Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Herbivory of oil-exposed submerged aquatic vegetation Ruppia maritima

  • Charles W. Martin ,

    Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

    martin.charles.w@gmail.com

    Affiliation University of Florida/Institute of Food and Agricultural Sciences Nature Coast Biological Station, Cedar Key, Florida, United States of America

  • Erick M. Swenson

    Roles Conceptualization, Data curation, Methodology, Writing – original draft, Writing – review & editing

    Affiliation Department of Oceanography and Coastal Sciences, Louisiana State University, Baton Rouge, Louisiana, United States of America

Herbivory of oil-exposed submerged aquatic vegetation Ruppia maritima

  • Charles W. Martin, 
  • Erick M. Swenson
PLOS
x

Abstract

Oil spills, such as the Deepwater Horizon spill in the Gulf of Mexico, have the potential to dramatically alter coastal food webs through a variety of mechanisms. While oil can have direct impacts on primary producers through toxicity and shading, it is also possible that more subtle, indirect changes to the interactions among organisms could alter energy flow through the ecosystem. Here, we present the results of a series of manipulative experiments to determine the impacts of oil exposure on herbivory of Ruppia maritima, one of the most common species of submerged vegetation found in the region impacted by the 2010 Deepwater Horizon oil spill. In previous experiments, R. maritima was grown in a range of manipulated sediment oil concentrations. Using plant tissue from this experiment, we analyzed the effects of oil on plant chemical composition and found that plant carbon:nitrogen ratio (C:N) was reduced by as much as 21% in plants exposed to higher concentrations of oil. Given that nitrogen plays a key role in herbivore preference patterns, we performed herbivory assays and found oil-contaminated plants were preferred by herbivores in choice trials, although subsequent no-choice experiments indicated herbivores consumed less oil-contaminated tissue. We hypothesize the reason for this is that more tissue of higher C:N content is needed to meet similar metabolic demands while avoiding the potentially negative impacts of feeding on contaminated tissues. These results indicate that substantial food web alterations may occur via enhanced consumption of oil-exposed plants and provides vital information necessary to assess the large-scale impact of oil on submerged macrophytes.

Introduction

The explosion of the Deepwater Horizon drilling rig off the coast of Louisiana in the Gulf of Mexico (GOM) was a large-scale disaster that resulted in loss of human life and numerous environmental consequences, many of which are still under investigation. Almost 5 million barrels of unrefined Sweet Louisiana Crude oil was released over a 3-month period in 2010, making it the largest marine spill in US history [1, 2]. Despite numerous efforts to protect coastal waters from released oil, including application of dispersants to enhance microbial breakdown of oil, burning of offshore oil, opening of Mississippi River control structures to increase freshwater discharge, and placement of oil protection booms and cleanup crews in strategic locations [3], more than 1700 km of shoreline was impacted in the northern GOM [4]. Oil impacted a wide variety of critical habitats from coastal Louisiana to the Florida Panhandle, including emergent marshes, oyster reefs, mangroves, beaches, and beds of submerged vegetation [47].

The coastal wetlands impacted by the spill provide a variety of key ecosystem functions that enhance the productivity and resilience of the region. Among these numerous ecosystem services, coastal wetlands provide abundant food sources and refugia for juvenile organisms (including those of commercial and recreational importance). While our knowledge of oil’s impact to emergent grasses such as Spartina alterniflora and Juncus roemerianus (reviewed in [8]) is substantial, much less is known about the effects on submerged vegetation. Given the lack of traditional monitoring and turbid waters that persist in many northern GOM estuaries, impact assessments of submerged vegetation fall far behind those of other macrophytes with fewer published studies (but see [6, 7, 9]) despite their importance as a food resource and refuge [1013].

A variety of submerged grasses persist in the estuaries of the northern GOM that were impacted by this spill [14, 15]. Among the most abundant and widely distributed is Ruppia maritima (herafter referred to as Ruppia), especially in coastal Louisiana [1618]. Ruppia is highly tolerant to the rapid, and often seasonal, fluctuations in salinity and other environmental parameters that occur in estuaries. It also supports a diverse food web, including invertebrates, fishes, and birds [1921]. Given the numerous organisms and productive food web supported by Ruppia, understanding the impact of oil on both the plant itself and the larger ecosystem is critical to conserving and managing estuarine resources. We know from previous work [6] that Ruppia is resilient to many of oil’s negative effects, with sustained growth and biomass, although subtle impacts to reproduction, root morphology, and erosion can occur.

