Month: June 2019

Zooming in: A closer look at bottlenose dolphin distribution patterns off of San Diego, CA

By: Alexa Kownacki, Ph.D. Student, OSU Department of Fisheries and Wildlife, Geospatial Ecology of Marine Megafauna Lab

Data analysis is often about parsing down data into manageable subsets. My project, which spans 34 years and six study sites along the California coast, requires significant data wrangling before full analysis. As part of a data analysis trial, I first refined my dataset to only the San Diego survey location. I chose this dataset for its standardization and large sample size; the bulk of my sightings, over 4,000 of the 6,136, are from the San Diego survey site where the transect methods were highly standardized. In the next step, I selected explanatory variable datasets that covered the sighting data at similar spatial and temporal resolutions. This small endeavor in analyzing my data was the first big leap into understanding what questions are feasible in terms of variable selection and analysis methods. I developed four major hypotheses for this San Diego site.

The study species: common bottlenose dolphin (Tursiops truncatus) seen along the California coastline in 2015. Image source: Alexa Kownacki.

Hypotheses:

H1: I predict that bottlenose dolphin sightings along the San Diego transect throughout the years 1981-2015 exhibit clustered distribution patterns as a result of the patchy distributions of both the species’ preferred habitats, as well as the social nature of bottlenose dolphins.

H2: I predict there would be higher densities of bottlenose dolphin at higher latitudes spanning 1981-2015 due to prey distributions shifting northward and less human activities in the northerly sections of the transect.

H3: I predict that during warm (positive) El Niño Southern Oscillation (ENSO) months, the dolphin sightings in San Diego would be distributed more northerly, predominantly with prey aggregations historically shifting northward into cooler waters, due to (secondarily) increasing sea surface temperatures.

H4: I predict that along the San Diego coastline, bottlenose dolphin sightings are clustered within two kilometers of the six major lagoons, with no specific preference for any lagoon, because the murky, nutrient-rich waters in the estuarine environments are ideal for prey protection and known for their higher densities of schooling fishes.

Data Description:

The common bottlenose dolphin (Tursiops truncatus) sighting data spans 1981-2015 with a few gap years. Sightings cover all months, but not in all years sampled. The same transect in San Diego was surveyed in a small, rigid-hulled inflatable boat with approximately a two-kilometer observation area (one kilometer surveyed 90 degrees to starboard and port of the bow).

I wanted to see if there were changes in dolphin distribution by latitude and, if so, whether those changes had a relationship to ENSO cycles and/or distances to lagoons. For ENSO data, I used the NOAA database that provides positive, neutral, and negative indices (1, 0, and -1, respectively) by each month of each year. I matched these ENSO data to my month-date information of dolphin sighting data. Distance from each lagoon was calculated for each sighting.

Figure 1. Map representing the San Diego transect, represented with a light blue line inside of a one-kilometer buffered “sighting zone” in pale yellow. The dark pink shapes are dolphin sightings from 1981-2015, although some are stacked on each other and cannot be differentiated. The lagoons, ranging in size, are color-coded. The transect line runs from the breakwaters of Mission Bay, CA to Oceanside Harbor, CA.

Results: 

H1: True, dolphins are clustered and do not have a uniform distribution across this area. Spatial analysis indicated a less than a 1% likelihood that this clustered pattern could be the result of random chance (Fig. 1, z-score = -127.16, p-value < 0.0001). It is well-known that schooling fishes have a patchy distribution, which could influence the clustered distribution of their dolphin predators. In addition, bottlenose dolphins are highly social and although pods change in composition of individuals, the dolphins do usually transit, feed, and socialize in small groups.

Figure 2. Summary from the Average Nearest Neighbor calculation in ArcMap 10.6 displaying that bottlenose dolphin sightings in San Diego are highly clustered. When the z-score, which corresponds to different colors on the graphic above, is strongly negative (< -2.58), in this case dark blue, it indicates clustering. Because the p-value is very small, in this case, much less than 0.01, these results of clustering are strongly significant.

