Ana Benítez-López, Luca Santini

Aim
Field ecologists and macroecologists often compete for the same grants and academic positions, with the former producing original data that the latter generally use for model parameterization. Original data are usually cited only in the supplementary materials thereby not counting formally as citations, creating an unfair system where field ecologists are routinely under-acknowledged and possibly disadvantaged in the race for funding and positions. Here we explore how the performance of authors contributing ecological data would change if all the citations to their work would be accounted for by bibliometric indicators.

Location
Worldwide

Time period
2008-2017

Major taxa studied
Homo sapiens academiae

Methods
We collected the track record of >2300 authors from Google Scholar and citation data from 600 papers published in 40 ecology journals, including field-based, conservation, general ecology and macroecology studies. Then we parameterize a simulation that mimics the current publishing system for ecologists and assessed author rankings based on number of citations, H-Index, Impact Factor and number of publications under a scenario where supplementary citations count.

Results
We found weak evidence for field ecologists being lower ranked than macroecologists or general ecologists, with publication rate being the main predictor of author performance. Accounting for supplementary citations in bibliometrics did not substantially change the current ranking dynamics.

Main conclusions
Current ranking dynamics are largely unaffected by supplementary citations as they are 10 times less than the number of main text citations. This is exacerbated by the common practice of citing datasets assembled by previous papers instead than the original articles. Nonetheless, researcher performance evaluations should include criteria that better capture authors’ contribution of new, publicly available, data. This could encourage field ecologists to collect and store new data in a systematic manner, thereby mitigating the data patchiness and bias in macroecology studies, and further accelerating the advancement of Ecology.