Climate‐driven shifts in leaf senescence are greater for boreal species than temperate species in the Acadian Forest region in contrast to leaf emergence shifts

Abstract The Acadian Forest Region is a temperate‐boreal transitional zone in eastern North America which provides a unique opportunity for understanding the potential effects of climate change on both forest types. Leaf phenology, the timing of leaf life cycle changes, is an important indicator of the biological effects of climate change, which can be observed with stationary timelapse cameras known as phenocams. Using four growing seasons of observations for the species Acer rubrum (red maple), Betula papyrifera (paper/white birch) and Abies balsamea (balsam fir) from the Acadian Phenocam Network as well as multiple growing season observations from the North American PhenoCam Network we parameterized eight leaf emergence and six leaf senescence models for each species which span a range in process and driver representation. With climate models from the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5) we simulated future leaf emergence, senescence and season length (senescence minus emergence) for these species at sites within the Acadian Phenocam Network. Model performances were similar across models and leaf emergence model RMSE ranged from about 1 to 2 weeks across species and models, while leaf senescence model RMSE ranged from about 2 to 4 weeks. The simulations suggest that by the late 21st century, leaf senescence may become continuously delayed for boreal species like Betula papyrifera and Abies balsamea, though remain relatively stable for temperate species like Acer rubrum. In contrast, the projected advancement in leaf emergence was similar across boreal and temperate species. This has important implications for carbon uptake, nutrient resorption, ecology and ecotourism for the Acadian Forest Region. More work is needed to improve predictions of leaf phenology for the Acadian Forest Region, especially with respect to senescence. Phenocams have the potential to rapidly advance process‐based model development and predictions of leaf phenology in the context of climate change.

[1]  Y. Vitasse,et al.  Leaf phenology as an indicator of ecological integrity , 2023, Ecosphere.

[2]  J. J. Camarero,et al.  Decoupled leaf-wood phenology in two pine species from contrasting climates: Longer growing seasons do not mean more radial growth , 2022, Agricultural and Forest Meteorology.

[3]  J. S. Brouard,et al.  Assisted migration is plausible for a boreal tree species under climate change: A quantitative and population genetics study of trembling aspen (Populus tremuloides Michx.) in western Canada , 2022, Ecology and evolution.

[4]  Chaoyang Wu,et al.  Increased drought effects on the phenology of autumn leaf senescence , 2022, Nature Climate Change.

[5]  Anthony R. Taylor,et al.  A review of climate change effects on the regeneration dynamics of balsam fir , 2022, The Forestry Chronicle.

[6]  Justin T. Maxwell,et al.  Warm springs alter timing but not total growth of temperate deciduous trees , 2022, Nature.

[7]  L. D’Orangeville,et al.  Relating the Growth Phenology and Biomass Allocation in Seedlings of 13 Acadian Tree Species With Their Drought Tolerance , 2022, Frontiers in Forests and Global Change.

[8]  D. Garbary,et al.  Climate change in Nova Scotia: temperature increases from 1961 to 2020 , 2021, Proceedings of the Nova Scotian Institute of Science (NSIS).

[9]  P. Comeau,et al.  Sequential droughts: A silent trigger of boreal forest mortality , 2021, Global change biology.

[10]  C. Bigler,et al.  Phenological shifts induced by climate change amplify drought for broad-leaved trees at low elevations in Switzerland , 2021 .

[11]  C. Bigler,et al.  Premature leaf discoloration of European deciduous trees is caused by drought and heat in late spring and cold spells in early fall , 2021 .

[12]  J. Kreyling,et al.  Late to bed, late to rise—Warmer autumn temperatures delay spring phenology by delaying dormancy , 2021, Global change biology.

[13]  D. Maclean,et al.  Natural disturbance regimes for implementation of ecological forestry: a review and case study from Nova Scotia, Canada , 2021, Environmental Reviews.

[14]  C. Zohner,et al.  Impact of microclimatic conditions and resource availability on spring and autumn phenology of temperate tree seedlings , 2021, The New phytologist.

[15]  W. R. Vaughn,et al.  Climate change experiment suggests divergent responses of tree seedlings in eastern North America’s Acadian Forest Region over the 21st century , 2021, Canadian Journal of Forest Research.

