Toxins in Marine Mammals: a Story

By: Alexa Kownacki, Ph.D. Student, OSU Department of Fisheries and Wildlife, Geospatial Ecology of Marine Megafauna Lab

As technology has developed over the past ten years, toxins in marine mammals have become an emerging issue. Environmental toxins are anything that can pose a risk to the health of plants or animals at a dosage. They can be natural or synthetic with varying levels of toxicity based on the organism and its physiology. Most prior research on the impacts toxins before the 2000s was conducted on land or in streams because of human proximity to these environments. However. with advancements in sampling methods, increasing precision in laboratory testing, and additional focus from researchers, marine mammals are being assessed for toxin loads more regularly.

A dolphin swims through a diesel slick caused by a small oil spill in a port. (Image Source: The Ocean Update Blog)

Marine mammals live most of their lives in the ocean or other aquatic systems, which requires additional insulation for protection from both cold temperatures and water exposure. This added insulation can take the form of lipid rich blubber, or fur and hair. Many organic toxins are lipid soluble and therefore are more readily found and stored in fatty tissues. When an organic toxin like a polychlorinated biphenyl (PCB) is released into the environment from an old electrical transformer, it persists in sediments. As these sediments travel down rivers and into the ocean, these toxic substances slowly degrade in the environment and are lipophilic (attracted to fat). Small marine critters eat the sediment with small quantities of toxins, then larger critters eat those small critters and ingest larger quantities of toxins. This process is called biomagnification. By the time a dolphin consumes large contaminated fishes, the chemical levels may have reached a toxic level.

The process by which PCBs accumulate in marine mammals from small particles up to high concentrations in lipid layers. (Image Source: World Ocean Review)

Marine mammal scientists are teaming with biochemists and ecotoxicologists to better understand which toxins are more lethal and have more severe long-term effects on marine mammals, such as decreased reproduction rates, lowered immune systems, and neurocognitive delays. Studies have already shown that higher contaminant loads in dolphins cause all three of these negative effects (Trego et al. 2019). As a component of my thesis work on bottlenose dolphins I will be measuring contaminant levels of different toxins in blubber.  Unfortunately, this research is costly and time-consuming. Many studies regarding the effects of toxins on marine mammals are funded through the US government, and this is where the public can have a voice in scientific research.

Rachel Carson examines a specimen from a stream collection site in the 1950s. (Image Source: Alfred Eisenstaedt/ The LIFE picture collection/ Getty Images.)

Prior to the 1960s, there were no laws regarding the discharge of toxic substances into our environment. When Rachel Carson published “Silent Spring” and catalogued the effects of pesticides on birds, the American public began to understand the importance of environmental regulation. Once World War II was over and people did not worry about imminent death due to wartime activities, a large portion of American society focused on what they were seeing in their towns: discharges from chemical plants, effluents from paper mills, taconite mines in the Great Lakes, and many more.

Discharge from a metallic sulfide mine collects in streams in northern Wisconsin. (Image Source: Sierra Club)

However, it was a very different book regarding pollutants in the environment that caught my attention – and that of a different generation and part of society – even more than “Silent Spring”. A book called “The Lorax”.  In this 1972 children’s illustrated book by Dr. Seuss, a character called the Lorax “speaks for the trees”. The Lorax touches upon critical environmental issues such as water pollution, air pollution, terrestrial contamination, habitat loss, and ends with the poignant message, “Unless someone like you cared a whole awful lot, nothing is going to get better. It’s not.”

The original book cover for “The Lorax” by Dr. Seuss. (Image source: Amazon.com)

Within a decade, the US Environmental Protection Agency (EPA) was formed and multiple acts of congress were put in place, such as the National Environmental Policy Act, Clean Air Act, Clean Water Act, and Toxic Substances Control Act, with a mission to “protect human health and the environment.” The public had successfully prioritized protecting the environment and the government responded. Before this, rivers would catch fire from oil slicks, children would be banned from entering the water in fear of death, and fish would die by the thousands. The resulting legislation cleaned up our air, rivers, and lakes so that people could swim, fish, and live without fear of toxic substance exposures.

The Cuyahoga River on fire in June 1969 after oil slicked debris ignited. (Image Source: Ohio Central History).

Fast forward to 2018 and times have changed yet again due to fear. According to a Pew Research poll, terrorism is the number one issue that US citizens prioritize, and Congress and the President should address. The environment was listed as the seventh highest priority, below Medicare (“Majorities Favor Increased Spending for Education, Veterans, Infrastructure, Other Govt. Programs.”). With this societal shift in priorities, research on toxins in marine mammals may no longer grace the covers of the National Geographic, Science, or Nature, not for lack of importance, but because of the allocation of taxpayer funds and political agendas. Meanwhile, long-lived marine mammals will still be accumulating toxins in their blubber layers and we, the people, will need to care a whole lot, to save the animals, the plants, and ultimately, our planet.

