Kelp to whales: New GEMM Lab publication explores indirect effects of a classic trophic cascade on gray whales

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

As many of our avid readers already know, the Pacific Coast Feeding Group (PCFG) of gray whales employs a wide range of foraging tactics to feed on a number of different prey items in various benthic substrate types (Torres et al. 2018). One example foraging tactic is when PCFG whales, particularly when they are in the Oregon portion of their feeding range, forage on mysid shrimp in and near kelp beds on rocky reefs. We have countless drone video clips of whales weaving their large bodies through kelp and many photographs of whales coming to the surface to breath completely covered in kelp, looking more like a sea monster than a whale (Figure 1). So, when former intern Dylan Gregory made an astute observation during the 2018 TOPAZ/JASPER field season in Port Orford about a GoPro video the field team collected that showed many urchins voraciously feeding on an unhealthy-looking kelp stalk (Figure 2a), it made us wonder if and how changes to kelp forests may impact gray whales. 

Fig 1. Gray whale surfacing in a large kelp patch. Photograph captured under NOAA/NMFS research permit #16111. Source: GEMM Lab.

Kelp forests are widely used as a marine example of trophic cascades. Trophic cascades are trigged by the addition/removal of a top predator to/from a system, which causes changes further down the trophic chain. Sea urchins are common inhabitants of kelp forests and in a balanced, healthy system, urchin populations are regulated by predators as they behave cryptically by hiding in crevices in the reef and individual urchins feed passively on drift kelp that breaks off from larger plants. When we think about who controls urchins in kelp forests, we probably think of sea otters first. However, sea otters have been absent from Oregon waters for over a century (Kone et al. 2021), so who controls urchins here? The answer is the sunflower sea star (Figure 2b). Sunflower sea stars are large predators with a maximum arm span of up to 1 m! Unfortunately, a disease epidemic that started in 2013 known as sea star wasting disease caused 80-100% population decline of sunflower sea stars along the coastline between Mexico and Alaska (Harvell et al. 2019). Shortly thereafter, a record-breaking marine heatwave caused warm, nutrient-poor water conditions to persist in the northeast Pacific Ocean from 2014 to 2016 (Jacox et al. 2018). These co-occurring stressors caused unprecedented and long-lasting decline of a previously robust kelp forest in northern California (Rogers-Bennett & Catton 2019), where sea otters are also absent. Given the biogeographical similarity between southern Oregon and northern California and the observation made by Dylan in 2018, we decided to undertake an analysis of the eight years of data collected during the TOPAZ/JASPER project in Port Orford starting in 2016, to investigate the trends of four trophic levels (purple sea urchins, bull kelp, zooplankton, and gray whales) across space and time. The results of our study were published last week in Scientific Reports and I am excited to be able to share them with you today.

Every day during the TOPAZ/JASPER field season, two teams head out to collect data. One team is responsible for tracking gray whales from shore using a theodolite, while the other team heads out to sea on a tandem research kayak to collect prey data (Figure 3). The kayak team samples prey in multiple ways, including dropping a GoPro camera at each sampling station. When the project was first developed, the original goal of these GoPro videos was to measure the relative abundance of prey. Since the sampling stations occur on or near reefs that are shallow with dense surface kelp, traditional methods to assess prey density, such as using a boat with an echosounder, are not suitable options. Instead, GEMM Lab PI Leigh Torres, together with the first Master’s student on this project Florence Sullivan, developed a method to score still images extracted from the GoPro videos to estimate relative zooplankton abundance. However, after we saw those images of urchins feeding on kelp in 2018, we decided to develop another protocol that allowed us to use these GoPro videos to also characterize sea urchin coverage and kelp condition. Once we had occurrence values for all four species, we were able to dig into the spatiotemporal trends.

Figure 3. Map of Port Orford, USA study area showing the 10 kayak sampling stations (white circles) within the two study sites (Tichenor Cove and Mill Rocks). The white triangle represents the cliff top location where theodolite tracking of whales was conducted. Figure and caption taken from Hildebrand et al. 2024.

When we examined the trends for each of the four study species across years, we found that purple sea urchin coverage in both of our study sites within Port Orford increased dramatically within our study period (Figure 4). In 2016, the majority of our sampled stations contained no visible urchins. However, by 2020, we detected urchins at every sampling station. For kelp, we saw the reverse trend; in 2016 all sampling stations contained kelp that was healthy or mostly healthy. But by 2019, there were many stations that contained kelp in poor health or where kelp was absent entirely. Zooplankton and gray whales experienced similar temporal trends as the kelp, with their occurrence metrics (abundance and foraging time, respectively) having higher values at the start of our study period and declining steadily during the eight years. While the rise in urchin coverage across our study area occurred concurrently with the decrease in kelp condition, zooplankton abundance, and gray whale foraging, we wanted to explicitly test how these species are related to one another based on prior ecological knowledge.

Figure 4. Temporal trends of purple sea urchin coverage, bull kelp condition, relative zooplankton abundance, and gray whale foraging time by year across the eight-year study period (2016–2023), from the generalized additive models. The colored ribbons represent approximate 95% confidence intervals. Line types represent the two study sites, Mill Rocks (MR; solid) and Tichenor Cove (TC; dashed). All curves are statistically significant (P < 0.05). Figure and caption taken from Hildebrand et al. 2024.

To test whether urchin coverage had an effect on kelp condition, we hypothesized that increased urchin coverage would be correlated with reduced kelp condition based on the decades of research that has established a negative relationship between the two when a trophic cascade occurs in kelp forest systems. Next, we wanted to test whether kelp condition had an effect on zooplankton abundance and hypothesized that increased kelp condition would be correlated with increased zooplankton abundance. We based this hypothesis on several pieces of prior knowledge, particularly as they pertain to mysid shrimp: (1) high productivity within kelp beds provides food for mysids, including kelp zoospores (VanMeter & Edwards 2013), (2) current velocities are one third slower inside kelp beds compared to outside (Jackson & Winant 1983), which might support the retention of mysids within kelp beds since they are not strong swimmers, and (3) the kelp canopy may serve as potential protection for mysids from predators (Coyer 1984). Finally, we wanted to test whether both kelp condition and zooplankton abundance have an effect on gray whales and we hypothesized that increased values for both would be correlated with increased gray whale foraging time. While the reasoning behind our hypothesized correlation between zooplankton prey and gray whales is obvious (whales eat zooplankton), the reasoning behind the kelp-whale connection may not be. We speculated that since kelp habitat may aggregate or retain zooplankton prey, gray whales may use kelp as an environmental cue to find prey patches. 

When we tested our hypotheses through generalized additive models, we found that increased urchin coverage was significantly correlated with decreased kelp condition in both study sites, providing evidence that a shift from a kelp forest to an urchin barren may have occurred in the Port Orford area. Additionally, increased kelp condition was correlated with increased zooplankton abundance, supporting our hypothesis that kelp forests are an important habitat and resource for nearshore zooplankton prey. Interestingly, this relationship was bell-shaped in one of our two study sites, suggesting that there are other factors besides healthy bull kelp that influence zooplankton abundance, which likely include upwelling dynamics, habitat structure, and local oceanographic characteristics. For the whale model, we found that increased kelp condition was significantly correlated with increased gray whale foraging time, which may corroborate our hypothesis that gray whales use kelp as an environmental cue to locate prey. Zooplankton abundance was significantly correlated with gray whale foraging time in one of our two sites. Once again, this relationship was bell-shaped, which suggests other factors influence gray whale foraging time, including prey quality (Hildebrand et al. 2022) and density.

Figure 5. Effects derived from trophic path generalized additive models of purple sea urchin coverage on kelp condition (A), kelp condition on relative zooplankton abundance (B), and kelp condition and relative zooplankton abundance on gray whale foraging time (C). The colored ribbons represent approximate 95% confidence intervals. Line types represent the two study sites, Mill Rocks (MR; solid) and Tichenor Cove (TC; dashed). Curves with asterisks indicate statistically significant (P < 0.05) relationships. Figure and caption taken from Hildebrand et al. 2024.

Our results highlight the potential larger impacts of reduced gray whale foraging time as a result of these trophic dynamics may cause at the individual and population level. If an area that was once a reliable source of food (like Port Orford) is no longer favorable, then whales likely search for other areas in which to feed. However, if the areas affected by these dynamics are widespread, then individuals may spend more time searching for, and less time consuming, prey, which could have energetic consequences. While our study took place in a relatively small spatial area, the trophic dynamics we documented in our system may be representative of patterns across the PCFG range, given ecological and topographic similarities in habitat use patterns. In fact, in the years with the lowest kelp, zooplankton, and whale occurrence (2020 and 2021) in Port Orford, the GRANITE field team also noted low whale numbers and minimal surface kelp extent in the central Oregon field site off of Newport. However, ecosystems are resilient. We are hopeful that the dynamics we documented in Port Orford are just short-term changes and that the system will return to its former balanced state with less urchins, more healthy bull kelp, zooplankton, and lots of feeding gray whales.

If you are interested in getting a more detailed picture of our methods and analysis, you can read our open access paper here: https://www.nature.com/articles/s41598-024-59964-x

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References

Coyer, J. A. (1984). The invertebrate assemblage associated with the giant kelp, Macrocystis pyrifera, at Santa Catalina Island, California: a general description with emphasis on amphipods, copepods, mysids, and shrimps. Fishery Bulletin, 82(1), 55-66.

