Space and time
If you are a nerd like me, the sheer magnitude of questions that can be addressed with Snapshot Serengeti data is pretty much the coolest thing in the world. Though, admittedly, the jucy lucy is a close second.
The problem with these really cool questions, however, is that they take some rather complicated analyses to answer. And there are a lot of steps along the way. For example, ultimately we hope to understand things like how predator species coexist, how the migration affects resident herbivores, and how complex patterns of predator territoriality coupled with migratory and resident prey drive the stability of the ecosystem… But we first have to be able to turn these snapshots into real information about where different animals are and when they’re there.
That might sound easy. You guys have already done the work of telling us which species are in each picture – and, as Margaret’s data validation analysis shows, you guys are really good at that. So, since we have date, time, and GPS information for each picture, it should be pretty easy to use that, right?
Sort of. On one hand, it’s really easy to create preliminary maps from the raw data. For example, this map shows all the sightings of lions, hyenas, leopards, and cheetahs in the wet and dry seasons. Larger circles mean that more animals were seen there; blank spaces mean that none were.
And it’s pretty easy to map when we’re seeing animals. This graph shows the number of sightings for each hour of the day. On the X-axis, 0 is midnight, 12 is noon, 23 is 11pm.
So we’ve got a good start. But then the question becomes “How well do the cameras reflect actual activity patterns?” And, more importantly, “How do we interpret the camera trap data to understand actual activity patterns?”
For example, take the activity chart above. Let’s look at lions. We know from years and years of watching lions, day and night, that they are a lot more active at night. They hunt, they fight, they play much more at night than during the day. But when we look at this graph, we see a huge number of lion photos taken between hours 10:00 to 12:00. If we didn’t know anything about lions, we might think that lions were really active during that time, when in reality, they’ve simply moved 15 meters over to the nearest tree for shade, and then stayed there. Because we have outside understanding of how these animals move, we’re able to identify sources of bias in the camera trapping data, and account for them so we can get to the answers we’re really looking for.
So far, shade seems to be our biggest obstacle in reconciling how the cameras see the world vs. what is actually going on. I’ve just shown you a bit about how shade affects camera data on when animals are active – next week I’ll talk more about how it affects camera data on where animals are.
Hard to find a better place to nap…
Drumroll, please
If you’ve been following Margaret’s blogs, you’ve known this moment was coming. So stop what you’re doing, put down your pens and pencils, and open up your internet browsers, folks, because Season 5 is here!
It’s been an admittedly long wait. Season 5 represents photos from June – December 2012. During those six months I was back here in Minnesota, working with Margaret and the amazing team at Zooniverse to launch Snapshot Serengeti; meanwhile, in Serengeti, Stanslaus Mwampeta was working hard to keep the camera trap survey going. I mailed the Season 5 photos back as soon as possible after returning to Serengeti – but the vagaries of cross-continental postal service were against us, and it took nearly 5 months to get these images from Serengeti to Minnesota, where they could be prepped for the Snapshot interface.
So now that you’ve finally kicked the habit, get ready to dive back in. As with Season 4, the photos in Season 5 have never been seen before. Your eyes are the first. And you might see some really exciting things.
For starters, you won’t see as many wildebeest. By now, they’ve moved back to the north – northern Serengeti as well as Kenya’s Masaai Mara – where more frequent rains keep the grass long and lush year-round. Here, June marks the onslaught of the dry season. From June through October, if not later, everything is covered in a relentless layer of dust. After three months without a drop of rain, we start to wonder if the water in our six 3,000 liter tanks will last us another two months. We ration laundry to one dusty load a week, and showers to every few field days. We’ve always made it through so far, but sometimes barely…and often rather smelly.
You might see Stan
Norbert
And occasionally Daniel
Or me
Checking the camera traps.
But most excitingly, you might see African wild dogs.
photo nabbed from: http://en.wikipedia.org/wiki/File:LycaonPictus.jpg
Also known as the Cape hunting dog or painted hunting dog, these canines disappeared from Serengeti in the early 1990’s. While various factors may have contributed to their decline, wild dog populations have lurked just outside the Serengeti, in multi-use protected areas (e.g. with people, cows, and few lions) for at least 10 years. Many researchers suspect that wild dogs have failed to recolonize their previous home-ranges inside the park because lion populations have nearly tripled – and as you saw in “Big, Mean, & Nasty”, lions do not make living easy for African wild dogs.