[16]  M. Friedl,et al.  Using time series of MODIS land surface phenology to model temperature and photoperiod controls on spring greenup in North American deciduous forests , 2021, Remote Sensing of Environment.

[17]  C. Staudhammer,et al.  Vegetation structure drives forest phenological recovery after hurricane , 2021 .

[18]  P. Thornton,et al.  Daymet Version 4 Monthly Latency: Daily Surface Weather Data , 2021 .

[19]  C. Körner,et al.  Elevation-specific responses of phenology in evergreen oaks from their low-dry to their extreme high-cold range limits in the SE Himalaya , 2021 .

[20]  M. Campioli,et al.  Timing of spring xylogenesis in temperate deciduous tree species relates to tree growth characteristics and previous autumn phenology. , 2020, Tree physiology.

[21]  T. A. Black,et al.  Seasonal variation in the canopy color of temperate evergreen conifer forests , 2020, The New phytologist.

[22]  H. Shugart,et al.  Using climate‐driven leaf phenology and growth to improve predictions of gross primary productivity in North American forests , 2020, Global change biology.

[23]  D. Maclean,et al.  A review of natural disturbances to inform implementation of ecological forestry in Nova Scotia, Canada , 2020 .

[24]  Benjamin Marquis,et al.  Probability of Spring Frosts, Not Growing Degree-Days, Drives Onset of Spruce Bud Burst in Plantations at the Boreal-Temperate Forest Ecotone , 2020, Frontiers in Plant Science.

[25]  Blas M. Benito,et al.  Late-spring frost risk between 1959 and 2017 decreased in North America but increased in Europe and Asia , 2020, Proceedings of the National Academy of Sciences.

[26]  P. Reich,et al.  Phenological responses of temperate and boreal trees to warming depend on ambient spring temperatures, leaf habit, and geographic range , 2020, Proceedings of the National Academy of Sciences.

[27]  S. Piao,et al.  Modeling leaf senescence of deciduous tree species in Europe , 2020, Global change biology.

[28]  A. Deslauriers,et al.  Calibrating PhenoCam Data with Phenological Observations of a Black Spruce Stand , 2020 .

[29]  Bijan Seyednasrollah,et al.  Tracking vegetation phenology across diverse biomes using Version 2.0 of the PhenoCam Dataset , 2019, Scientific Data.

[30]  K. Soudani,et al.  “Green pointillism”: detecting the within-population variability of budburst in temperate deciduous trees with phenological cameras , 2019, bioRxiv.

[31]  A. Richardson,et al.  On quantifying the apparent temperature sensitivity of plant phenology. , 2019, The New phytologist.

[32]  R. Q. Thomas,et al.  PhenoCam Dataset v2.0: Vegetation Phenology from Digital Camera Imagery, 2000-2018 , 2019 .

[33]  B. Cook,et al.  Rethinking false spring risk , 2019, Global change biology.

[34]  S. Piao,et al.  A new process-based model for predicting autumn phenology: How is leaf senescence controlled by photoperiod and temperature coupling? , 2019, Agricultural and Forest Meteorology.

[35]  Xiaolin Zhu,et al.  Plant phenology and global climate change: Current progresses and challenges , 2019, Global change biology.

[36]  Anthony R. Taylor,et al.  Forest structure more important than topography in determining windthrow during Hurricane Juan in Canada’s Acadian Forest , 2019, Forest Ecology and Management.

[37]  C. Zohner,et al.  Ongoing seasonally uneven climate warming leads to earlier autumn growth cessation in deciduous trees , 2019, Oecologia.

[38]  L. De Grandpré,et al.  Phenological synchrony between eastern spruce budworm and its host trees increases with warmer temperatures in the boreal forest , 2018, Ecology and evolution.

[39]  H. Hänninen,et al.  Long‐term changes in the impacts of global warming on leaf phenology of four temperate tree species , 2018, Global change biology.

[40]  Susanne S. Renner,et al.  Climate Change and Phenological Mismatch in Trophic Interactions Among Plants, Insects, and Vertebrates , 2018, Annual Review of Ecology, Evolution, and Systematics.