In general, seagrass and submerged vegetation support a diverse food web directly by providing energy and a food source for organisms (through herbivory), and indirectly as a refuge from predators [20, 2224]. To date, a number of studies have quantified the herbivory of (primarily) marine macrophytes through both field assessments [22, 25] and laboratory investigations [26]. Herbivory of Ruppia, however, has received comparatively less attention (but see [23]). Given the food web supported by Ruppia [20], a better understanding of the role of Ruppia as a food source, and the concomitant effects of oil contamination, are needed to construct more detailed food web models and habitat linkages, as well as risk assessments to disturbances such as oil spills.

Here, we assess the impacts of oil on herbivory of Ruppia. Using tissue from a previous experiment that exposed Ruppia to a range of oil concentrations, we performed feeding assays under controlled laboratory conditions to determine: 1) herbivore preference (choice) patterns for Ruppia grown in oil, and 2) the rate of foraging on oil-exposed Ruppia. Coupled with these investigations is an analysis to determine the chemical composition (C:N ratio) of plants as a potentially important covariate in these assessments. The overarching aim of this research was to determine the potential alterations to the trophic transfer from primary producer to herbivore that occurs via oil contamination.

Methods

Oil exposure and plant chemical composition

Previously, Martin et al. [6] reported on the growth, reproduction, and morphological characteristics of Ruppia grown under 4 oil concentrations: none (0 mL oil/L tank), low (0.26 mL oil/L tank volume), medium (0.53 mL oil/L tank volume), and high (1.05 mL oil/L tank volume) oil. Plants were grown in randomized, aerated mesocosms and harvested after 1 month. These concentrations were within the range found under coastal Louisiana field conditions [27]. Additional experimental details and results can be found in Martin et al. [6]. We utilized plant tissue from that experiment to test whether oil exposure affects herbivore preference and foraging patterns.

Available plant leaf material, likely the most susceptible and frequently grazed portion of the plant, was analyzed for chemical composition to determine the carbon:nitrogen (C:N) ratio, as C:N ratio has been found to be a strong determinant for herbivore preference [26]. Leaves were removed from the stem, dried to a constant weight at 60°C, ground to a powder using a mortar and pestle, and analyzed for C:N content using established methods [28, 29]. Ten replicates were conducted for each oil treatment.

Herbivore assays

To test herbivore preference patterns, two experiments were conducted: 1) choice tests and 2) foraging rate tests. Each experiment was performed using one of two herbivores: grass shrimp (Palaemonetes pugio) and amphipods (Gammarus mucronatus), both abundant and recognized herbivores of submerged vegetation [23, 24]. Pre-treatment husbandry conditions were consistent among animals that had been collected near Lake Pontchartrain, LA (USA) and held under identical lab conditions. We randomized individuals to treatments further ensuring we did not bias results due to herbivore selection. All trials using grass shrimp were conducted in 3.8 L aquaria with 5 shrimp in each and amphipod trials were conducted in 0.5 L aquaria with 8 amphipods in each, both within the range of natural densities found in the field. All aquaria were aerated and environmental conditions held constant throughout the duration of the trial (salinity 5–7, temperature 23°C). While shrimp and amphipod trials were conducted at separate times, as were choice and foraging rate experiments, all oil treatments were performed simultaneously and completely randomized and used individuals of consistent size. All herbivores were starved for 24 hours prior to the trial and no mortality was noted during trials.

Using remaining ground tissue from the above chemical analyses, artificial leaves were constructed by pouring agar and ground tissue over window screening cut to simulate the size of a leaf. Specifically, deionized water and agar at a ratio of 25 mL:0.3 g agar was microwaved for approximately 1 minute, poured into a plastic sheet with wells cut to fit the window screen, and 50 mg of plant tissue placed homogenously in each well. These methods are similar to previous herbivory assays [26, 28, 30, 31]. After the agar cooled, each artificial leaf was weighed on a balance pre- and post-experiment (described below). The proportion loss of material was calculated and used for all comparisons. During each experiment, autogenic controls with no herbivores were run to ensure that artificial leaves did not lose mass over the trial period; we did not note any loss of mass, therefore we did not include herbivore controls in subsequent analyses because inclusion of this data (all 0%, and thus no variance) would likely lead to a failure to meet the assumption of homogeneity of variance among treatments.

Experiment 1: Choice tests.

In choice tests, each herbivore was offered a choice between an artificial leaf from 2 of the previously mentioned oil treatments. Each pairwise comparison was tested: None vs Low, None vs Medium, None vs High, Low vs Medium, Low vs High, and Medium vs High. Shrimp or amphipods were allowed to feed for 24 hours before the trial ended and artificial leaves removed, patted dry with a paper towel, and reweighed. Each unique choice comparison was replicated 12 times.

Experiment 2: Foraging rate tests.

