Estimating the timing of animal and plant phenophases in a boreal landscape in Northern Sweden (Västerbotten) using camera traps

Detta är en Master-uppsats från SLU/Dept. of Wildlife, Fish and Environmental Studies

Sammanfattning: It is becoming more important to understand shifts in plant and animal phenology as climate is changing. However, the methods to study phenology used so far have shown to be limited over time and space. Therefore, a method such as camera traps is interesting to use since it bridges satellite remote sensing and on-ground observation methods. Over 53 weeks, our cameras have recorded daily changes in plant communities and the passages of all animals across a 200 km2 area in Västerbotten, Northern Sweden. This allowed the analysis of habitat types, plant and animal diversities and abundances, phenology as well as the changes in temperature and snow cover day after day through the software TRAPPER. The influence of temperature and daylength on deciduous species has been highlighted with a clear matching pattern between increasing temperatures and the onset of leaves. The presence of snow has shown to be of a greater impact for heath species. However, despite the lack of significant results for ungulates phenology, strong patterns have been assessed between the change in mountain hare coat colour and the whiteness of the landscape. The timing of such changes happened simultaneously within the same week or with more or less two weeks with week 15 (April 10th-16th) and week 47 (November 20th -26th), as breakpoint weeks showing changes in plant vegetative phenophases, shifts in both temperatures and snow cover and change in mountain hare coat colour. Whereas some shifts are easily observed such as vegetative phenophases and changes in coat colour for mountain hare, reproductive phenophases, fruit/seed phenophases for deciduous and heath types as well as vegetative phenophases for coniferous type, have been difficult to assess. However, camera traps have appeared to be a reliable tool, providing accurate data on various variables, over a long time and a broad area.

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