Last time, using the example of my recent road trip from California to Maine and back, I delved into the topic of long gradients—spatial changes in vegetation, such as from wet to dry or temperate to tropical, only visible across many hundreds of miles and not mainly the result of elevation change. These gradients are harder to take in than the much more compressed variety (generally elevation-driven) that I usually focus on, but for me the fact that the climatic forces producing long gradients are essentially invisible compensates for the overwhelming scale and gives these gradients a similarly empowering, “world-shrinking” effect.
For years I’ve been thinking about how to depict gradients like this—in a way that makes them easier to experience than through many hours on the road but somehow still communicates their large-scale reality, since it’s the very fact of this compression that would give the representation its power. My typical method of representing small-scale gradients—fracturing them into a handful of scenes and juxtaposing them to sharpen the contrasts between—wouldn’t be ideal for larger-scale patterns. Those fractured compositions wouldn’t be able to incorporate enough pieces to convey the nuance of fine gradations without becoming impossibly long and narrow. Plus, there’s a point at which this sort of depiction moves beyond the realm of aesthetics and more firmly into photo-documentation. Making it visually interesting would still be important, but it would need to be composed in a way that’s more methodical and less about creating pleasing geometries.
The most obvious method would be a linear sequence (a transect) of photographs taken at even intervals along the gradient. I made a very non-methodical attempt at this during the westbound leg of the road trip —more on that below. The closest I’ve come to a methodical version is instead along a short, elevational gradient—on Santa Cruz Island in the Galapagos, about 600m of rise across a 20km distance (shared in an earlier post about that island.) I felt that this was only minimally successful. One reason is that the result, below, has limited legibility without dramatically enlarging it; another is that, keeping a constant interval of roughly 30m of elevation gain between photos, many of the views end up capturing anomalous conditions that aren’t very representative of the gradient as a whole. It also raises questions about where to stand, which way to point the lens, and how much to include in each view. In particular, if travel is by road, asphalt tends to fill up a large percentage of each frame.
A photographic transect across the northern half of Santa Cruz Island from the arid coastal zone into the wet highland zone (traveling from bottom to top, north to south).
A transect down a long gradient would face these same issues of interval, vantage point, orientation, and extents, but magnified. Focusing on the issue of intervals, based on distance rather than elevation: there would need to be enough images to capture the typical condition of a given zone of the gradient, accurately conveying the overall rate of change. But “accuracy” depends on how fine a grain you’re talking about. Zooming out, the rate might look relatively constant, but zooming in, it increasingly won’t, as discontinuities (or “anomalies”—elements that seem misplaced) become more prominent. Even if the overall climatic gradient from wet to dry or cold to warm is relatively smooth, variation in local conditions like soil, topography, or moisture, and randomness in weather events or seed dispersal, create patchy distributions of species. Zooming in far enough, islands and edges overwhelm gradual transitions, resulting in what I think of as “tension zones”—areas of extra rapid change—and “milestones”—the clear beginning or end of a particular zone, or where certain species drop out or first appear. For instance if you could travel east to west across North America pre-agriculture, trees wouldn’t become more and more widely spaced until they disappear completely; rather, the continuous forest would start to break into patches that become smaller and smaller, around water sources or protected areas. Photos taken along the gradient might end up calling attention to discontinuities like this or missing them completely, and either one of those could make the representation more or less “accurate” depending on how you’re defining accuracy (how zoomed-in you are). The smaller the interval chosen, the less likely either of those outcomes, but it might also be possible to work some flexibility or complexity into the methodology to compensate. The main sequence of photos, shot at even intervals, could depict the overall (“zoomed-out”) gradient, while a secondary one (placed alongside) could capture tension zones or milestones that would be otherwise left out.
A tiny outpost of Valdivian (Chilean temperate) rainforest in Fray Jorge National Park, surrounded by desert. Fed by coastal fog, it’s many hundreds of miles north of the rainforests of Patagonia. Crossing the abrupt forest-desert edge it’s the anomalous island character of the forest that stands out, but zooming way out, you could think of it as a milestone marking the rainforest’s northernmost limit along Chile’s north-south gradient from dry to wet.