In foraging rate tests, we determined the rate at which herbivores feed on oil-contaminated tissues in the aforementioned concentrations. We offered herbivores one leaf (i.e., no choice) from each treatment. In this experiment, shrimp were allowed to feed for 24 hours and each treatment replicated 12 times. Amphipods were also allowed to feed for 24 hours. However, due to little feeding the experiment was repeated over 48 hours. Trials using amphipods in this experiment were replicated 18 times.

Statistical analyses

Prior to any analysis, assumptions of parametric statistics (normality and homogeneity of variance) were tested and transformed if necessary. Plant C:N ratio was analyzed using a one-way analysis of variance with Tukey’s post-hoc analysis to determine which treatments differed. Choice tests were analyzed using paired t-tests for each individual comparison. Foraging rate comparisons were made using a one-way analysis of variance, again with Tukey’s post hoc pairwise comparisons. In choice and foraging rate tests, each herbivore was tested separately. Results were considered significant at p < 0.05.

Ethics statement

Animals and plants used in this study were collected from wild populations on public lands. No vertebrates or protected species were used or impacted during this study. All collections were made under Louisiana Department of Wildlife and Freshwater Fisheries permit number SCP152.

Results

Oil exposure and plant chemical composition

Plants grown in different oil concentrations had significantly different C:N ratios (F3,36 = 4.81, p = 0.006). A clear trend of decreasing C:N ratio with increasing oil exposure was detected (Fig 1), with post hoc comparisons indicating that no oil was significantly different than medium (p = 0.049) and high oil (p = 0.001). Average C:N ratio in no oil was approximately 27.5, and decreased to around 25.3, 23.0, and 21.7 in low, medium, and high oil, respectively.

thumbnail
Fig 1. Carbon:nitrogen (C:N) ratio in plant tissues.

C:N ratio in plants grown in no (white), low (green), medium (yellow), and high (red) oil-contaminated sediments. Different letters indicate statistically significant differences.

https://doi.org/10.1371/journal.pone.0208463.g001

Herbivore assays

Experiment 1: Choice tests.

Grass shrimp generally demonstrated preference patterns for grasses grown under higher oil concentrations (Table 1, Fig 2). Significant differences in foraging were detected for comparisons of None vs Medium, None vs High, Low vs High, and Medium vs High (Table 1). In each case, more material was consumed in the tissue with oil higher exposure (Fig 2). In general, shrimp consumed between 5 and 30% of material during trials, within the optimal range for foraging trials [32].

thumbnail
Table 1. Results from paired t-tests comparing herbivore preference patterns in Experiment 2 among plants with no (0 mL oil/L tank), low (0.26 mL oil/L tank volume), medium (0.53 mL oil/L tank volume), and high (1.05 mL oil/L tank volume) oil exposure.

Significant results (p < 0.05) are shown in bold.

https://doi.org/10.1371/journal.pone.0208463.t001

thumbnail
Fig 2. Results from Experiment 1: Grass shrimp.

Paired choice experiments using grass shrimp (P. pugio) herbivores and plants grown in 4 oiled conditions: no (white), low (green), medium (yellow), and high (red). Asterisk indicates that a statistically significant difference exists.

https://doi.org/10.1371/journal.pone.0208463.g002

Amphipods also showed similar trends in consumption preferences, albeit with less amount of material consumed than grass shrimp (generally less than 10% of material consumed). Significant preferences (Table 1, Fig 3) were detected for the following comparisons: None vs High, Low vs High, and Medium vs High. Again, herbivores preferred plant tissue that had been grown under higher oil concentrations.

thumbnail
Fig 3. Results from Experiment 1: Amphipods.

Paired choice experiments using amphipod (G. mucronatus) herbivores and plants grown in 4 oiled conditions: no (white), low (green), medium (yellow), and high (red). Asterisk indicates that a statistically significant difference exists.

https://doi.org/10.1371/journal.pone.0208463.g003

Experiment 2: Foraging rate tests.

When not given a choice between plant tissues, different trends were observed with a larger proportion of tissue consumed in tissues with none/lower oil exposures. For grass shrimp, significant differences were detected in the amount of plant tissue consumed among plants from different oil exposures (F3,44 = 20.294, p < 0.001; Fig 4). More plant material was consumed from none (9.6%) and low (9.3%) treatments than from artificial leaves from medium (3.1%) and high (2.3%) oil concentrations.

thumbnail
Fig 4. Results from Experiment 2: Grass shrimp.

