How Unmanned Aircraft Systems (UAS, aka “drones”) are being applied in conservation research

By Leila Lemos, Ph.D. Student, Department of Fisheries and Wildlife, OSU

 

Unmanned Aircraft Systems (UAS), also known as “drones”, have been increasingly used in many diverse areas. Concerning field research, the use of drones has brought about reduced errors, increased safety and survey efforts, among other benefits, as described in a previous blog post of mine.

Several study groups around the world have been applying this new technology to a great variety of research applications, aiding in the conservation of certain areas and their respective fauna and flora. Examples of these studies include forest monitoring and tree cover analyses, .

Using drones for forest monitoring and tree cover analyses allows for many applications, such as biodiversity and tree height monitoring, forest classification and inventory, and plant disease and detection. The Ugalla Primate Project, for example, performed an interesting study on tree coverage mapping in western Tanzania (Figure 1).

Figure 1: Tree coverage analyses in Tanzania.
Source: Conservation Drones, 2016.

 

The access to this data (not possible before from the ground) and the acquired knowledge on tree density and structure were important to better understand how wild primates exploit a mosaic landscape. Here is a video about this project:

 

Forest restoration activities can also be monitored by drones. Rainforests around the world have been depleted through deforestation, partly to open up space for agriculture. To meet conservation goals, large areas are being restored to rainforests today (Elsevier 2015). It is important to monitor the success of the forest regeneration and to ensure that the inspected area is being replenished with the right vegetation. Since inspection events can be costly, labor intensive and time consuming, drones can facilitate these procedures, making the monitoring process more feasible.

Zahawi et al. (2015) conducted an interesting study in Costa Rica, being able to keep up with the success of the forest regeneration. They were also able to spot many fruit-eating birds important for forest regeneration (eg. mountain thrush, black guan and sooty-capped bush tanager). Researchers concluded that the automation of the process lead to equally accurate results.

Drones can also be used to inspect areas for illegal logging and habitat destruction. Conservationists have struggled to identify illegal activities, and the use of drones can accelerate the identification process of these activities and help to monitor their spread and ensure that they do not intersect with protected areas.

The Amazon Basin Conservation Association Los Amigos conservancy concession (LACC) has been monitoring 145,000 hectars of the local conservation area. Illegal gold mining and logging activities were identified (Figure 2) and drones have aided in tracking the spread of these activities and the progress of reforestation efforts.

Figure 2: Identification of illegal activities in the Amazon Basin.
Source: NPR, 2015.

 

Another remarkable project was held in Mexico, in one of the most important sites for monarch butterflies in the country: the Monarch Butterfly Biosphere Reserve. Around 10 hectars of vital trees were cut down in the reserve during 2013-2015, and a great decrease of the monarch population was perceived. The reserve did not allow researchers to enter in the area for inspection due to safety concerns. Therefore, drones were used and were able to reveal the illegal logging activity (Figure 3).

Figure 3: Identification of illegal logging at the Monarch Butterfly Biosphere Reserve, Mexico.
Source: Take Part, 2016.

 

Regarding the use of drones for mapping vulnerable areas, this new technology can be used to map potential exposed areas to avoid catastrophes. Concerning responses to fires or other natural disasters, drones can fly immediately, while planes and helicopters require a certain time. The drone material also allows for operating successfully under challenging conditions such as rain, snow and high temperatures, as in the case of fires. Data can be assessed in real time, with no need to have firefighters or other personnel at a dangerous location anymore. Drones can now fulfill this role. Examples of drone applications in this regard are the detection, monitoring and support for catastrophes such as landslides, tsunamis, ship collisions, volcanic eruptions, nuclear accidents, fire scenes, flooding, storms and hurricanes, and rescue of people and wildlife at risk. In addition, the use of a thermal image camera can better assist in rescue operations.

Researchers from the Universidad Politécnica de Madrid (UPM) are developing a system to detect forest fires by using a color index (Cruz et al. 2016). This index is based on vegetation classification techniques that have been adapted to detect different tonalities for flames and smoke (Figure 4). This new technique would result in more cost-effective outcomes than conventional systems (eg. helicopters, satellites) and in reaching inaccessible locations.

Figure 4: Fire detection with Forest Fire Detection Index (FFDI) in different scenes.
Source: UPM, 2016.

 

Marine debris detection by drones is another great functionality. The right localization and the extent of the problem can be detected through drone footage, and action plans for clean-ups can be developed.

A research conducted by the Duke University Marine Lab has been detecting marine debris on beaches around the world. They indicate that marine debris impacts water quality, and harms wildlife (eg. whales, sea birds, seals and sea turtles) that might confuse floating plastic with food. You can read a bit more about their research and its importance for conservation ends here.

Drones are also being extensively used for wildlife monitoring. Through drone footage, researchers around the world have been able to detect and map wildlife and habitat use, estimate densities and evaluate population status, detect rare behaviors, combat poaching, among others. One of the main benefits of using a drone instead of using helicopters or airplanes, or having researchers in the area, is the lower disturbance it may cause on wildlife.

A research team from Monash University is using drones for seabird monitoring in remote islands in northwestern Australia (Figure 5). After some tests, researchers were able to detect which altitude (~75 meters) the drone would not cause any disturbances to the birds. Results achieved by projects like this should be used in the future for approaching the species safely.

Figure 5: Photograph taken by a drone of a crested tern colony on a remote island in Australia.
Source: Conservation Drones, 2014.

