Tag Archive | elephants

Elles in the night

## I’m currently on a mini-holiday in the Minnesota wilderness (Boundary Waters Canoe Area). As I’ve lately been missing long mornings on the porch watching Serengeti wildlife, and Margaret wrote a recent post on one of the all-time most-watchable animals out there, I thought I’d share a story of a late-night elephant encounter from my first year in the field. I was in the car with Candida, a Lion Project Field assistant, and Philipp Henschel, a lion researcher for Panthera who has spent years working in west Africa, and the man who taught me how to camera trap, when we came across this…#

As we hurtled along the gutted road, we came face to face with a herd of elephants paying their respects to a fallen buffalo. At first, in the murk of night, we thought they huddled around one of their own, and concerned silence fell upon us. Ellies, for as aggressive as they can sometimes be, have earned our admiration and careful respect. They seem to me intelligent and emotional creatures; where they are not persecuted, they tolerate the roar of our passing engine with a casual glance. But they are supposedly nearsighted to the point of legal blindness*.  In heavily hunted areas we are sometimes charged by a protective female, but as we hold our breaths and brace for impact, they stop their charge short and listen…but give up and turn away. If we remain downwind in silence we are invisible…or so we hope.

The elephants tonight are agitated as they mill around the buffalo. Philipp tells us that ellies often investigate death in the forests where he’s worked. In an eerie display of some sort of cognizance, they seem to recognize that something is not right and come to look at fallen creatures. When they come across the bones of one of their own, he says, they pick them up and carry them away. It is sad and scary and moving and beyond my comprehension, what must be going on in the heads of these big, gray, lumbering beasts.

The two tour vehicles that are blocking the watering hole eventually pull away, and the ellies step forward to drink. They cluster close, pressing together side by side. Hesitant lions slowly creep back to reclaim their half-eaten kill, and the matriarch whirls around, her ears flaring, watching the lions in a silent stand-off. The air is still. It is thick with tension and heavy with the severity of the moment. One ill-timed thud against the car window or a frightened squeal from any of us, and we could incited a rampage. Silence is imperative and we hold our breaths as the ellies file past within inches of our landrover.We can almost feel their fear and my heart twists as I wonder what it must be like to stumble blindly through a blurry world, sensing death and its bearers all around you lurking in the hazy shadows and around every corner. As they disappear into the acacias, we hear a long, lumpy-sounding elephant fart and giggle nervously. We can breathe again.

We drive closer to the buffalo carcass and watch the lions return. In the faint starlight, we see that an adult female has already resumed her demolition; her whole head disappears inside the opened belly to rip solid tracts of muscle from the ribcage. We fumble for our headlamps and cameras; I look around optimitistically for an onslaught of hyenas. I have yet to see them challenge a lion kill, and begin to question the feasibility of my research plans. The subadult males pad around our car, their massive paws falling silently in the sandy soil. They are full, and are now studying us. Our windows are open, as always, and we glance around with slight unease – where did the two subadult males go? Suddenly we hear a loud chomp from the back of our vehicle. Fearing that they’ve gone of one of our tires, and hardly in any position to fix a flat, we frantically turn the car ignition and pull a few meters forward. In the sideview mirror, we see a lion trot into the darkness with our plastic tire cover dangling from his teeth. Candida’s jaw drops. We are not quite sure what inspired them to steal such an inedible adornment, but it is late and we have company coming that night. So we chalk the loss up to a casualty of the field…and as we drive home along the corrugated dirt road, we remind ourselves that at least we are better off than the buffalo.

*Elephants do have pretty bad vision, but it’s not as bad as I believed it was on this ominous night at the buffalo kill.

March of the Elephants

When you think of elephants, you may immediately think of their defining characteristics: trunks, big ears, tusks. Or you may think about how they live in large family groups and are very social. You may even think about the story of the blind men and the elephant. You probably don’t think about them as engineers of their ecosystem. But they are.

