Different blue whale populations sing different songs

By Dawn Barlow, PhD Candidate, OSU Department of Fisheries, Wildlife, and Conservation Sciences, Geospatial Ecology of Marine Megafauna Lab

In human cultures, how you sound is often an indicator of where you are from. Have you ever taken a linguistics quiz that tries to guess what part of the United States you grew up in? Questions about whether you pronounce the sugary sweet treat caramel as “carr-mul” or “care-a-mel”, whether you say “soda” or “pop”, or whether a certain type of intersection is called a “roundabout”, “rotary”, or “traffic circle” are used to make a guess at where in the country you were raised. I have spent time in the United States, Australia, and New Zealand, I was amused to learn that the shoes you might wear in summertime can be called flip flops, slippers, thongs, or jandals, depending on which English-speaking country you are in. We know that listening to how someone speaks can tell us about their heritage or culture. As it turns out, the same is true for blue whales. We can learn a lot about blue whales by listening to them.

A blue whale comes up for air in the South Taranaki Bight, New Zealand. We catch only a short glimpse of these ocean giants when they are at the surface. By listening to their vocalizations using acoustic recordings, we can gain a whole new perspective on their lives. Photo by D. Barlow.

Sound is an incredibly important sense to marine mammals, particularly since sound waves can efficiently transmit over long distances in the ocean where other senses, such as vision or smell, are limited. Therefore, passive acoustic monitoring—placing hydrophones underwater to listen for an extended period of time and record the sounds of animals and their environment—is a highly effective tool for studying marine mammals, including blue whales. Throughout the world, blue whales sing. In this case, “song” is defined as a limited number of sound types that are produced in succession to form a recognizable pattern (McDonald et al. 2006). These songs are presumed to be produced by males only, most likely used to maintain associations and mediate social interactions, and seem to play a role in reproduction (Oleson et al. 2007, Lewis et al. 2018). Furthermore, these songs are highly stereotyped, and stable over decadal scales (McDonald et al. 2006).

Figure reproduced from McDonald et al. (2006), illustrating the variation and in blue whale songs from different geographic regions, and their stability over time: Recordings from New Zealand (A), the Central North Pacific (B), Australia (C), the Northeast Pacific (D) and North Indian Ocean (E) illustrate the stable character of the blue whale song over long time periods. All song types for which long time spans of recordings are available show some frequency drift through time, but only minor change in character. These examples were chosen because recordings over a significant time span were available to the authors in raw form, and not because these song types are more stable than the others.

Fascinatingly, blue whale songs have acoustic characteristics that are distinct between geographic regions. A blue whale in the northeast Pacific sings a different song than a blue whale in the north Atlantic; the song heard around Australia is distinct from the one sung off the coast of Chile, and so on. Therefore, differences in blue whale songs between areas can be used as a provisional hypothesis about population structure (McDonald et al. 2006, Samaran et al. 2013, Balcazar et al. 2015). Vocalizations may evolve more rapidly than traditional markers such as genetics or morphology that are often used to delineate populations, particularly in long-lived mammalian species such as blue whales (McDonald et al. 2006).

Figure reproduced from McDonald et al. (2006): Blue whale residence and population divisions suggested from their song types. Arrows indicate the direction of seasonal movements.

Despite the general rule of thumb that population-specific blue whale songs occur in separate geographic regions, there are examples throughout the southern hemisphere where songs from different populations overlap and are recorded in the same location (Samaran et al. 2010, 2013, Tripovich et al. 2015, McCauley et al. 2018, Buchan et al. 2020, Leroy et al. 2021). However, these examples may be instances where the populations temporally or ecologically partition their use of the area. For example, there may be differences in the timing of peak occurrence so that overlap is minimized by alternating which population is predominantly present in different seasons (Leroy et al. 2018). Alternatively, whales from different populations may overlap in space and time, but occupy different ecological niches at the same site. In this case, an area may simultaneously be a migratory corridor for one population and a foraging ground for another (Tripovich et al. 2015).

Figure reproduced from Leroy et al. (2021): Distribution of the five blue whale acoustic populations of the Indian Ocean: the Sri Lankan—NIO (yellow); Madagascan—SWIO (orange); Australian—SEIO (blue); and Arabian Sea—NWIO (red) pygmy blue whales; the hypothesized Chagos pygmy blue whale (green); and the Antarctic blue whale (black dashed line). These distributions have been inferred from the acoustic recordings conducted in the area. The long-term recording sites used to infer these distribution areas are indicated by red stars. Blue whale illustration by Alicia Guerrero.

In the South Taranaki Bight (STB) region of New Zealand, where the GEMM lab has been studying blue whales for the past decade (Torres 2013), the New Zealand song type is recorded year-round (Barlow et al. 2018). New Zealand blue whales rely on a productive upwelling system in the STB that supports an important foraging ground (Barlow et al. 2020, 2021). Antarctic blue whales also seasonally pass through New Zealand waters, likely along their migratory pathway between polar feeding grounds and lower latitude areas (Warren et al. 2021). What does it mean in terms of population connectivity or separation when two different populations occasionally share the same waters? How do these different populations ecologically partition the space they occupy? What drives their differing occurrence patterns? These are the sorts of questions I am diving into as we continue to explore the depths of our acoustic recordings from the STB region. We still have a lot to learn about these blue whales, and there is a lot to be learned through listening.

References:

Balcazar NE, Tripovich JS, Klinck H, Nieukirk SL, Mellinger DK, Dziak RP, Rogers TL (2015) Calls reveal population structure of blue whales across the Southeast Indian Ocean and the Southwest Pacific Ocean. J Mammal 96:1184–1193.

Barlow DR, Bernard KS, Escobar-Flores P, Palacios DM, Torres LG (2020) Links in the trophic chain: Modeling functional relationships between in situ oceanography, krill, and blue whale distribution under different oceanographic regimes. Mar Ecol Prog Ser 642:207–225.

Barlow DR, Klinck H, Ponirakis D, Garvey C, Torres LG (2021) Temporal and spatial lags between wind, coastal upwelling, and blue whale occurrence. Sci Rep 11:1–10.

Barlow DR, Torres LG, Hodge KB, Steel D, Baker CS, Chandler TE, Bott N, Constantine R, Double MC, Gill P, Glasgow D, Hamner RM, Lilley C, Ogle M, Olson PA, Peters C, Stockin KA, Tessaglia-hymes CT, Klinck H (2018) Documentation of a New Zealand blue whale population based on multiple lines of evidence. Endanger Species Res 36:27–40.

Buchan SJ, Balcazar-Cabrera N, Stafford KM (2020) Seasonal acoustic presence of blue, fin, and minke whales off the Juan Fernández Archipelago, Chile (2007–2016). Mar Biodivers 50:1–10.

Leroy EC, Royer JY, Alling A, Maslen B, Rogers TL (2021) Multiple pygmy blue whale acoustic populations in the Indian Ocean: whale song identifies a possible new population. Sci Rep 11:8762.

Leroy EC, Samaran F, Stafford KM, Bonnel J, Royer JY (2018) Broad-scale study of the seasonal and geographic occurrence of blue and fin whales in the Southern Indian Ocean. Endanger Species Res 37:289–300.

Lewis LA, Calambokidis J, Stimpert AK, Fahlbusch J, Friedlaender AS, Mckenna MF, Mesnick SL, Oleson EM, Southall BL, Szesciorka AR, Širović A (2018) Context-dependent variability in blue whale acoustic behaviour. R Soc Open Sci 5.

McCauley RD, Gavrilov AN, Jolli CD, Ward R, Gill PC (2018) Pygmy blue and Antarctic blue whale presence , distribution and population parameters in southern Australia based on passive acoustics. Deep Res Part II 158:154–168.

McDonald MA, Mesnick SL, Hildebrand JA (2006) Biogeographic characterisation of blue whale song worldwide: using song to identify populations. J Cetacean Res Manag 8:55–65.

Oleson EM, Wiggins SM, Hildebrand JA (2007) Temporal separation of blue whale call types on a southern California feeding ground. Anim Behav 74:881–894.

Samaran F, Adam O, Guinet C (2010) Discovery of a mid-latitude sympatric area for two Southern Hemisphere blue whale subspecies. Endanger Species Res 12:157–165.

Samaran F, Stafford KM, Branch TA, Gedamke J, Royer J, Dziak RP, Guinet C (2013) Seasonal and Geographic Variation of Southern Blue Whale Subspecies in the Indian Ocean. PLoS One 8:e71561.

Torres LG (2013) Evidence for an unrecognised blue whale foraging ground in New Zealand. New Zeal J Mar Freshw Res 47:235–248.