Nonetheless, the Tanzanian government has initiated a wild dog relocation program that hopes to bring wild dogs back to Serengeti, where they thrived several decades ago. In August 2012, and again in December, the Serengeti National Park authorities released a total of 29 wild dogs in the western corridor of the park. While the release area is well outside of the camera survey area, rumor has it that the dogs booked it across the park, through the camera survey, on their journey to the hills of Loliondo. Only a handful of people have seen these newly released dogs in person, but it’s possible they’ve been caught on camera. So keep your eyes peeled! And if you see something that might be a wild dog, please tag it with #wild-dog!! Happy hunting!
Living with lions
A few weeks ago, I wrote about how awful lions are to other large carnivores. Basically, lions harass, steal food from, and even kill hyenas, cheetahs, leopards, and wild dogs. Their aggression usually has no visible justification (e.g. they don’t eat the cheetahs they kill), but can have devastating effects. One of my main research goals is to understand how hyenas, leopards, cheetahs, and wild dogs survive with lions. As I mentioned the other week, I think the secret may lie in how these smaller carnivores use the landscape to avoid interacting with lions.
Top predators (the big ones doing the chasing and killing) can create what we call a “landscape of fear” that essentially reduces the amount of land available to smaller predators. Smaller predators are so afraid of encountering the big guys that they avoid using large chunks of the landscape altogether. One of my favorite illustrations of this pattern is the map below, which shows how swift foxes restrict their territories to the no-man’s land between coyote territories.
A map of coyote and swift fox territories in Texas. Foxes are so afraid of encountering coyotes that they restrict their territories into the spaces between coyote ranges.
The habitat inside the coyote territories is just as good, if not better, for the foxes, but the risk of encountering a coyote is too great. By restricting their habitat use to the areas outside coyote territories, swift foxes have essentially suffered from habitat loss, meaning that they have less land and fewer resources to support their population. There’s growing evidence that this effective habitat loss may be the mechanism driving suppression in smaller predators. In fact, this habitat loss may have larger consequences on a population than direct killing by the top predator!
While some animals are displaced from large areas, others may be able to avoid top predators at a much finer scale. They may still use the same general areas, but use scent or noise to avoid actually running into a lion (or coyote). This is called fine-scale avoidance, and I think animals that can achieve fine-scale avoidance, instead of suffering from large-scale displacement, manage to coexist.
The camera traps are, fingers crossed, going to help me understand at what scale hyenas, leopards, cheetahs, and wild dogs avoid lions. My general hypothesis is that if these species are generally displaced from lion territories, and suffer effective habitat loss, their populations should decline as lion populations grow. If instead they are able to use the land within lion territories, avoiding lions by shifting their patterns of habitat use or changing the time of day they are active, then I expect them to coexist with lions pretty well.
So what have we seen so far? Stay tuned – I’ll share some preliminary results next week!
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Map adapted from: Kamler, J.F., Ballard, W.B., Gilliland, R.L., and Mote, K. (2003b). Spatial relationships between swift foxes and coyotes in northwestern Texas. Canadian Journal of Zoology 81, 168–172.
All in the name of science
Today’s guest blogger is Lucy Hughes. Lucy lived and worked on a private nature reserve in South Africa for four years, carrying out field research that included a camera-trap study into the reserve’s leopard population and twice monthly bird surveys for Cape Town University’s Birds in Reserves Project (BIRP).
Arrhhh, that really hurts! A three inch thorn had just penetrated my, admittedly inadequate, footwear and was stuck deep in the sole of my foot. Thorns are a serious hazard of camera trap placement in the South African bushveld where plants with thorns or hooks seem to make up about 90% of species.
My colleague Michelle ran back to the landy to get a first aid kit whilst I set about extracting the thorn, there seemed to be an awful lot of blood. I watched the path eagerly for Michelle’s return but as she got near she seemed to slow down and as she opened her mouth to speak I knew exactly what she was going to say. “Luce, if it’s not too painful, what about spreading your blood around a bit?”
Callous as it may seem it wasn’t a bad idea. We had been having trouble with capturing clear night shots of leopards. They always seem to be in a hurry and the shots we had were often blurry making it impossible to id the individuals. We needed a way to get the leopards to pause for a second or two in shot of the camera trap.
