By Dawn Barlow, MSc student, OSU Department of Fisheries and Wildlife, Geospatial Ecology of Marine Megafauna Lab
8:35pm on February 20th found the blue whale team smiling, singing, and dancing on the aft deck of the R/V Star Keys as the light faded and the sky glowed orange and we marked our final waypoint of the 2017 blue whale field season. What preceded was a series of days so near perfect that we had barely dared dream of the like. Sighting after sighting, and our team of scientists and the wonderful Star Keys crew began to work like a well-oiled machine—approach the whale gently and observe its behavior, fly the drone, deploy the CTD and echosounder, approach for photos, launch the small boat, approach for biopsy, leave the whale, re-apply sunscreen, find another whale, repeat. This series of events continued from sunrise until sunset, when the sky and water were painted brilliant colors. The sound of big blue whale breaths broke the silence over the glassy water, and the plumes of exhaled air lit up in the last bits of sunlight, lingering there without even a puff of wind to blow them away.
Despite coming to New Zealand during the “worst summer ever”, I’m pleased to say that this has been the most fruitful field season the New Zealand blue whale project has had. We covered a total of 1,635 nautical miles and recorded sightings of 68 blue whales, in addition to sightings of killer whales, pilot whales, common dolphins, dusky dolphins, sharks, and many seabirds. Five of our blue whale sightings included calves, reiterating that the South Taranaki Bight appears to be an important area for mother-calf pairs. Callum and Mike (Department of Conservation) collected 23 blue whale biopsy samples, more than twice the number collected last year. Todd flew the drone over 35 whales, observing and documenting behaviors and collecting aerial imagery for photogrammetry. We took 9,742 photos, which will be used to determine how many unique individuals we saw and how many of them have been sighted in previous years.
It is always hard to see a wonderful thing come to an end, and we agreed that we would all happily continue this work for much longer if funding and weather permitted. But as the small skiff returned to the Star Keys with our final biopsy sample and the dancing began, we all agreed that we couldn’t have asked for a better note to end on. There has already been plenty of wishful chatter about future field efforts, but in the meantime we’re still floating from this year’s success. I will certainly have my hands full when I return to Oregon, and in the best possible way. It feels good to have an abundance of data from a project I’m passionate about.
Thank you to Western Work Boats and Captain James “Razzle-Dazzle” Dalzell, Spock, and Jason of the R/V Star Keys for their hard work, patience, and good attitudes. James made it clear at the beginning of the trip that this was to be our best year ever, and it was nothing less. The crew went from never having seen a blue whale before the trip to being experts in maneuvering around whales, oceanographic data collection, and whale poop-scooping. Thank you to Callum Lilley and Mike Ogle from the Department of Conservation for their time, impressive marksmanship, and enthusiasm. And once again thank you to all of our colleagues, funders, and supporters—this project is made possible by collaboration. Now that we’ve wrapped up, blue whale team members are heading in different directions for the time being. We’ll be dreaming of blue whales for weeks to come, and looking forward to the next time our paths cross.
Join us for a couple boat rides as we study blue whales in the South Taranaki Bight of New Zealand.
In both videos below you can see and hear the field team coordinate to capture photo-identification images of the whale(s) while also obtaining a small tissue biopsy sample. It is important to match the individual whale to the sample so we can link biological data obtained from the sample (genetics, hormones, stable isotopes) to the individual whale. We also carefully take notes on where, when and what we collect in order to help us keep track of our data.
In this video clip you can watch as we gently approach two blues surfacing off the starboard bow of the RV Star Keys in order to capture photo-identification images and a small tissue biopsy sample. Callum Lilley (DOC) on the bow; Leigh Torres, Dawn Barlow, and Todd Chandler (OSU) photographing and coordinating from the flying bridge.
We are in the small boat here collecting data on a pair of blue whales. Callum Lilley (DOC) is on the rifle; Leigh Torres (OSU) is on the camera and taking notes; Todd Chandler (OSU) is on the helm.
