Final Report: Multiscale Assessment of the Population Status of Thalassia testudinum A New Approach to Ecosystem AssessmentEPA Grant Number: R825145
Title: Multiscale Assessment of the Population Status of Thalassia testudinum A New Approach to Ecosystem Assessment
Investigators: Carlson, Paul R. , Durako, Michael J. , Fourqurean, James W. , Madley, Kevin , McRae, Gil , Merello, Manuel , Moncreiff, Cynthia A. , Randall, Todd , Rose, Craig D. , Yarbro, Laura A.
Institution: Florida Marine Research Institute , Florida International University , Oregon State University , University of Southern Mississippi
EPA Project Officer: Packard, Benjamin H
Project Period: October 1, 1996 through September 30, 1999
Project Amount: $758,386
RFA: Ecological Assessment (1996) RFA Text | Recipients Lists
Research Category: Ecological Indicators/Assessment/Restoration , Ecosystems
The objective of this collaborative research project was to test the utility of demographic, morphological, physiological, and chemical characteristics of the turtle-grass (Thalassia testudinum) seagrass species as indicators of chronic environmental stress on estuarine and nearshore ecosystems. Turtle-grass was selected for four reasons: (1) it is abundant along the Gulf Coast; (2) it has a large investment in non-photosynthetic tissue (roots and rhizomes); (3) it is particularly sensitive to stress; and (4) in estuaries like Tampa Bay, it has proven more vulnerable than other seagrass species to human impacts. We have tested demographic characteristics (population structure inferred from shoot age distribution), plant morphology (leaf width, length, shoot-specific leaf area, and leaf area index), physiological parameters (rhizome carbohydrate levels, elemental carbon, nitrogen, phosphorous (C:N:P) ratios), and stable isotopic (del C-13, del N-15, and del S-34) composition of turtle-grass as potential stress indicators.
Turtle-grass indicators were tested at nine sites in the eastern Gulf of Mexico, between the Chandeleur Islands in Mississippi and the Florida Bay at the southern tip of the Florida Peninsula. The field sampling program at all nine sites used three nested grids of tesselated hexagons. This spatially distributed, random sampling design provided the statistical advantages of random sampling and structured spatial coverage of sampling areas. At each of the nine sites, we sampled 30 stations at three spatial scales (small-2,500 m2, medium-25,000 m2, and large-250,000 m2). We also attempted to determine the most effective sampling design and scale for assessing the impact of natural and human impacts on seagrass beds.
The findings are divided into five sections, reflecting the contributions from the project investigators at the four collaborating institutions.
Responses of Demographic, Morphological, and Chemical Characteristics of Turtle-Grass, Thalassia testudinum, to El Niño Runoff: An Unexpected Test of Indicators
For demographic, morphological, and chemical characteristics of Thalassia to be useful indicators of stress they must meet several criteria. They must exhibit a quantitative, dose-dependent, response to stress. They also must respond to stress rapidly enough that: (1) response can be definitely tied to a particular stress or stressors; and (2) corrective action can be taken before whole seagrass communities are lost.
El Niño runoff in 1998 gave us an unexpected opportunity to test the response of our suite of indicators to declines in water clarity across the entire West Florida region. In periods where we did not have quantitative water clarity data, we applied three criteria to evaluate the utility of our indicators to measure light stress in turtle-grass communities: (1) quantitative and understandable response to stress, (2) statistically significant response, and (3) consistency of response among estuaries.
In general, Thalassia morphological parameters respond to stress in a consistent temporal and spatial pattern. However, several morphological parameters lack the statistical power necessary to be useful indicators. The most promising morphological parameters are Thalassia shoot density, blade width, blade number, and shoot-specific leaf area. Many of the chemical parameters vary significantly among years across our four study sites. The chemical parameters that exhibit the most consistent and quantitative variation, are rhizome carbohydrate concentrations, sugar, starch, and total non-structural carbohydrate. These parameters are affected by shoot density, because light limitation in dense beds affects the photosynthetic production of individual shoots. In previous shading studies, we have found significant interactions between shoot density and rhizome carbohydrate concentrations: rhizome carbohydrate levels can be unaffected or rise slightly as shoot density declines in response to shading. As a result, a multi-metric parameter based on Thalassia shoot density and rhizome carbohydrate levels is probably more useful than either parameter alone in developing indicators of light stress in Thalassia.
The parameters we tested fall into three groups. The first group is composed of parameters, which are probably not useful indicators of seagrass health. These parameters lack the responsiveness or consistency required for an indicator to be applied confidently throughout the eastern Gulf of Mexico. The second group includes marginal parameters, which respond to stress and exhibit similar responses at several sites, but these parameters exhibit a large amount of within-site variability which decreases the ability to detect change. Parameters in the marginal group might be useful indicators if more samples or larger samples are taken to reduce the within-site variability. However, more and larger destructive samples might have unacceptable impacts on seagrass beds.