Tripovich JS, Klinck H, Nieukirk SL, Adams T, Mellinger DK, Balcazar NE, Klinck K, Hall EJS, Rogers TL (2015) Temporal Segregation of the Australian and Antarctic Blue Whale Call Types (Balaenoptera musculus spp.). J Mammal 96:603–610.

Warren VE, Širović A, McPherson C, Goetz KT, Radford CA, Constantine R (2021) Passive Acoustic Monitoring Reveals Spatio-Temporal Distributions of Antarctic and Pygmy Blue Whales Around Central New Zealand. Front Mar Sci 7:1–14.

Learning to Listen for Animals in the Sea

By Rachel Kaplan, PhD student, Oregon State University College of Earth, Ocean, and Atmospheric Sciences and Department of Fisheries, Wildlife, and Conservation Sciences, Geospatial Ecology of Marine Megafauna Lab

Part of what makes being a graduate student so exciting is the way that learning can flip the world around: you learn a new framework or method, and suddenly everything looks a little different. I am experiencing this fabulous phenomenon lately as I learn to collect and process active acoustic data, which can reveal the distribution and biomass of animals in the ocean – including those favored by foraging whales off of Oregon, like the tiny shrimp-like krill.

Krill, like this Thysanoessa spinifera, play a key role in California Current ecosystems. Photo credit: Scripps Institution of Oceanography.

We know that whales seek out the dense, energy-rich swarms that krill form, and that knowing where to expect krill can give us a leg up in anticipating whale distributions. Project OPAL (Overlap Predictions About Large whales) seeks to model and provide robust predictions of whale distributions off the coast of Oregon, so that managers can make spatially discrete decisions about potential fishery closures, minimizing burdens to fishermen while also maximizing protection of whales. We hope that including prey in our ecosystem models will help this effort, and working on this aim is one of the big tasks of my PhD.

So, how do we know where to expect krill to be off the coast of Oregon? Acoustic tools give us the opportunity to flip the world upside down: we use a tool called an echosounder to eavesdrop on the ocean, yielding visual outputs like the ones below that let us “see” and interpret sound.

Echograms like these reveal features in the ocean that scatter “pings” of sound, and interpreting these signals can show life in the water column.

This is how it works. The echosounder emits pulses of sound at a known frequency, and then it listens for their return after it bounces of the sea floor or things in the water column. Based on sound experiments in the laboratory, we know to expect our krill species, Euphausia pacifica and Thysanoessa spinifera, to return those echoes at a characteristic decibel level. By constantly “pinging” the water column with this sound, we can record a continuous soundscape along the cruise track of a vessel, and analyze it to identify the animals and features recorded.

I had the opportunity to use an echosounder for the first time recently, on the first HALO cruise. We deployed the echosounder soon after sunrise, 65 miles offshore from Newport. After a little fiddling and troubleshooting, I was thrilled to start “listening” to the water; I was able to see the frothy noise at its surface, the contours of the seafloor, and the pixelated patches that indicate prey in between. Although it’s difficult to definitively identify animals only based on the raw output, we saw swarms that looked like our beloved krill, and other aggregations that suggested hake. Sometimes, at the same time that the team of visual observers on the flying bridge of the vessel sighted whales, I also saw potential prey on the echogram.

 I spent much of the HALO cruise monitoring incoming data from the transducer on the SIMRAD EK60. Photo: Marissa Garcia.

I’m excited to keep collecting these data, and grateful that I can also access acoustic data collected by others. Many research vessels use echosounders while they are underway, including the NOAA Ship Bell M. Shimada, which conducts cruises in the Northern California Current several times a year. Starting in 2018, GEMM Lab members have joined these cruises to conduct marine mammal surveys.

This awesome pairing of data types means that we can analyze the prey that was available at the time of marine mammal sightings. I’ve been starting to process acoustic data from past Northern California Current cruises, eavesdropping on the preyscape in places that were jam-packed with whales, such as this echogram from the September 2020 cruise, below.

An echogram from the September 2020 NCC cruise shows a great deal of prey at different depths.

Like a lot of science, listening to animals in the sea comes down to occasional bursts of fieldwork followed by a lot of clicking on a computer screen during data analysis. This analysis can be some pretty fun clicking, though – it’s amazing to watch the echogram unfurl, revealing the preyscape in a swath of ocean. I’m excited to keep clicking, and learn what it can tell us about whale distributions off of Oregon.

Let me introduce you to… dugongs!

By Solène Derville, Postdoc, OSU Department of Fisheries, Wildlife, and Conservation Science, Geospatial Ecology of Marine Megafauna Lab

Today let me take you on a journey into the tropical waters of the Indo-Pacific Ocean, far from Oregon’s beautiful coasts. Although I have been working as a postdoc on the OPAL project for a year, the pandemic has prevented me from moving to the US as planned. Like so many around the globe, I have been working remotely from my study area (Oregon coastal waters), imagining my study species (blue, fin and humpback whales) gently swimming and feeding along the productive California Current system. One day, I’ll get to see these amazing animals for real, that’s for sure.

But in the meantime, I have taken this year as an opportunity to work with the GEMM lab, while continuing to enjoy the marvels of New Caledonia, a French overseas territory where I have lived for more than 6 years now. Among the animals that I get to approach and observe regularly in the coral reef lagoons that surround the island, the dugong (Dugon dugon) is perhaps the most emblematic and intriguing. This marine mammal is listed as vulnerable in the IUCN Red list of threatened species and has been the focus of important research and conservation efforts in New Caledonia over the last two decades1–3. During my previous post-doctoral position at the French Institute of Research for Sustainable Development, I contributed to some recent research involving satellite tracking of dugongs in the region. This work has led to a publication, now in review4, and will be the topic of my oral presentation at the 7th International Bio-Logging Science Symposium hosted in Hawaii in a couple weeks.

While I was analyzing dugong satellite tracks, writing this paper with my colleagues and preparing for the symposium, I learned a lot about these strange “sea cows”. Dugongs belong to the Sirenian marine mammal order, just like manatees (West Indian, Amazonian and West African species), which they are often mistaken for (watch out: Google Images will misleadingly suggest hundreds of manatee pictures if you make a “dugong” keyword search). The physiology and anatomy of dugongs is actually quite different from that of manatees (Figure 1). They also live in a different part of the world as they are broadly distributed in the Indo-Pacific coastal and island waters. Dugongs form separate populations, some of which are very isolated and at high risk of extirpation. They are found in 37 different countries, with Australia being home to the largest populations by far (exceeding 70,000 individuals5).

Figure 1: Manatee vs Dugong, can you tell them apart? Among other things, dugongs and manatees have a very different body shape. As the famous Sirenian specialist Helene Marsh said, a dugong essentially looks like “a manatee that goes to the gym”5! Illustration by S. Derville.

Sea cow or sea elephant?

Through the tree of evolution, the dugong and manatee’s closest relative is not the one you would think… other marine mammals like cetaceans or pinnipeds. Indeed, molecular genetic analyses have placed the Sirenians in the Afrotheria Superorder of mammals. Therefore, it appears that dugongs are more closely related to elephant and golden moles than to whales and dolphins!

As a memory aid to help remember this ancient origin, we may notice that both elephants and dugongs have tusks. Mature male and female dugongs have erupted tusks, although the females’ only erupt rarely and at a very old age. Interestingly, tusks are used by scientists to determine age. Analyses of growth layers in bisected dugong tusks have revealed that dugongs are long-lived, with a maximum longevity record of 73 years (estimated from a female individual found in Western Australia5).

An (almost) vegetarian marine mammal

Dugongs and manatees are the only predominantly herbivorous aquatic mammals. Given that manatees use both marine and fresh water ecosystems they tend to have a broader diet, eating many kinds of submerged, floating or emergent algae and seagrass (even bank growth!). On the other hand, dugongs are a strictly marine species and primarily feed on seagrass, which may look very similar to seaweeds, but are in fact marine flowering plants. Seagrass tend to form underwater shallow meadows that are among the most productive ecosystems in the world6. In fact, dugong grazing influences the biomass, species composition and nutritional quality of seagrass meadows7,8. Just like we take care of our gardens, dugongs regulate seagrass ecosystems. But there is more. Recent research conducted in the Great Barrier Reef indicates that seagrass seeds that have been digested by dugongs germinate at a faster rate9. As well as playing a role in dispersal10, it appears that dugongs are pooping seeds with enhanced germination potential, hence participating to seagrass meadow resilience.

Figure 2: Dugong mother and calf feeding on a dense seagrass bed (a) and solitary adult foraging in a very sparce seagrass bed (b). Seagrass grows in many different types of meadows, which may vary in density, species composition and substrate. For instance, seagrass species of the Halophila genus are among the preferred dugong’s meals although may be very thinly distributed (c). Photo credit: Serge Andréfouët, New Caledonia.

