Fig 1.
Study locations (black rectangles) containing peatland ponds where camera traps were deployed in 2020 and 2021, in the provinces of Lapland (1), Northern Ostrobothnia (2), and North Karelia (3). Note that due to map scale, individual peatland ponds (see an example of one in Fig 2) are not visible on the map. The maps were drawn under CC BY 3.0 (data by OpenStreetMap, under ODbL). The inset map was drawn using Natural Earth map data.
Fig 2.
a) The camera placement in one of the study sites, a peatland pond Pirttilammit in North Karelia.
The rectangles denote motion triggered and circles time-lapse cameras, with the years marked in different colour, and b) an example of an image where taiga bean geese were captured with a PIR sensor triggered camera in Pirttilammit, North Karelia, in 2021.
Table 1.
Summary of candidate count models. Summary of candidate models ran to investigate the effect of trigger type (time-lapse or motion sensor) on the daily count of taiga bean geese captured on game camera traps. ‘Effort’ means camera effort, which was calculated by totalling the number of 2 h time periods of recording per trigger type for each day. NB stands for negative binomial with two different parameterizations, NB1 (variance = μ(1 + ϕ), where µ is the mean (or expected count) and ϕ is the dispersion parameter of the negative binomial distribution) and NB2 (variance = µ(1 + µ/ϕ)) [36,37]. Models are ranked by AICc from lowest (AICc-top) to highest. The table includes the number of estimated parameters, K; both AICc and ΔAICc which is AICc minus the lowest AICc and the negative log-likelihood, L.
Table 2.
Summary of candidate models for capture probability. Summary of candidate models ran to investigate the effect of trigger type on the capture probability (probability of at least one goose being present in photos during one day) of taiga bean geese captured on game camera traps. ‘Effort’ means camera effort, which was calculated by totalling the number of 2 h time periods of recording per trigger type for each day. Models are ranked by AICc from lowest (AICc-top) to highest. The table includes the number of estimated parameters, K; both AICc and ΔAICc which is AIC, minus the lowest AICc and the negative log-likelihood, L.
Fig 3.
Conditional effects (on a response scale) of a) year and b) trigger type on the total number of taiga bean geese captured per day (goose count) with game camera traps on peatland ponds in Finland between 2020 and 2021.
The difference was significant between years (p < 0.001) but not significant between trigger types (p = 0.129). Points represent the mean and whiskers the 95% confidence interval.
Fig 4.
Conditional effects (on a response scale) of a) year, b) trigger type, and c) camera effort on the daily capture probability of taiga bean geese (probability of at least one goose being present in photos during one day) photographed with game camera traps.
Camera effort is the number of 2 h time periods of recording per trigger type for each day. The difference was significant between years (p < 0.001) and marginally significant between trigger types (p = 0.049). The amount of camera effort had a significant positive effect on the daily capture probability (p < 0.001). Points represent the mean and whiskers the 95% confidence interval.