Parameters, which fall into the third group, Thalassia shoot density, blade width, blade number, and shoot-specific leaf area, as well as rhizome carbohydrate concentrations, are worthy of additional testing for indicator development. These parameters exhibit temporal and spatial consistency as well as statistical significance in their response to light stress. Assessment thresholds and "dose-response" relationships should be determined for these parameters, and additional effort should focus on testing of multi-metric parameters and improving the statistical power of indicators.
Demographic and Morphological Variation of Turtle-Grass at Nine Sites in the Eastern Gulf of Mexico
At the nine sites, small-scale sampling grids were located near suspected anthropogenic or natural perturbations and sample stations were randomly located within each grid cell. A suite of abundance, demographic, and morphometric characteristics were measured at each sample station.
Overall average Thalassia short-shoot (264 short shoots m2) and rhizome apical (81 apicals m2) densities for the nine sites were at the low end of the reported ranges for this region; however, densities were highest at the two least-perturbed sites. Overall, branch frequencies were relatively high (31 percent) and indicate that a new rhizome apical is produced for every 3 to 4 short-shoots. The Braun-Blanquet visual technique produced estimates of Thalassia and Syringodium filiforme abundances that were highly correlated with those obtained from destructive core samples (r2 = 0.86 and 0.98 for Thalassia and Syringodium, respectively). The understory nature and patchiness of Halodule wrightii resulted in lower correlations between the visual and core-based abundance data (r2 = 0.57). However, Halodule wrightii did exhibit a significant scale-dependent change in shoot-density variability when core data for all the sites were pooled within each sampling scale. No other scale-dependent change in variability in seagrass abundance was observed. Within-site scale-based changes in shoot-density were significant at five of the nine sites; scale-based changes in cover were significant at four of the nine sites. The pattern of variability in abundance data generally corresponded to the perturbation gradients or to sample-site depth. Shoot-specific characteristics such as the number of leaves short-shoot (7 sites), maximum leaf length (8 sites), and leaf area index (5 sites) exhibited significant scale-dependent variability at more than half of the sites. Leaf width short-shoot age exhibited the least spatially dependent variability within each of sites. Abundance and structural characteristics did not generally follow the same spatial patterns relative to perturbation or depth. No significant scale-dependent change in amount of variability or latidudinal gradients were detected for any of the morphometric or demographic characteristics examined.
Significant scale-dependent variability was observed for the number of leaves short-shoot, maximum leaf length, and shoot-specific leaf area at more than half of the sites, but the spatial patterns for these characteristics did not always exhibit across-character correspondence. Leaf width and shoot age (in plastochrone intervals) exhibited the least variability across sampling scales, suggesting that these characteristics may have little utility for within basin assessment. The high correlation between seagrass abundance estimated by core data and abundance estimated by Braun-Blanquet data for the sites sampled in this study suggests that the visual assessment technique provides a reliable estimate of seagrass abundance in the eastern Gulf of Mexico coastal waters.
The main problem with estimating seagrass community characteristics is variability among sample-measurement data, the higher number of samples possible with visual estimation methods should reduce sampling error and increase precision over the more time-consuming and destructive harvesting methods. Because of its significant below-ground reserves and long shoot life span of up to 22 years (van Tussenbroek, 1994), changes in short-shoot or rhizome-apical abundance of Thalassia testudinum may be limited to indicating longer-term changes in ecological condition. Changes in cover, density changes, as well as changes in shoot-specific leaf characteristics may be a more sensitive indicator of shorter-term trends
Stable Carbon, Nitrogen, and Sulfur Isotope Composition of Thalassia testudinum Leaf Tissue
We focused on processing the 74 remaining 1999 biomass samples from the St. Joseph Bay study site (Chandeleur Islands and Perdido Key/Big Lagoon sties analyses are complete). Short shoot subsamples from the Anclote, Charlotte Harbor, Homosassa, Tampa Bay, and Sarasota Bay sites for 1999 were received in a timely manner, checked for consistency stable isotope analysis, and prepared for shipment.
All 1999 carbon, nitrogen, and phosphorous samples were shipped to the Florida International University (FIU) for analysis. Stable isotope samples from the Rabbit Key East and West sites from 1998 and 1999 field collections were received from FIU in March 2000 and shipped to the Environmental Isotope Laboratory (EIL) for 13C, 15N, and 34S analysis. A final shipment of material for stable isotope analyses, consisting of 22 samples from various sites, was received from FIU in April 2000, and this final set also was sent to the EIL for analysis. Results for the last two sample sets were received from the EIL on August 16, 2000.
Considerable variation occurred in the stable isotope ratios of all three elements (carbon, nitrogen, and sulfur) within each site. However, values for a given site tended to cluster in a range of N-15 and C-13 values.
