Finding the hot spot: incorporating thermal imagery into our whale research

By Leila Lemos and Leigh Torres

A couple weeks ago the GEMM Lab trialed something new in our gray whale research: the addition of a thermal imaging camera to our drone.

For those who do not know what a thermal imaging camera is, it is a device that uses infrared radiation to form an object, and operates in wavelengths as long as 14,000 nm (14 µm). A thermal camera uses a similar procedure as a normal camera, but responds to infrared radiation rather than visible light. It is also known as an infrared or thermographic camera.

All objects with a temperature above absolute zero emit infrared radiation, and thermography makes it possible to see with or without visible light. The amount of radiation emitted by an object intensifies with temperature, thus thermography allows for perception of temperature variations. Humans and other warm-blooded animals are easily detectable via infrared radiation, during the day or the night.

Infrared radiation was first discovered in 1800, by the astronomer Frederick William Herschel. He discovered infrared light by using a prism and a thermometer (Fig.1). He called it the infrared spectrum “dark heat”, which falls between the visible and microwave bands on the electromagnetic spectrum (Hitch 2016).

Figure 1: Astronomer Frederick William Herschel discovers infrared light by using a prism and a thermometer.
Source: NASA, 2012.

 

Around 30 years later it was possible to detect a person using infrared radiation within ten meters distance, and around 50 years later it was possible to detect radiation from a cow at 400 meters distance, as technology became gradually more sensitive (Langley, 1880).

Thermography nowadays is applied in research and development in a variety of different fields in industry (Vollmer and Möllmann 2017). Thermal imaging is currently applied in many applications, such as night vision, predictive maintenance, reducing energy costs of processes and buildings, building and roof inspection, moisture detection in walls and roofs, energy auditing, refrigerant leaks and detection of gas, law enforcement and anti-terrorism, medicinal and veterinary thermal imaging, astronomy, chemical imaging, pollution effluent detection, archaeology, paranormal investigation, and meteorology.

Some of the most interesting examples of its application are:

  • Detection of the presence of icebergs, increasing safety for navigators.
  • Detection of bombs
  • Non-invasive detection of breast cancer (Fig.2)
  • Detection of fire, and detection of fire victims in smoke-filled rooms or hidden under plywood, by the fire departments (Fig.3)
Figure 2: Thermography approved in 1982 to detect breast cancer. Method is able to detect 95% of early stages cancers.
Source: Hitch, 2016.

 

Figure 3: The use of thermal imaging cameras by the fire departments.
Source: MASC, 2017.

 

In environmental research, the thermal imaging camera is an interesting tool used to detect wildlife presence (especially for nocturnal species), to monitor wildlife and detect disease (Fig.4), and to better understand thermal patterns in animals (Fig.5), among others.

Figure 4: Wildlife monitoring: detection of mange infection in wolves of Yellowstone National Park. During winter, wolves infected with mange can suffer a substantial amount of heat loss compared to those without the disease, according to a study by the U.S. Geological Survey and its partners.
Source: Wildlife Research News 2012; USGS 2016.

 

Figure 5: Study on thermal patterns and thermoregulation abilities of emperor penguins in Antarctica.
Source: BBC 2013.

 

Now that thermal cameras are small enough for attachment to drones, we are eager to monitor whales with this device to potentially identify injuries and infections. This non-invasive method could contribute another aspect to our on-going blue and gray whale health assessment work. However, dealing with new technology is never easy and we are working to optimize settings to collect the data needed. Our test flights with the thermal camera were successful – we captured images and retrieved the expensive camera (always a good thing!) – but the whale images were less clear than desired. The camera was able to detect thermal variation between our research vessel and the ocean (Fig. 6: boat and people are displayed as hot coloration (yellow, orange and red tones), while the ocean exhibited a cold coloration (purple). Yet, the camera’s ability to differentiate thermal content of the whale while surfacing from the ocean was less evident (Fig. 7). We believe this problem is due to automatic gain control settings by the camera that essentially continually shifts the baseline temperature in the image so that thermal contrast between the whale and ocean was not very strong, except for those hot blow holes shinning like devil eyes (Fig. 7). We are working to adjust these gain settings so that our next trial will be more successful, and next time we will see our whales in all their colorful thermal glory.

Figure 6: Thermal image of the R/V Ruby captured by a thermal camera flown on a drone by the GEMM Lab on September 09th, 2017.
Source: GEMMLab 2017.
Figure 7. Thermal image of a gray whale captured by a thermal camera flown on a drone by the GEMM Lab on September 09th, 2017. Notice the ‘hot’ color (yellow-orange) of the blow holes indicating the heat within the whale’s body. (Image captured under NOAA/NMFS permit #16111).

 

References

BBC. 2013. In pictures: Emperor penguins’ ‘cold coat’ discovered. Available at: http://www.bbc.co.uk/nature/21669963

Hitch J. 2016. A Brief History of Thermal Cameras. Available at: http://www.newequipment.com/technology-innovations/brief-history-thermal-cameras /gallery?slide=1

Langley SP. 1880. The bolometer. Vallegheny Observatory, The Society Gregory, New York, NY, USA.

