Phylogenetic estimates of species-level phenology improve ecological forecasting
admin August 15, 2024

Phylogenetic estimates of species-level phenology improve ecological forecasting

  • IPCC Climate Change 2014: Impacts, Adaptation, and Vulnerability (eds Field, C. B. et al) (Cambridge Univ. Press, 2014).

  • Parmesan, C. & Yohe, G. A globally coherent fingerprint of climate change impacts across natural systems. Nature 421, 37–42 (2003).

    Article 
    CAS 

    Google Scholar 

  • Richardson, A. D. et al. Climate change, phenology, and phenological control of vegetation feedbacks to the climate system. Agric. For. Meteorol. 169, 156–173 (2013).

    Article 

    Google Scholar 

  • Dietze, M. Ecological Forecasting (Princeton Univ. Press, 2017).

  • Lewis, A. S. et al. The power of forecasts to advance ecological theory. Methods Ecol. Evol. 14, 746–756 (2023).

    Article 

    Google Scholar 

  • Chuine, I. & Regniere, J. Process-based models of phenology for plants and animals. Annu. Rev. Ecol. Evol. Syst. 48, 159–182 (2017).

    Article 

    Google Scholar 

  • Ettinger, A. et al. Winter temperatures predominate in spring phenological responses to warming. Nat. Clim. Change 10, 1137–1142 (2020).

    Article 

    Google Scholar 

  • Moorcroft, P., Hurtt, G. & Pacala, S. A method for scaling vegetation dynamics: the ecosystem demography model (ED). Ecol. Monogr. 71, 557–585 (2001).

    Article 

    Google Scholar 

  • Griffith, D. M. et al. Lineage-based functional types: characterising functional diversity to enhance the representation of ecological behaviour in land surface models. New Phytol. 228, 15–23 (2020).

    Article 

    Google Scholar 

  • Fuccillo Battle, K. et al. Citizen science across two centuries reveals phenological change among plant species and functional groups in the northeastern US. J. Ecol. 110, 1757–1774 (2022).

    Article 

    Google Scholar 

  • Diez, J. M. et al. Forecasting phenology: from species variability to community patterns. Ecol. Lett. 15, 545–553 (2012).

    Article 

    Google Scholar 

  • Gelman, A. & Hill, J. Data Analysis Using Regression and Multilevel/Hierarchical Models (Cambridge Univ. Press, 2006).

  • Wiens, J. J. et al. Niche conservatism as an emerging principle in ecology and conservation biology. Ecol. Lett. 13, 1310–1324 (2010).

    Article 

    Google Scholar 

  • Freckleton, R. P., Harvey, P. H. & Pagel, M. Phylogenetic analysis and comparative data: a test and review of evidence. Am. Nat. 160, 712–726 (2002).

    Article 
    CAS 

    Google Scholar 

  • Kochmer, J. P. & Handel, S. N. Constraints and competition in the evolution of flowering phenology. Ecol. Monogr. 56, 303–325 (1986).

    Article 

    Google Scholar 

  • Willis, C. G., Ruhfel, B., Primack, R. B., Miller-Rushing, A. J. & Davis, C. C. Phylogenetic patterns of species loss in Thoreau’s woods are driven by climate change. Proc. Natl Acad. Sci. USA 105, 17029–17033 (2008).

    Article 
    CAS 

    Google Scholar 

  • Davies, T., Wolkovich, E., Kraft, N., Salamin, N. & Travers, S. E. Phylogenetic conservatism in plant phenology. J. Ecol. 101, 1520–1530 (2013).

    Article 

    Google Scholar 

  • CaraDonna, P. J. & Inouye, D. W. Phenological responses to climate change do not exhibit phylogenetic signal in a subalpine plant community. Ecology 96, 355–361 (2014).