Foraging rate experimental results indicating consumption by grass shrimp (P. pugio). Colors represent plants grown under one of 4 different oil conditions: no (white), low (green), medium (yellow), and high (red). Different letters indicate statistically significant differences.

https://doi.org/10.1371/journal.pone.0208463.g004

For amphipods, similar trends were evident. When allowed to forage for 24 hours, no difference was detected (F3,68 = 2.51, p = 0.066, Fig 5A). However, amphipods consumed very little tissue during these trials (2.3% in no oil, and around 1% in other treatments). After a longer time to forage and almost twice the amount of plant material consumed, significant differences were detected (F3,68 = 7.14, p < 0.001; Fig 5B). In these 48 hours trials, significantly more plant material was consumed from the no oil treatment (4.4%) than from plants grown in low (1.8%), medium (2.0%), or high (1.5%) oil treatments.

thumbnail
Fig 5. Results from Experiment 2: Amphipods.

Foraging rate experimental results indicating consumption by amphipods (G. mucronatus) over 24 (A) and 48 (B) hour experimental durations. Colors represent plants grown under one of 4 different oil conditions: no (white), low (green), medium (yellow), and high (red). Different letters indicate statistically significant differences.

https://doi.org/10.1371/journal.pone.0208463.g005

Discussion

Over the past several decades, the GOM has been central to many ecological disturbances including invasive species [33, 34], hurricanes [35], wetland loss/erosion [36], overharvesting/fishery collapse [37], and, most recently, the Deepwater Horizon oil spill. To date, studies conducted in nearshore waters have highlighted the impacts of oil on saltmarshes [8], arthropod insects [38], benthic invertebrates [39, 40], fishes [4143], birds [44], and marine mammals [45]. While the impact of oil on interactions among organisms is the topic of theoretical [9] and field measurements [46], manipulative experiments quantifying the transfer of energy among organisms have been rare, especially at the primary producer-herbivore trophic level.

Historically, coastal and marine submerged macrophytes were thought to provide little energy to higher trophic levels through herbivory due to high C:N ratios [4749] and the indigestibility of cellulose content [50]. More recently, however, there is acknowledgement that these plants do play an important role in coastal food webs [51] because: 1) present-day measurements likely represent a very conservative estimate compared to the historical importance of these macrophytes due to the extirpation and global decline of large grazers such as marine mammals, reptiles, and waterfowl [5254]; 2) nitrogen concentrations in grasses are actually similar to algae [55]; and 3) many herbivorous fishes [56] and widespread abundance of invertebrates mesograzers such as amphipods and urchins [57, 58] exhibit generalist feeding behaviors. While estimates of seagrass production reaching higher trophic levels is highly variable (ranging from ~3–100%, [51, 59]) and site and season dependent, it is now recognized that these plants do play an important role in coastal food webs and, as such, these food webs are at risk from anthropogenic disasters such as oil spills.

Herbivore preference for plants with higher nitrogen content has been well documented in studies of both terrestrial [6062] and marine herbivores [51]. In marine organisms, a wide range of herbivores have exhibited this foraging pattern, including invertebrates [28, 63], fishes [26, 64], and large herbivores such as turtles [47, 65, 66] and dugongs [67]. Here, we documented a consistent decrease in the C:N ratio of plants as oil exposure increased. This change in plant chemical composition coincided with preferential feeding on oil-exposed plant tissues with higher relative N contents and, when no choice was present, grazers consumed greater proportions of tissues without oil exposure or with lower exposures that had lower relative N contents under laboratory conditions.

One potential explanation for the seemingly contradictory result of preference for higher exposure leaves (higher nitrogen) in choice trials, yet consumption of more tissue of lower exposure (lower nitrogen) is that this represents a compensatory response for grazers [28]. In short, grazers may need to consume more plant tissue when the food has lower nitrogen content to meet metabolic demands. This is a trend that has been previously observed in seagrass ecosystems. Valentine and Heck [28] performed a series of field and lab experiments manipulating nutrients (and therefore leaf nitrogen content) in Thalassia testudinum and found that Lytechinus variegatus urchins fed at higher rates from low nitrogen and consumed less from nitrogen-enriched leaves such that approximately equivalent amounts of nitrogen were consumed regardless of mass of tissue that needed to be ingested. This study confirms that these findings are also true for Ruppia and shrimp/amphipod herbivores and agrees with their finding [28] and adds that PAH contamination may not be a deterrent for grazers, especially when herbivores can benefit from getting high N tissues.

