Unreinforcing insularity: burning and soil moisture

I had a conversation with a prominent cattle rancher in town the other day. I asked him if he had followed any of the news on the recent research out of K-State on the timing of burning.

He said he had.

I asked him what he thought of it.

He said in his gravelly voice, "I think it's a bunch of bullshit."

When I asked him why, he said that if you burn early, everyone knows that the soils will dry out. With less litter, there will be more evaporation and less rainfall will enter the ground because more will run off. You are going to get less productivity.

He didn't know that I had helped write the paper, which was just fine. I got more honest answers than I would have otherwise.

I explained to him that having litter on the ground often reduces how much rain enters the ground--canopy interception creates a dispersed puddle that can evaporate before wetting the soil.

I also explained that there was never any strong evidence that soil moisture was lower when you burned early.

The only data on that are from 50 years ago and were never done in a manner that was scientifically rigorous enough to be definitive.

The data were taken with neutron probes, which is a fine technique, but there was confoundment between treatments and sites.

When you look at the data, the data suggest that early-burned grasslands have less soil moisture than late-burned watersheds.

But, a couple things are suspect with the data.

First, over the winter, soils should recharge so that they are wet throughout the soil profile regardless of the treatment. But, December and January soil moistures are already an inch lower in the early burns.

This is more likely due to that site just happening to be able to hold less water.

Second, if litter is important for holding soil moisture in, unburned soils should be wettest. They are the driest.

Third, the rate of decline of soil moisture during the growing season for the different treatments are almost exactly the same. When does the differential drying occur? This likely means they are using soil water at the same rate.

Fourth, let's say that data are correct and there is an inch less of water in the top five feet of soil.

How much of an effect would that have on production?

A general rainfall use efficiency is about 0.3 g m-2 mm-1 or 75 lbs/acre/inch.

What was the "effect" in the experiment of a having 1 inch less of soil moisture in the soil profile?

Typical rainfall use efficiencies would predict a reduction of productivity of 7-8 g m-2 or 75 lbs/acre.

What was seen? A reduction in productivity of over 1000 lbs/acre (100 g m-2).

Original data use to support idea that early-spring burning reduces productivity. Here, OU is ordinary uplands, which is probably the most relevant. Note the ~25% lower productivity in the pasture that was subjected to early-spring burning. Early-spring burning was March 20. Mid-spring April 10. Late spring was May 1.  

That's over an order of magnitude too much.

In all, that's really the only data out there that is used to support greater drying in early-burned grasslands.

It's unrealistic.

The rancher's response to these highlights?

Something to the effect of "Regardless of what the data say, I trust what other ranchers say they've seen."

Even though none of those ranchers would have ever seen a grassland that was burned in the fall for 20 years straight...

Insularity can be hard to break...

Multivariate statistics...what to use.

Path diagram to figuring out what type of multivariate statistics to use.

Dave Wedin use to joke that the Joe Craine way of analyzing the data is to take it all and put it into a PCA and see what you get. 

There's some truth to that. PCA has served me well. And almost every time I get forced to use a different multivariate analysis, PCA seems to give me similar results. 

For example, in the last burning paper a reviewer insisted we use NMDS for our plant cover data rather than PCA. Correlation coefficient between NMDS and PCA Axes 1-3: 0.93, 0.89, 0.71. Same story from each.

Still, it's good to know what other options there are out there. 

I've been looking at bacterial data with Noah and found the Ramette 2007 paper on multivariate analyses in microbial ecology. Noah uses Principal Coordinates Analysis and I was trying to remember the difference between PCA and PCoA.

It's a good user guide to multivariate statistics in general.

One thing that was interesting was a multivariate analysis of the different types of multivariate statistics different disciplines use. 

Ramette, A. 2007. Multivariate analyses in microbial ecology. FEMS Microbiology Ecology 62:142-160.

Quick hit on male bison weights

Display of bison weights from Konza over time. The upper bound of the data envelope shows the weight dynamics of the largest males.

We didn't EID tag any of the large males at Konza, but the raw data lets us infer a bit about what is going on with their weights.

