Evaluating Extinction Risk in Major Marine Taxa

By Olivia Schuitema, SRC intern

Over Earth’s history, there have been at least five mass extinctions in addition to other minor-scale extinctions (Bambach et al. 2004). The causes of such extinctions are varied, but many be associated with global climate variability (Doney et al. 2012). One article points to large-scale volcanism associated with global warming, acid rain and ocean acidification for the causes of extinctions (Bond et al. 2017). This is especially significant in recent years, because of the large and rapid increase in global temperatures (largely due to the burning of fossils fuels and deforestation) and corresponding varied changes in climate. Thus, in order to understand and predict future extinctions patterns, we must understand past ones.

The paleontological record (fossil record), gives much insight on these extinction events, allowing the present to look at past trends. In the effort to understand anthropogenic influence on modern marine biota, the fossil record can be analyzed and compared to the extant (living) groups (Carrasco et al. 2013). Thick fossil-rich marine sediments located around the world contain a plethora of information that can help prepare future extinction trends (Finnegan et al. 2015). These sediments (Figure 1) can give insight on particularly vulnerable taxa in potential danger of going extinct. Vulnerability among a population includes being threatened with a decline in numbers or genetic material, reduced fitness, or extinction (Dawso et al. 2011).

Fossils of various marine and terrestrial organisms are located in layers in the fossil record. The layers can give information on environmental conditions of the time and age of organisms (Wikimedia Commons).

A new study aimed to construct models of extinction risk and utilize them to evaluate baseline extinction vulnerabilities for some living marine taxa (Finnegan 2015). The article defines “extinction risk” as the probability of classifying fossil taxa as “extinct” based on its similarity to other extinct fossil taxa during the same time (Finnegan et al. 2015). The timeline used in the analysis was from the Neogene period to the Pleistocene period, encompassing about 23 million years in total. This time period was chosen to maximize faunal and geographic comparability (Finnegan et al. 2015). Some groups of organisms (taxa) found in this time interval are still living today and have similar geographical distributions as they did in the past. These similarities make it easier to compare marine taxa over varying conditions to help determine intrinsic risk. “Intrinsic risk” as used in the article, is the term for baseline vulnerability for marine taxa.

Six major marine taxonomic groups, including bivalves, gastropods, echinoids, sharks, mammals, and scleractinian corals were analyzed in this study (Finnegan et al. 2015). These groups were chosen for their relatively accurate representation of overall marine ecological, taxonomic, and functional diversity. The two best predictors for extinction risk are geographic range size and taxonomic identity (Finnegan et al. 2015). The predictors of extinction found in previous paleontological models (including geographic range size, latitude, etc.), were measured for the six marine taxa. Results indicate that the geographic area with the highest intrinsic risk was the tropics, especially the Indo-Pacific and the Western Atlantic (Finnegan et al. 2015). Similarly, another study highlights the increased extinction rates of North American mammals. Results showed a diversity crash in parts of North America during the Holocene Epoch (Carrasco et al. 2013). Although this mammalian extinction occurred later than the time period analyzed in the work of Finnegan et. al (2015), the geographic locations are similar, supporting the overall increasing extinction trend over time.

Another modeling system analyzed the hotspots for human activity and climate change velocity in contrast to the areas of high extinction risk of the six major marine genera (Finnegan et al. 2015). The results as seen in Figure 2, show that hotspots of anthropogenic influence and high climate change velocity overlap the areas of highest extinction risk (Finnegan et al. 2015), indicating a correlation between humans, climate change and extinction risk. The areas of overlap were mostly concentrated in the tropics and the subtropics. The tropics contain very high levels of biodiversity, providing habitat for unique species found nowhere else in the world. This is especially true for marine organisms. Conserving this diverse environment is important because of the many ecological services and economic benefits it provides.

Hotspots of anthropogenic impact and velocity of climate change overlaid on mean intrinsic risk (Finnegan et al. 2015).

