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Experimentally warmer and drier conditions in an Arctic plant community reveal microclimatic controls on senescence

Livensperger, Carolyn, Steltzer, Heidi, Darrouzet‐Nardi, Anthony, Sullivan, Patrick F., Wallenstein, Matthew, Weintraub, Michael N.
Ecosphere 2019 v.10 no.4 pp. e02677
carbon, climate change, cold, color, ecological function, ecosystems, growing season, heat sums, mathematical models, microclimate, phenology, plant communities, plant growth, remote sensing, snowmelt, temperature, tundra, vascular plants, Arctic region
The timing and duration of the plant growing season and its period of peak activity have shifted globally in response to climate change. These changes alter the period of maximum and potential total carbon uptake, especially in highly seasonal environments such as the Arctic. Earlier plant growth has been observed, and if plant senescence remains the same or is delayed, growing season extension will likely lead to greater carbon uptake and growth. We used phenology data from a multifactor climate change experiment to examine how altered seasonality influences the timing and rate‐of‐senescence and to compare direct observations of individual plant senescence with mathematical models of onset‐of‐senescence based on near‐surface remote sensing. Our three‐year experiment in an Arctic tundra ecosystem altered plant microclimates through factorial warming and earlier snowmelt treatments. We found that (1) early snowmelt and warmer temperatures led to earlier remotely sensed onset‐of‐senescence, but did not alter the rate‐of‐senescence, (2) the timing of color change for individual vascular plants did not change in response to the treatments, leading to a mismatch with remotely sensed phenology, and (3) cumulative, phenologically dependent microclimate metrics (e.g., soil cold degree‐days) best predicted the onset‐of‐senescence. Our study highlights the complexity of observing and understanding controls over phenological shifts that affect plant growth and consequently ecosystem functions. Experimental studies that include multiple approaches to observe and model phenological changes and microclimate are critical to develop phenological forecasting models.