Month: October 2023

Allison Dawn, MSc, GEMM Lab graduate, OSU Department of Fisheries, Wildlife and Conservation Sciences, Geospatial Ecology of Marine Megafauna Lab 

The second year of my master’s flew by. Gone were the days of feeling new to graduate school. While I was feeling more comfortable navigating courses, balancing time at both Corvallis and HMSC campuses, and leading recruitment and logistics for the TOPAZ/JASPER field seasons, I certainly felt intimidated by my long, yet exciting, list of research goals I planned to accomplish in order to graduate in Summer 2023. Now, I am proud to say we have come a long way from my (overly ambitious) research proposal and simple Pearson correlations.

At this time last year, I had narrowed down a few key environmental factors to assess relationships between zooplankton in reef systems where PCFG gray whales feed and environmental variability. Even still, I was feeling frustrated at my preliminary analysis results that suggested upwelling had little to no impact on zooplankton abundance or whale foraging effort. This result was dissatisfying given what we know about the upwelling and the California Current System (CCS), so I wondered if my analysis approach, upwelling metrics, or both, were limited. However, thanks to the dedicated mentorship of Leigh, and an informal chat on the water with Aaron Galloway while dive tending for CamDO deployments, I was encouraged to dig even deeper into the literature (and subsequent debates) on the role of upwelling in the nearshore. After several inspiring meetings with the lab about our latest literature deep-dive, I reconfigured my initial hypotheses and charged ahead into the next phases of analysis with a different metric of upwelling than I had calculated before, which I will describe further below. While my final chapter includes a total of seven environmental factors that capture both broad- and fine-temporal temporal scales, for the purposes of this blog I will just share the result of the broad-scale impact of intermittent upwelling on both zooplankton abundance and gray whale foraging effort.

First, a brief recap on upwelling — during the spring and summer in the CCS, strong northerly winds push surface waters offshore, bringing cold, nutrient rich waters from the deep; which creates coastal upwelling. However, upwelling is not persistent. There are periods of time when these northerly winds relax, reducing surface water advection, and upwelling stalls. This relaxation period allows for nearshore retention of primary productivity, which permeates trophic levels with important nutrients. The alternation between upwelling and relaxation is called “intermittent upwelling”, and researchers are finding that the occurrence of relaxation periods are just as important as upwelling itself. Both support biophysical mechanisms that deliver and retain nutrients in the system.

For an example of intermittent upwelling in the CCS,  Figure 1 shows a northerly wind stress plot taken from a coastal buoy near our Port Orford study area during 2016. On the y-axis we have northerly wind stress, where positive values show less strong northerly winds, indicating downwelling favorable conditions, and negative values represent strong northerly winds, indicating upwelling favorable conditions. The x-axis is months over time. Here, you can see how in the winter downwelling prevails, but in the summer time we mainly have upwelling favorable winds. However, these summer periods are punctuated by positive values of wind stress, demonstrating that alternations between upwelling and relaxation occur several times throughout the spring and summer period.

Figure 1: Example plot of northerly wind stress plot taken from NOAA Buoy 4601 in 2016 (near our Port Orford, Oregon study area).

The role of upwelling intermittency has been explored in previous work and was posited as the Intermittent Upwelling Hypothesis (IUH) by Menge and Menge 2013. Figure 2, left, demonstrates this hypothesis in theoretical plots. In panel A we see that the rates of ecological processes such as primary productivity and prey response are maximal in at middle values of persistent upwelling and downwelling. In panel B. we see ecological processes positively increase with an index of upwelling intermittency. In Figure 2, right, the authors tested this hypothesis on chlorophyll-a and barnacle and mussel larval recruitment across several study sites and found the results did closely match theory.

Figure 2: Left, Intermittent Upwelling Hypothesis (IUH) theoretical plots showing predicted unimodal relationship between nutrient availability and prey response along a gradient between persistent upwelling and persistent downwelling (panel A) and the expected linear relationship between nutrient availability and upwelling intermittency (panel B); Right, Chlorophyll-a, barnacle, and mussel recruitment responses to an upwelling and intermittency index. Menge and Menge 2013.