Unlike manatees, dugongs cannot feed over the whole water column and are strictly bottom feeders. They use their deflected snout (Figure 1) to search the seabed for their favorite food (Figure 2). The feeding trails left by dugongs in dense seagrass meadows are easily detectable from above, just like the sediment clouds that they generate when searching muddy bottoms. Although seagrass is undoubtedly the main component of the dugong’s diet, they may incidentally (or not) ingest algae and invertebrates5.

A legendary animal

The etymology for the word Sirenian comes from the mermaids, or “sirens” of the Greek mythology. These aquatic creatures with the upper body of a female human would sing to lure sailors towards the shore… and towards a certain death. The morphology of dugongs and manatees shares some resemblance with mermaids, at least enough for desperate and lonely sailors to think so!

In addition to having a scientific name rooted in legends, dugongs are also important to contemporary human cultures. In tropical islands and coastal communities, marine megafauna species such as dugongs are considered heritage, due to the strong bond that their people have forged with the ocean5. Dugongs may play an important cultural role because they can be part of the socio-symbolic organization of societies, associated with the imaginary world, or simply because they are seen as companions of the sea, which people frequently encounter. For New Caledonia’s indigenous people, the Kanaks, dugongs can be totem to tribes. Like other large marine species (whales, sharks), the dugong is also considered as an embodiment of ancestors11.

Dugongs have been hunted throughout their range since prehistoric times. Archaeological excavations such as those conducted on the island of Akab in the United Arab Emirates12, indicate that dugong hunting played a role in ancient rituals, in addition to providing a large quantity of meat. The cultural value of dugongs is recognized by multiple countries, which have therefore authorized indigenous dugong hunting, sometimes under quotas. For instance, in Australia, dugongs may be legally hunted by Aboriginal and Torres Strait Islander people (Figure 3) under section 211 of the Native Title Act 1993.

In New Caledonia, the dugong has been protected since 1962 and its hunting is only authorized in one province, with a dispensation for traditional Kanak celebrations13. However, in view of the critical situation in which the New Caledonian dugong population finds itself, estimated at around 700 individuals in 2008-201214, no hunting exemptions have been issued since 2004.

Figure 3: “Naath” (dugong hunting platform), hand colored linocut by Torres Strait Islander artist Dennis Nona. The art piece represents traditional dugong hunting where the hunter is guided by the phosphorescent glow the dugong would leave in the water at night.

What future for dugongs?

Despite legislations to forbid dugong meat consumption outside specific traditional permits, poaching persists, in New Caledonia and in many of the “low-income” countries that are home to dugongs. As climate change and demography intensifies risks to food security, scientists and stakeholders fear for dugongs. Moreover, dugongs entirely rely on seagrass ecosystems that are also disappearing at an alarming rate (7% per year6) as a result of coastal development, pollution and overfishing.

Can we preserve dugongs in regions of high climate vulnerability and where people still have low levels of access to basic needs? Can dugongs play the role of “umbrellas” for the conservation of the ecosystem they live in? I do not have the answer to these questions but I certainly believe that people’s well-being and environmental conservation are tightly intertwined. I hope that rising transdisciplinary approaches such as those supported by the “One Health” framework will help reconnect human populations to their environment, and achieve the goal of optimal health for everyone, humans and animals.

References

1.        Garrigue, C., Patenaude, N. & Marsh, H. Distribution and abundance of the dugong in New Caledonia, southwest Pacific. Mar. Mammal Sci. 24, 81–90 (2008).

2.        Cleguer, C., Grech, A., Garrigue, C. & Marsh, H. Spatial mismatch between marine protected areas and dugongs in New Caledonia. Biol. Conserv. 184, 154–162 (2015).

3.        Cleguer, C., Garrigue, C. & Marsh, H. Dugong (Dugong dugon) movements and habitat use in a coral reef lagoonal ecosystem. Endanger. Species Res. 43, 167–181 (2020).

4.        Derville, S., Cleguer, C. & Garrigue, C. Ecoregional and temporal dynamics of dugong habitat use in a complex coral reef lagoon ecosystem. Sci. Rep. (In review)

5.        Marsh, H., O’Shea, T. J. & Reynolds, J. E. I. Ecology and conservation of the Sirenia: dugongs and manatees, Vol 18. (Cambridge University Press, Cambridge, 2011).

6.        Unsworth, R. K. F. & Cullen-Unsworth, L. C. Seagrass meadows. Curr. Biol. 27, R443–R445 (2017).

7.        Aragones, L. V., Lawler, I. R., Foley, W. J. & Marsh, H. Dugong grazing and turtle cropping: Grazing optimization in tropical seagrass systems? Oecologia 149, 635–647 (2006).

8.        Preen, A. Impacts of dugong foraging on seagrass habitats: observational and experimental evidence for cultivation grazing. Mar. Ecol. Prog. Ser. 124, 201–213 (1995).

9.        Tol, S. J., Jarvis, J. C., York, P. H., Congdon, B. C. & Coles, R. G. Mutualistic relationships in marine angiosperms: Enhanced germination of seeds by mega-herbivores. Biotropica (2021) doi:10.1111/btp.13001.

10.      Tol, S. J. et al. Long distance biotic dispersal of tropical seagrass seeds by marine mega-herbivores. Sci. Rep. 7, 1–8 (2017).

11.      Dupont, A. Évaluation de la place du dugong dans la société néo-calédonienne. (Mémoire Master. Encadré par L. Gardes (Agence des Aires Marines Protégées) et C. Sabinot (IRD), 2015).

12.      Méry, S., Charpentier, V., Auxiette, G. & Pelle, E. A dugong bone mound: The Neolithic ritual site on Akab in Umm al-Quwain, United Arab Emirates. Antiquity 83, 696–708 (2009).

13.      Leblic, I. Vivre de la mer, vivre de la terre… en pays kanak. Savoirs et techniques des pêcheurs kanak du sud de la Nouvelle-Calédonie. (Société des Océanistes, 2008).

14.      Hagihara, R. et al. Compensating for geographic variation in detection probability with water depth improves abundance estimates of coastal marine megafauna. PLoS One 13, e0191476 (2018).

Where will the whales be? Ecological forecast models present new tools for conservation

By Dawn Barlow, PhD Candidate, OSU Department of Fisheries, Wildlife and Conservation Sciences, Geospatial Ecology of Marine Megafauna Lab

Dynamic forecast models predict environmental conditions and blue whale distribution up to three weeks into the future, with applications for spatial management. Founded on a robust understanding of ecological links and lags, a recent study by Barlow & Torres presents new tools for proactive conservation.

The ocean is dynamic. Resources are patchy, and animals move in response to the shifting and fluid marine environment. Therefore, protected areas bounded by rigid lines may not always be the most effective way to conserve marine biodiversity. If the animals we wish to protect are not within protected area boundaries, then ocean users pay a price without the conservation benefit. Management that is adaptive to current conditions may more effectively match the dynamic nature of the species and places of concern, but this approach is only feasible if we have the relevant ecological knowledge to implement it.

The South Taranaki Bight region of New Zealand is home to a foraging ground for a unique population of blue whales that are genetically distinct and present year-round. The area also sustains New Zealand’s most industrial marine region, including active petroleum exploration and extraction, and vessel traffic between ports.

To minimize overlap between blue whale habitat and human use of the area, we develop and test forecasts of oceanographic conditions and blue whale habitat. These tools enable managers to make decisions with up to three weeks lead time in order to minimize potential overlap between blue whales and other ocean users.

Overlap between blue whale habitat and industry presence in the South Taranaki Bight region. A blue whale surfaces in front of a floating production storage and offloading (FPSO) vessel, servicing the oil rigs in the area. Photo by Dawn Barlow.

Predicting the future

Knowing where animals were yesterday may not create effective management boundaries for tomorrow. Like the weather, our expectation of when and where to find species may be based on long-term averages of previous patterns, real-time descriptions based on recent data, and forecasts that predict the future using current conditions. Forecasts allow us to plan ahead and make informed decisions needed to produce effective management strategies for dynamic systems.

Just as weather forecasts help us make decisions about whether to wear a raincoat or pack sunscreen before leaving the house, ecological forecasts can enable managers to anticipate environmental conditions and species distribution patterns in advance of industrial activity that may pose risk in certain scenarios.

In our recent study, we develop and test models that do just that: forecast where blue whales are most likely to be, allowing informed decision making with up to three weeks lead time.

Harnessing accessible data for an applicable tool

We use readily accessible data gathered by satellites and shore-based weather stations and made publicly available online. While our understanding of the ecosystem dynamics in the South Taranaki Bight is founded on years of collecting data at-sea and ecological analyses, using remotely gathered data for our forecasting tool is critical for making this approach operational, sustainable, and useful both now and into the future.

