Why less complexity produces better forecasts: an independent data evaluation of kelp habitat models

Understanding how species are distributed in the environment is increasingly important for natural resource management, particularly for keystone and habitat forming species, and those of conservation concern. Habitat suitability models are fundamental to developing this understanding; however their use in management continues to be limited due to often-vague model objectives and inadequate evaluation methods. Along the Northeast Pacific coast, canopy kelps (Macrocystis pyrifera and Nereocystis luetkeana) provide biogenic habitat and considerable primary production to nearshore ecosystems. We investigated the distribution of these species by examining a series of increasingly complex habitat suitability models ranging from process-based models based on species' ecology to complex Generalised Additive Models applied to purpose-collected survey data. Seeking limits on model complexity, we explored the relationship between model complexity and forecast skill, measured using both cross-vali...