Nearshore systems in the CCS, like the ones described in this Menge and Menge 2013 paper, are vastly understudied. And while there is a growing body of literature investigating the role of intermittent upwelling on various prey metrics (Mace & Morgan, 2006; Roegner et al 2007; Benoit-Bird et al., 2019) as well as cetacean movement (Ryan et al., 2022), to our knowledge no study has yet assessed the role of intermittent upwelling on nearshore prey availability and marine mammal occurrence.

To investigate the role of intermittent upwelling, we used the coastal upwelling transport index (CUTI) as our proxy for upwelling. Using daily CUTI values we generated a cumulative upwelling index and number of relaxation events for each year of the study (Figure 3.). This cumulative upwelling information was used to define the day of spring transition (ST) and end of the upwelling season for each year (2016-2021), following the upwelling phenological definitions from Bograd et al. 2009.

Figure 3: Summed running mean of Cumulative Upwelling Transport Index (CUTI) at latitude 42°N across years 2016-2021, initial data source https://oceanview.pfeg.noaa.gov/products/upwelling/cutibeuti

Using of five-year dataset we investigated functional relationships between each environmental variable and either zooplankton abundance or whale foraging effort using Boosted Regression Tree analysis (Elith et al., 2008).  Model results demonstrate that  for both zooplankton and whales, species occurrence is high at the intersection between moderate values of accumulated upwelling and with an increasing number of relaxation events. Overall, this work identifies intermittent upwelling as a primary driver of zooplankton abundance and gray whale foraging effort in a nearshore region of Oregon.

Winds in the California Current System are projected to get stronger with climate change, and if upwelling-favorable winds increase in duration and intensity, this could potentially threaten this balance between relaxation and upwelling. While these changes may mean greater primary productivity on some scales, how exactly this increase might affect the very nearshore regions and intermittent upwelling is unknown. Thus, research should continue long-term monitoring of nearshore areas to assist with adaptive management solutions in the face of environmental change.

Preparing this manuscript for my first-first author publication has been another new and exciting process. I feel so grateful for my time as a Master’s student in the GEMM Lab, and for the support of my lab mates, the HMSC community, family, and friends who cheered me on each step of the way to the finish line.  

Figure 4: Toasting to a successful master’s defense seminar with GEMM Lab mates, friends and family.

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References

Benoit‐Bird, K. J., Waluk, C. M., & Ryan, J. P. (2019). Forage species swarm in response to coastal upwelling. Geophysical Research Letters, 46(3), 1537-1546.

Bograd, S. J., Schroeder, I., Sarkar, N., Qiu, X., Sydeman, W. J., & Schwing, F. B. (2009). Phenology of coastal upwelling in the California Current. Geophysical Research Letters, 36(1).

Curtis Roegner, G., Armstrong, D. A., Hickey, B. M., & Shanks, A. L. (2003). Ocean distribution of Dungeness crab megalopae and recruitment patterns to estuaries in southern Washington State. Estuaries, 26, 1058-1070.

Elith, J., Leathwick, J. R., & Hastie, T. (2008). A working guide to boosted regression trees. Journal of animal ecology, 77(4), 802-813.

Mace, A. J., & Morgan, S. G. (2006). Biological and physical coupling in the lee of a small headland: contrasting transport mechanisms for crab larvae in an upwelling region. Marine Ecology Progress Series, 324, 185-196.

Menge, B. A., & Menge, D. N. (2013). Dynamics of coastal meta‐ecosystems: the intermittent upwelling hypothesis and a test in rocky intertidal regions. Ecological Monographs, 83(3), 283-310.

Oestreich, W. K., Abrahms, B., McKenna, M. F., Goldbogen, J. A., Crowder, L. B., & Ryan, J. P. (2022). Acoustic signature reveals blue whales tune life‐history transitions to oceanographic conditions. Functional Ecology, 36(4), 882-895.