Elephants are native to the Serengeti ecosystem, but Serengeti elephants were likely all killed off for ivory in the 1800’s. At least, there weren’t any recorded there until the middle of the twentieth century when they started moving back in again. In the 1960’s they migrated in from both the north and the south, and by 1970 there were over 3,000 elephants in the Serengeti. Things got rocky for elephants again in the 1980’s as severe poaching reduced their numbers in Serengeti National Park to around 500. In 1988, elephants were given CITES endangered species status and worldwide trade in ivory was banned. This was good news for Serengeti elephants and their numbers rebounded again into the thousands.

These ups and downs in elephant population have allowed scientists to study the impact elephants have on their environment. I’ve written before about how the rainfall patterns in the Serengeti affect grasses, and about the role that fire plays. Elephants have their greatest impact on trees. Elephants eat both grasses and trees, but depend on trees for food during the dry season.

In the first half of the twentieth century, the number of trees per hectare was slowly declining across the Serengeti. But starting in the 1970’s, the number of trees rapidly increased. Scientists believe that the initial decrease in trees was due to the the disease rinderpest. Rinderpest killed off the majority of Serengeti’s wildebeest, allowing the grass to grow tall, and fueling huge, strong fires. These fires killed most tree seedlings, meaning that as trees died, they were not being replaced. When rinderpest was halted, the wildebeest population exploded, and the wildebeest kept the grass short and the fires smaller, allowing trees to gain a foothold once more.

Okay, but what about elephants? Well, elephants eat trees — especially small, tender saplings and regrowth from trees damaged by fire. In the 1980’s, while poaching was particularly severe on the Tanzanian side of Serengeti (Serengeti National Park), the Kenyan part of Serengeti (Maasai Mara) mounted a strong anti-poaching effort and kept its elephant numbers high. Across the Serengeti, the trees were increasing, but in the Maasai Mara there were also a lot of elephants. It turns out that in the Maasai Mara, the trees didn’t increase like they did across the border in Tanzania where the elephants had been greatly reduced. Instead the high number of elephants in the Maasai Mara is keeping tree numbers down, despite the reduction in fire intensity.

So elephants are key players in maintaining what scientists call “alternative stable states” in the Serengeti. While there are plenty of elephants once again in the Tanzanian part of the Serengeti, they don’t reduce the higher tree numbers; only fire can do that. But on the Kenyan side of the border, tree numbers remain low because elephants there have been continuously eating saplings; the tree population cannot increase because of the constant elephant pressure. The key difference between the two areas is simply their history.

I think the fourth blind man should get extra credit.

The Fourth reached out an eager hand,
And felt about the knee
“What most this wondrous beast is like
Is mighty plain,” quoth he:
“‘Tis clear enough the Elephant
Is very like a TREE!”

Grass

You’ve undoubtedly seen it: Grass. Tall waving grass. Lots of it. From here to the horizon. If you’re itching to get images of animals to classify, the “nothing here” grass images can seem annoying. Some people find the grass images soothing. The animals themselves, well, a lot of them seem to like it.

Some animals find that tall grass is nice for concealing themselves from predators, like these guys:


 
Or this impala:


 
And some animals think the grass is nice for eating, like here:


 
Or here:


 
This post is brought to you by Faulty Cameras that switch unexpectedly to video mode when they’re not supposed to. These Season 5 videos have no sound, but capture some of the movement you don’t get with the photographs, so I thought you might like them.

Some Results from Season 4

I was asked in the comments to last week’s blog post if I could provide some feedback about the results of Season 4. If you felt like you were seeing a lot of “nothing here” images, you’re right: of the 158,098 unique capture events we showed you, 70% were classified as having no animals in them. That left 47,320 with animals in them to classify, and the vast majority of these (94%) contained just one species. Here’s the breakdown of what was in all those images:

Season4

Maybe it won’t surprise you that Season 4 covered 2012’s wet season, when over a million wildebeest, zebra, and Thomson’s gazelle migrate through our study area. I find it interesting that hartebeest are also pretty numerous, but I wonder if it’s because of that one hartebeest that stood in front of the camera for hours on end.

This pie chart is based on the number of what we call “capture events,” which is the set of 1 or 3 pictures you see every time you make a classification. Once a camera has taken a set of pictures, we delay it from triggering again for about a minute. That way we don’t fill up the camera’s memory card with too many repeats of the same animals before we have a chance to replace them. But a minute isn’t a very long time for an animal that has decided to camp out in front of a camera, and so we frequently get sequences of many capture events that are all of the same animal. One of the things we’ll have to do in turning your classifications into valid research results is to figure out how to find these sequences in the data automatically.