H2: False, dolphins do not occur at higher densities in the higher latitudes of the San Diego study site. The sightings are more clumped towards the lower latitudes overall (p < 2e-16), possibly due to habitat preference. The sightings are closer to beaches with higher human densities and human-related activities near Mission Bay, CA. It should be noted, that just north of the San Diego transect is the Camp Pendleton Marine Base, which conducts frequent military exercises and could deter animals.

Figure 3. Histogram comparing the latitudes with the frequency of dolphin sightings in San Diego, CA. The x-axis represents the latitudinal difference from the most northern part of the transect to each dolphin sighting. Therefore, a small difference would translate to a sighting being in the northern transect areas whereas large differences would translate to sightings being more southerly. This could be read from left to right as most northern to most southern. The y-axis represents the frequency of which those differences are seen, that is, the number of sightings with that amount of latitudinal difference, or essentially location on the transect line. Therefore, you can see there is a peak in the number of sightings towards the southern part of the transect line.

H3: False, during warm (positive) El Niño Southern Oscillation (ENSO) months, the dolphin sightings in San Diego were more southerly. In colder (negative) ENSO months, the dolphins were more northerly. The differences between sighting latitude and ENSO index was significant (p<0.005). Post-hoc analysis indicates that the north-south distribution of dolphin sightings was different during each ENSO state.

Figure 4. Boxplot visualizing distributions of dolphin sightings latitudinal differences and ENSO index, with -1,0, and 1 representing cold, neutral, and warm years, respectively.

H4: True, dolphins are clustered around particular lagoons. Figure 5 illustrates how dolphin sightings nearest to Lagoon 6 (the San Dieguito Lagoon) are always within 0.03 decimal degrees. Because of how these data are formatted, decimal degrees is the easiest way to measure change in distance (in this case, the difference in latitude). In comparison, dolphins at Lagoon 5 (Los Penasquitos Lagoon) are distributed across distances, with the most sightings further from the lagoon.

Figure 5. Bar plot displaying the different distances from dolphin sighting location to the nearest lagoon in San Diego in decimal degrees. Note: Lagoon 4 is south of the study site and therefore was never the nearest lagoon.

I found a significant difference between distance to nearest lagoon in different ENSO index categories (p < 2.55e-9): there is a significant difference in distance to nearest lagoon between neutral and negative values and positive and neutral years. Therefore, I hypothesize that in neutral ENSO months compared to positive and negative ENSO months, prey distributions are changing. This is one possible hypothesis for the significant difference in lagoon preference based on the monthly ENSO index. Using a violin plot (Fig. 6), it appears that Lagoon 5, Los Penasquitos Lagoon, has the widest variation of sighting distances in all ENSO index conditions. In neutral years, Lagoon 0, the Buena Vista Lagoon has multiple sightings, when in positive and negative years it had either no sightings or a single sighting. The Buena Vista Lagoon is the most northerly lagoon, which may indicate that in neutral ENSO months, dolphin pods are more northerly in their distribution.

Figure 6. Violin plot illustrating the distance from lagoons of dolphin sightings under different ENSO conditions. There are three major groups based on ENSO index: “-1” representing cold years, “0” representing neutral years, and “1” representing warm years. On the x-axis are lagoon IDs and on the y-axis is the distance to the nearest lagoon in decimal degrees. The wider the shapes, the more sightings, therefore Lagoon 6 has many sightings within a very small distance compared to Lagoon 5 where sightings are widely dispersed at greater distances.

 

Bottlenose dolphins foraging in a small group along the California coast in 2015. Image source: Alexa Kownacki.

Takeaways to science and management: 

Bottlenose dolphins have a clustered distribution which seems to be related to ENSO monthly indices, and likely, their social structures. From these data, neutral ENSO months appear to have something different happening compared to positive and negative months, that is impacting the sighting distributions of bottlenose dolphins off the San Diego coastline. More research needs to be conducted to determine what is different about neutral months and how this may impact this dolphin population. On a finer scale, the six lagoons in San Diego appear to have a spatial relationship with dolphin sightings. These lagoons may provide critical habitat for bottlenose dolphins and/or for their preferred prey either by protecting the animals or by providing nutrients. Different lagoons may have different spans of impact, that is, some lagoons may have wider outflows that create larger nutrient plumes.