We had been advised that scent was the answer and were experimenting with various different ones and now it seemed human blood was to be the next test. I dutifully hobbled out in front of the camera and scraped my bleeding foot around on a nice flat rock Michelle had procured, wondering about the sensibleness of using human blood as bait for a predator. My slight discomfort was all in the name of science.
In the end it didn’t work, It rained a couple of nights later and my efforts where washed away. We never did find the perfect scent. We were told that tinned sardines worked wonders as well as catnip and perfume. We tried them all. It seems our cats where immune to these. The only thing that stopped them in their tracks was the scent of other leopards. I did learn however that the scent of tinned sardines was particularly interesting to giraffe of all animals. My method was to bury a plastic cup up to its rim in sand and put a blob of sardines in the cup. Now you would have thought that giraffe would have walked on by but as the picture below testifies, giraffe just have to take a closer look. You always learn something new!
Big, Mean, & Nasty
I recently gave a talk at the Arusha-based Interpretive Guide Society – a really cool group of people interested in learning more about the natural history of Tanzania’s places and animals. I’ve taken a few clips from the presentation that describe in a bit more detail how lions bully their competitors.
Looking at the photos above (all nabbed from the internet), how many of you would like to be a wild dog? A leopard? A cheetah? There’s no doubt about it – lions are big, and mean and nasty. If you are any other carnivore species in the Serengeti – or across Africa, lions chase you, steal your food, even kill you. So what do you do? How do you survive? That’s essentially what my dissertation seeks to answer. How smaller “large carnivores” – hyenas, leopards, cheetahs, and wild dogs — live with lions. Under what circumstances do they persist? Under what circumstances do they decline or even disappear?
There are a handful of ways in which these species interact, but what I’m most interested in is aggression and it’s repercussions. As the above pictures suggest, lions tend to dominate aggressive interactions.
The relationship between lions and hyenas is one that has wormed its way into the public psyche through nature documentaries such as “Eternal Enemies.” While such movies play up the frequency of such interactions, they certainly do happen. Lions not only kill a number of hyenas, but steal their hard-won kills. Dispel any notion of lions as some noble hunter — they in fact steal a lot of their food from other carnivores. In fact, research from Kay Holekamp’s group in Masaai Mara indicates that lions can suppress hyena populations just because they steal food from them! It’s actually a similar story for wild dogs – lions kill wild dogs too, but since wild dogs expend so much energy hunting, that if lions steal just a small fraction of the food that wild dogs catch, wild dogs simply cannot recover. They would have to hunt for more hours than there are in a day to make up for this caloric loss.
It doesn’t stop there. We don’t know how much food lions steal from cheetahs or leopards. We also don’t know how often lions kill leopards, but lions kill cheetah cubs left and right. Studies from Serengeti indicate that lions may be responsible for up to 57% of cheetah cub mortality!
So how do hyenas, wild dogs, leopards, and cheetahs survive? Well, that’s what I’m trying to figure out. But what I can tell you is that not all of these smaller carnivores sit back and take their beating quietly. Take hyenas. They’re about 1/3 the size of a lion, but they live in groups. Big groups. Much bigger groups than lions. And if there are no male lions around, if hyenas have strength in numbers, they can steal food from female lions, and even kill their cubs. While leopards don’t live in groups, they can easily kill (and eat!) a lion cub that has been hidden while mom is away hunting.
Unfortunately, what we don’t know is whether this reciprocal aggression by leopards and hyenas has any measurable affect on lion populations, and whether it’s this aggression that allows hyenas and leopards to coexist with lions. The cameras behind Snapshot Serengeti will provide the first-ever map of leopard and hyena distributions within the long-term lion study area – by comparing lion reproductive success (which we know from >45 years of watching individually identified animals) to leopard and hyena distributions, we can see if lions do better or worse in areas with lots of hyenas or leopards – and whether this is due to getting less food or producing fewer cubs.
What about cheetahs and wild dogs? Even though wild dogs, like hyenas, live in groups, there’s no evidence that this helps them defend themselves or their kills against lions. And cheetahs, well, there’s no record of them killing lion cubs, but who knows?
So how do these guys live with lions? To be honest, wild dogs don’t tend to do very well in places with lots of lions. In fact, it’s generally believed that wild dogs have failed to recolonize Serengeti, despite living *just* a few km from the border, because lion populations are so high. For a long time, researchers and conservationists believed that cheetahs also couldn’t survive in places with lots of lions – but that perception is beginning to change, due, in part, to data coming in from Snapshot Serengeti! It seems that cheetahs not only do just fine in reserves with lots of lions, but use the same areas within the park as lions do. I have a sneaking suspicion that how cheetahs use the habitat with respect to lions, how they avoid encountering lions even though they’re in the same places, holds the key to their success. Avoidance, combined with habitat that makes avoidance possible (read: not the short grass Serengeti plains you see below).