By Dawn Barlow, MSc student, Department of Fisheries and Wildlife, Geospatial Ecology of Marine Megafauna Lab
“The marine environment is patchy and dynamic”. This is a phrase I have heard, read, and written repeatedly in my studies of marine ecology, and it has become increasingly tangible during the past several weeks of fieldwork. The presence of the blue whales we’ve come here to study is the culmination of a chain of events that begins with the wind. As we huddle up at anchor or in port while the winds blow through the South Taranaki Bight, the water gets mixed and our satellite images show blooms of little phytoplankton lifeforms. These little phytoplankton provide food for the krill, the main prey item of far larger animals—blue whales. And in this dynamic environment, nothing stays the same for long. As the winds change, aggregations of phytoplankton, krill and whales shift.
When you spend hours and hours scanning for blue whales, you also grow intimately familiar with everything that could possibly look like a blue whale but is not. Teasers include whitecaps, little clouds on the horizon, albatrosses changing flight direction, streaks on your sunglasses, and floating logs. Let me tell you, if we came here to study logs we would have quite the comprehensive dataset! We have had a few days of long hours with good weather conditions and no whales, and it is difficult not to be frustrated at those times—we came here to find whales. But the whale-less days prompt musings of what drives blue whale distribution, foraging energetics, and dreams of elaborate future studies and analyses, along with a whole lot of wishing for whales. Because, let’s admit it, presence data is just more fun to collect.
But we’ve also had survey days filled with so many whales that I can barely keep track of all of them. When as soon as we begin to head in the direction of one whale, we spot three more in the immediate area. Excited shouts of “UP!! Two o’clock at 300 meters!” “What are your frame numbers for your right side photos?” “Let’s come 25 degrees to port” “UUUPPP!! Off the bow!” “POOOOOOP! Grab the net!!” fill the flying bridge as the team springs into action. We’ve now spotted 40 blue whales, collected 8 biopsy samples, 8 fecal samples, flown the drone over 9 whales, and taken 4,651 photographs. And we still have more survey days ahead of us!
In Leigh’s most recent blog post she described our multi-faceted fieldwork here in the South Taranaki Bight. Having a small inflatable skiff has allowed for close approaches to the whales for photo-identification and biopsy sample collection while our larger research vessel collects important oceanographic data concurrently. I’ve been reading numerous papers linking the distribution of large marine animals such as whales with oceanographic features such as fronts, temperature, and primary productivity. In one particular sighting, the R/V Star Keys idled in the midst of a group of ~13 blue whales, and I could see foamy lines on the surface where water masses met and mixed. The whales were diving deep—flukes the size of a mid-sized car gracefully lifting out of the water. I looked at the screen of the echosounder as it pinged away, bouncing off a dense layer of krill (blue whale prey) just above the seafloor at around 100 meters water depth. As I took in the scene from the flying bridge, I could picture these big whales diving down to that krill layer and lunge feeding, gorging themselves in these cool, productive waters. It is all mostly speculative at this point and lots of data analysis time remains, but ideas are cultivated and validated when you experience your data firsthand.
The days filled with whales make the days without whales worthwhile and valuable. To emphasize the dynamic nature of the environment we study, when we returned to an area in which we had seen heaps of whales just 12 hours before, we only found glassy smooth water and no whales whatsoever. Changing our trajectory, we came across nothing for the first half of the day and then one pair of whales after another. Some traveling, some feeding, and two mother-calf pairs.
The dynamic nature of the marine environment and the high mobility of our study species is what makes this work challenging, frustrating, exciting, and fascinating. Now we’re ready to take advantage of our next weather window to continue our survey effort and build our ever-growing dataset. I relish the wind-swept, sunburnt days of scanning and musing, and I also look forward to settling down with all of these data to try my best to compile all of the pieces of this blue whale puzzle. And I know that when I find myself behind a computer screen processing and analyzing photos, survey effort, drone footage, and oceanographic data I will be imagining the blue waters of the South Taranaki Bight, the excitement of seeing the water glow brilliantly just before a whale surfaces off our bow, and whale-filled survey days that end only when the sun sets over the water.