The term “global warming” has evolved into the term “climate change” because of the new understanding of the changes in overall climate (weather patterns, natural disasters, sea level rise, etc.), and not solely an increase in global temperatures. Climate change has a variety of extinction-inducing mechanisms including ocean acidification, anoxia (lack of oxygen) and global warming (Bond et al. 2017). The variability of these factors puts stress on organisms, causing them to migrate or to die out if they cannot adapt quickly enough. Thus, the coupled effects of climate change and human activity on highly diverse environments can cause increased extinction vulnerabilities among taxa (Finnegan et al. 2015). This possible loss of biodiversity and evolutionary potential must be taken seriously (Dawson et al. 2011).

Works Cited

Bambach, R. K., Knoll, A. H., & Wang, S. C. (2004). Origination, extinction, and mass depletions of marine diversity. Paleobiology, 30(4), 522-542.

Bond, & Grasby. (2017). On the causes of mass extinctions. Palaeogeography, Palaeoclimatology, Palaeoecology, 478, 3-29.

Carrasco, Marc A. (2013). The impact of taxonomic bias when comparing past and present species diversity. Palaeogeography, Palaeoclimatology, Palaeoecology, 372, 130.

Dawson, T., Jackson, S., House, J., Prentice, I., & Mace, G. (2011). Beyond Predictions: Biodiversity Conservation in a Changing Climate. Science, 332(6025), 53-58.

Doney, S. C., Ruckelshaus, M., Duffy, J. E., Barry, J. P., Chan, F., English, C. A., … & Polovina, J. (2011). Climate change impacts on marine ecosystems.

Finnegan, S., Anderson, S., Harnik, P., Simpson, C., Tittensor, D., Byrnes, J., . . . Pandolfi, J. (2015). Extinctions. Paleontological baselines for evaluating extinction risk in the modern oceans. Science (New York, N.Y.), 348(6234), 567-70.

Noise Pollution in the Ocean: A Growing Problem

By Rachael Ragen, SRC intern

Marine animals face many forms of pollution, but one of the less obvious forms that has potentially dangerous effects is noise pollution. Humans have always established civilizations near the water, but humans continue to explore further into the ocean and discover new resources. This shift brings a large amount of anthropogenic noise that can be “categorized as high-intensity and acute such as the noise produced by military sonar, pile driving and seismic explorations, or lower-level and chronic such as ship noise.” (Codarin 2009). Sound travels about four times faster in water than making the effects of sound pollution much more pronounced. It often goes unnoticed by humans since the sound of a motor may not be loud above water, but below it can be deafening. This can cause a great amount of stress for animals. Stress can be defined as “a threat to homeostasis” (Romano 2004). This stress can disrupt the normal behaviors of these animals including communication, diving, and hunting.

Cargo Ships [https://commons.wikimedia.org/wiki/ File:Cargo_Ships_at_Sekondi-Takoradi_Harbour_(Takoradi_Harbour).jpg]

Sound as a form of communication is especially important to the ecology of marine mammals. Many marine mammals live in groups and can be used as part of their social structure or group hunting strategies. It is also often used in locating prey as seen by the bottlenose dolphin and their use of echolocation.

The most extreme example is the response of beaked whales to sonar. There are mass strandings of beaked whales that coincide with military activities. It is believed that these sounds can disrupt normal diving behavior of these whales and cause them to rise much more rapidly. This can lead to gas bubbles in the tissues and the supersaturation of nitrogen in tissues, which could possibly lead to decompression sickness (Rommel 2006). This is likely the cause of death and mass strandings of these organisms. Ear injuries are also common in specimens from mass strandings. Many theories exist on this topic but the definitive cause of the strandings is still unclear.

Beaked Whale [https://commons.wikimedia.org/wiki/ File:The_True%27s_beaked_whale_

Sensitivity to sound pollution has been shown across many species of marine mammals, including one study by Romano et. al. This study demonstrated the neural-immune response of a white whale and a bottlenose dolphin with the effect of intense sound from a seismic water gun, BEN water gun, and BEN tone. Blood was taken before and after an intense sound and the hormones were analyzed. While there were only two animals used in this study, the results of the blood analysis showed several changes in the immune response. As the study went on the animals began to become desensitized and did not show the same level of stress.

