Into the Krillscape: A Remote Expedition in Research and Mentorship

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

What are the most unexpected things you’ve done on Zoom in the last year? Since the pandemic dramatically changed all our lives in 2020, I think we’ve all been surprised by the diversity of things we’ve done remotely. I’ve baked bagels with a friend in Finland, done oceanography labs from my kitchen, had dance parties with people across the country, and conducted an award ceremony for my family’s Thanksgiving scavenger hunt – all on Zoom. Over the last several months, I’ve also mentored an Undergraduate Research, Scholarship, & the Arts (URSA) Engage student, named Amanda. Although we haven’t met in person yet, we’ve been connecting over Zoom since October. 

Amanda is an Ocean Sciences student working with me and Dr. Kim Bernard (CEOAS) to conduct a literature review about the two species of krill found off the coast of Oregon. Thysanoessa spinifera and Euphausia pacifica are an important food source for many of the animals that live off our coast — including blue, humpback, and fin whales. I am trying to learn how krill distributions shape those of humpback and blue whales as part of project OPAL, as well as which oceanographic factors drive krill abundances and distributions.

Thysanoessa spinifera (source: Scripps Institute of Oceanography). 

We’re also interested in T. spinifera and E. pacifica for the crucial roles they serve in ecosystems, beyond providing dinner for whales. Krill do many things that are beneficial to ecosystems and people, termed “ecosystem services.” These include facilitating carbon drawdown from the surface ocean to the deep, supporting lucrative fisheries species like salmon, flatfish, and rockfish, and feeding seabirds like auklets and shearwaters. We want to understand more fully the niche that T. spinifera and E. pacifica each fill off the coast of Oregon, which will help us anticipate how these important animals can be impacted by forces such as global climate change and marine management efforts.

Trying to understand the ecosystem services fulfilled by krill is inherently interdisciplinary, which means we have to learn a lot of new things, making this project a lot of fun. The questions Amanda and I have pursued together have ranged from intensely specific, to surprisingly broad. How many calories do blue whales need to eat in a day? How many krill do salmon need to eat? How big are krill fecal pellets, and how fast do they sink?

Trying to answer these questions has basically amounted to a heroic scouring of the internet’s krillscape by Amanda. She has hunted down papers dating back to the 1960s, pulled together findings from every corner of the world, and pursued what she refers to as “treasure troves” of data. In the process, she has also revealed the holes that exist in the literature, and given us new questions. This is the basis of the scientific process: understanding the current state of knowledge, identifying gaps in that knowledge, and developing the questions and methods needed to fill those gaps.

Euphausia pacifica (source: University of Irvine California, Peter J. Bryant).

Filling in knowledge gaps about T. spinifera and E. pacifica can help us better understand these animals, the ecosystems where they live, and the whales and other animals that depend on them for prey. It’s exciting to know that we will have the opportunity to help fill some of these gaps, as both Amanda and I continue this research over the course of our degrees.

Being able to engage in remote research and mentorship has been really rewarding, and it has shown me how far we’ve all come over the last year. Learning how to work together remotely has been crucial as we have adjusted to the funny new normal of the pandemic. As much as I miss working with people in person, I’ve learned that there’s a lot of great connection to be found even in remote collaboration – I’ve loved meeting Amanda’s pets on Zoom, learning about her career goals, and seeing her incredibly artistic representations of the carbon cycle held up to the camera.

Even though most of our conversations take place on Zoom from our homes, this research still feels plugged into a bigger community. Amanda and I also join Kim’s bigger Zooplankton Ecology Lab meetings, which include two other graduate students and eight undergraduate students, all of whom are working on zooplankton ecology questions that span from the Arctic to the Antarctic. Even though we’ve never met in person, a supportive and curious community has developed among all of us, which I know will persist when we can move back to in-person research and mentorship.

Snacks at the surface: New GEMM Lab publication reveals insights into blue whale surface foraging through drone observations and prey data

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

As the largest animals on the planet, blue whales have massive prey requirements to meet energy demands. Despite their enormity, blue whales feed on a tiny but energy-rich prey source: krill. Furthermore, they are air-breathing mammals searching for aggregations of prey in the expansive and deep ocean, and must therefore budget breath-holding and oxygen consumption, the travel time it takes to reach prey patches at depth, the physiological constraints of diving, and the necessary recuperation time at the surface. Additionally, blue whales employ an energetically demanding foraging strategy known as lunge feeding, which is only efficient if they can locate and target dense prey aggregations that compensate for the energetic costs of diving and lunging. In our recent paper, published today in PeerJ, we examine how blue whales in New Zealand optimize their energy use through preferentially feeding on dense krill aggregations near the water’s surface.