MASC. 2017. Thermal Imaging Camera. Available at: https://duckduckgo.com/ ?q=detection+of+victim+fire+department+thermal+camera&atb=v76-7_u&iax=1&ia= images&iai=http%3A%2F%2Fwww.masc.sc%2FSiteCollectionImages%2Fuptown%2F Super_Red_Hot.jpg

NASA. 2012. Beyond the Visible Light. Available at: https://www.nasa.gov/topics/ technology/features/webb-beyond-vis.html

USGS. 2016. Study Shows Cold and Windy Nights Physically Drain Mangy Wolves. Available at: https://www.usgs.gov/news/study-shows-cold-and-windy-nights-physically-drain-mangy-wolves

Vollmer M. and Möllmann KP. 2018. Infrared Thermal Imaging: Fundamentals, research and Applications. Second Edition. Wiley-VCH: Weinheim, Germany.

Wildlife Research News, 2012. Tool: Infrared Monitoring. Available at: https://wildliferesearchnews.wordpress.com/2012/04/24/tool-infrared-monitoring/

Diving Deeper

By Taylor Mock, GEMM Lab intern

Greetings, all!

My name is Taylor Mock. Since February I have been volunteering in the GEMM Lab and am ecstatic to make my online debut as part of the team!

For many years, I had a shallow relationship with Hatfield Marine Science Center. As a Newport native, I would spend mornings and evenings glancing over at the Hatfield buildings while driving over the bridge to and from school. I was always intrigued. Sure, I would hear snippets of research from my peers about what projects their parents were involved in, but the inner workings of the complex mystified me.

Toward the end of my Freshman year in 2012 at Westmont College in Santa Barbara, California, my mom asked me what my summer plans were. I replied with the typical “I don’t know… Get a job?” She insisted that instead of a job I think about getting an internship; experience that will last more than a summer. I inquired through a family friend (because every person in this little community is woven together some way or another) if any internships or volunteer opportunities were available at Hatfield. She pointed me in the direction of the Environmental Protection Agency and thus began my Hatfield volunteering saga. I worked that summer, and the next, at the EPA under the direction of Ted DeWitt and Jody Stecher on denitrification studies in estuarine marshes. That summer provided me a glorious front row seat to field research and a greater understanding of my potential as a person and as a scientist. Now, this experience was marvelous, but I knew shortly after starting that my heart was elsewhere.

It was during my study abroad semester in Belize as part of my internship at the Toledo Institute for Development and Environment (TIDE) that I realized I wanted to work with marine macroorganisms. At TIDE, I engaged in radio telemetry conservation efforts tracking Hicatee (Dermatemys mawii) aquatic turtles. We would spend days on a small boat floating through canals and setting nets in hopes of capturing individuals of this small population to outfit them with radio tracking devices. These would be later used to track foraging, mating, and travel patterns in the region. It was an amazing time, to say the least. I remember waking up on my 21st birthday from my camping hammock and staring up at the lush rainforest above my head with a warm breeze across my face, followed by spending the day in the presence of these glorious creatures. It was heaven. I returned to Westmont the following term and took a Marine Mammal Eco-Physiology course and absolutely fell in love with Cetacea. Yes, I had always been captivated by this clade of beings (and truthfully when I was eight years old had a book on “How to Become a Marine Mammal Trainer”), but this was deeper. Of course, pinnipeds and otters and polar bears and manatees were enjoyable to learn about. There was something about the Cetacea though and how they migrated up and down the coast (just like me!) that I really connected with. My time learning about these animals created an intimate understanding of another group of species that developed into a rich, indescribable empathetic connection. I had to take a couple years away from scholastics and away from biology for health and wellness reasons. One day, though, a couple years after graduating and returning to Newport I rekindled with Jody from the EPA. He asked me if I would like to volunteer under Leigh Torres in the Marine Mammal Institute at HMSC. I do not think I could have possibly said no. I have been enjoying my time in the GEMM Lab ever since!

Though I am available to help anyone with any task they need, the work I do mostly centers around photogrammetry.

Using photogrammetry skills to measure gray whales in the GEMM Lab.

Photogrammetry, essentially, means geo-spatially measuring objects using photographs. What that looks like for me is taking an aerial photograph (extracted from overhead drone video footage) of a whale, running the image through a computer program called “Matlab”, taking a series of measurements from the whale (e.g., tip of the mandible to the notch of the fluke, distance between each tip of the fluke, and several measurements across the midsection of the whale). Several images of individuals are processed in order to find an average set of measurements for each whale.