Stress responses have been observed across a wide range of animals besides marine mammals. Fish can communicate vocally, and it has been shown that anthropogenic sounds can greatly decrease the ability of fish to hear each other. Sensitivity was studied in damselfish, brown meagre, and the red-mouthed goby during this experiment. While the effect of the noise changes based on frequency, all species of fish were negatively affected (Codarin 2009).

Damselfish [https://en.wikipedia.org/wiki/Chromis _chromis#/media/File:Chromis_chromis_2.jpg]

Noise pollution is a problem for a large variety of marine animals. Further consideration for mitigation measures is required since the long term effects of sound pollution are relatively unknown and could be problematic for many animals. If stress is considered “a threat to homeostasis,” the increased stress levels could lower the ability of their immune system, reproductive success, and many other factors. This could be catastrophic for wild populations if management strategies are not established.

Works Cited

Codarin, A., L. Wysocki, F. Ladich, and M. Picciulina. 2009. Effects of ambient and boat noise on hearing and communication in three fish species living in a marine protected area (Miramare, Italy). 58(12):1880-1887.

Romano, T.A., M.J. Keogh, C. Kelly, P. Feng, L. Berk, C.E. Schlundt, D.A. Carder, and J.J. Finneran. 2004. Anthropogenic sound and marine mammal health: measures of the nervous and immune systems before and after intense sound exposure. Can. J. Fish. Aquat. Sci. 61:1124-1134.

Rommel, S.A., A. M. Costidis, A. Fernandez, P.D. Jepson, D.A. Pabsta, W.A. McLellana, D.S. Houser, T.W. Cranford, A.L. Van Heldenaa, D.M. Allen, and N.B.Barros. 2006. Elements of beaked whale anatomy and diving physiology and some hypothetical causes of sonar-related stranding. 7(3):189-209.

Sea-ice loss boosts visual search: fish foraging and changing pelagic interactions in polar oceans

By Nicole Suren, SRC Intern

Light availability is one of the most important factors in the success of visual foraging. It can be controlled by many variables such as turbidity or weather, but in polar ecosystems ice cover and seasonality are the primary controls for light availability. Climate change has had and will continue to have a huge effect on polar ecosystems through temperature and weather changes, but one of the most notable side effects examined in this study is how increased light availability caused by receding ice and reduced snow cover will affect the success of polar visual foragers. The study modeled the success of planktivorous, visually foraging fish, with the underlying principle of the model being that increased ambient light will increase visual range, thereby making prey detectable at a larger distance and increasing foraging efficiency. The results showed that declines of polar sea ice would boost the visual search of planktivorous fish, but only seasonally. While light availability related to ice cover can be variable due to climate change, the long dark periods caused by polar seasonality are factors independent of climate, and therefore will still place limits on visual foraging during those seasons.

Figure 1

(a) The blue line shows how sea ice extent has decreased over the past decades, and below is a diagram demonstrating that prey will become more likely to be visually detected as the thickness of sea ice decreases. (b) A variety of factors influence prey detection, including the nature and angle of incoming light. Predator, prey, and visual range are not drawn to scale. (Langbehn & Varpe, 2017)

The models predict that several things will change due to light availability caused by loss of ice cover. First, primary productivity may increase, depending on nutrient availability. Second, seasonal feeding migrations into the poles are expected due to the removal of the limiting factor of lack of light for visual foragers. This prediction has already been verified by real-world data; increased feeding forays by Atlantic Salmon, Atlantic Mackerel, and Atlantic Herring have been recorded, and these coincide with decreasing ice cover over the past 35 years. More generally, mobile, fast-swimming predators are predicted to take advantage of these foraging opportunities the most. However, increased light availability can also increase the likelihood of planktivorous predators being spotted and predated upon by larger visual predators in a higher trophic level. This means that not only will the ideal user of these seasonal foraging grounds be mobile and fast-swimming, but they will either be apex predators or schooling fish, which can use the technique of schooling to forage in relative safety despite being visible.