Carbon isotope values for most sites range from -14 to -8, although the Charlotte Harbor site has values as low as -20, reflecting the riverine dominance of this estuary. Del S-34 values range from -10 to +20, reflecting varying contributions of sediment sulfide and seawater sulfate, respectively, in plant tissue. Lowest values occurred at the Perdido Key and Rabbit Key East sites, and highest values occurred at the Anclote River site. N-15 values also showed a wide range from -3 to +5 with lowest values at the Anclote River, Rabbit Key West, and Charlotte Harbor sites. Highest values occurred at Chandeleur Islands. Charlotte Harbor exhibited the greatest range of values (-2 to +5 ppt).
The primary determinants of del C-13 values are photosynthetic pathways and inorganic carbon sources for plants. Thalassia typically has del C-13 values in the range of C-4 plants (grasses, etc.). However, values are lowered by remineralization of terrrestrial organic matter derived from C-3 plants. The resulting dissolved carbon dioxide and bicarbonate have lower del C-13 values than marine dissolved inorganic carbon, and seagrasses using this "terrestrial" inorganic carbon develop low del C-13 values in their tissue. Mean del C-13 values ranged from -15 at Charlotte Harbor to -9 at the Rabbit Key West site, but most sites had mean values between -11 and -9. In addition to having the lowest del C-13 values, Charlotte Harbor Thalassia samples also exhibit a considerable range of del C-13 values, reflecting the varying contribution of terrigenous material to dissolved inorganic carbon along the estuarine gradient.
Lowest mean del N-15 values (-1 ppt) occurred at the Anclote River and Rabbit Key West sites. Highest values (+3 ppt) occurred in the northern Gulf sites, Chandeleur Islands and St. Joe Bay. Low del N-15 values, ranging from -1 to +1 ppt, typically result from nitrogen fixed by bacteria. High values are often associated with anthropogenic and terrigenous nitrogen. However, elevated del N-15 values can also occur in environments where nitrogen fixation is inhibited and nitrogen recycling is intense. Agricultural and urban stormwater runoff can have del N-15 values greater than +10 ppt, so the high values of +3 ppt encountered in Chandeleur Islands and St. Joe Bay are not alarming. What is cause for concern is the perception that these two sites are less heavily impacted by human activity than other sites; these del N-15 values might indicate that terrestrial runoff does impact these sites. However, an alternate explanation is that nitrogen fixation by heterotrophic bacteria is limited at these sites.
Mean del S-34 values ranged from -2 ppt at Perdido Key and Rabbit Key East to values greater than +14 ppt at Anclote River, Charlotte Harbor, St. Joe Bay, and Tampa Bay. Sulfide produced by bacterial sulfate reduction in marine sediments typically has low del S-34 values (< 0 ppt) while seawater sulfate has a del S-34 value near +20 ppt. The range of values seen in this study reflect differing abundance of sulfur within Thalassia tissue derived from sulfide and sulfate. The means and standard deviations of stable sulfur and carbon isotope ratios are sufficient to identify Thalassia tissue from most sites. However, isotopic composition of Thalassia from Anclote River and St. Joe Bay overlap considerably as do Perdido Key and Rabbit Key Basin.
Rabit Key Site Characteristics and Elemental Ratios of Thalassia testudinum Leaf Tissue
Our group was responsible for the yearly sampling of two areas within the Rabbit Key basin in Florida Bay: the southeast basin (RE) and the northwest basin (RW). All sampling was conducted from October thru December for 3 successive years (1997-1999). In 1997, small (S), medium (M), and large (L) scales were sampled in RE only because the sampling of RW was not decided until it was passed our sampling window. RE was fully sampled in both 1998 and 1999. All three scales of RW were sampled in 1998, however, in 1999, due to turbid conditions and the lingering effects of Hurricane Irene, only the large scale in RW was sampled.
Whenever possible, at each site, water depth, secchi disk depth, water temperature, salinity, and turbidity were measured.
Water depth and secchi disk depth were measured using an incremented 2 meter PVC pole. The secchi disk was attached at the bottom. Whenever water depth was greater than 2 m, this was indicated. For calculations, actual values for water depths were estimated to the nearest half meter. Water temperature and salinity were measured on a conductivity meter. Turbidity samples were collected in a single 20 ml plastic scintillation vial and measured on a HF portable turbidimeter (HF Scientific, DRT-15CE) in nephelometric turbidity units (ntu's).
Summary statistics for these parameters were computed for RE and RW. Water depth was never higher than 3 m, with means falling within the 1.5 to 2.0 m range. In RE, secchi disk depth approximated or was equal to water depth during the 3 years; however, in RW, secchi disk depths were noticeably lower, especially in 1999, when Hurricane Irene and a series of cold fronts passing across south Florida resulted in increased run-off and turbidity, and reduced water temperatures and salinity.