Other than the Marine Mammal Protection Act and small protected zones, there are no safeguards in place for these dolphins, whose population hovers around 500 individuals. Therefore, specific coastal areas surrounding lagoons that are more vulnerable to habitat loss, habitat degradation, and/or are more frequented by dolphins, may want greater protection added at a local, state, or federal level. For example, the Batiquitos and San Dieguito Lagoons already contain some Marine Conservation Areas with No-Take Zones within their reach. The city of San Diego and the state of California need better ways to assess the coastlines in their jurisdictions and how protecting the marine, estuarine, and terrestrial environments near and encompassing the coastlines impacts the greater ecosystem.

This dive into my data was an excellent lesson in spatial scaling with regards to parsing down my data to a single study site and in matching my existing data sets to other data that could help answer my hypotheses. Originally, I underestimated the robustness of my data. At first, I hesitated when considering reducing the dolphin sighting data to only include San Diego because I was concerned that I would not be able to do the statistical analyses. However, these concerns were unfounded. My results are strongly significant and provide great insight into my questions about my data. Now, I can further apply these preliminary results and explore both finer and broader scale resolutions, such as using the more precise ENSO index values and finding ways to compare offshore bottlenose dolphin sighting distributions.

What areas on the landscape do you value? Application of Human Ecology Mapping in Oregon

By: Jackie Delie, M.S. Student, OSU Department of Fisheries and Wildlife, Human Dimensions Lab (Dr. Leigh Torres, committee member providing spatial analysis guidance)

 

Mapping sociocultural data for ecosystem-based planning, like people’s values or cultural land use practices, has gained importance in conservation science, as reflected in the use of terms such as social-ecological systems (Lischka et al. 2018). The emergence of the geospatial revolution – where data have a location associated with it – has changed how scientists analyze, visualize, and scale their perceptions of landscapes and species. However, there is a limited collection of spatial sociocultural data compared to biophysical data.

To address the restricted spatial sociocultural data available, scientists (such as social scientists), community leaders, and indigenous groups have used various mapping methods for decision-making in natural resources planning to capture people’s uses, values, and interaction between people and landscapes. Some mapping methods are termed community values mapping (Raymond et al. 2009), landscape values mapping (Besser et al. 2014), public participation GIS (Brown & Reed 2009), and social values mapping (Sherrouse et al. 2011). Mclain et al. (2013) applies the umbrella term Human Ecology Mapping (HEM) to refer to all these mapping approaches that span across academic disciplines and sub-disciplines. HEM focuses on understanding human-environmental interactions, intending to gather spatial data on aspects of human ecology that can potentially be important to ecosystem-based management and planning. As an early career scientist, I embraced the opportunity to incorporate a HEM approach, more specifically the mapping of landscape values, into my thesis.

My research explores the human-black bear relationship in Oregon. The American black bear (Ursus americanus) is one species identified by the Oregon Department of Fish and Wildlife with a stable or increasing population (25,000 to 35,000 individuals) where many human-black bear interactions occur (ODFW 2012). One component of my research incorporates understanding how recreationists use the landscape and the values they associate with different places. For 18 days in the summer of 2018, I was at various trailheads throughout Oregon, approaching people to request their interest in taking my survey (Image 1 & 2). The consenting participants were asked to identify on the digital map of Oregon the primary places they use or visit on the landscape. Participants had the option to draw a point, line, or polygon to identify up to three places within the state (Image 3). Then, participants were asked to choose the type of activity they prefer at each primary location from a list of 17 recreational activities (e.g., hiking, hunting, fishing, camping, etc.). Finally, they were asked to select one primary value they associate with each identified place from a list of five standardized landscape values (Brown & Reed 2009; Besser et al. 2014). The most important values for my study are aesthetic, economic, intrinsic, subsistence, and social. An example of an aesthetic value statement: “I value this area for its scenic qualities”.

Now that my data is collected, I am creating GIS layers of the various ways recreationists uses the landscape, and the values they assign to those places, showing the distribution of aggregated uses (Image 4) and their relationship to known human-black bear interaction areas. The approach I employed to collect social-spatial data is just one strategy out of many, and it is recognized that maps are never fully objective representations of reality. However, mapping landscape values is a useful tool for identifying and visualizing human-environment relations. The geographically referenced data can be used to map areas of high value (density) or associated with different types of values (diversity). Further, these maps can be overlaid with other biophysical and land use layers to help land managers understand the variety of landscape values and activities.