 

Drones are also being used to combat elephant and rhino poaching in Africa. They are being implemented to predict, trace, track and catch suspects of poaching. The aim is to reduce the number of animals being killed for the detusking and dehorning practices and the illegal trade. You can read more about this theme here. The drone application on combating one of these illegal practices is also shown here in this video.

As if the innovation of this device alone was not enough, drones are also being used to load other tools. A good example is the collection of whale breath samples by attaching Petri dishes or sterile sponges in the basal part of the drones.

The collection of lung samples allows many health-monitoring applications, such as the analysis of virus and bacteria loads, DNA, hormones, and the detection of environmental toxins in their organisms. This non-invasive physiological tool, known as “Snotbot”, allows sampling collection without approaching closely the individuals and with minimal or no disturbance of the animals. The following video better describes about this amazing project:

It is inspiring to look at all of these wonderful applications of drones in conservation research. Our GEMM Lab team is already applying this great tool in the field and is hoping to support the conservation of wildlife.

 

 

References

Conservation Drones. 2014. Conservation Drones for Seabird Monitoring. Available at: https://conservationdrones.org/2014/05/05/conservation-drones-for-seabird-monitoring/

Conservation Drones. 2016. Tree cover analyses in Tanzania in collaboration with Envirodrone. Available at: https://conservationdrones.org/2016/09/17/tree-cover-analyses-in-tanzania-in-collaboration-with-envirodrone/

Cruz H, Eckert M, Meneses J and Martínez JF. 2016. Efficient Forest Fire Detection Index for Application in Unmanned Aerial Systems (UASs). Sensors 16(893):1-16.

Elsevier. 2015. Drones Could Make Forest Conservation Monitoring Significantly Cheaper: new study published in the Biological Conservation wins Elsevier’s Atlas award for September 2015. Available at: https://www.elsevier.com/about/press-releases/research-and-journals/drones-could-make-forest-conservation-monitoring significantly-cheaper

NPR. 2015. Eyes In The Sky: Foam Drones Keep Watch On Rain Forest Trees. Available at: http://www.npr.org/sections/goatsandsoda/2015/05/19/398765759/eyes-in-the-sky-styrofoam-drones-keep-watch-on-rainforest-trees

Take Part. 2016. Drones Uncover Illegal Logging in Critical Monarch Butterfly Reserve. Available at: http://www.takepart.com/article/2016/06/22/drones-uncover-illegal-logging-monarch-butterfly-habitat

UPM. 2016. New automatic forest fire detection system by using surveillance drones. Available at: http://www.upm.es/internacional/UPM/UPM_Channel/News/dc52fff26abf7510VgnVCM10000009c7648aRCRD

Zahawi RA, Dandois JP, Holl KD, Nadwodny D, Reid JL and Ellis EC. 2015. Using lightweight unmanned aerial vehicles to monitor tropical forest recovery. Biological Conservation 186:287–295.

 

Beyond the Rock: Using Satellite Trackers to Study the Lives of Common Murres

By Stephanie Loredo, Seabird Oceanography Lab, OSU

Photo credit: Seabird Oceanography Lab

Common murres (Uria aalgee) are the most abundant seabird on the Oregon Coast. At least half of the population in the California Current Ecosystem breeds on the Oregon Coast (half a million seabirds). This makes them ecologically important consumers of forage fish, especially during the breeding season when they use state-waters.

While they spend most of their time at sea, murres must come to shore to breed. During this time, they are highly visible by humans as they breed in large masses on rocky islands. While they are not the most agile on land, due to their short and stubby legs, they are actually amazing divers. Their short flipper-like wings help them swim, and they typically reach depths of 30-60m to catch their prey.

Aside from their underwater aviation skills, they make great parents as well. Both parents will incubate and care for their chick – murres only lay one egg a year – until they fledge; once they leave the rock, male murres take full responsibility for their chicks while the moms go on vacation (they worked hard to lay the egg so they need some time to recuperate). After the breeding season, murres leave the rock in large quantities – this is often the last time humans will see them this year in large aggregations from shore.

Despite their omnipresence and importance as a marine predator in Oregon, there is still a lot we don’t know about murres. Where do murres go when they are not breeding? Do they migrate? Where do they feed during the breeding and non-breeding period? What habitat characteristics are associated with feeding areas? By answering these questions, we increase knowledge of murre ecology in Oregon. Moreover, a more comprehensive understanding of the year-round movements of murres aids marine spatial planners take more informed actions on the current decisions regarding offshore renewable energy development. This is what I hope to achieve through my Masters research project at OSU.

Most of what is known about the offshore distribution of murres in Oregon comes from vessel observations. However, vessel data only provide snapshots in time, and not a continuous picture of area-use. Within the Seabird Oceanography Lab (SOL), we are using individual satellite tracking devices to follow the movements of murres associated with the Yaquina Head colony, which is a prominent breeding colony in Oregon located near Newport.

A common murre displaying a satellite tag prior to release.

SOL was able to track 15 common murres associated with the Yaquina Head colony in 2015 and 2016.  These tags were deployed periodically throughout the breeding period and have been successful in tracking birds for up to three months. Thus far, we have tracking data ranging from May to December (only one bird tracked during December).

Tracking data from 2015 and 2016 of murres off the Yaquina Head colony provide an interesting comparison.  In both years, murres experienced warmer ocean conditions, high Bald eagle disturbance rates, and consequently high Western gull egg predation at the colony. Some data also indicate low prey availability.  The combination of all these factors is most likely the reason for the observed reproductive failure at the colony in both years. Tracking data showed that 13 of the 15 birds tagged dispersed from the colony earlier than expected. The maps below summarize the dispersal of birds by year and by time of deployment.