When the big males get on the scale they rarely have any other individuals with them and they move slow across, so we can get a pretty accurate weight.

If you look at all the data, you can see a clear pattern with the upper bound of the dataset. These are the big males.

Since early April, it looks like the big males gained about 200 kg.

In early July, the upper bound was 920 kg. That's over 2000 lbs.

For reference, during the fall roundup we once had an animal hit 930 kg. After that, top weights were no more than 850 kg (1870 lbs).

Since early July, it looks the biggest males have lost about 100 kg**.

That's a tremendous amount of weight to lose in just a month.

**Note that it could be that the biggest males decided to not walk over the scale during the past month. But, right now all the males and females are together, so if the females have been walking over it, so have the males.

That degree of weight loss is plausible. July and August are the rut, and that's when the bulls are going to be eating the least and "exercising" the most.

Where this becomes interesting is starting to understand the continental scale patterns and thinking about how climate change will affect grazers.

We know that cool, northern grasslands produce bigger bison than warmer, southern grasslands. At least in the fall.

One hypothesis is that the fall weights might be higher for bison in the north, but mid-summer weights are the same. In southern grasslands, forage quality drops enough such that the southern animals lose weight while the northern animals maintain it.

Alternatively, the northern animals might be even bigger midsummer.

In a few weeks, I'll head up to South Dakota to install a walk over scale there.

By this time next year, we just might have the answer.

More forensics on burning

There still is debate smoldering over the timing of burning on grasslands here in the Flint Hills.

Much of the debate stems from research conducted here in Kansas over 50 years ago.

A little more forensics is illuminating.

The key evidence to suggest that burning should be done in late spring is from the weight gain of cattle in an experiment that burned pastures at different times: early-, mid-, and late-spring with an unburned contrast, too. In the experiment, each month, the cattle would be taken off pasture and weighed to examine monthly weight gain. The experiment was carried out from 1950-1966.

In the first reporting of the results from the experiment (Anderson et al. 1970), the authors showed no significant difference in monthly weight gain for cattle placed on pastures with early- and late-spring burns.

Their conclusion was a lot more certain than their data.

“Mid- and late-spring burning produced more weight gain on steers than nonburning. Late-spring burning also increased steer gains over early-spring burning. The weight gain obtained with early-spring burning was essentially equal to that obtained with nonburning.”

So, although there were never any significant differences in weight gain, the conclusions were that there were.

It is possible that when you add up all the monthly gains for a year, you get significant increases in weight gain. As far as I can tell, that was never tested.

When the data were summarized in a later publication, the monthly weight gains are compiled into a 5-month weight gain. But there are no error bars. No tests of significance.

Often, these results have been reported as stating that burning in late spring leads to 32 pounds greater weight gain over a 5 month period (May – September). I’m not sure where that number comes from because the graph only shows 26 pounds difference. Yet, most of the cattle in the Flint Hills are only left out on pasture for 3 months. May, June, and July. If you go back to the 1970 paper, over the 3-month May-July period, differences in weight gain were measured at just 9 pounds.

9 pounds is still 9 pounds, though. Yet, is it? There is no evidence to show that the 9 pounds, no less 26 pounds, is actually significant. That means 9 pounds might be 0 pounds.

There are other parts of the research that are curious. For example, if you look at the productivity data, burning just 42 d earlier results in a 25% reduction in grass productivity. In contrast, 20 years of data at Konza shows no significant reduction in grass productivity. What would cause such a marked reduction in productivity? In the past, it was suspected that soils dried out a lot faster without any cover, but there is actually little evidence to support this.

Could it have been differences in forage quality? Again, no data were ever taken on forage quality for pastures burned at different times.

Also, the average date of burn for the late-season burn was May 1. The stocking date for all the animals? May 1. How that actually happened, I have no idea.

So what might be going on here?

One limitation of the work is that there was no spatial replication for the experiment. Each pasture had a different treatment. There was only one pasture for each treatment. Treatments were not rotated among pastures. Replication came from measuring the same pasture year after year.

In scientific terms, that means site differences and treatment differences were confounded. In lay terms, we have no way to know whether any differences in weight gain were because of the pasture that happened to be picked for the early-season burn happened to have worse forage than the late-season pastures.