Final result of the photogrammetry method on a gray whale

You might be wondering, “How can one measure the distance accurately from just a photograph?” I am glad you asked! The drones are outfitted with a barometer to measure the atmospheric pressure and, in turn, altitude. The changing altitudes are recorded in a separate program that is run simultaneously with the video footage. Thus, we have the altitudinal measurements for every millisecond of the drone’s flight. To monitor the accuracy and functionality of the barometer, calibrations are completed upon deployment and retrieval of each drone flight. To calibrate: the initial takeoff height is measured, a board of known length is thrown into the water, the drone will then rise or lower slowly above the board between 10 and 40 m, photographs of the board are then taken from varying altitudes, and are processed in Matlab.

During my time in the GEMM Lab, I have had the pleasure of completing photogrammetry assignments for both Leila on the Oregon Coast gray whale and for Dawn on the New Zealand blue whale projects. These ladies, and the other members of the GEMM Lab, have been so patient and gracious in educating me on the workings of Matlab and the video processing systems. It is a distinct honor working with them and to delight in the astounding nature of these creatures together. Each day I am struck in sheer awe of how beautiful and powerful these whales truly are. Their graceful presence and movement through the water rivals even the most skillful dancer.

Over the last 6 years, I am delighted to say that my relationship with Hatfield has become much deeper. The people and the experiences I have encountered during my time here, especially in the GEMM Lab, have been nothing short of incredible. I am sincerely grateful for this continued opportunity. It fills my soul with joy to engage in work that contributes to the well being of the ocean and its inhabitants.

Thank you, Leigh and all of the GEMM Lab members. I hope to continue volunteering with you for as long as you will have me.

New and old methods in our gray whale field season 2017

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

On June 6th the GEMM Lab officially started the second year of fieldwork of our “Noise Physiology” Project with gray whales along the Oregon coast. To date, we have spent 14 days at sea (12 around the Newport area and 2 in Port Orford, our control area), with a total of 32:31 hrs of effort. In 29 whale sightings of approximately 40 whales we have been able to collect 6 fecal samples for hormonal analysis, to fly the drone 17 times over the whales, to deploy a GoPro 6 times for qualitative prey analysis, and to deploy a light trap 2 times for quantitative prey analysis. While this sounds good, we have only just begun, with our field season extending into October. The graph below displays the sightings and data collection by area.

Figure 1: Sightings and data collection by area and month.

We have added a couple new components to our project this year. First, we are now using a “the light trap”, as mentioned above, to capture zooplankton prey of gray whales. The light trap (Figure 2), designed by our collaborator of Kim Bernard (OSU, College of Earth, Ocean, and Atmospheric Sciences). The light trap is composed of a water jug with a cut-out cone entrance where prey might enter the jug after being attracted by the chem lights we put in the jug. The jug is weighted down to maintain position, but swivels off the drop line by its own floats; and it’s all connected to a surface float.

Figure 2: Components of the light trap.
Source: Leila Lemos

The light trap is left overnight and recovered in the next day. Trapped prey are sieved (Figure 4), stored in properly labeled jars or Ziploc bags, and kept frozen until analysis (Figure 5 and 6) including species identification, community analysis, and caloric content.

Figure 3: Todd Chandler, our research technician, preparing the light trap to be deployed in Port Orford.
Source: Leila Lemos
Figure 4: Collected preys with our light trap being sieved for storage on June 27th.
Source: Dawn Barlow
Figure 5: Kim Bernard proud of the zooplankton sample collected in Newport on June 26th.
Source: Dawn Barlow
Figure 6: Our GEMM Lab intern Alyssa holds the prey sample collected in July 1st.
Source: Leigh Torres

The second component we have added this year is the fixed-location hydrophone (Figure 7) to record acoustic noise data over the entire summer season. Last year we used a temporarily deployed “drifting hydrophone” that only recorded noise data punctually. Because of the fixed hydrophone, this year we will be able to compare our hormone data with a wider range of acoustic data, and improve our analyses.

Figure 7: Joe Haxel, our acoustician, checking the hydrophone in July 14th that was previously deployed in Newport at the beginning of the summer season.
Source: Leila Lemos

We also made our first trip down to Port Orford, our control area, to intensively collect data over only two days (July 5th and 6th). Since Port Orford is a smaller city with reduced vessel traffic, we want to evaluate if whales observed in this area show a reduced stress response when compared to the whales that inhabit the area around Newport and Depoe Bay, where vessel traffic is higher. However, we were not able to collect any fecal sample during this trip to Port Orford, so more trips south to come!

Figure 8: Sharon Nieukirk, our acoustician, Leigh Torres, and Todd Chandler checking on RV Ruby before being lifted into the water at the port of Port Orford on July 5th.
Source: Leila Lemos
Figure 9: Our mascots Pepper and Avery didn’t get to go out in the boat with us, but they enjoyed our trip to Port Orford so much that they couldn’t stay awake on the way back to Newport.
Source: Leila Lemos and Leigh Torres

The other components we used last year such as photo identification (Figure 10), fecal samples (Figures 11 and 12), drones, and GoPros are still being put to use this year. If you want to know more about our Noise Physiology project, check here.