Harvell, C. D., Montecino-Latorre, D., Caldwell, J. M., Burt, J. M., Bosley, K., Keller, A., … & Gaydos, J. K. (2019). Disease epidemic and a marine heat wave are associated with the continental-scale collapse of a pivotal predator (Pycnopodia helianthoides). Science advances, 5(1), eaau7042.

Hildebrand, L., Sullivan, F. A., Orben, R. A., Derville, S., & Torres, L. G. (2022). Trade-offs in prey quantity and quality in gray whale foraging. Marine Ecology Progress Series, 695, 189-201.

Jackson, G. A., & Winant, C. D. (1983). Effect of a kelp forest on coastal currents. Continental Shelf Research, 2(1), 75-80.

Jacox, M. G., Alexander, M. A., Mantua, N. J., Scott, J. D., Hervieux, G., Webb, R. S., & Werner, F. E. (2018). Forcing of multi-year extreme ocean temperatures that impacted California Current living marine resources in 2016. Bull. Amer. Meteor. Soc, 99(1).

Kone, D. V., Tinker, M. T., & Torres, L. G. (2021). Informing sea otter reintroduction through habitat and human interaction assessment. Endangered Species Research, 44, 159-176.

Rogers-Bennett, L., & Catton, C. A. (2019). Marine heat wave and multiple stressors tip bull kelp forest to sea urchin barrens. Scientific reports, 9(1), 15050.

Torres, L. G., Nieukirk, S. L., Lemos, L., & Chandler, T. E. (2018). Drone up! Quantifying whale behavior from a new perspective improves observational capacity. Frontiers in Marine Science, 5, 319.

VanMeter, K., & Edwards, M. S. (2013). The effects of mysid grazing on kelp zoospore survival and settlement. Journal of Phycology, 49(5), 896-901.

Who, where, when: Estimating individual space use patterns of PCFG gray whales

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

Understanding how baleen whales are affected by human activity is a central goal for many research projects in the GEMM Lab. The overarching goal of the GRANITE (Gray whale Response to Ambient Noise Informed by Technology and Ecology) project is to quantify baleen whale physiological response to different stressors (e.g., boat presence and noise) and model the subsequent impacts of these stressors on the population. We will achieve this goal by implementing our long-term, replicate dataset of Pacific Coast Feeding Group (PCFG) gray whales into a framework called population consequences of disturbance (PCoD). I will not go into the details of PCoD in this blog (but I wrote a post a few years ago that you can revisit). Instead, I will explain the approach I am taking to assess where and when individual whales spend time in our study area, which will form an essential component of PCoD and be one of the chapters of my PhD dissertation.

Individuals in a population are unlikely to be exposed to a stressor in a uniform way because they make decisions differently based on intrinsic (e.g., sex, age, reproductive status) and extrinsic (e.g., environment, prey, predators) factors (Erlinge & Sandell 1986). For example, a foraging female gray whale who is still nursing a calf will need to consider factors that are different to ones that an adult single male might need to consider when choosing a location to feed. These differences in decision-making exist across the whole population, which makes it important to understand where individuals are spending time and how they overlap with stressors in space and time before trying to quantify the impacts of stressors on the population as a whole (Pirotta et al. 2018). I am currently working on an analysis that will determine an individual’s exposure to a number of stressors based on their space use patterns. 

We can monitor space use patterns of individuals in a population through time using spatial capture-recapture techniques. As the name implies, a spatial capture-recapture technique involves capturing an individual in a marked location during a sampling period, releasing it back into the population, and then (hopefully) re-capturing it during another sampling period in the future, at either the same or a different location. With enough repeat sampling events, the method should build spatial capture histories of individuals through time to better understand an individual’s space use patterns (Borchers & Efford 2008). While the use of the word capture implies that the animal is being physically caught, this is not necessarily the case. Individuals can be “captured” in a number of non-invasive ways, including by being photographed, which is how we “capture” individual PCFG gray whales. These capture-recapture methods were first pioneered in terrestrial systems, where camera traps (i.e., cameras that take photos or videos when a motion sensor is triggered) are set up in a systematic grid across a study area (Figure 1; Royle et al. 2009, Gray 2018). Placing the cameras in a grid system ensures that there is an equal distribution of cameras throughout the study area, which means that an animal theoretically has a uniform chance of being captured. However, because we know that individuals within a population make space use decisions differently, we assume that individuals will distribute themselves differently across a landscape, which will manifest as individuals having different centers of their spatial activity. The probability of capturing an individual is highest when a camera trap is at that individual’s activity center, and the cameras furthest away from the individual’s activity center will have the lowest probability of capturing that individual (Efford 2004). By using this principle of probability, the data generated from spatial capture-recapture field methods can be modelled to estimate the activity centers and ranges for all individuals in a population. The overlap of an individual’s activity center and range can then be compared to the spatiotemporal distribution of stressors that an individual may be exposed to, allowing us to determine whether and how an individual has been exposed to each stressor. 

Figure 1. Example of camera trap grid in a study area. Figure taken from Gray (2018).

While capture-recapture methods were first developed in terrestrial systems, they have been adapted for application to marine populations, which is what I am doing for our GRANITE dataset of PCFG gray whales. Together with a team of committee members and GRANITE collaborators, I am developing a Bayesian spatial capture-recapture model to estimate individual space use patterns. In order to mimic the camera trap grid system, we have divided our central Oregon coast study area into latitudinal bins that are approximately 1 km long. Unfortunately, we do not have motion sensor activated cameras that automatically take photographs of gray whales in each of these latitudinal bins. Instead, we have eight years of boat-based survey effort with whale encounters where we collect photographs of many individual whales. However, as you now know, being able to calculate the probability of detection is important for estimating an individual’s activity center and range. Therefore, we calculated our spatial survey effort per latitudinal bin in each study year to account for our probability of detecting whales (i.e., the area of ocean in km2 that we surveyed). Next, we tallied up the number of times we observed every individual PCFG whale in each of those latitudinal bins per year, thus creating individual spatial capture histories for the population. Finally, using just those two data sets (the individual whale capture histories and our survey effort), we can build models to test a number of different hypotheses about individual gray whale space use patterns. There are many hypotheses that I want to test (and therefore many models that I need to run), with increasing complexity, but I will explain one here.

Over eight years of field work for the GRANITE project, consisting of over 40,000 km2 of ocean surveyed with 2,169 sightings of gray whales, our observations lead us to hypothesize that there are two broad space use strategies that whales use to optimize how they find enough prey to meet their energetic needs. For the moment, we are calling these strategies ‘home-body’ and ‘roamer’. As the name implies, a home-body is an individual that stays in a relatively small area and searches for food in this area consistently through time. A roamer, on the other hand, is an individual that travels and searches over a greater spatial area to find good pockets of food and does not generally tend to stay in just one place. In other words, we except a home-body to have a consistent activity center through time and a small activity range, while a roamer will have a much larger activity range and its activity center may vary more throughout the years (Figure 2). 

Figure 2. Schematic representing one of the hypotheses we will be testing with our Bayesian spatial capture-recapture models. The schematic shows the activity centers (the circles) and activity ranges (vertical lines attached to the circles) of two individuals (green and orange) across three years in our central Oregon study area. The green individual represents our hypothesized idea of a home-body, whereas the orange individuals represents our idea of a roamer.

While this hypothesis sounds straightforward, there are a lot of decisions that I need to make in the Bayesian modeling process that can ultimately impact the results. For example, do all home-bodies in a population have the same size activity range or can the size vary between different home-bodies? If it can vary, by how much can it vary? These same questions apply for the roamers too. I have a long list of questions just like these, which means a lot of decision-making on my part, and that long list of hypotheses I previously mentioned. Luckily, I have a fantastic team made up of Leigh, committee members, and GRANITE collaborators that are guiding me through this process. In just a few more months, I hope to reveal how PCFG individuals distribute themselves in space and time throughout our central Oregon study area, and hence describe their exposure to different stressors. Stay tuned! 

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References

Borchers DL, Efford MG (2008) Spatially explicit maximum likelihood methods for capture-recapture studies. Biometrics 64:377-385.

Efford M (2004) Density estimation in live-trapping studies. Oikos 106:598-610.

Erlinge S, Sandell M (1986) Seasonal changes in the social organization of male stoats, Mustela erminea: An effect of shifts between two decisive resources. Oikos 47:57-62.

Gray TNE (2018) Monitoring tropical forest ungulates using camera-trap data. Journal of Zoology 305:173-179.

Pirotta E, Booth CG, Costa DP, Fleishman E, Kraus SD, and others (2018) Understanding the population consequences of disturbance. Ecology and Evolution 8(19):9934–9946.Royle J, Nichols J, Karanth KU, Gopalaswamy AM (2009) A hierarchical model for estimating density in camera-trap studies. Journal of Applied Ecology 46:118-127.

Familiar flukes and flanks: The 9th GRANITE field season is underway

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

The winds are consistently (and sometimes aggressively) blowing from the north here on the Oregon coast, which can only mean one thing – summer has arrived! Since mid-May, the GRANITE (Gray whale Response to Ambient Noise Informed by Technology and Ecology) team has been looking for good weather windows to survey for gray whales and we have managed to get five great field work days already. In today’s blog post, I am going to share what (and who) we have seen so far.

