Streams don't run from dry soils

Konza streamflow and precipitation as a function of soil moisture at 25 cm

The fraction of precipitation retained by soil is a major source of variation in soil water availability to plants. For a given site, much of the variation that we see in this is associated with the pattern of precipitation, external disturbances on vegetation not withstanding. Precipitation pattern is hard to quantify in an ecologically meaningful way, though. A large, intense rainfall event might be lost to the stream if soils are saturated, but if soils are dry might be retained completely. Yet, heavy rain on dry soils might also be associated with heavy runoff if the rain falls faster than the soil can absorb it. You can occasionally see it on your front lawn, but flow paths are pretty short there compared to an intact grassland. Then again, rivers do flood in deserts.

There has been a lot of uncertainty at Konza on this, so I dug into the data to test it. I used the biweekly soil moisture data and matched it up with precipitation and streamflow during April-July (day 105-214 from our critical precipitation periods). 27 years of data here.

First cut analysis shows high precipitation falling a range of soils, but high flows in the major stream draining Konza only when soils are wet. Really no cases of high flows off dry soils.

The data aren't perfect. Soil moisture is only taken biweekly, and I used the interpolated soil moisture for each day rather than actual or the previous soil moisture. We really need daily data on this and that doesn't exist. 

Upshot? Plants get access to all the precipitation that falls when soils are dry, but can lose a significant amount when soils are wet. Losing water from wet soils might not impact plants immediately, but likely does later as the soils dry out.

Turns out we have pretty good evidence of this. More on that later.

Canopy interception and the dispersed puddle

Taking a walk through grass after a light rain is a soaking affair. Even walking through a recently mowed lawn in the morning would wet your sneakers while going to school. It was always better to let the sun come out for a little bit before short-cutting across a yard.

The principle that most children learn at a young age likely has important ramifications for understanding the dynamics of how grasslands work. Through one of two mechanisms, my guess is that canopy interception sets up a negative feedback loop that constrains how much grass is produced.

First, a quick review.

In grasslands, approximately half of the precipitation can be intercepted by biomass without reaching the soils. For small precipitation events, 70% of the precipitation can be intercepted by a dry canopy, with the fraction of precipitation intercepted declining with event size (Ataroff and Naranjo 2009). A single square meter of grassland can withhold 2 L of water from reaching the soil.

Relationship between precipitation and canopy interception for a tropical pasture grass. From Ataroff and Naranjo 2009.

Half of the precipitation that could fall on a grassland might never reach the soil. And the more grass there is, the less precipitation would reach the soil. Seasonally, as grass grows and canopies develop, the demand for water would be ever increasing. Yet, because of interception, less and less precipitation would reach the soil.

Increasing demand, decreasing supply. A classic negative feedback that would be limiting growth. Even if plants had access to deep water, the consequences might be greater for N supply and cause transitive limitation as surface soils where N mineralization occurs would be prevented from rewetting.

Evolutionarily, we haven't explored whether there would be selection on herbaceous species to promote (or not promote!) throughfall of precipitation. Altered leaf angle, waxy cuticles, stemminess, would all alter how much water is retained or passed on to the soil. Ecologically, with just a few papers on the topic, there are likely some large unexplored ramifications besides promoting seasonal water limitations. For example, from first principles, rain coming in larger events should promote growth, not retard it, as the water is stored in the soil rather than the canopy.

Most importantly of all, if you haven't learned it yet, never cut across a wet lawn in the morning wearing sneakers. Might as well jump in a puddle.

Nutrient limitation, climate, and bison

Relationships between mid- (a, c) and late-summer (b, d) precipitation and bison weights for each year for Konza Prairie (a, b) and Tallgrass Prairie Preserve (c, d). Calf weights and yearling weight gain (YWG) were adjusted for differences in sex ratios to represent the average weight of an average male and average female bison. Midsummer weights were standardized for variation in late-summer precipitation and vice versa.

In RSWP, I write a lot about nutrient limitation of plants. One thing that comes out strongly as we look at how ecosystems function is that nutrient limitation in plants can induce nutrient limitation in herbivores. Especially for nitrogen which animals generally cannot access through other means except by eating plants.