This is exactly why scientists replicate.

Still, replication at this scale is certainly hard. We only have so much land to work with. You do the best you can.

Yet, is it impossible to do? No. Can it still be done? Yes.

Scientists could easily work with ranchers to use their operations as experiments. Different ranchers could burn at different times and they could record their animals weight gains. That’s a whole lot better than extrapolating from a few hundred acres at one spot to a much broader area.

In all, was the past work suggestive that late-spring burning was optimal. Certainly. But there are too many questions about the certainty of the results and their broader relevance.

At this point, the most conservative, commutative interpretation of all the data is that there are no significant effects of early-season burning on weight gain.

Interpreted within the context of the experimental design and more recent data, it is hard to be convinced of the necessity to burn in late April in the Flint Hills.

Forensics on research and non-commutative property of science

We learn early on that when adding numbers, order doesn't matter.

2 + 3 = 5

3 + 2 = 5

Like addition, science should be commutative.

Any time new data are collected, the whole of the evidence needs to be reexamined with no favor given to hypotheses that were favored in the past.

Yet, science (and its application) is often not commutative. Order does matter.

The bar for disproving an idea is higher than proving it initially.

Here's an example.

Gene Towne and I just published a new study on burning of grasslands. The study examines 20 years of data from watersheds burned at different times of year--fall, winter, and late spring. It's the most comprehensive study of the importance of the season of burning in North American grasslands.

In short, the research shows that burning grasslands in the fall or winter compared to the late spring has little effect on grasses productivity, while favoring cool-season grasses and forbs. The details of the study can be found here or here.

To the rest of society, it's an important study because it has implications for how much of the last remaining tallgrass prairie is managed. This affects the grasslands that support a million or so cattle each year. But it also affects the millions of people that are downwind of the region when the grasslands burn.

Currently, in the Flint Hills, ranchers (and conservationists) burn prairie frequently every year. Based on recommendations, burning is concentrated in the late spring. When that happens, air quality standards are often exceeded in major cities downwind of the fires.

What is interesting here is to dig into where the recommendations came from. Scientific forensics.

When you examine the research upon which the recommendations are based, almost all of the research was conducted over 40 years ago. Moreover, it seems evident that the findings on when to burn are fairly equivocal.

And probably wouldn't pass rigorous scientific scrutiny today.

For example, the research from the 1960's and early 70's showed that plant biomass was found to be lower when grasslands were burned in early spring vs. late spring. Yet, these means were generated for just one small experimental plot per treatment.

The old data also showed that when grasslands were burned earlier soil moisture was lower, which presumably caused the lower productivity. Yet, in the particular study conducted in the 1960's, soil moisture data are reported as being lower in January in the early-season burn than the late-spring burn, two months before the burning has occurred. This result was likely a site effect.

Another major line of evidence to recommend late-spring burning was long-term data on cattle weight gain. The data on weight gain showed a trend of 6% greater steer weight gain from May to September over 16 years when burning on average on April 10 vs. March 20. Yet, as with other data, the weight gain of steers was again measured in just one pasture with no control for site differences that might be confounded with treatments. As for the data collected, although the weight gain of steers was significantly higher in burned than unburned pastures across 16 years, there was no significant difference in monthly weight gain with timing of burning (P > 0.1).

Based on the data circa 1970, if you had to choose a time to burn, late spring made sense. Yet, when all the past and current evidence are taken together, there is little evidence to support burning exclusively in the late spring.

Burning Flint Hills grasslands earlier is unlikely to have any major negative consequence for grass or cattle production, and may actually be beneficial (see the paper).

Unfortunately, more than likely, unlodging the idea that burning in late spring is necessary will be a lot harder than lodging it in the first place.

Unlike elementary addition, order is likely to matter here.

Update on seasonal weight gain of bison

More bison data are rolling in off the field scale. At Konza, we set up a scale for bison to walk over and weigh themselves. So far, they seem to be obliging.