Here’s a sequence of an elephant family hanging out around our camera for the night about a year ago. (Hat tip to dms246 who put together a collection of most of these images to answer the concerned question of some classifiers who saw just one image out of the whole sequence: is that elephant dead or just sleeping?)

1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31

If you’re interested in how I made the above pie chart, keep reading. But we’re going to get technical here, so if algorithms don’t interest you, feel free to stop.

Read More…

It begins again.

### I’m traveling to Tanzania currently, about to begin my final field season (which will be Season 6 on Snapshot Serengeti). As usual, I’m running terribly behind getting ready to go – so thought I’d share a blog post I wrote while embarking on Season 2. ###

It Begins Again: Wet Season Survey 2011

As I leave Minnesota, winter seems to be already breaking. Amidst the national mid-winter heatwave, mountains of snow are melting, turning the roads into rivers and the hockey rinks back into lakes. For the third time, I am watching cheesy movies across the atlantic, fast forwarding through day and night, racing the sun eastward across the ocean and winning by 30 lengths like Secretariat in the Belmont Stakes.

Just some of the many casualties. Photo taken by Daniel Rosengren.

Just some of the many casualties. Photo taken by Daniel Rosengren.

Except this doesn’t feel spectacular anymore. I am on my way to Tanzania, once again, with 240 lbs of luggage catapulting around the belly of the plane. My back feels thrown and the plane feels cramped, and the woman sitting next to me snorts and sniffles like some Sesame Street character.

After three weeks of delays, I’m finally heading…home? I’m dreading – just a bit – the madness that awaits me in Serengeti. A solid three weeks behind, I have 200 traps to place in the next 10 days….which happens to be humanly impossible.

See, my research relies primarily on camera traps – remote, automatic cameras that are triggered by heat and motion, attached to trees so that they take pictures of wildlife night and day. On the street they’re known as “hyena bait.” On my street anyway.

Yeah, that’s right. I’ve discovered that hyenas are like big ugly puppies – the world is their chew toy. However, unlike your neighbor’s cute, squirmy blue heeler, hyenas have no responsible owner to say “No! No demolishing the $200 camera trap!” Last year alone, hyenas ate nearly $8,000 in cameras. I would arrive at my excruciatingly selected camera site to find bits and pieces of plastic, the stray LED, a fragment of circuit board…just no camera. Elephants took down about $5,000 in cameras, but with minimal destruction. They typically ripped the offending trap from the tree and flung it out of site. Those cameras usually worked, with some minor case modifications. But the hyena victims? Beyond repair.

Given the abysmal loss rates from the first year of this ambitious (crazy?) camera trapping study, I am now returning to the Serengeti with replacement cameras and heavy duty steel protective cases…which happen to weigh about 1.35 tons apiece. That might be an exaggeration, but the point is that they are very, very heavy. And hopefully hyena-proof.

It is dark outside, though the fancy seat-back TV map says we are smack dab over the Atlantic. I feel like my mind should be racing with plans for my research, or meandering down memory lane – but mostly I am thinking about how good the red wine tastes, and how tired my eyes feel. The night outside seems endless, the world feels far away and frozen in time – like Zach used to do on “Saved by the Bell” – and in my alternate reality I slip guiltlessly into mass-market movies, into staring blankly out the window, the wine wrapping its velvet fingers around my fraying neurons.

I have a million things to do by…yesterday, but my brain is tired and does not want to work. I do not want to think about where on earth I put my hard drive, or the fact that I have not yet filed my taxes despite my imminent disappearance into the bush. I want to fade into the bright, apoplectic flashes of the action movie’s runaway trains or the feel-good underdog story of the horse that could. When I get to Serengeti, it will be a flat-out race against the rains. I want to get my cameras set before the rains keep me hamstrung for days at a time. Today is Feb 19; the rains start at the beginning of March. Can it be done? I guess we’ll see when I get there.

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