Application of underwater videography to characterize seagrass habitats in Little Egg Harbor, New Jersey.
KEY WORDS: Underwater videography, aerial platforms, benthic habitat imaging, seagrasses, Little Egg Harbor.
Eutrophication poses the most serious threat to the long-term ecosystem health of the Barnegat Bay--Little Egg Harbor Estuary (Kennish 2001a, 2002; BBNEP, 2005). Nutrient enrichment and associated organic carbon loading in this shallow, lagoon-type estuary have been linked to an array of cascading environmental problems such as increased micro- and macroalgal growth, harmful algal blooms (HABs), bacterial and viral pathogens, high turbidity, altered benthic invertebrate communities, impacted harvestable fisheries, and loss of essential habitat (e.g., seagrass and shellfish beds) (Kennish, 2001b). The net insidious effect of progressive eutrophication is the potential for the permanent alteration of biotic communities and ongoing ecosystem-level impacts. The Barnegat Bay--Little Egg Harbor Estuary is classified as a highly eutrophic estuary, and because it is shallow, poorly flushed, and bordered by highly developed watershed areas, it is particularly susceptible to the effects of nutrient loading and other anthropogenic stressors. Consequently, monitoring programs must continue to assess priority indicators of eutrophication and associated water quality changes for effective long-term management of the system.
Seagrass beds comprise critical habitat in the Barnegat Bay--Little Egg Harbor Estuary, supporting many benthic invertebrate populations, fish, waterfowl, and other organisms and serving as a key indicator of water quality conditions and ecosystem health (Kennish, 2001a), vital roles demonstrated in other coastal bays as well (Corbett et al., 2000). They form an important structural component in an otherwise barren sandy bottom of the estuary (BBNEP, 2005). These beds are also critical to the survival of bay scallops (Argopecten irradians) in the system. Recurring phytoplankton and benthic macroalgal blooms reduce light availability for seagrass growth (Dennison et al., 1989, 1993; Bricelj and Lonsdale, 1997; Lathrop et al., 2001), and acute light attenuation can markedly reduce seagrass survivorship (Bortone, 2000). In addition, brown tide (Aureococcus anophagefferans) blooms may significantly increase bay scallop mortality (Bologna et al., 2001; Gastrich and Wazniak, 2002). The result is often a substantial decline in seagrass areal coverage and the elimination of essential habitat for bay scallops, hard clams (Mercenaria mercenaria), and other organisms. During the past two decades, the Barnegat Bay--Little Egg Harbor Estuary has been the site of increasing frequency and magnitude of phytoplankton and benthic macroalgal blooms. Brown tide blooms have commonly occurred in the estuary since 1995 (Kennish 2001a; BBNEP, 2005).
Most of the seagrass beds in New Jersey (75%) occur in the Barnegat Bay--Little Egg Harbor Estuary, covering an area of more than 6,000 ha (Lathrop et al., 2001). However, Bologna et al. (2001) reported that more than 60% of the seagrass beds in Little Egg Harbor were lost over a 25-year period from the mid-1970s to 1999. Lathrop et al. (2001) also noted the possible loss of ~25% (~2000 ha) of the seagrass beds in Barnegat Bay between 1987 and 1999, with the greatest reduction in spatial coverage of seagrasses observed in deeper border areas.
Assessment of the distribution and abundance of seagrasses in the Barnegat Bay--Little Egg Harbor Estuary is necessary to track escalating eutrophication impacts in the system, most notably diminishing seagrass habitat and altered biotic communities (Kennish, 2001a). Since changes in seagrass distribution and abundance can occur during periods as short as weeks or months, rapid and cost effective tools are needed to determine seagrass condition and to quantify cause and effect relationships. A two-pronged monitoring program was therefore initiated in the estuary, first assessing the system-wide distribution of seagrass habitat using ortho-rectified, 1-m pixel size, 4-band (green, red, blue, and near-infrared) digital aerial photography captured in May 2003 (Lathrop et al., 2005). In addition, an in situ biomonitoring sampling strategy was undertaken in 2004 to address the emerging seagrass habitat problems in the system. This strategy consisted of establishing a series of sampling transects, with an array of quadrat, core, and hand sampling sites (Kennish et al., 2005). Aerial imaging served as a complementary component of the sampling program.
