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Limits on phenological response to high temperature in the Arctic

  • Berner, L. T. et al. Summer warming explains widespread but not uniform greening in the Arctic tundra biome. Nat. Commun. 11, 4621 (2020).

    Article 
    ADS 
    CAS 

    Google Scholar 

  • Elmendorf, S. C. et al. Plot-scale evidence of tundra vegetation change and links to recent summer warming. Nat. Clim. Change 2, 453–457 (2012).

    Article 
    ADS 

    Google Scholar 

  • Overland, J. E. et al. Surface air temperature. In Arctic Report Card: Update for 2019 (eds Richter-Menge, J. et al.) (U.S. National Park Service, 2020).

    Google Scholar 

  • Post, E., Steinman, B. A. & Mann, M. E. Acceleration of phenological advance and warming with latitude over the past century. Sci. Rep. 8, 3927 (2018).

    Article 
    ADS 

    Google Scholar 

  • Diepstraten, R. A. E., Jessen, T. D., Fauvelle, C. M. D. & Musiani, M. M. Does climate change and plant phenology research neglect the Arctic tundra?. Ecosphere 9, e02362 (2018).

    Article 

    Google Scholar 

  • Flynn, D. F. B. & Wolkovich, E. M. Temperature and photoperiod drive spring phenology across all species in a temperate forest community. New Phytol. 219, 1353–1362 (2018).

    Article 
    CAS 

    Google Scholar 

  • Billings, W. D. & Bliss, L. C. An alpine snowbank environment and its effects on vegetation, plant development, and productivity. Ecology 40, 388–397 (1959).

    Article 

    Google Scholar 

  • Billings, W. D. & Mooney, H. A. The ecology of arctic and alpine plants. Biol. Rev. 43, 481–529 (1968).

    Article 

    Google Scholar 

  • Sørensen, T. Temperature relations and phenology of the northeast Greenland flowering plants. Meddr Gronland 1–305 (1941).

  • Barrett, R. T. & Hollister, R. D. Arctic plants are capable of sustained responses to long-term warming. Polar Res. 35, 25405 (2016).

    Article 

    Google Scholar 

  • Julitta, T. et al. Using digital camera images to analyse snowmelt and phenology of a subalpine grassland. Agric. For. Meteorol. 198–199, 116–125 (2014).

    Article 
    ADS 

    Google Scholar 

  • Petraglia, A. et al. Responses of flowering phenology of snowbed plants to an experimentally imposed extreme advanced snowmelt. Plant Ecol. 215, 759–768 (2014).

    Article 

    Google Scholar 

  • Semenchuk, P. R. et al. High Arctic plant phenology is determined by snowmelt patterns but duration of phenological periods is fixed: An example of periodicity. Environ. Res. Lett. 11, 125006 (2016).

    Article 
    ADS 

    Google Scholar 

  • Hollister, R. D., Webber, P. J. & Bay, C. Plant response to temperature in northern Alaska: Implications for predicting vegetation change. Ecology 86, 1562–1570 (2005).

    Article 

    Google Scholar 

  • Oberbauer, S. et al. Phenological response of tundra plants to background climate variation tested using the International Tundra Experiment. Philos. Trans. R. Soc. B Biol. Sci. 368, 20120481 (2013).

    Article 
    CAS 

    Google Scholar 

  • Tieszen, L. L. Photosynthesis in the principal Barrow, Alaska, species: A summary of field and laboratory responses. In Vegetation and Production Ecology of an Alaskan Arctic Tundra (ed. Tieszen, L. L.) 241–268 (Springer, 1978).

    Chapter 

    Google Scholar 

  • Körner, Ch. CO2 exchange in the alpine sedge Carex curvula as influenced by canopy structure, light and temperature. Oecologia 53, 98–104 (1982).

    Article 
    ADS 

    Google Scholar 

  • Tieszen, L. L. Photosynthesis and respiration in arctic tundra grasses: Field light intensity and temperature responses. Arct. Alp. Res. 5, 239–251 (1973).

    Article 
    CAS 

    Google Scholar 

  • Huang, M. et al. Air temperature optima of vegetation productivity across global biomes. Nat. Ecol. Evol. 3, 772–779 (2019).

    Article 

    Google Scholar 

  • Marchand, F. L., Mertens, S., Kockelbergh, F., Beyens, L. & Nijs, I. Performance of high arctic tundra plants improved during but deteriorated after exposure to a simulated extreme temperature event. Glob. Change Biol. 11, 2078–2089 (2005).

    Article 
    ADS 

    Google Scholar 

  • Yan, W. An equation for modelling the temperature response of plants using only the cardinal temperatures. Ann. Bot. 84, 607–614 (1999).

    Article 

    Google Scholar 

  • Zhou, G. & Wang, Q. A new nonlinear method for calculating growing degree days. Sci. Rep. 8, 10149 (2018).

    Article 
    ADS 

    Google Scholar 

  • Kramer, K. Selecting a model to predict the onset of growth of Fagus sylvatica. J. Appl. Ecol. 31, 172 (1994).

    Article 

    Google Scholar 

  • Nakano, Y., Higuchi, Y., Sumitomo, K. & Hisamatsu, T. Flowering retardation by high temperature in chrysanthemums: Involvement of FLOWERING LOCUS T-like 3 gene repression. J. Exp. Bot. 64, 909–920 (2013).

    Article 
    CAS 

    Google Scholar 

  • del Olmo, I., Poza-Viejo, L., Piñeiro, M., Jarillo, J. A. & Crevillén, P. High ambient temperature leads to reduced FT expression and delayed flowering in Brassica rapa via a mechanism associated with H2A.Z dynamics. Plant J. 100, 343–356 (2019).