Figure 10: Me in our boat platform waiting for whales to appear to photograph them in July 13th.
Source: Joe Haxel
Figure 11: Joe Haxel collecting a fecal sample in Newport in July 13th.
Source: Leila Lemos
Figure 12: Fecal sample collected in Newport on July 13th.
Source: Leila Lemos

We are progressively spotting more gray whales along the Oregon coast and we will continue our field efforts and data collection until October. So, for now enjoy some photos taken during the last couple of months. Until next time!

Figure 13: Gray whale’s fluke just south of the Yaquina Lighthouse, in Newport, on July 13th.
Source: Leila Lemos
Figure 14: Gray whale breaching just north of the Yaquina Lighthouse, in Newport, on July 9th.
Source: Leila Lemos
Figure 15: Gray whale breaching in Newport, on June 6th.
Source: Leigh Torres

Migrating to higher latitudes

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

On September 10th of 2015 I was catching an airplane to start a whole new phase of my life in Oregon, United States. Many thoughts, many doubts, many fears, many expectations, and one big dream that was about to come true: I was finally going to United States to work with whales.

I am from Rio de Janeiro, Brazil, a big city known for pretty beaches, tropical weather and restless nights. Thus, to arrive in a really small city on the countryside that usually rains for about six months a year was the opposite of what I was always used to. Trying to understand another language and culture differences was also not an easy step.

In addition, taking my first classes was a big challenge. It was hard to understand everything that was being said, but recording and listening to the classes afterwards definitely was what helped me the most. Also, my first meetings and discussions where I needed to explain my thoughts in another language was difficult, but when I look back and I can now see how much I have improved and it is gratifying to know that all of my efforts were worth it.

Feeling welcome was essential to start overcoming all of the difficulties. My advisor Leigh and my lab mates (Florence, Amanda, Rachael, Erin, Dawn and Courtney) always created a friendly atmosphere and I started being more confident over time. I also had amazing and understanding teachers who were patient and helped me along the way. My first roommates Jane and Angie, from US, and the students and teachers from Crossroads (an English group that I attend) made me practice English every day and I started feeling more comfortable about speaking (and also thinking) in English, and they became my “Oregon family” together with new friends I made from different nationalities. Also important were my family and friends back in Brazil that never stopped encouraging and supporting me.

Figure 1: GEMM-Lab, from left to right, starting at the top: Leigh Torres, me, Erin, Amanda, Dawn, Rachael, our interns from 2016 season (Catherine, Cat and Kelli), and Florence.

 

Figure 2: Practicing English at Crossroads.

 

The weather and seasons here are also very different from Brazil. We don’t have cold weather or snow, and we don’t see all of the changes that happen here from season to season. The first season I saw was the fall. Seeing all of the fall colors in the trees for the first time was magical and I can already say that fall is my favorite season here. The winter was a bit cruel for me, not because of the cold or eventually the snow, but because of the rain. There is a saying in my city that “people from Rio de Janeiro do not like gray days” and it is true: my mood changes with weather. However, I did travel a bit around Oregon during winter and got to enjoy the snow, and how fun is to slide in the snow, make snow angels and throw snowballs. The spring starts bringing sunny days after cold months and endless rain. Also all of the flowers around the Corvallis campus are so pretty and colorful. Finally the summer is hot, and in some days it can almost be as hot as Rio de Janeiro. However, I spend summer days in the coast, where the temperature is mild. For me, summer days are synonymous with fieldwork, since gray whales are migrating northbound and becoming resident along the Oregon coast to feed, and this is right when the fun begins!

Figure 3: Different seasons in Oregon: (A) Trees during the fall in Corvallis, (B) Winter in Crater Lake, (C) Spring at OSU campus: my office at Hovland Building, and (D) fieldwork in Port Orford during the summer.

 

I finally saw my first gray whale in July of 2016 and got to dive into all of the methodologies we wanted to apply in this project. I learned how to photograph whales for photo-identification, how to take important notes, how to collect fecal samples for hormonal analysis, and how to fly with a drone for the photogrammetry method.

Figure 4: Learning how to fly with a drone over gray whales.
Source: Florence Sullivan

 

I had to digest a lot of information while trying to equilibrate in the boat and to not get seasick. However, it was so pleasurable to see how my field skills were getting better over time and how close I was to the Pacific marine fauna.

During my master’s degree I worked on toxicology in dolphins, which means working with dead carcasses. I remember telling myself all of the time that I wanted to do something different for my PhD – that I would be involved in a project with live animals. I am very glad I could accomplish that goal. Gray whales, sea lions, seals and a variety of marine birds are just some examples of the great diversity the Pacific Ocean has to offer and I am totally amazed.

Figure 5: Great diversity of the Oregon coast. Source: GEMMLab (Leila Lemos, Leigh Torres and Florence Sullivan)

After months of fieldwork it was time to return to the land and start learning how to work with all of the data we collected. We have amazing collaborators working with us and I have had wonderful opportunities to learn from all of them about the different methods we are applying in our project.

