Reciprocal illumination

Apparently, a number of people were more familiar with this phrase than I was...which is to say I had never heard it used before.

In general, it is used to denote the idea that different disciplines can inform one another and help generate advances collectively.

One use is:
http://evolvethought.blogspot.com/2005/02/reciprocal-illumination-of.html

It seems to be a more common term in phylogenetics.

Soil C patterns in the US (and world)

When working with the global soil 15N database, we put together global relationships between soil C and climate as well as texture.

I hadn't seen this put together before, but it turns out they were for the US.

The first paper on this was from Guo et al. 2006 in SSSAJ. The second one was by Homann et al. in 2007 in Biogeochemistry.

I think the Homann paper does a better job of showing relationships than Guo, though neither would necessarily be ready for a text book. The both try to show too much of the dependency rather than the generality.

In short, the authors use data on soils from across the US that had been compiled earlier. Examining the patterns region by region, They then show that clayey soils from wet, cold have higher total C in the top 20 cm (mineral soils) than sandy soils from hot, dry sites.

At some point, someone needs to do a better job of showing this so the figures can get into textbooks.

That said, the basic patterns that we see with our global database match pretty well with the US patterns.

For example, from 5 to 15°C, soil C concentrations declines by roughly 50% in the global dataset, which is pretty similar to what Homann saw for US regions.

For our data, log soil %C declines at a rate of 0.011 per °C. They found a decline of 0.016. Our data showed log soil %C increased 0.49 per log unit of MAP. They showed 0.33. 

Differences can be hashed over, but the global patterns with our somewhat ad hoc data [it was put together for other reasons that soil C] seem to be pretty robust.

Something like what is directly above needs to be in a textbook...

Ecology humor: desert edition

[To be read slowly, dead-pan, with little inflection. Should take about 10 seconds to read. Pause a second with each comma and period.]

About a month ago, I got a cactus. 


A week later, it died. 


I was really depressed because I was like ‘Damn! I am less nurturing than a desert.'

--Demetri Martin

Iconic figure: global climate space

If I had to vote for an iconic figure from work with which I've been associated, it's the global climate space that Andrew Elmore put together. We used this as the basis for a new Whittaker biome diagram earlier, but when it stands alone it's still pretty special. 

What I like about it is that in just a glance you can appreciate:

• The extent of places with ice (or potentially underlain by ice). There's a lot of land with mean annual temperature < 0°C.
• The general wedge shape of precipitation and temperature. 
• The position of the temperate rainforests that sit around 5°C MAT. 
• The occurrence of land that receives > 4 m of rain a year.  

This is a figure that needs to be in every ecology-related textbook. The map of continents just never shows this quite right.

One neat way to use this graph is to overlay data from research to understand the distribution of climates in a given study.

For example, I'll use the climate space diagram as the backdrop for arraying the points where we had samples for the soil 15N synthesis. 

You can see in an instant how well (or not) you've covered a particular portion of the climate envelope.

For this study, we're still a bit short on cold sites and hadn't represented the temperate rainforests well. Hot deserts are undersampled, too.

Something is off...

I've been wrestling over the past few days with trying to understand why soils from the Tibetan Plateau had soil carbon concentrations that were an order of magnitude lower than you expected based on climate. thought it might be the altitude as most of the Plateau is >4000m. Turns out their soils are very sandy with only 3% clay. That explained it.

Then I got a slug of data from beech forests in NE France. Their surface mineral soils averaged -5‰. Soils shouldn't have a del15N less than 0 ‰, no less -5‰. Beech are ectomycorrhizal and their litter is relatively depleted in 15N, but the leaves of these forests were even more enriched than the soil.

Still haven't figured that one out.

In all, when putting together large databases, you have to check the data as it comes in. I've rerun the statistics for this dataset over 100 times. Every time new data comes in, I check to make sure it fits (or doesn't fit) the pattern. You test your mental hypotheses over and over, while error-checking data. Not too different than long-term data needing to be analyzed every year.

Earlier today, Ben Turner sent some data from the dune fields of Haast, New Zealand.

The paper he sent along had pictures that looked like this:

The lat/long he sent looked something like this in google maps:

Doesn't quite look like temperate rainforest. 

[mostly, just rounding error here. The Haast dune system is just north of the town. Kendra and I spent a night there about 10 years ago.]

http://www.doc.govt.nz/parks-and-recreation/tracks-and-walks/west-coast/south-westland/walks-north-of-haast-township/

Landscape level patterns of soil N flux and N isotopes

This might be of interest to just a few, but I've been working hard to understand the degree to which global patterns of soil del15N represent differences in the proportion of gaseous N loss (fractionating loss hypothesis) vs. difference in the degree of decomposition of soil organic matter (microbial processing hypothesis).

There are few papers that try to contextualize losses of N via gaseous pathways vs. leaching, for example.

There also are few papers that look at spatial patterns of gaseous N flux, local or global.

Velthof 2000 did a great gradient study involving 162 flux chambers along 400 m of slope in a grassland.

This is probably the best study that asks whether spatial variation in gaseous N flux patterns soil del15N.

At least over 4 days of measurements, they found a good correlation between the two.

Best correlations were with shallow soils (0-5 cm). r2 was about 0.4. But correlations for del 15N of soils even just 10-15cm deep were non-significant (r2 = 0.03, P > 0.3)

For what it's worth, they said that "Both the del15N values and N2O fluxes were highest at the steepest part of the slope."

Would steep slopes also have more processed OM?

Velthof, G. L., J. W. van Groenigen, G. Gebauer, S. Pietrzak, S. C. Jarvis, M. Pinto, W. Corre, and O. Oenema. 2000. Temporal stability of spatial patterns of nitrous oxide fluxes from sloping grassland. Journal of Environmental Quality 29:1397-1407.

Global patterns of soil C concentration--an index for relative decomposition rates

Patterns of soil C concentrations as a function of mean annual temperature and precipitation in surface soils for 600+ soils from around the world.

One of the keys to understanding global N cycling patterns is understanding the global patterns of rates of decomposition. There are a few syntheses of litter bag studies, but the net result of inputs and outputs of C for soils are hard to interpret.

One of the best indices (I think) of the rate of decomposition relative to inputs is just soil concentration.

Most syntheses to date have examined soil C content, not concentration. Mostly because the goal is to determine soil C storage. Concentration only helps to determine content.

The major syntheses I can think of--Mac Posts 1982 and Batjes 1996--examine patterns for different soil orders. temperature or precipitation is never on the x-axis.

Bearing that, there should be an advance possible by putting climate on the x-axis and %C on the y-axis.

It seems like this would have been done, but I can't find a graph like it and people that are likely to know about it seems surprised when I show them.

For the 570 mineral soils I looked at, MAT and MAP explain about 60% of the variation in log-transformed soil C concentrations. That's a high r2 given all the variability out there in the world and other factors like how much clay is in soil, the quality of the plants,  and whether plants are eaten or not.

The interpretation of the patterns essentially is that if soil %C is an index of the amount of decomposition of plant biomass relative to primary productivity, then hot, dry places have soils with highly processed C.

The patterns of relative decomposition now seem pretty clear.

The question now becomes whether those hot, dry places consistently are elevated in 15N, such that soil 15N patterns are being caused by relative decomposition rates.

Two tests here.

1) Soil %C and soil 15N should scale across sites.
2) If soil 15N increases with increasing MAT and decreasing MAP, the relationship should disappear after accounting for variation in soil %C.