On our first day of the field season, PI Leigh Torres, postdoc KC Bierlich and myself, were joined by a special guest: Dr. Andy Read. Andy is the director of the Duke University Marine Lab, where he also runs his own lab, which focuses on conservation biology and ecology of marine vertebrates. Andy was visiting the Hatfield Marine Science Center as part of the Lavern Weber Visiting Scientist program and was hosted here by Leigh. For those of you that do not know, Andy was Leigh’s graduate school advisor at Duke where she completed her Master’s and doctoral degrees. It felt very special to have Andy on board our RHIB Ruby for the day and to introduce him to some friends of ours. The first whale we encountered that day was “Pacman”. While we are always excited to re-sight an individual that we know, this sighting was especially mind-blowing given the fact that Leigh had “just” seen Pacman approximately two months earlier in Guerrero Negro, one of the gray whale breeding lagoons in Mexico (read this blog about Leigh and Clara’s pilot project there). Aside from Pacman, we saw five other individuals, all of which we had seen during last year’s field season. 

The first day of field work for the 2023 GRANITE field season! From left to right: Leigh Torres, Lisa Hildebrand, Andy Read, and KC Bierlich. Source: L. Torres.

Since that first day on the water, we have conducted field work on four additional days and so far, we have only encountered known individuals in our catalog. This fact is exciting because it highlights the strong site fidelity that Pacific Coast Feeding Group (PCFG) gray whales have to areas within their feeding range. In fact, I am examining the residency and space use of each individual whale we have observed in our GRANITE study for one of my PhD chapters to better understand the level of fidelity individuals have to the central Oregon coast. Furthermore, this site fidelity underpins the unique, replicate data set on individual gray whale health and ecology that the GRANITE project has been able to progressively build over the years. So far during this field season in 2023, we have seen 13 unique individuals, flown the drone over 10 of them and collected four fecal samples from two, which represent critical data points from early on in the feeding season.

Our sightings this year have not only highlighted the high site fidelity of whales to our study area but have also demonstrated the potential for internal recruitment of calves born to “PCFG mothers” into the PCFG. Recruitment to a population can occur in two ways: externally (individuals immigrate into a population from another population) or internally (calves born to females that are part of the population return to, or stay, within their mothers’ population). Three of the whales we have seen so far this year are documented calves from females that are known to consistently use the PCFG range, including our central Oregon coast study area. In fact, we documented one of these calves, “Lunita”, just last year with her mother (see Clara’s recap of the 2022 field season blog for more about Lunita). The average calf survival estimate between 1997-2017 for the PCFG was 0.55 (Calambokidis et al. 2019), though it varied annually and widely (range: 0.34-0.94). Considering that there have been years with calf survival estimates as low as ~30%, it is therefore all the more exciting when we re-sight a documented calf, alive and well!

“Lunita”, an example of successful internal recruitment

We have also been collecting data on the habitat and prey in our study system by deploying our paired GoPro/RBR sensor system. We use the GoPro to monitor the benthic substrate type and relative prey densities in areas where whales are feeding. The RBR sensor collects high-frequency, in-situ dissolved oxygen and temperature data, enabling us to relate environmental metrics to relative prey measurements. Furthermore, we also collect zooplankton samples with a net to assess prey community and quality. On our five field work days this year, we have predominantly collected mysid shrimp, including gravid (a.k.a. pregnant) individuals, however we have also caught some Dungeness and porcelain crab larvae. The GEMM Lab is also continuing our collaboration with Dr. Susanne Brander’s lab at OSU and her PhD student Lauren Kashiwabara, who plan on conducting microplastic lab experiments on wild-caught mysid shrimp. Their plan is to investigate the growth rates of mysid shrimp under different temperature, dissolved oxygen, and microplastic load conditions. However, before they can begin their experiments, they need to successfully culture the mysids in the lab, which is why we collect samples for them to use as their ‘starter culture’. Stay tuned to hear more about this project as it develops!

So, all in all, it has been an incredibly successful start to our field season, marked by the return of many familiar flukes and flanks! We are excited to continue collecting rock solid GRANITE data this summer to increase our efforts to understand gray whale ecology and physiology. 

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References

Calambokidis, J., Laake, J., and Perez, A. (2019). Updated analyses of abundance and population structure of seasonal gray whales in the Pacific Northwest, 1996-2017. IWC, SC/A17/GW/05 for the Workshop on the Status of North Pacific Gray Whales. La Jolla: IWC.

The road to candidacy is paved with knowledge

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

As I sat down to write this blog, I realized that it is the first post I have written in 2023! This is largely because I have spent the last seven weeks preparing for (and partly taking) my PhD qualifying exams, an academic milestone that involves written and oral exams prepared by each committee member for the student. The point of the qualifying exams is for the student’s committee to determine the student’s understanding of their major field, particularly where and what the limits of that understanding are, and to assess the student’s capability for research. How do you prepare for these exams? Reading. Lots of reading and synthesis of the collective materials assigned by each committee member. My dissertation research covers a broad range of Pacific Coast Feeding Group (PCFG) gray whale ecology, such as space use, oceanography, foraging theory and behavioral responses to anthropogenic activities. Accordingly, my assigned reading lists were equally broad and diverse. For today’s blog, I am going to share some of the papers that have stuck with me and muse about how these topics relate to my study system, the Pacific Coast Feeding Group (PCFG) of gray whales.

Space use & home range

For decades, ecologists have been interested in defining an animal’s use of space through time, often referred to as an animal’s home range. The seminal definition of a home range comes from Burt (1943) who outlined it as “the area traversed by an individual in its normal activities of food gathering, mating, and caring for young.”. I like this definition of a home range because it is biologically grounded and based on an animal’s requirements. However, quantifying an animal’s home range based on this definition is harder than it may sound. In an ideal world, it could be achieved if we were able to collect location data that is continuous (i.e., one location per second), long-term (i.e., at least half the lifespan of an animal) and precise (i.e., correct to the nearest meter) together with behavior for an individual. However, a device that could collect such data, particularly for a baleen whale, does not currently exist. Instead, we must use discontinuous (i.e., one location per hour, day or month) and/or short-term (i.e., <1 year) data with variable precision to calculate animal home ranges. A very common and simple analytical method that is used to calculate an animal’s home range is the minimum convex polygon (MCP). MCP draws the smallest polygon around points with all interior angles less than 180º. While this method is appealing and widely used, it often overestimates the home range by including areas not used by an animal at all (Figure 1).

Figure 1. (a) 10 point locations where an individual was observed; (b) the home range as determined by the minimum convex polygon method; (c) the red path shows the movements the animal actually took. Note the large white area in (c) where the animal never went even though it is considered part of the animal’s home range.

This example is just one of many where home range estimators inaccurately describe an animal’s space use. However, this does not mean that we should not attempt to make our best approximations of an animal’s home range using the tools and data we have at our disposal. Powell & Mitchell perfectly summarized this sentiment in their 2012 paper: “Understanding animal’s home ranges will be a messy, irregular, complex process and the results will be difficult to map. We must embrace this messiness as it simply represents the real behaviors of animals in complex and variable environments.”. For my second dissertation chapter, I am investigating individual PCFG gray whale space use patterns by calculating activity centers and ranges. The activity center is simply the geographic center of all points of observation (Hayne, 1949) and the range is the distance from the activity center to the most distant point of observations in either poleward direction. While the actual activity center is probably relatively meaningless to a whale, we hope that by calculating these metrics we can identify different strategies of space use that individuals employ to meet their energetic requirements (Figure 2).

Figure 2. Sightings of nine different PCFG individuals across our GRANITE study area. Each circle represents a location where an individual was sighted and circles are color-coded by year. Plotting the raw data of sighting histories of these individuals hints at patterns in space use by different individuals, which I will explore further in my second dissertation chapter.

Non-stationary responses to oceanography

Collecting spatiotemporally overlapping predator-prey datasets at the appropriate scales is notoriously challenging in the marine environment. As a result, marine ecologists often try to find patterns between marine species and oceanographic and/or environmental covariates, as these can sometimes be easier to sample and thus make marine species predictions simpler. This approach has been applied successfully in hundreds, if not thousands, of studies (e.g., Barlow et al., 2020; Derville et al., 2022). Unfortunately, these relationships are not always proving to be stable over time, a phenomenon called non-stationarity. For example, Schmidt et al. (2014) showed that the reproductive successes of Brandt’s cormorants and Cassin’s auklets on southeast Farallon Island were positively correlated with each other from 1975 to 1995 and were associated with negative El Niño-Southern Oscillation. However, around the mid-1990s this relationship broke down and by 2002, the reproductive successes of the two species were significantly negatively correlated (Figure 3). Furthermore, the relationships between reproductive success and most physical oceanographic conditions became highly variable from year to year and were non-stationary. Thus, if the authors continued to use the relationships defined early on in the study (1975-1995) to predict seabird reproductive success relative to ocean conditions from 2002-2012, their predictions would have been completely wrong. After reading this study, I thought a lot about what the oceanographic conditions have been since the GEMM Lab started studying PCFG gray whales vs. the years prior. Leigh launched the GRANITE project in 2016, right at the tail end of the record marine heatwave in the Pacific, known as “the Blob”. While we do not have as long of a dataset as the Schmidt et al. (2014) study, I wonder whether we might find non-stationary responses between PCFG gray whales and environmental and/or oceanographic variables, given how the effects of the Blob lingered for a long time and we may have captured the central Oregon coast environment shifting from ‘weird to normal’. Non-stationarity is something I will at least keep in mind when I am working on my third dissertation chapter which will investigate the environmental and oceanographic drivers of PCFG gray whale space use strategies.

Figure 3. Figure and caption taken from Schmidt et al. (2014).