After four full-on days at sea covering 873 nautical miles, we are back in port as the winds begin to howl again and I now sip my coffee with a much appreciated still horizon. Our dedicated team worked the available weather windows hard and it paid off with more great absence data and excellent presence data too: blue whales, killer whales, common dolphins, and happily swimming pilot whales not headed to nearby Farewell Spit where a sad, massive stranding has occurred. It has been an exhausting, exhilarating, frustrating, exciting, and fulfilling time. As I reflect on all this work and reward, I can’t help but feel gratified for our persistent and focused planning that made it happen successfully. So, as we clean-up, organize data, process samples, and sit in port for a few days I would like to share some of our highlights over the past four days. I hope you enjoy them as much as we did.
“This is the worst summer ever in New Zealand.” During our four days of prep in Wellington before heading off on our vessel, almost all my friends and colleagues I spoke to said this statement (often with added emphasis). It’s been cold and windy here all summer long, and when the weather has cleared it has brought only brief respite. These comments don’t bode well for our blue whale survey dependent on calm survey conditions, but February is typically the prime month for good weather in New Zealand so I’m holding out hope. And this unpredictable weather is the common denominator of all field work. Despite months (years?) of preparation, with minute attention to all sort of details (e.g., poop net handle length, bag size limits, length of deployment lines), one of the most important factors to success is something we have absolutely no control over: the weather.
After just one day on the water, I can see that the oceanographic conditions this year are nothing like the hot-water El Niño conditions we experienced last summer. Surface water temperatures today ranged between 12.8 and 13.6 ⁰C. These temps are 10 degrees (Celsius) cooler than the 22 ⁰C water we often surveyed last summer. 10 degrees! Additionally, the current windy conditions have stirred up the upper portion of the ocean water column causing the productive mixed layer to be much deeper (therefore larger) than last year. While Kiwis may complain about the ‘terrible’ weather this summer, the resulting cold and productive oceanographic conditions are likely preferable for the whales. But where are the whales and can we find them with all this wind?
Today we had a pocket of calm conditions so our dedicated research team and crew hit it with enthusiasm, and collected a whole lot of great absence data. “Absence data?” you may ask. Absence data is all the information about where the whales are not, and is just as important as presence data (information about where the whales are) because it’s the comparison between the two sets of data (Presence vs Absence) that allows us to describe an animal’s “habitat use patterns”. Today we surveyed a small portion of the South Taranaki Bight for blue whales for about 6 hours, but the only blue animals we saw were little blue penguins and a blue shark (plus fur seals, dolphins, albatrosses, shearwaters, gannets, prions, kahawai, and saury). But during this survey effort we collected a lot of synoptic environmental data to describe these habitats, including continuous depth and temperature data along our track, nine CTD water column profiles of temperature, salinity and florescence (productivity) from the surface to the seafloor, and continuous prey (zooplankton) availability data with our transducer (echosounder).
So, now that we have absence data, we need presence data. But, the winds are howling again and are predicted to continue for the next few days. As we hunker down in a beautiful protected cove I know the blue whales continue to search this region for dense food patches, unencumbered by human-perceived obstacles of high wind and swell. So, while my Kiwi friends are right – this summer is not like previous years – I also know that it is the effects of these dynamic weather patterns that we have come so far, and worked so hard, to study. Even as my patience wears thin and my frustrations mount, I will continue to wait to pounce on the right weather window to collect our needed presence data (and more absence data too, I’m sure).
Our research team collecting absence data aboard the RV Star Keys:
Today we are flying to the other side of the world and boarding a 63-foot boat to study the largest animals ever to have inhabited this planet: blue whales (Balaenoptera musculus). Why do we study them, and how will we do it? Before I tell you, first let me say that no fieldwork is ever straightforward, and consequently no fieldwork lacks exciting learning opportunities. I have learned a lot about the logistics of an international field season in the past month, which I will share with you here!
Unmanned aerial systems (UAS, a.k.a. “drones”) are becoming more prevalent in our field as a powerful and minimally invasive tool for studying marine mammals. Last year, our team was able to capture what we believe is the first aerial footage of nursing behavior in baleen whales, in addition to feeding and traveling behaviors. And beyond behavior, these aerial images contain morphological and physiological information about the whales such as how big they are, whether they are pregnant or lactating, and if they are in good health. I’ll start making a packing list for you to follow along with. So far it contains two drones and all of their battery supplies and chargers.