 

Southern Oregon in August 2018. Lots of fires in the area during this time and that had an impact on where I could collect data as certain forest areas were closed to the public.

 

Me collecting data at Upper Table Rock Trailhead in Southern Oregon

 

Use of an Ipad and the software Mappt to collect socio-spatial data while at trailheads in Oregon. Participants used the digital map to identify up to three places they primarily use the landscape.

 

Preliminary map displaying all the areas of preferred landscape use (orange) marked by survey participants.

 

References:

Besser, D., McLain, R., Cerveny, L., Biedenweg, K. and Banis, D. 2014. Environmental Reviews and Case Studies: Mapping Landscape Values: Issues, Challenges and Lessons Learned from Field Work on the Olympic Peninsula, Washington, Environmental Practice, 16(2): 138–150.

Brown, G., and Reed, P. 2009. Public Participation GIS: A New Method for Use in National Forest Planning. Forest Science, 55(2): 162-182.

Lischka, S., Teel, T., Johnson, H., Reed, S., Breck, S., Don Carlos, A., Crooks, K. 2018. A conceptual model for the integration of social and ecological information to understand human-wildlife interactions. Biological Conservation 225: 80-87.

McLain, R., Poe, M., Biedenweg, K., Cerveny, L., Besser, D., and Blahna, D. 2013. Making sense of human ecology mapping: An overview of approaches to integrating socio-spatial data into environmental planning. Human Ecology, 41(1).

Oregon Department of Fish and Wildlife (ODFW). 2012. Oregon Black Bear Management Plan.

Raymond, M., Bryan, A., MacDonald, H., Cast, A., Strathearn, S., Grandgirard, A., and Kalivas, T. 2009. Mapping Community Values for Natural Capital and Ecosystem Services. Ecological Economics 68: 1301–1315.

Sherrouse, B. C., Clement, J. M., and Semmens, D. J. 2011. A GIS Application for Assessing, Mapping, and Quantifying the Social Values of Ecosystem Services. Applied Geography, 31: 748–760.

Our GEM(M), Ruby, is back in action!

By Lisa Hildebrand, MSc student, OSU Department of Fisheries and Wildlife, Geospatial Ecology of Marine Megafauna Lab

Every season, or significant period of time, usually has a distinct event that marks its beginning. For example, even though winter officially begins when the winter solstice occurs sometime between December 20 and December 23, many people often associate the first snowfall as the real start of winter. To mark the beginning of schooling, when children start 1stgrade in Germany (which is where I’m from), they receive something called a “Zuckertüte”, which translated means “sugar bag”. It is a large (sometimes as large as the child) cone-shaped container made of cardboard filled with toys, chocolates, sweets, school supplies and various other treats topped with a large bow.

Receiving my Zuckertüte in August of 2001 before starting 1st grade. Source: Ines Hildebrand.

I still remember (and even have) mine – it was almost as tall as I was, had a large Barbie printed on it (and a real one sitting on top of it) and was bright pink. And of course, while at a movie theatre, once the lights dim completely and the curtain surrounding the screen opens just a little further, members of the audience stop chit-chatting or sending text messages, everyone quietens down and puts their devices away – the film is about to start. There are hundreds upon thousands of examples like these – moments, events, days that mark the start of something.

In the past, the beginning of summer has always been tied to two things for me: the end of school and the chance to be outside in the sun for many hours and days. This reality has changed slightly since moving to Oregon. While I don’t technically have any classes during the summer, the work definitely won’t stop. There are still dozens of papers to read, samples to run in the lab, and data points to plot. For anyone from Oregon or the Pacific Northwest (PNW), it’s pretty well known that the weather can be a little unpredictable and variable, meaning that summer might not always be filled with sunny days. Despite somewhat losing these two “summer markers”, I have found a new event to mark the beginning of summer – the arrival of the gray whales.