Roegner, G. C., Armstrong, D. A., & Shanks, A. L. (2007). Wind and tidal influences on larval crab recruitment to an Oregon estuary. Marine Ecology Progress Series, 351, 177-188.

Ryan, J. P., Benoit‐Bird, K. J., Oestreich, W. K., Leary, P., Smith, K. B., Waluk, C. M., … & Goldbogen, J. A. (2022). Oceanic giants dance to atmospheric rhythms: Ephemeral wind‐driven resource tracking by blue whales. Ecology Letters, 25(11), 2435-2447.

By Lisa Hildebrand, PhD student, OSU Department of Fisheries, Wildlife, & Conservation Sciences, Geospatial Ecology of Marine Megafauna Lab

Baleen whales face a multitude of threats on a daily basis. The exposure to some of these threats can be assessed visually. For example, the presence of propeller scars on a whale are indicative that the individual was struck by a boat. However, there are some threats that are not easily detected from visual assessments. One of these threats is the ingestion of microparticles (MPs), which include microplastics and other anthropogenic debris. While MP research has entered its second decade and documentation of MPs in the marine environment is common, we still lack empirical information on the rates of MP ingestion by baleen whales and their prey. Hence, one of the objectives of the Coastal Oregon Zooplankton Investigation (COZI; read more about it in a previous blog), which GEMM Lab PI Leigh Torres led, was to determine to what extent Pacific Coast Feeding Group (PCFG) gray whales and their nearshore zooplankton prey are impacted by MPs. The results of this work were recently published in the journal Frontiers in Marine Science and I am going to summarize them for you here today.

A number of studies have documented MP ingestion in baleen whales, including in humpback (Besseling et al., 2015), fin (Fossi et al., 2012, 2014, 2016, 2017), Bryde’s, and sei whales (Zantis et al., 2022). The effects of ingesting MPs on baleen whales are theorized to include blockage of internal organs, mechanical damage of the digestive tract, false feeling of satiation (full from eating), and potentially leaching of toxicants depending on the length of the digestive period (Donohue et al., 2019; Hudak & Sette 2019; Zhu et al., 2019; Novillo et al., 2020). Despite the fact that MPs have been documented in a number of baleen whale species, there is still a lack of knowledge regarding MP ingestion rates by baleen whales from empirical data, although modeled estimates have been derived for a few species (Zantis et al., 2022; Kahane-Rapport et al., 2022). Basically, we know whales eat MPs because it has been detected in their stomachs, but we do not know how much MPs they consume. The COZI team therefore aimed to quantify baleen whale MP consumption rates from empirically counted MP loads in zooplankton prey and to look at MP exposure of baleen whales from “zoop to poop” (Figure 1). 

In order to accomplish this aim, we used “zoop” and “poop” samples collected between 2017 to 2019 during the GEMM Lab’s long-term GRANITE (Gray whale Response to Ambient Noise Informed by Technology and Ecology) project. We analyzed MP loads in three prey zooplankton species found in nearshore Oregon waters (the amphipod Atylus tridens and the mysid shrimp Holmesimysis sculpta and Neomysis rayii), all of which are known PCFG gray whale prey (Hildebrand et al., 2021), as well as five fecal samples collected from four unique individual gray whales. While the field collection of these samples was led by the GEMM Lab, the processing and MP analysis was led by Dr. Susanne Brander and conducted by a number of undergraduate student workers. MP analysis is no easy feat as it involves many, many meticulous and time-intensive steps in order to get from a sample of gray whale prey or poop to a known number of MPs that the sample contained. The process involves (1) sorting and identifying the prey into the different species; (2) rinsing the individuals to ensure no external MPs are counted; (3) digesting the sample in potassium hydroxide (KOH) for 24-72 hours; (4) sieving and filtering the digested samples; (5) picking out suspected MPs from the filters and measuring them; (6) analyzing the suspected MPs to confirm chemical composition. On top of all of these steps, anyone working with the samples has to try and minimize potential MP contamination, which is not easy since MPs are practically everywhere, such as synthetic fibers from our clothes or microplastics that are floating around in the air. 