 

Each map (Left: 2015, Right: 2016) illustrates all birds that dispersed from the colony and did not engage in central-place foraging (feeding trips to and from the colony). Sample size: n2015=7, n2016_spring=1, n2016_summer=3.

Most birds made a northward movement and traveled as far north as British Columbia, Canada.  Along their movement north, they used inlets and bays, but one of the most prominent areas used was the Columbia River plume. Birds used the Columbia River mouth area during the summer and fall, with the most time spent there during the summer. Dispersal from the colony was not what we expected; we expected individuals to breed on colony and engage in central-place foraging  (feeding to and from the breeding site) nearshore until mid-August when they usually leave the rock. However, we are still interested in the habitat characteristics of feeding areas and the conditions that led to movement from one feeding area to the next.

Prior to examining habitat associations of murre feeding areas, we must first determine their behavior state at each point location derived from the satellite tags.  After data cleaning and filtering out erroneous locations, we applied a behavioral analysis (Residence in Space and Time method) to determine behaviors associated with each point location. This analysis has allowed us to distinguish between intensive foraging, transiting, and extensive foraging. Extensive foraging locations can be interpreted as a set of locations that are mostly spread out in space, where murres searched for prey. On the other hand, intensive foraging locations can be interpreted as a set of locations that are very close together in space where murres likely found prey, and thus spent more time.

We are finalizing the extraction of environmental data for each point location from satellite data. Once all data are extracted, we can begin analysis for determining what environmental conditions were sought during dispersal and what types of habitats are preferred. Some of the ocean conditions that will be examined are sea surface temperate, wind, upwelling index, and primary net productivity. Some other habitat descriptors we are interested in assessing are substrate, distance to river mouth, salinity, depth, distance to the 200-m isobath, and distance to shore. For now, exploration of data indicates differences in habitat associations by behavior and between seasons.

Sample size means everything in a study like this so I am happy to say that more data is yet to come: SOL plans to deploy 15 more tags during spring and summer of 2017. I am excited to see what the additional tagged murres will do, and whether they will follow a pattern similar to those tracked in 2015 and 2016. However this time around, we will deploy tags as late in the summer/early fall as we can, in hope of acquiring some novel winter data to fill this knowledge gap. If we are successful, we may finally have a better idea of what life is like for common murres during more of the year beyond the rock.

 

Celebrating Hydrothermal Vents!

By Florence Sullivan, MSc Student OSU

40 years ago, in 1977 OSU researchers led an NSF funded expedition to the Galapagos on a hunt for suspected hydrothermal vents. From the 1960s to the mid-1970s, mounting evidence such as (1) temperature anomalies found deep in the water column, (2) conduction heat flow probes at mid ocean ridges recording temperatures much lower than expected, (3) unusual mounds found on benthic mapping surveys, and (4) frequent, small, localized earthquakes at mid oceanic ridges, had the oceanographic community suspecting the existence of deep sea hydrothermal vents. However, until the 1977 cruise, no one had conclusive evidence that they existed.  During the discovery cruise at the Galapagos rift, the PI (principle investigator), Dr. Jack Corliss from OSU, used tow-yos (a technique where you drag a CTD up and down through the water in a zig zag pattern – see gif) to pinpoint the location of the hydrothermal vent plume. The team then sent the Deep Submergence Vehicle (DSV) Alvin to investigate and returned with the first photographs and samples from a hydrothermal vent. While discovery of the vent systems helped answer many questions about chemical and heat fluxes in the deep sea, it generated so many new questions that novel fields of study were created in biology, microbiology, marine chemistry, marine geology, planetary science, astrobiology and the study of the origin of life.

 “Literally every organism that came up was something that was unknown to science up until that time. It made it terribly exciting. Anything that came [up] on that basket was a new discovery,” – Dr. Richard Lutz (Rutgers University)

In celebration of this great discovery, OSU’s College of Earth, Ocean and Atmospheric Sciences sponsored a seminar looking at the past, present, and future of hydrothermal vent sciences. Dr. Robert Collier began with a timeline of how the search for hydrothermal vents began, and a commemoration of all the excellent researchers and collaborations between institutions and agencies that made the discovery possible. He acknowledged that such collaborations are often somewhat tense in terms of who gets credit for which discovery, and that while Oregon State University was the lead of the project, it takes a team to get the work done.  Dr. Jack Corliss proudly followed up with a wonderful rambling explanation of how vent systems work, and a brief dip into his ground breaking paper, “An Hypothesis concerning the relationship between submarine hot springs and the origin of life on Earth.” Published in 1981, with co-authors Dr. John Baross and Dr. Sarah Hoffman, they postulate that the temperature and chemical gradients seen at hydrothermal vents provide pathways for the synthesis of chemical compounds, formation and evolution of ‘precells’ and eventually, the evolution of free living organisms.