    Article 

    Google Scholar 

  • Wolkovich, E. M. et al. Warming experiments underpredict plant phenological responses to climate change. Nature 485, 494 (2012).

    Article 
    ADS 
    CAS 

    Google Scholar 

  • Hollister, R. D. et al. A review of open top chamber (OTC) performance across the ITEX Network. Arct. Sci. https://doi.org/10.1139/AS-2022-0030 (2022).

    Article 

    Google Scholar 

  • Bütikofer, L. et al. The problem of scale in predicting biological responses to climate. Glob. Change Biol. 26, 6657–6666 (2020).

    Article 
    ADS 

    Google Scholar 

  • Gu, S. Growing degree hours—A simple, accurate, and precise protocol to approximate growing heat summation for grapevines. Int. J. Biometeorol. 60, 1123–1134 (2016).

    Article 
    ADS 
    CAS 

    Google Scholar 

  • Roltsch, W. J., Zalom, F. G., Strawn, A. J., Strand, J. F. & Pitcairn, M. J. Evaluation of several degree-day estimation methods in California climates. Int. J. Biometeorol. 42, 169–176 (1999).

    Article 
    ADS 

    Google Scholar 

  • Richardson, A. D. et al. Ecosystem warming extends vegetation activity but heightens vulnerability to cold temperatures. Nature 560, 368–371 (2018).

    Article 
    ADS 
    CAS 

    Google Scholar 

  • Ettinger, A. K., Buonaiuto, D. M., Chamberlain, C. J., Morales-Castilla, I. & Wolkovich, E. M. Spatial and temporal shifts in photoperiod with climate change. New Phytol. 230, 462–474 (2021).

    Article 
    CAS 

    Google Scholar 

  • Seyednasrollah, B., Swenson, J. J., Domec, J.-C. & Clark, J. S. Leaf phenology paradox: Why warming matters most where it is already warm. Remote Sens. Environ. 209, 446–455 (2018).

    Article 
    ADS 

    Google Scholar 

  • Breshears, D. D. et al. Underappreciated plant vulnerabilities to heat waves. New Phytol. 231, 32–39 (2021).

    Article 

    Google Scholar 

  • Chaudhry, S. & Sidhu, G. P. S. Climate change regulated abiotic stress mechanisms in plants: A comprehensive review. Plant Cell Rep. 41, 1–31 (2022).

    Article 
    CAS 

    Google Scholar 

  • Sun, X. et al. Global diurnal temperature range (DTR) changes since 1901. Clim. Dyn. 52, 3343–3356 (2019).

    Article 

    Google Scholar 

  • Ballinger, T. J. NOAA Arctic Report Card 2021: Surface Air Temperature. https://doi.org/10.25923/53XD-9K68 (2021).

  • Jagadish, S. V. K., Way, D. A. & Sharkey, T. D. Plant heat stress: Concepts directing future research. Plant Cell Environ. 44, 1992–2005 (2021).

    Article 
    CAS 

    Google Scholar 

  • Gilmore, E. C. Jr. & Rogers, J. S. Heat units as a method of measuring maturity in corn. Agron. J. 50, 611–615 (1958).

    Article 

    Google Scholar 

  • Sánchez, B., Rasmussen, A. & Porter, J. R. Temperatures and the growth and development of maize and rice: A review. Glob. Change Biol. 20, 408–417 (2014).

    Article 
    ADS 

    Google Scholar 

  • Molitor, D., Junk, J., Evers, D., Hoffmann, L. & Beyer, M. A high-resolution cumulative degree day-based model to simulate phenological development of grapevine. Am. J. Enol. Vitic. 65, 72–80 (2014).

    Article 

    Google Scholar 

  • CaraDonna, P. J., Iler, A. M. & Inouye, D. W. Shifts in flowering phenology reshape a subalpine plant community. Proc. Natl. Acad. Sci. 111, 4916–4921 (2014).

    Article 
    ADS 
    CAS 

    Google Scholar 

  • Inouye, B. D., Ehrlén, J. & Underwood, N. Phenology as a process rather than an event: From individual reaction norms to community metrics. Ecol. Monogr. 89, e01352 (2019).

    Article 

    Google Scholar 

  • Miles, W. T. S. et al. Quantifying full phenological event distributions reveals simultaneous advances, temporal stability and delays in spring and autumn migration timing in long-distance migratory birds. Glob. Change Biol. 23, 1400–1414 (2017).

    Article 
    ADS 

    Google Scholar 

  • Moussus, J.-P., Julliard, R. & Jiguet, F. Featuring 10 phenological estimators using simulated data. Methods Ecol. Evol. 1, 140–150 (2010).

    Article 

    Google Scholar 

  • Dowle, M. & Srinivasan, A. data.table: Extension of ‘data.frame’ (2019).

  • Auguie, B. egg: Extensions for ‘ggplot2’: Custom Geom, Custom Themes, Plot Alignment, Labelled Panels, Symmetric Scales, and Fixed Panel Size (2019).

  • Wood, S. & Scheipl, F. gamm4: Generalized Additive Mixed Models using ‘mgcv’ and ‘lme4’ (2020).

  • Auguie, B. gridExtra: Miscellaneous Functions for ‘Grid’ Graphics (2017).

  • Hamner, B. & Frasco, M. Metrics: Evaluation Metrics for Machine Learning (2018).

  • Gilli, M., Maringer, D. & Schumann, E. Numerical Methods and Optimization in Finance (Elsevier/Academic Press, 2019).

    MATH 

    Google Scholar 

  • Garnier, S. viridis: Default Color Maps from ‘matplotlib’ (2018).

  • Wickham, H. et al. Welcome to the Tidyverse. J. Open Source Softw. 4, 1686 (2019).

    Article 
    ADS 

    Google Scholar 


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