Water temperatures ranged between 22.1 and 31.7°C in RE and 15.9 and 27.8°C in RW within the three annual sampling periods. Differences between basins are mainly attributed to the later sampling of RW. Salinity was higher in 1997 and 1998 for RE and RW, but decreased with the increased precipitation and run-off events identified in 1999.
Water column turbidity exhibited much lower values in 1998 (with a range of 0.38 to 0.91 ntu's for RE and a range of 0.27 to 3.60 ntu's for RW) than 1999, when RE values ranged between 0.57 and 9.31 ntu's and RW values ranged between 1.41 and 14.62 ntu's.
One diver, using a 0.25 m2 quadrat, estimated the percent cover of seagrasses and macroalgae using a modified Braun-Blanquet abundance scoring scale. Four samples were collected adjacent to the boat at each site. Estimates were used to calculate the frequency (percent occurrence), abundance (mean score when present within a quadrat), and density (mean score out of four quadrats) for each taxon. In RE and RW, the dominant species was Thalassia testudinum. Halodule wrightii and the broad category of total calcareous green algae (CGT), which encompasses all of the calcareous green algal species (primarily Penicillus and Halimeda) were present at a large percentage of the sites; although their abundance and frequency exhibited greater variability at a site, within a basin, and between years.
Difference maps in spatial variability of the calculated Braun-Blanquet abundances for Thalassia testudinum, Halodule wrightii, and CGT were created for samples collected within RE between 1997 and 1999. In summary for the RE, spatial patterns within and between years do not reveal any significant changes in abundance in the three dominant species present in RE. Divers did observe what appeared to be localized areas of traditional seagrass die-off, but these occurrences were not detected by our sampling regime. Spatial contours maps of Braun-Blanquet abundance values in RW suggest that for the data collected in 1998, Thalassia testudinum is generally less abundant in the RW basin than in the RE basin with a few sites having a Braun-Blanquet abundance > 3. Halodule wrightii in RW, on the other hand, exhibits an increased spatial heterogeneity and abundance relative to RE.
At each site, 10 SS of Thalassia testudinum were collected by hand within a 1 to 2 m2 area adjacent to the boat. In the lab, leaf number, width, and length were recorded for each individual SS. Leaves were scraped to remove any epiphytic material, rinsed in freshwater, dried to a constant mass (48 hours), weighed, and ground to a fine powder for subsequent elemental and stable isotopic content analyses.
Leaf mass of Thalassia testudinum ranged between 45.7 and 364.3 mg SS-1 over the 3 years sampled in RE, and means among years significantly varied. Significant variation also was observed among sampling scales, with SS collected at the S scale having a consistently higher leaf mass than L scale samples across all 3 years of sampling (P = 0.019). In RW, leaf mass and one-sided leaf area in 1998 were significantly higher in the L scale. Both leaf number and leaf width did not significantly vary among scales. Comparisons among years revealed no significant differences between leaf morphometric characteristics.
1997-1999 Thalassia Leaf C:N:P Inter-Estuary Comparisons. Within each year sampled, significant differences were observed among the estuaries sampled for Thalassia leaf C:N, C:P, and N:P, when all the sites sampled (regardless of scale) were pooled.
Mean leaf C:N (from pooled estuarine values) ranged between 13.8 to 21.8. Perdido Key had the highest C:N values, while Charlotte Harbor, Rabbit West, and Tampa Bay each had the lowest C:N ratios. Leaf C:N significantly varied among years in most estuarine systems, but only Rabbit West and the Chandeleur Islands exhibited a significant source of variation due to sampling scale.
Mean leaf C:P (from pooled estuarine values) ranged between 127 to 2,576, with scalar means ranging between 127 to 3,312, and individual site means between 92 to 15,596. The three estuaries from the north coast of the Gulf of Mexico, Chandeleur Islands, Perdido Key, and St. Joe Bay exhibited the highest C:P values, whereas Charlotte Harbor had the lowest observed leaf C:P ratios. Five of the seven estuaries, where yearly comparisons were made, exhibited a significant source of variation from the different sampling times for leaf C:P. Three estuaries-Homosassa River, Perdido Key, and Rabbit West-exhibited a significant source of variation from sampling scale.
Mean leaf N:P (from pooled estuarine values) ranged between 9.2 and 121.3, with scalar means ranging between 9.1 and 155.6, and individual sites means between 6.7 and 727.0. The same patterns were observed as with leaf C:P ratios, where the three estuaries from the north coast of the Gulf of Mexico exhibited the highest N:P values, whereas Charlotte Harbor had the lowest observed leaf N:P ratios.
These patterns suggest that the three northern estuaries are phosphorus limited. Significant differences between sampling years were observed in six of the seven estuaries tested, and four estuarine systems exhibited significant variation due to sampling scale-Homosassa River, Perdido Key, Rabbit East, and Rabbit West. From these preliminary analyses, it appears that the effects of sampling scale are overshadowed or minimized by the even greater degree of variability that occurs between sampling years.