Figure 6: Learning the hormonal analysis technique at the Seattle Aquarium.

 

Thus, after one year and a half in Oregon I can already say that I feel home. The experience as an international student is not easy, but that’s what makes it such a valuable and gratifying experience. It has been a great journey, and I hope to continue to see improvements over time and keep learning throughout this amazing project studying gray whales.

 

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.

 

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.

Challenges of fecal analyses (Round 1)

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

Fieldwork is done for the year and lab analyses just started with some challenges. This is not unexpected since no previous hormonal analysis has been conducted with any gray whale tissue, and whale fecal sample analysis is a relatively new technique. So, I have been thinking, learning, consulting, and creating a methodology as I go along. I am grateful to the expert advice and help from many great collaborators:

  • Kathleen Hunt (Northern Arizona University, AZ, United States)
  • Shawn Larson (Seattle Aquarium, WA, United States)
  • Amy Green (Seattle Aquarium, WA, United States)
  • Rachel Ann Hauser-Davis (Fiocruz, RJ, Brazil)
  • Maziet Cheseby (Oregon State University, OR, United States)
  • Scott Klasek (Oregon State University, OR, United States)

I have learned that an important step before undertaking fecal a hormonal analysis is the desalting process of the samples since salts can interfere in hormonal determinations, leading to false results. In order to remove salt content, each sample was first filtered (Fig. 1A), to remove a majority of the salt water content (Fig. 1B) that is inevitably collected along with the fecal sample. Each sample was then re-suspended in ultra-pure water, to dilute the remaining salt content in a higher water volume (Fig. 1C).

Figure 1: Analytical processes: (A) Filtration of the samples; (B) Result from filtration; (C) Addition of pure water to the samples.
Figure 1: Analytical processes: (A) Filtration of the samples; (B) Result from filtration; (C) Addition of pure water to the samples.

After these steps were completed for each sample, the samples were centrifuged (Fig. 2A) to  precipitate the fecal matter and leave the lighter salt ions in the supernatant (the liquid lying above a solid residue; Fig. 2B). After finishing these two phases, the water was removed with aid of a plastic pippete (Fig. 2C), and I was left with only desalted fecal at the bottom of the tubes (Fig. 2D).

Figure 2: Analytical processes: (A) Samples centrifugation; (B) Result from the centrifugation; (C, D) Results from separating water and sample.
Figure 2: Analytical processes: (A) Samples centrifugation; (B) Result from the centrifugation; (C, D) Results from separating water and sample.

The fecal samples were then frozen at -80°C (Fig. 3A & 3B) and then freeze-dried on a lyophilizer for 2 days to remove all remaining water content (Fig. 3C). Finally, I have what I need: desalted, dry fecal samples, ready for hormone analysis (Fig. 3D).

Figure 3: Analytical processes: (A) Freezing process of the samples; (B) Frozen samples ready to go to the lyophilizer; (C) Samples in the lyophilizer; (D) Final result of the lyophilizing process.
Figure 3: Analytical processes: (A) Freezing process of the samples; (B) Frozen samples ready to go to the lyophilizer; (C) Samples in the lyophilizer; (D) Final result of the lyophilizing process.

Writing this now, this process seems simple, but it was laborious, and took time to find the equipment needed at the right times. The end product is crucial to get a good final result, so my time investment (and my own increased stress level!) was worth it. This type of analysis is very new for marine mammals and our research lab is still in the learning the best methods. Along the way we were unsure of some decisions, some mistakes were made, and we were afraid of losing precious fecal material. But, this is the fun and challenge of working with a new species and new type of sample and, importantly, we have developed a working protocol that should make the process more efficient and reduce our stress levels next time around.

At the end of this sample preparation process, our 53 samples look great and are ready to be analyzed during my training at the Seattle Aquarium. We are also planning to analyze the water that was removed from the samples (Fig. 2D) to see if any hormone leached out from the poop into the water.

Results from this process will aid in future whale fecal hormone studies. Perhaps only the centrifugation step is needed and we can discard the water without losing hormone content. Or, perhaps we need to analyze both portions of the sample and sum the hormones found in each. We shall know the answer when we get our hormone metabolite results. Just another protocol to be worked out as I move ahead with the hormone analysis of these fecal samples. And through all these challenges I keep the end goal of this work in my mind: to learn about the reproductive and stress hormonal variation in gray whales and to link these variations to nutritional status and noise events. Onward!

 

 

 

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):

Olympians in Rio: keep your mouths closed! But what are the resident marine animals to do?

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

August 5th was the Olympic games opening date in Rio de Janeiro, Brazil, the city where I am from. The opening ceremony was a big success and everybody seems to be enjoying the sporting events and all of the news that the city is offering. However, behind all the colors, magic and joy of this big event, Brazilians are very unsatisfied about hosting an event like this while the whole country is simultaneously dealing with a big educational, health, political and economic crisis at the moment.