I’ll write more about avoidance and habitat another day. In fact, I’m currently revising a paper for a peer-reviewed journal that addresses how cheetahs and wild dogs differ in the ways they avoid lions – if accepted, it will be the first appearance of Snapshot Serengeti data in the scientific literature! I’ll keep you posted…
Data-palooza
You might remember the Kibumbu pride from their rather gruesome encounter with a leopard. But probably not – that was a long time ago.
They now have a new claim to fame. As of April 22, 2013, the Kibumbu lions became the first Serengeti pride to bear a GPS collar. GPS collars are cool, but if you are a nerd like me, and trying to calibrate 225 camera traps against the known reality of animal movements, GPS collars are really [expletive deleted] cool.
Daniel collaring a study lion
With regular old radio-collars, we have to get out in the field, driving (seemingly aimlessly to bystanders) in circles on hills until we get a signal in the direction of a given lion pride. With 26 prides being monitored now, we get to each pride about once a week. But with GPS collars, the data comes to US. On it’s own. EVERY HOUR. I can tell you where the lions are without ever leaving my hyena-chewed, baboom-mangled armchair. Data of this richness are simply impossible to get otherwise. I tried a few “all-night follows” – trying to serve as a living GPS collar. Trying to figure out why, when lions are lurking 300 meters from a camera trap, they don’t appear in it. I usually fall asleep by 9pm. Apparently I don’t make a very good GPS collar.
You might wonder why on earth we don’t have 26 GPS collars, instead of 1. Unfortunately, they are expensive (read >$5,500 a pop), and the battery life doesn’t last as long as regular old VHF collars, meaning we would have to dart lions more often – which is a stress that we like to minimize. But Ingela Janssen had an extra collar from her conservation work in the Ngorongoro Conservation Area, and the chance of calibrating camera trap captures against hourly lion movements was too good to pass up!
Here’s the first map of Kibumbu’s movements. The first position came in at 6pm on April 22, and the last was recorded on the 23rd at 9pm. Since lions are nocturnal, we take one position every hour from 6pm to 7am, and then one position during the day (at noon). You can see from the lines that lions can move quite a ways without actually getting very far.
Kibumbu’s first GPS recorded movements
And here’s their latest map.
And the last few weeks…
I realize that these graphics don’t give you any sense of where in the study area the lions are. Until I figure out how to work some really cool magic with Google Earth, here’s a map of where the cameras are. You can see from Kibumbu’s maps that they are hanging out along a (sometimes dry) river – the Ngare Nanyuki – which I’ve circled in red on this camera layout map.
Camera Traps – Ngare Nanyuki River circled
The GPS collar won’t show up until Season 6 camera photos — but it looks a bit different from our normal collars with two big lumps instead of one:
Vectronic GPS collar – stock image
So keep your eyes peeled!
Spot that leopard!
Today’s guest blogger is Lucy Hughes. Lucy lived and worked on a private nature reserve in South Africa for four years, carrying out field research that included a camera-trap study into the reserve’s leopard population and twice monthly bird surveys for Cape Town University’s Birds in Reserves Project (BIRP).
Trying to discover how many individual leopards used a reserve in South Africa was challenging work in more ways than one. Unlike the Serengeti Lion Project’s (SLP) 200-odd camera traps, I could count ours on one hand. That said the study area was much smaller at around 2,500 hectares. The technique was also very different. Whereas the SLP is trying to get a snapshot of animal interaction over a vast area I was interested in individual animals, so setting the camera traps up systematically on a grid basis was not the best option. Instead, to make best use of our limited camera traps, I selected sites that I thought a leopard was most likely to pass.
These sites fell into two categories, the survey sites and the random event sites. Based on recent tracks and scats on game trails and roads, the cameras were moved around the reserve on a regular basis in an attempt to survey the whole area. One or two cameras were reserved for the random events: a fresh kill, old carcass, or hunches about certain water holes or koppies (rocky hills).