Figure 2

The extent of sea ice is averaged from 2010-2015 in (a) and (b), and (c) and (d) show how visual range correlates with these averages. Data from the Bering Sea and the Barents Sea are shown. (Langbehn & Varpe, 2017)

No matter how efficiently visual foragers learn to take advantage of increased light availability at the poles during the summer months, the darkness of winter will still be a significant limiting factor in regards to permanent habitat expansion. Polar winters will always be long and dark, even if climate change alters the ice cover in that time. This means that the permanent inhabitants of the poles will likely remain the only permanent inhabitants due to their specialized adaptations for living in darkness, while trophic interactions are likely to change during the summer.

Work Cited

Langbehn, T. J., & Varpe, Ø. (2017). Sea-ice loss boosts visual search: Fish foraging and changing pelagic interactions in polar oceans. Global Change Biology, (November 2016). https://doi.org/10.1111/gcb.13797

Polar Bears are Vulnerable to Loss of Sea Ice

By Rachael Ragen

Figure 1

Polar Bear, https://sealevel.nasa.gov/ system/news_items/main_images/ 74_polarbear768.jpeg

Polar bears are currently facing a major problem: declining sea ice. As greenhouse gases continue to increase due to anthropogenic factors causing temperatures to rise and ice to melt. Since polar bears rely on sea ice as they search for prey, the decline in sea ice makes hunting much more difficult. The current population of polar bears is estimated to be 26,000 with 19 subpopulations in 4 ecoregions (Figure 2). It is very difficult to properly assess each subpopulation of polar bears as they live in extreme environments. Therefore, no global assessment has been done and the status of some subpopulations is unknown. The study by Regehr et al. aimed to look at the effect of sea ice decline on polar bears by determining the generation length, forming a standardized sea ice metric, and then using statistical models and computer simulations.

Figure 2

Map of Ecoregions, Regehr et al.

In order to determine the generation length, the authors looked at the age of female polar bears with a cub and found the average to be 11.5 to 13.6 years. Live capture data was used to determine these numbers. The upper level is used to account for variations in generation length.

A sea ice metric was determined using satellite data from 1979 to 2014. This data was used to establish the carrying capacity, which is the maximum amount of organisms the habitat can support, for the polar bears. Then the value found for K (carrying capacity) was used in linear models. This analysis generated predicted future values of ice as well, as the effect these values had on subpopulations. The ice decline was shown to affect all subpopulations.

The statistical models and computer simulations looked at the relationship between polar bear populations and sea ice over three generations using three different methods. First they assumed that changes in sea ice are directly proportional to changes in subpopulation abundance. This method was useful for populations with limited data. Second they looked at a linear relationship between ice and subpopulation abundance for subpopulations, although data was only available for seven of the nineteen. There was not shown to be a significant change due to variations in the status subpopulations as well as uncertainty in estimates of abundance. Lastly they again looked at a linear relationship between ice and population but for each of the four ecoregions. Some ecoregions showed a significant change, whereas others did not, showing that dynamics and biological productivity varies between subpopulations.

Figure 3

Table of data found, Regehr et al.

This study looked at the IUCN Red List’s guidelines for risk tolerance. The culmination of these studies showed that the first generation’s mean global population size was to decrease by 30%, the second by 4%, and the third by 43% (Table 1). Since there was shown to be a high risk of the population decreasing by 30% and a low chance of the population decreasing by 50% (Table 1), polar bears are classified as vulnerable.

The need for MPAs in the Antarctic

By Haley Kilgour, SRC Intern

With global climate change in effect the Arctic ice sheet has been losing area and has gone from 7.5 million km^2 in 1979 to 4 million km^2 in 2016 (Figure 1). The loss of ice coverage is detrimental to many species, but on the other hand opens up areas to new fishing grounds, oil and gas deposits, deep sea minerals, and shorter shipping routes that were previously inaccessible. While economically it is beneficial to exploit these now accessible resources, it is also necessary to designate Marine Protected Areas (MPAs) to preserve habitat and biodiversity.

Figure 1

Year round see ice cover for the periods of 1979-1984 and 2012-2016.

Geomorphic features such as seamounts, submarine canyons, hydrothermal vents, submarine plateaus, ridges, and escarpments serve as a proxy for benthic communities and ecological processes as they are often areas of high biodiversity and important to processes such as upwelling. Harris et al looked at the distribution of geomorphic features on the sea floor to assess their current level of protection within MPAs. They also aimed to see if these features were occurring within or outside of MPAs and identify ones that were once inaccessible due to year round sea ice.

