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The concentration of particulate organic nitrogen (PON) in seawater plays a central role in ocean biogeochemistry. The limited availability of PON data obtained directly from in situ sampling methods hinders development of a thorough understanding and characterization of spatiotemporal variability in PON and associated source and sink processes within the global ocean. Measurements of inherent optical properties (IOPs) of seawater, which can be performed over extended temporal and spatial scales from various in situ and remote-sensing platforms, represent a valuable approach to address this gap. We present the analysis of relationships between PON and particulate IOPs, including the absorption coefficients of total particulate matter, ap(λ); phytoplankton, aph(λ); and non-algal particles, ad(λ), as well as the particulate backscattering coefficient, bbp(λ). This analysis is based on an extensive field dataset of concurrent measurements of PON and particulate IOPs in the near-surface oceanic waters and shows that reasonably strong relationships hold across a range of diverse oceanic and coastal marine environments. The coefficients ap(λ) and aph(λ) show the best ability to serve as PON proxies over a broad range of PON from open-ocean oligotrophic to coastal waters. The particulate backscattering coefficient can also provide a good proxy for PON in open-ocean environments. The relationships presented here demonstrate a promising means to assess PON from optical measurements conducted from spaceborne and airborne remote-sensing platforms and in situ autonomous platforms. In support of this potential application, we provide the relationships between PON and spectral IOPs at light wavelengths consistent with those used by satellite ocean color sensors.

The magnitude and spectral shape of the optical backscattering coefficient of particles, b bp(λ), is being increasingly used to infer information about the particles present in seawater. Relationships between b bp and particle properties in the Arctic are poorly documented, and may differ from other oceanic regions which contribute the majority of data used to develop and parameterize optical models. We utilize recent field measurements from the Chukchi and Beaufort Seas to examine relationships between the spectral backscattering coefficient of particles in seawater and the mass concentration, bulk composition, and size distribution of the suspended particle assemblage. The particle backscattering coefficient spanned six orders of magnitude from the relatively clear waters of the Beaufort Sea to extremely turbid waters on the Mackenzie shelf. This coefficient was highly correlated with the mass concentration of particles, and to a lesser extent with other measures of concentration such as particulate organic carbon or chlorophyll a. Increased backscattering and high mass-specific b bp(λ) was associated with mineral-rich assemblages that tended to exhibit steeper size distributions, while reduced backscattering was associated with organic-dominated assemblages having a greater contribution of large particles. Our results suggest that algorithms which employ composition-specific relationships can lead to improved estimates of particle mass concentration from backscattering measurements. In contrast to theoretical models, however, we observe no clear relationship between the spectral slope of b bp(λ) and the slope of the particle size distribution in this environment.

As the Western Antarctic Peninsula (WAP) region responds to a warmer climate, the impacts of glacial meltwater on the Southern Ocean are expected to intensify. The Antarctic Peninsula fjord system offers an ideal system to understand meltwater's properties, providing an extreme in the meltwater's spatial gradient from the glacio-marine boundary to the WAP continental shelf. Glacial meltwater discharge in Arctic and Greenland fjords is typically characterized as relatively lower temperature, fresh and with high turbidity. During two cruises conducted in December 2015 and April 2016 in Andvord Bay, we found a water lens of low salinity and low temperature along the glacio-marine interface. Oxygen isotope ratios identified this water lens as a mixture of glacial ice and deep water in Gerlache Strait suggesting this is glacial meltwater. Conventional hydrographic measurements were combined with optical properties to effectively quantify its spatial extent. Fine suspended sediments associated with meltwater (nanoparticles of ~ 5nm) had a significant impact on the underwater light field and enabled the detection of meltwater characteristics and spatial distribution. In this study, we illustrate that glacial meltwater in Andvord Bay alters the inherent and apparent optical properties of the water column, and develop statistical models to predict the meltwater content from hydrographic and optical measurements. The predicted meltwater fraction is in good agreement with in-situ values. These models offer a potential for remote sensing and high-resolution detection of glacial meltwater in Antarctic waters. Furthermore, the possible influence of meltwater on phytoplankton abundance in the surface is highlighted; a significant correlation is found between meltwater fraction and chlorophyll concentration.