Measurements of conditions such as wind speed and ocean temperature anomaly are paired with known measurements of the lag times between wind input, upwelling, productivity, and blue whale foraging opportunities to produce forecasted environmental conditions.

Example environmental forecast maps, illustrating the predicted sea surface temperature and productivity in the South Taranaki Bight region, which can be forecasted by the models with up to three weeks lead time.

The forecasted environmental layers are then implemented in species distribution models to predict suitable blue whale habitat in the region, generating a blue whale forecast map. This map can be used to evaluate overlap between blue whale habitat and human uses, guiding management decisions regarding potential threats to the whales.

Example forecast of suitable blue whale habitat, with areas of higher probability of blue whale occurrence shown by the warmer colors and the area classified as “suitable habitat” denoted by the white boundaries. This habitat suitability map can be produced for any day in the past 10 years or for any day up to three weeks in the future.

Dynamic ecosystems, dynamic management

These forecasts of whale distribution can be effectively applied for dynamic spatial management because our models are founded on carefully measured links and lags between physical forcing (e.g., wind drives cold water upwelling) and biological responses (e.g., krill aggregations create feeding opportunities for blue whales). The models produce outputs that are dynamic and update as conditions change, matching the dynamic nature of the ecosystem.

A blue whale raises its majestic fluke on a deep foraging dive in the South Taranaki Bight. Photo by Leigh Torres.

Engagement with stakeholders—including managers, scientists, industry representatives, and environmental organizations—has been critical through the creation and implementation of this forecasting tool, which is currently in development as a user-friendly desktop application.

Our forecast tool provides managers with lead time for decision making and allows flexibility based on management objectives. Through trial, error, success, and feedback, these tools will continue to improve as new knowledge and feedback are received.

The people behind the science, from data collection to conservation application. Left: Dawn Barlow and Dr. Leigh Torres aboard a research vessel in New Zealand in 2017, collecting data on blue whale distribution patterns that contributed to the findings in this study. Right: Dr. Leigh Torres and Dawn Barlow at the Parliament buildings in Wellington, New Zealand, where they discussed research findings with politicians and managers, gathered feedback on barriers to implementation, and subsequently incorporated feedback into the development and implementation of the forecasting tools.

Reference: Barlow, D. R., & Torres, L. G. (2021). Planning ahead: Dynamic models forecast blue whale distribution with applications for spatial management. Journal of Applied Ecology, 00, 1–12. https://doi.org/10.1111/1365-2664.13992

This post was written for The Applied Ecologist Blog and the Geospatial Ecology of Marine Megafauna Lab Blog

Supporting marine life conservation as an outsider: Blue whales and earthquakes

By Mateo Estrada Jorge, Oregon State University undergraduate student, GEMM Lab REU Intern

Introduction

My name is Mateo Estrada and this past summer I had the pleasure of working with Dawn Barlow and Dr. Leigh Torres as a National Science Foundation (NSF) Research Experience for Undergraduates (REU) intern. I had the chance to proactively learn about the scientific method in the marine sciences by studying the acoustic behaviors of pygmy blue whales (Balaenoptera musculus brevicauda) that are documented residents of the South Taranaki Bight region in New Zealand (Torres 2013, Barlow et al. 2018). I’ve been interested in conducting scientific research since I began my undergraduate education at Oregon State University in 2015. Having the opportunity to apply the skills I gained through my education in this REU has been a blessing. I’m a physics and computer science major, but more than anything I’m a scientist and my passion has taken me in new, unexpected directions that I’m going to share in this blog post. My message for any students who feel like they haven’t found their path yet is: hang in there, sometimes it takes time for things to take shape. That has been my experience and I’m sure it’s been the experience of many people interested in the sciences. I’m a Physics and Computer Science student, so why am I studying blue whales, and more specifically, how can I be doing marine science research having only taken intro to biology 101?

My background

I decided to apply for the REU in the Spring 2021 because it was a chance to use my programming skills in the marine sciences. I’m also passionate about conservation and protecting the environment in a pragmatic way, so I decided to find a niche where I could put my technical skills to good use. Finally, I wanted to explore a scientific field outside of my area of expertise to grow as a student and to learn from other researchers. I was mostly inspired by anecdotal tales of Physicist Richard Feynman who would venture out of the physics department at Caltech and into other departments to learn about what other scientists were investigating to inspire his own work. This summer, I ventured into the world of marine science, and what I found in my project was fascinating.

Whale watching tour

Figure 1. Me standing on a boat on the Pacific Ocean off Long Beach, CA.

To get into the research mode, I decided to go on a whale watching tour with the Aquarium of the Pacific. The tour was two hours long and the sunburn was worth it because we got to see four blue whales off the Long Beach coast in California. I got to see the famous blue whale blow and their splashes. It was the first time I was on a big boat in the ocean, so naturally I got seasick (Fig 1). But it was exciting to get a chance to see blue whales in action (luckily, I didn’t actually hurl). The marine biologist onboard also gave a quick lecture on the relative size of blue whales and some of their behaviors. She also pointed out that they don’t use Sonar to locate whales as this has been shown to disturb their calling behaviors. Instead, we looked for a blow and splashing. The tour was a wonderful experience and I’m glad I got to see some whales out in nature. This experience also served as a reminder of the beauty of marine life and the responsibility I feel for trying to understand and help conserving it.

Context of blue whale calling

Sound plays a significant role in the marine environment and is a critical mode of communication for many marine animals including baleen whales. Blue whales produce different vocalizations, otherwise known as calls.  Blue whale song is theorized to be produced by males of the species as a form of reproductive behavior, similar to how male peacocks engage females by displaying their elongated upper tail covert feathers in iridescent colors as a courtship mechanism. Then there are “D calls” that are associated with social mechanisms while foraging, and these calls are made by both female and male blue whales (Lewis et al. 2018) (Fig. 2).

Figure 2. Spectrogram of Pygmy blue whale D calls manually (and automatically) selected, frequency 0-150 Hz.

Understanding research on blue whales

The most difficult part about coming into a project as an outsider is catching up. I learned how anthropogenetic (human made) noise affects blue whale communication. For example, it has been showing that Mid Frequency Active Sonar signals employed by the U.S. Navy affect blue whale D calling patterns (Melcón 2012). Furthermore, noise from seismic airguns used for oil and gas exploration has also impact blue whale calling behavior (Di Lorio, 2010). Understanding the environmental context in which the pygmy blue whales live and the anthropogenic pressures they face is essential in marine conservation. Protecting the areas in which they live is important so they can feed, reproduce and thrive effectively. What began as a slowly falling snowflake at the start of a snowstorm turned into a cascading avalanche of knowledge pouring into my mind in just two weeks.

Figure 3. The white stars show the hydrophone locations (n = 5). A bathymetric scale of the depth is also given.

The research question I set out to tackle in my internship was: do blue whales change their calling behavior in response to natural noise events from earthquake activity? To do this, I used acoustic recordings from five hydrophones deployed in the South Taranaki Bight (Fig. 3), paired with an existing dataset of all recorded earthquakes in New Zealand (GeoNet). I identified known earthquakes in our acoustic recordings, and then examined the blue whale D calls during 4 hours before and after each earthquake event to look for any change in the number of calls, call energy, entropy, or bandwidth.

A great mentor and lab team

The days kept passing and blending into each other, as they often do with remote work. I began to feel isolated from the people I was working with and the blue whales I was studying. The zoom calls, group chats, and working alongside other remote interns kept me afloat as I adapted to a work world fully online. Nevertheless, I was happy to continue working on this project because I felt like I was slowly becoming part of the GEMM Lab. I would meet with my mentor Dawn Barlow at least once a week and we would spend time talking about the project and sorting out the difficult details of data processing. She always encouraged my curiosity to ask questions. Even if they were silly questions, she was happy to ponder them because she is a curious scientist like myself.

What we learned

Pygmy blue whales from the South Taranaki Bight region do not change their acoustic behavior in response to earthquake activity. The energy of the earthquake, magnitude, depth, and distance to the origin all had no influence on the number of blue whale D calls, the energy of their calling, the entropy, and the bandwidth. A likely reason for why the blue whales would have no acoustic response to earthquakes (magnitude < 5) is that the STB region is a seismically active region due to the nearby interface of the Australian and Pacific plates. Because of the plate tectonics, the region averages about 20,000 recorded earthquakes per year (GeoNet: Earthquake Statistics). Given that pygmy blue whales are present in the STB region year-round (Barlow et al. 2018), the blue whales may have adapted to tolerate the earthquake activity (Fig 4).

Figure 4. Earthquake signal from MARU (1, 2, 3, 4, 5) and blue whale D calls, Frequency 0-150 Hz.

