First trait-based characterization of Arctic ice meiofauna taxa

Trait-based approaches connect the traits of species to ecosystem functions to estimate the functional diversity of communities and how they may respond to environmental change. For the first time, we compiled a traits matrix across 11 traits for 28 species of Arctic ice meiofauna, including Copepoda (Subclass), Nematoda (Phylum), Acoela (Order), Rotifera (Phylum), and Cnidaria (Phylum). Over 50 years of pan-Arctic literature were manually reviewed, and trait categories were assigned to enable future trait–function connections within the threatened ice-associated ecosystem. Approximately two-thirds of the traits data were found at the genus or species level, ranging from 44% for Nematoda to 100% for Cnidaria. Ice meiofauna were shown to possess advantageous adaptations to the brine channel network within sea ice, including a majority with small body widths < 200 μm, high body flexibility, and high temperature and salinity tolerance. Diets were found to be diverse outside of the algal bloom season, with most organisms transitioning to ciliate-, omnivore-, or detritus-based diets. Eight species of the studied taxa have only been recorded within sea ice, while the rest are found in a mixture of sympagic–pelagic–benthic habitats. Twelve of the ice meiofauna species have been found with all life stages present in sea ice. Body width, temperature tolerance, and salinity tolerance were identified as traits with the largest research gaps and suffered from low-resolution taxonomic data. Overall, the compiled data show the degree to which ice meiofauna are adapted to spending all or portions of their lives within the ice

Hydrologic Modeling of Urban Development Scenarios and Low-Impact Design Systems on an Undisturbed Coastal Forested Watershed under Extreme Rainfall-Runoff Events and Hydro-Meteorological Conditions in a Changing Climate

Watershed 80 (WS80), a reference watershed located in the USDA Forest Service Santee Experimental Forest, has been undisturbed since 1937, including from the silviculture that has historically characterized the region. Therefore, the results from this study are assumed to serve as a baseline of the developmental behavior for similar watersheds along the Southeastern Coastal Plain. The purpose of this study was first to analyze and compare the outputs of two rainfall-runoff models, the NRCS program WinTR-55 and the USGS Regional Regression Equations (RREs), with historical data gathered from WS80 to examine which model most accurately fits existing peak flow data. An accurate sense of peak flows is crucial in both the conservation and planning of sites, as proper stormwater management and infrastructure preserve the integrity of both natural resources and humanmade structures. Second, the study sought to analyze the impact of hypothetical development on design peak flow rate with up to 15% watershed imperviousness using each model. Additionally, two hypothetical scenarios of low-impact design (LID) practices such as vegetative rooftops and permeable pavements on development within the watershed were examined using the Purdue University software L-THIA. The USGS RREs overpredicted peak flows by 84% at a 5-yr return period to 12% at a 100-yr return period. WinTR-55 underpredicted peak flows by 31% at a 5-yr return period to 52% at a 100-yr return period. Increases in impervious surfaces led to subsequent increases in modeled design peak flows, with the greatest post-development change in design peak flow rate occurring within the USGS model. Although results showed that neither the USGS nor WinTR-55 models accurately predicted the design peak flow data from the watershed, USGS predictions were closer to the observed values for 50-yr or higher return periods than that from WinTR-55. Though LID practices were only applied up to a hypothetical 15% of the watershed, when fully implemented they were estimated to exert a 98% reduction in runoff which translated to a total reduction in volume by 20% and depth by 16% as compared to traditional design counterparts. This hypothesized evidence indicates the merit for using LID practices for runoff management even in situations of low imperviousness

Seasonal dynamics of sea-ice protist and meiofauna in the northwestern Barents Sea

The rapid decline of Arctic sea ice makes understanding sympagic (ice-associated) biology a particularly urgent task. Here we studied the poorly known seasonality of sea-ice protist and meiofauna community composition, abundance and biomass in the bottom 30 cm of sea ice in relation to ice properties and ice drift trajectories in the northwestern Barents Sea. We expected low abundances during the polar night and highest values during spring prior to ice melt. Sea ice conditions and Chlorophyll a concentrations varied strongly seasonally, while particulate organic carbon concentrations were fairly stable throughout the seasons. In December to May we sampled growing first-year ice, while in July and August melting older sea ice dominated. Low sea-ice biota abundances in March could be related to the late onset of ice formation and short time period for ice algae and uni- and multicellular grazers to establish themselves. Pennate diatoms, such as Navicula spp. and Nitzschia spp., dominated the bottom ice algal communities and were present during all seasons. Except for May, ciliates, dinoflagellates, particularly of the order Gymnodiales, and small-sized flagellates were co-dominant. Ice meiofauna (here including large ciliates and foraminifers) was comprised mainly of harpacticoid copepods, copepod nauplii, rotifers, large ciliates and occasionally acoels and foraminifers, with dominance of omnivore species throughout the seasons. Large ciliates comprised the most abundant meiofauna taxon at all ice stations and seasons (50–90 %) but did not necessarily dominate the biomass. While ice melt might have released and reduced ice algal biomass in July, meiofauna abundance remained high, indicating different annual cycles of protist versus meiofauna taxa. In May highest Chlorophyll a concentrations (29.4 mg m− 2 ) and protist biomass (107 mg C m− 2 ) occurred, while highest meiofauna abundance was found in August (23.9 × 103 Ind. m− 2 ) and biomass in December (0.6 mg C m− 2 ). The abundant December ice biota community further strengthens the emerging notion of an active biota during the dark Arctic winter. The data demonstrated a strong and partially unexpected seasonality in the Barents Sea ice biota, indicating that changes in ice formation, drift and decay will significantly impact the functioning of the ice-associated ecosystem