Unfortunately, the crisis also affects the environment and is consequently affecting athletes that are competing in our “carioca” waters. Guanabara Bay, more specifically, where the sailing competitions are taking place, receive waters from more than 50 rivers and streams, as displayed below.

Figure 1: Hydrographic map of the Guanabara Bay region, Rio de Janeiro, Brazil, showing rivers and streams (in blue) that feed into the Bay.
Figure 1: Hydrographic map of the Guanabara Bay region, Rio de Janeiro, Brazil, showing rivers and streams (in blue) that feed into the Bay.

 

Much of the water is not treated and brings sewage and garbage from upstream (Fig.2). Although the government reports that the pollution index in the Bay conforms to national and international standards, and that the areas where competitions are taking place are clean and present no risk to athlete health, public health experts advise athletes to keep their mouth closed whenever they are in contact with the water, as reported by the Independent newspaper (http://www.independent.co.uk/sport/olympics/2016-rio-olympics-water-feces-athletes -mouth-shut-brazil-a7163021.html). The goal was to clean up 80% of the Bay in time for the Olympic games, however this goal was far from achieved and the “solution” was to install barriers to try to avoid waste and untreated sewage reaching the event area.

Figure 2: Pollution contrasting with the beauty of the Sugar Loaf, one of the main tourist attractions in the city. The photo shows the area where competitions are taking place. Source: http://www.insidethegames.biz/articles/1027142/brazilian-politician-accused-of-undermining-effort-to-clean-guanabara-bay-by-publicity-seeking-jump-into-water
Figure 2: Pollution contrasting with the beauty of the Sugar Loaf, one of the main tourist attractions in the city. The photo shows the area where competitions are taking place.
Source: http://www.insidethegames.biz/articles/1027142/brazilian-politician-accused-of-undermining-effort-to-clean-guanabara-bay-by-publicity-seeking-jump-into-water.

 

Bacteria, fecal coliforms and metals occur in the Bay. Professionals from Oswaldo Cruz Foundation (Fiocruz), one of the world’s main public health research institutions, found a drug-resistant bacterium in the Bay waters, which is resistant to antibiotics and may cause multiple infections (https://www.rt.com/news/214807-brazil-olympic-venue-superbug/). Metals like mercury, one of the most toxic metals, can also be found in the Bay and shows long-term effects on marine life of the ecosystem.

Guanabara Bay used to be part of the migratory route of Southern right whales (Eubalaena australis), but unfortunately we do not see the whales in the area anymore. We also do not see turtles any longer and populations of prawns are extremely reduced. On the other hand, mussels, biological indicators of ambient pollution due to their sessile and filter-feeding habits, are continuously proliferating in the Bay. These individuals can accumulate high pollutant levels and are not safe to eat when present in polluted areas. However, local fishermen persist in eating mussels and fish from the Bay.

The Guiana dolphin (Sotalia guianensis) is the only mammal that still frequents the Bay waters and, while about 400 Guiana dolphins inhabited the region in the 80s, currently there are only 34 individuals (http://www.abc.net.au/news/2016-06-27/rio27s-dolphins-need-olympic-effort-to-survive-toxic-waters/7543544). The project MAQUA, responsible for monitoring the dolphins in the Guanabara Bay, correlated the decline of the population with worsening water quality, fishing and noise, as published in an article in “O Globo”, the main Brazilian newspaper (http://oglobo.globo.com/rio/populacao-de-golfinhos-da-baia-de-guanabara-sofre-reducao-de-90-em-tres-decadas-1-16110633).
In this article they presented pictures of dolphins from the Guiana dolphin population in the Bay, including the unfortunate consequences on human interactions (Fig.3).

Figure 3: Guiana dolphins in Guanabara Bay, Rio de Janeiro. A: some of the remaining individuals of Guiana dolphin population from the Guanabara Bay; B: a dolphin plays with a plastic bag; C: a dolphin that suffered an accident with a nylon yarn when young presents a scar across its whole circumference; D: a dolphin exhibit the absence of the pectoral fin. Source: O Globo, 2015 (http://oglobo.globo.com/rio/populacao-de-golfinhos-da-baia-de-guanabara-sofre-reducao-de-90-em-tres-decadas-1-16110633).
Figure 3: Guiana dolphins in Guanabara Bay, Rio de Janeiro. A: some of the remaining individuals of Guiana dolphin population from the Guanabara Bay; B: a dolphin plays with a plastic bag; C: a dolphin that suffered an accident with a nylon yarn when young presents a scar across its whole circumference; D: a dolphin exhibit the absence of the pectoral fin.
Source: O Globo, 2015 (http://oglobo.globo.com/rio/populacao-de-golfinhos-da-baia-de-guanabara-sofre-reducao-de-90-em-tres-decadas-1-16110633).

 

This dolphin population is living in heavily polluted waters caused solely by human behavior. Although dolphins may distinguish between trash and food, they feed on contaminated fish – a consequence of bioaccumulation.

