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Investigating the effect of oil spills
on the environment and public health.
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Funding Source: Year 3-5 Investigator Grants (RFP-II)

Project Overview

The Environmental Effects of an Oil Spill on Blue Crabs in the Gulf of Mexico and the Dynamics of Recovery: Integrating Oceanography and Molecular Ecology

Principal Investigator
University of Louisiana at Lafayette
Department of Biology
Member Institutions
Tulane University, University of Louisiana at Lafayette

Abstract:

Overview
Dr. Joseph Neigel at the University of Louisiana at Lafayette and Co-PI Caz Taylor at Tulane University were awarded an RFP-II grant at $1,366,817 to conduct the RFP-II project titled, “The Environmental Effects of an Oil Spill on Blue Crabs in the Gulf of Mexico and the Dynamics of Recovery: Integrating Oceanography and Molecular Ecology”. The project consisted of 2 institutions (University of Louisiana at Lafayette, Tulane University), 1 principal investigator (Neigel), 1 co-PI (Taylor), 3 post-docs (Gyory, Plouviez, Yednock), 7 graduate students (Chaisson, Giltz, Kelly, Korsman, Levenson, Starr, Sullivan), and participation by several research technicians and undergraduate students.


The Deepwater Horizon oil (DHOS) spill of 2010 occurred during the critical spawning season of the blue crab, Callinectes sapidus, a commercially and ecologically important species in the Gulf of Mexico (GOM). The eggs of the blue crab hatch into planktonic larvae that spend weeks feeding in offshore waters. When they complete their larval phase, they move into shallower waters, settle to the bottom, and begin developing into juvenile crabs. Laboratory studies have shown that gulf oil and the dispersant used to accelerate the breakdown of the oil are toxic to blue crab larvae. It was therefore anticipated that the oil spill would result in massive mortality of crab larvae leading to a sharp reduction in the abundance of crabs the following year. However, instead of a decrease, the number of crabs in 2011 actually increased. There are multiple possible explanations for why blue crabs did not decline following the oil spill: relatively few larvae may have encountered oil or dispersant at toxic levels, larvae from other sources may have compensated for those lost as a result of the oil spill, or after being broken down by bacteria the oil entered the food web and provided more food for larvae and increased their survival. Another complicating factor is that the biggest accidental marine oil spill on record prompted one of the largest fishery closures on record. Release from both directed crab fishing and bycatch in shrimp trawls could have had such a large positive effect on blue crabs that it overwhelmed the negative effects of the oil spill. Although there is little direct evidence to support the latter explanation, it would explain why not only crabs, but many species of fish also increased in numbers after the oil spill. It also makes it difficult to say whether or not the oil spill did cause an increase in mortality for crab larvae, or what would have happened if the fisheries had not been closed. It was important to answer these questions so that we could understand and learn from what happened during the oil spill.


Before the oil spill, the two investigators on this proposal were already studying blue crabs in the northern GOM. They were collecting specimens and generating data on larval dispersal, rates of larval settlement, and population genetics. They continued this work through the oil spill of 2010 and afterwards, providing them with a unique opportunity to study the effects of the oil spill on blue crabs and address the questions raised in this proposal. They conducted laboratory experiments to assess how blue crabs are affected by oil and dispersant at concentrations found during the spill. These experiments allowed them to identify the chemical signatures of oil exposure, determine the physiological effects of exposure under environmental conditions that match the Gulf of Mexico, and identify genes that are regulated in response to oil or dispersant exposure. They tested larvae from different sites along the coast to see if they had the chemical signatures of exposure. These results were correlated with oceanographic models based on data from 2010 to reconstruct the movements of larvae through the Gulf of Mexico and determine whether the larvae that settled along the coast were exposed to oil while they were developing offshore. They used population genetic methods to determine if larvae from more distant sources could have compensated for larvae lost in the Gulf of Mexico.


This project addressed theme 3 of RFP-II in two ways. First, it investigated the environmental effects of the petroleum/dispersant system on organisms. Second, by looking at the factors that may have prevented or compensated the expected catastrophic impact on blue crabs in the northern Gulf of Mexico, it addressed the science of ecosystem recovery. Results from this research will inform management and policy decisions regarding blue crab fisheries. Members of both the Neigel and Taylor labs presented their findings to stakeholders, management agencies and academics. They involved students through outreach programs for K-12 students (UNO-CERF) and minority students (SACNAS, LAMP) and through informal interactions with students.

