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Stranger danger: A meta-analysis of the dear enemy hypothesis

Cite this dataset

Werba, Jo; Stuckert, Adam; Edwards, Matthew; McCoy, Michael (2022). Stranger danger: A meta-analysis of the dear enemy hypothesis [Dataset]. Dryad.


The dear enemy hypothesis predicts that territorial individuals will be less aggressive toward known neighbors than to strangers. This hypothesis has been well studied and there is a wealth of data demonstrating its prevelance among some taxa. However, a quantitative synthesis is needed to test the generality of the phenomenon, identify key mechanisms driving the behavior, and guide future research. Here we made a comprehensive collection of Dear Enemy data from 138 studies representing 105 species spread over eight taxonomic classes. The associated paper finds that Dear Enemy is a common phenomenon but drivers of this phenomenon are still understudied and current knowledge is unable to disentangle competing hypotheses of drivers of this behavior.


This data was collected from 138 unique studies of Dear Enemy behavior. Data was collected from several sequential literature searches on Science Direct and Google Scholar. Our initial search in Science direct using search term “dear enemy” in journals related to Agricultural and Biological Sciences, Earth and Planetary Sciences, and Environmental Science resulted in 221 unique hits. Later searches in Google Scholar using the key words neighbor or neighbour and “dear enemy” yielded 712 and 68425 studies respectively. We excluded studies if the dear enemy hypothesis, neighbor-stranger discrimination, or nasty neighbor phenomenon were not mentioned in the abstract, if the study did not directly test individual territorial responses to conspecifics or if measures of variance were missing. We contacted authors to acquire data whenever possible. Data was extracted with Data thief or from tables.

Usage notes

We have included a README for the data set: Stranger_Danger_Data_README.txt and a README for the code: README.txt