My job was to trundle around the reserve, mostly on foot, searching for signs of leopard. Looking for tracks and scats on the network of sand roads was easy and for the most part it seemed these big cats do love a nice clear road to walk down. Wandering down a dry river bed following a set of tracks idly wondering if the leopard is asleep in one of the big Marula trees is one thing, but suddenly realizing that the pug marks seem to have doubled in size and that you are hot on the trail of two lions jolts you to a stop. Finding signs off these roads was a little harder, the substrate of the game trails was often tangled with grasses and small thorny bushes and picking up tracks was virtually impossible.
Half an eye was always on the sky watching for vultures. Their activity often led to carcasses but it was the sense of smell that served best. The smell of rotting carcasses is fairly potent and travels far and my nose became super sensitive to the whiffs. Unfortunately not having the skills of a bloodhound I would flounder around in the bush turning this way and that trying to pin down the source of the smell.
Setting up a camera trap on a dead wildebeest
Other than spending just a little too much time around dead things, camera-trapping carcasses lead to some great data. One surprise was just how often kills seemed to be ‘shared’. The following two shots from the same eland kill highlight this. You can see even without comparing spot patterns that these two leopards are different.
Female 1
Male 3
The first is a young female and the second is the reserve’s dominant male so it’s hardly surprising that he has stolen her meal. At other kills, though, we had various combinations of leopard visitors including three different adult males within two nights to the same zebra kill. The fact that the leopards stayed put in front of the cameras, munching, meant we managed to get shots from every angle, which helped a lot in putting together ID charts. At no time did we tie down any of the carcasses so clearly the leopards where not fazed by the cameras.
This following shot shows a jackal at the same eland kill. The leopards on this reserve where under very little pressure from lions, which only passed through occasionally. They hardly ever resorted to stashing kills up trees as leopards in areas of high lion density would.
Jackal at eland kill
This meant that many smaller mammals took advantage of the leftovers. Other than the obvious spotted hyena, we recorded brown hyena, side-striped and black-backed jackal, honey badger, civet, bush pig, and mongoose. This following shot looks harmonious, but the series shows that the honey badger definitely had the upper hand on the jackal.
Honey badger and jackal
The one thing that fellow researcher, Michele, and I were always aware of was that we were spending a lot of time in places that big cats also spent a lot of time. When you are setting up a camera on a fresh kill you can’t help but wonder if the killer is laying somewhere close watching you!
Check out the time stamps on this next set of pics to illustrate this point!
12:35 – Setting camera
15:58 – Leopard
Photos copyright Michele Altenkirk/Lucy Hughes, Lisssataba NR
Faulty Cameras (video-style)
Ali has written about the beatings that the cameras take, and you’ve likely seen Snapshot Serengeti images tilted at odd angles, or at the sky, or face-down in the dirt.
Every once in a rare while, a camera suddenly switches from “snapshot” mode to “video” mode and instead of taking three pictures, takes ten seconds of video. This video “feature” eats up camera memory very fast and so isn’t good for our research, as we end up running out of memory before we have a chance to re-service the camera. It also doesn’t record any sound.
But the resulting video can be amusing. Here is a series of ten-second clips taken on May 6, 2012. I think I know how the camera got flipped to video mode! Do you?
Running in place
The Red Queen Hypothesis in evolutionary biology describes an arms race between predators and prey that leaves each party running as fast as they can just to stay in place. Sometimes I feel a little bit like I am caught in this race with my cameras and the various creatures that maul, munch, or invade them. Granted, the animals aren’t evolving or learning new tricks to overcome each new defense, but it seems that as soon as I conquer one source of damage, something new appears. I thought you might be interested to see the “evolution” of my camera trap weaponry over the last few years.
June 2010
Perhaps I should have known better. But the naked cameras that I set up during my 2009 pilot season alongside Panthera’s indefatigable Philipp Henschel didn’t get destroyed en masse. So I was completely unprepared for the destruction that followed. 90 cameras lost in 6 months to hyenas, ele(phant)s, and fire.
naked camera.
Just some of the many casualties. Photo taken by Daniel Rosengren.
Feb 2011
I returned to Serengeti armed with 200 pounds of steel cases. This made my luggage rather unpleasant.
steel cases. camo color means you can’t see them, right?
Unfortunately, the straps we used to attach the cameras to trees were crap, and still broke with a quick tug from hyena or elle.
ele trunk, up close!