After many long years of lab work (COVID lab restrictions included), we are excited (and a little daunted) to share the results of this collaborative project with you. We detected MPs in all 26 zooplankton prey samples that we analyzed and found that the number of MPs in the three species were pretty similar, with an average of 4 MPs per gram of zooplankton (Figure 2). Over 50% of the 418 suspected MPs that we identified in the zooplankton samples were fibers. We also detected MPs in all five gray whale fecal samples that we analyzed. While we also detected fibers among the 37 suspected MPs pulled from the fecal samples, we found a higher proportion of larger MPs such as fragments and pellets in the “poop” samples, than we did in the “zoop” samples (Figure 3). We also tested some seawater samples as controls to see how the composition of MPs in seawater compared to that of zooplankton and gray whale feces. We found that seawater was dominated by fibers, similar to the zooplankton prey. This finding suggests that the larger MPs (e.g., fragments, pellets) that we found in gray whale feces must be coming from somewhere other than their prey and the ambient seawater. This led us to hypothesize that gray whales are likely exposed to MPs through two pathways, via (1) trophic transfer from their zooplankton prey and (2) indiscriminate consumption of ambient MPs in the benthos while foraging benthically (Figure 1). 

Next we wanted to estimate the daily ingestion rates of MPs by gray whales. For this estimation, we used our known values of zooplankton MP ingestion (from our analyzed samples) and extrapolated them using daily energetic needs of gray whales (i.e., how many calories does the whale need each day). The only published values of daily gray whale caloric needs are for pregnant and lactating females (Villegas-Amtmann et al., 2015, 2017), which is why we were only able to estimate daily MP ingestion rates for these two demographic groups. The numbers we calculated were rather staggering (and led us to double-, triple-, and quadruple-check our math) as we estimate that if a pregnant gray whale only ate the mysid N. rayii in a day, she would consume 9.55 million MP per day. We made these estimates for all three prey species that we analyzed as well as a “composite preyscape” (an average of the three prey species) and you can see all of those results in Table 1.

These results are frightening. They still are to me even though I have spent months with this knowledge after having done a lot of the data analysis for this project. I think it is particularly frightening to think about the fact that MPs are not the only anthropogenic threat that gray whales (and really any organism in the ocean) are exposed to. The good news is that you can do something to help reduce this threat in the oceans. Below are just a few suggestions of what you can do to reduce MP pollution to the environment:

1. A major source of pollution in the ocean comes from microfibers through our laundry (as you saw in our results). You can help stop this pathway by simply using a Cora Ball or installing a filter (such as this one) in your washing machine that captures microfleece & polyester fibers.
2. Minimize your use of single-use plastics. There are so many ways to do so including reuseable water bottles, travel mugs for coffee or tea, fabric totes as shopping bags, carry a set of utensils for takeout food, beeswax wraps instead of plastic wrap or sandwich bags.
3. Use public transport when possible as another huge source of microplastics comes from tire treads! This solution also helps reduce your carbon footprint.

References

Besseling E., Foekema E. M., Van Franeker J. A., Leopold M. F., Kühn S., Bravo Rebolledo E. L., et al. (2015). Microplastic in a macro filter feeder: humpback whale Megaptera novaeangliae. Mar. pollut. Bull. 95, 248–252. doi: 10.1016/j.marpolbul.2015.04.007

Donohue M. J., Masura J., Gelatt T., Ream R., Baker J. D., Faulhaber K., et al. (2019). Evaluating exposure of northern fur seals, callorhinus ursinus, to microplastic pollution through fecal analysis. Mar. pollut. Bull. 138, 213–221. doi: 10.1016/j.marpolbul.2018.11.036

Fossi M. C., Panti C., Guerranti C., Coppola D., Giannetti M., Marsili L., et al. (2012). Are baleen whales exposed to the threat of microplastics? a case study of the Mediterranean fin whale (Balaenoptera physalus). Mar. pollut. Bull. 64, 2374–2379. doi: 10.1016/j.marpolbul.2012.08.013