Rhizome Carbohydrate Reserves
Florida Marine Research Institute (FMRI) staff were the lead investigators for rhizome carbohydrate analyses. Rhizome carbohydrates-non-structural carbohydrates (sugars and starches) are important metabolic reserves for seagrasses. They accumulate during periods when production exceeds respiration, and they are utilized during rapid growth or periods when production is suppressed. Because high levels of rhizome carbohydrates are indicative of high production, we anticipated that rhizome carbohydrate levels would be useful indicators of overall plant health.
To test that hypothesis, we have analyzed starch and sugar concentrations in approximately 5,400 rhizome samples collected from all 9 study sites over the past 3 years. In 1999, we also sampled a tenth estuary, Sarasota Bay, and analyzed approximately 1,200 rhizome carbohydrate samples. Healthy rhizome tissue attached to the same shoots used for elemental ratio and stable isotope analyses was frozen on dry ice in the field and sequentially extracted with hot ethanol and sodium hydroxide to release sugars and starch, respectively. Carbohydrate concentrations in the ethanol and sodium hydroxide extracts reacted with a mixed sulfuric acid/tryptophan reagent to produce a colored product which is measured spectrophotometrically.
The highest sugar concentrations (61 mg/g fresh weight rhizome tissue (FW)) were found on the Homosassa River at Charlotte Harbor, and the lowest concentrations (14 mg/g FW) were found at the northwest Florida Bay site. The northwest Florida Bay site also had the lowest starch concentrations (35 mg/g FW), and the Anclote River site had the highest starch values (74 mg/g FW). On the basis of total carbohydrate concentrations, the ten sites sampled in 1999 separated into three groups, Homosassa, Anclote, and Sarasota Bay had total carbohydrate concentrations greater than 120 mg/g FW. The second tier of sites, Perdido Key, Chandeleur Islands, and Charlotte Harbor had total carbohydrate concentrations near 100 mg/g FW. The third tier of sites, including southeast Rabbit Key Basin, Tampa Bay, and St. Joe Bay had concentrations between 80 and 90 mg/g FW. Only the northwest Rabbit Key Basin, characterized by continuously turbid conditions, had total carbohydrate concentrations lower than 80 mg/g FW.
Winter rainfall totals ranged from 130 to 170 percent of normal values. These high rainfall volumes resulted in low salinities at all sites, and secondary phytoplankton blooms were documented at the Homosassa, Anclote, and Tampa Bay sites. Total carbohydrate concentrations at Tampa Bay, Anclote, and Homosassa sites rebounded in 1999, reflecting the return to normal salinity regimes and the end of the El Niño generated phytoplankton blooms in the region. Surprisingly, the Florida Bay sites, St. Joe Bay, and Perdido Key, dropped and recovered only slightly in response to El Niño conditions. The Chandeleur Islands site showed a moderate rise in carbohydrate concentrations between 1998 and 1999, but that response might be more related to recovery from Hurricane Georges, which passed directly over the study site on September 28, 1998.
The response of rhizome carbohydrate concentrations to the 1997-1998 El Niño rainfall suggests that rhizome carbohydrates might be a very useful ecological indicator. Jackson, et al. (2000) have elegantly outlined the criteria that indicators must meet: relevance, feasibility, responsiveness, interpretability, and utility. Rhizome carbohydrates meet most, if not all, of those criteria.
The relevance of rhizome carbohydrate levels to an assessment of nearshore and estuarine ecosystem health is conceptually clear: benthic ecosystem health, in general, and seagrass health, in specific, is dependent on water clarity. Water clarity is degraded by human impact, but principally by phytoplankton blooms driven by nutrient discharges. As water clarity decreases, seagrass photosynthesis and stored reserves (rhizome carbohydrates) also decline.
The real key to successful implementation of an indicator for seagrass health is its responsiveness, and an indicator based on Thalassia rhizome carbohydrate concentrations (among other characteristics) seems promising.
The carbohydrate index represents the 1997 or 1999 rhizome carbohydrate concentrations at each site divided by the corresponding concentrations for 1998, and each of the five sites exhibited a different response to the El Niño-driven phytoplankton blooms. The Anclote site was most severely affected, followed by Homosassa and Tampa Bay. The Florida Bay (FBSE) site was unaffected, and rhizome carbohydrate levels in Charlotte Harbor (CH) in 1998 were actually higher than 1997 and 1999. These two exceptions actually support the index because the FBSE site is so far removed from freshwater influence that a negligible response is expected. Charlotte Harbor, on the other hand, is strongly river-dominated, so either increased runoff is decreasing residence time (and thereby improving water clarity) or the high color content of the Peace and Myakka Rivers might inhibit phytoplankton blooms within the Harbor.
