15As interdisciplinary branches of ecology are developing rapidly in the 21 st 16 century, contents of ecological researches have become more abundant 17 than ever before. Along with the exponential growth of number of 18 published literature, it is more and more difficult for ecologists to get a 19 clear picture of their discipline. Nevertheless, the era of big data has 20 brought us massive information of well documented historical literature 21 and various techniques of data processing, which greatly facilitates the 22 implementation of bibliometric analysis on ecology. Frequency has long 23 been used as the primary metric in keyword analysis to detect ecological 24 hotspots, however, this method could be somewhat biased. In our study, 25 we have suggested a method called PAFit to measure keyword popularity, 26 which considered ecology-related topics in a large temporal dynamical 27 knowledge network, and found out the popularity of ecological topics 28 follows the "rich get richer" and "fit get richer" mechanism. Feasibility of 29 network analysis and its superiority over simply using frequency had been 30 explored and justified, and PAFit was testified by its outstanding 31 performance of prediction on the growth of frequency and degree. In 32 addition, our research also encourages ecologists to consider their domain 33 knowledge in a large dynamical network, and be ready to participate in 34 interdisciplinary collaborations when necessary. 3 35