Dr. Corliss, Dr. Baross, and Dr. Hoffman were the first to suggest the now popular theory of the origin of life at hydrothermal vents. (click on image to read full paper)

Because of time constraints, the podium was swiftly handed over to Dr. Bill Chadwick (NOAA PMEL/ HMSC CIMRS) who brought us forward to the present day with an exciting overview of current vent research.  He began by saying “at the beginning, we thought, ‘No one has seen one of these systems before, they must be very rare…’ Now, we have found them [hydrothermal vents] in every ocean basin – including the arctic and southern oceans. We just needed to know how to look!”  Dr. Chadwick also reminded us that even 40 years later, new discoveries are still being made. For example, on his most recent cruise aboard the R/V Falkor in December 2016, they found a sulfur chimney that was alternately releasing bubbles of gas (sulfur, CO2 or other, hard to know without sampling) or bubbles of liquid sulfur! Check out the video below:

Some of the goals for this recent cruise included mapping new areas of the Mariana back-arc, and investigating differences in the biological communities between vents in the Mariana trench region (a subduction zone) and vents in the back arc (a spreading zone) to see if geology plays a role in biological community composition.  For some very cool video footage of the expedition and the various dives performed by the brand new ROV SUBastian (because all scientists love puns), check out the Schmidt Ocean Institute youtube channel.

Dr. Chadwick showed this video to highlight results from his last cruise.

Finally, Dr. Andrew Thurber wrapped up the session with some thoughts about hydrothermal vents from the perspective of an ecosystem services model. Even after 40 years of research, there are still many unknowns about these ecosystems.  Individual vent systems are inherently unique due to their deep sea isolation. However, most explored sites have revealed metals and mineral deposits that have generated a lot of interest from commercial sea floor mining companies. Exploitation of these deposits would be an example of ecosystem “provisioning services” (products that are obtained from the ecosystem). Other examples include the biology of the vents as a source of new genetic material, and the thermal and chemical gradients as natural laboratories that could lead to breakthroughs in pharmaceutical research. Cultural services are those non-material benefits that people obtain from an ecosystem. At hydrothermal vents these include new scientific discoveries, educational uses (British children’s television show “The Octonauts,” has several episodes featuring hydrothermal vent creatures), and creative inspiration for artists and others. Dr. Thurber cautions that there are ethical questions to be answered before considering exploitation of these resources, but there is a lot of potential for commercial and non-commercial use of vent ecosystems.

Vent inspired art by Lily Simonson

As an undergraduate at the University of Washington, I spent time as a research assistant in Dr. John Baross’ astrobiology lab. We studied evolutionary pathways of hydrothermal vent viruses and bacteria to inform the search for life on exoplanets such as Jupiter’s moon Europa.  It was very fun and exciting for me to attend this seminar, hear stories from pioneers in the field, and remember the systems I worked on in undergrad.  I may have moved up the food chain a little now, but as we all work on our pieces of the puzzle, it is important for scientists to remember the interdisciplinary nature of our work, and how there is always something more to learn.

 

 

Challenges of fecal hormone analyses (Round 2): finally in Seattle!

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).

Figure 1: View of the Seattle Aquarium.

 

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.

Figure 2: Analytical processes: (A) Sample weighing; (B) Transference of the sample to a glass tube; (C) Result from the performed steps.

 

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.

Figure 3: Analytical processes: (A) Methanol addition; (B) Sample + methanol; (C) Plate shaker; (D) Centrifuge.

 

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.

Figure 4: Analytical processes: (A) Methanol transference; (B) Methanol drying; (C) Water addition.

 

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.

Figure 5: (A) Filling the assay table with the samples to be analyzed; (B) Assay kit to be used; (C) Preparation of the plate; (D) Plate ready to be read.

 

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).

Figure 6: Example of a good parallelism test. The dark blue line indicates the standard curve; the pink line indicates a good parallelism test, showing a parallel displacement; and the ratios in black indicate the dilution factors.
Source: Brown et al. (2005)

 

Figure 7: Examples of bad parallelism tests. The dark blue line indicates the standard curve; the light blue line is an example of no displacement; the pink line is an example of low concentration of the sample; and the green line is an example of non-parallel displacement.
Source: Brown et al. (2005)

 

Figure 8: Example of a good accuracy test while analyzing hormone levels of pregnanediol glucuronide (Pdg) in elephant urine. The graph shows good linearity (R2 of 0.9986) and would allow for accurate concentration calculations.
Source: Brown et al. (2005)

 

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.

 

Cited Literature:

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.

Simple behavior classification of tracking data with residence in space and time

By Rachael Orben PhD., Postdoctoral Scholar in the Seabird Oceanography Lab and the Geospatial Ecology and Marine Megafauna Lab 

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.

24 GPS tracks of grey-headed albatross incubation foraging trips; tracked from Campbell Island, New Zealand.

So how might this method work? First, let’s 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).

p1080393
A thick-billed murre (Uria lomvia), St. Paul Island, Alaska.

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.

murretrack

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 manner than 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.

murretrack_1sec_rst-copy

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?

murretrack_10sec_rst-copy

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). I keep an updated version of the R code, a short guide, an example dataset on a GitHub repository: https://github.com/raorben/RST.

Here is the spaghetti from above (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!  albatrosstracks_rst

How we craft our messages

By: Erin Pickett, MSc

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.

Images of past, present and future conditions (Baldwin & Leemers 2016-Supporting information Fig. S1)

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.

Liberals pro-environmental attitudes remain similar between conditions, while conservatives pro-environmental attitude is higher given a past-focused condition (Baldwin & Lammers 2016, Fig. 2)

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.

Examples of future and past-focused environmental charities (Balwin & Lammers 2016-supporting information Fig. S3)

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.

References:

Baldwin, M., & Lammers, J. (2016). Past-focused environmental comparisons promote proenvironmental outcomes for conservatives. Proceedings of the National Academy of Sciences113(52), 14953-14957.