Research Highlights

Research from Dr. Neigel and Dr. Taylor has to-date resulted in 8 peer-reviewed publications and 19 datasets submitted to the GoMRI Information and Data Cooperative (GRIIDC), which are/will be available to the public. Significant outcomes of this research, according to GoMRI Research Theme 3 are highlighted below.


Year 1: Analysis of fisheries data. In our proposal we presented a preliminary analysis of blue crab catch-per-unit-effort (CPUE) data from the Louisiana Department of Wildlife and Fisheries (LDWF) fishery-independent sampling program. This analysis found no evidence of reduction in the CPUE for blue crabs in 2010, the year of the DHOS, or the following year. We subsequently examined more data, including records for 17 additional species. Overall, we have found no evidence for unusual declines in CPUE for 2010 or 2011. Indeed, for some species pronounced increases occurred in 2011 (figure1). However, landings were below average in 2010, which suggests that reduced landings resulted from reduced fishing effort, perhaps associated with fisheries closures during the DHOS and decreased market demand associated with public perceptions. Fishery species with decreased landings in 2010 tended to exhibit increased CPUE in 2011, which could be interpreted as evidence for increases in stocks caused by decreases in fishing effort (figure 2). There are important caveats associated with this analysis, and so before drawing conclusions that could have important consequences we planned to extend the analysis with data collected in subsequent years and consider the effects of other, potentially confounding factors.


 

Figure 1. Catch-per-unit-effort of nine coastal Louisiana species in the years preceding, during and after the DHOS. Vertical red lines indicate the year of the DHOS, vertical blue lines the year following the DHOS.

Figure 2. Changes in catch-per-unit effort in 2011 vs. changes in landings in Louisiana for 2010, the year of the DHOS. Points in the upper left quadrant represent species that had increased CPUE a year after decreased landings.

 

Transcriptome Analysis. We exposed juvenile blue crabs for 24-hours to a water- accommodated fraction (WAF) of surrogate oil at a final concentration of 2.5 ppm. This is below the lethal concentration determined from previous studies and was intended to represent a level of exposure that blue crabs likely encountered during the DHOS. After exposure, we extracted RNA from gill and hepatopancreas tissues and contracted a core facility at UC Davis to sequence cDNA libraries made from this RNA. We conducted all subsequent bioinformatics steps at UL Lafayette, including assembling the reads into
transcriptomes, detecting differentially expressed genes, and identifying likely functions for those genes (gene annotation). Patterns of gene expression differed sharply between gill and hepatopancreas tissues, and for both tissues we identified over 2000 transcripts that were significantly different between controls and oil-exposed crabs (figure 3).


The results of this experiment extend our knowledge of the metabolic responses of blue crabs to oil exposure. For example, in the hepatopancreas the two most highly upregulated transcripts following oil exposure encode a short chain dehydrogenase reductase and a glucuronosyltransferase; both were over 8000 fold higher than in controls. In humans and model organisms these two enzymes play key roles in the metabolism of xenobiotic compounds. It therefore appears that we have found two key biomarkers for oil exposure in the blue crab.


We also identified over 300,000 single nucleotide polymorphisms (SNPs) in blue crab transcriptomes, a primary goal for the first year of the project. We began development of high-throughput assays for SNPs in genes that respond to oil exposure and other stressors.

 

Figure 3. Changes in gene expression in juvenile blue crabs following exposure to oil.


Year 2: Particle Tracking Model. The dispersal of blue crab larvae in the northern Gulf of Mexico from western Louisiana to the Florida panhandle spawned in the spring and summer of 2010 was simulated by a Lagrangian particle-tracking model coupled to model-generated flow fields. The model showed that the Mississippi River delta should act as a partial barrier to dispersal and that a significant proportion of larvae (28%) should return to their parent estuary (figure 4). The model also showed that for some spawning events, as much as 96% of the larvae that settled east of the Mississippi delta would have been exposed to oil from the Deepwater Horizon oil spill.