Differences among sites in the severity of the 1998 El Niño event's impact on rhizome carbohydrate levels also reflects differences in watershed nutrient loading and hydrographic conditions among sites. Watershed nutrient yields, depth, circulation, and residence time affect the magnitude of phytoplankton blooms and resulting losses in water clarity at each site.
In order for a carbohydrate index to be a useful indicator of seagrass community health, the criteria of assessment thresholds and dose-response characteristics must be addressed. We know, from previous experiments where we have shaded Thalassia, that there is a relationship between ambient light levels and rhizome carbohydrates. However, Thalassia often responds to light stress by decreasing shoot density. As shoot density declines, competition among shoots for light decreases, and rhizome carbohydrate levels can actually increase. Therefore, an indicator calculated as the product of Thalassia shoot density and rhizome carbohydrate concentrations might be more useful than either parameter by itself. We will review data from this project and the shading studies cited above to determine the response characteristics of composite indicators incorporating rhizome carbohydrate levels.
Cambridge ML, Chiffings AW, Brittan C, Moore L, McComb AJ. The loss of seagrass in Cockburn Sound, Western Australia. Possible causes of seagrass decline. Aquatic Botany 1986;24:269-285.
Carlson PR, Yarbro LA, Barber TR. Role of sediment sulfide in mortality of Thalassia testudinum in Florida Bay. Bulletin of Marine Sciences 1994;54:733-746.
Dennison WC. Effects of light on seagrass photosynthesis, growth and depth distribution. Aquatic Botany 1987;27:15-26.
Dennison WC, Orth RJ, Moore KA, Stevenson JC, Carter V, Kollar S, Bergstrom PW, Batiuk RA. Assessing water quality with submersed aquatic vegetation. Bioscience 1993;43:86-93.
Duarte CM. Seagrass depth limits. Aquatic Botony 1991;40:363-377.
Gallegos CL, Correll DL, Pierce JW. Modeling spectral diffuse attenuation, absorption, and scattering coefficients in a turbid estuary. Limnology and Oceanography 1990;35:1,486-1,502.
Kenworthy WJ, Haunert DE, eds. The light requirements of seagrasses. In: Proceedings of the National Oceanographic and Atmospheric Administration (NOAA) Workshop, Technical Memo NMFS-SEFC-287 Beaufort, NC 1991, 181 pp.
Lewis RR, Durako MJ, Moffler MD, Phillips RC. Seagrass meadows of Tampa Bay: A Review. In: Treat SF, ed. Proceedings of the Tampa Bay Area Scientific Information Symposium (BASIS) 1982, pp. 210-246.
Orth RJ, Moore KA. Chesapeake Bay: an unprecedented decline in submerged aquatic vegetation. Science 1983;222:51-53.
Pulich WM, White WA. Decline of submerged vegetation in the Galveston Bay system: chronology and relationships to physical processes. Journal of Coastal Research 1991;7:1,125-1,138.
Stevenson JC, Staver LW, Staver KW. Water quality associated with survival of submersed aquatic vegetation along an estuarine gradient. Estuaries 1993;16:346-361.
Zieman JC. The ecology of the seagrasses of South Florida: a community profile. Fish and Wildlife Service, Office of Biological Services, Washington, DC, 1982/25, 123 pp.
Boesch DF, Armstrong NE, D'Elia CF, Maynard NG, Paerl HW, Williams SL. Deterioration of the Florida Bay ecosystem: an evaluation of the scientific evidence. Report to the Interagency Working Group on the Florida Bay. National Fish and Wildlife Foundation, Washington, DC, 1993, 27 pp.
Boesch DF, Armstrong NE, Cloern JE, Deegan LA, Perkins RD, Williams SL. Report of the Florida Bay science review panel on Florida Bay Science Conference: a report by principal investigators. Florida Bay Research Program, Program Management Committee, Miami, FL, 1995, 19 pp.
Carlson PR, Acker JG. Effects of in situ shading on Thalassia testudinum: preliminary experiments. In: Webb FJ, ed. Proceedings of the Twelfth Annual Conference on Wetland Restoration and Creation, Hillsborough Community College, Tampa, FL, 1985, pp. 64-73.
Dethier MN, Graham ES, Cohen S, Tear LM. Visual versus random-point percent cover estimations: objective is not always better. Marine Ecology Progress Series 1993;96:93-100.
Duarte CM, Sand-Jensen K. Seagrass colonization: biomass development and shoot demography in Cymodocea nodosa patches. Marine Ecology Progress Series 1990;67:97-103.
Duke TW, Kruczynski WL. Report on the status and trends of emergent and submerged vegetated habitats of Gulf of Mexico Coastal Waters. United States Environmental Protection Agency, Office of Water, Gulf of Mexico Program, Stennis Space Center, 800-R-92-003.
