Different drivers, common mechanism; the distribution of a reef fish is restricted by local-scale oxygen and temperature constraints on aerobic metabolism

The distributions of ectothermic marine organisms are limited to temperature ranges and oxygen conditions that support aerobic respiration, quantified within the metabolic index (ϕ) as the ratio of oxygen supply to metabolic oxygen demand. However, the utility of ϕ at local scales and across heterogenous environments is unknown; yet, these scales are often where actionable management decisions are made. Here, we test if ϕ can delimit the entire distribution of marine organisms when calibrated across an appropriate temperature range and at local scales (~10 km) using the endemic reef fish, Chrysoblephus laticeps, which is found in the highly heterogenous temperature and oxygen environment along the South African coastal zone, as a model species. In laboratory experiments, we find a bidirectional (at 12°C) hypoxia tolerance response across the temperature range tested (8 to 24°C), permitting a piecewise calibration of ϕ. We then project this calibrated ϕ model through temperature and oxygen data from a high spatial resolution (11 to 13 km) ocean model for the periods 2005 to 2009 and 2095 to 2099 to quantify various magnitudes of ϕ across space and time paired with complementary C. laticeps occurrence points. Using random forest species distribution models, we quantify a critical ϕ value of 2.78 below which C. laticeps cannot persist and predict current and future distributions of C. laticeps in line with already observed distribution shifts of other South African marine species. Overall, we find that C. laticeps’ distribution is limited by increasing temperatures towards its warm edge but by low oxygen availability towards its cool edge, which is captured within ϕ at fine scales and across heterogenous oxygen and temperature combinations. Our results support the application of ϕ for generating local- and regional-scale predictions of climate change effects on organisms that can inform local conservation management decisions.