I’m traveling in Mexico this week, so a short post – check out the British Ecological Society’s annual photo contest! My image of Death Valley was the runner-up, and several other images were featured.
You can see all the images at the BBC’s website.
A full moon in the Sonoran desert is a beautiful thing, lighting up canyons and cacti in an unearthly shade of light that is unseen during the day.
The transition from full to new has biological consequences, too. Many animals’ behavior changes depending on the levels of light available in the night. The foraging behavior (and competition) of many rodent species, for example, depends on the phase of the moon (e.g. Kotler 1984). And further from my desert home, dung beetles are able to navigate in darkness with the polarized light of the moon (Dacke et al. 2003).
But in my home, the light of the moon is easily diminished by the lights of the city. This urban light pollution probably has major consequences for animal behavior. I wonder what an animal sees, looking out from the desert to the miles of glittering human development we have built in the last century.
Quiz time – in the map below, can you name the two species whose distributions are shown in red and blue dots? You can see that the occurrences of A are associated with warmer temperatures, whereas the occurrences of B are associated with colder temperatures and higher latitudes.
Whatever you guessed, you were probably wrong. Species A represents all the franchises of the American chain, Dunkin’ Donuts, while Species B represents franchises of the Canadian donut chain, Tim Hortons. Data are for the year 2010. Sometimes economic diversity can look a lot like ecological diversity.
I became interested in this topic on a few long road trips where the same ‘species’ would appear over and over again – endless seas of Burger Kings, Denny’s restaurants every few miles, multiple Starbucks on the same city block. Do these businesses obey the same macroecological rules that biological species do?
I recently finished up a study of this question. It was just published in the open-access journal PLoS One as “Separating Macroecological Pattern and Process: Comparing Ecological, Economic, and Geological Systems“. We bring together datasets for North American trees, birds, and minerals, then contrast these patterns with data for several hundred chain businesses as well as a recent United States Census of business types. Below (Lima, Peru) and above (Canóvanas, Puerto Rico) you can see a lot of these American chains have extended their distributions far from home.
Macroecology is generally concerned with the distribution of diversity: how common are different sets of species across space and time? One central ‘first order’ metric is the species-abundance distribution, which describes the number of species that have a certain number of individuals. Most ecological communities show ‘hollow curves’ where most species are rare (low # of individuals) and only a few species are common (high # of individuals). Another key ‘first order’ metric is the decay of similarity with distance, which states that for two ecological communities separated by a given distance, the fraction of species shared between those communities decays as distance increases. This makes intuitive sense: the pine forests of Arizona are more similar to the pine-juniper forests of New Mexico than the hardwood forests of Georgia.
We show that using these and other macroecological metrics, economic and ecological systems look remarkably similar. Abundance distributions and several other first-order patterns all follow the same patterns. Only by examining the less-considered spatial scale dependence of these patterns (‘second-order’ metrics) can we distinguish economic and ecological systems.
These results suggest that first-order metrics are statistically inevitable when objects are partitioned into categories over space, and only second-order metrics let us test theories that are uniquely relevant to ecology.
One of the most striking second-order patterns is that at larger spatial scales, economic diversity maintains much higher similarity at large distances. Working with our chain business dataset, we constructed test communities of the approximate size of a county (30 x 30 miles), then computed a Jaccard similarity coefficient between all possible pairs of communities. We found that even at 4000 km distances, more than 80% of the same chain businesses are found in each community. This ‘everything is everywhere’ finding provides quantitative support for the feeling of anonymity and homogeneity that I have felt on many of my travels through my country.
The commonality of first-order patterns does suggest that macroecology can provide some strong constraints on possible economic diversity patterns. For example, the ‘hollow curve’ abundance distribution suggests that more businesses will always be rare than are common, consistent with the continued existence of a few large and influential companies in every system, and contrary to our hopes of building communities centered around all small or local businesses. However, the constraint is only on the existence of a ‘hollow curve’ distribution, and not on its parameters – so shifts in the mean and variance of this distribution are certainly still possible.
I think the key thing this study leaves unaddressed is how strong macroecological constraints are on economic systems that are rapidly changing: undergoing growth or collapse (as in the Panama City neighborhood above), or shifts from rural to suburban or urban land use (as in the Miami neighborhood below).
We’re following up on all of these questions, and I hope that macroecology will soon have much more to say about non-ecological systems.
The surest sign of winter in my Arizona mountains is the fall change of colors. The summer’s greens are replaced by greys and browns, as ferns die back, sunflowers set seed, and the trees lose their last leaves. The change is remarkably synchronous. It feels like in a single day, summer is replaced by winter.
This rapid change could be achieved in a few different ways. One is that species evolve a ‘fixed program’ where the time for autumn dieback is fixed. Another is that species evolve a ‘fixed response’ where the time is a fixed response to a certain environmental signal. The second option is more robust if environmental change doesn’t occur at a fixed time each year. There are a few such signals plants can recognize as indicative of the time of year – changes in temperature, changes in day length, changes in the peak wavelength of sunlight. Plants are exquisitely sensitive to the environment.
On my mountain the late afternoon temperatures have just begun to drop down below the freezing point, and the plants know it. The aspens have just lost their last leaves, and the forests will keep a wan shade of white-gray for the coming months. The forest floor is carpeted in a rainbow of colors – a visual transition from the growth of summer to the quiet of the long and coming winter.