Based on the results of this study, we hypothesize that significant food web impacts may occur as a result of sublethal oil exposure to plants that form a foraging base for the food web. Despite this, we also acknowledge a number of drawbacks that limit the findings of this study and provide fruitful topics for future research. The study conducted here was a lab-based assessment, and future efforts need to verify these patterns in the field and confirm these patterns in a more realistic setting where variability in environmental conditions, predator presence, and additional food choices exist. Moreover, while plants were exposed to oil, herbivores were not exposed to oil, which may additionally alter herbivore health and physiology and impact foraging activities. Herbivores may also exhibit long-term consequences from foraging on oil contaminated tissues that were not documented within the time frame of this study. Additional research documenting mortality rates for these herbivores, as well as sublethal implications such as foraging, reproduction, and predator response, could yield greater insights into the cumulative impacts of oil in coastal environments. Changes in feeding could be due to contaminant loads in tissue, which were not measured during this study. By switching between foraging on unpolluted (lower N) and oil-contaminated tissues (higher N), herbivores may be able to meet metabolic demands while keep contaminant loads in check. While we hypothesized that changes in choice patterns and feeding rates were the result of C:N ratios, it is also possible that an undocumented and unquantified covarying variable influenced this trend. For example, C:N may be correlated with phenolics or other chemical defenses that would alter feeding patterns [68]. Moreover, we know little about the levels of ecological significance in these ratios and a better understanding of food web dynamics may be attained by determining variability in C:N ratios and the ensuing food web consequences. Finally, we also lack a detailed understanding of the mechanisms behind the reported shift in plant chemical composition. We speculate that shifts in microbial communities may have altered the available resources for the plant and resulted in the shift documented here. Moreover, the change in C:N content could be due to mortality of old leaves and rapid new growth, which may have lower C:N ratios.

In conclusion, research to date has focused primarily on the direct impacts of oil [69, 70]. However, findings presented here indicate that important indirect effects may occur through the subtle alterations of trophic pathways that link primary producers with higher trophic levels. Expanding these lab-based results into field settings is critical for developing a more comprehensive understanding of oil’s direct and indirect impacts in coastal ecosystems. Incorporating such knowledge into ongoing ecological modeling efforts will elicit greater insights into food webs, threats, and resilience of northern GOM estuaries, with the key implications for the management and protection of these vital areas.

Acknowledgments

This research was made possible by a grant from The Gulf of Mexico Research Initiative. Data are publicly available through the Gulf of Mexico Research Initiative Information & Data Cooperative (GRIIDC) at https://data.gulfresearchinitiative.org (doi:<R4.x264.000:0080>). We thank R.E. Turner, M. Polito, T. Mauney, J. Valentine, A. McDonald, C. Milan, J. Lee, and L. Hollis for their assistance that contributed toward the completion of this project and the constructive comments from the PLoS Editorial Staff and anonymous reviewers.