Figure 1. A blue whale lunges on a dense aggregation of krill at the surface. Note the krill jumping away from the mouth of the onrushing whale. UAS piloted by Todd Chandler.
Figure 2. Survey tracklines in 2017 in the South Taranaki Bight (STB) with locations of blue whale sightings, and where surface lunge feeding was observed, denoted. Inset map shows location of the STB within New Zealand. Figure reprinted from Torres et al. 2020.

To understand how predators such as blue whales optimize foraging strategies, knowledge of predator behavior and prey distribution is needed. In 2017, we surveyed for blue whales in New Zealand’s South Taranaki Bight region (STB, Fig. 2) while simultaneously collecting prey distribution data using an echosounder, which allowed us to identify the location, depth, and density of krill aggregations throughout the region. When blue whales were located, we observed their behavior from the research vessel, recorded their dive times, and used an unmanned aerial system (UAS; “drone”) to assess their body condition and behavior.

Much of what is known about blue whale foraging behavior and energetics comes from extensive studies off the coast of California, USA using accelerometer tags to track fine-scale kinematics (i.e., body movements) of the whales. In the California Current, the krill species targeted by blue whales are denser at depth, and therefore blue whales regularly dive to depths of 300 meters to lunge on the most energy-rich prey aggregations. However, given the reduced energetic costs of feeding closer to the surface, optimal foraging theory predicts that blue whales should only forage at depth when the energetic gain outweighs the cost. In New Zealand, we found that blue whales foraged where krill aggregations were relatively shallow and dense compared to the availability of krill across the whole study area (Fig. 3). Their dive times were quite short (~2.5 minutes, compared to ~10 minutes in California), and became even shorter in locations where foraging behavior and surface lunge feeding were observed.

Figure 3. Density contours comparing the depth and density (Sv) of krill aggregations at blue whale foraging sightings (red shading) and in absence of blue whales (gray shading). Density contours: 25% = darkest shade, 755 = medium shade, 95% = light shade. Blue circles indicate krill aggregations detected within 2 km of the sighting of the UAS filmed surface foraging whale analyzed in this study. Figure reprinted from Torres et al. 2020.
Figure 4. Kinematics of a blue whale foraging dive derived from a suction cup tag. Upper panel shows the dive profile (yellow line), with lunges highlighted (green circles), superimposed on a prey field map showing qualitative changes in krill density (white, low; blue, medium; red, high). The lower panels show the detailed kinematics during lunges at depth. Here, the dive profile is shown by a black line. The orange line shows fluking strokes derived from the accelerometer data, the green line represents speed estimated from flow noise, and the grey circles indicate the speed calculated from the vertical velocity of the body divided by the sine of the body pitch angle, which is shown by the red line. Figure and caption reprinted from Goldbogen et al. 2011.

Describing whale foraging behavior and prey in the surface waters has been difficult due to logistical limitations of conventional data collection methods, such as challenges inferring surface behavior from tag data and quantifying echosounder backscatter data in surface waters. To compliment these existing methods and fill the knowledge gap surrounding surface behavior, we highlight the utility of a different technological tool: UAS. By analyzing video footage of a surface lunge feeding sequence, we obtained estimates of the whale’s speed, acceleration, roll angle, and head inclination, producing a figure comparable to what is typically obtained from accelerometer tag data (Fig. 4, Fig. 5). Furthermore, the aerial perspective provided by the UAS provides an unprecedented look at predator-prey interactions between blue whales and krill. As the whale approaches the krill patch, she first observes the patch with her right eye, then turns and lines up her attack angle to engulf almost the entire prey patch through her lunge. Furthermore, we can pinpoint the moment when the krill recognize the impending danger of the oncoming predator—at a distance of 2 meters, and 0.8 seconds before the whale strikes the patch, the krill show a flee response where they leap away from the whale’s mouth (see video, below).

Figure 5. Body kinematics during blue whale surface lunge feeding event derived from Unmanned Aerial Systems (UAS) image analysis. (A) Mean head inclination and roll (with CV in shaded areas), (B) relative speed and acceleration, and (C) distance from the tip of the whale’s rostrum to the nearest edge of krill patch. Blue line on plots indicate when krill first respond to the predation event, and the purple dashed lines indicate strike at time = 0. The orange lines indicate the time at which the whale’s gape is widest, head inclination is maximum, and deceleration is greatest. Figure reprinted from Torres et al. 2020

In this study, we demonstrate that surface waters provide important foraging opportunities and play a key role in the ecology of New Zealand blue whales. The use of UAS technology could be a valuable and complimentary tool to other technological approaches, such as tagging, to gain a comprehensive understanding of foraging behavior in whales.

