High-resolution app data reveal sustained increases in recreational fishing effort in Europe during and after COVID-19 lockdowns

Abstract

It is well recognized that COVID-19 lockdowns impacted human interactions with natural ecosystems. One example is recreational fishing, which, in developed countries, involves approximately 10% of people. Fishing licence sales and observations at angling locations suggest that recreational fishing effort increased substantially during lockdowns. However, the extent and duration of this increase remain largely unknown. We used four years (2018-2021) of high-resolution data from a personal fish-finder device to explore the impact of COVID-19 lockdowns on angling effort in four European countries. We show that relative device use and angling effort increased 1.2-3.8-fold during March-May 2020 and generally remained elevated even at the end of 2021. Fishing during the first lockdown also became more frequent on weekdays. Statistical models explained 50-70% of the variation, suggesting that device use and angling effort were relatively consistent and predictable through space and time. Our study demonstrates that recreational fishing behaviour can change substantially and rapidly in response to societal shifts, with profound ecological, human well-being and economic implications. We also show the potential of angler devices and smartphone applications for high-resolution fishing effort analysis and encourage more extensive science and industry collaborations to take advantage of this information.

Keywords: COVID-19; anthropause; inland and coastal fisheries; non-probabilistic methods; recreational fishing effort; smartphone applications.

Figure 1.

Estimated mean daily standardized fishing effort (as the number of sonar device users) per administrative unit during weekdays and weekends by country, shown for each study period (pre-lockdown, during lockdown 1, post-lockdown 1, during lockdown 2, post-lockdown 2). The effort was estimated for each country's average administrative unit size after accounting for variation due to season, year and the uptake of the device. The effort is scaled to the weekday of the pre-lockdown stage, which is therefore set to 1 (shown as a dashed horizontal line). For effort predictions across all administrative unit population sizes, see electronic supplementary material, figure S9. The error bars represent 95% confidence intervals from the general linear mixed effect model predictions. Note that visualization of single fixed effects in mixed effect models does not reveal the full effect size, since a lot of variation is explained by random and other fixed effects. Therefore, fixed effect significance should not be assessed from this figure, but from model outputs presented in table 2.

Figure 2.

Association between relative fishing effort per administrative unit and human population density for the pre-lockdown period. Associations remained similar for all five studied periods (electronic supplementary material, figure S9).