A social media-based framework for quantifying temporal changes to wildlife viewing intensity: Quantifying changes to wildlife viewing intensity
Ecological Modelling
; 476, 2023.
Article
in English
| Scopus | ID: covidwho-2244053
ABSTRACT
Documenting how human pressure on wildlife changes over time is important to minimise potential adverse effects through implementing appropriate management and policy actions;however, obtaining objective measures of these changes and their potential impacts is often logistically challenging, particularly in the natural environment. Here, we developed a modular stochastic model that infers the ratio of actual viewing pressure on wildlife in consecutive time periods (years) using social media, as this medium is widespread and easily accessible. Pressure was calculated from the number of times individual animals appeared in social media in pre-defined time windows, accounting for time-dependent variables that influence them (e.g. number of people with access to social media). Formulas for the confidence intervals of viewing pressure ratios were rigorously developed and validated, and corresponding uncertainty was quantified. We applied the developed framework to calculate changes to wildlife viewing pressure on loggerhead sea turtles (Caretta caretta) at Zakynthos island (Greece) before and during the COVID-19 pandemic (2019–2021) based on 2646 social media entries. Our model ensured temporal comparability across years of social media data grouped in time window sizes, by correcting for the interannual increase of social media use. Optimal sizes for these windows were delineated, reducing uncertainty while maintaining high time-scale resolution. The optimal time window was around 7-days during the peak tourist season when more data were available in all three years, and >15 days during the low season. In contrast, raw social media data exhibited clear bias when quantifying changes to viewing pressure, with unknown uncertainty. The framework developed here allows widely-available social media data to be used objectively when quantifying temporal changes to wildlife viewing pressure. Its modularity allowed viewing pressure to be quantified for all data combined, or subsets of data (different groups, situations or locations), and could be applied to any site supporting wildlife exposed to tourism. © 2022 The Author(s)
Greece; Ionian Sea; Mediterranean Sea; Zakynthos Canyon; Animals; Ecology; Social networking (online); Stochastic models; Uncertainty analysis; Eco-tourisms; Human pressures; Monitoring tourism pressure; Social media; Social media datum; Stochastic ecological model; Temporal change; Time windows; Uncertainty; Uncertainty quantifications; ecological modeling; ecotourism; environmental monitoring; stochasticity; temporal variation; wildlife management; Stochastic systems; Stochastic ecological modelling; Uncertainty quantification
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
Ecological Modelling
Year:
2023
Document Type:
Article
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