Fossi M. C., Coppola D., Baini M., Giannetti M., Guerranti C., Marsili L., et al. (2014). Large Filter feeding marine organisms as indicators of microplastic in the pelagic environment: the case studies of the Mediterranean basking shark (Cetorhinus maximus) and fin whale (Balaenoptera physalus). Mar. Environ. Res. 100, 17–24. doi: 10.1016/j.marenvres.2014.02.002

Fossi M. C., Marsili L., Baini M., Giannetti M., Coppola D., Guerranti C., et al. (2016). Fin whales and microplastics: the Mediterranean Sea and the Sea of cortez scenarios. Environ. pollut. 209, 68–78. doi: 10.1016/j.envpol.2015.11.022

Fossi M. C., Romeo T., Baini M., Panti C., Marsili L., Campani T., et al. (2017). Plastic debris occurrence, convergence areas and fin whales feeding ground in the Mediterranean marine protected area pelagos sanctuary: a modeling approach. Front. Mar. Sci. 4. doi: 10.3389/fmars.2017.00167

Hildebrand L., Bernard K. S., Torres L. G. (2021). Do gray whales count calories? comparing energetic values of gray whale prey across two different feeding grounds in the eastern north pacific. Front. Mar. Sci. 8. doi: 10.3389/fmars.2021.683634

Hudak C. A., Sette L. (2019). Opportunistic detection of anthropogenic micro debris in harbor seal (Phoca vitulina vitulina) and gray seal (Halichoerus grypus atlantica) fecal samples from haul-outs in southeastern Massachusetts, USA. Mar. pollut. Bull. 145, 390–395. doi: 10.1016/j.marpolbul.2019.06.020

Kahane-Rapport S. R., Czapanskiy M. F., Fahlbusch J. A., Friednlaender A. S., Calambokidis J., Hazen E. L., et al. (2022). Field measurements reveal exposure risk to microplastic ingestion by filter-feeding megafauna. Nat. Commun. 13, 6327. doi: 10.1038/s41467-022-33334-5

Novillo O., Raga J. A., Tomás J. (2020). Evaluating the presence of microplastics in striped dolphins (Stenella coeruleoalba) stranded in the Western Mediterranean Sea. Mar. pollut. Bull. 160, 111557. doi: 10.1016/j.marpolbul.2020.111557

Torres, L. G., Brander, S. M., Parker, J. I., Bloom, E. M., Norman, R., Van Brocklin, J. E., Lasdin, K.S., Hildebrand, L. (2023) Zoop to poop: assessment of microparticle loads in gray whale zooplankton prey and fecal matter reveal high daily consumption rates. Front. Mar. Sci. https://doi.org/10.3389/fmars.2023.1201078

Villegas-Amtmann S., Schwarz L. K., Sumich J. L., Costa D. P. (2015). A bioenergetics model to evaluate demographic consequences of disturbance in marine mammals applied to gray whales. Ecosphere 6, 1–19. doi: 10.1890/ES15-00146.1

Villegas-Amtmann S., Schwarz L. K., Gailey G., Sychenko O., Costa D. P. (2017). East Or west: the energetic cost of being a gray whale and the consequence of losing energy to disturbance. Endangered Species Res.34, 167–183. doi: 10.3354/esr00843

Zantis L. J., Bosker T., Lawler F., Nelms S. E., O’Rorke R., Constantine R., et al. (2022). Assessing microplastic exposure of large marine filter-feeders. Sci. Total Environ. 818, 151815. doi: 10.1016/j.scitotenv.2021.151815

Zhu J., Yu X., Zhang Q., Li Y., Tan S., Li D., et al. (2019). Cetaceans and microplastics: first report of microplastic ingestion by a coastal delphinid, Sousa chinensis. Sci. Total Environ. 659, 649–654. doi: 10.1016/j.scitotenv.2018.12.389