    Article 

    Google Scholar 

  • Yang, Z. et al. Phylogenetic conservatism in heat requirement of leaf-out phenology, rather than temperature sensitivity, in Tibetan plateau. Agric. For. Meteorol. 304, 108413 (2021).

    Article 

    Google Scholar 

  • Rafferty, N. E. & Nabity, P. D. A global test for phylogenetic signal in shifts in flowering time under climate change. J. Ecol. 105, 627–633 (2017).

    Article 

    Google Scholar 

  • Larcher, W. Plant Physiological Ecology (Springer, 1980).

  • Bonamour, S., Chevin, L. M., Charmantier, A. & Teplitsky, C. Phenotypic plasticity in response to climate change: the importance of cue variation. Philos. Trans. R. Soc. B 374, 20180178 (2019).

    Article 

    Google Scholar 

  • Ackerly, D. Conservatism and diversification of plant functional traits: evolutionary rates versus phylogenetic signal. Proc. Natl Acad. Sci. USA 106, 19699–19706 (2009).

    Article 
    CAS 

    Google Scholar 

  • Davies, T. J., Regetz, J., Wolkovich, E. M. & McGill, B. J. Phylogenetically weighted regression: a method for modelling non-stationarity on evolutionary trees. Glob. Ecol. Biogeogr. 28, 275–285 (2019).

    Article 

    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 

  • Housworth, E. A., Martins, E. P. & Lynch, M. The phylogenetic mixed model. Am. Nat. 163, 84–96 (2004).

    Article 

    Google Scholar 

  • Uyeda, J. C., Pennell, M. W., Miller, E. T., Maia, R. & McClain, C. R. The evolution of energetic scaling across the vertebrate tree of life. Am. Nat. 190, 185–199 (2017).

    Article 

    Google Scholar 

  • Wolkovich, E. M. et al. Observed Spring Phenology Responses in Experimental Environments (OSPREE). Knowledge Network for Biocomplexity (2019).

  • Smith, S. A. & Brown, J. W. Constructing a broadly inclusive seed plant phylogeny. Am. J. Bot. 105, 302–314 (2018).

    Article 

    Google Scholar 

  • Laube, J. et al. Chilling outweighs photoperiod in preventing precocious spring development. Glob. Change Biol. 20, 170–182 (2014).

    Article 

    Google Scholar 

  • Wolkovich, E. M. & Donahue, M. J. How phenological tracking shapes species and communities in non-stationary environments. Biol. Rev. 96, 2810–2827 (2021).

    Article 
    CAS 

    Google Scholar 

  • Nakagawa, H. et al. Flowering response of rice to photoperiod and temperature: a QTL analysis using a phenological model. Theor. Appl. Genet. 110, 778–786 (2005).

    Article 
    CAS 

    Google Scholar 

  • Basler, D. & Körner, C. Photoperiod sensitivity of bud burst in 14 temperate forest tree species. Agric. For. Meteorol. 165, 73–81 (2012).

    Article 

    Google Scholar 

  • Zohner, C. M., Benito, B. M., Svenning, J. C. & Renner, S. S. Day length unlikely to constrain climate-driven shifts in leaf-out times of northern woody plants. Nat. Clim. Change 6, 1120–1123 (2016).

    Article 

    Google Scholar 

  • Hunter, A. F. & Lechowicz, M. J. Predicting the timing of budburst in temperate trees. J. Appl. Ecol. 29, 597–604 (1992).

    Article 

    Google Scholar 

  • Schaber, J. & Badeck, F. Physiology-based phenology models for forest tree species in Germany. Int. J. Biometeorol. 47, 193–201 (2003).

    Article 

    Google Scholar 

  • Way, D. A. & Montgomery, R. A. Photoperiod constraints on tree phenology, performance and migration in a warming world. Plant Cell Environ. 38, 1725–1736 (2015).

    Article 

    Google Scholar 

  • Kramer, K. et al. Chilling and forcing requirements for foliage bud burst of European beech (Fagus sylvatica L.) differ between provenances and are phenotypically plastic. Agric. For. Meteorol. 234, 172–181 (2017).

