Erin L. Hestir

Use of Hyperspectral Remote Sensing to Evaluate Efficacy of Aquatic Plant Management

Abstract Invasive aquatic weeds negatively affect biodiversity, fluvial dynamics, water quality, and water storage and conveyance for a variety of human resource demands. In Californias Sacramento–San Joaquin River Delta, one submersed species—Brazilian egeria—and one floating species—waterhyacinth—are actively managed to maintain navigable waterways. We monitored the spatial and temporal dynamics of these species and their communities in the Sacramento-San Joaquin River Delta using airborne hyperspectral data and assessed the effect of herbicide treatments used to manage these species from 2003 to 2007. Each year, submersed aquatic plant species occupied about 12% of the surface area of the Delta in early summer and floating invasive plant species occupied 2 to 3%. Since 2003, the coverage of submersed aquatic plants expanded about 500 ha, whereas the coverage of waterhyacinth was reduced. Although local treatments have reduced the coverage of submersed aquatic plants, Delta-wide cover has not been significantly reduced. Locally, multiyear treatments could decrease submersed aquatic plants spread, given that no residual plants outside the treated area were present. In contrast, the spread of waterhyacinth either has been constant or has decreased over time. These results show that (1) the objectives of the Egeria densa Control Program (EDCP) have been hindered until 2007 by restrictions imposed on the timing of herbicide applications; (2) submersed aquatic plants appeared to function as ecosystem engineers by enabling spread to adjacent areas typically subject to scouring action; (3) repeated herbicide treatment of waterhyacinth has resulted in control of the spread of this species, which also appears to have facilitated the spread of waterprimrose and floating pennywort. These results suggest that management of the Delta aquatic macrophytes may benefit by an ecosystem-level implementation of an Integrated Delta Vegetation Management and Monitoring Program, rather than targeting only two problematic species. Nomenclature: Brazilian egeria, Egeria densa Planch.; floating pennywort, Hydrocotyle ranunculoides L. f.; waterhyacinth, Eichhornia crassipes (Mart.) Solms.; waterprimrose, Ludwigia L. spp.

Classification Trees for Aquatic Vegetation Community Prediction From Imaging Spectroscopy

The goal of historic image classification using signature extension techniques is of widespread interest for remote sensing applications. Historic ground reference data for classifier training is frequently unavailable, necessitating unsupervised transfer learning techniques. Environmental and data variability over time create variable spectral target classes, creating a challenge for knowledge transfer. There is a need for robust classifiers that account for data with high variability and non-normal distributions, and can be successfully applied to unlabeled data; ensemble classification trees are one solution to this problem. With the goal of detecting submerged aquatic vegetation, we trained an ensemble classifier with one collection of 48 imaging spectroscopy flightlines from a single year (2008). We then tested its performance when applied to four years (2004-2007) of historic imaging spectroscopy of the same size over the same area. We validated the resulting classifications with corresponding historic ground reference data. Knowledge transfer success was varied, depending on which image year dataset was used to train the classifier. The 2008-trained classifier had the most stable performance when applied to historic image datasets: overall accuracies ranged from 78.8% to 85.9%. Detection of submerged aquatic vegetation was limited most by the percent cover of the canopy. Water column depth above the plant canopy did not have an effect on detection. The classifier was successful because the training dataset encompassed the range of variability of the study area and the historic datasets.

Image spectroscopy and stable isotopes elucidate functional dissimilarity between native and nonnative plant species in the aquatic environment

• Nonnative species may change ecosystem functionality at the expense of native species. Here, we examine the similarity of functional traits of native and nonnative submersed aquatic plants (SAP) in an aquatic ecosystem. • We used field and airborne imaging spectroscopy and isotope ratios of SAP species in the Sacramento-San Joaquin Delta, California (USA) to assess species identification, chlorophyll (Chl) concentration, and differences in photosynthetic efficiency. • Spectral separability between species occurs primarily in the visible and near-infrared spectral regions, which is associated with morphological and physiological differences. Nonnatives had significantly higher Chl, carotene, and anthocyanin concentrations than natives and had significantly higher photochemical reflectance index (PRI) and δ(13) C values. • Results show nonnative SAPs are functionally dissimilar to native SAPs, having wider leaf blades and greater leaf area, dense and evenly distributed vertical canopies, and higher pigment concentrations. Results suggest that nonnatives also use a facultative C(4) -like photosynthetic pathway, allowing efficient photosynthesis in high-light and low-light environments. Differences in plant functionality indicate that nonnative SAPs have a competitive advantage over native SAPs as a result of growth form and greater light-use efficiency that promotes growth under different light conditions, traits affecting system-wide species distributions and community composition.

Variation of energy and carbon fluxes from a restored temperate freshwater wetland and implications for carbon market verification protocols

Temperate freshwater wetlands are among the most productive terrestrial ecosystems, stimulating interest in using restored wetlands as biological carbon sequestration projects for greenhouse gas reduction programs. In this study, we used the eddy covariance technique to measure surface energy carbon fluxes from a constructed, impounded freshwater wetland during two annual periods that were 8 years apart: 2002–2003 and 2010–2011. During 2010–2011, we measured methane (CH4) fluxes to quantify the annual atmospheric carbon mass balance and its concomitant influence on global warming potential (GWP). Peak growing season fluxes of latent heat and carbon dioxide (CO2) were greater in 2002–2003 compared to 2010–2011. In 2002, the daily net ecosystem exchange reached as low as −10.6 g C m−2 d−1, which was greater than 3 times the magnitude observed in 2010 (−2.9 g C m−2 d−1). CH4 fluxes during 2010–2011 were positive throughout the year and followed a strong seasonal pattern, ranging from 38.1 mg C m−2 d−1 in the winter to 375.9 mg C m−2 d−1 during the summer. The results of this study suggest that the wetland had reduced gross ecosystem productivity in 2010–2011, likely due to the increase in dead plant biomass (standing litter) that inhibited the generation of new vegetation growth. In 2010–2011, there was a net positive GWP (675.3 g C m−2 yr−1), and when these values are evaluated as a sustained flux, the wetland will not reach radiative balance even after 500 years.