To determine their area of study, Harris et al used the average minimum sea ice coverage from 1979-1983. They looked at the years 1979-1983 and 2012-2016 (the earliest and latest time periods) to see how much of the geomorphic features are now exposed. Twenty-nine categories of features were mapped using Shuttle Radar Topography Mapping (Shuttle Radar Topography) and MPA boundaries were taken from the IUCN and UNEP-WCMC database. The program ArcGIS was then used to compute areas.

On average, 31% of all previously year round covered features in the Arctic are now in open water in September. In 1979-1983, only 2.33% of areas below year round sea ice were in MPAs, and these were mostly areas on coastal and shelf habitats (Figure 2). This lack of diversity in features that are protected means there is high potential for them to be exploited now that year round ice no longer prevents access.

Figure 2

MPAs within the Arctic in relation to September sea ice cover in the periods 1979-1983 and 2012-2016.

As it stands, only 2.3% of the areas used in this study are in MPAs. While this seems to pose a problem, Canada, Denmark, Russia, Norway, and the USA have signed a “Declaration concerning the regulation of unregulated high seas fishing in the central Arctic Ocean” and a moratorium. Thereby, the areas beyond national jurisdiction have a degree of protection from fishing pressure at the current time.

Current MPAs mostly cover coastlines and inner shelf regions. Abyssal plains are not covered at all and there negligible protection for slope habitats. While the current MPAs do provide a small effect, they are not representative in the standard MPA design.

There are many geomorphic features that have been left exposed and all are fragile ecosystems. Basins collect sediment and anthropogenic contaminants, making them particularly susceptible to pollution from runoff and chemicals. Submarine canyons are considered biodiversity hot spots and prime fishing grounds, making them vulnerable to degradation. Only .2% of canyons are within existing MPAs and retreating sea ice now exposes 37% of their area. Submarine canyons face particular danger because they are associated with oil and gas deposits. Plateaus are mostly unexplored worldwide and thus need further examination and protection.

These underwater geomorphic regions are high in biodiversity but are finding themselves in peril with retreating sea ice. Many of these areas are likely under rapid ecological transition as the Arctic responds to global climate change. These ecosystems are highly unexplored and sensitive. They could be lucrative economically, but are also most likely highly important for conservation. MPAs will play a major role in protecting these areas.

Does marine debris affect tourist perception and tourism revenue?

By Casey Dresbach, SRC Intern

The top worldwide providers of ecosystem services of both leisure and recreation include coastal areas such as beaches and estuaries (Millennium Ecosystem Assessment, 2005). These natural environments are home to hundreds of thousands of marine organisms, all of which require clean domains to flourish, thrive, and grow in. Unfortunately, human pollution has made its way into these areas, as depicted in Figure 1. “Marine debris” can be defined as any solid, persistent, human-created waste that has been deliberately or accidentally introduced into a waterway or ocean from shorelines to the ocean floor (Oregon Coast STEM Hub, 2017). Not only does this breed of debris directly affect marine species ocean-wide, but current research is also showing that it is taking a toll on both tourism and tourists’ destination choices worldwide.

Figure 1

Dr. Sylvia Earle engaging with a Laysan albatross nesting among marine debris. (USFWS – Pacific Region, 2012)

Marine debris is complex in its nature and jeopardizes other coastal entities. The debris has a dual effect on both the marine life as well income generated from local tourism. The interaction between marine debris and tourism is complex because items may form in regions other than the places where the litter is stranded and where tourism occurs (Krelling, Williams, & Turra, 2017). Individuals visiting beaches and coastal regions are more likely so seek alternate destinations if their overall experience is not remarkably enjoyable, and a substantial amount of scattered litter may play into that alternative choice of destination.

