Estimating physiological mechanisms from monitoring data reveals
challenges and opportunities for forecasting distribution shifts
Abstract
Species distribution modeling is increasingly used to describe and
anticipate consequences of a warming ocean. These models often identify
statistical associations between distribution and environmental
conditions such as temperature and oxygen, but rarely consider the
mechanisms by which these environmental variables affect metabolism.
Oxygen and temperature jointly govern the rate of oxygen supply to
oxygen demand, and theory predicts thresholds in these rates below which
species population densities are diminished. However, parameterizing
models with this joint dependence is challenging because of the paucity
of experimental work for most species, and the limited applicability of
experimental findings in situ. Here we ask whether the joint effects of
temperature and oxygen can be reliably inferred from species
distribution observations in the field, using the U.S. Pacific Coast as
a model system. Through simulation testing, we found that our
statistical model—which adapted the metabolic index to jointly
consider oxygen and temperature by applying an Arrhenius equation and
used a non-linear threshold function to link the index to fish
distribution—could not precisely estimate the parameters due to
inherent features of the distribution data. However, the model reliably
estimated an overall metabolic index threshold effect, and provided a
better fit to sablefish (Anoplopoma fimbria) spatial distribution than
previously used models. This mechanistic approach may improve
predictions of species distribution, even in novel environmental
conditions. Further efforts to combine insights from mechanistic
responses and realized species distributions will improve forecasts of
species’ responses to future environmental changes.