References

  1. 1. Camilli R, Reddy CM, Yoerger DR, Van Mooy BA, Jakuba MV, Kinsey JC, et al. Tracking hydrocarbon plume transport and biodegradation at Deepwater Horizon. Science 2010; 330(6001): 201–204. pmid:20724584
  2. 2. Crone TJ, Tolstoy M. Magnitude of the 2010 Gulf of Mexico oil leak. Science 2010; 330(6004): 634–634. pmid:20929734
  3. 3. Peterson CH, Anderson SS, Cherr GN, Ambrose RF, Anghera S, Bay S, et al. A tale of two spills: novel science and policy implications of an emerging new oil spill model. BioScience 2012; 62(5): 461–469.
  4. 4. Michel J, Owens EH, Zengel S, Graham A, Nixon Z, Allard T., et al. Extent and degree of shoreline oiling: Deepwater Horizon oil spill, Gulf of Mexico, USA. PloS ONE 2013; 8(6): e65087. pmid:23776444
  5. 5. Silliman BR, van de Koppel J, McCoy MW, Diller J, Kasozi GN, Earl K, et al. Degradation and resilience in Louisiana salt marshes after the BP–Deepwater Horizon oil spill. Proceedings of the National Academy of Sciences 2012; 109(28): 11234–11239.
  6. 6. Martin CW, Hollis LO, Turner RE. Effects of oil-contaminated sediments on submerged vegetation: an experimental assessment of Ruppia maritima. PloS ONE 2015; 10(10): e0138797. pmid:26430971
  7. 7. Kenworthy WJ, Cosentino-Manning N, Handley L, Wild M, Rouhani S. Seagrass response following exposure to Deepwater Horizon oil in the Chandeleur Islands, Louisiana (USA). Marine Ecology Progress Series 2017; 576: 145–161.
  8. 8. Pezeshki SR, DeLaune RD. United States Gulf of Mexico coastal marsh vegetation responses and sensitivities to oil spill: a review. Environments 2015; 2(4): 586–607.
  9. 9. McCann MJ, Able KW, Christian RR, Fodrie FJ, Jensen OP, Johnson JJ, et al. Key taxa in food web responses to stressors: the Deepwater Horizon oil spill. Frontiers in Ecology and the Environment, 2017; 15(3): 142–149.
  10. 10. Beck MW, Heck KL, Able KW, Childers DL, Eggleston DB, Gillanders BM, et al. The identification, conservation, and management of estuarine and marine nurseries for fish and invertebrates: a better understanding of the habitats that serve as nurseries for marine species and the factors that create site-specific variability in nursery quality will improve conservation and management of these areas. Bioscience 2001; 51(8): 633–641.
  11. 11. Heck KL, Hays G, Orth RJ. Critical evaluation of the nursery role hypothesis for seagrass meadows. Marine Ecology Progress Series 2003; 253: 123–136.
  12. 12. Martin CW, Valentine JF. Impacts of a habitat-forming exotic species on estuarine structure and function: an experimental assessment of Eurasian milfoil. Estuaries and Coasts 2011; 34(2): 364–372.
  13. 13. Rozas LP, Martin CW, Valentine JF. Effects of reduced hydrological connectivity on the nursery use of shallow estuarine habitats within a river delta. Marine Ecology Progress Series 2013; 492: 9–20.
  14. 14. Martin CW, Valentine JF. Eurasian milfoil invasion in estuaries: physical disturbance can reduce the proliferation of an aquatic nuisance species. Marine Ecology Progress Series 2012; 449: 109–119.
  15. 15. Hillmann ER, DeMarco KE, LaPeyre MK. Establishing a Baseline of Estuarine Submerged Aquatic Vegetation Resources Across Salinity Zones Within Coastal Areas of the Northern Gulf of Mexico. Journal of the Southeastern Association of Fish and Wildlife Agencies 2016; 3: 25–32.
  16. 16. Poirrier MA, Handley LR. Chandeleur Islands. Seagrass status and trends in the northern Gulf of Mexico, 2002, 62–71.
  17. 17. Cho HJ, Poirrier MA. Seasonal growth and reproduction of Ruppia maritima L. sl in Lake Pontchartrain, Louisiana, USA. Aquatic Botany 2005; 81(1): 37–49.
  18. 18. Cho HJ, Biber P, Nica C. The rise of Ruppia in seagrass beds: changes in coastal environment and research needs. Handbook on Environmental Quality. Nova Science, New York, 2009; pp. 1–15.
  19. 19. Orth RJ, Moore KA. Distribution of Zostera marina L. and Ruppia maritima L. sensu lato along depth gradients in the lower Chesapeake Bay, USA. Aquatic Botany 1988; 32(3): 291–305.
  20. 20. Kanouse S, La Peyre MK, Nyman JA. Nekton use of Ruppia maritima and non-vegetated bottom habitat types within brackish marsh ponds. Marine Ecology Progress Series 2006; 327: 61–69.
  21. 21. McCall DD, Rakocinski CF. Grass shrimp (Palaemonetes spp.) play a pivotal trophic role in enhancing Ruppia maritima. Ecology 2007; 88(3): 618–624. pmid:17503590
  22. 22. Kirsch KD, Valentine JF, Heck KL. Parrotfish grazing on turtlegrass Thalassia testudinum: evidence for the importance of seagrass consumption in food web dynamics of the Florida Keys National Marine Sanctuary. Marine Ecology Progress Series 2002; 227: 71–85.