Their propensity for coastal waters and near-shore feeding is part of what makes gray whales so unique and arguably “easier” to study than some other baleen whale species. Image captured under NOAA/NMFS permit #21678. Source: Leigh Torres.

 

It’s official – the gray whale field season is upon us! As many of you may already know, the GEMM Lab has two active gray whale research projects: investigating the impacts of ocean noise on gray whale physiology and exploring potential individual foraging specialization among the Pacific Coast Feeding Group (PCFG) gray whales. Both projects involve field work, with the former operating out of Newport and the latter taking place in Port Orford, both collecting photographs and a variety of samples and tracklines to study the PCFG, which is a sub-group of the larger Eastern North Pacific (ENP) population. June 1st is the widely accepted “cut-off date” for the PCFG whales, whereby gray whales seen after June 1st along the PNW coastline (specifically northern California, Oregon, Washington and British Columbia) are considered members of the PCFG. While this date is not the only qualifying factor for an individual to be considered a PCFG member, it is a good general rule of thumb. Since last week happened to be the first week of June, PI Leigh Torres, field technician Todd Chandler and myself launched out onto the Pacific Ocean in our trusty RHIB Ruby twice looking for gray whales, and it sure was a successful start to the season!

Even though I have done small boat-based field work before, every project and field team operates a little differently, which is why I was a little nervous at first. There are a lot of components to the Newport-based project as Leigh & co. assess gray whale physiology by collecting fecal samples, drone imagery and taking photographs, observing behavior patterns, as well as assessing local prey through GoPro footage and light traps. I wasn’t worried about the prey components of the research, since there is plenty of prey sampling involved in my Port Orford research, however I was worried about the whale side of things. I wasn’t sure whether I would be able to catch the drone as it returned back home to Ruby, fearing I might fumble and let it slip through my fingers. I also experienced slight déjà vu when handling the net we use to collect the fecal samples as I was forced to think back to some previous field work that involved collecting a biopsy dart with a net as well. During that project, I had somehow managed to get the end of the net stuck in the back of the boat and as I tried to scoop up the biopsy dart with the net-end, the pole became more and more stuck while the water kept dragging the net-end down and eventually the pole ended up snapping in my hands. On top of all this anxiety and work, trying to find your footing in a small RHIB like Ruby packed with lots of gear and a good amount of swell doesn’t make any of those tasks any easier.

However, as it turned out, none of my fears came to fruition. As soon as Todd fired up Ruby’s engine and we whizzed out and under the Newport bridge, I felt exhilarated. I love field work and was so excited to be out on the water again. During the two days I was able to observe multiple individuals of a species of whale that I find unique and fascinating.

Markings and pigmentation on the flukes are also unique to individuals and allow us to perform photo identification to track individuals over months and years. Image captured under NOAA/NMFS permit #21678. Source: Leigh Torres.

I felt back in my natural element and working with Leigh and Todd was rewarding and fun, as I have so much to learn from their years of experience and natural talent in the field dealing with stressful situations and juggling multiple components and gear. Even though I wasn’t out there collecting data for my own project, some of my observations did get me thinking about what I hope to focus on in my thesis – individualization. It is always interesting to see how differently whales will behave, whether due to the substrate we find them over, the water depths we find them in, or what their surfacing patterns are like. Although I still have six weeks to go until my field season starts and feel lucky to have the opportunity to help Leigh and Todd with the Newport field work, I am already looking forward to getting down to Port Orford in mid-July and starting the fifth consecutive gray whale field season down there.

But back to Newport – over the course of two days, we were able to deploy and retrieve one light trap to collect zooplankton, collect two fecal samples, perform two GoPro drops, fly the drone three times, and take hundreds of photos of whales. Leigh and Todd were both glad to be reunited with an old friend while I felt lucky to be able to meet such a famous lady – Scarback. A whale with a long sighting history not just for the GEMM Lab but for various researchers along the coast that study this population. Scarback is well-known (and easily identified) by the large concave injury on her back that is covered in whale lice, or cyamids. While there are stories about how Scarback’s wound came to be, it is not known for sure how she was injured. However, what researchers do know is that the wound has not stopped this female from reproducing and successfully raising several calves over her lifetime. After hearing her story from Leigh, I wasn’t surprised that both she and Todd were so thrilled to get both a fecal sample and a drone flight from her early in the season. The two days weren’t all rosy; most of day 1 was shrouded in a cloud of mist resulting in a thin but continuous layer of moisture forming on our clothes, while on day 2 we battled with some pretty big swells (up to 6 feet tall) and in typical Oregon coast style we were victims of a sudden downpour for about 10 minutes. We had some excellent sightings and some not-so-excellent sightings. Sightings where we had four whales surrounding our boat at the same time and sightings where we couldn’t re-locate a whale that had popped up right next to us. It happens.

