Quantifying structural physical habitat attributes using LIDAR and hyperspectral imagery

Structural physical habitat attributes include indices of stream size, channel gradient, substrate size, habitat complexity, and riparian vegetation cover and structure. The Environmental Monitoring and Assessment Program (EMAP) is designed to assess the status and trends of ecological resources at different scales. High-resolution remote sensing provides unique capabilities in detecting a variety of features and indicators of environmental health and condition. LIDAR is an airborne scanning laser system that provides data on topography, channel dimensions (width, depth), slope, channel complexity (residual pools, volume, morphometric complexity, hydraulic roughness), riparian vegetation (height and density), dimensions of riparian zone, anthropogenic alterations and disturbances, and channel and riparian interaction. Hyperspectral aerial imagery offers the advantage of high spectral and spatial resolution allowing for the detection and identification of riparian vegetation and natural and anthropogenic features at a resolution not possible with satellite imagery. When combined, or fused, these technologies comprise a powerful geospatial data set for assessing and monitoring lentic and lotic environmental characteristics and condition.     

Data fusion modeling for groundwater systems

Engineering projects involving hydrogeology are faced with uncertainties because the earth is heterogeneous, and typical data sets are fragmented and disparate. In theory, predictions provided by computer simulations using calibrated models constrained by geological boundaries provide answers to support management decisions, and geostatistical methods quantify safety margins. In practice, current methods are limited by the data types and models that can be included, computational demands, or simplifying assumptions. Data Fusion Modeling (DFM) removes many of the limitations and is capable of providing data integration and model calibration with quantified uncertainty for a variety of hydrological, geological, and geophysical data types and models. The benefits of DFM for waste management, water supply, and geotechnical applications are savings in time and cost through the ability to produce visual models that fill in missing data and predictive numerical models to aid management optimization. DFM has the ability to update field-scale models in real time using PC or workstation systems and is ideally suited for parallel processing implementation. DFM is a spatial state estimation and system identification methodology that uses three sources of information: measured data, physical laws, and statistical models for uncertainty in spatial heterogeneities. What is new in DFM is the solution of the causality problem in the data assimilation Kalman filter methods to achieve computational practicality. The Kalman filter is generalized by introducing information filter methods due to Bierman coupled with a Markov random field representation for spatial variation. A Bayesian penalty function is implemented with Gauss–Newton methods. This leads to a computational problem similar to numerical simulation of the partial differential equations (PDEs) of groundwater. In fact, extensions of PDE solver ideas to break down computations over space form the computational heart of DFM. State estimates and uncertainties can be computed for heterogeneous hydraulic conductivity fields in multiple geological layers from the usually sparse hydraulic conductivity data and the often more plentiful head data. Further, a system identification theory has been derived based on statistical likelihood principles. A maximum likelihood theory is provided to estimate statistical parameters such as Markov model parameters that determine the geostatistical variogram. Field-scale application of DFM at the DOE Savannah River Site is presented and compared with manual calibration. DFM calibration runs converge in less than 1 h on a Pentium Pro PC for a 3D model with more than 15,000 nodes. Run time is approximately linear with the number of nodes. Furthermore, conditional simulation is used to quantify the statistical variability in model predictions such as contaminant breakthrough curves.     

