
Best environmental predictors of breeding phenology differ with elevation in a common woodland bird species
Author(s) -
Bison Marjorie,
Yoccoz Nigel G.,
Carlson Bradley,
Klein Geoffrey,
Laigle Idaline,
Van Reeth Colin,
Asse Daphné,
Delestrade Anne
Publication year - 2020
Publication title -
ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.17
H-Index - 63
ISSN - 2045-7758
DOI - 10.1002/ece3.6684
Subject(s) - phenology , snowmelt , larch , ecology , climate change , snow , altitude (triangle) , elevation (ballistics) , physical geography , environmental science , biology , geography , geometry , mathematics , meteorology , surface runoff
Temperatures in mountain areas are increasing at a higher rate than the Northern Hemisphere land average, but how fauna may respond, in particular in terms of phenology, remains poorly understood. The aim of this study was to assess how elevation could modify the relationships between climate variability (air temperature and snow melt‐out date), the timing of plant phenology and egg‐laying date of the coal tit ( Periparus ater ). We collected 9 years (2011–2019) of data on egg‐laying date, spring air temperature, snow melt‐out date, and larch budburst date at two elevations (~1,300 m and ~1,900 m asl) on a slope located in the Mont‐Blanc Massif in the French Alps. We found that at low elevation, larch budburst date had a direct influence on egg‐laying date, while at high‐altitude snow melt‐out date was the limiting factor. At both elevations, air temperature had a similar effect on egg‐laying date, but was a poorer predictor than larch budburst or snowmelt date. Our results shed light on proximate drivers of breeding phenology responses to interannual climate variability in mountain areas and suggest that factors directly influencing species phenology vary at different elevations. Predicting the future responses of species in a climate change context will require testing the transferability of models and accounting for nonstationary relationships between environmental predictors and the timing of phenological events.