  23. 23. Valinoti CE, Ho CK, Armitage AR. Native and exotic submerged aquatic vegetation provide different nutritional and refuge values for macroinvertebrates. Journal of Experimental Marine Biology and Ecology 2011; 409(1–2): 42–47.
  24. 24. Kauffman TC, Martin CW, Valentine JF. Hydrological alteration exacerbates the negative impacts of invasive Eurasian milfoil Myriophyllum spicatum by creating hypoxic conditions in a northern Gulf of Mexico estuary. Marine Ecology Progress Series 2018; 592: 97–108.
  25. 25. Duffy JE, Richardson JP, Canuel EA. Grazer diversity effects on ecosystem functioning in seagrass beds. Ecology Letters 2003; 6(9): 881–881.
  26. 26. Goecker ME, Heck KL, Valentine JF. Effects of nitrogen concentrations in turtlegrass Thalassia testudinum on consumption by the bucktooth parrotfish Sparisoma radians. Marine Ecology Progress Series 2005; 286: 239–248.
  27. 27. Turner RE, Overton EB, Meyer BM, Miles MS, McClenachan G, Hooper-Bui L, et al. Distribution and recovery trajectory of Macondo (Mississippi Canyon 252) oil in Louisiana coastal wetlands. Marine Pollution Bulletin 2014; 87(1–2): 57–67. pmid:25176275
  28. 28. Valentine JF, Heck KL. The role of leaf nitrogen content in determining turtlegrass (Thalassia testudinum) grazing by a generalized herbivore in the northeastern Gulf of Mexico. Journal of Experimental Marine Biology and Ecology 2001; 258(1): 65–86. pmid:11239626
  29. 29. Herman RW, Valls FC, Hart T, Petry MV, Trivelpiece WZ, Polito MJ. Seasonal consistency and individual variation in foraging strategies differ among and within Pygoscelis penguin species in the Antarctic Peninsula region. Marine Biology 2017; 164(5): 115.
  30. 30. Hay ME. Patterns of fish and urchin grazing on Caribbean coral reefs: are previous results typical?. Ecology 1984; 65(2): 446–454.
  31. 31. Prado P, Heck KL. Seagrass selection by omnivorous and herbivorous consumers: determining factors. Marine Ecology Progress Series 2011; 429: 45–55.
  32. 32. Peterson CH, Renaud PE. Analysis of feeding preference experiments. Oecologia, 1989; 80(1): 82–86. pmid:23494349
  33. 33. Martin CW, Valentine MM, Valentine JF. Competitive interactions between invasive Nile tilapia and native fish: the potential for altered trophic exchange and modification of food webs. PLoS ONE 2010; 5(12): e14395. pmid:21200433
  34. 34. Scyphers SB, Powers SP, Akins JL, Drymon JM, Martin CW, Schobernd ZH, et al. The role of citizens in detecting and responding to a rapid marine invasion. Conservation Letters 2015; 8(4): 242–250.
  35. 35. Tweel AW, Turner RE. Contribution of tropical cyclones to the sediment budget for coastal wetlands in Louisiana, USA. Landscape Ecology 2014; 29(6): 1083–1094.
  36. 36. Osland MJ, Griffith KT, Larriviere JC, Feher LC, Cahoon DR, Enwright NM, et al. Assessing coastal wetland vulnerability to sea-level rise along the northern Gulf of Mexico coast: Gaps and opportunities for developing a coordinated regional sampling network. PloS ONE 2017; 12(9): e0183431. pmid:28902904
  37. 37. Frederick P, Vitale N, Pine B, Seavey J, Sturmer L. Reversing a rapid decline in oyster reefs: effects of durable substrate on oyster populations, elevations, and aquatic bird community composition. Journal of Shellfish Research 2016; 35(2): 359–367.
  38. 38. Pennings SC, McCall BD, Hooper-Bui L. Effects of oil spills on terrestrial arthropods in coastal wetlands. BioScience 2014; 64(9): 789–795.
  39. 39. Deis DR, Fleeger JW, Bourgoin SM, Mendelssohn IA, Lin Q, Hou A. Shoreline oiling effects and recovery of salt marsh macroinvertebrates from the Deepwater Horizon Oil Spill. PeerJ 2017; 5: e3680. pmid:28828273
  40. 40. Fleeger JW, Riggio MR, Mendelssohn IA, Lin Q, Hou A, Deis DR. Recovery of saltmarsh meiofauna six years after the Deepwater Horizon oil spill. Journal of Experimental Marine Biology and Ecology 2018; 502: 182–190.
  41. 41. Able KW, López-Duarte PC, Fodrie FJ, Jensen OP, Martin CW, Roberts BJ, et al. Fish assemblages in Louisiana salt marshes: effects of the Macondo oil spill. Estuaries and Coasts 2011; 38(5): 1385–1398.
  42. 42. Vastano AR, Able KW, Jensen OP, López-Duarte PC, Martin CW, Roberts BJ. Age validation and seasonal growth patterns of a subtropical marsh fish: The Gulf Killifish, Fundulus grandis. Environmental Biology of Fishes 2017; 100(10): 1315–1327.
  43. 43. Martin CW. Avoidance of oil contaminated sediments by estuarine fishes. Marine Ecology Progress Series 2017; 576: 125–134.
  44. 44. Haney JC, Geiger HJ, Short JW. Bird mortality from the Deepwater Horizon oil spill. I. Exposure probability in the offshore Gulf of Mexico. Marine Ecology Progress Series 2014, 513: 225–237.