The Lorax telling the reader how to save the planet. (Image Source: “The Lorax” by Dr. Seuss via the Plastic Bank)

Citations:

“Majorities Favor Increased Spending for Education, Veterans, Infrastructure, Other Govt. Programs.” Pew Research Center for the People and the Press, Pew Research Center, 11 Apr. 2019, www.people-press.org/2019/04/11/little-public-support-for-reductions-in-federal-spending/pp_2019-04-11_federal-spending_0-01-2/.

Marisa L. Trego, Eunha Hoh, Andrew Whitehead, Nicholas M. Kellar, Morgane Lauf, Dana O. Datuin, and Rebecca L. Lewison. Environmental Science & Technology 2019 53 (7), 3811-3822. DOI: 10.1021/acs.est.8b06487

Zooming in: A closer look at bottlenose dolphin distribution patterns off of San Diego, CA

By: Alexa Kownacki, Ph.D. Student, OSU Department of Fisheries and Wildlife, Geospatial Ecology of Marine Megafauna Lab

Data analysis is often about parsing down data into manageable subsets. My project, which spans 34 years and six study sites along the California coast, requires significant data wrangling before full analysis. As part of a data analysis trial, I first refined my dataset to only the San Diego survey location. I chose this dataset for its standardization and large sample size; the bulk of my sightings, over 4,000 of the 6,136, are from the San Diego survey site where the transect methods were highly standardized. In the next step, I selected explanatory variable datasets that covered the sighting data at similar spatial and temporal resolutions. This small endeavor in analyzing my data was the first big leap into understanding what questions are feasible in terms of variable selection and analysis methods. I developed four major hypotheses for this San Diego site.

The study species: common bottlenose dolphin (Tursiops truncatus) seen along the California coastline in 2015. Image source: Alexa Kownacki.

Hypotheses:

H1: I predict that bottlenose dolphin sightings along the San Diego transect throughout the years 1981-2015 exhibit clustered distribution patterns as a result of the patchy distributions of both the species’ preferred habitats, as well as the social nature of bottlenose dolphins.

H2: I predict there would be higher densities of bottlenose dolphin at higher latitudes spanning 1981-2015 due to prey distributions shifting northward and less human activities in the northerly sections of the transect.

H3: I predict that during warm (positive) El Niño Southern Oscillation (ENSO) months, the dolphin sightings in San Diego would be distributed more northerly, predominantly with prey aggregations historically shifting northward into cooler waters, due to (secondarily) increasing sea surface temperatures.

H4: I predict that along the San Diego coastline, bottlenose dolphin sightings are clustered within two kilometers of the six major lagoons, with no specific preference for any lagoon, because the murky, nutrient-rich waters in the estuarine environments are ideal for prey protection and known for their higher densities of schooling fishes.

Data Description:

The common bottlenose dolphin (Tursiops truncatus) sighting data spans 1981-2015 with a few gap years. Sightings cover all months, but not in all years sampled. The same transect in San Diego was surveyed in a small, rigid-hulled inflatable boat with approximately a two-kilometer observation area (one kilometer surveyed 90 degrees to starboard and port of the bow).

I wanted to see if there were changes in dolphin distribution by latitude and, if so, whether those changes had a relationship to ENSO cycles and/or distances to lagoons. For ENSO data, I used the NOAA database that provides positive, neutral, and negative indices (1, 0, and -1, respectively) by each month of each year. I matched these ENSO data to my month-date information of dolphin sighting data. Distance from each lagoon was calculated for each sighting.

Figure 1. Map representing the San Diego transect, represented with a light blue line inside of a one-kilometer buffered “sighting zone” in pale yellow. The dark pink shapes are dolphin sightings from 1981-2015, although some are stacked on each other and cannot be differentiated. The lagoons, ranging in size, are color-coded. The transect line runs from the breakwaters of Mission Bay, CA to Oceanside Harbor, CA.

Results: 

H1: True, dolphins are clustered and do not have a uniform distribution across this area. Spatial analysis indicated a less than a 1% likelihood that this clustered pattern could be the result of random chance (Fig. 1, z-score = -127.16, p-value < 0.0001). It is well-known that schooling fishes have a patchy distribution, which could influence the clustered distribution of their dolphin predators. In addition, bottlenose dolphins are highly social and although pods change in composition of individuals, the dolphins do usually transit, feed, and socialize in small groups.

Figure 2. Summary from the Average Nearest Neighbor calculation in ArcMap 10.6 displaying that bottlenose dolphin sightings in San Diego are highly clustered. When the z-score, which corresponds to different colors on the graphic above, is strongly negative (< -2.58), in this case dark blue, it indicates clustering. Because the p-value is very small, in this case, much less than 0.01, these results of clustering are strongly significant.

H2: False, dolphins do not occur at higher densities in the higher latitudes of the San Diego study site. The sightings are more clumped towards the lower latitudes overall (p < 2e-16), possibly due to habitat preference. The sightings are closer to beaches with higher human densities and human-related activities near Mission Bay, CA. It should be noted, that just north of the San Diego transect is the Camp Pendleton Marine Base, which conducts frequent military exercises and could deter animals.