Feinberg, M., & Willer, R. (2013). The moral roots of environmental attitudes. Psychological Science24(1), 56-62.

Nisbet, M. C., & Mooney, C. (2009). Framing science. Science316.

Reflecting on the graduate school experience

By: Amanda Holdman, MS student, Geospatial Ecology and Marine Megafauna Lab & Oregon State Research Collective for Applied Acoustics, MMI

This Thanksgiving I had a little something extra to be thankful for; two and a half weeks ago I successfully defended my master’s thesis, “Spatio-temporal patterns and ecological drivers of harbor porpoise off the central Oregon Coast”. It’s a good thing too because I think it was starting to turn me into a harbor porpoise. The last month, I was solitary, constantly eating, and I think I was starting to sleep with one hemisphere of my brain, while the other kept working.

In the weeks leading up to the submission of my thesis, I daydreamed about my life on the ‘other side’.  As a means of pushing myself over the final hurdle I envisioned what it would be like to be free of a thesis, to reclaim my weekends, and how relieved I would feel to hand over the culmination of two and a half years of work – and at last here I am:  on the other side, well almost.

The first week after my defense was just about as busy as the weeks leading up to my defense. I spent my time filing paperwork and moving things, packing up my office and house to head back to my home state of Indiana for the holidays, and tying up loose ends in Newport. For the past couple of weeks, I have been finishing up revisions on my thesis and formatting my work for publication, all while starting to look for a new job. After defending my masters I found time to “actually breathe” – I’m still as busy as always but now with a more consistent sleep schedule. The shift from all-research-and-writing-all-the-time has given me time to reflect a bit on what I’ve gained from the graduate school experience and what I know I still want or need to learn from it. Graduate school has supplied me with a tool box of skills that I didn’t realize I was acquiring day to day. Now, however, looking back over the years I realize how much I’ve grown as both a scholar and a person and in more ways than just learning how to craft scientific tweets in less than 140 characters (this really does take some skill).

Perseverance and Diligence

One big thing I learned from graduate school was how to transition from “panic” to “problem solving”. There were endless days of back breaking work that I had nothing to show for and days when I succumbed to imposter syndrome. I learned to pick myself up and solve the problems at hand though and find a way to move forward, sometimes even scratching my original idea to move towards something that worked in the end. That’s life. Things go wrong, plans don’t work out and yet our ability to pick ourselves up and carry on is one of the best skills we have. In graduate school you learn to never give up.

Time Management

I now assume that anyone who has been to graduate school is essentially an expert at multi-tasking. Between running a field season, taking and teaching courses, submitting research proposals, and trying to balance a social life, I didn’t realize how much of a pro I became at juggling many things at once. In other words, gaining a fundamental skill for being a working scientist

Resourcefulness

Graduate school taught me how to find the information I need. Every day I had a moment where I didn’t know an answer. In the beginning, I thought all you had to do was ask, but sometimes the first person you ask doesn’t know the answer either. Over time, I learned to dig through the literature, ask an expert in the field, or my favorite “try several different things and see how they differ”. Once I learned the hard lesson that there isn’t always an easy way out, I had subconsciously created an order of operations to figure it out.

Collaboration (and giving back the help to others who struggle where you once did)

Not many jobs teach us to work with a bunch of different minded people, but grad school does! I learned to work as a team, with scientists within and outside my lab who had personalities different from mine. Graduate school taught me to collaborate as much as possible and, more importantly, help someone with less experience to figure out their coding problems, or help them get their research proposals or publications out. Offering advice or expertise for a certain skill or method when I was busy helped me develop my team-building skills and proved to myself that I had skills to share.

There are good moments within bad moments

When a bad moment presented itself, I learned to focus on the good and recognize the moments that things worked out because I didn’t give up. These included following a bad presentation with a strong one, sparking the interest of collaborators, receiving an award for a conference presentation, or just the simple self-satisfaction of getting an R code to work properly. There are a lot of good moments in grad school, and it became important for me to celebrate them when they happened, but also not to take them for granted because they don’t come as often as the bad ones.

Importance of a strong support system

Unlike a harbor porpoise – I am very social person. Some can get through graduate school without any social interaction or encouragement from others, but there was no way that would have worked for me. Everyone copes with bad moments in graduate school in different ways – so my friends and family were my life-raft, especially those living in Newport. Mental and physical health are important to maintain in graduate school and it was beneficial for me to form a community early to help me through the tough moments. Although friends and family cannot completely relate to your situation (unless maybe they are also a graduate student) they will hear you out, care, listen and pull you out of a slump. Accepting their support and help drastically improved my mental health.

Work smarter, not necessarily harder, and forge your own path

When I look back at my past 2.5 years of graduate school now, I realize how hard I did truly work. I worked nights, weekends and evenings on weekdays. But in my last few months,  I became more competent as my productivity peaked. I learned how to multi-task and plan better – not just in school, but also in my daily life. Graduate programs force you to do unique research, as you can’t write a thesis by reproducing someone else’s work. You have to learn from what others have done and then get creative. Creating something original demands trust in yourself, and avoiding trying to compare yourself to others. Forging your own path can be uncomfortable, but necessary.

I am confident to say that graduate school overall made me a better scientist, and a better person. I value the training and education that I was fortunate enough to receive. It seems everyone starts graduate school with stars in their eyes, and then sometime in the middle we get weighed down by the failures and frustrations of graduate life, and we can fail to remember what brought us here in the first place: Intense curiosity, a desire to learn, and a chance to improve the world. These factors made me opt for this experience and in spite of all the hardships along the way, grad school gave me a set of life skills. So if you are contemplating graduate school, currently working toward a graduate degree, or in a transitional phase of job-seeking or career-changing, I suggest taking a minute to reflect on what you have already, or could gain, from graduate school.