Little Egg Harbor is the southern segment of the Barnegat Bay--Little Egg Harbor Estuary (Figure 1). With a surface area of ~82 [km.sup.2] and volume of ~1.16 x [10.sup.8] [m.sup.3], it forms an irregular shallow tidal basin. Water temperatures and salinities range from about -1.5-30[degrees]C and 10-32%[per thousand], respectively. Water depths generally range from 1-3 m, but extensive shoals occur outside of the Intracoastal Waterway. Greatest depths (~7 m) are found in lower Little Egg Harbor (Kennish, 2001b).
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Seagrass beds in the estuary, consistently principally of eelgrass (Zostera marina) and widgeon grass (Ruppia maritima), have historically been most abundant in Little Egg Harbor. They are densest along the eastern side of the embayment where bottom sediments consist of well-sorted sands (Kennish et al., 2005). The beds have a patchy distribution, particularly as deeper waters (> 1 m) are approached.
Detailed aerial imaging and in situ sampling of seagrass beds were conducted in the Barnegat Bay--Little Egg Harbor Estuary during the spring-fall period in 2004 and 2005 to provide baseline data on seagrass dynamics in the system. The main objectives of these investigations were to determine the demographic characteristics and spatial habitat change of seagrass (Zostera marina and Ruppia maritima) over an annual growing period, as well as the potential impacts of benthic macroalgae on the seagrass beds. Disjunct seagrass beds in Little Egg Harbor (~1700 ha) and Barnegat Bay (~1550 ha) were sampled at ten equally spaced points along six, east-west trending transects during the two-year study period (Kennish et al., 2005). A total of 360 samples were collected at 120 transect sites, with nearly 1000 biotic measurements obtained each year. At the 120 sampling sites, the following demographic data were collected on all sampling dates: aboveground and below-ground biomass of seagrass, average shoot height, and percent cover of seagrass and macroalgae. Physico-chemical data (temperature, salinity, pH, dissolved oxygen, turbidity, and percent sand, silt, and clay) were also collected at each sampling site using a handheld YSI 600 data sonde coupled with a handheld YSI 650 MDS display unit. In addition, Secchi disk measurements were taken in the study area. Several nutrient parameters (ammonium, nitrate, nitrite, total dissolved nitrogen, and phosphate) were likewise measured along the seagrass beds (Kennish et al., 2005).
The in situ sampling approaches used in the biomonitoring surveys to assess the natural variability of seagrass beds and potential anthropogenic impacts followed the standard protocols of Short et al. (2002). Although conventional field sampling methods were used in these surveys to characterize the system attributes, they were found to be labor intensive, time consuming, and costly (Kennish et al., 2005). To address these deficiencies, we developed and applied a practical method to monitor seagrass habitat conditions in the estuary. This boat-based approach involved the adaptation of an innovative, low-cost technique--underwater videography--to generate comprehensive benthic biotic databases for coastal resource management programs. While underwater videography provides some trade offs with information collected by conventional methods, it generates spatially rectified images that are direct evidence of seagrass condition unmatched by other sampling approaches.
The major objective of this project was to test the effectiveness of a high-resolution, underwater video imaging system to quantify the distribution, abundance, and areal coverage of seagrasses and macroalgae in the Barnegat Bay--Little Egg Harbor Estuary. The benthic (seabed) imaging technique involved the coupling of differential global positioning system (GPS) data to underwater video images of bottom habitats using a standard digital video camera and recording unit. It generated thematic maps and the quantification of the basal area of seagrass cover for effective comparison of population data over well-defined temporal scales. This in-situ imaging tool offers several advantages over high-resolution, remote sensing techniques (i.e., aerial photography and satellite imaging), which yield broad spatial coverage of an estuarine system, but are not effective for assessing fine detail in spatially restricted, habitat areas. The deep edges of seagrass beds can be difficult to delineate through aerial photographs. In addition, remote sensing platforms are usually limited by local weather and astronomical factors (cloud cover, sun angle, and wind), estuarine surface conditions, water depth, and water clarity. In addition, remote sensing surveys are normally limited to one imaging mission due to cost constraints, which may or may not miss the peak biomass period for the targeted seagrass species. Single-snapshot remote sensing missions, therefore, provide no information on the yearly temporal variability of seagrass habitat or health.