We just had a paper published that illustrates a few important points regarding nutrient limitation in grazers and the distal controls on grazer performance. In the paper, we examined how interannual variation in the timing and magnitude of precipitation affected the weight gain of free-roaming bison. Every year, the bison herds are rounded up, and each individual weighed. Bison weights of calves and animals in their second growing season (yearlings) were analyzed for 14 years for Konza Prairie, Kansas, and 12 years for Tallgrass Prairie Preserve, Oklahoma. The sites are both native grasslands on the drier edge of what is considered humid grasslands. The records of weight gain for wild herbivores are among the longest known—only Marco Festa-Bianchet’s excellent work on mountain goats is comparable.

As we looked at how much weight the animals gained each year, we found was that more rain late in the summer increased the weight gain of the bison. Not much of a surprise there. More rain in August, which is often dry, means more green grass later for the animals, which would allow them to grow more. What was unexpected (to some) was that having more precipitation early in the middle of the growing season (late June, early July) caused animals to gain less weight. Why? Here, it’s not the quantity of food, but its quality. What we found was that having high precipitation in the middle of the growing season also increased flowering (see previous post on flowering). More flowering means more low-quality stems, which lowers the average protein concentrations of the grass, and lowers weight gain. This idea wasn’t entirely unknown—some ranchers say a dry June is money in the bank—but it was the first time quantified scientifically.

Now, it also might be the quality of the leaves that is low in high mid-summer precipitation years (we don’t have data on that), but the data illustrate a few key points. First, in grasslands, quality is as important to consider as quantity when considering grazer performance. As I describe in RSWP, there are glaring examples of this being glossed over (as well as great examples of its consideration). Second, as we think about how grasslands are structured and how they might change, the timing of precipitation can be as important as the amount. Increase or decrease the amount of precipitation by half and bison gain the same weight. Shift it from August to early July and weight plummets.

What we learn from simple observations continues to amaze me. By no means have we plumbed the depths of understanding the complexity of grasslands. Complements to both Konza’s Gene Towne and The Nature Conservancy’s Bob Hamilton for doing such a great job for more than a decade.

Craine JM, Joern A, Towne EG, Hamilton RG. 2009. Consequences of climate variability for the performance of bison in tallgrass prairie. Global Change Biology 15: 772-779.

Grass flowering and climate

25-year record of flowering of Schizachyrium scoparium (open circles uplands, closed circles lowlands).

We’re just about ready to submit a paper that analyzes 25 years of flowering for three grass species at Konza. As far as I know, this is the longest continuous record of flowering effort for grasses (although there always seems to be some European record that dwarfs any North American record). In short, every fall, the number and weight of flowering culms for three species of grass (Andropogon gerardii, Sorghastrum nutans, and Schizachyrium scoparium) are measured in an annually burned watershed. The three species are, more or less, the three dominant grasses at Konza.

When I asked what people expected from the data, there were two main beliefs. First, species were offset in their flowering. It was generally held that some years were good flowering years for Andropogon, others for Sorghastrum. Second, flowering was much greater after a dry year, especially for Sorghastrum. The latter was likely an extension of the Birch effect, which I’ve talked about in previous posts.

In general, we found that a good flowering year for one species was a good flowering year for all species. By no means was there an inverse relationship for flowering between species among years. The differences among species, were interesting though, and reinforced the idea that it is not just the amount of precipitation that falls that is important in grasslands, but the timing of the precipitation. For example, years with greater precipitation early in the growing season benefited Sorghastrum flowering, while greater precipitation late in the growing season benefited Schizachyrium. Why the belief for inverse relationships among species? More than likely its due to their differences in flowering phenology. This year was a good flowering year for all three species, but a person would have sworn it was a good year for Andropogon in mid July, as it is the first to start to flower, while the same person would have sworn it was a good year for Schizachyrium in early late August when it began to flower in earnest.

The offsets in flowering are important components of understanding questions such as species coexistence, but it is the question about antecedent climates that tests our fundamental understanding of how grasslands work. At the heart of the matter is whether conditions during the previous year will generally affect current year’s dynamics. If so, processes like the Birch effect become more central and ecosystems become a lot more complex.