The case for a global inland water quality product

This paper argues for the development of a quantitative global inland water quality product based on satellite optical remote sensing. Water quality is a critical component of global fresh water security and ecosystem health, yet is often overlooked when global analyses of water security are undertaken. In the face of declining surface measurements and datasets across the globe, alternatives to conventional water quality measurement are required. The case for an optical remote sensing based inland water quality product is a strong one. Global products of ocean color and their dissemination infrastructure are operational and widely used, providing a framework for global inland products. Furthermore, coastal and inland water quality algorithms based on spectral inversion algorithms are now sufficiently mature to cope with the greater variability of inherent optical properties in these systems. While these algorithms provide the greatest promise for reliable, robust and simultaneous retrieval of several water quality variables across sensors, limited knowledge of the bio-optical properties of inland waters and limited validation currently prevent global implementation. Internationally coordinated efforts are required to accumulate representative bio-optical data to improve our understanding of the optical complexity and variability of inland waters.

Novel Species Interactions in a Highly Modified Estuary: Association of Largemouth Bass with Brazilian Waterweed Egeria densa

AbstractFrequent invasions in coastal ecosystems result in novel species interactions that have unknown ecological consequences. Largemouth Bass Micropterus salmoides and Brazilian waterweed Egeria densa are introduced species in the Sacramento–San Joaquin River Delta (the Delta) of California, a highly modified estuary. In this system, Brazilian waterweed and Largemouth Bass have seen marked increases in distribution and abundance in recent decades, but their association has not been specifically studied until now. We conducted a 2-year, bimonthly electrofishing survey with simultaneous sampling of water quality and submerged aquatic vegetation (SAV) biomass at 33 locations throughout the Delta. We used generalized linear mixed models to assess the relative influences of water temperature, conductivity, Secchi depth, and SAV biomass density on the abundance of both juvenile-sized and larger Largemouth Bass. Water temperature had a positive relationship with the abundance of both size-classes, but only ju...

Remote Sensing for Biodiversity

Remote sensing (RS)—taking images or other measurements of Earth from above—provides a unique perspective on what is happening on the Earth and thus plays a special role in biodiversity and conservation applications. The periodic repeat coverage of satellite-based RS is particularly useful for monitoring change and so is essential for understanding trends, and also provides key input into assessments, international agreements, and conservation management. Historically, RS data have often been expensive and hard to use, but changes over the last decade have resulted in massive amounts of global data being available at no cost, as well as significant (if not yet complete) simplification of access and use. This chapter provides a baseline set of information about using RS for conservation applications in three realms: terrestrial, marine, and freshwater. After a brief overview of the mechanics of RS and how it can be applied, terrestrial systems are discussed, focusing first on ecosystems and then moving on to species and genes. Marine systems are discussed next in the context of habitat extent and condition and including key marine-specific challenges. This is followed by discussion of the special considerations of freshwater habitats such as rivers, focusing on freshwater ecosystems, species, and ecosystem services.

A spaceborne visible-NIR hyperspectral imager for coastal phenology

The temporal variability, or phenology, of animals and plants in coastal zone and marine habitats is a function of geography and climatic conditions, of the chemical and physical characteristics of each particular habitat, and of interactions between these organisms. These conditions play an important role in defining the diversity of life. The quantitative study of phenology is required to protect and make wise use of wetland and other coastal resources. We describe a low cost space-borne sensor and mission concept that will enable such studies using high quality, broad band hyperspectral observations of a wide range of habitats at Landsat-class spatial resolution and with a 3 day or better revisit rate, providing high signal to noise observations for aquatic scenes and consistent view geometry for wetland and terrestrial vegetation scenes.

Inland water quality monitoring in Australia

Consistent and accurate information on inland water quality over wider areas of the Australian continent are required to assess current condition and trends in response to key environmental and climatic impacts. Optical remote sensing offers a method to objectively assess this over multiple spatial scales provided retrieval algorithms are accurate. Here, we present the results of initial research aimed at exploring the optical variability in Australian inland waters and of linear matrix inversion algorithms applied to both in situ reflectance spectra and high resolution satellite data to retrieve water inland water quality parameters. In situ sampling reveals a high degree of optical variability both within and between lakes across the regions sampled with regional patterns evident; sub-tropical and tropical lakes exhibited greater optical complexity than deep lakes in mid-latitude regions. Clustering analysis indicated the presence of 8 different optical water types in the water bodies measured. The ability of the linear matrix inversion algorithm to map water quality, tested on in situ reflectance and WorldView2 image datasets, showed relative accuracy when parameter sets were sufficient to achieve algorithm closure. Improved algorithm parameterization will be required to account for the high degree in spatial and temporal optical variability observed in Australian inland waters.