There are so many more studies and musings that I could write about. I keep being told by others who have been through this qualifying exam process that this is the smartest I am ever going to be, and I finally understand what they mean. After spending almost two months in my own little study world, my research, and where it fits within the complex web of ecological knowledge, has snapped into hyperfocus. I can see clearly where past research will guide me and where I am blazing a new trail of things never attempted before. While I still have the oral portion of my exams before me (in fact, it’s tomorrow!), I am already giddy with excitement to switch back to analyzing data and making progress on my dissertation research.

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References

Barlow, D.R., Bernard, K.S., Escobar-Flores, P., Palacios, D.M., Torres, L.G. 2020. Links in the trophic chain: modeling functional relationships between in situ oceanography, krill, and blue whale distribution under different oceanographic regimes. Marine Ecology Progress Series 642: 207−225. 

Burt, W.H. 1943. Territoriality and home range concepts as applied to mammals. Journal of Mammalogy 24(3): 346-352. https://doi.org/10.2307/1374834

Derville, S., Barlow, D.R., Hayslip, C., Torres, L.G. 2022. Seasonal, annual, and decadal distribution of three rorqual whale species relative to dynamic ocean conditions off Oregon, USA. Frontiers in Marine Science 9. https://doi.org/10.3389/fmars.2022.868566

Hayne, D.W. 1949. Calculation of size of home range. Journal of Mammalogy 30(1): 1-18. 

Powell, R.A., Mitchell, M.S. 2012. What is a home range? Journal of Mammalogy 93(4): 948-958. https://doi.org/10.1644/11-MAMM-S-177.1

Schmidt, A.E., Botsford, L.W., Eadie, J.M., Bradley, R.W., Di Lorenzo E., Jahncke, J. 2014. Non-stationary seabird responses reveal shifting ENSO dynamics in the northeast Pacific. Marine Ecology Progress Series 499: 249-258. https://doi.org/10.3354/meps10629

Decisions, decisions: New GEMM Lab publication reveals trade-offs in prey quantity and quality in gray whale foraging

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

Obtaining enough food is crucial for predators to ensure adequate energy gain for maintenance of vital functions and support for energetically costly life history events (e.g., reproduction). Foraging involves decisions at every step of the process, including prey selection, capture, and consumption, all of which should be as efficient as possible. Making poor foraging decisions can have long-term repercussions on reproductive success and population dynamics (Harris et al. 2007, 2008, Grémillet et al. 2008), and for marine predators that rely on prey that is spatially and temporally dynamic and notoriously patchy (Hyrenbach et al. 2000), these decisions can be especially challenging. Prey abundance and density are frequently used as predictors of marine predator distribution, movement, and foraging effort, with predators often selecting highly abundant or dense prey patches (e.g., Goldbogen et al. 2011, Torres et al. 2020). However, there is increased recognition that prey quality is also an important factor to consider when assessing a predator’s ecology and habitat use (Spitz et al. 2012), and marine predators do show a preference for higher quality prey items (e.g., Haug et al. 2002, Cade et al. 2022). Moreover, negative impacts of low-quality prey on the health and breeding success of some marine mammals (Rosen & Trites 2000, Trites & Donnelly 2003) have been documented. Therefore, examining multiple prey metrics, such as prey quantity and quality, in predator ecology studies is critical.

Figure 1. Site map of the Port Orford TOPAZ/JASPER integrated projects. Blue squares represent the location of the 12 sampling stations within the 2 study sites (site boundaries demarcated with black lines). Brown dot represents the cliff-top observation site where theodolite tracking occurred.

Our integrated TOPAZ/JASPER projects in Port Orford do just this! We collect both prey quantity and quality data from a tandem research kayak, while we track Pacific Coast Feeding Group (PCFG) gray whales from shore. The prey and whale sampling overlap spatially (and often temporally within the same day). This kind of concurrent predator-prey sampling at similar scales is often logistically challenging to achieve, yet because PCFG gray whales have an affinity for nearshore, coastal habitats, it is something we have been able to achieve in Port Orford. Since 2016, a field team comprised of graduate, undergraduate, and high school students has collected data during the month of August to investigate gray whale foraging decisions relative to prey. Every day, a kayak team collects GoPro videos (to assess relative prey abundance; AKA: quantity) and zooplankton samples using a tow net (to assess prey community composition; AKA: quality through caloric content of different species) (Figure 1). At the same time, a cliff team surveys for gray whales from shore and tracks them using a theodolite, which provides us with tracklines of individual whales; We categorize each location of a whale into three broad behavior states (feeding, searching, transiting) based on movement patterns. Over the years, the various students who have participated in the TOPAZ/JASPER projects have written many blog posts, which I encourage you to read here (particularly to get more detailed information about the field methods). 

Figure 2. An example daily layer of relative prey abundance (increasing color darkness corresponds with increasing abundance) in one study site with a whale theodolite trackline recorded on the same day overlaid and color-coded by behavioral state.

Several years of data are needed to conduct a robust analysis for our ecological questions about prey choice, but after seven years, we finally had the data and I am excited to share the results, which are due to the many years of hard work from many students! Our recent paper in Marine Ecology Progress Series aimed to determine whether PCFG gray whale foraging decisions are driven by prey quantity (abundance) or quality (caloric content of species) at a scale of 20 m (which is slightly less than 2 adult gray whale body lengths). In this study, we built upon results from my previous Master’s publication, which revealed that there are significant differences in the caloric content between the six common nearshore zooplankton prey species that PCFG gray whales feed on (Hildebrand et al. 2021). Therefore, in this study we addressed the hypothesis that individual whales will select areas where the prey community is dominated by the mysid shrimp Neomysis rayii, since it is significantly higher in caloric content than the other two prey species we identified, Holmesimysis sculpta (a medium quality mysid shrimp species) and Atylus tridens (a low quality amphipod species) (Hildebrand et al. 2021). We used spatial statistics and model to make daily maps of prey abundance and quality that we compared to our whale tracks and behavior from the same day. Please read our paper for the details on our novel methods that produced a dizzying amount of prey layers, which allowed us to tease apart whether gray whales target prey quantity, quality, or a mixture of both when they forage. 

Figure 3. Figure shows the probability of gray whale foraging relative to prey abundance (color-coded by prey species). Dark grey vertical line represents the mean threshold for the H. sculpta curves (12.0); light grey vertical lines: minimum (7.2) and maximum (15.3) thresholds for the H. sculpta curves. Inflection points could not be calculated for the N. rayii curves

So, what did we find? The models proved our hypothesis wrong: foraging probability was significantly correlated with the quantity and quality of the mysid H. sculpta, which has significantly lower calories than N. rayii. This result puzzled us, until we started looking at the overall quantity of these two prey types in the study area and realized that the amount of calorically-rich N. rayii never reached a threshold where it was beneficial for gray whales to forage. But, there was a lot of H. sculpta, which likely made for an energetic gain for the whales despite not being as calorically rich as N. rayii. We determined a threshold of H. sculpta relative abundance that is required to initiate the gray whale foraging behavior, and the abundance of N. rayii never came close to this level (Figure 3). Despite not having the highest quality, H. sculpta did have the highest abundance and showed a significant positive relationship with foraging behavior, unlike the other prey items. Interestingly, whales never selected areas dominated by the low-calorie species A. tridens. These results demonstrate trade-off choices by whales for this abundant, medium-quality prey.

To our knowledge, individual baleen whale foraging decisions relative to available prey quantity and quality have not been addressed previously at this very fine-scale. Interestingly, this trade-off between prey quantity and quality has also been detected in humpback whales foraging in Antarctica at depths deeper than where the densest krill patches occur; while the whales are exploiting less dense krill patches, these krill composed of larger, gravid, higher-quality krill (Cade et al. 2022). While it is unclear how baleen whales differentiate between prey species or reproductive stages, several mechanisms have been suggested, including visual and auditory identification (Torres 2017). We assume here that gray whales, and other baleen whale species, can differentiate between prey species. Thus, our results showcase the importance of knowing the quality (such as caloric content) of prey items available to predators to understand their foraging ecology (Spitz et al. 2012). 

References

Cade DE, Kahane-Rapport SR, Wallis B, Goldbogen JA, Friedlaender AS (2022) Evidence for size-selective pre- dation by Antarctic humpback whales. Front Mar Sci 9:747788

Goldbogen JA, Calambokidis J, Oleson E, Potvin J, Pyenson ND, Schorr G, Shadwick RE (2011) Mechanics, hydrody- namics and energetics of blue whale lunge feeding: effi- ciency dependence on krill density. J Exp Biol 214:131−146

Grémillet D, Pichegru L, Kuntz G, Woakes AG, Wilkinson S, Crawford RJM, Ryan PG (2008) A junk-food hypothesis for gannets feeding on fishery waste. Proc R Soc B 275: 1149−1156

Harris MP, Beare D, Toresen R, Nøttestad L, and others (2007) A major increase in snake pipefish (Entelurus aequoreus) in northern European seas since 2003: poten- tial implications for seabird breeding success. Mar Biol 151:973−983

Harris MP, Newell M, Daunt F, Speakman JR, Wanless S (2008) Snake pipefish Entelurus aequoreus are poor food for seabirds. Ibis 150:413−415

Haug T, Lindstrøm U, Nilssen KT (2002) Variations in minke whale (Balaenoptera acutorostrata) diet and body condi- tion in response to ecosystem changes in the Barents Sea. Sarsia 87:409−422

Hildebrand L, Bernard KS, Torres LG (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 8:1008

Hyrenbach KD, Forney KA, Dayton PK (2000) Marine pro- tected areas and ocean basin management. Aquat Con- serv 10:437−458

