A Community EcoHealth Index from EnviroAtlas Ecosystem Services Metrics.

Human health is inextricably tied to ecosystem services (ES), including those associated with greenspace in urban communities. EnviroAtlas provides close to 100 maps of ES metrics based on high-resolution land cover data in featured communities across the contiguous United States. Using selected EnviroAtlas ES metrics, a Community EcoHealth Index (CEHI) was created based on an ecohealth framework including health promotion and hazard buffering domains. Aggregation of eight selected ES metrics in these domains entailed a weighted distance measure, where objective, data-driven weights were generated. CEHI was calculated by Census Block Group (CBG) at both the local level and the national level for 22 EnviroAtlas communities. Results were mapped to show one- to five-star CBGs or neighborhoods within and across all 22 featured communities. At the national level, CEHI favors communities in forested ecoregions. The local version of CEHI is more appropriate to inform social, economic, and environmental decision-making for improving community ES associated with human health.

Leveraging Big Data Towards Functionally-Based, Catchment Scale Restoration Prioritization.

The persistence of freshwater degradation has necessitated the growth of an expansive stream and wetland restoration industry, yet restoration prioritization at broad spatial extents is still limited and ad-hoc restoration prevails. The River Basin Restoration Prioritization tool has been developed to incorporate vetted, distributed data models into a catchment scale restoration prioritization framework. Catchment baseline condition and potential improvement with restoration activity is calculated for all National Hydrography Dataset stream reaches and catchments in North Carolina and compared to other catchments within the river subbasin to assess where restoration efforts may best be focused. Hydrologic, water quality, and aquatic habitat quality conditions are assessed with peak flood flow, nitrogen and phosphorus loading, and aquatic species distribution models. The modular nature of the tool leaves ample opportunity for future incorporation of novel and improved datasets to better represent the holistic health of a watershed, and the nature of the datasets used herein allow this framework to be applied at much broader scales than North Carolina.

Ecuador's mangrove forest carbon stocks: a spatiotemporal analysis of living carbon holdings and their depletion since the advent of commercial aquaculture.

In this paper we estimate the living carbon lost from Ecuador's mangrove forests since the advent of export-focused shrimp aquaculture. We use remote sensing techniques to delineate the extent of mangroves and aquaculture at approximately decadal periods since the arrival of aquaculture in each Ecuadorian estuary. We then spatiotemporally calculate the carbon values of the mangrove forests and estimate the amount of carbon lost due to direct displacement by aquaculture. Additionally, we calculate the new carbon stocks generated due to mangrove reforestation or afforestation. This research introduces time and LUCC (land use / land cover change) into the tropical forest carbon literature and examines forest carbon loss at a higher spatiotemporal resolution than in many earlier analyses. We find that 80 percent, or 7,014,517 t of the living carbon lost in Ecuadorian mangrove forests can be attributed to direct displacement of mangrove forests by shrimp aquaculture. We also find that IPCC (Intergovernmental Panel on Climate Change) compliant carbon grids within Ecuador's estuaries overestimate living carbon levels in estuaries where substantial LUCC has occurred. By approaching the mangrove forest carbon loss question from a LUCC perspective, these findings allow for tropical nations and other intervention agents to prioritize and target a limited set of land transitions that likely drive the majority of carbon losses. This singular cause of transition has implications for programs that attempt to offset or limit future forest carbon losses and place value on forest carbon or other forest good and services.

Highly stable surface functionalization of microgas chromatography columns using layer-by-layer self-assembly of silica nanoparticles.

A controllable and high-yield surface functionalization of silicon microchannels using layer-by-layer (LbL) self-assembly of SiO2 nanoparticles (SNPs) is presented. The application of SNPs (45 nm average diameter) coating as a stationary phase for chromatographic separation is also demonstrated with surface functionalization using chloroalkylsilanes. This method facilitates a simple, low-cost, and parallel processing scheme that also provides homogeneous and stable nanoparticle-based stationary phases with ease of control over the coating thickness. The SNP-functionalized microfabricated columns with either single capillary channels (1 m long, 150 µm wide, 240 µm deep) or very narrow multicapillary channels (25 cm long, 30 µm wide, 240 µm deep, 16 parallel channels) successfully separated a multicomponent gas mixture with a wide range of boiling points with high reproducibility.