An extensive data set of measurements within the Chukchi and Beaufort Seas is used to characterize the optical properties of seawater associated with different phytoplankton communities. Hierarchical cluster analysis of diagnostic pigment concentrations partitioned stations into four distinct surface phytoplankton communities based on taxonomic composition and average cell size. Concurrent optical measurements of spectral absorption and backscattering coefficients and remote-sensing reflectance were used to characterize the magnitudes and spectral shapes of seawater optical properties associated with each phytoplankton assemblage. The results demonstrate measurable differences among communities in the average spectral shapes of the phytoplankton absorption coefficient. Similar or smaller differences were also observed in the spectral shapes of nonphytoplankton absorption coefficients and the particulate backscattering coefficient. Phytoplankton on average, however, contributed only 25% or less to the total absorption coefficient of seawater. Our analyses indicate that the interplay between the magnitudes and relative contributions of all optically significant constituents generally dampens any influence of varying phytoplankton absorption spectral shapes on the total absorption coefficient, yet there is still a marked discrimination observed in the spectral shape of the ratio of the total backscattering to total absorption coefficient and remote-sensing reflectance among the phytoplankton assemblages. These spectral variations arise mainly from differences in the bio-optical environment in which specific communities were found, as opposed to differences in the spectral shapes of phytoplankton optical properties per se. These results suggest potential approaches for the development of algorithms to assess phytoplankton community composition from measurements of seawater optical properties in western Arctic waters.

We develop an optical classification of marine particle assemblages from an extensive dataset of particle optical properties collected in the Chukchi and Beaufort Seas. Hierarchical cluster analysis of the spectral particulate backscattering-to-absorption ratio partitioned the dataset into seven optically-distinct clusters of particle assemblages, each associated with different characteristics of particle concentration, composition, and phytoplankton taxonomic composition and size. Three phytoplankton-dominated clusters were identified. One was characterized by small-sized phytoplankton that are typically associated with regenerated production, and comprised samples from the subsurface chlorophyll-a maximum in oligotrophic waters of the Beaufort Sea. The other two clusters represented diatom-dominated particle assemblages in turbid shelf waters with differing contributions of photoprotective pigments. Such situations are generally associated with significant new production. Two clusters were dominated by organic nonalgal material, one representing clear waters off the shelf, the other representative of post-diatom bloom conditions in the Chukchi Sea. Another distinct cluster represented mineral-dominated particle assemblages that were observed in the Colville and Mackenzie River plumes and near the seafloor. Finally, samples in a cluster of mixed particle composition were scattered throughout all locations. Optical classification improved performance of predictive bio-optical relationships. These results demonstrate a capability to discriminate distinct assemblages of suspended particles associated with specific ecological conditions from hyperspectral measurements of optical properties, and the potential for identification of ecological provinces at synoptic time and space scales from optical sensors. Analogous analysis of multispectral optical data strongly reduced this capability.

The capability to estimate the oceanic particulate organic carbon concentration (POC) from optical measurements is crucial for assessing the dynamics of this carbon reservoir and the capacity of the biological pump to sequester atmospheric carbon dioxide in the deep ocean. Optical approaches are routinely used to estimate oceanic POC from the spectral particulate backscattering coefficient b bp , either directly (e.g., with backscattering sensors on underwater platforms like BGC-Argo floats) or indirectly (e.g., with satellite remote sensing). However, the reliability of algorithms which relate POC to b bp is typically limited due to the complexity of interactions between light and natural assemblages of marine particles, which depend on variations in particle concentration, composition, and size distribution. This study expands on our previous work by analysis of an extended field dataset created with judicious data inclusion criteria with the aim to provide POC algorithms for multiple light wavelengths of measured b bp , which can be useful for applications with in situ optical sensors as well as above-water active or passive measurement systems. We describe an improved empirical multivariable approach to estimate POC from simultaneous measurements of b bp and chlorophyll-a concentration (Chla) to better account for the effects of variable particle composition on the relationship between POC and b bp . The multivariable regression models are formulated using a relatively large dataset of coincident measurements of POC, b bp , and Chla, including surface and subsurface data from the Atlantic, Pacific, Arctic, and Southern Oceans. We show that the multivariable algorithm provides reduced uncertainty of estimated POC across diverse marine environments when compared with a traditional univariate algorithm based on only b bp . We also propose an improved formulation of univariate algorithm based on b bp alone. Finally, we examine performance of several algorithms to estimate POC using our dataset as well as a dataset consisting of optical measurements from BGC-Argo floats and traditional POC measurements collected during a coincident research cruise in the Atlantic Ocean.