April 2011
Power tools! Rich Howell at Trail Cam Pro sent me out a super fancy Bosch impact driver and hundreds of steel lagbolts. I spent the next 3 months playing with power tools.
Unfortunately, the 3” lagbolts still broke if tugged on solidly by an ele. Cameras were wrestled from their cases by baboons and really determined hyenas. They were stolen by poachers and Masaai who herded their cattle across the border from NCA. They got waterlogged in the heavy rains. Cases were not quite the panacea I had hoped for.
January 2012
I arrived in Serengeti with 5” lagbolts of the best grade steel I could find. And padlocks. And dessicant sacks to keep the cameras dry. Now the cameras were staying on the trees, but getting punctured by teeth, invaded by ants, and waterlogged by the rains. “Water resistant” apparently doesn’t mean a whole lot in the world of ScoutGuard…nor does “manufacturer warranty.” And I still don’t understand how bugs get inside a “water resistant” camera that has no obvious damage.
Not entirely sure what happened here…
January 2013
I armed myself with more padlocks, more lagbolts, and 6 tubes of silicone sealant. My luggage was filled with new cameras, grimly awaiting their doom. I can replace punctured flash covers with clear plastic. Sensor covers are another story, and apparently it is impossible to buy replacements. We’ll see how well the silicone works to fend off ants and raindrops.
Next up? Spikes! I’m going to weld bits of steel to the camera case so that hyenas can’t get their maws around them. Take that, you big, ugly puppies!
Trees
The rain is crazy. Not as windy as yesterday, when it blew our furniture off the veranda, but crazy nonetheless. I could see it coming, not just your typical clouds stretching to the earth in the distance – I could see the waves of water hitting the ground between the scattered trees, moving closer with every second. It was a race – I wanted to reach the valley, with its low profile and scattered trees, before the storm reached me. I know that in a lightening storm, you’re not supposed to seek shelter beneath a tree. But in my giant Landrover, with its 4.5 foot antennae beckoning to the sky, I don’t like being the only blip on the plains. Logical or not. (Comments from lightning experts welcome.)
And so here I am. Somewhere between cameras L05 and L06, hunkered down as the torrents of water wash over Arnold & me. The endless tubes of silicone sealant have done their job – most of me, and most of my equipment, is dry – there are only two leaks in the roof.
The sky is gray for miles – I am done for the day. It’s only 5pm! In wet season, I can normally work until 7pm, and still prep my car for camping before it’s too dark to see. Today feels like one of those cherished half-days from elementary school – not as magical as a snow day, mind you, but exciting nonetheless. Except I am trapped in my car…
So, with that, I open a beer, shake out the ants and grass clippings from my shirt, and hunker down in the front seat to wait out the rain. And to think. I’ve been thinking a lot about trees lately. Mostly what they mean for the how the carnivores are using their landscape.
See, from the radio-collaring data, we know that lions are densest in the woodlands. Living at high densities that is, not stupid. But the cameras in the woodlands don’t “see” lions very well. Out on the plains, a lone tree is a huge attractant. It’s the only shade for miles, the only blip on the horizon. All the carnivores, but expecially the musclebound, heat-stressed lions, will seek it out. In contrast, in the woodlands, even though there are more lions, the odds of them walking in front of the one of 10,000 trees that has my camera on it are…slim.
This map is one of many I’ve been making the last week or so. Here, lion densities, as calculated from radiocollar data, are the red background cells; camera traps are in circles, sized proportionally to the number of lions captured there. As you can see, the sheer number of lions captured in each camera trap doesn’t line up especially well with known lion densities. Disappointing, but perhaps unsurprising. One camera really only captures a very tiny window in front of it – not the whole 5km2 grid cell whose center it sits in. One of my goals, therefore, is to use what we know about the habitat to align the camera data with what we know about lion ranging patterns. I think the answer lies in characterizing the habitat at multiple different spatial scales – spatial scales that matter to the decision-making of a heat-stressed carnivore who sees blips on the horizon as oases of shade. And so I’m counting trees. Trees within 20 meters, 50 meters, 200 meters of the camera. One tree in a thick clump is still pretty attractive if that clump is the only thing for miles. Once I can interpret the landscape for lions, once I can match camera data with what we know to be true for lion ranging, I can be comfortable interpreting patterns for the other species. I hope.
The rain is letting up now, and it’s getting dark. Time to pack the car for camping – equipment on the roof and in the front seat. Bed in the back. And a sunset to watch with beer in hand.