My days as a current GEMM lab member are dwindling down as finish my edits, preparing publications, search for jobs, and rekindle my network – but I look forward to being a long distance cheerleader for the current and future members of the GEMM lab.

When I entered graduate school – one of my committee members told me I would go through the five stages of grief – and she was right – but the end reward was more than worth it.

“Being a graduate student is like becoming all of the Seven Dwarves. In the beginning, you’re Dopey and Bashful. In the middle, you are usually sick (Sneezy), tired (Sleepy), and irritable (Grumpy). But at the end, they call you Doc, and then you’re Happy.”

Good news: You are Brilliant, the Earth is Hiring

By: Erin Pickett, M.S. Student, Oregon State University

GEMM lab UPDATE: Amanda Holdman successfully defended her master’s thesis this week!

Amanda wisely planned her defense date for November 7th, 2016, the day before Election Day. As I anxiously watched the New York Times election forecast needle bounce back and forth, from left to right on Election night, I thought to myself, why didn’t I think of that? If you are unfamiliar with what I am talking about, this “forecast needle” was an animated graphic on the NYT website that bounced constantly all night between the two Presidential candidates. It caused a great deal of unease for those of us that found it difficult to look away. The animation sparked some debate online among bloggers and tweeters, my favorite comment being, “it borders on irresponsible data visualization”. I came to the realization pretty quickly on Tuesday night that despite the outcome of the election, I would still need to turn in my thesis the following week.

Personally, I did not feel motivated to get out of bed on Wednesday. I wasn’t feeling inspired, or overcome with positive thoughts about what my day of thesis writing would bring. Thankfully, here at OSU, we graduate students have good leaders to keep us on track. Wednesday afternoon, we received an encouraging email from our Department Head, Dr. Selina Heppell. I took away two important points from this email. The first: stay positive, and remember that we do great work with great people and that our work matters. Secondly, think about the lessons that we have learned from this election. For those of us that were shocked about who our country has chosen as the next President of the United States, one important lesson is that we need to focus more on engaging people who exist outside of the echo chambers of our scientific communities.

The recent election has left many scientists and environmentalists concerned about what the future political climate will bring in terms of research funding, job opportunities, and environmental protection. More so now than ever it is important to remain positive and hopeful, and to reconsider the way we communicate our research and engage outside communities whose views are unlike our own. Both of these tasks are particularly challenging due to the long list of environmental problems we face. As it turns out, having a hopeful outlook is important for tackling seemingly insurmountable conservation issues, and empowering others to want to do the same (Swaisgood & Sheppard 2010, Garnett & Lindenmayer 2011).

The title of this blog comes from an eloquent commencement speech by Paul Hawken about the importance of remaining optimistic when the data tells us otherwise. While the address was given to the University of Portland class of 2009, I think it is worth reading because it is a relevant and moving reminder of why hope is important.

But, before you read that, take a look at what has been done recently to protect biodiversity around the world-

Photo credit: Mark Sullivan NMFS Permit 10137-07/NOAA

President Obama quadrupled the size of a marine national monument in Hawaii. You can read more about the significance of this monument, called Papahānaumokuākea, in a previous blog of mine.

Photo credit: Northeast U.S. canyons expedition science team and NOAA Okeanos Explorer Program (2013)

Soon after announcing the expansion of Papahānaumokuākea, President Obama established the first marine national monument in the Atlantic. You can read more about the aptly named Northeast Canyons and Seamounts Marine National Monument here.

Photo credit:  Ari Friedlaender

And finally, to top it off, an international body comprised of 24 countries, called the Commission for the Conservation of Antarctic Marine Living Resources, recently came to a consensus to designate a vast portion of the Antarctic’s remote Ross Sea as the world’s largest marine reserve.

 

References

  • Garnett, S. T., & Lindenmayer, D. B. (2011). Conservation science must engender hope to succeed. Trends in Ecology & Evolution, 26(2), 59-60.
  • Swaisgood, R. R., & Sheppard, J. K. (2010). The culture of conservation biologists: Show me the hope!. BioScience, 60(8), 626-630.

 

“Evolution”: a board game review

By Florence Sullivan MSc student, Department of Fish and Wildlife.

Another grad student once told me that in order to survive grad school, I would need three things:

(1) an exercise routine, (2) a pet, and (3) a hobby. My Pilates class on Wednesdays is a great mid-week reminder to stretch. I don’t have a pet, so that advice gets fulfilled vicariously through friends. As for my hobby, I think you’ll find that even when scientists take a break from work, we really don’t get that far away from the subject matter…..

Board games have evolved significantly since the early ‘90s when I grew up on such family staples as Monopoly, Risk, Sorry!, Candyland, and Chutes and Ladders, etc. Now, table-top games tend to fall into three loose categories – “Euro-games” that focus on strategy and economic themes as well as keeping all players in the game until the end, “American-style” that tend toward luck and direct player contact so that not everyone plays until the end, and “Party” that are easy to learn and are often played in large groups as social icebreakers or to provide entertainment.

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A few of my favorite games.