Rosen DAS, Trites AW (2000) Pollock and the decline of Steller sea lions: testing the junk-food hypothesis. Can J Zool 78:1243−1250

Spitz J, Trites AW, Becquet V, Brind’Amour A, Cherel Y, Galois R, Ridoux V (2012) Cost of living dictates what whales, dolphins and porpoises eat: the importance of prey quality on predator foraging strategies. PLOS ONE 7:e50096

Torres LG, Barlow DR, Chandler TE, Burnett JD (2020) Insight into the kinematics of blue whale surface forag- ing through drone observations and prey data. PeerJ 8: e8906

Torres LG (2017) A sense of scale: foraging cetaceans’ use of scale-dependent multimodal sensory systems. Mar Mamm Sci 33:1170−1193

Trites AW, Donnelly CP (2003) The decline of Steller sea lions Eumetopias jubatus in Alaska: a review of the nutri- tional stress hypothesis. Mammal Rev 33:3−28

Reuniting with some old friends: The 8th GRANITE field season is underway

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

We are almost halfway through June which means summer has arrived! Although, here on the Oregon coast, it does not entirely feel like it. We have been swinging between hot, sunny days and cloudy, foggy, rainy days that are reminiscent of those in spring or even winter. Despite these weather pendulums, the GEMM Lab’s GRANITE project is off to a great start in its 8th field season! The field team has already ventured out onto the Pacific Ocean in our trusty RHIB Ruby on four separate days looking for gray whales and in this blog post, I am going to share what we have seen so far.

The core GRANITE field team before the May 24th “trial run”. From left to right: Leigh Torres, KC Bierlich, Clara Bird, Lisa Hildebrand, Alejandro Fernández Ajó. Source: L. Torres.

PI Leigh, PhD candidate Clara and I headed out for a “trial run” on May 24th. While the intention for the day was to make sure all our gear was running smoothly and we still remembered how to complete the many tasks associated with our field work (boat loading and trailering, drone flying and catching, poop scooping, data download, to name a few), we could not resist surveying our entire study range given the excellent conditions. It was a day that all marine field scientists hope for – low winds (< 5 kt all day) and a 3 ft swell over a long period. Despite surveying between Waldport and Depoe Bay, we only encountered one whale, but it was a whale that put a smile on each of our faces. After “just” 252 days, we reunited with Solé, the star of our GRANITE dataset, with record numbers of fecal samples and drone flights collected. This record is due to what seems to be a strong habitat or foraging tactic preference by Solé to remain in a relatively small spatial area off the Oregon coast for most of the summer, rather than traveling great swaths of the coast in search for food. Honest truth, on May 24th we found her exactly where we expected to find her. While we did not collect a fecal sample from her on that day, we did perform a drone flight, allowing us to collect a critical early feeding season data point on body condition. We hope that Solé has a summer full of mysids on the Oregon coast and that we will be seeing her often, getting rounder each time!

Our superstar whale Solé. Her identifying features are a small white line on her left side (green box) and a white dot in front of her dorsal hump on the right side (red circle). Source: GEMM Lab. Photograph captured under NOAA/NMFS permit #21678

Just a week after this trial day, we had our official start to the field season with back-to-back days on the water. On our first day, postdoc Alejandro, Clara and I were joined by St. Andrews University Research Fellow Enrico Pirotta, who is another member of the GRANITE team. Enrico’s role in the GRANITE project is to implement our long-term, replicate dataset into a framework called Population consequences of disturbance (PCoD; you can read all about it in a previous blog). We were thrilled that Enrico was able to join us on the water to get a sense for the species and system that he has spent the last several months trying to understand and model quantitatively from a computer halfway across the world. Luckily, the whales sure showed up for Enrico, as we saw a total of seven whales, all of which were known individuals to us! Several of the whales were feeding in water about 20 m deep and surfacing quite erratically, making it hard to get photos of them at times. Our on-board fish finder suggested that there was a mid-water column prey layer that was between 5-7 m thick. Given the flat, sandy substrate the whales were in, we predicted that these layers were composed of porcelain crab larvae. Luckily, we were able to confirm our hypothesis immediately by dropping a zooplankton net to collect a sample of many porcelain crab larvae. Porcelain crab larvae have some of the lowest caloric values of the nearshore zooplankton species that gray whales likely feed on (Hildebrand et al. 2021). Yet, the density of larvae in these thick layers probably made them a very profitable meal, which is likely the reason that we saw another five whales the next day feeding on porcelain crab larvae once again.

On our most recent field work day, we only encountered Solé, suggesting that the porcelain crab swarms had dissipated (or had been excessively munched on by gray whales), and many whales went in search for food elsewhere. We have done a number of zooplankton net tows across our study area and while we did collect a good amount of mysid shrimp already, they were all relatively small. My prediction is that once these mysids grow to a more profitable size in a few days or weeks, we will start seeing more whales again.

The GRANITE team from above, waiting & watching for whales, as we will be doing for the rest of the summer! Source: GEMM Lab.

So far we have seen nine unique individuals, flown the drone over eight of them, collected fecal samples from five individuals, conducted 10 zooplankton net tows and seven GoPro drops in just four days of field work! We are certainly off to a strong start and we are excited to continue collecting rock solid GRANITE data this summer to continue our efforts to understand gray whale ecology and physiology.

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Literature cited

Hildebrand L, Bernard KS, Torres LGT. 2021. Do gray whales count calories? Comparing energetic values of gray whale prey across two different feeding grounds in the Eastern North Pacific. Frontiers in Marine Science 8. doi: 10.3389/fmars.2021.683634

Dive into Oregon’s underwater forests

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

When I was younger, I aspired to be a marine mammal biologist. I thought it was purely about knowing as much about marine mammal species as possible. However, over time and with experience in this field, I have realized that in order to understand a species, you need to have a holistic understanding of its prey, habitat, and environment. When I first applied to be advised by Leigh in the GEMM Lab, I had no idea how much of my time I would spend looking at tiny zooplankton under a microscope, thinking about the different benefits of different habitat types, or reading about oceanographic processes. But these things have been incredibly vital to my research to date and as a result, I now refer to myself as a marine ecologist. This holistic understanding that I am gaining will only grow throughout my PhD as I am broadly looking at the habitat use, site fidelity, and population dynamics of the Pacific Coast Feeding Group (PCFG) of gray whales for my thesis research. 

The PCFG display many foraging tactics and occupy several habitat types along the Oregon coast while they spend their summer feeding seasons here (Torres et al. 2018). Here, I will focus on one of these habitats: kelp. When you hear the word kelp, you probably conjure an image of long, thick stalks that reach from the ocean floor to the surface, with billowing fronds waving around (Figure 1a). However, this type is only one of three basic morphologies (Filbee-Dexter & Scheibling 2014) and it is called canopy kelp, which often forms extensive forests. The other two morphologies are stipitate and prostrate kelps. The former forms midwater stands (Figure 1b) while the latter forms low-lying kelp beds (Figure 1c). All three of these morphologies exist on the Oregon coast and create a mosaic of understory and canopy kelp patches that dot our coastline.

Figure 1. Examples of the three different kelp morphologies. a: bull kelp (Nereocystis luetkeana) is a type of canopy kelp and the dominant kelp on the Oregon coast (Source: Oregon Coast Aquarium); b: sea palm (Postelsia palmaeformis) is a type of stipitate kelp that forms mid-water stands (Source: Oregon Conservation Strategy); c: sea cabbage (Saccharina sessilis) is a type of prostrate kelp that is stipeless and forms low-lying kelp beds (Source: Central Coast Biodiversity).

One of the most magnificent things about kelp is that it is not just a species itself, but it provides critical habitat, refuge, and food resources to a myriad of other species due to its high rates of primary production (Dayton 1985). Kelp is often referred to as a foundation species due to all of these critical services it provides. In Oregon, many species of rockfish, which are important commercial and recreational fisheries, use kelp as habitat throughout their life cycle, including as nursery grounds. Lingcod, another widely fished species, forages amongst kelp. A large number of macroinvertebrates can be found in Oregon kelp forests, including anemones, limpets, snails, sea urchins, sea stars, and abalone, to name a fraction of them. 

Kelps grow best in cold, nutrient-rich waters (Tegner et al. 1996) and their growth and distribution patterns are highly naturally variable on both temporal and spatial scales (Krumhansl et al. 2016). However, warm water, low nutrient or light conditions, intensive grazing by herbivores, and severe storm activity can lead to the erosion and defoliation of kelp beds (Krumhansl et al. 2016). While these events can occur naturally in cyclical patterns, the frequency of several of these events has increased in recent years, as a result of climate change and anthropogenic impacts. For example, Dawn’s blog discussed increasing marine heatwaves that represent an influx of warm water for a prolonged period of time. In fact, kelps can be useful sentinels of change as they tend to be highly responsive to changes in environmental conditions (e.g., Rogers-Bennet & Catton 2019) and their nearshore, coastal location directly exposes them to human activities, such as pollution, harvesting, and fishing (Bennett et al. 2016).

