Inferring microalgae density and net ecosystem production on soft sediments using infrared imaging

Abstract

Measuring microalgae density in soft-sediment benthos has challenges for even the most sophisticated methods. If the goal is to assess the photosynthetic potential of epipelon, then microalgae should be sampled only at the surface of the benthos to the depth of light penetration. Furthermore, microalgae density may show spatial and temporal variability that can only be captured by using many point samples and nondestructive sampling. Here, we use simple near-infrared (NIR) imagery to assess surface density of microalgae in soft underwater sediments and to infer their photosynthetic capacity. In lab studies, NIR imagery gives estimates of epipelon density that are strongly correlated with standard chlorophyll a (Chl a) assays using pigment extraction and fluorometry ($R_{\mathrm{adj}}^2$  = 0.70), but NIR imagery is better able to separate experimental treatments. In analyses of sediment samples from a lake, NIR imagery gives estimates of epipelon Chl a density that are strongly correlated to net ecosystem production (NEP). Near-infrared imagery also gives a fine-grained assessment of the spatial distribution of epipelon that helps to explain the relationship between epipelon density and NEP. Finally, images from an underwater NIR camera over the course of a wind disturbance event give estimates of the relative density of microalgae that is buried and is likely to be, at least temporarily, photosynthetically inactive. These results show that NIR imagery provides an easy and nondestructive method for sampling surface densities of microalgae which is particularly suitable for remote field locations and for educational settings in which students can generate results with cheap and robust equipment.