The coast of Paraná state in southern Brazil is one of the most frequented tourist destinations in this region (Krelling, Williams, & Turra, 2017). Many tourists, such as second-home owners and users (SHOU) and non-recurrent vacationers, frequent this Brazilian coast. A single SHOU is an individual or group of individuals who have an additional property, or vacation home elsewhere. And a non-recurrent tourist is an individual who has no territorial tie to a destination – is interested in vacation without having loyalty of a piece of land. In a recent study by researchers Allan Krelling, Allan Williams and Alexandra Turra, both the perceptions and reactions of these two distinct groups of beach users were compared. More than 70% of the visitors are SHOU. In fact, some of Paraná’s cities are dependent on property taxes from these second homeowners as well as the expenditures spent by the non-recurrent tourists on services such as food, activities, and other conveniences. Collectively, the two user groups and their tourism revenue drive the economy in the coastal area.

Figure 2

(a) Depicts the entire coastal region of Paraná State in southern Brazil. (Top right) Pontal Do Sul, a highly frequented estuarine beach in the coastal region of southern Brazil. (Bottom right) lpanema, a highly frequented open ocean beach in the coastal region of southern Brazil (Krelling, Williams, & Turra, 2017).)

The study compared both the perceptions and reactions of the two user groups. SHOU and non-recurrent tourists were administered a questionnaire to determine socioeconomic characteristics at two Brazilian sub-tropical beaches: Pontal do Sul and Ipanema, exhibited in Figure 2. Pontal do Sul is an estuarine beach and Ipanema is an open-ocean beach, which is more frequented by non-recurrent tourists. The ultimate goal of the questionnaire was to characterize these beach users’ socioeconomic characteristics such as yearly income, level of education, daily per person expenditure, frequency of trips and period of permanence (Krelling, Williams, & Turra, 2017). The survey also examined perceptions and reactions, especially those regarding the potential negative economic impacts of marine debris. Pontal do Sul and Ipanema were selectively chosen because of their varying geographical characteristics, ultimately adding more variability to the study set.

The general findings showed that SHOU might have a different reaction towards the marine debris than the average tourist. This can be linked to their loyalty to the destination, specifically tied to the property they have there. Results did show, however, that if debris were to reach a significant amount (>15 items/m2), more than 85% of beachgoers would look elsewhere when searching for a coastal region to vacation (Krelling, Williams, & Turra, 2017). If this were the case the stranded litter would threaten the Brazilian economy by reducing local tourism income by 39.1%, (Krelling, Williams, & Turra, 2017) which would present losses up to $8.5 million a year.

In order to improve beach users’ experience, moving forward, an issue like marine debris should be prioritized. Marine debris can be a stressor that impacts coastal tourism worldwide. An evaluation of economic impacts caused by litter presence is a unique approach to analyzing how to minimize the threat litter may pose to tourism revenue. Some factors that may influence a visitor’s beach choice may include beach length, scenery, water quality, amenities (restaurants, shops, etc.), and quantity of litter. The additive effect of these factors determines the overall impression the trip will leave on the visitor. Stranded beach litter is considered to be one of the five most important aspects regarding beach quality in Europe, USA, Mexico, and the Caribbean (Krelling, Williams, & Turra, 2017). More research should be done in order for authorities to decide how to best go about balancing investments to remove marine litter and minimize the potential reduction of tourism revenue. Through integrated planning, the sources of litter can be determined and preventive strategies can be put into play. This would help to avoid a reduction in environmental quality and income generated from tourism.

Works Cited

Krelling, A. P., Williams, A. T., & Turra, A. (2017, August 15). Differences in perception and reaction of tourist groups to beach marine debris that can influence a loss of tourism revenue in coastal areas. (H. Smith, Ed.) Marine Policy.

Millennium Ecosystem Assessment. (2005). Ecosystems and Human Well-being: Synthesis. Washington, DC: Island Press.

Oregon Coast STEM Hub. (2017). Marine Debris – Composition and Abundance. (L. C. Schools, O. C. Newport, N. M. Program, & S. G. (Oregon), Producers) Retrieved from Conserve Wildlife New Jersey:

USFWS – Pacific Region. (2012, January 11). Dr. Sylvia Earle talks to an albatross nesting among marine debris. (A. Collins, Producer) Retrieved from Wikimedia Commons: https://commons.wikimedia.org/wiki/ File:Dr._Sylvia_Earle_talks_to_an_albatross_nesting_among_marine_debris.jpg