Perhaps you read my first GEMM Lab blog post, about identifying individual blue whales from photographs? Using these individual IDs, I plan to generate an abundance estimate for this blue whale population, as well as look at residency and movement patterns of individuals. Needless to say, we will be collecting photo-ID images this year as well! Add two large pelican cases with cameras and long lenses to the packing list.
Now wouldn’t it be great to capture video of animal behavior in some way other than with the UAS? Maybe even from underwater? Add two GoPros and all of their associated paraphernalia to the mounting gear pile.
Now, bear with me. There is a wealth of physiological information contained in blue whale fecal matter. And when hormone analysis from fecal samples is paired with photogrammetry from UAS images, we can develop a valuable picture of individual and population-level health, stress, nutrition, and reproductive status. So, say we are able to scoop up lots of blue whale fecal samples – wouldn’t that be fantastic? Yes! Alright, add two nets, a multitude of jars, squirt bottles, and gloves to the gear list. And then we still need to bring them back to our lab here in Newport. How does that happen? Well, we need to filter out the sea water, transfer the samples to smaller tubes, and freeze them… in the field, on a moving vessel. Include beakers, funnels, spatulas, and centrifuge tubes on the list. Yes, we will be flying back with a Styrofoam cooler full of blue whale “poopsicles”. Of course, we need a cooler!
Alright, and now remember the biopsy sampling that took place last season? Collecting tissue samples allows us to assess the genetic structure of this population, their stable isotopic trophic feeding level, and hormone levels. Well, we are prepared to collect tissue samples once again! Remember to bring small tubes and scalpel blades for storing the samples, and to get ethanol when we arrive in Wellington.
An important piece in investigating the habitat of a marine predator is learning about the prey they are consuming. In the case of our blue whales, this prey is krill (Nyctiphanes australis). We study the prey layer with an echo sounder, which sends out high frequency pings that bounce off anything they come in contact with. From the strength of the signal that bounces back it is possible to tell what the composition of the prey layer is, and how dense. The Marine Mammal Institute here at OSU has an echo sounder, and with the help of colleagues and collaborators, positive attitudes, and perseverance, we successfully got the transducer to communicate with the receiver, and the receiver to communicate with the software, and the software to communicate with the GPS. Add one large pelican case for the receiver. Can we fit the transducer in there as well? Hmmm, this is going to be heavy…
Now the daunting, ever-growing to-do lists have been checked off and re-written and changed and checked off again. The mountain of research gear has been evaluated and packed and unpacked and moved and re-evaluated and packed again. The countdown to our departure date has ended, and this evening Leigh, Todd, and I fly out of Portland and make our way to Wellington, New Zealand. To think that from here all will be smooth and flawless is naïve, but not being able to contain my excitement seems reasonable. Maybe it’s the lack of sleep, but more likely it’s the dreams coming true for a marine ecologist who loves nothing more than to be at sea with the wind in her face, looking for whales and creatively tackling fieldwork challenges.
In the midst of the flurry of preparations, it can be easy to lose sight of why we are doing this—why we are worrying ourselves over poopsicle transport and customs forms and endless pelican cases of valuable equipment for the purpose of spending several weeks on a vessel we haven’t yet set foot on when we can’t even guarantee that we’ll find whales at all. This area where we will work (Figure 1) is New Zealand’s most industrially active region, where endangered whales share the space with oil rigs, shipping vessels, and seismic survey vessels that have been active since October in search of more oil and gas reserves. It is a place where we have the opportunity to study how these majestic giants fit into this ecosystem, to learn what about this habitat is driving the presence of the whales and how they’re using the space relative to industry. It is an opportunity for me as a scientist to pursue questions in ecology—the field of study that I love. It is also an opportunity for me as a conservation advocate to find my voice on issues of industry presence, resource extraction, and conflicts over ocean spaces that extend far beyond one endangered species and one region of the world.
By Leila Lemos, Ph.D. Student, Department of Fisheries and Wildlife, OSU
In a previous blog of mine, you could read about the challenges I have been facing while I am learning to analyze the hormone content in fecal samples of gray whales (Eschrichtius robustus). New challenges appeared along the way over the last month, while I was doing my training at the Seattle Aquarium (Fig. 1).
