I have a PhD in Ecology and a BS in CS. I find the bifurcation portrayed here exaggerated. The best modern ecologists merge rigorous fieldwork with advanced modeling; we need to harness vast, underutilized datasets, not just generate new ones.

The 'computer scientist' quote illustrates a frustrating trend: tech-centric 'drive-bys' that lack the ecological context required for good science. On the flip side, the 'old guard' who ignore modern data assimilation are leaving massive potential on the table. The field is rightfully shifting from site-specific anecdotes to foundational, broad-scale work, but we need both skillsets to do it justice.

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ip26 5 hours ago | parent [-]

Seems to me there are potentially opportunities for greater returns to data gathering work as quality data can inform many more papers in the future. How that will work still needs to be brokered…

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tony_cannistra 5 hours ago | parent | next [-]

Absolutely. There are a few excellent projects in this vein, as well - where deeper investment in data gathering, done in ways to optimize its broad use in research, is occurring.

An example is the National Science Foundation NEON project, which is a long-term ecological monitoring initiative with common field methodologies across 81 North American sites. https://www.neonscience.org/

	▲	jofer 4 hours ago \| parent [-]
		Huh. I weirdly enough have worked with a lot of those sites from the remote sensing side, but never really know what the overall project was. Just "use the NEON sites for examples". I should have looked it up more at the time. Thanks for sharing!

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nick49488171 5 hours ago | parent | prev [-]

It leads to hoarding data (or artifacts) within labs for exclusive analysis.

	▲	marcus_holmes 4 hours ago \| parent [-]
		This. It's this broken publishing model we have at the moment that is the real problem. You should be able to publish data as a paper and get academic credit for doing that. Then others can publish analyses of that data, crediting you.