Monday, March 2, 2020

March 2020 Science Journal Article Summary

Frozen waterfall


This month I've been focused on science practice and science writing (and some vacation) rather than science reading. So this is a mini-review with just three articles. Sorry!

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Sanderson et al. 2020 make a straightforward but often overlooked point about soil carbon and grazing lands. In semiarid rangelands (like the Western Great Plains in the U.S.), the best way to maximize soil carbon is to prevent rangelands from being converted (to farms, housing, etc.) rather than changing grazing practices. Soil C increases from management are typically small and variable, while soil C losses from conversion are large and consistent. They do a great job of making this point and explaining why it's true. The only caveat is that they focus on soil C and not total GHG balance; considering methane and nitrous oxide of both rangelands and alternative land uses makes the net GHG impact more complex.

Global estimates of % protection hide the fact that protection varies widely for different  cosystems and habitat types. Sayre et al. 2020 splits that up into 278 natural ecosystems (based on temperature, moisture, elevation, land cover, etc). If you limit protection to IUCN 1-4 (stricter protection), 9 of those 278 were totally unprotected and 206 were below 8.5% protected (half way to Aichi targets). If you use IUCN 1-6 (including  areas allowing more human use) only 1/3 of ecosystems are below 8.5%. Table 5 shows how much of each major land cover group (forests, grasslands, etc.) has been lost, Table 4 has the details for the 278 ecosystems. Some figures are easier to see online:

I've been referring to the concept in Lehmann & Rillig 2014 for years but never actually reviewed it. Essentially they argue that we should distinguish between uncertainty and variation. Variation we can explain is not uncertainty: if we plant cover crops on 100 farms, and soil organic goes up in some and stays the same in others, but we can explain that with soil type and climate, it's not uncertainty. We just have to recognize that results will vary depending on a set of variables we can describe. Variation we CANNOT explain is uncertainty, e.g. if we run the same cropping experiment and farms with the same values for the variables we think are relevant still have different results, that represents uncertainty (that we don't yet know what drives outcomes). It's a useful framework in many context, for example the impact of conservation practices on water quality is extremely variable by context, but true uncertainty is fairly low.

Lehmann, J., & Rillig, M. (2014). Distinguishing variability from uncertainty. Nature Climate Change, 4(3), 153.

Sanderson, J. S., Beutler, C., Brown, J. R., Burke, I., Chapman, T., Conant, R. T., … Sullivan, T. (2020). Cattle, conservation, and carbon in the western Great Plains. Journal of Soil and Water Conservation, 75(1), 5A-12A.

Sayre, R., Karagulle, D., Frye, C., Boucher, T., Wolff, N. H., Breyer, S., … Possingham, H. (2020). An assessment of the representation of ecosystems in global protected areas using new maps of World Climate Regions and World Ecosystems. Global Ecology and Conservation, 21(December), e00860.



p.s. If you'd like to keep track of what I write as well as what I read, I always link to both my informal blog posts and my formal publications (plus these summaries) at