SUPPORTING INFORMATION:
S1 Appendix. Survey questionnaire. Multiple images used in the survey have been omitted
because not all images are part of the creative commons.
S2 Appendix. De-identified data set.
S1 Table. Survey respondents’ demographic characteristics and ownership of domestic animals.
S2 Table. Confirmatory factor analysis for respondents’ support for biosecurity for different survey versions that presented the ecological impacts, economic impacts, human
health and wellbeing impacts, or all impacts of pathogen transmission.
S3 Table. Distribution of respondents’ prior knowledge of reasons for herpetological
imports (n = 2,007).
S4 Table. Confirmatory factor analysis for respondents’ prior knowledge of reasons for
herpetological imports (‘knowledge of herpetological imports’) for different survey versions that presented the ecological impacts, economic impacts, human health and wellbeing impacts, or all impacts of pathogen transmission.
S5 Table. Distribution of responses to the question “How much do you like or dislike the
following animals?” (n = 2,007).
S6 Table. Confirmatory factor analysis for respondents’ ‘attitudes towards herpetofauna’
for different survey versions that presented the ecological impacts, economic impacts,
human health and wellbeing impacts, or all impacts of pathogen transmission.
S7 Table. Distribution of responses to the questions used to measure respondents’ sensitivity to general health risks (n = 2,007).
S8 Table. Confirmatory factor analysis for the importance that respondents placed on protecting the health of animals in the live animal trade, native wildlife, the natural environment, pets, and livestock (‘sensitivity to general health risks’) for different survey versions
that presented the ecological impacts, economic impacts, human health and wellbeing
impacts, or all impacts of pathogen transmission.
S9 Table. Distribution of responses to the questions used to measure respondents’ sensitivity to herpetological trade risks (n = 2,007).
S10 Table. Confirmatory factor analysis for respondents’ level of concern about pathogen
transmission from captive herpetofauna to other captive animals, native wildlife, pets,
livestock, and humans (‘sensitivity to herpetological trade risk’) for different survey versions that presented the ecological impacts, economic impacts, human health and wellbeing impacts, or all impacts of pathogen transmission.
S11 Table. Distribution of respondents’ risk perceptions pertaining to transmission of Bd,
Bsal, ranaviruses and Salmonella by captive herpetofauna (n = 2,007).
S12 Table. Confirmatory factor analysis for respondents’ ‘susceptibility to herpetological
pathogen transmission’ for different survey versions that presented the ecological impacts,
economic impacts, human health and wellbeing impacts, or all impacts of pathogen transmission.
S13 Table. Distribution of respondents’ risk concerns about the ecological impacts of pathogen transmission through the herpetological trade (n = 995).
S14 Table. Confirmatory factor analysis for respondents’ concern pertaining to ecological
impacts of pathogen transmission through the herpetological trade (‘sensitivity to ecological risks’).
S15 Table. Distribution of respondents’ risk concerns about the economic impacts of pathogen transmission through the herpetological trade (n = 995).
(PDF)
S16 Table. Confirmatory factor analysis for respondents’ concern pertaining to economic
impacts of pathogen transmission through the herpetological trade (‘sensitivity to economic risks’).
S17 Table. Distribution of respondents’ risk perceptions related to the economic impacts
of pathogen transmission through the live herpetological trade (n = 995).
S18 Table. Confirmatory factor analysis for respondents’ perceived ‘susceptibility to economic risks’ associated with pathogen transmission through the live herpetological trade.
S19 Table. Distribution of respondents’ concerns about the human health and wellbeing impacts of pathogen transmission through the live herpetological trade (n = 993).
S20 Table. Confirmatory factor analysis for respondents’ concern pertaining to human health and wellbeing impacts of pathogen transmission through the live herpetological trade (‘sensitivity to human health and wellbeing risks’).
S21 Table. Respondents’ trust in the government to mitigate pathogen transmission risks associated with the live herpetological trade (n = 2,007).
S22 Table. Confirmatory factor analysis for respondents’ ‘social trust’ for different survey versions that presented the ecological impacts, economic impacts, human health and wellbeing impacts, or all impacts of pathogen transmission.
S23 Table. Distribution of responses to the Environmental Portrait Value Questionnaire: “Below are some statements about a random man/woman/person.
How similar is this person to you?” (n = 2,007).
S24 Table. Confirmatory factor analysis for respondents’ ‘biospheric values’.
S25 Table. Confirmatory factor analysis for respondents’ ‘altruistic values’.
S26 Table. Confirmatory factor analysis for respondents’ ‘hedonic values’.
S27 Table. Confirmatory factor analysis for respondents’ ‘egoistic values’.
S28 Table. Structural equation model of respondents’ support for improved biosecurity measures when presented with the ecological risks associated with pathogen transmission through the live herpetological trade (model 1, n = 507).
S29 Table. Structural equation model of respondents’ support for improved biosecurity measures when presented with the economic risks associated with pathogen transmission through the live herpetological trade (model 2, n = 507).
S30 Table. Structural equation model of respondents’ support for improved biosecurity measures when presented with the human health and wellbeing risks associated with pathogen transmission through the live herpetological trade (model 3, n = 505).
S31 Table. Structural equation model of respondents’ support for improved biosecurity measures when presented with the ecological, economic, and human health and wellbeing risks associated with pathogen transmission through the live herpetological trade (model 4, n = 488).