Looking at the future

I presented my work at the end of my REU internship program, which was a difficult challenge for me because I am often intimidated by public speaking (who isn’t?). Communicating science has always been a big interest of me. I love reading news articles about new breakthroughs and being a small part of that is a huge privilege for me. Finding my own voice and having new insights to contribute to the scientific world has always been my main objective. Now I will get to deliver a poster presentation of my REU work at the Association for the Sciences of Limnology and Oceanography (ASLO) Conference in March 2022. I am both excited and nervous to take on this new adventure of meeting seasoned professionals, communicating my results, and learning about the ocean sciences. I hope to gain new inspirations for my future academic and professional work.

References:

About Earthquake Drums – GeoNet. geonet.Org. Retrieved June 23, 2021, from https://www.geonet.org.nz/about/earthquake/drums

Barlow, D. R., Torres, L. G., Hodge, K. B., Steel, D., Scott Baker, C., Chandler, T. E., Bott, N., Constantine, R., Double, M. C., Gill, P., Glasgow, D., Hamner, R. M., Lilley, C., Ogle, M., Olson, P. A., Peters, C., Stockin, K. A., Tessaglia-Hymes, C. T., & Klinck, H. (2018). Documentation of a New Zealand blue whale population based on multiple lines of evidence. Endangered Species Research, 36, 27–40. https://doi.org/10.3354/esr00891

Di Iorio, L., & Clark, C. W. (2010). Exposure to seismic survey alters blue whale acoustic communication. Biology Letters, 6(3), 334–335. https://doi.org/10.1098/rsbl.2009.0967

Lewis, L. A., Calambokidis, J., Stimpert, A. K., Fahlbusch, J., Friedlaender, A. S., McKenna, M. F., Mesnick, S. L., Oleson, E. M., Southall, B. L., Szesciorka, A. R., & Sirović, A. (2018). Context-dependent variability in blue whale acoustic behaviour. Royal Society Open Science, 5(8). https://doi.org/10.1098/rsos.180241

Melcón, M. L., Cummins, A. J., Kerosky, S. M., Roche, L. K., Wiggins, S. M., & Hildebrand, J. A. (2012). Blue whales respond to anthropogenic noise. PLoS ONE, 7(2), 1–6. https://doi.org/10.1371/journal.pone.0032681

Torres LG. 2013 Evidence for an unrecognised blue whale foraging ground in New Zealand. NZ J. Mar. Freshwater Res. 47, 235–248. (doi:10. 1080/00288330.2013.773919)

The early phases of studying harbor seal pup behavior along the Oregon coast

By Miranda Mayhall, Masters Student, OSU Department of Fisheries, Wildlife, and Conservation Sciences, Geospatial Ecology of Marine Megafauna Lab

Recently, when expected to choose a wildlife species for behavioral observation for one of my Oregon State University graduate courses, I immediately chose harbor seals as my focus. Harbor seals (Fig 1) are an abundant species and in proximity to the Hatfield Marine Science Center (HMSC) (Steingass et al., 2019) where I will be spending much of my time this summer, making logistics easy. Studying pinnipeds (marine mammals with a finned foot, seals, walrus, and sea lions) is appealing due to their undeniably cute physique, floppy nature on land, and super agile nature in the water. I am working to iron out my methods for this study, which I hope to work through in this initial phase of my research project.

Figure 1. Harbor seal hauling out to rest on rocks off Oregon Coast near HMSC.

Behaviors:

At times it can appear that the most interesting harbor seal behaviors occur under water, and the haul out time is simply time for resting. During mating season, most adult seal behaviors take place in the water, such as the incredible vocal acoustics displayed by the males to attract the females (Matthews et al., 2018). However, I hypothesize that young pups can capitalize on haul out time by practicing becoming adults (while the adults are taking that time to rest) and therefore I plan to observe their haul out behaviors in their first summer of life. Specifically, I will document seal pup vocal behavior to evaluate how they are learning to use sound. I am beginning this study in late July, which is just after pupping season (Granquist et al., 2016). This should give me the opportunity to find pups along the Oregon coast near HMSC, so I intend to visit several locations where harbor seals are known to frequently haul out. Knowing that field work and animal behavior is unpredictable, there is no telling what behaviors I will observe on a given day, or if I will see seals at all. Some days I could come home with lots of seal data and great photos, and other days I could come home with little to report. This will be my first hurdle combined with my time limit (strictly completing this observation in the next five weeks). I intend to schedule at least eight hours of field observation at haul-out sites over the next two weeks and will adjust my schedule based on my success in data collection at that point.  

Figure 2. Harbor Seals hauling out on rocks not too far from HMSC.

Timing:

Prior knowledge on harbor seal haul-out sites along the Oregon coast is clearly important for this project’s success, but I must also pay close attention to the tide cycles. During low tides, haul out locations are exposed and occupied by seals. When the tide is high, the seals are less likely to haul-out (Patterson et al., 2008). Furthermore, according to a recent study conducted on harbor seals residing on the Oregon coast, these seals spend on average 71% of their time in the water and will haul-out for the remainder of their time (Steingass et al., 2019). Therefore, it is crucial to maximize my observation time of hauled out pups wisely.

Concerning timing, I also need to observe locations and periods without too many tourists who can get near the haul-out site. As I learned recently, when children show up and start throwing rocks into the water near where harbor seals are swimming, the seals will recede from the area and no longer be available for observation. As an experiment, I waited for the noisy crowds with unchecked children to leave and only myself, my trusty sidekick (my daughter), and one quiet photographer were left on the beach. Once that happened, we noticed more and more seal heads popping up out of the water. Then they came closer and closer to the beach, splashing around doing somersaults visibly on the surface of the water. It was quite a show. I will either need to account for the presence of humans when evaluating seal behavior or assess only periods without disturbance. Seal pups are easily disturbed by humans, so I will keep a non-invasive distance while positioning myself to hear the vocals.

Figure 3. Hauled-out adult harbor seal on the Oregon coast near HMSC. 

Data Collection and Analysis Approach:

The aspect of this project I am still working out is how to quantify pup vocalizations and their associated behaviors. As I mentioned, I will go out each week for eight hours and record each time I notice a pup exhibiting vocal behavior. I will categorize and describe the sound produced by the pup, and document any associated behavior of the pup or behavioral responses from nearby adult seals. Prior research has found that harbor seals are much attuned to vocal behavior. Mother harbor seals learn to quickly distinguish their own pup’s call within a few days of their birth (Sauve et al. 2015). I hypothesize that pups themselves can discern and use vocalizations, and I am excited to watch them develop over the course of my field observations.

Figure 4. Seal pup on the far-left rock, watching the adults as they appear to rest.

References

Granquist, S.M., & Hauksson, E. (2016). Seasonal, meteorological, tidal, and diurnal effects on haul-out patterns of harbour seals (Phoca vitulina) in Iceland. Polar Biology, 39 (12), 2347-2359.

Matthews, L.P., Blades, B., Parks, S. (2018). Female harbor seal (Phoca vitulina) behavioral response to playbacks of underwater male acoustic advertisement displays. PeerJ, 6, e4547.

Patterson, J., Acevedo-Gutierrez, A. (2008). Tidal influence on the haul-out behavior of harbor seals (Phoca vitulina) At all time levels. Northwestern Naturalist, 89 (1), 17-23.

Sauve, C., Beauplet, G., Hammil, M., Charrier, I. (2015). Mother-pup vocal recognition in harbour seals: influence of maternal behavior, pup voice and habitat sound properties. Animal Behavior, 105 (July 2015), 109-120

Steingass, S., Horning, M., Bishop, A. (2019). Space use of Pacific harbor seals (Phoca vitulina richardii) from two haulout locations along the Oregon coast. PloS one. 14 (7), e0219484.

Rorquals of the California Current

By Solène Derville, Postdoc, OSU Department of Fisheries, Wildlife, and Conservation Science, Geospatial Ecology of Marine Megafauna Lab

About 10 months have passed since I started working on OPAL, a project that aims to identify the co-occurrence between whales and fishing effort in Oregon to reduce entanglement risk. During this period, you would be surprised to know how little ecology I have actually done and how much time has been devoted to data processing! I compiled several million GPS trackline positions, processed hundreds of marine mammal observations, wrote several thousand lines of R code, downloaded and extracted a couple Gb of environmental data… before finally reaching the modeling phase of the OPAL project. And with it, finally comes the time to look more closely at the ecology and behavior of my species of interest. While the previous steps of the project were pretty much devoid of ecological reasoning, the literature homework now comes in handy to guide my choices regarding habitat use models, such as  selecting environmental predictors of whale occurrence, deciding on what seasons should be modeled, and choosing the spatio-temporal scale at which the data should be aggregated.

Whale diversity on the US west coast

The productive waters off the US west coast host a great diversity of cetaceans. Eight species of baleen whales are reported to occur there by NOAA fisheries: blue whales, Bryde’s whales, fin whales, gray whales, humpback whales, minke whales, North Pacific right whales and sei whales. Among them, no less than five are listed as Endangered under the Endangered Species Act. Whether they are only passing by or spending months feeding in the region, the timing and location where these animals are observed varies greatly by species and by population.

