の観察がうまく一致しないことが多いが,むしろそこから人間行動の特性を引き出し,モデルを改良することが重要である。

This article reviews the basic principles of optimal foraging theoryand their application to human foraging. The optimization approachused in behavioral ecology assumes that individual foragers behave so asto maximize some currency (usually net rate of energy return per unit offoraging time) which is assumed to correlate with fitness, and employsmodels consisting of currencies to be maximized, decisions or foragingproblems to analyzed, and constraints specifying options available to theforagers and their effects.The classical diet breadth model predicts a set of food resources thatmaximizes energy return rate under a set of assumptions: a "finegrained"environment (homogeneous resource distribution) , randomencounters, mutually exclusive search and handling costs, a rank of allfood resource types on the basis of net return rate on encounter, andcomplete information. While the model can predict qualitative subsistencepatterns, such as a fluctuation of diet breadth in accordance withchanges in search or handling costs derived from technological changes,many of the quantitative tests have revealed discrepancies between themodel's predictions and observed patterns. This is mainly due to thefact that the human foraging patterns in question sometimes violate theassumptions of the model. It is common that male foragers often ignoreplant foods that would increase overall energy return rates of foraging ifcollected. Tests made within a set of animal foods or one of plant foodsshow close fits between predictions and observations.For a "patchy" environment, where resources are distributed in aheterogeneous fashion, optimal patch use models are used to predict anarray of habitats (patches) to be exploited and how long a forager staysin a patch before leaving for another. The optimal patch choice modelhas the same structure and procedure as those of the optimal diet breadthmodel, while replacing resource types with patch types. The optimalpatch residence time is solved by using the marginal value theorem,which assumes diminishing returns and determines the point at which aforager should leave a depleting patch to search for another one tomaximize energy return rate. We can so far find no anthropologicalstudies of patch residence time that meet the assumptions of the marginalvalue theorem except for one case. Most of the studies incorrectly attemptto predict the proportion of time foragers spend exploitingdifferent patches on the assumption that optimal foragers preferentiallyallocate foraging time to patches with higher return rates.Relaxing and changing assumptions can modify the classic dietbreadth and patch use models. The central-place-foraging model inwhich foraging is modeled as a trip with a given point (a camp or village)of departure and return is more suited to human foraging than the classicmodels. Foraging models focused on acquisition and sharing of informationabout resource conditions among foraging groups and reductionof risk (variance in food consumption) by food sharing, which areunique to human foragers, allow interesting predictions to be madeabout choice behavior and social interaction.Humans are omnivorous animals and exploit simultaneouslyvarious food resources greatly different in nutritional composition. Theclassic foraging models reduce nutritional values of food only to energy.Most of the critiques of the optimal foraging models have been directedtoward this point. The problem of multiple nutrient requirements hasbeen treated with a linear programming model that aims to predict theleast costly solution to an economic problem in which resources (labor,energy, raw material, and money) must be allocated among competingactivities. Another approach to evaluating food resources along morethan one scale is indifference analysis, borrowed from microeconomics.This analysis predicts a utility-maximizing mix of different but complementaryand substitutable food resources. Each approach has itsstrengths and weaknesses.