In-Situ Survey Instruments
The underwater digital video camera and recording system consists of high resolution elements. The camera (i.e., Seaviewer Sea Drop Camera) is a color unit attached to the video in-channel on the recording device. The recorder is a SONY min-DVD camera system (Model# DCR-DVD301). It incorporates the audio signal from the Red Hen Systems Video Mapping System (VMS 300) and the video signal from the underwater camera. The camera records data in a DVD format which is later downloaded to a personal computer and into a geographic information system for analysis.
The GPS unit is a THALES 12b12 GPS system. It has an accuracy of less than 5 m (horizontal) and is capable of a satellite-based augmentation through the North America Wide Area Augmentation System or WAAS. The VMS 300 takes THALES GPS data and converts it into audio signals which are then read into the recording unit at 1 hertz through the audio in-channel.
The software used to process the collected imagery includes ESRI ArcGIS, especially the ARCmap software package. The media viewer extension created by the Red Hen Systems allows the temporal and GPS data from the audio channel to incorporate the video directly into the Geographic Information Systems (GIS). In addition, the video data can be analyzed and compared to other types of digital datasets (e.g., aerial photography). The image processing software Erdas Imagine and Adobe Photoshop are also utilized to sharpen the collected imagery.
Images were collected with the Sea Drop Camera at randomly selected sites along two transects to survey the SAV beds and to groundtruth a concurrently running Light Detection and Ranging (LiDAR) remote sensing survey (Figures 1 and 2). The sampling method entailed the deployment of the digital camera attached to a boat-based, graduated PVC rod with a GPS antenna that was mobilized to image 1-[m.sup.2] sampling units (Figure 3). A total of 317 images were collected by following this approach.
[FIGURES 2-3 OMITTED]
Figures 4-7 show a series of video images of seagrass taken by the benthic camera and recording system along the sampling transects in Little Egg Harbor during summer 2005. Only Zostera marina was observed in the video images of the sampling sites. Figure 4 is the image of a dense seagrass bed, with basal areal coverage of Z. marina amounting to ~95%. As the boundary of the seagrass bed is approached, the density and percent coverage of Z. marina decline appreciably. Figure 5 exhibits a seagrass bed with ~50% coverage of Z. marina, as evidenced by an extensive area of barren substrate. Beyond the seagrass bed boundary, unvegetated estuarine floor is conspicuous (Figure 6). Barren habitat is often draped by drifting macroalgae, notably Ulva lactuca, the predominant green algal form in the estuary. However, other macroalgal species are also abundant, notably the red algae Spyridia filamentosa, Gracilaria tikvahiae, and Champia parvula, which ranked among the most common seaweeds in the study area during surveys conducted in 2004 (Kennish et al., 2005). Figure 7 illustrates a bare bottom area with ~60% coverage by benthic macroalgae.
[FIGURES 4-7 OMITTED]
Figure 2 exhibits the percent coverage of Z. marina along the two transects in Little Egg Harbor based on videographic imaging of the estuarine floor. A total of 317 images were taken along the two transects and later analyzed in the laboratory. The highest percent coverage of Z. marina occurred along the northern segment of both transects in areas where seagrass beds have been historically densest. Table 1 provides measurements of the number and percentage of images classified as seagrass, benthic macroalgae, seagrass and macroalgae, and bare bottom. Seagrass was the dominant component, being recorded in 84% (267) of the videographic images. Macroalgae appeared in 48% (152) of the images, with seagrass and macroalgae together observed in 44% (138). Only 4% (13) of the images were classified as bare bottom devoid of any vegetation. Vegetation types could not be determined in 5% of the images due to high turbidity. Seagrass covered a mean area of 62.8% of the sampling units along the transects compared to a mean area of 14.2% of the sampling units covered by macroalgae (Table 2).