  45. 45. Wallace BP, Brosnan T, McLamb D, Rowles T, Ruder E, Schroeder B, et al. Effects of the Deepwater Horizon oil spill on protected marine species. Endangered Species Research 2017; 33: 1–7.
  46. 46. Polito MJ, Lopez-Duarte PC, Olin J, Johnson JJ, Able K, Martin CW, et al. Quantifying Trophic Interactions and carbon Flow in Louisiana Salt Marshes Using Multiple Biomarkers. In AGU Fall Meeting Abstracts. 2017.
  47. 47. Bjorndal KA. Nutrition and grazing behavior of the green turtle Chelonia mydas. Marine Biology 1980; 56(2): 147–154.
  48. 48. Duarte CM. Seagrass nutrient content. Marine Ecology Progress Series 1990; 201–207.
  49. 49. Valiela I. 2013. Marine Ecological Processes. Springer Science & Business Media.
  50. 50. Lawrence JM. On the relationships between marine plants and sea urchins. Oceanography and Marine Biology: An Annual Review 1975; 13: 213–286.
  51. 51. Valentine JF, Heck KL. Seagrass herbivory: evidence for the continued grazing of marine grasses. Marine Ecology Progress Series 1999; 291–302.
  52. 52. Dayton PK, Thrush SF, Agardy MT, Hofman RJ. Environmental effects of marine fishing. Aquatic Conservation: Marine and Freshwater Ecosystems 1995; 5(3): 205–232.
  53. 53. Jackson JB, Kirby MX, Berger WH, Bjorndal KA, Botsford LW, Bourque BJ et al. Historical overfishing and the recent collapse of coastal ecosystems. Science 2001; 293(5530): 629–637. pmid:11474098
  54. 54. Valentine JF, Duffy JE. The central role of grazing in seagrass ecology. In Seagrasses: Biology, Ecology and Conservation (pp. 463–501). Springer, Dordrecht. 2007.
  55. 55. Thayer GW, Bjorndal KA, Ogden JC, Williams SL, Zieman JC. Role of larger herbvores in seagrass communities. Estuaries 1984; 7(4): 351–376.
  56. 56. Hay ME. The ecology and evolution of seaweed-herbivore interactions on coral reefs. Coral Reefs, 1997, 16(1): S67–S76.
  57. 57. Zimmerman MS, Livingston RJ. Effects of kraft-mill effluents on benthic macrophyte assemblages in a shallow-bay system (Apalachee Bay, North Florida, USA). Marine Biology 1976; 34(4): 297–312.
  58. 58. Valentine JF, Heck KL. The role of sea urchin grazing in regulating subtropical seagrass meadows: evidence from field manipulations in the northern Gulf of Mexico. Journal of Experimental Marine Biology and Ecology 1991; 154(2): 215–230.
  59. 59. Klumpp DW, Salita-Espinosa JT, Fortes MD. Feeding ecology and trophic role of sea urchins in a tropical seagrass community. Aquatic Botany 1993; 45(2–3): 205–229.
  60. 60. Kraft SK, Denno RF. Feeding responses of adapted and non-adapted insects to the defensive properties of Baccharis halimifolia L.(Compositae). Oecologia 1982; 52(2): 156–163. pmid:28310500
  61. 61. Coley PD. Herbivory and defensive characteristics of tree species in a lowland tropical forest. Ecological Monographs 1983; 53(2): 209–234.
  62. 62. Schroeder LA. Changes in tree leaf quality and growth performance of lepidopteran larvae. Ecology 1986; 67(6): 1628–1636.
  63. 63. Lilly GR. The influence of diet on the growth and energetics of the tropical sea urchin, Tripneustes ventricosus (Lamarck). PhD. Dissertation, University of British Columbia, Vancouver. 216 p. 1975
  64. 64. McGlathery KJ. Nutrient and grazing influences on a subtropical seagrass community. Marine Ecology Progress Series 1995; 239–252.
  65. 65. Zieman JC, Macko SA, Mills AL. Role of seagrasses and mangroves in estuarine food webs: temporal and spatial changes in stable isotope composition and amino acid content during decomposition. Bulletin of Marine Science 1984; 35(3): 380–392.
  66. 66. Williams SL. Thalassia testudinum productivity and grazing by green turtles in a highly disturbed seagrass bed. Marine Biology 1988; 98(3): 447–455.
  67. 67. Preen A. Impacts of dugong foraging on seagrass habitats: observational and experimental evidence for cultivation grazing. Marine Ecology Progress Series 1995; 201–213.
  68. 68. Steele L, Valentine JF. Seagrass deterrence to mesograzer herbivory: evidence from mesocosm experiments and feeding preference trials. Marine Ecology Progress Series 2015; 524: 83–94.
  69. 69. Lin Q, Mendelssohn IA. Impacts and recovery of the Deepwater Horizon oil spill on vegetation structure and function of coastal salt marshes in the northern Gulf of Mexico. Environmental Science & Technology 2012; 46(7): 3737–3743.
  70. 70. Fodrie FJ, Able KW, Galvez F, Heck KL, Jensen OP, López-Duarte PC, et al. Integrating organismal and population responses of estuarine fishes in Macondo spill research. BioScience 2014; 64(9): 778–788.