Recent studies have provided detail of the mechanisms by which plants and animals interact, but attempts to apply this knowledge to understand function at the scale of whole fields or grazed ecosystems can be fraught with difficulties. Faced with a plethora of detail, and yet demands to make models more comprehensive, modellers face pressure to revert to simplified accounts for what are assumed to be well‐established biological phenomena, for example, for describing plant growth and intake, but this raises the risk that important insights may be lost, or that the analyses may face errors of scaling. The predictions of a previously described spatial model are compared with those of a non‐spatial rendition of the same model to identify the differences in predictions and the sources of these differences. In particular, the use of the conventional empirical growth functions and their interaction with temporal and spatial scaling errors are examined. The comparison exposed how substantial errors could be made in predicting yield and stability under grazing. It is proposed that such errors might be avoided by ensuring that the functional responses used capture the insights of more detailed studies, and by recognizing the difficulties of scaling‐up from the level of processes to the field scale and beyond.
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Parsons et al. (2001) studied this question.
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