Food Webs and Energy Flow

Objective: Read arrows as transfers and place organisms in context.

Primary producers use light or chemical energy to build organic molecules from inorganic carbon. Consumers obtain organic matter from other organisms; decomposers and detritivores process dead material and wastes, making nutrients available through different mechanisms. A food-web arrow conventionally points from the organism or material consumed to the consumer, tracing matter and energy transfer. Omnivores may occupy more than one trophic level, so a species is not always assigned exactly one position. Decomposers are part of the web rather than an endpoint that recycles all usable energy.

Objective: Distinguish energy, biomass, and individual counts.

Gross primary productivity is the total rate of carbon fixation by producers; net primary productivity is the rate remaining after producer respiration, often summarized as NPP = GPP − R under consistent units and boundaries. Only some energy or biomass at one trophic level is passed to the next because material is not all consumed or assimilated and organisms use energy for metabolism. The familiar 10 percent transfer rule is a rough teaching approximation, not a fixed law. Energy pyramids must account for flow per area per time, while standing biomass and organism-number pyramids can have different shapes. An energy transfer never creates new energy.

Objective: Predict indirect consequences while acknowledging uncertainty.

Food webs represent multiple feeding paths rather than a single chain. If one species changes in abundance, direct consumers and resources may respond, and indirect effects can propagate through the network. A trophic cascade describes effects across levels mediated by altered consumer pressure, but its direction and size depend on context, behavior, and other links. Redundant feeding pathways may buffer some disturbances, while strong dependencies can amplify them. A diagram indicates possible routes, not exact numerical outcomes. Controlled comparisons, time series, and knowledge of environmental changes help test causal explanations.