Predictors of specialist avifaunal decline in coastal marshes

Coastal marshes are one of the world's most productive ecosystems. Consequently, they have been heavily used by humans for centuries, resulting in ecosystem loss. Direct human modifications such as road crossings and ditches and climatic stressors such as sea‐level rise and extreme storm events have the potential to further degrade the quantity and quality of marsh along coastlines. We used an 18‐year marsh‐bird database to generate population trends for 5 avian species (Rallus crepitans, Tringa semipalmata semipalmata, Ammodramus nelsonii subvirgatus, Ammodramus caudacutus, and Ammodramus maritimus) that breed almost exclusively in tidal marshes, and are potentially vulnerable to marsh degradation and loss as a result of anthropogenic change. We generated community and species trends across 3 spatial scales and explored possible drivers of the changes we observed, including marsh ditching, tidal restriction through road crossings, local rates of sea‐level rise, and potential for extreme flooding events. The specialist community showed negative trends in tidally restricted marshes (?2.4% annually from 1998 to 2012) but was stable in unrestricted marshes across the same period. At the species level, we found negative population trends in 3 of the 5 specialist species, ranging from ?4.2% to 9.0% annually. We suggest that tidal restriction may accelerate degradation of tidal marsh resilience to sea‐level rise by limiting sediment supply necessary for marsh accretion, resulting in specialist habitat loss in tidally restricted marshes. Based on our findings, we predict a collapse of the global population of Saltmarsh Sparrows (A. caudacutus) within the next 50 years and suggest that immediate conservation action is needed to prevent extinction of this species. We also suggest mitigation actions to restore sediment supply to coastal marshes to help sustain this ecosystem into the future.     

EFFECTS OF CONTROLLED DRAINAGE ON STORM EVENT HYDROLOGY IN A LOBLOLLY PINE PLANTATION1

ABSTRACT: A paired watershed approach was utilized to study the effects of three water management regimes on storm event hydrology in three experimental watersheds in a drained loblolly pine (Pinus taeda L.) plantation in eastern North Carolina. The regimes were: (1) conventional drainage, (2) controlled drainage (CD) to reduce outflows during spring fish recruitment, and (3) controlled drainage to reduce outflows and conserve water during the growing season. Data from two pit‐treatment years and three years of CD treatment with raised weirs at the watershed outlet are presented. CD treatment resulted in rises in water table elevations during the summer. But the rises were small and short‐lived due to increased evapotranspiration (ET) rates as compared to the spring treatment with lower ET demands. CD treatment had no effect on water tables deeper than 1.3 m. CD treatments, however, significantly (α= 0.05) reduced the stoning outflows for all events, and peak outflow rates for most of the events depending upon the outlet weir level. In some events, flows did not occur at all in watersheds with CD. When event outflows occurred, duration of the event was sharply reduced because of reduced effective ditch depth. Water table depth at the start of an event influenced the effect of CD treatment on storm event hydrology.     

Use of isotopic analysis of vertebrae in reconstructing ontogenetic feeding ecology in white sharks

We conducted stable 13C and 15N analysis on white shark vertebrae and demonstrated that incremental analysis of isotopes along the radius of a vertebral centrum produces a chronological record of dietary information, allowing for reconstruction of an individual's trophic history. Isotopic data showed significant enrichments in 15N with increasing sampling distance from the centrum center, indicating a correlation between body size and trophic level. Additionally, isotopic values verified two distinct ontogenetic trophic shifts in the white shark: one following parturition, marking a dietary switch from yolk to fish; and one at a total length of >341 cm, representing a known diet shift from fish to marine mammals. Retrospective trophic-level reconstruction using vertebral tissue will have broad applications in future studies on the ecology of threatened, endangered, or extinct species to determine life-long feeding patterns, which would be impossible through other methods.     

Characterization of polycyclic aromatic hydrocarbons in urban stormwater runoff flowing into the tidal Anacostia River, Washington, DC, USA

To investigate the sources, fate, and transport dynamics of PAHs (polycyclic aromatic hydrocarbons) in stormwater runoff that is a leading source of pollution in urban watersheds, storm and base flow samples were collected in six branches along the lower Anacostia River. PAHs in storm flow (1510-12,500 ng/L) were significantly enriched in the particle phase, which accounted for 68-97% of the total PAHs. It suggests that reducing particles in stormwater using post-treatment system would decrease PAHs considerably. The solid-water distribution coefficients (KD) of PAHs in the storm flow samples were up to 340 times higher than predicted values. A greater portion of high molecular weight PAHs and their distribution patterns indicate higher contribution of automobile originated pyrogenic PAHs. Total suspended solids in storm flow had a positive relationship with flow rates and exceeded benchmark level for the protection of aquatic biota in some samples.