During my master’s degree at the Oswaldo Cruz Foundation in Rio de Janeiro, I undertook a toxicological analysis of different species of dolphins (Lemos et al. 2013; http://www.sciencedirect.com/science/article/pii/S0147651313003370). We found high levels of different metals, such as mercury and cadmium, in animals along the north coast of Rio de Janeiro. Just like the mussels, dolphins bioaccumulate high pollutant levels in their tissues and organs, primarily via feeding, but also through dermal contact. Metals and other pollutants present in polluted waters, like the Guanabara Bay, enter the food chain and affect multiple trophic levels, compromising health.

Dolphins from the Guanabara Bay are feeding on the same prey as the local fisherman, and act as sentinels of the environment, warning of public health concerns for humans. Just like humans, these dolphins are long-lived and large mammals, but they live every day in these waters and must open their mouths to survive. If we are concerned about human athletes spending a few hours in the water, we should be outraged at the conditions we force marine animals to live in daily in the Rio de Janeiro region. The dolphins have the intrinsic right to live in a non-polluted environment and be healthy.

Unmanned Aircraft Systems: keep your distance from wildlife!

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

Unmanned aircraft systems (UAS) or “drones” are becoming commonly used to observe natural landscapes and wildlife. These systems can provide important information regarding habitat conditions, distribution and abundance of populations, and health, fitness and behavior of the individuals (Goebel et al. 2015, Durban et al. 2016).

The benefits for the use of UAS by researchers and wildlife managers are varied and include reduced errors of population estimations, reduced observer fatigue, increased observer safety, increased survey effort, and access to remote settings and harsh environments (Koski et al. 2010, Vermeulen et al. 2013, Goebel et al. 2015, Smith et al. 2016). Importantly, data gathered from UAS can provide needed information for the conservation and management of several species. Although it is often assumed that wildlife incur minimal disturbance from UAS due to the reduced noise compared to traditional aircraft used for wildlife monitoring (Acevedo-Whitehouse et al. 2010), the impacts of UAS on most wildlife populations is currently unexplored.

Several studies have tried to comprehend the effects of UAS flights over animals and so far there is no evidence of behavioral disturbance. For instance Vermeulen et al. (2013) conducted a study where authors observed a group of elephants’ reaction or warning behavior while a UAS passed ten times over the individuals at altitudes of 100 and 300 meters, and no disturbance was recorded. Furthermore, a study conducted by Acevedo-Whitehouse et al. (2010) reported that six different species of large cetaceans (Bryde’s whale, fin whale, sperm whale, humpback whale, blue whale and gray whale) did not display avoidance behavior when approached by the UAS for blow sampling, suggesting that the system caused minimal distress (negative stress) to the individuals.

However, the fact that we cannot visually see an effect in the animal does not mean that a stress response is not occurring. A study analyzed the effects of UAS flights on movements and heart rate responses of American black bears in northwestern Minnesota (Ditmer et al. 2015). It was observed that all bears, including an individual that was hibernating, responded to UAS flights with increased heart rates (123 beats per minute above the pre-flight baseline). In contrast, no behavioral response by the bears was recorded (Figure 1).

By Leila Lemos, Ph.D. Student, Department of Fisheries and Wildlife, OSU Unmanned aircraft systems (UAS) or “drones” are becoming commonly used to observe natural landscapes and wildlife. These systems can provide important information regarding habitat conditions, distribution and abundance of populations, and health, fitness and behavior of the individuals (Goebel et al. 2015, Durban et al. 2016). The benefits for the use of UAS by researchers and wildlife managers are varied and include reduced errors of population estimations, reduced observer fatigue, increased observer safety, increased survey effort, and access to remote settings and harsh environments (Koski et al. 2010, Vermeulen et al. 2013, Goebel et al. 2015, Smith et al. 2016). Importantly, data gathered from UAS can provide needed information for the conservation and management of several species. Although it is often assumed that wildlife incur minimal disturbance from UAS due to the reduced noise compared to traditional aircraft used for wildlife monitoring (Acevedo-Whitehouse et al. 2010), the impacts of UAS on most wildlife populations is currently unexplored. Several studies have tried to comprehend the effects of UAS flights over animals and so far there is no evidence of behavioral disturbance. For instance Vermeulen et al. (2013) conducted a study where authors observed a group of elephants’ reaction or warning behavior while a UAS passed ten times over the individuals at altitudes of 100 and 300 meters, and no disturbance was recorded. Furthermore, a study conducted by Acevedo-Whitehouse et al. (2010) reported that six different species of large cetaceans (Bryde’s whale, fin whale, sperm whale, humpback whale, blue whale and gray whale) did not display avoidance behavior when approached by the UAS for blow sampling, suggesting that the system caused minimal distress (negative stress) to the individuals. However, the fact that we cannot visually see an effect in the animal does not mean that a stress response is not occurring. A study analyzed the effects of UAS flights on movements and heart rate responses of American black bears in northwestern Minnesota (Ditmer et al. 2015). It was observed that all bears, including an individual that was hibernating, responded to UAS flights with increased heart rates (123 beats per minute above the pre-flight baseline). In contrast, no behavioral response by the bears was recorded (Figure 1).
Figure 1: (A) Movement rates (meters per hour) of an adult female black bear with cubs prior to, during, and after a UAS flight (gray bar); (B) The corresponding heart rate (beats per minute) of the adult female black bear. Source: Modified from Figure 1 from Ditmer et al. 2015.