My training lasted a week and I am truly grateful to the energy and time our collaborators Shawn Larson (research coordinator), Amy Green and Angela Smith (laboratory technicians) contributed. They accompanied me throughout my training to ensure I would be able to conduct hormonal analysis in the future, and to handle possible problems along the way.
The first step was weighing all of the fecal samples (Fig. 2A). Subsequently, the samples were transferred to appropriate glass tubes (Figs. 2B & 2C) for the next laboratorial step.
The second conducted step was the hormone extraction. The extraction began with the addition of an organic solvent, called methanol (CH3OH), to the sample tubes (Fig. 3A & 3B). Hormones leach out from the samples and dissolve in the methanol, due to their affinity for this polar solvent.
Tubes were then placed on a plate shaker (Fig. 3C) for 30 minutes, which is used to mix the substances, in order extract the hormones from the fecal samples. The next step was to place the tubes in a centrifuge (Fig. 3D) for 20 minutes. The centrifuge uses the sedimentation principle, causing denser substances or particles to settle to the bottom of the tube, while the less dense substances rise to the top.
After this process, the two different densities were separated: the high-density particles of the feces were in the bottom of the tube, while the methanol containing the extracted hormones was at the top. The top phase (methanol + hormones) was then pipetted into a different tube (Fig. 4A). The solvent was then evaporated, by using an air dryer apparatus (Fig. 4B), with only the hormones remaining in the tube.
The third performed step was dilution. A specific amount of water, measured in correlation with sample weight and to the amount of the methanol mixed with each sample, was added to each tube (Fig. 4C). Since the hormones were concentrated in the methanol, the readings would exceed the measurement limits of the equipment (plate reader). Thus, in order to prepare the extracts for the immunoassays, different dilutions were made.
The fourth and final step was to finally conduct the assays. Each assay kit is specific to the hormone to be analyzed with specified instructions for each kit. Since we were analyzing four different hormones (cortisol, testosterone, progesterone, and triiodothyronine – T3) we followed four different processes accordingly.
First, a table was filled with the identification numbers of the samples to be analyzed in that specific kit (Fig. 5A). The kit (Fig. 5B) includes the plate reader and several solutions that are used in the process to prepare standard curves, to initiate or stop chemical reactions, among other functions.
A standard curve, also known as calibration curve, is a common procedure in laboratory analysis for determining the concentration of an element in an unknown sample. The concentration of the element is determined by comparison with a set of standard samples of known concentration.
The plate contains several wells (Fig. 5C & 5D), which are filled with the samples and/or these other solutions. When the plate is ready, (Fig.5D) it is carried to the microplate reader that measures the intensity of the color of each of the wells. The intensity of the color is inversely proportional to the concentration of the hormone in both the standards and the samples.
Since this is the first fecal hormone analysis being performed in gray whales, a validation process of the method is required. Two different tests (parallelism and accuracy) were performed with a pool of three different samples. Parallelism tests that the assay is measuring the antigen (hormone) of interest and also identifies the most appropriate dilution factor to be used for the samples. Accuracy tests that the assay measurement of hormone concentration corresponds to the true concentration of the sample (Brown et al. 2005).
This validation process only needs to be done once. Once good parallelism and accuracy results are obtained, and we have identified the correct dilution factor and approximate concentration of the samples, the samples are ready to be analyzed. Below you can see examples of a good parallelism test (parallel displacement; Fig. 6) and bad parallelism tests (Fig. 7) that indicate no displacement, low concentration or non-parallel displacement; and a good accuracy test (Fig. 8).
After the validation tests returned reliable results, the samples were also analyzed. However, many complications were encountered during the assay preparations and important lessons were learned that I know will allow this work to proceed more smoothly and quickly in the future. For instance, I now know to try to buy assay kits of the same brand, and to be extremely careful while reading the manual of the process to be performed with the assay kit. With practice over the coming years, my goal is to master these assay preparations.
Now, the next step will be to analyze all of the results obtained in these analyses and start linking the multiple variables we have from each individual, such as age, sex and body condition. The results of this analysis will lead to a better understanding of how reproductive and stress hormones vary in gray whales, and also link these hormone variations to nutritional status and noise events, one of my PhD research goals.