 

Figure 4. Connectivity matrix for larvae released during a full or new moon in the spring and summer of 2010. Color intensity indicates proportion of larvae from each source estuary (vertical axis) that would successfully settle in each destination estuary (horizontal axis). From B.J. Jones, et al. Transport of blue crab larvae in the northern Gulf of Mexico during the Deepwater Horizon oil spill. Marine Ecology Progress Series 527: 143-156

Transcriptome Analysis. By year 2 we had performed RNA-Seq gene expression analysis on two species: the blue crab (Callinectes sapidus) as originally proposed and the bay anchovy (Anchoa mitchilli) to discover how each species responds transcriptionally to the water-accommodated fraction of Macondo crude oil. Extending our analysis to a second species gave us valuable insights. In both species, a substantial fraction of the sequences in the transcriptomes represent alternative transcriptional isoforms of the same genes. Furthermore, in the responses of both species to oil exposure, changes in abundance of different isoforms from the same gene were far more numerous than net changes in abundance of all isoforms from the same gene (Table 1).

Table 1. Differentially expressed isoforms and genes with a false discovery rate < 0.05.


To test the possibility that apparent differences in levels of isoform expression were artifacts created by the transcriptome assembly software (e.g., due to paralogous gene sequences) we quantified isoform abundance with a completely independent method: real-time PCR using isoform-specific primers (Figure 5).

Figure 5. Example of validation of differential expression of isoforms of glucuronosyltransferase (ugt1) and short-chain dehydrogenase reductase (sdr1) in blue crab by real-time PCR with isoform-specific primers. Triplicate real-time PCR ct values are shown for controls (no oil exposure – isoform not detected) and treatment (oil exposure – isoform detected).

Previous work on stress-induced responses in mammals and insects identified the blocking of mRNA splicing as a mechanism to halt protein synthesis. However, this does not appear to be the case for either the blue crab or bay anchovy in their response to oil exposure. The predicted increase in isoform length upon oil exposure was not observed in either species (Figure 6).

Figure 6. Length of up-regulated isoform minus length of the down-regulated isoform for components with one up-regulated and one down-regulated isoform, versus log2Fold difference in expression.

Year 3: Analysis of Fishery-Independent Trawl Data. We compared catch-per-unit- effort (CPUE) for the five years preceding the Deepwater Horizon Spill (2005 – 2009), the year of the oil spill (2010) and the five years following the spill (2011-2011). Data were from the Louisiana Department of Wildlife and Fisheries otter trawl surveys. We used ANOVA to test for an effect of the degree of shoreline oiling on CPUE for the 10 most common species; oiling data were from Michel et al. (2013). Our main results were as follows:

  • When dramatic changes in CPUE occurred in 2010 they were generally increases, as would be expected after fishery closures (an example is shown in figure 7).
  • Level of shoreline oiling (light vs. heavy) did not significantly affect post-spill
  • changes in CPUE for any of the 10 most abundant species.
  • CPUE did decline for some species, but these declines were not statistically associated with heavy oiling.
  • Year-to-year changes in CPUE can be misinterpreted if not examined in the context of long- term trends that began in the years prior to the oil spill and have continued afterwards (an example is shown in figure 8).

Figure 7. An example of a species that showed dramatic increases in CPUE in 2010

Figure 8. Declines in 2010 and afterwards following long-term trends that began earlier.


Effect of DWH oil spill on, and contamination of, blue crabs. Our analysis of megalopal settlement patterns did not show any significant effect of the spill on numbers of settled blue crab megalope. However, we did detect the presence of oil- derived hydrocarbon in magalopae collected in 2010, the year of the spill, whereas megalopae collected in 2011 did not contain detectable levels of oil-derived hydrocarbons. We also detected wastewater contaminants in blue crabs, most notably 4-nonylphenols which are used in industrial surfactants and BHT, which is a plastics- and food-additive.

 

Blue crab population connectivity. Our particle-tracking model had shown that the Mississippi River Delta (MRD) acts as an impediment to larval dispersal and that the greatest exposure of larvae to oil would have occurred east of the MRD. Our population genetic analysis confirmed that the MRD is a highly permeable barrier: allele

frequencies (in pre-spill years) were not significantly different across the delta. These conditions are favorable for detecting effects of the oil spill on genetic variation: the existence of a partial barrier allows selection to shift allele frequencies without immediately being homogenized by dispersal while the permeability of the barrier reduces background levels of genetic difference to near zero. We began investigating differences in allele frequencies for genes involved in detoxification, stress responses, and responses to pathogens.