The high-resolution images also yielded observations on the relative abundance of epiphytic algae and other organisms attached to the seagrass blades (see Figures 4-7). Abundance of epiphytes on SAV peaked in the Barnegat Bay--Little Egg Harbor Estuary during mid-summer. High epiphytic loading (epiphyte biomass to seagrass biomass) on seagrass blades is potentially a serious problem because the epiphytes intercept solar radiation, and this process can significantly inhibit light availability to the vascular plants resulting in decreased primary production of the SAV beds (Miller-Myers and Virnstein, 2000). Persistent elevated epiphytic loading is a likely cause of diminished seagrass coverage. Videographic imaging of SAV beds can clearly track these effects over broad spatial scales and yield measurements of the health of this vital subsystem. As noted previously, seagrasses are important indicators of estuarine water quality, and underwater videography serves as a useful tool for evaluating the ecosystem condition.
Underwater video imaging linked to global positioning system data provides an excellent method of groundtruthing remote sensing surveys, while concurrently generating high-resolution benthic measures. It is an effective tool for mapping shallow benthic habitats, monitoring seagrass beds, and characterizing the ecological condition of the epibenthos. By combining aerial imaging with diver- and boat-based observations, comprehensive databases can be generated from estuary-wide surveys of submerged aquatic vegetation, including measurements of seagrass cover in space and time, macroalgal abundance, and shifts in epibiotic inhabitants. While the use of an underwater digital video camera often yields clear images of the seabed and its epibenthic community, image quality is occasionally compromised by elevated turbidity levels, extremely shallow depths, and poor meteorological conditions.
There are also several technical limitations to aerial imaging of seagrass beds and other habitats in shallow estuarine environments. The detection depths of imaging from aerial platforms are commonly limited by atmospheric conditions, surface water roughness, air-water interface interactions (e.g., refraction), water clarity, water column light attenuation, and other factors that hinder image acquisition (Phinn et al., 2000). Of particular interest is the shallowing of the maximum detection depth of the aerial photography, which can be substantial when turbidity levels and the aforementioned factors are not favorable. The maximum detection depth must be considered when surveying the deeper boundaries of seagrass beds, seabed habitat patchiness, and spatially-limited bottom structural features (e.g., reefs). The distribution and extent of seagrass beds estimated by optical remote sensing are subject to substantial error when the maximum detection depth lies above the deeper boundaries of the beds (Mount, 2003).
Aerial- and satellite-based remote sensing surveys are generally costly, thereby constraining the frequency of their use. In contrast, the application of underwater benthic videography and associated diver--and boat-based observations are relatively low-cost techniques that can be readily conducted and more easily adapted to seasonal sampling (Norris et al., 1997). When applied as complementary technologies, aerial photographic imaging, underwater benthic videography, and in situ hand sampling provide researchers with powerful tools for monitoring and mapping seagrass habitats. Aerial photography gives broad spatial coverage of a system. Underwater benthic videography, in turn, focuses on data recovery at discrete sites or zones for more precise, fine-scale monitoring and habitat detection which are needed for identification and classification of habitat types (Mount, 2003). Utilizing both technologies, therefore, is one of the most useful ways of conducting comprehensive assessment of seagrass habitats.
In designing a seagrass survey, it is important to consider both the size of the study area and the level of detail necessary to answer a specific question. Aerial- and satellite-based remote sensing studies generate limited information over an extensive area, whereas in situ-based investigations yield more detailed information at discrete locations. Underwater videography surveys provide more information than smaller-scale remote sensing surveys, but they cover less area per unit time. Conversely, underwater videography surveys cover more area per unit time than in-situ monitoring; however, they produce less information. Underwater videography, therefore, lies along a continuum between smaller scale remote sensing surveys and in-situ based surveys in regard to areal coverage and the amount of information generated (Figure 8). If underwater videography could be used as a rapid, non-destructive method of quantifying plant health (i.e., biomass and vigor), it would be exceptionally valuable for benthic floristic studies in estuarine and coastal marine environments.