Brown J, Walker S and Steinman K. 2005. Endocrine manual for reproductive assessment of domestic and non-domestic species. Smithsonian’s National Zoological Park, Conservation and Research Center, Virginia 1-69.
At 2pm, Jan 3, our paper entitled “Classification of Animal Movement Behavior through Residence in Space and Time” was published. At 14:03 I clicked on the link and there it was, type-set and crisp as a newly minted Open Access scientific contribution.
So, what is this paper about? It presents a simple – yes simple – method of identifying simple behaviors states in two-dimensional animal tracking data (think latitude and longitude). Since the paper is open access you can go find the methods there. Categorizing these “dots on a map” into behaviors allows us to ask questions about how often, why, when and where simple behaviors happen. These behaviors really are simple (hopefully the somewhat grating repetitiveness of the word ‘simple’ has driven that point home by now!). We are identifying three basic, but fundamental, states:
1) transit, characterized by fast somewhat straight line movement from a to b,
2) a sedentary state characterized by relatively more time spent in an area with little distance traveled (such as resting behavior) and
3) an active state characterized by lots of time spent in an area where an animal is also moving around a lot and covering a lot of ground.
This new method, that we termed Residence in Space and Time (RST), can assist the fast-growing, sophisticated, big-data generating, conservation-orientated field of animal movement ecology. One of the first hurdles is data exploration and visualization. Modern ecologists deploy tracking devices that collect location data remotely to understand animal distribution and behavior. But at first glance tracks (like the figure below) can look like spaghetti dinner. Identifying movement behaviors can help to us see patterns in the tangles.
So how might this method work? First lets start with a track. Below is a very short foraging trip from a thick-billed murre tracked with a GPS logger during chick rearing from St. Paul Island in Alaska (see Parades et al 2015).
The track below has points every second and we can imagine the murre flying from the colony, landing on the water, and then diving (indicated by the lack of GPS position data when the bird dives below the water to forage). Then the bird flies back to the colony to feed its chick. This trip is roughly 14 minutes long.
So I can take this track and run RST to identify three behavior states. As color-coded below, the black points indicate transit, red indicates relatively stationary behavior, and blue indicates points where the bird was flying in a less direct mannerthan pure transit potentially circling around before landing and moving between dives. The high resolution of the GPS data really helps us to understand how this bird was moving. Such behavior information is easily conserved in a high-resolution track like this. Though in this case the bird did a lot of transiting and only exhibited different movement behaviors in the vicinity of the two dives.
Logging locations at 1 second intervals is a stretch for the battery life of these miniaturized GPS loggers (~15g), and more often than not we would like the loggers to last much longer than 14 mins. So instead of 1 second we typically have tracks with less frequent locations. To me this is akin to taking a 1 second track and then taking off my glasses and trying to see the same behaviors. Deciphering behavior states becomes a bit (or a lot) fuzzier. In the case of this murre track, when we down-sample the locations to every 10 seconds much of the resolution of this track is lost (see plot below). What happens when we run RST?
As you can see some of the behavior is maintained and some of it is a bit fuzzier.
A good rule of thumb is that if a behavior happens faster than the sampling interval the logger is recording at, then the behavior is not recorded. Seems simple, but it is an important consideration when programming loggers and designing animal movement studies. For murres these quick trips to forage for their chicks are easily lost even at a 5 minute sampling interval, which is often used in seabird tracking studies where the birds are at-sea for days. Often we work with such lower resolution location data and, instead of one trip from one bird, we have many trips from many individuals. RST allows a fast way to quickly and accurately identify simple behaviors in order to help with initial data exploration efforts and for answering more complex questions such as behavior specific habitat models.
So, if you have some tracking data – of birds, marine mammals, or your dog! – you can learn how RST works (basically by summing up time and distance covered within a circle). The R code, a short guide, and example dataset are available as links at the end of the paper.
Here is the spaghetti from above (really tracks of Grey-headed albatrosses) with the behavioral states labeled using RST: 93,481 points and this behavior classification took only 14 seconds to run!
Communicating science has become more important than ever as major social and political issues, such as climate change, require increasing input from scientists. In a recent article published by the Proceedings of the National Academy of Science, a research group from the University of Cologne in Cologne, Germany, explores how social cognition influences our ability to market science.
