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 theory
and their application to human foraging. The optimization approach
used in behavioral ecology assumes that individual foragers behave so as
to maximize some currency (usually net rate of energy return per unit of
foraging time) which is assumed to correlate with fitness, and employs
models consisting of currencies to be maximized, decisions or foraging
problems to analyzed, and constraints specifying options available to the
foragers and their effects.
The classical diet breadth model predicts a set of food resources that
maximizes energy return rate under a set of assumptions: a "finegrained"
environment (homogeneous resource distribution) , random
encounters, mutually exclusive search and handling costs, a rank of all
food resource types on the basis of net return rate on encounter, and
complete information. While the model can predict qualitative subsistence
patterns, such as a fluctuation of diet breadth in accordance with
changes in search or handling costs derived from technological changes,
many of the quantitative tests have revealed discrepancies between the
model's predictions and observed patterns. This is mainly due to the
fact that the human foraging patterns in question sometimes violate the
assumptions of the model. It is common that male foragers often ignore
plant foods that would increase overall energy return rates of foraging if
collected. Tests made within a set of animal foods or one of plant foods
show close fits between predictions and observations.
For a "patchy" environment, where resources are distributed in a
heterogeneous fashion, optimal patch use models are used to predict an
array of habitats (patches) to be exploited and how long a forager stays
in a patch before leaving for another. The optimal patch choice model
has the same structure and procedure as those of the optimal diet breadth
model, while replacing resource types with patch types. The optimal
patch residence time is solved by using the marginal value theorem,
which assumes diminishing returns and determines the point at which a
forager should leave a depleting patch to search for another one to
maximize energy return rate. We can so far find no anthropological
studies of patch residence time that meet the assumptions of the marginal
value theorem except for one case. Most of the studies incorrectly attempt
to predict the proportion of time foragers spend exploiting
different patches on the assumption that optimal foragers preferentially
allocate foraging time to patches with higher return rates.
Relaxing and changing assumptions can modify the classic diet
breadth and patch use models. The central-place-foraging model in
which 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 classic
models. Foraging models focused on acquisition and sharing of information
about resource conditions among foraging groups and reduction
of risk (variance in food consumption) by food sharing, which are
unique to human foragers, allow interesting predictions to be made
about choice behavior and social interaction.
Humans are omnivorous animals and exploit simultaneously
various food resources greatly different in nutritional composition. The
classic foraging models reduce nutritional values of food only to energy.
Most of the critiques of the optimal foraging models have been directed
toward this point. The problem of multiple nutrient requirements has
been treated with a linear programming model that aims to predict the
least costly solution to an economic problem in which resources (labor,
energy, raw material, and money) must be allocated among competing
activities. Another approach to evaluating food resources along more
than one scale is indifference analysis, borrowed from microeconomics.
This analysis predicts a utility-maximizing mix of different but complementary
and substitutable food resources. Each approach has its
strengths and weaknesses.