[FIGURE 8 OMITTED]
Results of this study show that the basal areal coverage of seagrasses in the Barnegat Bay--Little Egg Harbor Estuary can be determined by employing a high-resolution, underwater digital video camera and recording system. With video imaging linked to GIS, high precision point estimates of seagrass coverage have been obtained along sampling transects that cut across disjunct beds on the eastern side of the estuary. Visual images of the subtidal seagrass beds at GPS-sited locations have been readily processed in the laboratory, and subjective measures of seagrass, macroalgae, and bare bottom cover within the tidal basin have been recorded in a spreadsheet format for quantification analysis. These data indicate that seagrass beds are the predominant benthic habitat along the eastern side of the estuary, with their most extensive coverage occurring in the northern portion of the study area where seagrass abundance was previously found to peak (Kennish et al., 2005). Seagrass percent cover commonly exceeds 75% at northern sampling sites on the straight-line transects.
Basal areal coverage estimates of seagrass relative to macroalgae, together with metric measurements of the vegetation (density and biomass) and aerial photographic imaging, yield data necessary to assess both site-specific habitat characteristics and system-wide conditions. They are important for monitoring the responses of the seagrasses to anthropogenic alterations, such as nutrient enrichment, which is a serious insidious problem in this highly eutrophic estuary (Kennish, 2001a). Additional site-specific biotic data, such as metric measurements of epiphytes and benthic macroinvertebrates, will enable investigators to generate more comprehensive and ecologically sensitive databases to accurately document the condition of seagrass habitats in this important coastal bay system.
This publication is part of an ongoing effort to assess water quality and habitat conditions in New Jersey's coastal bays. We thank Dr. Richard Lathrop and other members of the Center for Remote Sensing and Spatial Analysis at Cook College, Rutgers University, for advice on aerial imaging aspects of this study. Funding support of the Barnegat Bay National Estuary Program, National Estuarine Research Reserve System, and Jacques Cousteau National Estuarine Research Reserve is gratefully acknowledged. The names of companies or products reported in this paper do not constitute endorsement by the authors or Rutgers University. This is Publication No. 2006-42 of the Institute of the Marine and Coastal Sciences, Rutgers University, and Contribution No. 100-32 of the Jacques Cousteau National Estuarine Research Reserve.
MICHAEL J. KENNISH, SCOTT M. HAAG, AND GREGG P. SAKOWICZ
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MICHAEL J. KENNISH, (1) SCOTT M. HAAG, (2) AND GREGG P. SAKOWICZ (3)
(1) INSTITUTE OF MARINE AND COASTAL SCIENCES, RUTGERS UNIVERSITY, NEW BRUNSWICK, NJ 08901 KENNISH@MARINE.RUTGERS.EDU
(2) CENTER FOR REMOTE SENSING AND SPATIAL ANALYSIS, RUTGERS UNIVERSITY, NEW BRUNSWICK, NJ 08901 SCOTTH@CRSSA.RUTGERS.EDU
(3) RUTGERS UNIVERSITY MARINE FIELD STATION, INSTITUTE OF MARINE AND COASTAL SCIENCES, RUTGERS UNIVERSITY, TUCKERTON, NJ 08087 SAKOWICZ@IMCS.RUTGERS.EDU
Table 1. Number and percentage of images classified as seagrass, macroalgae, seagrass and macroalgae, and bare bottom habitat in Little Egg Harbor based on videographic imaging of transect sites. NO. OF SEAGRASS AND IMAGES SEAGRASS MACROALGAE MACROALGAE BARE BOTTOM 317 267 (84%) 152 (48%) 138 (44%) 13 (4%) Table 2. Percent coverage of seagrass and macroalgae in Little Egg Harbor based on videographic imaging of 1-[m.sup.2] sampling units along transects. VEGETATION MEAN(%) MIN(%) MAX(%) STANDARD DEVIATION Seagrass 62.8 1 95 32.3 Macroalgae 14.2 0 100 21.9
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|Author:||Kennish, Michael J.; Haag, Scott M.; Sakowicz, Gregg P.|
|Publication:||Bulletin of the New Jersey Academy of Science|
|Date:||Mar 22, 2006|
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