Climate might directly or indirectly affect the population dynamics of several rodent species including Apodemus flavicollis, a very common forest small mammal and an important reservoir for several emerging zoonotic pathogens. We thus investigated how climatic data alone might be useful to predict rodent population dynamics. We used rodent data gathered through a long-term monitoring effort carried out for 17 years (2000–2017) using a capture-mark-recapture method in northern Italy. Temperature and precipitation data were obtained from a weather station close to the study area. Linear models were implemented to assess how mice density was associated with weather conditions considering various time lags. We found that warmer summers 2 years before sampling were positively related to A. flavicollis annual average population densities. Conversely, precipitation occurring the autumn 1 year before sampling negatively influenced mice abundance. To the best of our knowledge, this is one of the first attempts at investigating how rodent abundance is associated with climatic conditions in the central European region of the Alps. Our results highlight important correlations, which eventually might be used for estimating risk of transmission of rodent-borne zoonotic pathogens
Marini, G.; Arnoldi, D.; Rizzoli, A.; Tagliapietra, V. (2023). Estimating rodent population abundance using early climatic predictors. EUROPEAN JOURNAL OF WILDLIFE RESEARCH, 69 (2): 36. doi: 10.1007/s10344-023-01666-2 handle: https://hdl.handle.net/10449/79075
Estimating rodent population abundance using early climatic predictors
Marini, Giovanni
Primo
;Arnoldi, Daniele;Rizzoli, Annapaola;Tagliapietra, ValentinaUltimo
2023-01-01
Abstract
Climate might directly or indirectly affect the population dynamics of several rodent species including Apodemus flavicollis, a very common forest small mammal and an important reservoir for several emerging zoonotic pathogens. We thus investigated how climatic data alone might be useful to predict rodent population dynamics. We used rodent data gathered through a long-term monitoring effort carried out for 17 years (2000–2017) using a capture-mark-recapture method in northern Italy. Temperature and precipitation data were obtained from a weather station close to the study area. Linear models were implemented to assess how mice density was associated with weather conditions considering various time lags. We found that warmer summers 2 years before sampling were positively related to A. flavicollis annual average population densities. Conversely, precipitation occurring the autumn 1 year before sampling negatively influenced mice abundance. To the best of our knowledge, this is one of the first attempts at investigating how rodent abundance is associated with climatic conditions in the central European region of the Alps. Our results highlight important correlations, which eventually might be used for estimating risk of transmission of rodent-borne zoonotic pathogensFile | Dimensione | Formato | |
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