As board games proliferate, we see the use of many themes and often, there are valuable educational lessons included in the game design!  There are militaristic or survival games (Betrayal at the House on the Hill, Dead of Winter), economic and engineering (Settlers of Catan, Istanbul, Ticket to ride, Carcassonne), fantasy and art (Small World, Dixit), cooperative vs competitive (Hanabi, Forbidden Desert vs. 7 Wonders), and some of my favorites – the sciences (Compounded, Bioviva, Pandemic).

Today, let’s talk about my current favorite – Evolution. It is immediately obvious that the game designers responsible are either giant nerds (I use this in the most loving way possible) or have spent some quality time with ecologists.  Not only is the art work beautiful, and the game play smooth, but the underlying mechanics allow serious ecological theories such as ‘predator and prey mediated population cycles’, ‘co-evolution’ and ‘evolutionary arms-races’ to be acted out and easily understood.

Players set up their species around the watering hole, and contemplate their next moves.
Players set up their species (1 green/yellow tile = 1 species) around the watering hole, and contemplate their next moves.

In game play, as in life, the point of the game is to eat – victory is achieved by the player who has managed to ‘digest’ the most food tokens. All players begin with a single species, and with each turn, can either add traits (ie. fat tissue, scavenger, etc.) to the species, increase the body size of a species, gain a population level, or gain additional species.  Next, players take food from a limited, random supply until there is no food left. Species that have not been fed to their full capacity (population levels) will starve, and can even become extinct – much like the reality of environmental cycles.  Finally, all food that has been ‘eaten’ is digested, and the next round begins.

Since a player can never be sure how much food will appear on the watering hole each turn, it is a good strategy to capitalize on traits like foraging which allows a species to take twice as much food every time it feeds.  If your species cooperates with another, that means that it gets to eat every time you feed the first species. A player who combines foraging traits with multiple cooperating species in a “cooperation chain” can quickly empty the watering hole before any other players get a chance.  Much like a species perfectly adapted to its niche in the real world will out compete more generalist species.

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The pack-hunting carnivore on the left can easily take down the fertile defensive herding species in the upper right. The efficient foraging species in the middle is protected by its horns, and cooperates with the next species to the right. The burrowing species is protected from carnivores only as long as it is full (and presumably no longer needs to venture out of its burrow).

One way to avoid the competition for food at the watering hole is to play the carnivore trait.  This species must now consume other species in order to feed itself.  A few caveats; a carnivore must be larger in body size than anything it tries to eat, and can no longer eat plant food as it is an obligate carnivore. As soon as a carnivore appears on the board, the evolutionary arms-race begins in earnest!  Traits such as burrowing, climbing, hard shells, horns, defensive herding and warning calls become vital to survival.  But carnivores can be clever, and apply ambush to species with warning call, or pack-hunting to a species with defensive herding.  In everything, there is a certain balance, and quickly, players will find themselves acting out a classic ‘boom and bust population growth cycle’ scenario, where herbivores go extinct due to low food supply at the watering hole and/or high predation pressure, and carnivores soon follow when there are no un-protected species for them to feed upon.

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A flying creature must first pay the ‘upkeep cost’ of its body size in food, before it can feed its population. Good thing it has the extra cliff-side food source that is only accessible to other species with wings!

An expansion has been released for the game – it is called Flight – and introduces traits such as flight, camouflage, good eyesight, and others.  From an ecologist’s perspective, it fits the original game well both scientifically and thematically.  To achieve flight, a higher price must be paid (in terms of cards discarded) to gain the trait card, and unlike other species, an ‘upkeep cost’ must be gathered in food tokens before the species actually eats any food tokens during the round.  However, flight also gives access to a cliff-side watering hole that is not accessible to earthbound species. This neatly mirrors the real world where flight is an energetically costly activity that also opens new niches.

The next expansion is just arriving in stores, and I can’t wait to play it! It’s called Climate, and adds traits such as nocturnal, claws, and insectivore. Perhaps more exciting though, are the ‘event cards’ which will trigger things like desertification, cold snaps, heatwaves, volcanic eruptions and meteor strikes. A climate tracker will keep track of whether the planet is in an ice age or a warming period, and certain traits will make your species more or less likely to survive – can you guess which ones might be useful in either scenario? I think it will be enormously fun to play through different climate scenarios and see how traits stack and species interactions evolve.  Perhaps this new addition to the game will even cause a new game review in Nature – check out their initial assessment here: http://www.nature.com/nature/journal/v528/n7581/full/528192a.html

Games like evolution are useful thought exercises for students and researchers because they promote discussion of adaptive traits, predator-prey cycles, climate, and ecosystem dynamics as related to our own projects. Watching a story unfold in front of you is a great way to truly understand some of the core principles of ecology (and other subjects). This is especially relevant in the GEMM lab where we continuously ask ourselves why our study species act the way they do? How do they find prey, and how are/will they adapt(ing) to our changing climate?

The five senses of fieldwork

By Leila Lemos, PhD student

 

This summer was full of emotions for me: I finally started my first fieldwork season after almost a year of classes and saw my first gray whale (love at first sight!).

During the fieldwork we use a small research vessel (we call it “Red Rocket”) along the Oregon coast to collect data for my PhD project. We are collecting gray whale fecal samples to analyze hormone variations; acoustic data to assess ambient noise changes at different locations and also variations before, during and after events like the “Halibut opener”; GoPro recordings to evaluate prey availability; photographs in order to identify each individual whale and assess body and skin condition; and video recordings through UAS (aka “drone”) flights, so we can measure the whales and classify them as skinny/fat, calf/juvenile/adult and pregnant/non-pregnant.