Previous results from our lab showed that exposure to oil can result in downregulation of genes involved in immune defense. Following this lead, we added to our protocol for genotyping blue crabs DNA-based assays for bacterial (Vibrio spp.) and dinoflagellate (Hematodinium perezi) pathogens. This resulted in the first reported cases of infection of blue crabs in Louisiana by H. perezi as well as the first report of this parasite in the larvae of any crustacean in the US. We began investigating the relationship of infection to oil exposure and other environmental factors.

Year 4: Misidentification of larvae and studies of blue crab settlement. We identified an important concern regarding studies of blue crab settlement in the GOM. There are two species of Callinectes common in the GOM, the blue crab, C. sapidus, and the lesser blue crab, C. similis, with larvae that are extremely difficult to distinguish morphologically. In literature survey, we found that in all of 19 previous studies of blue crab settlement either the characters used to identify larvae were unreliable or no attempt was made to distinguish the larvae of the two Callinectes species. We developed a DNA “barcoding” method to distinguish the larvae of blue crabs from other Callinectes, and discovered that many of the anomalies and discrepancies among previous studies can be explained by misidentification of larvae. For example, we found that C. sapidus and C. similis exhibit complementary seasonal patterns of settlement, such that at some times nearly all settling Callinectes larvae are sapidus and at other times nearly all are similis (Figure 9).


Figure 9.
Species composition of Callinectes spp. megalopae collected from water column at sites where settlement was occurring near (A) Galveston and (B) Freeport. Values in parentheses indicate number of megalopae identified by sequencing. From: Sullivan and Neigel, 2017. Mar Ecol Prog Ser 565: 95–111.

 

Effects of oil and exposure on embryo, larval, and juvenile blue crabs. We found that blue crab embryos (eggs) exposed to low concentrations of oil did not experience higher direct mortality but were more likely to hatch in a pre-zoeal stage. We detected no effects of oil on growth of larvae For juveniles exposed to oil, time between molts increased.


Summary

Our research was initially focused on explaining the lack of an oil-spill associated decline in blue crab abundance. As we progressed, we saw the need to consider the potential effects of the oil spill along with other factors that could affect blue crab abundance. These factors include fishing pressure, other forms of pollution, and disease. Although over a thousand peer-reviewed papers on blue crabs had been published, we found critical gaps in what was known about blue crabs in the GOM that needed to be addressed. This led to some surprising findings, which not only aided our investigations of the effects of the DHOS but also suggested that some widely-held assumptions about blue crabs in the GOM needed to be revised.


Since 2005, blue crabs in the northern GOM have been in decline, and it has been natural to consider the DHOS as the most obvious cause. However, we found no evidence that the DHOS had lasting impacts on blue crab abundance in Louisiana. There was a transient increase the year after the spill, after which previously established long- term trends resumed. We did find evidence of other, potentially more serious threats to blue crabs in the GOM. As is recognized by managers, fishing pressure on blue crabs has been high, and release from this pressure during the closures that followed the DHOS can explain the increase in abundance in 2011. We also found: 1) blue crab larvae are exposed to high levels of pollution from sources other than the DHOS, 2) exposure to oil results in genetic and physiological changes that could compromise digestion, immunity, and growth, and 3) a major disease of blue crabs on the Atlantic coast is far more prevalent in the GOM than previously suspected.


We developed new resources for studying blue crabs. Transcriptome sequencing identified oil-responsive genes and thousands of single-nucleotide polymorphisms (SNPs) that can be used in future physiological and genetic studies. Our DNA barcoding assay can now be used to distinguish early life stages of blue crabs from those of related species. Our particle-tracking model predicts the connectivity of blue crabs across GOM and indicates probable sources of larvae that settle in different estuaries.


Although some of the work described in this report has been published, more is in review or being prepared for submission. Some of the main goals of our project required multiple years of data collection that was only completed a few months before this report was prepared. This report itself will serve as the starting point for a paper that synthesizes what we have learned from our blue crab research over the past four years.


PDF Proposal Abstract


This research was made possible by a grant from BP/The Gulf of Mexico Research Initiative.
www.gulfresearchinitiative.org