As to the data, first, are examples of a 3-year-old cow (red) and a 2-year-old cow (blue). These are the individuals that we've had the most data for. You can see that over ~60 d they've put on almost 100 kg. As far as we know, neither of these animals have had a calf this year. Although the sample size is small here, it looks like weight gain has started to level off here. 

Bison mass (kg) vs. day of year for 2 cows at Konza.

With 90 calves tagged last year, we have a lot more data for this year's yearlings. If I standardize for individual variation in weight among animals (for those animals that have enough data to look at trajectories), this is the general trajectory. More or less linear increases in weight over the past 60 d. About 80kg of weight gain.

Residual weight vs. day of year for yearlings at Konza.

We still have some kinks to work out of the system. For example, we are just getting it to the point where we can remotely harvest the data. Also, we need to tag all the animals out there, which should happen this fall.

For everything we know about seasonal patterns of dietary quality, weight gain should be leveling off right about now.

This technique is going to be pretty important in order to understand seasonal weight dynamics and eventually how climate change will affect grazers in grasslands. For example, we see that bison in the north reach greater size than those in the south. Is this because they have a longer period of weight gain, or gain more weight at a given time? As it gets warmer, what mechanism will climate affect our grazers?

How much weight different animals will gain in the next month is going to be super interesting.

[Note: the average yearling mass as of July 12 is approximately 245 kg. If you look at the 2013 Oikos paper, average yearling mass in the October roundups ranged among years from 234.1–281.6 kg. That means, if this was a typical year the animals would gain just another 20 kg, but they might put on another 35 kg.]

The trajectory of nitrogen in grasslands

N concentrations for grasses from Konza's 1D watershed from 1983-2010.

Plant N concentrations might seem like another esoteric ratio, but they are the key to a number of ecosystem services. In grasslands, they determine the nutritional quality of grass for grazers, how much C plants take up, as well as how fast dead grass material decomposes. And grass that doesn't decompose fast is more likely to fuel burns later.

Whether plant N concentrations have been increasing or decreasing in grasslands is one of the greatest unknowns for modern ecosystem ecologists.

For example, Kendra's previous work had shown that N concentrations had declined by 25% in Kansas grasslands over the past 75 years. That study relied on plants collected for herbaria in Kansas over the past century.

Based on the timing of declines and what we know for other supporting evidence, the most likely explanation for the declines in plant N concentrations was that increasing CO2 concentrations have been driving down plant N concentrations.

Despite this single line of evidence, could grass N concentrations have actually been increasing?

N deposition rates have been increasing, for example. When N deposition is high enough, it's enough to eutrophy the grasslands with a cascade of effects.

To answer this question, we examined the N concentrations of grasses collected over 25 years at Konza Prairie. The grasses come from a single watershed under the same burn regime (annual burning) with no grazing during this time.

Now what trajectory the plants would take was uncertain. When grasses were first measured CO2 concentrations were 343 ppm. By 2010, they were 390 ppm. 14% higher.

Was that enough added CO2 to pick up a signal?

The quick answer was no. There were no significant declines in N concentrations (or 15N:14N ratios for that matter).

Could there be another driving factor that was offsetting the decline? We checked a lot of things. No trends in climate. No trends in species composition. No trends in productivity. No trends in water availability.

The grasslands was really similar to what it was like in 1982**.

**The Nature Conservancy's Joe Fargione's response to this was "Conservation works!" Essentially, we could hold a grassland pretty similar to what it was before.

Given the differences in results, now the rectification begins. The herbarium data suggest declines in N availability and plant N concentrations. The Konza data suggests no significant declines in either.

Is the difference time scale? Local conditions? Collection protocols?

Unknown at this point.

One thing is clear, though. Neither study supports eutrophication of the Kansas grasslands. Despite elevated N deposition, there is no indication of greater N availability.

Looking forward, the future of the grasslands is still uncertain for so many reasons.

For those grasslands that are preserved, whether N availability, plant N concentrations, and forage quality will decline is a question that only further monitoring and testing will be able to answer.

McLauchlan, K. K., J. M. Craine, J. B. Nippert, and T. W. Ocheltree. 2014. Lack of eutrophication in a tallgrass prairie ecosystem over 27 years. Ecology 95:1225-1235.