Figure 3. Histogram comparing the latitudes with the frequency of dolphin sightings in San Diego, CA. The x-axis represents the latitudinal difference from the most northern part of the transect to each dolphin sighting. Therefore, a small difference would translate to a sighting being in the northern transect areas whereas large differences would translate to sightings being more southerly. This could be read from left to right as most northern to most southern. The y-axis represents the frequency of which those differences are seen, that is, the number of sightings with that amount of latitudinal difference, or essentially location on the transect line. Therefore, you can see there is a peak in the number of sightings towards the southern part of the transect line.

H3: False, during warm (positive) El Niño Southern Oscillation (ENSO) months, the dolphin sightings in San Diego were more southerly. In colder (negative) ENSO months, the dolphins were more northerly. The differences between sighting latitude and ENSO index was significant (p<0.005). Post-hoc analysis indicates that the north-south distribution of dolphin sightings was different during each ENSO state.

Figure 4. Boxplot visualizing distributions of dolphin sightings latitudinal differences and ENSO index, with -1,0, and 1 representing cold, neutral, and warm years, respectively.

H4: True, dolphins are clustered around particular lagoons. Figure 5 illustrates how dolphin sightings nearest to Lagoon 6 (the San Dieguito Lagoon) are always within 0.03 decimal degrees. Because of how these data are formatted, decimal degrees is the easiest way to measure change in distance (in this case, the difference in latitude). In comparison, dolphins at Lagoon 5 (Los Penasquitos Lagoon) are distributed across distances, with the most sightings further from the lagoon.

Figure 5. Bar plot displaying the different distances from dolphin sighting location to the nearest lagoon in San Diego in decimal degrees. Note: Lagoon 4 is south of the study site and therefore was never the nearest lagoon.

I found a significant difference between distance to nearest lagoon in different ENSO index categories (p < 2.55e-9): there is a significant difference in distance to nearest lagoon between neutral and negative values and positive and neutral years. Therefore, I hypothesize that in neutral ENSO months compared to positive and negative ENSO months, prey distributions are changing. This is one possible hypothesis for the significant difference in lagoon preference based on the monthly ENSO index. Using a violin plot (Fig. 6), it appears that Lagoon 5, Los Penasquitos Lagoon, has the widest variation of sighting distances in all ENSO index conditions. In neutral years, Lagoon 0, the Buena Vista Lagoon has multiple sightings, when in positive and negative years it had either no sightings or a single sighting. The Buena Vista Lagoon is the most northerly lagoon, which may indicate that in neutral ENSO months, dolphin pods are more northerly in their distribution.

Figure 6. Violin plot illustrating the distance from lagoons of dolphin sightings under different ENSO conditions. There are three major groups based on ENSO index: “-1” representing cold years, “0” representing neutral years, and “1” representing warm years. On the x-axis are lagoon IDs and on the y-axis is the distance to the nearest lagoon in decimal degrees. The wider the shapes, the more sightings, therefore Lagoon 6 has many sightings within a very small distance compared to Lagoon 5 where sightings are widely dispersed at greater distances.

 

Bottlenose dolphins foraging in a small group along the California coast in 2015. Image source: Alexa Kownacki.

Takeaways to science and management: 

Bottlenose dolphins have a clustered distribution which seems to be related to ENSO monthly indices, and likely, their social structures. From these data, neutral ENSO months appear to have something different happening compared to positive and negative months, that is impacting the sighting distributions of bottlenose dolphins off the San Diego coastline. More research needs to be conducted to determine what is different about neutral months and how this may impact this dolphin population. On a finer scale, the six lagoons in San Diego appear to have a spatial relationship with dolphin sightings. These lagoons may provide critical habitat for bottlenose dolphins and/or for their preferred prey either by protecting the animals or by providing nutrients. Different lagoons may have different spans of impact, that is, some lagoons may have wider outflows that create larger nutrient plumes.

Other than the Marine Mammal Protection Act and small protected zones, there are no safeguards in place for these dolphins, whose population hovers around 500 individuals. Therefore, specific coastal areas surrounding lagoons that are more vulnerable to habitat loss, habitat degradation, and/or are more frequented by dolphins, may want greater protection added at a local, state, or federal level. For example, the Batiquitos and San Dieguito Lagoons already contain some Marine Conservation Areas with No-Take Zones within their reach. The city of San Diego and the state of California need better ways to assess the coastlines in their jurisdictions and how protecting the marine, estuarine, and terrestrial environments near and encompassing the coastlines impacts the greater ecosystem.

This dive into my data was an excellent lesson in spatial scaling with regards to parsing down my data to a single study site and in matching my existing data sets to other data that could help answer my hypotheses. Originally, I underestimated the robustness of my data. At first, I hesitated when considering reducing the dolphin sighting data to only include San Diego because I was concerned that I would not be able to do the statistical analyses. However, these concerns were unfounded. My results are strongly significant and provide great insight into my questions about my data. Now, I can further apply these preliminary results and explore both finer and broader scale resolutions, such as using the more precise ENSO index values and finding ways to compare offshore bottlenose dolphin sighting distributions.