To see the spectacle of a blue whale surface lunge feeding, we invite you to take a look at the video footage, below:

The publication is led by GEMM Lab Principal Investigator Dr. Leigh Torres. I led the prey data analysis portion of the study, and co-authors include our drone pilot extraordinaire Todd Chandler and UAS analysis guru Dr. Jonathan Burnett. We are grateful to all who assisted with fieldwork and data collection, including Kristin Hodge, Callum Lilley, Mike Ogle, and the crew of the R/V Star Keys (Western Workboats, Ltd.). Funding for this research was provided by The Aotearoa Foundation, The New Zealand Department of Conservation, The Marine Mammal Institute at Oregon State University, Greenpeace New Zealand, OceanCare, Kiwis Against Seabed Mining, The International Fund for Animal Welfare, and The Thorpe Foundation.

Read Oregon State University’s press release about the publication here.

Marine heatwaves and their impact on marine mammals

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

In recent years, anomalously warm ocean temperatures known as “marine heatwaves” have sparked considerable attention and concern around the world. Marine heatwaves (MHW) occur when seawater temperatures rise above a seasonal threshold (greater than the 90th percentile) for five consecutive days or longer (Hobday et al. 2016; Fig. 1). With global ocean temperatures continuing to rise, we are likely to see more frequent and more intense MHW conditions in the future. Indeed, the global prevalence of MHWs is increasing, with a 34% rise in frequency, a 17%  increase in duration, and a 54% increase in annual MHW days globally since 1925 (Oliver et al. 2018). With sustained anomalously warm water temperatures come a range of ecological, sociological, and economic consequences. These impacts include changes in water column structure, primary production, species composition, marine life distribution and health, and fisheries management including closures and quota changes (Oliver et al. 2018).

Figure 1. Illustration of how marine heatwaves are defined. Source:

The notorious “warm blob” was an MHW event that plagued the northeast Pacific Ocean from 2014-2016. Some of the most notable consequences of this MHW were extremely high levels of domoic acid, extreme changes in the biodiversity of pelagic species, and an unprecedented delay in the opening of the Dungeness crab fishery, which is an important and lucrative fishery for the West Coast of the United States (Santora et al. 2020). The “warm blob” directly impacted the California Current ecosystem, which is typically a highly productive coastal area driven by seasonal upwelling. Yet, as a consequence of the 2014-2016 MHW, upwelling habitat was compressed and constricted to the coastal boundary, resulting in a contraction in available habitat for humpback whales and a shift in their prey (Santora et al. 2020; Fig. 2).

Figure 2. A figure from Santora et al. 2020 illustrating the compression in available upwelling habitat, defined by areas with SST<12°C (delineated by the black line), during the 2014-2016 marine heatwave in the California Current ecosystem.

Shifting to an example from another part of the world, the austral summer of 2015-2016 coincided with a strong regional MHW in the Tasman Sea between Australia and New Zealand, which lasted for 251 days and had a maximum intensity of 2.9°C above the climatological average (Oliver et al. 2017). Subsequently, the conditions were linked to a significant shift in zooplankton species composition and abundance in Australia (Evans et al. 2020). Ocean warming, including MHWs, also appears to decrease primary production in the Tasman Sea and large portions of New Zealand’s marine ecosystem (Chiswell & Sutton 2020). In New Zealand’s South Taranaki Bight region, where we study the ecology of blue whales, we observed a shift in blue whale distribution in the MWH conditions of February 2016 relative to more typical ocean conditions in 2014 and 2017 (Fig. 3). The first chapter of my dissertation includes a detailed analysis of the impacts of the 2016 MHW on New Zealand oceanography, krill, and blue whales, documenting how the warm, stratified water column of 2016 led to consequences across multiple trophic levels, from phytoplankton, to zooplankton, to whales.

Figure 3. Maps showing monthly sea surface temperature (SST) in the South Taranaki Bight region of New Zealand during our three years of survey effort to document blue whale distribution (February 2014, 2016, and 2017). Vessel tracklines are shown in black, with blue whale sighting locations shown in dark red. Red circles are scaled by the number of blue whales observed at each sighting. The color ramp of SST values is consistent across the three maps, making the dramatically warmer ocean conditions of 2016 evident.