[41]  Y. Bergeron,et al.  Beneficial effects of climate warming on boreal tree growth may be transitory , 2018, Nature Communications.

[42]  W. R. Nettles,et al.  Ecosystem warming extends vegetation activity but heightens vulnerability to cold temperatures , 2018, Nature.

[43]  E M Wolkovich,et al.  Temperature and photoperiod drive spring phenology across all species in a temperate forest community. , 2018, The New phytologist.

[44]  A. Zanne,et al.  Functional biogeography of angiosperms: life at the extremes. , 2018, The New phytologist.

[45]  Tom Milliman,et al.  An integrated phenology modelling framework in r , 2018 .

[46]  H. Hänninen,et al.  Larger temperature response of autumn leaf senescence than spring leaf‐out phenology , 2018, Global change biology.

[47]  Andrew Gelman,et al.  Global shifts in the phenological synchrony of species interactions over recent decades , 2018, Proceedings of the National Academy of Sciences.

[48]  Tom Milliman,et al.  Intercomparison of phenological transition dates derived from the PhenoCam Dataset V1.0 and MODIS satellite remote sensing , 2018, Scientific Reports.

[49]  John A. Silander,et al.  Predicting autumn phenology: How deciduous tree species respond to weather stressors , 2018 .

[50]  Margaret Kosmala,et al.  Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery , 2018, Scientific Data.

[51]  Yann Vitasse,et al.  Global warming leads to more uniform spring phenology across elevations , 2017, Proceedings of the National Academy of Sciences.

[52]  Anthony R. Taylor,et al.  Rapid 21st century climate change projected to shift composition and growth of Canada’s Acadian Forest Region , 2017 .

[53]  Andrew D. Richardson,et al.  Observing Spring and Fall Phenology in a Deciduous Forest with Aerial Drone Imagery , 2017, Sensors.

[54]  J. Régnière,et al.  Process-Based Models of Phenology for Plants and Animals , 2017 .

[55]  David Morin,et al.  Phenocams Bridge the Gap between Field and Satellite Observations in an Arid Grassland Ecosystem , 2017, Remote. Sens..

[56]  Wenjian Wang,et al.  Error estimation based on variance analysis of k-fold cross-validation , 2017, Pattern Recognit..

[57]  Other Contributors Are Indicated Where They Contribute Python Software Foundation , 2017 .

[58]  Sari Metsämäki,et al.  Networked web-cameras monitor congruent seasonal development of birches with phenological field observations , 2017 .

[59]  E. Dufrene,et al.  Tree phenological ranks repeat from year to year and correlate with growth in temperate deciduous forests , 2017 .

[60]  Margaret Kosmala,et al.  Season Spotter: Using Citizen Science to Validate and Scale Plant Phenology from Near-Surface Remote Sensing , 2016, Remote. Sens..

[61]  Rachel Gaulton,et al.  Use of a digital camera onboard a UAV to monitor spring phenology at individual tree level , 2016, 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

[62]  C. Körner,et al.  Where, why and how? Explaining the low‐temperature range limits of temperate tree species , 2016 .

[63]  M. Migliavacca,et al.  Phenopix: A R package for image-based vegetation phenology , 2016 .

[64]  Nicolas Delpierre,et al.  Temperate and boreal forest tree phenology: from organ-scale processes to terrestrial ecosystem models , 2016, Annals of Forest Science.

[65]  D. Basler Evaluating phenological models for the prediction of leaf-out dates in six temperate tree species across central Europe , 2016 .

[66]  Andrew D Richardson,et al.  Multiscale modeling of spring phenology across Deciduous Forests in the Eastern United States , 2016, Global change biology.

[67]  Sanyam Shukla,et al.  Analysis of k-Fold Cross-Validation over Hold-Out Validation on Colossal Datasets for Quality Classification , 2016, 2016 IEEE 6th International Conference on Advanced Computing (IACC).

[68]  E. Nikinmaa,et al.  Interpreting canopy development and physiology using a European phenology camera network at flux sites , 2015 .