 

Therefore, behavioral analysis alone may not be able to describe the complete effects of UAS on wildlife, and it is important to consider other possible stress responses of wildlife.

Regarding marine mammals, only a few studies have systematically documented the effects of UAS on these animals. A review of these studies was produced by Smith et al. (2016) and the main factors influencing behavioral disturbance were identified as (1) noise and visual stimulus (from the UAS or its shadow), and (2) flight altitude of the UAS. Thus, studies that approach marine mammals closely with UAS (e.g., blow sampling in cetaceans) should be closely monitored for behavioral reactions because the noise level and visual stimulus will likely be increased.

Fortunately, when UAS work is applied to cetaceans and sirenians (manatees and dugongs) the air-water interface acts as a barrier to sound so these animals are unlikely to be acoustically disturbed by UAS. However, acoustic detection and response are still possible when an animal’s ears are exposed in the air during a surfacing event.

The best way to minimize stress responses in wildlife is to use caution while operating UAS at any altitude. According to National Oceanic and Atmospheric Administration (NOAA), “UAS can also be disruptive to both people and animals if not used safely, appropriately, or responsibly”. Therefore, since 2012, the Federal Aviation Administration (FAA) has required UAS operators in the United States to have a certified and registered aircraft, a licensed pilot, and operational approval, known as Section 333 Exemption (Note: in late August 2016, the 333 will be replaced by a revision to part 107). These authorizations require an air worthiness statement or certificate and registered aircraft. Public entities, like Oregon State University, operate under a certificate of authorization (COA.) As a public entity OSU certifies its own aircraft and sets standards for UAS operators. These permit requirements discourage illegal operations and improves safety.

Regarding marine mammals, all UAS operators should also be aware of The Marine Mammal Protection Act (MMPA) of 1972. This law makes it illegal to harass marine mammals in the wild, which may cause disruption to behavioral patterns, including, but not limited to, migration, breathing, nursing, breeding, feeding, or sheltering. A close UAS approach has the potential to cause harassments to marine mammals, thus federal guidelines recommend keeping a safe distance from these animals in the wild. The required vertical distance is 1000 ft for most marine mammals, but increases for endangered animals such as the North Atlantic right whales with a required buffer of 1500 ft (http://www.nmfs.noaa.gov/pr/uas.html). Therefore, NOAA evaluates all scientific research that use UAS within 1000 ft of marine mammals in order to ensure that the benefits outweigh possible hazards. NOAA distributes research permits accordingly.

Of course, with new technology the rules are always changing. In fact, last week the Department of Transportation (DOT) and the FAA finalized the first operational rules for routine commercial use of small UAS. These new guidelines aim to support new innovations in order to spur job growth, advance critical scientific research and save lives, and are designed to minimize risks to other aircraft and people and property on the ground. These new regulations include several requirements (e.g., height and speed restrictions) and hopefully allow for a streamlined system that enables beneficial and exciting wildlife research.

For my PhD project we are using UAS to collect aerial images from gray whales in order to describe behavioral patterns and apply a photogrammetry methodology. Through these methods we will determine the overall body condition and health of the individuals for comparison to variable ambient ocean noise levels. This project is conducted in collaboration with the NOAA Pacific Marine Environmental Lab.

Since October 2015, we have conducted 31 over-flights of gray whales using our UAS (DJI Phantom 3) and no behavioral disturbance has been observed. When over the whale(s) we generally fly between 25 and 40 m above the animals. We have a FAA certified UAS operator and fly under our NOAA/NMFS permit 16111. Prior to each flight we ensure that the weather conditions are safe, the whales are behaving normally, and that no on-lookers from shore or other boats will be disturbed.

Here is a video showing the launch and retrieval of the UAS system, our research vessel, the surrounding Oregon coastline beauty and gray whale individuals. The video includes some interesting footage of a gray whale foraging over a shallow reef, indicating that this UAS flight did not disturb the animal’s natural behavior patterns.

We all have the responsibility to help keep wildlife safe. Here in the GEMM Lab, we commit to using UAS safely and responsibly, and aim to use this new and exciting technology to continue our efforts to better protect and understand marine mammals.

 

References

Acevedo‐Whitehouse K, Rocha‐Gosselin A and Gendron D. 2010. A novel non‐invasive tool for disease surveillance of free‐ranging whales and its relevance to conservation programs. Anim. Conserv. 13(2):217–225.

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