 

A local celebrity – Scarback. Image captured under NOAA/NMFS permit #21678. Source: Lisa Hildebrand.

 

An ecstatic Lisa with wild hair standing in the bow pulpit of Ruby camera at the ready. Source: Leigh Torres.

Field work is certainly one of my favorite things in the world. The smell of the salt, the rustling of cereal bar wrappers, the whipping of hair, the perpetual rosy noses and cheeks no matter how many times you apply and re-apply sunscreen, the awkward hilarity of clambering onto the back of the boat where the engine is housed to take a potty break, the whooshing sound of a blow, the sometimes gentle and sometimes aggressive rocking of the boat, the realization that you haven’t had water in four hours only to chug half of your water in a few seconds, the waft of peanut butter and jelly sandwiches, the circular footprint where a whale has just gracefully dipped beneath the surface slipping away from view. I don’t think I will ever tire of any of those things.

 

 

Current gray whale die-off: a concern or simply the circle of life?

By Leila Lemos, PhD Candidate in Wildlife Sciences, Fisheries and Wildlife Department / OSU

Examination of a dead gray whale found in Pacifica, California, in May 2019.
Source: CNN 2019.

 

The avalanche of news on gray whale deaths this year is everywhere. And because my PhD thesis focuses on gray whale health, I’ve been asked multiple times now why this is happening. So, I thought it was a current and important theme to explore in our blog. The first question that comes to (my) mind is: is this a sad and unusual event for the gray whales that raises concern, or is this die-off event expected and simply part of the circle of life?

At least 64 gray whales have washed-up on the West Coast of the US this year, including the states of California, Oregon and Washington. According to John Calambokidis, biologist and founder of the Cascadia Research Collective, the washed-up whales had one thing in common: all were in poor body condition, potentially due to starvation (Calambokidis in: Paris 2019). Other than looking skinny, some of the whale carcasses also presented injuries, apparently caused by ship strikes (CNN 2019).

Cascadia Research Collective examining a dead gray whale in 9 May 2019, washed up in Washington state. Cause of death was not immediately apparent but appeared consistent with nutritional stress.
Source: Cascadia Research Collective 2019.

To give some context, gray whales migrate long distances while they fast for long periods. They are known for performing the longest migration ever seen for a mammal, as they travel up to 20,000 km roundtrip every year from their breeding grounds in Baja California, Mexico, to their feeding grounds in the Bering and Chukchi seas (Calambokidis et al. 2002, Jones and Swartz 2002, Sumich 2014). Thus, a successful feeding season is critical for energy replenishment to recover from the previous migration and fasting periods, and for energy storage to support their metabolic needsduring the migration and fasting periods that follow. An unsuccessful feeding season could likely result in poor body condition, affecting individual performance in the following seasons, a phenomenon known as the carry-over effect(Harrison et al., 2011).

In addition, environmental change, such as climate variations, might impact shifts in prey availability and thus intensify energetic demands on the whales as they need to search harder and longer for food. These whales already fast for months and spend large energy reserves supporting their migrations. When they arrive at their feeding grounds, they need to start feeding. If they don’t have access to predictable food sources, their fitness is affected and they become more vulnerable to anthropogenic threats, including ship strikes, entanglement in fishery gear, and contamination.

For the past three years, I have been using drone-based photogrammetry to assess gray whale body condition along the Oregon coast, as part of my PhD project. Coincident to this current die-off event, I have observed that these whales presented good body condition in 2016, but in the past two years their condition has worsened. But these Oregon whales are feeding on different prey in different areas than the rest of the ENP that heads up to the Bering Sea to feed. So, are all gray whales suffering from the same broad scale environmental impacts? I am currently looking into environmental remote sensing data such as sea surface temperature, chlorophyll-a and upwelling index to explore associations between body condition and environmental anomalies that could be associated.

