Read and listen.

A Spectrogram of music. The colour intensity is logarithmic!

I’m one of those people that loves to listen to music while working and reading. So here are a few papers I’m enjoying along with some tracks to accompany them.

A classic paper (May, 1976) deserves a classic tune. There is some challenging maths. But I have this (unrealistic but awesome) image of Lord Robert May bopping to Blue Oyster Cult and (Don’t fear) The Reaper and doing some differential equations.

I also like this paper by Olivero et al 2012 (Olivero et al., 2012), this is a good methods paper that provides some interesting insights to defining biogeographic regions. Being a methods paper you sometimes feel like you can hardly keep you head above water, but these tracks should help you swim.

A main part of my PhD is trying to describe drivers of deep-sea biodiversity at oceanic and global scales. This paper looks at the temporal variability in ocean productivity (Behrenfeld et al., 2006). One it’s an interesting paper, but two, temporal variability should be explored when looking at predictors of biodiversity. Here is a classic Thelonious Monk album which is well known for its treacherous tempo changes. If you’re not a Jazz fan, maybe pop is more your thang

And finally,  Belanger et al (2012) predict global biogeographic structure for shallow marine environments. An interesting paper that compares existing qualitative bioregionalisation to models built on correlations between species occurrence data and environmental predictors. Not surprisingly temperature came out on top.

Until next time,


Behrenfeld, M.J., O’Malley, R.T., Siegel, D.A., McClain, C.R., Sarmiento, J.L., Feldman, G.C., Milligan, A.J., Falkowski, P.G., Letelier, R.M. & Boss, E.S. (2006) Climate-driven trends in contemporary ocean productivity. Nature, 444, 752-755.

Belanger, C.L., Jablonski, D., Roy, K., Berke, S.K., Krug, A.Z. & Valentine, J.W. (2012) Global environmental predictors of benthic marine biogeographic structure. Proceedings of the National Academy of Sciences, 109, 14046-14051.

May, R.M. (1976) Simple mathematical models with very complicated dynamics. Nature, 261, 459-467.

Olivero, J., Márquez, A.L. & Real, R. (2012) Integrating Fuzzy Logic and Statistics to Improve the Reliable Delimitation of Biogeographic Regions and Transition Zones. Systematic Biology,

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1 Response to Read and listen.

  1. Pingback: Recent Qaecologist blog posts | Quantitative & Applied Ecology Group

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