However, in order to collect all of these data, we need to first find the whales. This is when we use our first sense: vision. We are always looking at the horizon searching for a blow to come up and once we see it, we safely approach the animal and start watching the individual’s behavior and taking photographs.

If the animal is surfacing regularly to allow a successful drone overflight, we stay with the whale and launch the UAS in order to collect photogrammetry and behavior data.

Each team member performs different functions on the boat, as seen in the figure below.

Figure 1: UAS image showing each team members’ functions in the boat at the moment just after the UAS launch.
Figure 1: UAS image showing each team members’ functions in the boat at the moment just after the UAS launch.

 

While one member pilots the boat, another operates the UAS. Another team member is responsible for taking photos of the whales so we can match individuals with the UAS videos. And the last team member puts the calibration board of known length in the water, so that we can later calculate the exact size of each pixel at various UAS altitudes, which allows us to accurately measure whale lengths. Team members also alternate between these and other functions.

Sometimes we put the UAS in the air and no whales are at the surface, or we can’t find any. These animals only stay at the surface for a short period of time, so working with whales can be really challenging. UAS batteries only last for 15-20 minutes and we need to make the most of that time as we can. All of the members need to help the UAS pilot in finding whales, and that is when, besides vision, we need to use hearing too. The sound of the whale’s respiration (blow) can be very loud, especially when whales are closer. Once we find the whale, we give the location to the UAS pilot: “whale at 2 o’clock at 30 meters from the boat!” and the pilot finds the whale for an overflight.

The opposite – too many whales around – can also happen. While we are observing one individual or searching for it in one direction, we may hear a blow from another whale right behind us, and that’s the signal for us to look for other individuals too.

But now you might be asking yourself: “ok, I agree with vision and hearing, but what about the other three senses? Smell? Taste? Touch?” Believe it or not, this happens. Sometimes whales surface pretty close to the boat and blow. If the wind is in our direction – ARGHHHH – we smell it and even taste it (after the first time you learn to close your mouth!). Not a smell I recommend.

Fecal samples are responsible for the 5th sense: touch!

Once we identify that the whale pooped, we approach the fecal plume in order to collect as much fecal matter as possible (Fig.2).

Figure 2: A: the poop is identified; B: the boat approaches the feces that are floating at the surface (~30 seconds); C: one of the team members remains at the bow of the boat to indicate where the feces are; D: another team member collects it with a fine-mesh net. Filmed under NOAA/NMFS permit #16111 to John Calambokidis).
Figure 2: A: the poop is identified; B: the boat approaches the feces that are floating at the surface (~30 seconds); C: one of the team members remains at the bow of the boat to indicate where the feces are; D: another team member collects it with a fine-mesh net. Filmed under NOAA/NMFS permit #16111 to John Calambokidis).

 

After collecting the poop we transfer all of it from the net to a small jar that we then keep cool in an ice chest until we arrive back at the lab and put it in the freezer. So, how do we transfer the poop to the jar? By touching it! We put the jar inside the net and transfer each poop spot to the jar with the help of water pressure from a squeeze bottle full of ambient salt water.

Figure 3: Two gray whale individuals swimming around kelp forests. Filmed under NOAA/NMFS permit #16111 to John Calambokidis).
Figure 3: Two gray whale individuals swimming around kelp forests. Filmed under NOAA/NMFS permit #16111 to John Calambokidis).

 

That’s how we use our senses to study the whales, and we also use an underwater sensory system (a GoPro) to see what the whales were feeding on.

GoPro video of mysid swarms that we recorded near feeding gray whales in Port Orford in August 2016:

Our fieldwork is wrapping up this week, and I can already say that it has been a success. The challenging Oregon weather allowed us to work on 25 days: 6 days in Port Orford and 19 days in the Newport and Depoe Bay region, totaling 141 hours and 50 minutes of effort. We saw 195 whales during 97 different sightings and collected 49 fecal samples. We also performed 67 UAS flights, 34 drifter deployments (to collect acoustic data), and 34 GoPro deployments.

It is incredible to see how much data we obtained! Now starts the second part of the challenge: how to put all of this data together and find the results. My next steps are:

– photo-identification analysis;

– body and skin condition scoring of individuals;

– photogrammetry analysis;

– analysis of the GoPro videos to characterize prey;

– hormone analysis laboratory training in November at the Seattle Aquarium

 

For now, enjoy some pictures and a video we collected during the fieldwork this summer. It was hard to choose my favorite pictures from 11,061 photos and a video from 13 hours and 29 minutes of recording, but I finally did! Enjoy!

Figure 4: Gray whale breaching in Port Orford on August 27th. (Photo by Leila Lemos; Taken under NOAA/NMFS permit #16111 to John Calambokidis).
Figure 4: Gray whale breaching in Port Orford on August 27th. (Photo by Leila Lemos; Taken under NOAA/NMFS permit #16111 to John Calambokidis).

 

Figure 5: Rainbow formation through sunlight refraction on the water droplets of a gray whale individual's blow in Newport on September 15th. (Photo by Leila Lemos; Taken under NOAA/NMFS permit #16111 to John Calambokidis).
Figure 5: Rainbow formation through sunlight refraction on the water droplets of a gray whale individual’s blow in Newport on September 15th. (Photo by Leila Lemos; Taken under NOAA/NMFS permit #16111 to John Calambokidis).

 

Likely gray whale nursing behavior (Taken under NOAA/NMFS permit #16111 to John Calambokidis):