Durako MJ. Indicators of seagrass ecological condition: an assessment based on spatial and temporal changes associated with the mass mortality of the tropical seagrass Thalassia testudinum. In: Dyer KR, Orth RJ, (eds), Changes in Fluxes in Estuaries: Implications for Science to Management, Olsen and Olsen, Fredensborg, Denmark 1995, p. 261-266.
Durako MJ. Seagrass die-off in Florida Bay (USA): changes in shoot demography and populations dynamics. Marine Ecology Progress Series 1994;110:59-66.
Durako MJ, Kuss KM. Effects of labyrinthula infection on the photosynthetic capacity of Thalassia testudinum. Bulletin of Marine Science 1994;54:727-732.
Durako MJ, Phillips RC, Lewis RR, (eds.). Proceedings of the Symposium on Subtropical-Tropical Seagrasses of the Southeastern United States. Florida Marine Research Publications 1987;42:209.
Eleuterius LN. Seagrass ecology along the coasts of Alabama, Louisiana, and Mississippi. In: Durako MJ, Phillips RC, Lewis RR, eds. Proceedings of the Symposium on Subtropical-Tropical Seagrasses of the Southeastern United States. Florida Marine Research Publications 1987;42:11-24.
Environmental Protection Agency. 1990. Environmental monitoring and assessment program overview. EPA/600/9-90/001. 5 pp.
Fourqurean JW, Powell GVN, Kenworthy WJ, Zieman JC. The effects of long-term manipulation of nutrient supply on competition between the seagrasses Thalassia testudinum and Halodule wrightii in Florida Bay. Oikos 1995;72:349-358.
Fourqurean JW, Durako MJ, Hall MO, Hefty LN. Seagrass distribution in south Florida: a multi-agency coordinated monitoring program. In: Porter JW, Porter KG, eds. Linkages Between Ecosystems in the South Florida Hydroscape: the River of Grass Continues. CRC Press, Boca Raton, FL (in press).
Goerte RW. The Florida Bay economy and changing environmental conditions. United States Library of Congress, Congressional Research Service Report. No. 94-435 ENR. Washington, D.C. 1994. p. 1-19.
Gordon DM, Grey KA, Chase SC, Simpson CJ. Changes to the structure and productivity of a Posidonia sinuosa meadow during and after imposed shading. Aquatic Botany 1994;47:265-275.
Hall MO, Tomasko DA, Courtney FX. Responses of Thalassia testudinum to in situ light reduction. In: Kenworthy WJ, Haunert D, eds. The Light Requirements of Seagrasses: Proceedings of a Workshop to Examine the Capability of Water Quality Criteria, Standards and Monitoring Programs to Protect Seagrasses. National Oceanic and Atmospheric Administration Technical Memorandum, NMFS-SEFC-287. Beaufort, North Carolina, 1991, p. 85-94.
Hall MO, Durako MJ, Fourqurean JW, Zieman JC. Decadal-scale changes in seagrass distribution and abundance in Florida Bay. Estuaries 1999;22:445-459.
Hamburg SP, Homann PS. Utilization of growth parameters of eelgrass, Zostera marina, for productivity estimation under laboratory and in situ conditions. Marine Biology 1986;93:299-303.
Iverson RL, Bittaker HF. Seagrass distribution and abundance in Eastern Gulf of Mexico coastal waters. Estuarine Coastal Shelf Science 1986;22:577-602.
Kaldy JE, Dunton KH. Above- and below-ground production, biomass and reproductive ecology of Thalassia testudinum (turtle grass) in a subtropical coastal lagoon. Marine Ecology Progress Series 2000;193:271-283.
Lewis III RR, Estevez ED. The ecology of Tampa Bay, Florida: an estuarine profile. United States Fish and Wildlife Service, National Wetlands Research Center, Slidell, LA. Biological Report 85(7.18) 1988.
Mellors JE. An evaluation of a rapid visual technique for estimating seagrass biomass. Aquatic Botany 1991;42:67-73.
Mueller-Dombois D, Ellenberg H. Aims and Methods of Vegetation Ecology. John Wiley and Sons, New York, 1974, 547 pp..
Neckles HA. Indicator development: seagrass monitoring and research in the Gulf of Mexico. United States Environmental Protection Agency, EPA/620/R-94/029, Gulf Breeze, FL, 62 pp.
Neverauskas VP. Response of a Posidonia community to prolonged reduction in light. Aquatic Botany 1988;31:361-366.
Phillips RC, Lewis RR. Influence of environmental gradients in variations in leaf widths and transplant success in North American seagrasses. Marine Technology Society Journal 1983;17:59-68.
Robblee MB, Barber TR, Carlson PR, Durako MJ, Fourqurean JW, Muehlstein L, Porter LD, Yarbro LA, Zieman RT, Zieman JC. Mass mortality of the tropical seagrass Thalassia testudinum in Florida Bay (USA). Marine Ecology Progress Series 1991;71:297-299.