During the 113 hours of aerial survey effort and 264 hours of boat-based search conducted for the OPAL project, 563 groups of baleen whales have been observed to-date (up to mid-May 2021 to be exact… more data coming soon!). Among the observations where animals could be identified to the species level, humpback whales are preponderant, as they represent about half of the whale groups observed (n = 293). Blue (n = 41) and gray whales (n = 46) come next, the latter being observed in more nearshore waters. Finally, a few fin whale groups were observed (n = 28). The other baleen whale species reported by NOAA in the US west coast species list were very rarely or not observed at all during OPAL surveys.

The OPAL aerial surveys conducted in partnership with the United States Coast Guard (USCG) were specifically designed to study whales occurring on the continental shelf along the coast of Oregon. Hence, most of this survey effort is located in waters from 800 m to 30 m deep, which may explain the relatively low number of gray whales detected. Indeed, gray whales observed in Oregon may either be migrating along the coast to and from their breeding grounds in Baja California, or be part of the small Pacific Coast Feeding Group that forage in Oregon nearshore and shallow waters during the summer. This group of whales is one the main GEMM lab’s research focus, being at the core of no less than three ongoing research projects: AMBER, GRANITE, and TOPAZ.

So today, let’s turn our eyes to the sea horizon and talk about some other members of the baleen whale community: rorquals. Conveniently, the three species of baleen whales (gray whales aside) most commonly observed during OPAL surveys are all part of the rorqual family, a.k.a Balaenopteridae: humpback whales, blue whales and fin whales (Figure 1). They are morphologically characterized by the pleated throat grooves that allow them to engulf large quantities of food and water, for instance when lunge-feeding. Known cases of hybridization between these three species demonstrate their close relatedness (Jefferson et al., 2021)⁠. They all have worldwide distributions and display unequally understood migratory behaviors, seasonally traveling between warm tropical breeding grounds and temperate-polar feeding grounds. They occur in great numbers in productive waters such as the upwelling system of the California Current.

The three accomplices

Figure 1: Aerial view of three rorquals species: a humpback whale (left), a fin whale (center), and a blue whale (right). Photo credit: Leigh Torres and Craig Hayslip. Photos taken off the Oregon coast under NOAA/NMFS permit during USCG helicopter flights conducted as part of the OPAL project

Humpback whales (Megaptera novaeangliae) are easily differentiated from other rorquals because of their long pectoral fins (up to one third of their body length!), which inspired their scientific name, Megaptera, « big-winged » (Figure 1). Individuals observed in Oregon mostly belong to a mix of two Distinct Population Segments (DPS): the threatened Mexico and endangered Central American DPS. Although humpback whales from different DPS do not show any morphological differences, they are genetically distinct because they have been mating separately in distinct breeding grounds for generations and generations. This genetic differentiation has great implications in terms of conservation since the Central American DPS is recovering at a lesser rate than the Mexican and is therefore subject to different management measures (recovery plan, monitoring plan, designated critical habitats). Humpback whales migrate and feed off the US west coast, with a peak in abundance in the mid to late summer. Compared to other rorquals that are found in the open ocean, humpback whales are mostly observed on the continental shelf (Becker et al., 2019)⁠. They are considered to have a relatively generalist diet, as they feed on a mix of krill (Euphausiids) and fishes (e.g. anchovy, sardines) and are capable of switching their feeding behavior depending on relative prey availability (Fleming, Clark, Calambokidis, & Barlow, 2016; Fossette et al., 2017)⁠.

Blue whales (Balaenoptera musculus) are the largest animals ever known (max length 33 m, Jefferson et al., 2008), and sadly the most at risk of global extinction among our three species of interest (listed as « endangered » in the IUCN red list). They have a distinctive mottled blue and light gray skin, a slender body and a broad U-shaped head (or as some say « like a gothic arch », Figure 1). Blue whales tend to be open ocean animals, but they regroup seasonally to feed in highly productive nearshore areas such as the Southern California Bight (Becker et al. 2019, Abrahms et al. 2019). Blue whales migrating or feeding along the US west coast belong to the Eastern North Pacific stock and are subject to great research and conservation efforts. Contrary to their other rorqual counterparts, blue whales are quite picky eaters, as they exclusively feed on krill. This difference in diet leads to resource partitioning facilitating rorqual coexistence in the California Current (Fossette et al., 2017)⁠. These differences in feeding strategies have important implications for designing predictive models of habitat use.

Fin whales (Balaenoptera physalus) are nicknamed « greyhounds of the sea » due to their exceptional swim speed (max 46 km/h). They are a little smaller than blue whales (max length 27 m, Jefferson, Webber, & Pitman, 2008)⁠ but share a similar sleek and streamlined shape. Their coloration is their most distinctive feature: the left lower jaw being mostly dark while the right is white. V-shaped light-gray « chevrons » color their back, behind the head (Figure 1). The California/Oregon/Washington is one of the three stocks recognized in the North Pacific (NOAA Fisheries, 2018)⁠. Within this region, there is genetic evidence for a geographic separation north and south of Point Conception, CA (Archer et al., 2013)⁠. Like other rorquals, they are migratory, but their seasonal distribution is relatively less well understood as they appear to spend a lot of time in open oceans. For instance, a meta-analysis for the North Pacific found little evidence for fin whales using distinct calving areas (Mizroch, Rice, Zwiefelhofer, Waite, & Perryman, 2009)⁠. In the California Current System, satellite tracking has provided great insights into their space-use patterns. In the Southern California Bight, fin whales show year-round residency and seasonal shifts in habitat use as they move further offshore and north during the spring/summer (Scales et al., 2017)⁠. The Northern California Current offshore waters appeared to be used during the summer months by the whales tagged in the Southern California Bight. Yet, fin whales are observed year-round in Oregon (NOAA Fisheries, 2018)⁠.

Towards predictive models of rorqual distribution

Enough observations have now been collected as part of the OPAL project to be able to model the habitat use of some of these rorqual species. Based on 12 topographic (i.e., depth, slope, distance to canyons) and physical variables (temperature, chlorophyll-a, water column stratification, etc.), I have made my first attempt at predicting seasonal distribution patterns of humpback whales and blue whales in Oregon. These models will be improved in the coming months, with more data pouring in and refined parametrizations, but they already bring insights into the shared habitat use patterns of these species, as well as their specificities.

Across multiple cross-validations of the species-specific models, sea surface temperature, sea surface height and depth were recurrently selected among the most important variables influencing both humpback and blue whale distributions. Predicted densities of blue whales were relatively higher at less than 40 fathoms compared to humpback whales, although both species’ hotspots were located outside this newly implemented seasonal fishing limit (Figure 2). Higher densities were generally predicted off Newport and Port Orford, and north of North Bend.

Figure 2: Predicted densities of humpback and blue whales during the month of September 2018, 2019, and 2020 in Oregon waters (OPAL project). Core areas of use (predicted densities in the top 25%) are represented, with darker shades of blue and orange showing higher predicted densities. Dashed lines represent the tracklines followed by USCG monthly aerial surveys. The black line represents the 40 fathom isobath. Grey boxes overlayed on predictions delineate the areas of extrapolation where environmental conditions are non-analogous to the conditions in which the models were trained. Disclaimer: these model outputs are preliminary and should be interpreted with caution.

Once our rorqual models are finalized, we will work with our partners at the Oregon Department of Fisheries and Wildlife to overlay predicted whale hotspots with areas of high crab pot densities. This overlap analysis will help us understand the times and places where co-occurrence of suitable whale habitat and fishing activities put whales at risk of entanglement.

References

Archer, F. I., Morin, P. A., Hancock-Hanser, B. L., Robertson, K. M., Leslie, M. S., Bérubé, M., … Taylor, B. L. (2013). Mitogenomic Phylogenetics of Fin Whales (Balaenoptera physalus spp.): Genetic Evidence for Revision of Subspecies. PLoS ONE, 8(5). https://doi.org/10.1371/journal.pone.0063396

Becker, E. A., Forney, K. A., Redfern, J. V, Barlow, J., Jacox, M. G., Roberts, J. J., & Palacios, D. M. (2019). Predicting cetacean abundance and distribution in a changing climate. Diversity and Distributions, 25(4), 626–643. https://doi.org/10.1111/ddi.12867

Fleming, A. H., Clark, C. T., Calambokidis, J., & Barlow, J. (2016). Humpback whale diets respond to variance in ocean climate and ecosystem conditions in the California Current. Global Change Biology, 22, 1214–1224. https://doi.org/10.1111/gcb.13171

Fossette, S., Abrahms, B., Hazen, E. L., Bograd, S. J., Zilliacus, K. M., Calambokidis, J., … Croll, D. A. (2017). Resource partitioning facilitates coexistence in sympatric cetaceans in the California Current. Ecology and Evolution, 7, 9085–9097. https://doi.org/10.1002/ece3.3409

Jefferson, T. A., Palacios, D. M., Clambokidis, J., Baker, S. C., Hayslip, C. E., Jones, P. A., … Schulman-Janiger, A. (2021). Sightings and Satellite Tracking of a Blue / Fin Whale Hybrid in its Wintering and Summering Ranges in the Eastern North Pacific. Advances in Oceanography & Marine Biology, 2(4), 1–9. https://doi.org/10.33552/AOMB.2021.02.000545

Jefferson, T. A., Webber, M. A., & Pitman, R. L. (2008). Marine Mammals of the World. A comprehensive guide to their identification. Elsevier, London, UK.