Despite the assurances, over 25 years, there was no effect of previous year’s precipitation. Wet years had a lot of flowering regardless of whether the previous year was dry or wet. Dry years had little flowering, regardless of whether the previous year was dry or wet.

The conclusions seemed pretty straightforward, except for a short paper by Knapp and Hulbert in 1985. They had measured flowering in the same watershed as our dataset a few years before our dataset began. What was interesting was that flowering in 1981 was 6-10 times greater than any year of our 25 year record. 1981 was a sea of grass horse high not because 1981 was especially wet, but because 1980 was especially dry. A month where every day was over 100 degrees Celsius. Cows starving. Lawns dying.

As such, even though Konza had a 25-year record, some events happen rarely, and when they do, they can be spectacular. There are a lot of questions that are raised by the dataset. Was it the Birch effect that caused the immense flowering or reduced competition from plants dying? How dry to soils have to be for how long for N to explode? What really struck me was that no long-term dataset is ever long enough. 25 years of data just wasn’t long enough to capture even a hint of the importance of rare events. Who knows what year 26 will bring? I’m sure a lot of people will be watching a bit more closely.

Transitive limitation and precipitation

Thinking more about N and water, I was looking over the Huxman-Smith et al. 2004 Nature paper. This paper summarizes the sensitivity of ANPP to precipitation. With data from 14 sites, they calculate rainfall use efficiencies across years to see how RUE changes with mean annual precipitation. They find that wetter sites have lower RUE, but all sites converge on a constant RUE. (Above figure is precipitation vs. ANPP (g m-2), each x-axis tick is 500 mm y-1).

The most interesting art of the paper are statements on resource limitation.

Here are some key sentences:

1) the authors predict that “the removal of other resource limitations so that precipitation becomes the primary limiting resource will result in an increase in site-level RUE that approaches RUEmax.”

2) “sites with high production potential in years with greater than average precipitation, soil nitrogen or other limiting resources might transiently limit biological activity.”

3) They also state that “biogeochemical constraints (limitation of activity by resources other than water) can increase with increasing precipitation”.

The approach the authors take to limitation is generally one of serial limitation. First one resource limits, and then another. The authors seem to hold the idea that multiple resources can co-limit ANPP, but they are mute about mechanisms or what the tradeoffs are. There is no evidence they considered substitutability leading to co-limitation, or transitive limitation (water limiting N availability). Looking at statement 3 above, they just as easily could have said that biogeochemical constraints can also decrease with increasing precipitation.

The unstated model they use follows something like this: less rain, greater water stress, less limitation by other resources, less production, greater WUE.

The existence of transitive limitation changes the entire story of ANPP responses to increased precipitation: less rain, less nitrogen mineralized, greater limitation by N, less production.

The relationship between ANPP and precipitation is, here, just a ratio. The important part of research is always to look one level of mechanism below the pattern of interest.

For example, if plant WUE was a key factor in RUE, then wouldn’t sites dominated by C4 vegetation have an inherently higher RUE than sites dominated by C3 vegetation? But, if the observed RUE was driven by N mineralization responses to increased soil moisture, wouldn’t they be the same? Although Cedar Creek (CDR) might show no increase in ANPP with increased precipitation due to strong N limitation, there might be unique patterns of sensitivity of N mineralization to variation in precipitation there. For example, maybe with the sandy soils, soil moisture isn't much greater in a high precipitation year.

At this point, both mechanistic hypotheses should be considered equally (one can’t be favored because it comes first). It’d be interesting to see how much of the patterns could be explained by transitive limitation.

Huxman, T. E., M. D. Smith, P. A. Fay, A. K. Knapp, M. R. Shaw, M. E. Loik, S. D. Smith, D. T. Tissue, J. C. Zak, J. F. Weltzin, W. T. Pockman, O. E. Sala, B. M. Haddad, J. Harte, G. W. Koch, S. Schwinning, E. E. Small, and D. G. Williams. 2004. Convergence across biomes to a common rain-use efficiency. Nature 429:651-654.