Rose CD, Sharp WC, Kenworthy WJ, Hunt JH, Lyons WG, Prager EJ, Valentine JF, Hall MO, Whitfield PE, Fourqurean JW. Overgrazing of a large seagrass bed by the sea urchin Lytechinus variegatus in outer Florida Bay. Marine Ecology Progress Series 1999;190:211-222.
Spence DH. Light and plant response in freshwater. In: Evans GC, Bainbridge R, Rackman O, eds. Light as an Ecological Factor, Volume II. Blackwell Scientific, Oxford, 1975 pp. 93-134.
Thayer GW, Murphy PL, LaCroix MW. Responses of plant communities in western Florida Bay to the die-off of seagrasses. Bulletin of Marine Science 1994;54:718-726
Thorhaug A, Blake N, Shroeder PB. The effect of heated effluents from power plants on seagrass (Thalassia) communities quantitatively comparing estuaries in the subtropics to the tropics. Marine Pollution Bulletin 1978;9:181-187.
Tomasko DA, Dawes CJ. Depth distribution of Thalassia testudinum in two meadows on the west coast of Florida; a difference in effect of light availability. Marine Ecology 1988;9:123-130.
Tomlinson PB. On the morphology and anatomy of turtle grass, Thalassia testudinum (hydrocharitaceae), leaf anatomy and development. Bulletin of Marine Science 1972;22:75-93.
Tomlinson PB. Vegetative morphology and meristem dependence-the foundation of productivity in seagrasses. Aquaculture 1974;4:107-130.
Treshow M. Environment and Plant Response. McGraw-Hill, New York 1970.
van Tussenbroek BI. Aspects of the reproductive ecology of Thalassia testudinum in Puerto Morelos reef lagoon, Mexico. Botanica Marina 1994;37:413- 419.
White D, Kimerling AJ, Overton WS. Cartographic and geometric components of a global sampling design for environmental monitoring. Cartography and Geographic Information Systems 1992;19:5-22.
Zieman JC. The ecology of the seagrasses of south Florida: a community profile. United States Fish and Wildlife Service , Office of Biological Services, Washington, D.C., 1982/25.
Zieman JC. A review of certain aspects of the life, death, and distribution of seagrasses of the southeastern Unites States 1960-1985. In Durako MJ, Phillips RC. 1987, p. 53-76.
Lewis, ed. Proceedings of the Symposium on Subtropical-Tropical Seagrasses
of the Southeastern United States. Florida Marine Research Publications,
Zieman JC, Zieman RT. The ecology of the seagrass meadows of the west coast of Florida: a community profile. Minerals Management Service and United States Fish and Wildlife Service, Research and Development, Biological Report 85(7.25), 1989.
Zieman JC, Fourqurean JW, Iverson RL. Distribution, abundance and productivity of seagrasses and macroalgae in Florida Bay. Bulletin of Marine Science 1989;44:292-311.
Zieman JC, Fourqurean JW, Frankovich TA. Seagrass die-off in Florida Bay: long-term trends in abundance and growth of turtle grass, Thalassia testudinum. Estuaries 1999;22:460-470.
Duarte CM, Marbá N, Agawin N, Cebrián J, Enríquez S, Fortes MD, Gallegos ME, Merino M, Olesen B, Sand-Jensen K, Uri J, Vermaat J. Reconstruction of seagrass dynamics: age determinations and associated tools for the seagrass ecologist. Marine Ecology Progress Series 1994;107:195-209.
Durako MJ. Seagrass die-off in Florida Bay: changes in shoot demographic characteristics and population dynamics in Thalassia testudinum. Marine Ecology Progress Series 1994;110:59-66.
Durako MJ. Indicators of seagrass ecological condition: an assessment based on spatial and temporal changes associated with the mass mortality of the tropical seagrass Thalassia testudinum. In: Dyer KR, Orth RJ (eds.), Changes in Fluxes in Estuaries: Implications for Science to Management. Olsen and Olsen, Fredensborg, Denmark. 1995. pp. 261-266.
Fourqurean JW, Zieman JC, Powell GVN. Relationships between porewater nutrients and seagarsses in a subtropical carbonate environment. Marine Biology 1992;114:57-65.
Landsberg JH, Blakesley BA. Resource health issues in Florida Bay: linking disease and mortalities. In: A Report by Principal Investigators or the Florida Bay Science Conference, October 17-18, 1995, pp. 185-188.
Neckles HA. Indicator development: seagrass monitoring and research in the Gulf of Mexico. United States Environmental Protection Agency, Office of Research and Development, EPA/620/R-94/029, 64 pp.
Zimmerman RC, Smith RD, Alberte RS. Thermal acclimation and whole-plant carbon balance in Zostera marina L. (eelgrass). Journal of Experimental Marine Biology and Ecology 1989;130:93-109.