The response of marine mammals is tightly linked to shifts in their environment and prey (Silber et al. 2017). With MHWs and changing ocean conditions, there will likely be “winners” and “losers” among marine predators including large whales. Blue whales are highly selective krill specialists (Nickels et al. 2019), whereas other species of whales, such as humpback whales, have evolved flexible feeding tactics that allow them to switch target prey species when needed (Cade et al. 2020). In California, humpback whales have been shown to switch their primary prey from krill to fish during warm years (Fossette et al. 2017, Santora et al. 2020). By contrast, blue whales shift their distribution in response to changing krill availability during warm years (Fossette et al. 2017), however this strategy comes with increased risk and energetic cost associated with searching for prey in new areas. Furthermore, in instances when a prey resource such as krill becomes increasingly scarce for a multi-year period (Santora et al. 2020), krill specialist predators such as blue whales are at a considerable disadvantage. It is also important to acknowledge that although the humpbacks in California may at first seem to have a winning strategy for adaptation by switching their food source, this tactic may come with unforeseen consequences. Their distribution overlapped substantially with Dungeness crab fishing gear during MHW conditions in the warm blob years, resulting in record numbers of entanglements that may have population-level repercussions (Santora et al. 2020).

While this is certainly not the most light-hearted blog topic, I believe it is an important one. As warming ocean temperatures contribute to the increase in frequency, intensity, and duration of extreme conditions such as MHW events, it is paramount that we understand their impacts and take informed management actions to mitigate consequences, such as lethal entanglements as a result of compressed whale habitat. But perhaps more importantly, even as we do our best to manage consequences, it is critical that we as individuals realize the role we have to play in reducing the root cause of warming oceans, by being conscious consumers and being mindful of the impact our actions have on the climate. 


Cade DE, Carey N, Domenici P, Potvin J, Goldbogen JA (2020) Predator-informed looming stimulus experiments reveal how large filter feeding whales capture highly maneuverable forage fish. Proc Natl Acad Sci USA.

Chiswell SM, Sutton PJH (2020) Relationships between long-term ocean warming, marine heat waves and primary production in the New Zealand region. New Zeal J Mar Freshw Res.

Evans R, Lea MA, Hindell MA, Swadling KM (2020) Significant shifts in coastal zooplankton populations through the 2015/16 Tasman Sea marine heatwave. Estuar Coast Shelf Sci.

Fossette S, Abrahms B, Hazen EL, Bograd SJ, Zilliacus KM, Calambokidis J, Burrows JA, Goldbogen JA, Harvey JT, Marinovic B, Tershy B, Croll DA (2017) Resource partitioning facilitates coexistence in sympatric cetaceans in the California Current. Ecol Evol.

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Santora JA, Mantua NJ, Schroeder ID, Field JC, Hazen EL, Bograd SJ, Sydeman WJ, Wells BK, Calambokidis J, Saez L, Lawson D, Forney KA (2020) Habitat compression and ecosystem shifts as potential links between marine heatwave and record whale entanglements. Nat Commun.

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More than just whales: The importance of studying an ecosystem


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

I have the privilege of studying the largest animals on the planet: blue whales (Balaenoptera musculus). However, in order to understand the ecology, distribution, and habitat use patterns of these ocean giants, I have dedicated the past several months to studying something much smaller: krill (Nyctiphanes australis). New Zealand’s South Taranaki Bight region (“STB”, Figure 1) is an important foraging ground for a unique population of blue whales [1,2]. A wind-driven upwelling system off of Kahurangi Point (the “X” in Figure 1) generates productivity in the region [3], leading to an abundance of krill [4], the desired blue whale prey [5].

Our blue whale research team collected a multitude of datastreams in three different years, including hydroacoustic data to map krill distribution throughout our study region. The summers of 2014 and 2017 were characterized by what could be considered “typical” conditions: A plume of cold, upwelled water curving its way around Cape Farewell (marked with the star in Figure 1) and entering the South Taranaki Bight, spurring a cascade of productivity in the region. The 2016 season, however, was different. The surface water temperatures were hot, and the whales were not where we expected to find them.

Figure 2. Sea surface temperature maps of the South Taranaki Bight region in each of our three study years. The white circles indicate where most blue whale sightings were made in each year. Note the very warm temperatures in 2016, and more westerly location of blue whale sightings.