This article, titled “Past-focused environmental comparisons promote pro-environmental outcomes for conservatives” focuses specifically on understanding why there is a political divide in the United States regarding the issue of climate change (Baldwin & Lammers 2016). While our research in the GEMM lab focuses on spatial ecology (rather than social science) I thought this article was worth sharing because of its insights about “framing science”. The conservation science that we conduct in the GEMM lab will not be effective if we cannot properly communicate our objectives and our findings to funders and stakeholders.
“Framing” is a term in psychology that describes how you craft a message based on your intended audience. It is important to note that use of the term framing (or marketing) science doesn’t imply misrepresentation of facts (Nisbet & Mooney 2007). Rather,“Frames organize central ideas, defining a controversy to resonate with core values and assumptions” (Nisbet & Mooney 2007). Baldwin & Lammers (2016) demonstrated that subtle differences in framing significantly affect how environmental messages are perceived. These authors investigated the effect of framing with regards to temporal comparisons, environmental attitudes and behavior.
The specific problem these authors address is the failure of climate change advocates to bridge the political divide between liberals and conservatives in the United States. The authors hypothesize that the temporal comparisons used in arguments for action on climate change explain the dichotomy between liberal and conservative views on this issue (which garners less support from conservatives).
The primary hypothesis guiding this study is that conservatives are more likely to favor a “past-focused” message rather than a “future-focused” message about climate change. The authors surmise that this framing bias is rooted in a conservative ideology that favors past traditions over a progressive future, which is more favored by liberals. Many pro-environmental arguments and appeals to address climate change are future focused, e.g. Balwin & Lemmers (2016) quote UN Secretary-General Ban-Ki Moon, speaking about climate change:
“…We need to find a new, sustainable path to the future we want”.
If temporal comparisons do elicit framing bias, then our framing of the issue of climate change, and possibly other environmental issues, could be more effective if presented to conservatives as past-focused messages.
The authors tested these hypotheses on participants in a series of online studies. You can find more details on methods in the papers supporting information found here. In the first three studies, the authors investigated the effect of temporal comparisons on pro-environmental beliefs. Study participants were asked to read messages, or view images, that addressed the issue of climate change by comparing the present to the past, or the present to the future. Following these comparisons, participants ranked their pro-environmental attitudes. Examples of these comparisons were statements such as, “Looking forward to our Nation’s future… there is increasing traffic on the road” (future-focused), and, “Looking back to our Nation’s past…there was less traffic on the road” (past-focused).
You can see examples of past and future-focused images below.
The authors found significant evidence to support their hypothesis that presenting conservatives with past-focused messages is more effective in terms of promoting pro-environmental messages than presenting future-focused messages. Temporal comparisons did not affect the pro-environmental attitudes of liberals.
The authors also investigated the temporal focus of environmental organizations and found that overall, environmental charities promote future-focused messages. Study participants were allotted small amounts of cash to donate to these charities, and conservatives gave more to past-focused charities than to future-focused charities. You can see examples of charities with differing temporal focuses below.
In a final meta-analysis, these authors found that employing past-focused comparisons nearly made up for the difference between liberals and conservatives in terms of their pro-environmental attitudes. The implication of these findings is that we can improve the way we communicate about controversial issues such as climate change by subtly altering our arguments. For example, in one study that was cited by Baldwin & Lammers (2016), conservatives favored the words ‘purity’ and ‘sanctity’ over ‘harm’ and ‘care’ (Fienberg & Willer 2012). Based on these studies, an example of an effective message for a conservative audience would be, “It is important that we restore the Earth because it has become contaminated”.
These findings could be true for other environmental issues as well, and so it is worth thinking critically about how to craft messages about our scientific findings for our intended audiences. We need to carefully frame our messages whether we are writing grant proposals, peer-reviewed manuscripts, press releases, or posts intended for social media.
I originally discovered this paper after listening to a short radio interview that was conducted by CBC Radio, and if you are interested in this research I encourage you to check it out! You can following this link: how to convince a climate change skeptic.
Baldwin, M., & Lammers, J. (2016). Past-focused environmental comparisons promote proenvironmental outcomes for conservatives. Proceedings of the National Academy of Sciences, 113(52), 14953-14957.