AIM: We investigated the effects of disease on the local abundances and distributions of species at continental scales by examining the impacts of white‐nose syndrome, an infectious disease of hibernating bats, which has recently emerged in North America. LOCATION: North America and Europe. METHODS: We used four decades of population counts from 1108 populations to compare the local abundances of bats in North America before and after the emergence of white‐nose syndrome to the situation in Europe, where the disease is endemic. We also examined the probability of local extinction for six species of hibernating bats in eastern North America and assessed the influence of winter colony size prior to the emergence of white‐nose syndrome on the risk of local extinction. RESULTS: White‐nose syndrome has caused a 10‐fold decrease in the abundance of bats at hibernacula in North America, eliminating large differences in species abundance patterns that existed between Europe and North America prior to disease emergence. White‐nose syndrome has also caused extensive local extinctions (up to 69% of sites in a single species). For five out of six species, the risk of local extinction was lower in larger winter populations, as expected from theory, but for the most affected species, the northern long‐eared bat (Myotis septentrionalis), extinction risk was constant across winter colony sizes, demonstrating that disease can sometimes eliminate numerical rarity as the dominant driver of extinction risk by driving both small and large populations extinct. MAIN CONCLUSIONS: Species interactions, including disease, play an underappreciated role in macroecological patterns and influence broad patterns of species abundance, occurrence and extinction.

In midsummer, diatoms have taken advantage of thinning ice cover to feed in nutrient-rich waters. Phytoplankton blooms over Arctic Ocean continental shelves are thought to be restricted to waters free of sea ice. Here, we document a massive phytoplankton bloom beneath fully consolidated pack ice far from the ice edge in the Chukchi Sea, where light transmission has increased in recent decades because of thinning ice cover and proliferation of melt ponds. The bloom was characterized by high diatom biomass and rates of growth and primary production. Evidence suggests that under-ice phytoplankton blooms may be more widespread over nutrient-rich Arctic continental shelves and that satellite-based estimates of annual primary production in these waters may be underestimated by up to 10-fold.

Measurements of the particulate volume scattering function, βp(ψ), at light wavelength of 532 nm, particle size distribution, PSD, and several metrics of particulate concentration and composition were made on eight contrasting seawater samples from nearshore and coastal oceanic environments including river estuary and offshore locations. Both βp(ψ) and PSDs were measured on original (unfiltered) samples and particle sizefractionated samples obtained through filtration using mesh filters with pore sizes of 5 and 20 μm. We present results based on direct size-fractionated measurements and data adjusted for imperfect fractionation, which provide insights into the roles played by particle size and composition in angle-resolved light scattering produced by highly variable natural assemblages of aquatic particles. Despite intricate interplay between the effects of particle size and composition, small particles (< 5 μm in size) consistently produced a major or dominant contribution (~ 50–80%) to the particulate backscattering coefficient, bbp, in organic, either phytoplankton or nonalgal, dominated samples regardless of significant variations in PSD between these samples. The notable exception was a sample dominated by large-celled diatoms from microphytoplankton size range, which exemplifies a scenario when large particles (> 20 μm) can produce a considerable contribution (~ 40%) to b bp. We also observed a trend for inorganic-dominated samples exhibiting consistently lower contributions (~ 30–40%) of small particles to b bp. The particle size-based budget for the particulate scattering coefficient, b p, indicates a significant decrease in the role of small particles accompanied by an increase in the role of larger particles compared to the b bp budget.

Seasonal patterns in pathogen transmission can influence the impact of disease on populations and the speed of spatial spread. Increases in host contact rates or births drive seasonal epidemics in some systems, but other factors may occasionally override these influences. White-nose syndrome, caused by the emerging fungal pathogen Pseudogymnoascus destructans, is spreading across North America and threatens several bat species with extinction. We examined patterns and drivers of seasonal transmission of P. destructans by measuring infection prevalence and pathogen loads in six bat species at 30 sites across the eastern United States. Bats became transiently infected in autumn, and transmission spiked in early winter when bats began hibernating. Nearly all bats in six species became infected by late winter when infection intensity peaked. In summer, despite high contact rates and a birth pulse, most bats cleared infections and prevalence dropped to zero. These data suggest the dominant driver of seasonal transmission dynamics was a change in host physiology, specifically hibernation. Our study is the first, to the best of our knowledge, to describe the seasonality of transmission in this emerging wildlife disease. The timing of infection and fungal growth resulted in maximal population impacts, but only moderate rates of spatial spread.