Figure 4. A. Observed, volume normalized total particle numbers from 9 casts taken at different times of the day at ETNP station P2. B. Calculated particle size distribution slopes of those particles. These data have not been binned by depth in order to better show sample to sample variability. Horizontal blue lines indicate the top and bottom of the ODZ, while the horizontal green line indicates the base of the photic zone. Hour corresponds to local, Mexican General Standard, time. Particles are binned into 5 m depth increments.

Estimated particle flux sometimes increases with depth in the ODZ core

Optimization found best agreement between particle flux measured by traps, and UVP estimated particle flux when per particle flux is fit by the equation
Flux = (133 μ mol C / m^2/day) = 133 * Size (mm) ^2.00 (Eqn 5)
This equation represents an empirical relationship between particle flux from traps and particle size measured by UVP. Applying this fit to the UVP data resulted in a UVP predicted flux profile that broadly fit the expected trap observed flux profiles (Figure 3).
Particle flux profiles, predicted from the above particle size abundances and fit, varied between casts between the base of the photic zone and 500 m (Figure 5A-5B). To examine the rate of change of flux and to identify regions and time points where flux appeared to increase with depth, we examined the rate of change of flux. This rate of change was fifth root transformed to normalize the data and to allow us to focus on the cases where flux attenuation varied about zero, since we were interested in identifying factors that related to whether flux was positive or negative. Between 250 m and 500 m, particle flux appeared to increase on some, but not all, casts, while attenuating slowly on the other casts (Figure 5C). Below 500 m, there were not enough casts to measure variability between casts.
The general additive model that quantified how the of change of flux between 250 m and 500 m varied with depth, decimal study day and decimal hour found that depth (p = 0.061) and hour of the day (p = 0.196) did not statistically associate with the fifth root transformed rate of change of flux while day of study did (p = 0.019, R2 = 0.264, Figure S6). There were generally increases in flux over this region towards the beginning and end of the sampling period and decreases in flux nearer to day 10 (Figure S6B). A general additive model that looked only at the relationship between study day and rate of change of flux (fifth root transformed) in this region suggested that day accounted for 14% of the variance in this value, as determined by adjusted R­­2 (p = 0.040). If the fifth root transformation was not applied to the rate of change of flux, there was a statistically significant relationship between depth and rate of change (p = 0.001), but not study day (p = 0.062) or hour (p = 0.719, R2 = 0.341). This pattern indicated that, without the transformation, any temporal signal is swamped by the substantial changes in rate of change in depth, with shallower depths losing flux faster than deeper ones.