Due to its foundational role, changes or impacts to kelp can reverberate throughout the ecosystem and negatively affect many other species. As mentioned previously, kelp is naturally highly variable, and like many other ecological processes, undergoes boom and bust cycles. For over four decades, dense, productive kelp forests have been shown to transition to sea urchin barrens, and back again, in natural cycles (Sala et al. 1998; Pinnegar et al. 2000; Steneck et al. 2002; Figure 2). These transitions are called phase shifts. In a healthy, balanced kelp forest, sea urchins typically passively feed on detrital plant matter, such as broken off pieces of kelp fronds that fall to the seafloor. A phase shift occurs when the grazing intensity of sea urchins increases, resulting in them actively feeding on kelp stalks and fronds to a point where the kelp in an area can become greatly reduced, creating an urchin barren. Sea urchin grazing intensity can change for a number of reasons, including reduction in sea urchin predators (e.g., sea otters, sunflower sea stars) or poor kelp recruitment events (e.g., due to warm water temperature). Regardless of the reason, the phases tend to transition back and forth over time. However, there is concern that sea urchin barrens may become an alternative stable state of the subtidal ecosystem from which kelp in an area cannot recover (Filbee-Dexter & Scheibling 2014). 

Figure 2. Screenshots from GoPro videos from 2016 (left) and 2018 (right) at the same kayak sampling station in Port Orford showing the difference between a dense kelp forest and what appears to be an urchin barren. (Source: GEMM Lab).

For example, in 2014, bull kelp canopy cover in northern California was reduced by >90% and has not shown signs of recovery since (Rogers-Bennet & Catton 2019; Figure 3). This massive decline was attributed to two major events: 1) the onset of sea star wasting disease (SSWD) in 2013 and 2) the “warm blob” of 2014-2016. SSWD affected over 20 sea star species along the coast from Mexico to Alaska, with the predatory sunflower sea star, which consumes purple sea urchins, most affected, including population declines of 80-100% along the coast (Harvell et al. 2019). Following this SSWD outbreak, the “warm blob”, which was an extreme marine heatwave in the Pacific Ocean, caused ocean temperatures to spike. These two events allowed purple sea urchin populations to grow unchecked by their predators, and created nutrient-poor and warm water conditions, which limited kelp growth and productivity. Intense grazing on bull kelp by growing urchin populations resulted in the >90% reduction in bull kelp canopy cover and has left behind widespread urchin barrens instead (Rogers-Bennet & Catton 2019). Consequently, there have been ecological and economic impacts on the ecosystem and communities in northern California. Without bull kelp, red abalone and red sea urchin populations starved, leading to a subsequent loss of the recreational red abalone (estimated value of $44 million/year) and commercial red urchin fisheries in northern California (Rogers-Bennet & Catton 2019).

Figure 3. Surface kelp canopy area pre- and post-impact from sites in Sonoma and Mendocino counties, northern California from aerial surveys (2008, 2014-2016). Figure and figure caption taken from Rogers-Bennett & Catton (2019).

As I mentioned earlier, while phase shifts between kelp forests and urchin barrens are common cycles, the intensity of the events described above in northern California are an example of sea urchin barrens potentially becoming a stable state of the subtidal ecosystem (Filbee-Dexter & Scheibling 2014). Given that marine heatwaves are only expected to increase in intensity and frequency in the future (Frölicher et al. 2018), the events documented in northern California may not be an isolated incidence. 

Considering that parts of the Oregon coast, particularly the southern portion, are very similar to northern California biogeographically, and that it was not exempt from the “warm blob”, similar changes in kelp forests may be occurring along our coast. There are many individuals and groups that are actively working on this issue to examine potential impacts to kelp and the species that depend on the services it provides. For more information, check out the Oregon Kelp Alliance

Figure 4. A gray whale surfaces in a large kelp bed during a foraging bout along the Oregon coast. (Source: GEMM Lab).

So, what does all of this information have to do with gray whales? Given their affinity for kelp habitats (Figure 4) and their zooplankton prey that aggregates there, changes to kelp ecosystems may affect gray whale health and ecology. This aspect of the complex kelp trophic web has not been examined to date; thus one of my PhD chapters focuses on the response of gray whales to changing kelp ecosystems along the southern Oregon coast. To do this, I am examining 6 years of data collected during the TOPAZ/JASPER project in Port Orford, to look at the relationships between kelp health, sea urchin density, zooplankton abundance, and gray whale foraging effort over space and time. Documenting impacts of changing kelp forests on gray whales is important to assist management efforts as healthy and abundant kelp seems critical in providing ample food opportunities for these iconic Pacific Northwest marine predators.

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References

Bennett S, et al. The ‘Great Southern Reef’: Social, ecological and economic value of Australia’s neglected kelp forests. Marine and Freshwater Research 67:47-56.

Dayton PK (1985) Ecology of kelp communities. Annual Review of Ecology and Systematics 16:215-245.

Filbee-Dexter K, Scheibling RE (2014) Sea uechin barrens as alternative stable states of collapsed kelp ecosystems. Marine Ecology Progress Series 495:1-25.

Frölicher TL, Fischer EM, Gruber N (2018) Marine heatwaves under global warming. Nature 560:360-364.

Harvell CD, et al. (2019) Disease epidemic and a marine heat wave are associated with the continental-scale collapse of a pivotal predator (Pycnopodia helianthoides). Science Advances 5(1) doi:10.1126/sciadv.aau7042.

Krumhansl KA, et al. (2016) Global patterns of kelp forest change over the past half-century. Proceedings of the National Academy of Sciences of the United States of America 113(48):13785-13790.

Pinnegar JK, et al. (2000) Trophic cascades in benthic marine ecosystems: lessons for fisheries and protected-area management. Environmental Conservation 27:179-200.

Rogers-Bennett L, Catton CA (2019) Marine heat wave and multiple stressors tip bull kelp forest to sea urchin barrens. Scientific Reports 9:15050.

Sala E, Boudouresque CF, Harmelin-Vivien M (1998) Fishing, trophic cascades and the structure of algal assemblages; evaluation of an old but untested paradigm. Oikos 82:425-439.

Steneck RS, et al. (2002) Kelp forest ecosystems: biodiversity, stability, resilience and future. Environmental Conservation 29:436-459.

Tegner MJ, Dayton PK, Edwards PB, Riser KL (1996) Is there evidence for the long-term climatic change in southern California kelp forests? California Cooperative Oceanic Fisheries Investigations Report 37:111-126.

Torres LG, Nieukirk SL, Lemos L, Chandler TE (2018) Drone up! Quantifying whale behavior from a new perspective improves observational capacity. Frontiers in Marine Science doi:10.3389/fmars.2019.00319.

Introducing IndividuWhale!

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

If you are an avid reader of our blog, you probably know quite a bit about gray whales, specifically the Pacific Coast Feeding Group (PCFG) of gray whales. Of the just over 50 GEMM Lab blogs written in 2021, 43% of them were about PCFG gray whales (or at least mentioned gray whales in some way). I guess this statistic is not too surprising when you consider that six of the 10 GEMM Lab members conduct gray whale-related research. You might think that we would have reached our annual limit of online gray whale content with that many blogs featuring these gentle giants, but you would in fact be wrong…

At the end of 2021, we launched a brand new website all about gray whales called IndividuWhale! It features stories of some of the Oregon coast’s most iconic gray whales, as well as information about how we study them, stressors they experience in our waters, and even a game to test your gray whale identification skills. IndividuWhale is a true labor of love that took over a year to create and that we are extremely proud to share with you today. Before I tell you more about the website, I want to take a moment to give a huge shout out to Erik Urdahl who was instrumental in getting this website off the ground and making it as interactive and beautiful as it is – hurrah Erik!

Equal‘s right side with visible boat propeller scars. Source: GEMM Lab.

Like us humans, gray whales have individual personalities and stories. They experience life-altering events, go through periods of stress, must provide for their offspring, and can behave differently to one another. Since Leigh & co. have been conducting in-depth research about PCFG gray whales in Oregon waters since 2016, we have been able to document several fascinating stories and events that these individuals have experienced. Take Equal, for example, a male whale that is at least 7 years old. The GEMM Lab observed Equal on consecutive days in June 2018, where on the first day he looked healthy and normal, but on the second day had fresh boat propeller-like scars on his back. Not only did we document these scars in photographs, but we were also able to collect a fecal sample from Equal the day we observed him with these scars. After analyzing his fecal sample for stress hormones, we discovered that Equal had very high stress levels compared to previous samples collected – unsurprising seeing as he had been hit by a boat! While this event was certainly sad for Equal (although don’t worry – we have seen him many times again in the years after this event looking healthy & normal once again), it was a very fortuitous occurrence for us since we were able to “validate” our stress hormone data relative to the value from Equal when he was clearly stressed out. Find out more about Equal as well as seven other gray whales here!

You might be wondering, how we knew that the whale with the boat propeller scar was Equal and how we recognize him again years after the incident. Gray whales have unique pigmentation patterns on their bodies and flukes that allow us to re-identify individuals between years and distinguish them from one another. Additionally, scars, such as those that Equal now carries on his back, can also be useful in telling whales apart. Therefore, we take photographs of every whale we see to match markings and identify whales. This process is called photo ID. Some individuals can have very distinctive markings, such as Roller Skate who has two big white dots on her right side, while others can look more inconspicuous, like Clouds. Therefore, conducting photo ID requires a lot of attention to detail and perseverance. To learn more about the different features we use to identify individuals, check out the “Studying Whales With Photographs” page. Do you think you have what it takes to tell individuals apart? Then try your luck at our photo ID game after!

Test your photo ID skills in our whale match game!

