Dog equality in training and a mostly spring-like ride

The dogs and I rolled out into a transformed world today. The warm sun and wind has melted and sublimated our snow. Out in open meadows, only patches survived the onslaught.

The same meadow looked like an arctic tundra a week ago.

The dogs continued their obsession with something up in a dense aspen grove so I called them back to me. To his credit, R responded with a whip-around rapid recall, arriving before K even came into the camera's sight.

I showered R in treats and praise. But then, as K galloped toward me, R undertook an unprecedented move, sprinting straight at K to cut her off as she approached. When K got close enough, R launched himself at her, fully airborne for an instant.

K veered away from him, skirted his play attack, and churned toward me to receive her reward for a recall.

I always very carefully reward both dogs equally when they do the same behavior. For example, I alternately give each one a treat for at least 30 seconds when they both do a recall.

I just discovered a study (Range, F. et al., PNAS 106, p. 340-345, 2009) that showed that this 'equality' in rewards is critical in keeping dogs enthusiastic about training. In the study, dogs were placed in pairs and alternately did a handshake on cue with a human. If they both received the same treats as rewards, they both remained enthusiastic and engaged over many repeats of the handshake. However, if one dog received a reward and the other didn't, the unrewarded dog gave up on offering his paw for a handshake much sooner. In fact, with this inequality, he gave up even more rapidly than if he worked alone (with no canine partner by his side) while receiving no rewards for handshaking with the human. Thus, it seems that dogs get upset and lose motivation if their partner gets paid for the same work that they're doing for free!

Another big question in understanding dog cognition is whether they learn by imitating each other. I haven't yet done any library research on this question. However, I've seen numerous examples with my own dogs where I'm almost certain that they learned by watching and imitating each other. Indeed, during a break in today's bike ride, I asked K to put her paws on a fallen tree trunk. It's a trick that she's done a million times, and she happily complied. You can't see her paws in the photo but her shoulders were so high because her paws rested on the trunk.

As I fed her treats, R stared and cocked his head as if he was analyzing the situation. I'd never trained him to do this trick. Then, to my utter surprise, he placed his paws on the same trunk, but from the other side. I showered him in treats and praise. I love seeing dogs thinking and taking initiative. This case seemed obvious to me - R wanted to get treats and imitated K's behavior because I was feeding her treats! Very cool!

After a romping good time on the trails with the dogs, I rolled out for a solo trail ride, sticking with my snow bike because I thought that north-facing slopes would still harbor deep snow. For much of the ride, it seemed a ridiculous choice of bike. Even on a heavily forested trail, the snow had melted in our spring-like weather.

A bobcat had boldly marked a trail as his own. Snow carpeted this trail yesterday morning so he must have marked the trail last night. His markings and tracks appear on this trail about every other day throughout the year. The photo shows his scratched out depression, the loose duff thrown in a pile, and his scat deposited near it.

I'm eager to try to get a bobcat photo using my infrared wildlife camera. The new camera is set up outside our house because I want to test it nearby before placing it in the forest. Alas, for the first time since last May, we've gone quite a while with no animal visitors to test it. I'm still waiting! I'm learning that this wildlife camera hobby requires great patience.

I rolled on after checking out the bobcat marking, planning to ride a snowy gulch, but finding that the hunters had compacted the snow down to glistening ice with their 4wd vehicles. So, I changed my plan and climbed a ridge that looked dry despite our recent huge snow storm. Although the towering giants in the distance wore snowy coats, the ground under my tires was dry and brown.

I rumbled along the ridge's spine on my snowbike, still feeling that it was a ridiculous bike choice for the day. In the photo below, my trail was dry, and I was about to ascend the toughest climb of the day. It followed the edge of the forest on rocky and technical terrain, peaking just above the snowy area. It's a climb that I can ride (rather than walk) if I focus every nerve and muscle on the task. Today, I managed it, despite the rough and tumble snowbike that I piloted! The photo doesn't give credit to how steep the climb becomes at the top.

After the climb, I decided to plummet down the north-facing, densely forested, side of the ridge. I'd entered an alternative universe where snow carpeted the world, and a winter-like chill permeated the air. Now, my snowbike could excel at what it was designed to do.

After leaving a popular trail, I floated through deep snow, where no other humans had trod since the storm. Plenty of other animals, like coyotes, deer, and elk had left tracks but no humans.

On a whim, I took trail that I've never explored before, and I promptly found myself in completely unfamiliar terrain (with no GPS because exploring wasn't in my plans for today). However, I'm finding that by forcing myself to explore new places regularly, I no longer get as disoriented as I did before. I noted the sun direction, a deep gulch nearby, and a ridge in the distance. Using those as my guides, I wove my way through the forest, never panicking (my usual reaction to feeling worried about being lost). I soon recognized a familiar trail with a deep and plush carpet of snow, and I rode it out to the main road.

A few glimpses of familiar mountains in the distance also helped me recover my bearings so quickly. It's fun to finally be learning how to navigate after so many years of wandering in forests!