The city changes the daily activity of urban adapters: Camera-traps study ofApodemus agrariusbehaviour and new approaches to data analysis
Artykuł w czasopiśmie
MNiSW
140
Lista 2021
| Status: | |
| Autorzy: | Łopucki Rafał, Kiersztyn Adam |
| Dyscypliny: | |
| Aby zobaczyć szczegóły należy się zalogować. | |
| Rok wydania: | 2020 |
| Wersja dokumentu: | Drukowana | Elektroniczna |
| Język: | angielski |
| Wolumen/Tom: | 110 |
| Numer artykułu: | 105957 |
| Strony: | 1 - 9 |
| Web of Science® Times Cited: | 12 |
| Scopus® Cytowania: | 12 |
| Bazy: | Web of Science | Scopus | Biological Abstracts | BIOSIS | Chemical Abstracts |
| Efekt badań statutowych | NIE |
| Materiał konferencyjny: | NIE |
| Publikacja OA: | TAK |
| Licencja: | |
| Sposób udostępnienia: | Witryna wydawcy |
| Wersja tekstu: | Ostateczna wersja opublikowana |
| Czas opublikowania: | W momencie opublikowania |
| Data opublikowania w OA: | 30 listopada 2020 |
| Abstrakty: | angielski |
| As a result of the widespread use of camera-traps, the analysis of the daily activity of animals based on field data has become a common practice, which is addressed in ecological studies. The more frequent consideration of this issue in ecological research, however, has not led to any advancement in the techniques of analysis of these activity patterns. In this work, we have two main aims: ecological and methodological. Firstly, using camera-traps in the winter period, we examine the differences in the daily activity of wild small mammal populations, which are affected or unaffected by urbanization; we treated changes in daily activity as indicators of species adaptation to urban conditions. Secondly, we test four different approaches to data analysis regarding the determination and comparison of activity patterns, which are not based on the traditional methods that have been used to date, such as particle swarm optimization (PSO), neural networks, decision trees and cluster analysis. We found that the urbanized environment modifies the daily activity patterns of the mammals studied. Animals from the urban population have a longer active period than their rural counterparts and can forage under more favourable thermal conditions, so that the energetic cost of foraging is lower. PSO and neural networks allow for a more detailed analysis of patterns of daily activity than traditional methods, and their results correspond well with each other. Daily activity analysis shows great potential in the application of new statistical approaches that could supplement and enrich the traditionally used methods (e.g. the kernel density estimation). Our approach may help researchers to gain a broader perspective during their analysis of daily activity patterns and lead to a better description of the ecology of the species or even to more balanced wildlife management decisions. |