Unfortunately, these whales do not live in a pristine environment, as is evidenced by Equal’s story. Their main objective during the summer when in Oregon waters is to gain weight (energy stores) by consuming large amounts of prey, which is made more difficult by a number of stressors, including potential fishery entanglements, ocean noise, vessel traffic, and habitat changes. We describe these four stressors on the IndividuWhale website since we are trying to assess the impacts of them on gray whales through our research, however they are certainly not the only stressors that these whales experience. Little is known about the level at which these stressors may have a negative impact on the whales, and how whales react when they experience some of these stressors in concert. The answers to these questions are difficult to tease apart but the GRANITE project is aiming to do so through a framework called Population Consequences of Multiple Stressors (read more about it here). This approach requires a lot of data on a lot of individuals in a population and as you can see from the IndividuWhale website, we are slowly starting to get there! 2022 will certainly bring many more gray whale-themed blogs to this website, and you can share in our journey of learning about the lives of PCFG gray whales by exploring the IndividuWhale website (https://www.individuwhale.com).

How much energy does that mouthful cost?

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

Tagging a whale is no easy feat, nor is it without some impact to the whale – no matter how minimized through the use of non-penetrating suction cup tags. Yet, in August 2021 the GEMM Lab initiated a new phase in our research on gray whales, aimed at obtaining a better understanding of the underwater lives and energetics of a gray whale (Figure 1, top image). We captured some amazing data through these specialized, non-invasive tags that provide a brief window into their world and physiology. The video recordings from the tags showed us whales digging their heads into the benthos generating billowing clouds of sediment, likely exploiting desirable prey patches (Figure 1, middle images). We also saw foraging whales undertake dizzying spins and headstands for hours, demonstrating the fascinating maneuverability and flexibility of gray whales (Figure 1, bottom image). But what is motivating us to capture this information?

The GEMM Lab has researched the ecology and physiology of Pacific Coast Feeding Group (PCFG) gray whales since 2015. Our efforts have filled crucial knowledge gaps to better understand this sub-group of the Eastern North Pacific (ENP) gray whale population. We now know that gray whale body condition increases throughout a foraging season and can fluctuate considerably between years (Soledade Lemos et al. 2020). Additionally, body condition varies significantly by reproductive state, with calves and pregnant females displaying higher body conditions (Soledade Lemos et al. 2020). We have also validated and quantified fecal steroid and thyroid hormone metabolite concentrations, providing us with thresholds to identify a stressed vs. a not stressed whale based on its hormone levels (Lemos et al. 2020). These validations have allowed us to make correlations between poor body condition and the steroid hormone cortisol which confirm that slim whales are stressed, while chubby whales are relaxed (Lemos et al. 2021). These physiological results are particularly salient in the light of our recent findings that PCFG gray whales select prey quality over prey quantity when foraging (Hildebrand et al. in review) and that the caloric content of available prey species in the PCFG range vary significantly (Hildebrand et al. 2021).

While we have addressed several fundamental questions about the PCFG in the last 7 years, answering one question has led to asking 10 more questions – a common pattern in science. Given that we know (1) PCFG whales improve their body condition over the course of the foraging season (Soledade Lemos et al. 2020), (2) PCFG females are able to successfully give birth to and wean calves (Calambokidis & Perez 2017), and (3) certain prey in the PCFG region are of higher caloric value than prey in the ENP Arctic foraging grounds (Hildebrand et al. 2021), a big question that we continue to scratch our heads about is why does the PCFG sub-group have such a small abundance (~250 individuals; Calambokidis et al. 2017) in comparison to the much larger ENP population (~21,000 individuals; Stewart & Weller 2021). Several hypotheses have been suggested including that the energetic costs of feeding may differ between ENP and PCFG whales, with the latter having to expend more energy to obtain prey due to the different foraging behaviors employed (Torres et al. 2018) to obtain diverse prey types, thus justifying the larger abundance of the ENP (Hildebrand et al. 2021). 

Quantifying the energetic cost of baleen whale behaviors is not simple. However, the development of animal-borne tags has allowed scientists to make big strides regarding behavioral cost quantification. The majority of this work has focused on rorqual whales (i.e., blue, humpback, fin whales; e.g., Goldbogen et al. 2013; Cade et al. 2016) as their characteristic lunge-feeding strategy produces a distinct signal in the accelerometer sensors integrated within the tags, making feeding events easier to identify. Gray whales, unlike rorquals, do not lunge-feed. ENP gray whales predominantly feed benthically; diving down to the benthos where they turn onto their side and suction mouthfuls of soft sediment (mud) that contains amphipods that they filter out of the mud (Nerini & Oliver 1983). PCFG whales feed benthically as well, but they also use a number of other feeding behaviors to obtain a variety of prey in a variety of benthic habitats, including headstands, bubble blasts, and sharking (Torres et al. 2018). The above-mentioned gray whale feeding behaviors involve much subtler movements than the powerful, distinctive lunges displayed by rorquals, yet they undoubtedly still incur some energetic cost to the whales. However, exactly how energetically costly the various gray whale feeding behaviors are remains unknown.

One of the three suction cup tags we deployed on gray whales. Dr. Cade printed special “kelp shields” (blue part of the tag) to prevent kelp from potentially getting caught underneath the tag since PCFG whales often forage on reefs with a lot of kelp. This tag includes a video camera (the lens can be seen in the center of the tag) to record video of the whale’s underwater behavior. Source: L. Torres.

This knowledge gap is one of the reasons why the GEMM Lab initiated a new project in close collaboration with Dr. Dave Cade from Stanford University and John Calambokidis from Cascadia Research Collective to quantify and understand the energetics and underwater behavior of gray whales using suction-cup tags. The project was kick-started with a very successful pilot effort the week of August 16th this year. Tags were placed on the backs of three different PCFG gray whales with a long carbon fiber pole and attached to the whales with four suction cups. The tags recorded video, position, accelerometry, and magnetometry data, which we will use to recreate the animal’s movements (pitch, roll), heading, trackline, and environment. Although the weather forecast did not look promising for most of the week, we lucked out with perfect conditions for one day during which we managed to deploy three tags on three different gray whales that are well-known, long-term study animals of the GEMM Lab. The tags stayed on the whales for 1-6 hours and were all recovered (including an adventurous trip up the Alsea River which involved a kayak deployment!). 

Dr. Cade spent the rest of the week teaching GEMM Lab PI Leigh Torres, University of British Columbia Master’s student Kate Colson (who is co-advised by Leigh and Dr. Andrew Trites), and myself the intricacies of data download, processing, and preliminary analysis of the tag data. For her Master’s research, Kate will develop a bioenergetics model for the PCFG sub-group that includes data on foraging energetics (estimated from the tag data) and prey availability in the PCFG foraging range. I plan on using the tag data to assess behavior patterns of PCFG whales relative to habitat as part of my PhD research. All together analysis of the data from these short-term tag deployments will help us get closer to understanding the behavioral choices, habitat needs, and energetic trade-offs of whales living in a rapidly changing ocean. With the success of this pilot effort, we plan to conduct another suction-cup tagging effort next summer to hopefully capture and explore more mysterious underwater behaviors of the PCFG.

An ecstatic team at the end of a very long yet successful day of suction cup tagging. Bottom (from left): Leigh Torres, Lisa Hildebrand, Clara Bird, Dave Cade, KC Bierlich. Top: John Calambokidis.

This project was funded by sales and renewals of the special Oregon whale license plate, which benefits MMI. We gratefully thank all the gray whale license plate holders, who made this research effort possible.

Literature cited

Cade, D. E., Friedlaender, A. S., Calambokidis, J., & Goldbogen, J. A. 2016. Kinematic diversity in rorqual whale feeding mechanisms. Current Biology 26(19):2617-2624. doi:10.1016/j.cub.2016.07.037.

Calambokidis, J., & Perez, A. 2017. Sightings and follow-up of mothers and calves in the PCFG and implications for internal recruitment. IWC Report SC/A17/GW/04 for the Workshop on the Status of North Pacific Gray Whales (La Jolla: IWC). 

Calambokidis, J., Laake, J., & Perez, A. 2017. Updated analysis of abundance and population structure of seasonal gray whales in the Pacific Northwest, 1996-2015. IWC Report SC/A17/GW/05 for the Workshop on the Status of North Pacific Gray Whales (La Jolla: IWC).

Goldbogen, J. A., Friedlaender, A. S., Calambokidis, J., McKenna, M. F., Simon, M., & Nowacek, D. P. 2013. Integrative approaches to the study of baleen whale diving behavior, feeding performance, and foraging ecology. BioScience 63(2):90-100. doi:10.1525/bio.2013.63.2.5.

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. Frontiers in Marine Science 1008. doi:10.3389/fmars.2021.683634.

Lemos, L. S., Olsen, A., Smith, A., Burnett, J. D., Chandler, T. E., Larson, S., Hunt, K. E., & Torres, L. G. 2021. Stressed and slim or relaxed and chubby? A simultaneous assessment of gray whale body condition and hormone variability. Marine Mammal Science. doi:10.111/mms.12877.

Lemos, L.S., Olsen, A., Smith, A., Chandler, T.E., Larson, S., Hunt, K., and L.G. Torres. 2020. Assessment of fecal steroid and thyroid hormone metabolites in eastern North Pacific gray whales. Conservation Physiology 8:coaa110.

Nerini, M. K., & Oliver, J. S. 1983. Gray whales and the structure of the Bering Sea benthos. Oecologia 59:224-225. doi:10.1007/bf00378840.

Soledade Lemos, L., Burnett, J. D., Chandler, T. E., Sumich, J. L., & Torres, L. G. 2020. Intra- and inter-annual variation in gray whale body condition on a foraging ground. Ecosphere 11(4):e03094.