What happened to the blue whales’ food source under these different conditions in 2016? Before I share some preliminary findings from my recent analyses, it is important to note that there are many possible ways to measure krill availability. For example, the number of krill aggregations, as well as how deep, thick, and dense those aggregations are in an area will all factor into how “desirable” krill patches are to a blue whale. While there may not be “more” or “less” krill from one year to the next, it may be more or less accessible to a blue whale due to energetic costs of capturing it. Here is a taste of what I’ve found so far:

In 2016, when surface waters were warm, the krill aggregations were significantly deeper than in the “typical” years (ANOVA, F=7.94, p <0.001):

Figute 3. Boxplots comparing the median krill aggregation depth in each of our three survey years.

The number of aggregations was not significantly different between years, but as you can see in the plot below (Figure 4) the krill were distributed differently in space:

Figure 4. Map of the South Taranaki Bight region with the number of aggregations per 4 km^2, standardized by vessel survey effort. The darker colors represent areas with a higher density of krill aggregations. 

While the bulk of the krill aggregations were located north of Cape Farewell under typical conditions (2014 and 2017), in the warm year (2016) the krill were not in this area. Rather, the area with the most aggregations was offshore, in the western portion of our study region. Now, take a look at the same figure, overlaid with our blue whale sighting locations:

Figure 5. Map of standardized number of krill aggregations, overlaid with blue whale sighting locations in red stars.

Where did we find the whales? In each year, most whale encounters were in the locations where the most krill aggregations were found! Not only that, but in 2016 the whales responded to the difference in krill distribution by shifting their distribution patterns so that they were virtually absent north of Cape Farewell, where most sightings were made in the typical years.

The above figures demonstrate the importance of studying an ecosystem. We could puzzle and speculate over why the blue whales were further west in the warm year, but the story that is emerging in the krill data may be a key link in our understanding of how the ecosystem responds to warm conditions. While the focus of my dissertation research is blue whales, they do not live in isolation. It is through understanding the ecosystem-scale story that we can better understand blue whale ecology in the STB. As I continue modeling the relationships between oceanography, krill, and blue whales in warm and typical years, we are beginning to scratch the surface of how blue whales may be responding to their environment.

  1. Torres LG. 2013 Evidence for an unrecognised blue whale foraging ground in New Zealand. New Zeal. J. Mar. Freshw. Res. 47, 235–248. (doi:10.1080/00288330.2013.773919)
  2. Barlow DR et al. 2018 Documentation of a New Zealand blue whale population based on multiple lines of evidence. Endanger. Species Res. 36, 27–40. (doi:
  3. Shirtcliffe TGL, Moore MI, Cole AG, Viner AB, Baldwin R, Chapman B. 1990 Dynamics of the Cape Farewell upwelling plume, New Zealand. New Zeal. J. Mar. Freshw. Res. 24, 555–568. (doi:10.1080/00288330.1990.9516446)
  4. Bradford-Grieve JM, Murdoch RC, Chapman BE. 1993 Composition of macrozooplankton assemblages associated with the formation and decay of pulses within an upwelling plume in greater cook strait, New Zealand. New Zeal. J. Mar. Freshw. Res. 27, 1–22. (doi:10.1080/00288330.1993.9516541)
  5. Gill P. 2002 A blue whale (Balaenoptera musculus) feeding ground in a southern Australian coastal upwelling zone. J. Cetacean Res. Manag. 4, 179–184.

Scratching the Surface

By Dr. Leigh Torres, Assistant Professor, Oregon State University, Geospatial Ecology of Marine Megafauna Lab

I have been reminded of a lesson I learned long ago: Never turn your back on the sea – it’s always changing.

The blue whales weren’t where they were last time. I wrongly assumed oceanographic patterns would be similar to our last time out in 2014 and that the whales would be in the same area. But the ocean is dynamic – ever changing. I knew this. And I know it better now.

Below (Fig. 1) are two satellite images of sea surface temperature (SST) within the South Taranaki Bight and west coast region of New Zealand that we surveyed in Jan-Feb 2014 and again recently during Jan-Feb 2016. The plot on the left describes ocean surface conditions in 2014 and illustrates how SST primarily ranged between 15 and 18 ⁰C. By comparison, the panel on the right depicts the sea surface conditions we just encountered during the 2016 field season, and a huge difference is apparent: this year SST ranged between 18 and 23 ⁰C, barely overlapping with the 2014 field season conditions.