The lush interior of the forest pocket.
This all becomes even more complicated given that few long gradients on earth still maintain anything close to a continuous natural condition. Certainly none of them exist along major roads. So most large-scale gradients in natural vegetation, broken up by cities, agricultural land, and various smaller disturbances, are even less smooth that they would have been originally. The problem isn’t necessarily the “unnaturalness” itself—climate affects vegetation patterns, in ways worth observing, even where we’ve largely created them—but instead the greater complexity of the patterns. The more impacted and heterogenous the landscape, the more photographs (at a smaller interval) are probably needed for a meaningful representation, since the goal would be to capture as many conditions as possible and essentially create an “average” picture of the landscape, smoothing over most of that small-scale heterogeneity. Though the tension point and milestone concepts can still apply to human-dominated landscapes (more on that later), they tend to be obscured by land use or planting decisions that have little to do with localized natural conditions let alone larger-scale climatic constraints.
So these long gradients are tough to capture in two dimensions in a way that’s representative of reality on some chosen level, as well as digestible; that’s true for many reasons aside from the fact that they require big investments in time, organization and/or gasoline. This recent road trip was the first time I’ve made any attempt at it, specifically along the central segment (with the clearest and most linear part of the wet-dry gradient) of the westward, southern route, roughly between St. Louis and Albuquerque. In fact I’d say it barely counts as an attempt, particularly given what I’ve just explained regarding the challenges of human-created patchworks. (There are some large, quasi-natural, forest areas remaining toward the eastern end of that segment, but in the Great Plains farmland has mostly obliterated any trace of the original forest-and-prairie mosaic, and further west ranching has certainly had a major impact on the character of the steppe and semi-desert landscapes.) The effort was pretty much an afterthought, and not at all methodical. I took about 80 photos over 1300 miles, nowhere near enough, and at no regular interval. Except for a handful they leave out most of the Missouri and New Mexico ends of the segment for no other reason than that it didn’t occur to direct my attention there, plus we crossed most of the Texas Panhandle in the dark. And, photographing through the car window on the freeway is not ideal for composing views.
Satellite image (overlaid on a rainfall gradient) of the central segment of the drive; the yellow numbers identify the locations of the photos in the transect below. (Satellite image from Google Maps; rainfall map from https://gisgeography.com/us-precipitation-map/)
Landscape transect along the central segment of the westward drive, the photos numbered based on their locations on the diagram above. One challenge with this type of representation is making it legible given the size of the photos—and this one has many, many fewer than there ought to be.
The photos show a mix of landscapes that generally progress from forest to field to grazing land from east to west, but given the relatively small number of views, not in the frequency that they actually occur. So instead of being able to use dozens or hundreds of photos to show how that frequency (the average mix) changed from east to west, I selected views that each individually captured a sense of that average mix. Once I pared those down to represent somewhat even intervals, I was left with just seven—not very useful except for the record. You can see the overall transition there, but the transect obviously doesn’t capture any nuances of the gradient, including two tension points that I picked up on: the relatively rapid drop in forest cover around Oklahoma City, and a quick transition from grassy plains to cactus-y semi-desert right before (appropriately?) the New Mexico border.
More thoughts on representation next time….
Darren
Patches of forest like this are common in eastern Oklahoma, but less so than further east (and they have a “drier” aspect to them)—they’d only work in the transect if it included enough additional views, in the right ratios, to show the patches in this context.
These two views about 20 miles east of the New Mexico border are less than three miles apart. They’re not actually that different from each other, but to me the right looks like the Great Plains and the left looks like the West. (The shrubs are cholla cacti.) I could’ve included this “tension zone” in the above transect if every one of the views had been spaced at a similarly small interval rather than the current average spacing of about 100mi.