Quaking aspen is my favorite tree. In the autumn its leaves change color to a warm yellow, making a perfect contrast against its white and black bark. At sunset the forest glows with the light filtering through the stands of this species.
I never stop learning new things about it, either. On a recent hike on Mt. Bigelow in Arizona, I came across two aspen saplings, both growing in a sunny meadow that was heavily disturbed by a recent wildfire. The two trunks were only a meter apart, but one had leaves the size of a coin, and the other, leaves the size of a dinner plate (photo credit: Kristine de Leon).
The high level of trait variation in aspen is something that has always fascinated me, and has been the subject of a few past papers. But this dimorphism was beyond what I had seen before – the closest example I could recall was a clone growing in the shadow of a cabin in Colorado, where the shade leaves were large and the sun leaves were small. But not this big and not this small.
Then I remembered a fact that my friend (and fellow ecologist) Burke Greer once mentioned to me. Aspen is sometimes triploid. This means it can have three copies of each chromosome instead of two, probably an outcome of reproduction between normal haploid gametes with abnormal diploid gametes that failed to separate during meiosis.
Why should that matter? Well, three copies of each chromosome mean a bigger genome, and a bigger genome requires a bigger cell to fit it in. All else being equal, that could cause bigger leaves and larger growth. The relationship between triploidy, leaf size, and trunk size was long-ago recognized in a related European species Populus tremula, and subsequently also found in our North American species Populus tremuloides (e.g. Ynge Melander’s 1938 report from Sweden).
This variation in traits between diploid and triploid individuals presumably has ecological consequences as well: variation in growth rates, water usage, thermal tolerance, and so on. A recent study by Mock et al. was able to show that triploidy is widespread in North American aspens, but more common in colder areas where (presumably) sexual reproduction may be more difficult. Not, in other words, Arizona.
This led me to wonder: if I had a diploid aspen in one hand, and a triploid in the other, with very different performance characteristics, what were they doing growing in the same place? I don’t know. Two answers suggest themselves: first, that one of the two clones may soon die, ending a brief evolutionary experiment; or second, that they actually aren’t diploid and triploid at all. I didn’t have the cytotyping resources on hand to be sure, and didn’t think to bring back leaf samples on my pleasure walk.
So – the mystery will have to wait until the next time someone more curious and better equipped walks that ridgeline!
Last week the remnants of Hurricane Simon passed through Tucson. The city received just an inch of rain, but the story was different up in the mountains. The summit of Mt. Lemmon, rising almost 7000′ above the city, recorded five inches of precipitation in a single day. The reason is orographic lift – mountains force air to rise, where it cools and loses its water storage capacity, resulting in precipitation. It’s one of the reasons some of the wettest places in the world are on windward mountain slopes.
These mountains are primarily hard rock, with very little soil development. The result is that five inches of rain can’t be buffered underground, leading to surface flows, rockslides, and waterfalls.
One of the consequences of all this rain is a canyon ecosystem full of life, once the flash floods clear out.
Here is some milkweed (Apocynaceae) with a caterpillar on a branch – maybe a queen butterfly (Danaus sp.)?
In five years of living in the desert, I’ve never seen the mountain so dynamic, or shrouded in clouds. It was beautiful.
One of best known patterns in ecology is the latitudinal gradient in biodiversity. Near the poles there tend to be fewer species than in the tropics. Here are two examples from my own travels.
First, a moist lowland forest on the Pacific slope of Costa Rica (9°N latitude). In a hectare of forest you can easily find one or two hundred species.
Second, a montane forest in central Norway (63°N latitude). Here a hectare of forest may only have one or two species.
So why this striking difference? This pattern underlies so much of the earth’s biodiversity, and has rightly fascinated ecologists for a century. But satisfying explanations have been lacking. Part of the trouble is that there are too many possible explanations, because most of the options (for example, warmer temperatures, available energy, longer time for evolution) correlate strongly with each other. This makes it hard to falsify any given hypothesis.
I recently had a paper come out that tries to find a way forward. It was just published in PNAS, co-authored with Christine Lamanna, Cyrille Violle, and many other scientists from the BIEN eco-informatics initiative. In the paper, we argue that focusing on species diversity is less useful than focusing on functional diversity. Rather than counting numbers of species, we should be counting the number of ecological strategies available to species. We argue that this shift is useful, because many theories of biodiversities can be naturally expressed in terms of functional variation. So we recast several major theories in terms of functional traits, which are properties of species that reflect their ecological strategies. Then we collected or compiled data for hundreds of forests throughout the New World – surveys of species and of traits. Here are a few photographs from some fieldwork at a site in Costa Rica.
In the end, what we showed is that none of the major biodiversity theories make predictions that are consistent with observed data. This is a big challenge to our current understandings of the pattern. The biggest issue seems to be understanding why functional diversity peaks where it does. You might imagine that tropical regions can support more species because there are more available strategies – whereas closer to the poles, environments are so extreme that there are fewer viable strategies available to plants. It turns out this isn’t true! We find that temperate regions support more strategies that tropical regions, even though tropical regions have more species. In the below movie, you can see the three-dimensional overlap between temperate and tropical functional traits (made with the hypervolume R package). The temperate region is larger – and you can confirm this quantitatively in Figure 3 of the paper).
We don’t understand why the world works this way yet – but it’s hard to argue with data. I hope explaining this diversity mismatch will help us get just a bit closer to understanding the fundamental and elusive latitudinal diversity gradient.