Monday, June 1, 2020
June 2020 science journal article summary
I hope you're all doing well. I'm finding working on my porch when I can gives me a chance to safely get in some bird-watching and socially distant contact w/ neighbors.
I hurt my arm, so I'm relying on voice dictation to type which has slowed me down a lot. As a result, I'm only covering a few science articles this month. But they're all good ones! Although I'm biased as I'm an author of two of them (recommendations for scientists to improve their research impact, and a methods paper w/ an easy way for social science surveys to collect more spatial data).
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Fisher et al. 2020 is the paper I wish I had read when I started working as a scientist. It has clear recommendations for scientists to improve the impact of their research. We drew from our successes, failures, and suggestions from other colleagues and the scientific literature. Then we distilled all that into what we hope is a paper that is both practical and accessible to anyone. At a high level we recommend: (a) identify and understand the audience for the research; (b) clarify the need for evidence; (c) gather “just enough” evidence; and (d) share and discuss the evidence. For each we talk about why it matters and how to do it. You can read it at https://conbio.onlinelibrary.wiley.com/doi/full/10.1111/csp2.210 We are still working on a blog and 1-page version, but we do have a recording of a talk based on the paper here: https://www.openchannels.org/webinars/2019/improving-your-impact-guidelines-doing-science-influences-policy-and-management Feedback is welcome!
Masuda et al. 2020 is a fairly simple methods paper. We show that during household surveys, asking respondents to draw spatial boundaries (e.g. of their farm plots) on digital tablets w/ ArcGIS Collector is relatively easy, accurate, and practical. By making the surveys spatially explicit, we could then both use the survey data to improve remote sensing, and use remote sensing data to spot discrepancies in the survey data. Essentially we felt this method delivered a lot of value for very little effort, and that it should be used much more commonly. There's a blog about it at https://www.ifpri.org/blog/leveraging-local-knowledge-map-and-link-agricultural-plots-farmer-practices
You've heard about the climate impacts of habitat destruction, but Goldstein et al. 2020 add a new twist. They identify which ecosystems have the most 'irrecoverable carbon,' which once lost can't be recovered in time to help with climate (see Figure 1). Figure 2 has the results; tropical peatlands followed by mangroves are clear priorities for protection (scored by total irrecoverable carbon rather than carbon density, although it's a similar ranking). The next tier is other peatlands, old-growth forests, marshes, and seagrasses. Other habitats generally have lower irrecoverable carbon. They note that they don't account for impacts of climate forcing, so boreal forest benefits are overestimated and tropical forests are underestimated. They only looked in the top meter of soil for peat, so over the long term the estimates for peat are likely on the low side. Finally, some of this carbon will be lost to climate change (e.g. thawing permafrost soils oxidizing) even without local conversion, so we should ensure protections for habitat actually address the dominant threat. You can read the article for free here: https://www.nature.com/articles/s41558-020-0738-8.epdf?author_access_token=poj3Fn4fkhP7_SK-yFKaTNRgN0jAjWel9jnR3ZoTv0OGVcM5jAVKvW5GyId6F2q0ve6uY5HlQ2nGzEyTtPTSUIuTOykc5x3bM9HdnsqyTZdAL_YY02dyngC4HUYA6LeqaLA-r26jCXCx1eABw5d_FQ%3D%3D
Fisher, J. R. B., Wood, S. A., Bradford, M. A., & Kelsey, T. R. (2020). Improving scientific impact: How to practice science that influences environmental policy and management. Conservation Science and Practice, e0210. https://doi.org/10.1111/csp2.210
Goldstein, A., Turner, W. R., Spawn, S. A., Anderson-Teixeira, K. J., Cook-Patton, S., Fargione, J., … Hole, D. G. (2020). Protecting irrecoverable carbon in Earth’s ecosystems. Nature Climate Change, 10(4), 287–295. https://doi.org/10.1038/s41558-020-0738-8
Masuda, Y. J., Fisher, J. R. B., Zhang, W., Castilla, C., Boucher, T. M., & Blundo-Canto, G. (2020). A respondent-driven method for mapping small agricultural plots using tablets and high resolution imagery. Journal of International Development. https://doi.org/10.1002/jid.3475
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 http://sciencejon.blogspot.com/