    Article 

    Google Scholar 

  • Aitken, S. N. & Bemmels, J. B. Time to get moving: assisted gene flow of forest trees. Evol. Appl. 9, 271–290 (2016).

    Article 

    Google Scholar 

  • Gotelli, N. J. & Graves, G. R. In Null Models in Ecology (eds Gotelli, N. J. & Graves, G. R.) 95–111 (Smithsonian Institution, 1996).

  • Grime, J. P. Evidence for existence of 3 primary strategies in plants and its relevance to ecological and evolutionary theory. Am. Nat. 111, 1169–1194 (1977).

    Article 

    Google Scholar 

  • Serrano-Bueno, G., Romero-Campero, F. J., Lucas-Reina, E., Romero, J. M. & Valverde, F. Evolution of photoperiod sensing in plants and algae. Curr. Opin. Plant Biol. 37, 10–17 (2017).

    Article 
    CAS 

    Google Scholar 

  • Rinne, P., Saarelainen, A. & Junttila, O. Growth cessation and bud dormancy in relation to ABA level in seedlings and coppice shoots of Betula pubescens as affected by a short photoperiod, water stress and chilling. Physiol. Plant. 90, 451–458 (1994).

    Article 
    CAS 

    Google Scholar 

  • Wilczek, A. M., Cooper, M. D., Korves, T. M. & Schmitt, J. Lagging adaptation to warming climate in Arabidopsis thaliana. Proc. Natl Acad. Sci. USA 111, 7906–7913 (2014).

    Article 
    CAS 

    Google Scholar 

  • Azeez, A. & Sane, A. P. Photoperiodic growth control in perennial trees. Plant Signal. Behav. 10, e1087631 (2015).

    Article 

    Google Scholar 

  • Bennett, J. M. et al. The evolution of critical thermal limits of life on earth. Nat. Commun. 12, 1198 (2021).

    Article 
    CAS 

    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 

  • Molina-Venegas, R. et al. Assessing among-lineage variability in phylogenetic imputation of functional trait datasets. Ecography 41, 1740–1749 (2018).

    Article 

    Google Scholar 

  • Molina-Venegas, R., Morales-Castilla, I. & Rodríguez, M. Á. Unreliable prediction of B-vitamin source species. Nat. Plants 9, 31–33 (2023).

    Article 

    Google Scholar 

  • Cornes, R. C., van der Schrier, G., van den Besselaar, E. J. & Jones, P. D. An ensemble version of the E-OBS temperature and precipitation data sets. J. Geophys. Res. 123, 9391–9409 (2018).

    Article 

    Google Scholar 

  • Sheffield, J., Goteti, G. & Wood, E. F. Development of a 50-year high-resolution global dataset of meteorological forcings for land surface modeling. J. Clim. 19, 3088–3111 (2006).

    Article 

    Google Scholar 

  • Baumgarten, F., Zohner, C. M., Gessler, A. & Vitasse, Y. Chilled to be forced: the best dose to wake up buds from winter dormancy. New Phytol. 230, 1366–1377 (2021).

    Article 
    CAS 

    Google Scholar 

  • Buonaiuto, D. M., Donahue, M. & Wolkovich, E. M. Experimental designs for testing the interactive effects of temperature and light in ecology: the problem of periodicity. Funct. Ecol. 37, 1747–1756 (2023).

    Article 
    CAS 

    Google Scholar 

  • Pearse, W. D. et al. Pez: phylogenetics for the environmental sciences. Bioinformatics 31, 2888–2890 (2015).

    Article 
    CAS 

    Google Scholar 

  • Morales-Castilla, I. MoralesCastilla/PhenoPhyloMM: initial release. Zenodo (2024).

  • CONTENT CREDIT

    Leave a Reply

    Your email address will not be published. Required fields are marked *