Understanding how multiple environmental stressors interact to affect seagrass health (measured as morphological and physiological responses) is important for responding to global declines in seagrass populations. We investigated the interactive effects of temperature stress (24, 27, 30 and 32°C) and shading stress (75, 50, 25 and 0% shade treatments) on the seagrass Zostera muelleri over a 3-month period in laboratory mesocosms. Z. muelleri is widely distributed throughout the temperate and tropical waters of south and east coasts of Australia, and is regarded as a regionally significant species. Optimal growth was observed at 27°C, whereas rapid loss of living shoots and leaf mass occurred at 32°C. We found no difference in the concentration of photosynthetic pigments among temperature treatments by the end of the experiment; however, up-regulation of photoprotective pigments was observed at 30°C. Greater levels of shade resulting in high photochemical efficiencies, while elevated irradiance suppressed effective quantum yield (ΔF/FM’). Chlorophyll fluorescence fast induction curves (FIC) revealed that the J step amplitude was significantly higher in the 0% shade treatment after 8 weeks, indicating a closure of PSII reaction centres, which likely contributed to the decline in ΔF/FM’ and photoinhibition under higher irradiance. Effective quantum yield of PSII (ΔF/FM’) declined steadily in 32°C treatments, indicating thermal damage. Higher temperatures (30°C) resulted in reduced above-ground biomass ratio and smaller leaves, while reduced light led to a reduction in leaf and shoot density, above-ground biomass ratio, shoot biomass and an increase in leaf senescence. Surprisingly, light and temperature had few interactive effects on seagrass health, even though these two stressors had strong effects on seagrass health when tested in isolation. In summary, these results demonstrate that populations of Z. muelleri in south-eastern Australia are sensitive to small chronic temperature increases and light decreases that are predicted under future climate change scenarios.