Abstract. Biochemical transformations of organic matter (OM) are a primary driver of river corridor biogeochemistry, thereby modulating ecosystem processes at
local to global scales. OM transformations are driven by diverse biotic and abiotic processes, but we lack knowledge of how the diversity of those
processes varies across river corridors and across surface and subsurface components of river corridors. To fill this gap we quantified the number
of putative biotic and abiotic transformations of organic molecules across diverse river corridors using ultra-high-resolution mass
spectrometry. The number of unique transformations is used here as a proxy for the diversity of biochemical processes underlying observed profiles
of organic molecules. For this, we use public data spanning the contiguous United States (ConUS) from the Worldwide Hydrobiogeochemical Observation
Network for Dynamic River Systems (WHONDRS) consortium. Our results show that surface water OM had more biotic and abiotic transformations than OM
from shallow hyporheic zone sediments (1–3 cm depth). We observed substantially more biotic than abiotic transformations, and the numbers of biotic
and abiotic transformations were highly correlated with each other. We found no relationship between the number of transformations in surface water
and sediments and no meaningful relationships with latitude, longitude, or climate. We also found that the composition of transformations in
sediments was not linked with transformation composition in adjacent surface waters. We infer that OM transformations represented in surface water
are an integrated signal of diverse processes occurring throughout the upstream catchment. In contrast, OM transformations in sediments likely
reflect a narrower range of processes within the sampled volume. This indicates decoupling between the processes influencing surface water and
sediment OM, despite the potential for hydrologic exchange to homogenize OM. We infer that the processes influencing OM transformations and the
scales at which they operate diverge between surface water and sediments.
In northern climates, locating overwintering fish can be very challenging due to thick ice cover. Areas near the coast of the Beaufort Sea provide valuable overwintering habitat for both resident and anadromous fish species; identifying them and understanding their use of overwintering areas is of special interest. Synthetic aperture radar (SAR) imagery from two spaceborne satellites was examined as an alternative to radiotelemetry for identifying anadromous fish overwintering. The presence of water and ice were sampled at 162 sites, and fish were sampled at 16 of these sites. From SAR imagery alone, we successfully identified large pools inhabited by overwintering fish in the ice‐covered Sagavanirktok River, Alaska. In addition, the imagery was able to identify all of the larger pools (mean minimum length = 138 m, SD = 131, range = 15–470 m) of water located by field sampling. The effectiveness of SAR in identifying these pools varied from 31% to 100%, depending on imagery polarization, the incidence angle range, and the orbit. Horizontal transmit—vertical receive (HV) polarization appeared to be best. The accuracy of SAR was also assessed at a finer pixel‐by‐pixel scale (30 × 30 m). The best correspondence at this finer scale was obtained with an image having HV polarization. The levels of agreement ranged from 54% to 69%. The presence of broad whitefish Coregonus nasus (the only anadromous species present) was associated with salinity and pool size (estimated with SAR imagery); fish were more likely to be found in larger pools with low salinity. This research illustrates that SAR imaging has great potential for identifying under‐ice overwintering areas of riverine fish. These techniques should allow managers to identify critical overwintering areas more easily and at lower cost than traditional techniques permit.
This study examines maritime routes between ports along the Atlantic coast of the US, utilising Automated Identification System (AIS) data for the years 2010 through 2012. The delineation of vessel routes conducted in this study was motivated by development planned for offshore Wind Energy Areas (WEAs) along the Atlantic coast of the US and the need to evaluate the effect of these development areas on commercial shipping. To this end, available AIS data were processed to generate commercial vessel tracks for individual vessels, though cargo vessels are the focus in this study. The individual vessel tracks were sampled at transects placed along the Atlantic coast. The transect samples were analysed and partitioned by voyages between Atlantic ports to facilitate computation of vessel routes between ports. The route boundary analysis utilised a definition from UK guidance in which routes' boundaries encompassed 95% of the vessel traffic between ports. In addition to delineating route boundaries, we found multi-modal transverse distributions of vessels for well-travelled routes, which indicated preference for lanes of travel within the delineated routes.
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