Feinberg, M., & Willer, R. (2013). The moral roots of environmental attitudes. Psychological Science, 24(1), 56-62.
Nisbet, M. C., & Mooney, C. (2009). Framing science. Science, 316.
By Dawn Barlow, MSc Student, Department of Fisheries and Wildlife, Oregon State University
The year is rapidly coming to a close, and what a busy year it has been in the Geospatial Ecology of Marine Megafauna Lab! In 2016, our members have traveled to six continents for work (all seven if we can carry Rachael’s South African conference over from the end of 2015…), led field seasons in polar, temperate, and tropical waters, presented at international conferences, processed and analyzed data, and published results. Now winter finds us holed up in our offices in Newport, and various projects are ramping up and winding down. With all of the recent turmoil 2016 has brought, it is a nice to reflect on the good work that was accomplished over the last 12 months. In writing this, I am reminded of how grateful I am to work with this talented group of people!
The year started with a flurry of field activity from our southern hemisphere projects! Erin spent her second season on the Antarctic peninsula, where she contributed to the Palmer Station Long Term Ecological Research Project.
The New Zealand blue whale project launched a comprehensive field effort in January and February, and it was a fruitful season to say the least. The team deployed hydrophones, collected tissue biopsy and fecal samples, and observed whales feeding, racing and nursing. The data collected by the blue whale team is currently being analyzed to aid in conservation efforts of these endangered animals living in the constant presence of the oil and gas industry.
Midway atoll is home to one of the largest albatross colony in the world, and Rachael visited during the winter breeding season. In addition to deploying tracking devices to study flight heights and potential conflict with wind energy development, she became acutely aware of the hazards facing these birds, including egg predation by mice and the consumption of plastic debris.
Early summertime brought red-legged kittiwakes to the remote Pribilof Islands in Alaska to nest, and Rachael met them there to study their physiology and behavior.
As the weather warmed for us in the northern hemisphere, Solene spent the austral winter with the humpback whales on their breeding grounds in New Caledonia. Her team traveled to the Chesterfield Reefs, where they collected tissue biopsy samples and photo-IDs, and recorded the whale’s songs. But Solene studies far more than just these whales! She is thoroughly examining every piece of environmental, physical, and oceanographic data she can get her hands on in an effort to build a thorough model of humpback whale distribution and habitat use.
Summertime came to Oregon, and the gray whales returned to these coastal waters. Leigh, Leila, and Todd launched into fieldwork on the gray whale stress physiology project. The poop-scooping, drone-flying team has gotten a fair bit of press recently, follow this link to listen to more!
And while Leigh, Leila, and Todd followed the grays from the water, Florence and her team watched them from shore in Port Orford, tracking their movement and behavior. In an effort to gain a better understanding of the foraging ecology of these whales, Florence and crew also sampled their mysid prey from a trusty research kayak.
With the influx of gray whales came an influx of new and visiting GEMM Lab members, as Florence’s team of interns joined for the summer season. I was lucky enough to join this group as the lab’s newest graduate student!
Our members have presented their work to audiences far and wide. This summer Leigh, Amanda, and Florence attended the International Marine Conservation Congress, and Amanda was awarded runner-up for the best student presentation award! Erin traveled to Malaysia for the Scientific Convention on Antarctic Research, and Rachael and Leigh presented at the International Albatross and Petrel Conference in Barcelona. With assistance from Florence and Amanda, Leigh led an offshore expedition on OSU’s research vessel R/V Oceanus to teach high school students and teachers about the marine environment.
Wintertime in Newport has us tucked away indoors with our computers, cranking through analyses and writing, and dreaming about boats, islands, seabirds, and whales… Solene visited from the South Pacific this fall, and graced us with her presence and her coding expertise. It is a wonderful thing to have labmates to share ideas, frustrations, and accomplishments with.
As the year comes to a close, we have two newly-minted Masters of Science! Congratulations to Amanda and Erin on successfully defending their theses, and stay tuned for their upcoming publications!
We are looking forward to what 2017 brings for this team of marine megafauna enthusiasts. Happy holidays from the GEMM Lab!