Mizroch, S. A., Rice, D. W., Zwiefelhofer, D., Waite, J., & Perryman, W. L. (2009). Distribution and movements of fin whales in the North Pacific Ocean. Mammal Review, 39(3), 193–227. https://doi.org/10.1111/j.1365-2907.2009.00147.x

NOAA Fisheries. (2018). Fin whale stock assessment report ( Balaenoptera physalus physalus ): California / Oregon / Washington Stock.

Scales, K. L., Schorr, G. S., Hazen, E. L., Bograd, S. J., Miller, P. I., Andrews, R. D., … Falcone, E. A. (2017). Should I stay or should I go? Modelling year-round habitat suitability and drivers of residency for fin whales in the California Current. Diversity and Distributions, 23(10), 1204–1215. https://doi.org/10.1111/ddi.12611

Roger that, we are currently enamored

Blog by Rachel Kaplan, PhD student, Oregon State University College of Earth, Ocean, and Atmospheric Sciences and Department of Fisheries, Wildlife, and Conservation Sciences, Geospatial Ecology of Marine Megafauna Lab

Figures by Dawn Barlow, PhD Candidate, OSU Department of Fisheries, Wildlife, and Conservation Sciences, Geospatial Ecology of Marine Megafauna Lab

Hello from the RV Bell M. Shimada! We are currently sampling at an inshore station on the Heceta Head Line, which begins just south of Newport and heads out 45 nautical miles west into the Pacific Ocean. We’ll spend 10 days total at sea, which have so far been full of great weather, long days of observing, and lots of whales.

Dawn and Rachel in matching, many-layered outfits, 125 miles offshore on the flying bridge of the RV Bell M. Shimada.

Run by NOAA, this Northern California Current (NCC) cruise takes place three times per year. It is fabulously interdisciplinary, with teams concurrently conducting research on phytoplankton, zooplankton, seabirds, and more. The GEMM Lab will use the whale survey, krill, and oceanographic data to fuel species distribution models as part of Project OPAL. I’ll be working with this data for my PhD, and it’s great to be getting to know the region, study system, and sampling processes.

I’ve been to sea a number of times and always really enjoyed it, but this is my first time as part of a marine mammal survey. The type and timing of this work is so different from the many other types of oceanographic science that take place on a typical research cruise. While everyone else is scurrying around, deploying instruments and collecting samples at a “station” (a geographic waypoint in the ocean that is sampled repeatedly over time), we – the marine mammal team – are taking a break because we can only survey when the boat is moving. While everyone else is sleeping or relaxing during a long transit between stations, we’re hard at work up on the flying bridge of the ship, scanning the horizon for animals.

Top left: marine mammal survey effort (black lines), and oceanographic sampling stations (red diamonds). Top right: humpback whale sighting locations. Bottom left: fin whale sighting locations. Bottom right: pacific white-sided dolphin sighting locations.

During each “on effort” survey period, Dawn and I cover separate quadrants of ocean, each manning either the port or starboard side. We continuously scan the horizon for signs of whale blows or bodies, alternating between our eyes and binoculars. During long transits, we work in chunks – forty minutes on effort, and twenty minutes off effort. Staring at the sea all day is surprisingly tiring, and so our breaks often involve “going to the eye spa,” which entails pulling a neck gaiter or hat over your eyes and basking in the darkness.  

Dawn has been joining these NCC cruises for the last four years, and her wealth of knowledge has been a great resource as I learn how to survey and identify marine mammals. Beyond learning the telltale signs of separate species, one of the biggest challenges has been learning how to read the sea better, to judge the difference between a frothy whitecap and a whale blow, or a distant dark wavelet and a dorsal fin. Other times, when conditions are amazing and it feels like we’re surrounded by whales, the trick is to try to predict the positions and trajectory of each whale so we don’t double-count them.

Over the last week, all our scanning has been amply rewarded. We’ve seen pods of dolphins play in our wake, and spotted Dall’s porpoises bounding alongside the ship. Here on the Heceta Line, we’ve seen a diversity of pinnipeds, including Northern fur seals, Stellar sea lions, and California sea lions. We’ve been surprised by several groups of fin whales, farther offshore than expected, and traveled alongside a pod of about 12 orcas for several minutes, which is exactly as magical as it sounds.

Killer whales traveling alongside the Bell M. Shimada, putting on a show for the NCC science team and ship crew. Photo by Dawn Barlow.

Notably, we’ve also seen dozens of humpbacks, including along what Dawn termed “the humpback highway” during our transit offshore of southern Oregon. One humpback put on a huge show just 200 meters from the ship, demonstrating fluke slapping behavior for several minutes. We wanted to be sure that everyone onboard could see the spectacle, so we radioed the news to the bridge, where the officers control the ship. They responded with my new favorite radio call ever: “Roger that, we are currently enamored.”

A group of humpbacks traveling along the humpback highway. Photo by Dawn Barlow.
A humpback whale fluke slapping. Photo by Dawn Barlow.

Even with long days and tired eyes, we are still constantly enamored as well. It has been such a rewarding cruise so far, and it’s hard to think of returning back to “real life” next week. For now, we’re wishing you the same things we’re enjoying – great weather, unlimited coffee, and lots of whales!

SpeciesNumber of sightingsTotal number observed
California Sea Lion26
Dall’s Porpoise325
Fin Whale1118
Humpback Whale140218
Killer Whale321
Northern Fur Seal99
Northern Right Whale Dolphin28
Pacific White-sided Dolphin13145
Steller Sea Lion33
Unidentified Baleen Whale104127
Unidentified Dolphin628
Unidentified Whale22

The Road to Oregon

By Imogen Lucciano, incoming graduate student, OSU Department of Fisheries, Wildlife and Conservation Sciences, Geospatial Ecology of Marine Megafauna Lab

There are moments in our individual lifetimes that we can define as noteworthy and right now, as I prepare to start my graduate career within the Marine Mammal Institute (MMI) at OSU, I would say this is it for me. As I sit down to write this blog and document how surreal my future adventure is, I simultaneously feel this path is felicitous. After a year of being cooped up due to COVID, time presently seems to be going by at rocket speed. I am moving constantly in through my day to continue running my current life, while simultaneously arranging all that will encompass my new life. And while I answer questions to my 10-year-old daughter who is doing geometry homework in the living room, while hollering “That is not yours!” to the kitchen where the recently adopted feral dog is sticking his entire head under the trash can lid, while arranging our books in a cardboard box at the packing station I set up on the dining room table, I cannot deny a sense of serenity. This moment in my life, becoming a part of the GEMM Lab and MMI, and relocating to Corvallis is great.

This moment’s noteworthiness is emphasized by embarking on probably the most variable-heavy road trip I have planned to date. Since the age of 19, when I left my small mountain town on the Appalachian trail in Pennsylvania, I have transferred locations ~20 times. Due to extensive travel while serving in the Army (various Army trainings and overseas mission deployments), I have bounced around the US and to other countries often. Over time, one becomes acclimated to the hectic nature of this sort of lifestyle, and yet this new adventure holds significance. 

So here are the details of the adventure trip that lies ahead: I will drive my 2002 Jeep Grand Cherokee across the country; from Charlottesville, Virginia to Corvallis, Oregon. My projected route will extend 2,822 miles and take ~43 driving hours total. The route will fall within the boundaries of 11 states (see Figure 1.)

 Figure 1. Blue Line indicates route from Charlottesville to Corvallis (Google Maps)

Attached to the hitch of the Jeep will be a 6×12 rented cargo trailer containing our treasured books, furniture and things. Inside the Jeep will be three living variables: Mia (the 10-year-old), Angus (hyperactive border collie/ pit bull mix) and Mr. Gibbs (feral pirate dog); all three will need to be closely monitored for potential hiccups in the plan.