Trying to answer the question I previously mentioned “is this event worrisome or natural?”, I would estimate that this die-off is mostly due to natural patterns, mainly as a consequence of ecological patterns. This Eastern North Pacific (ENP) gray whale population is now estimated at 27,000 individuals (Calambokidis in: Paris 2019) and it has been suggested that this population is currently at its carrying capacity(K), which is estimated to be between 19,830 and 28,470 individuals (Wade and Perryman, 2002). Prey availability on their primary foraging grounds in the Bering Sea may simply not be enough to sustain this whole population.

The plot below illustrates a population in exponential growth over the years. The population reaches a point (K) that the system can no longer support. Therefore, the population declines and then fluctuates around this K point. This pattern and cycle can result in die-off events like the one we are currently witnessing with the ENP gray whale population.

Population at a carrying capacity (K)
Source: Conservation of change 2019.

 

According to the American biologist Paul Ehrlich: “the idea that we can just keep growing forever on a finite planet is totally imbecilic”. Resources are finite, and so are populations. We should expect die-off events like this.

Right now, we are early on the 2019 feeding season for these giant migrators. Mortality numbers are likely to increase and might even exceed previous die-off events. The last ENP gray whale die-off event occurred in the 1999-2000 season, when a total of 283 stranded whales in 1999 and 368 in 2000 were found displaying emaciated conditions (Gulland et al. 2005). This last die-off event occurred 20 years ago, and thus in my opinion, it is too soon to raise concerns about the long-term impacts on the ENP gray whale population, unless this event continues over multiple years.

 

References

Calambokidis, J. et al. 2002. Abundance, range and movements of a feeding aggregation of gray whales (Eschrichtius robustus) from California to southeastern Alaska in 1998. Journal of Cetacean research and Management. 4, 267-276.

Cascadia Research Collective (2019, May 10). Cascadia and other Washington stranding network organizations continue to respond to growing number of dead gray whales along our coast and inside waters. Retrieved from http://www.cascadiaresearch.org/washington-state-stranding-response/cascadia-and-other-washington-stranding-networkorganizations?fbclid=Iw AR1g7zc4EOMWr_wp_x39ertvzpjOnc1zZl7DoMbBcjI1Ic_EbUx2bX8_TBw

Conservation of change (2019, May 31). Limits to Growth: the first law of sustainability. Retrieved from http://www.conservationofchange.org/limits

CNN (2019, May 15). Dead gray whales keep washing ashore in the San Francisco Bay area.Retrieved from https://www.cnn.com/2019/05/15/us/gray-whale-deaths-trnd-sci/index.html

Gulland, F. M. D., H. Pérez-Cortés M., J. Urbán R., L. Rojas-Bracho, G. Ylitalo, J. Weir, S. A. Norman, M. M. Muto, D. J. Rugh, C. Kreuder, and T. Rowles. 2005. Eastern North Pacific gray whale (Eschrichtius robustus) unusual mortality event, 1999-2000. U. S. Dep. Commer., NOAA Tech. Memo. NMFS-AFSC-150, 33 p.

Harrison, X. A., et al., 2011. Carry-over effects as drivers of fitness differences in animals. Journal of Animal Ecology. 80, 4-18.

Jones, M. L., Swartz, S. L., Gray Whale, Eschrichtius robustus. Encyclopedia of Marine Mammals. Academic Press, San Diego, 2002, pp. 524-536.

Paris (2019, May 27). Gray Whales Wash Up On West Coast At Near-Record Levels.Retrieved from https://www.wbur.org/hereandnow/2019/05/27/gray-whales-wash-up-record-levels

Sumich, J. L., 2014. E. robustus: The biology and human history of gray whales. Whale Cove Marine Education.

Wade, P. R., Perryman, W., An assessment of the eastern gray whale population in 2002. IWC, Vol. SC/54/BRG7 Shimonoseki, Japan, 2002, pp. 16.