Meta-analysis of marine nutrient-enrichment experiments: Variation in the magnitude of nutrient limitation

Nutrient bioassay experiments have been performed in many marine and estuarine environments around the world. Although protocols have been relatively uniform, these experiments have yielded mixed results, implicating nitrogen, phosphorus, silica, iron, and several other elements as factors limiting phytoplankton growth. Meta-analysis has the potential to explain much of this variation by exploring the relationship between the magnitude of limitation and various environmental characteristics. We quantified limitation with a simple metric, Delta r, that estimates the change in the per unit growth rate of phytoplankton directly attributable to addition of a specific nutrient, such as nitrogen, iron, or phosphorus. Preliminary analyses indicated that experiments lasting less than or equal to 1 d exhibited time lags in the numerical response of phytoplankton to nutrient addition, while experiments lasting >7 d confounded nutrient limitation with processes such as increased grazing or depletion of other nutrients. Thus, we restricted the meta-analysis to results from 2-7 d experiments. These analyses showed that phosphorus enrichment usually had little impact on phytoplankton growth, while enrichments of nitrogen and iron increased phytoplankton growth by 0.1-0.3 d(-1). Nutrient limitation due to N, P, and Fe varied significantly among sites. Nitrogen limitation was greatest in nearshore, nutrient-polluted, and temperate environments (where most experiments have been performed), while phosphorus and iron limitation were strongest in open ocean, unpolluted, and tropical ecosystems, or those receiving pollutants with high N:P ratios. Because phosphorus-enrichment studies have been most often performed in relatively polluted coastal waters, the possible role of phosphorus in limiting primary production in unpolluted oceanic systems may have been underestimated. Examining heterogeneity of responses of different systems to experiments is a valuable application of meta-analysis and can facilitate the development of new ecological insights.