If we are going to make it to our destination hotel/Airbnb each night of the trip, I must be organized and calculate road time each day while factoring in breaks to the loo and fueling up. These calculations need to be precise, with little margin for error. I cannot play it too safely either, or it will take us too long to get across the country (I must start my graduate work after all). On the other hand, I cannot realistically expect too many road hours in a day. I think at this point I have got it worked out (Table 1.)

Table 1. Driving Hours and Miles Per Day

When I look back on my career, I had no idea that my not-so-smooth road would lead me to my dream goal of studying marine mammals. I took the Army placement tests at the age of 19, which led me to the field of “information operations” where I earned a great knowledge base in data analysis and encountered fantastic leaders whom I might not have known otherwise. I learned immensely on this path and it set me up very well for moving forward into research and collaboration in the sciences. I am so grateful that my life took this journey because working in the military provided me with the utmost respect for my opportunities and greater empathy for others. This route had many extreme obstacles and was intensely intimidating at times, but I am all the better for it. And I was never able to shake the dream of where I wanted to be (see Figures 2 & 3.) Timing is everything.

Figure 2 & 3. Two of the images of the Pacific coast I have hung up in my house. Keeping my eye on the prize, so to speak. 

It will feel great to cross over the Oregon state line. I cannot wait to meet GEMM Lab in-person and all the other wonderful researchers and staff at MMI and Hatfield Marine Science Center. I am eager to step onto the RV Pacific Storm and begin my thesis research on the magnificent cetaceans off the Oregon coast, and hopefully do some good in the end. As I evaluate the logistics of my trip from Charlottesville to Corvallis, I feel relieved rather than overwhelmed. We could attribute this relief to my not-so-smooth road to get to where I am. Looking ahead, of course, I see a road that will require focus, attention, passion, care, and lots of fuel. Even if this road is not completely smooth, I will have my hands on 10 and 2, and feel so grateful and ready to be on it.

Making predictions: A window into ecological forecast models

By Dawn Barlow, PhD Candidate, OSU Department of Fisheries, Wildlife and Conservation Sciences, Geospatial Ecology of Marine Megafauna Lab

“What is the weather going to be like tomorrow?” “How long will it take to drive there, with traffic?” We all rely on forecasts to make decisions, such as whether to bring a rain jacket, when to get in the car to arrive at a certain destination on time, or any number of situations where we want a prediction of what will happen in the near future. Statistical models underpin many of these examples, using past data to inform future predictions.

Early on in graduate school, I was told that “all models are wrong, but some models work.” Any model is essentially a best approximation, using mathematical relationships, of how we understand a pattern. Models are powerful tools in ecology, enabling us to distill complex, dynamic, and interacting systems into terms and parameters that can be quantified. This ability can help us better understand our study systems and use that understanding to make predictions. We will never be able to describe every nuance of an ecosystem. Instead, the challenge is to collect enough information to build an informed model that can enhance our understanding, without over-simplifying or unnecessarily complicating the system we aim to describe. As Dr. Simon Levin stated in his 1989 seminal paper:

A good model does not attempt to reproduce every detail of the biological system; the system itself suffices for that purpose as the most detailed model of itself. Rather, the objective of a model should be to ask how much detail can be ignored without producing results that contradict specific sets of observations, on particular scales of interest.”1

Species distribution models (SDMs) are the particular branch of models that underpin much of my PhD research on blue whale ecology and distribution in New Zealand. SDMs are mathematical algorithms that correlate observations of a species with environmental conditions at their observed locations to gain ecological insight and predict spatial distributions of the species (Fig. 1)2. The model is a best attempt to quantify and describe the relationships between predictors, e.g., temperature and the observed species distribution pattern. For example, blue whale occurrence is higher in areas of lower temperatures and greater krill availability, and these relationships can be described with models3. So, a model essentially takes all the data available, and synthesizes that information in terms of the relationships between the predictors (environment) and response (species occurrence). Then, we can look at the fitted relationships to ask what we would expect from the species distribution pattern when temperature, or krill availability, or any other predictor, is at a particular value. 

Figure 1. A schematic of a species distribution model (SDM) illustrating how the relationship between mapped species and environmental data (left) is compared to describe “environmental space” (center), and then map predictions from a model using only environmental predictors (right). Note that inter-site distances in geographic space might be quite different from those in environmental space—a and c are close geographically, but not environmentally. The patterning in the predictions reflects the spatial autocorrelation of the environmental predictors. Figure reproduced from Elith and Leathwick (2009).

So, if a model is simply a mathematical description of how terms interact to produce a particular outcome, how do predictions work? To make a spatial prediction, e.g., a map of the probability of a species being present, you need two things: a model describing the functional relationships between species presence and your environmental predictors, and the values of your predictor variables on the day you are interested in predicting to. For example, you may need to obtain a map of sea surface temperature, productivity, temperature anomaly, and surface currents on a day you want to know where whales are expected to be. Your model is the applied across that stack of spatial environmental layers and, based on the functional relationships derived by the model, you get an estimate of the probability of species occurrence based on the temperature, productivity, anomaly, and surface current values at each location. By applying the model over a range of values, you can obtain a continuous surface with the probability of presence, in the form of a map. These maps are typically for the past or present because that is when we can typically acquire spatial environmental layers. However, to make predictions for a future time of interest, we need to have spatial environmental layers for the future.

Forecasts are predictions for the future. Recent advances in technology and computing have led to an emergence of environmental and ecological forecasting tools that are being developed around the world to produce marine forecasts. These tools include predictions of the physical environment such as ocean temperatures or currents, and biological patterns such as where species will be distributed in space and timing of events like salmon spawning or lobster landings4. The ability to generate forecast of marine ecosystems is of particular interest to resource users and managers because it can allow them to be proactive rather than reactive. Forecasts enable us to anticipate events or patterns and prepare, rather than having to respond in real-time or after the fact.

The South Taranaki Bight region in New Zealand is an area where blue whale foraging habitat frequently coincides with industry pressures, including petroleum and mineral extraction, exploration for petroleum reserves using seismic airgun surveys, vessel traffic between ports, and even an ongoing proposal for seabed mining5. Static spatial restrictions to mitigate impacts from these activities on blue whales may be met with resistance from industry user groups, but dynamic spatial management6–8 of blue whale habitat could be more attractive and acceptable. The key for successful dynamic management is knowing where and when to put those boundaries; and this is where ecological forecast models can show their strength. If we can predict suitable blue whale habitat for the future, proactive regulations can be applied to enhance conservation management in the region. Can we develop reliable and useful ecological forecasts for the South Taranaki Bight? Well, given that we have already developed robust models of the relationships between blue whales and their habitat3 and have documented the spatial and temporal lags between wind, upwelling, and blue whales9, we feel confident that we can develop forecast models to predict where blue whales will be in the STB region. As we continue working hard toward this goal, we invite you to check back for our findings in the future. So, consider this blog post a forecast of sorts, and stay tuned!  

Figure 2. A blue whale surfaces in front of an oil extraction platform in the South Taranaki Bight, demonstrating the overlap between whales and industry in the region. Photo by D. Elvines.

References:

1.        Levin, S. A. The problem of pattern and scale. Ecology 73, 1943–1967 (1992).

2.        Elith, J. & Leathwick, J. R. Species Distribution Models: Ecological Explanation and Prediction Across Space and Time. Annu. Rev. Ecol. Evol. Syst. 40, 677–697 (2009).

3.        Barlow, D. R., Bernard, K. S., Escobar-Flores, P., Palacios, D. M. & Torres, L. G. Links in the trophic chain: Modeling functional relationships between in situ oceanography, krill, and blue whale distribution under different oceanographic regimes. Mar. Ecol. Prog. Ser. 642, 207–225 (2020).

4.        Payne, M. R. et al. Lessons from the first generation of marine ecological forecast products. Front. Mar. Sci. 4, 1–15 (2017).

5.        Torres, L. G. Evidence for an unrecognised blue whale foraging ground in New Zealand. New Zeal. J. Mar. Freshw. Res. 47, 235–248 (2013).

6.        Hyrenbach, K. D., Forney, K. A. & Dayton, P. K. Marine protected areas and ocean basin management. Aquat. Conserv. Mar. Freshw. Ecosyst. 10, 437–458 (2000).

7.        Maxwell, S. M. et al. Dynamic ocean management: Defining and conceptualizing real-time management of the ocean. Mar. Policy 58, 42–50 (2015).

8.        Oestreich, W. K., Chapman, M. S. & Crowder, L. B. A comparative analysis of dynamic management in marine and terrestrial systems. Front. Ecol. Environ. 18, 496–504 (2020).

9.        Barlow, D. R., Klinck, H., Ponirakis, D., Garvey, C. & Torres, L. G. Temporal and spatial lags between wind, coastal upwelling, and blue whale occurrence. Sci. Rep. 11, (2021).