Stewart, J. D., & Weller, D. W. 2021. Abundance of eastern North Pacific gray whales 2019/2020. Department of Commerce, NOAA Technical Memorandum NMFS-SWFSC-639. United States: NOAA. doi:10.25923/bmam-pe91.

Torres, L.G., Nieukirk, S.L., Lemos, L., and T.E. Chandler. 2018. Drone Up! Quantifying Whale Behavior From a New Perspective Improves Observational Capacity. Frontiers in Marine Science: https://doi.org/10.3389/fmars.2018.00319.

 

A little help from my friends to study gray whales in Port Orford

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

The 2021 TOPAZ (Theodolite Overlooking Predators And Zooplankton) field season in Port Orford has come to a close. Its close also signals the end of my tenure as field project lead, after I took over from my predecessor Florence Sullivan (OSU/GEMM Lab MSc grad) in the summer of 2018. Allison Dawn, incoming GEMM Lab Master’s student, is my successor and I am excited to pass the torch to her and see what new directions she will take the project. In today’s post, I will not recap the field season as I often do at the end of August. However, I strongly encourage you to read the blog posts written by the JASPER (Journey for Aspiring Scientists Pursuing Ecological Research) interns that made up Team “Heck Yeah”, Nadia Leal, Damian Amerman-Smith, and Jasen White, as they did an excellent job summarizing what we saw and experienced over the last six weeks. Instead, I want to take this opportunity to highlight a few people in Port Orford (and their most memorable gray whale encounters) who created a home away from home for me in Port Orford and played a large part in creating rich and meaningful experiences during my time as field project lead.

Tom Calvanese. Source: WildHuman.

Up first is Tom Calvanese, the OSU Port Orford Field Station manager. The field station can be an extremely busy place, especially during the summer when ideal weather conditions allow many marine scientists to conduct their research. There can be a lot of comings and goings at the field station, with swift turnarounds between groups and individuals from different departments and projects; some staying just one night, while others (such as the TOPAZ field teams) stay for several weeks. Leigh and I like to call Tom “the man behind the machine” because he manages to keep this busy field station running smoothly. From the get go, Tom has been a solid rock for me in Port Orford and he has never hesitated to give me the time and attention I needed, be it because I was seeking him out for advice about how to handle a personnel issue, a lesson in how to tie strong knots, or just a friendly conversation at the end of a long field day. I know that I have found a life-long friend and colleague in Tom through this project and for this I am very grateful.

One of Tom’s most iconic gray whale encounters happened when he was kayak fishing with a few friends in Tichenor Cove (coincidentally one of the two TOPAZ study sites). The individual kayakers were scattered throughout the cove, all in search of a good spot to hook some rockfish or lingcod. The group had not been out on the water for very long, which likely plays a large part in the shock and surprise that comes next, when Tom suddenly heard the blow of whale. He looked up from his fishing in the direction of the blow, only to see that a gray whale was surfacing right underneath one of his kayak fishing friends. Said friend could do nothing as he sat paralyzed in his kayak which slowly slid off the back of the gray whale as it dove once again. Neither whale nor human was harmed in this encounter, as the whale went back to foraging in the area, and the human (after several minutes of incredulity) went back to fishing. Every year, Tom has warned me of this location where this interaction happened (an uncharacteristically deep spot in Tichenor Cove compared to the rest of the area), though his warning is always accompanied with a twinkle in his eye.

An image captured by 2018’s Team “Whale Storm” aboard the kayak while sampling in Tichenor Cove, Port Orford. Source: GEMM Lab.
Dave Lacey. Source: L Hildebrand.

Dave Lacey owns South Coast Tours (SCT), a tour operating business that offers boat, kayak, and snorkeling tours, as well as surf lessons. Dave has been one of the most generous individuals to the TOPAZ/JASPER projects, never hesitating to loan us wetsuits and/or kayaks and allowing us to use his office and storage areas every day. He has also delivered excellent kayak paddle & safety instruction to the field teams over the last two years. Dave has truly become a vital partner during the Port Orford field seasons. It has been such a pleasure to be able to learn from and work with him, as well as see his business grow each year. Even though I will not be leading the project in Port Orford anymore, I am excited to continue my working relationship with Dave through obtaining important photo identification and sighting data of gray whales in the area when the GEMM Lab team is not there.

Although SCT is not even 10 years old (though it will be next year in 2022!), Dave has had so many gray whale encounters that he said it was really hard for him to pick just one. However, he ultimately picked the first time that he smelled a gray whale’s breath. It happened during a kayak tour when the group rounded the corner from Tichenor to Nellie’s Cove and a whale suddenly surfaced right in front of everyone, hitting them with the misty cloud of its blow. Up until this moment, Dave had both seen and heard hundreds of whale blows, but had never smelled one. He says, “to hear and see [the blow] is pretty normal but to get the third sense [of smell] is really phenomenal.”. Upon asking what he thinks of the smell, Dave replied that he does not think it is as gross as some people may think and during tours on his boat, the Black Pearl, he now actually tries to (safely) maneuver the boat downwind of the blow so that his clients can get a whiff as well.

The misty cloud emitted by whales when they come to the surface to breathe is referred to as the “blow”. Source: GEMM Lab.
Mike Baran. Source: L Hildebrand.

Mike Baran is a co-owner of Port Orford Sustainable Seafood (POSS) and he also occasionally guides kayak and snorkel tours for SCT. POSS is a community supported fishery that delivers wild, line-caught seafood direct from Port Orford to communities throughout western Oregon. I developed a great friendship with Mike through seeing him on the water a lot as a kayak guide for SCT in my first summer leading the TOPAZ/JASPER projects (2018), as well as seeing him at the field station on most days since POSS’ office and fish-processing facility are located there as well. If you are a keen follower of the GEMM Lab blog, you will know by now that the field season in Port Orford is short, yet very intense and taxing. Therefore, uplifting and sometimes goofy interactions with someone can really turn an upsetting day (potentially due to kayak gear loss or simply exhaustion) into a better one. Mike provided me with a lot of uplifting and goofy interactions and always helped put a smile on my face. 

As a SCT kayak guide, Mike has also had many gray whale encounters, however none are as memorable as the one he had on August 2nd, 2019. Mike describes it as a typical Port Orford day: “windy with lots of whale activity all morning”, though all of the activity had been at a distance (the whale blows were far away). Yet, on the paddle back through Tichenor Cove along the backside of the port jetty, Mike and his tour glimpsed a whale that was headstanding along the jetty rocks. The paddlers slowed down and kept their distance, watching as the gray whale foraged, diving down for 3-4 minutes at a time before resurfacing in almost the same location as it had surfaced in before. Suddenly, the whale surfaced right in the middle of the kayak group, with Mike to its left, a mere meter or so away, and the rest of the group to its right. Despite the fact that the sudden appearance of the whale scared the living daylights out of Mike, he was able to take a picture of the surfacing, which features one of the tour clients in the background with her hands lifted up to her face in total shock. So, thankfully for us the moment is not just eternalized in Mike’s memory but also in photographic form.

The photo of the gray whale that surfaced right next to Mike’s kayak, which also captured the shock & surprise of one of the tour clients in the background. Source: South Coast Tours.
Tara Ramsey. Source: L Hildebrand.

Last but certainly not least is Tara Ramsey, the coordinator of the Redfish Rocks Community Team since the summer of 2020. Despite arriving to Port Orford and her job in the middle of a pandemic, Tara has developed a lot of exciting new outreach and education material for the Redfish Rocks Marine Reserve, including an excellent walking tour of Port Orford (if you are ever there, I cannot recommend it highly enough – it starts at the Visitor Center!). While I have not known Tara as long as the other individuals featured in this blog, she has become a really great friend of mine, teaching me a lot about the reserve and Port Orford in general, including the best spot on Battle Rock beach for a small nighttime bonfire. 

Tara’s most memorable encounter with a gray whale is in fact her only encounter with a gray whale to date, and it happened just a few weeks ago when she was doing an Instagram livestream of the Redfish Rocks Marine Reserve aboard SCT’s Black Pearl. The purpose of the livestream was to bring the public into the reserve without having to leave the comfort and current safety of their homes. Tara describes the conditions in the reserve as “quite eerie” that day as there was a combination of smoke, fog, and no wind in the air. These conditions resulted in some pretty poor visibility, but gave the reserve an almost mystical appearance. Tara was actually mid-sentence on the livestream, talking about how special this moment was for her because it was her first time being in the reserve, when a whale surfaced a few meters from the boat. While the encounter was brief (the whale only surfaced 3 or 4 times before disappearing into the fog), Tara says the vision will be etched in her memory forever as Redfish Rocks is “a circle of islands, kind of like an amphitheater and it was amazing to see the whale just in the middle of it all.” 

An aerial view of Redfish Rocks Marine Reserve. Source: FishTracker.

I will miss being the field project lead of the TOPAZ and JASPER projects. I will miss kayaking every other day and spying on gray whales from the cliff site. I will miss having the opportunity to work closely with and train a new crop of aspiring marine scientists. I will miss my daily interactions with Tom, Dave, Mike, Tara, and many more individuals, when I do not go to Port Orford for six weeks next summer. I will cherish all the memories I have amassed over my last four summers in Port Orford for a very long time. Most of all, I will always be grateful to the gray whales that brought me back every summer and who (in a way) made all those memories happen.

PI Leigh Torres and Lisa at the end of the 2021 TOPAZ field season in Port Orford after the annual community presentation with Battle Rock Beach, Humbug Mountain, and Redfish Rocks Marine Reserve in the background. Source: L Torres.