Figure 1. A comparison of satellite images of sea surface temperature (SST) in the South Taranaki Bight region of New Zealand between late January 2014 and early February 2016. The white circles on each image denote where the majority of blue whales were encountered during each field season.
Figure 1. A comparison of satellite images of sea surface temperature (SST) in the South Taranaki Bight region of New Zealand between late January 2014 and early February 2016. The white circles on each image denote where the majority of blue whales were encountered during each field season.

While whales can live in a wide range of water temperatures, their prey is much pickier. Krill, tiny zooplankton that blue whales seek and devour in large quantities, tend to aggregate in pockets of nutrient-rich, cool water in this region of New Zealand. During the 2014 field season, we encountered most blue whales in an area where SST was about 15 ⁰C (within the white circle in the left panel of Fig. 1). This year, there was no cool water anywhere and we mainly found the whales off the west coast of Kahurangi shoals in about 21 ⁰C water (within the white circle in the right panel of Fig. 1. NB: the cooler water in the Cook Strait in the southeast region of the right panel is a different water mass than preferred by blue whales and does not contain their prey.)

The hot water we found this year across the survey region can likely be attributed, at least in part, to the El Niño conditions that are occurring across the Pacific Ocean currently. El Niño has brought unusually settled conditions to New Zealand this summer, which means relatively few high wind events that normally churn up the ocean and mix the cool, nutrient rich deep water with the hot surface layer water. These are ideal conditions for Kiwi sun-bathers, but the ocean remains highly stratified with a stable layer of hot water on top. However, this stratification does not necessarily mean the ocean is un-productive – it only means that the SST satellite images are virtually useless for helping us to find whales this year.

Although SST data can be informative about ocean conditions, it only reflects what is happening in the thin, top slice of the ocean. Sub-surface conditions can be very different. Ocean conditions during our two survey periods in 2014 and 2016 could be more similar when compared underwater than when viewed from above. This is why sub-surface sensors and data collection is critical to marine studies. Ocean conditions in 2014 and 2016 could both potentially provide good habitat for the whales. In fact, where and when we encountered whales during both 2014 and 2016 we also detected high densities of krill through hydro-acoustics (Fig. 2). However, in 2014 we observed many surface swarms of krill that we rarely saw this recent field season, which could be due to elevated SST. But, we did capture cool drone footage this year of a brief sub-surface foraging event:

An overhead look of a blue whale foraging event as the animal approaches the surface. Note how the distended ventral (throat) grooves of the buccal cavity (mouth) are visible. This is a big gulp of prey (krill) and water. The video was captured using a DJI Phantom 3 drone in the South Taranaki Bight of New Zealand in on February 2, 2016 under a research permit from the New Zealand Department of Conservation (DOC) permit # 45780-MAR issued to Oregon State University.

Figure 2. An echo-sounder image of dense krill patches at 50-80 m depth captured through hydroacoustics in the South Taranaki Bight region of New Zealand.
Figure 2. An echo-sounder image of dense krill patches at 50-80 m depth captured through hydroacoustics in the South Taranaki Bight region of New Zealand.

Below are SST anomaly plots of January 2014 and January 2016 (Fig. 3). These anomaly plots show how different the SST was compared to the long-term average SST across the New Zealand region. As you can see, in 2014 (left panel) SST conditions in our study area were ~1 ⁰C below average, while in 2016 (right panel) SST conditions were ~1 ⁰C above average. So, what are normal conditions? What can we expect next year when we come back to survey again for blue whales across this region? These are challenging questions and illustrate why marine ecology studies like this one must be conducted over many years. One year is just a snap shot in the lifetime of the oceans.

Figure 3. Comparison of sea surface temperature (SST) anomaly plots of the New Zealand region between January 2014 (left) and January 2016 (right). The white box in both plots denotes the general location of our blue whale study region. (Apologies for the different formats of these plots - the underlying data is directly comparable.)
Figure 3. Comparison of sea surface temperature (SST) anomaly plots of the New Zealand region between January 2014 (left) and January 2016 (right). The white box in both plots denotes the general location of our blue whale study region. (Apologies for the different formats of these plots – the underlying data is directly comparable.)

Like all marine megafauna, blue whales move far and fast to adjust their distribution patterns according to ocean conditions. So, I can’t tell you what the ocean will be like in January 2017 or where the whales will be, but as we continue to study this marine ecosystem and its inhabitants our understanding of ocean patterns and whale ecology will improve. With every year of new data we will be able to better predict ocean and blue whale distribution patterns, providing managers with the tools they need to protect our marine environment. For now, we are just beginning to scratch the (sea) surface.