[69]  Alex J. Cannon,et al.  Bias Correction of GCM Precipitation by Quantile Mapping: How Well Do Methods Preserve Changes in Quantiles and Extremes? , 2015 .

[70]  L. Kajfez-Bogataj,et al.  Do variations in leaf phenology affect radial growth variations in Fagus sylvatica? , 2015, International Journal of Biometeorology.

[71]  Andrew D Richardson,et al.  The timing of autumn senescence is affected by the timing of spring phenology: implications for predictive models , 2015, Global change biology.

[72]  Josep Peñuelas,et al.  Alteration of the phenology of leaf senescence and fall in winter deciduous species by climate change: effects on nutrient proficiency , 2015, Global change biology.

[73]  Amanda S. Gallinat,et al.  Autumn, the neglected season in climate change research. , 2015, Trends in ecology & evolution.

[74]  David Medvigy,et al.  Macroscale prediction of autumn leaf coloration throughout the continental United States , 2014 .

[75]  C. Körner,et al.  The interaction between freezing tolerance and phenology in temperate deciduous trees , 2014, Front. Plant Sci..

[76]  Wenping Yuan,et al.  Comparison of Phenology Models for Predicting the Onset of Growing Season over the Northern Hemisphere , 2014, PloS one.

[77]  S. Abella,et al.  Climate, trees, pests, and weeds: change, uncertainty, and biotic stressors in eastern US national park forests , 2014 .

[78]  M. Friedl,et al.  Tracking forest phenology and seasonal physiology using digital repeat photography: a critical assessment. , 2014, Ecological applications : a publication of the Ecological Society of America.

[79]  Scott R. Abella,et al.  Climate, trees, pests, and weeds: Change, uncertainty, and biotic stressors in eastern U.S. national park forests , 2014 .

[80]  Mark A. Friedl,et al.  Evaluating remote sensing of deciduous forest phenology at multiple spatial scales using PhenoCam imagery , 2014 .

[81]  M. Hutchinson,et al.  Change and Evolution in the Plant Hardiness Zones of Canada , 2014 .

[82]  Y. Vitasse,et al.  Is the use of cuttings a good proxy to explore phenological responses of temperate forests in warming and photoperiod experiments? , 2014, Tree physiology.

[83]  A. Dhar,et al.  Variability in height growth, survival and nursery carryover effect of Betula papyrifera provenances , 2014 .

[84]  Christopher M. Gough,et al.  Evidence of autumn phenology control on annual net ecosystem productivity in two temperate deciduous forests , 2013 .

[85]  McKenneyDaniel,et al.  Spatial climate models for Canada’s forestry community , 2013 .

[86]  C. Körner,et al.  Elevational adaptation and plasticity in seedling phenology of temperate deciduous tree species , 2013, Oecologia.

[87]  Frank-M. Chmielewski,et al.  Shortcomings of classical phenological forcing models and a way to overcome them , 2012 .

[88]  P. Duinker,et al.  Modelling the effects of climate change and timber harvest on the forests of central Nova Scotia, Canada , 2012, Annals of Forest Science.

[89]  Brian J. McGill,et al.  Sensitivity of Spring Phenology to Warming Across Temporal and Spatial Climate Gradients in Two Independent Databases , 2012, Ecosystems.

[90]  Jenica M. Allen,et al.  Phenological tracking enables positive species responses to climate change. , 2012, Ecology.

[91]  Nathan J B Kraft,et al.  Warming experiments underpredict plant phenological responses to climate change , 2012, Nature.

[92]  Richard B Primack,et al.  Leaf-out phenology of temperate woody plants: from trees to ecosystems. , 2011, The New phytologist.

[93]  D. McKenney,et al.  Revisiting projected shifts in the climate envelopes of North American trees using updated general circulation models , 2011 .

[94]  Isabelle Chuine,et al.  Modelling the timing of Betula pubescens budburst. II. Integrating complex effects of photoperiod into process-based models , 2011 .

[95]  Y. Bergeron,et al.  Response of northeastern North American forests to climate change: Will soil conditions constrain tree species migration? , 2010 .

[96]  C. Augspurger Spring 2007 warmth and frost: phenology, damage and refoliation in a temperate deciduous forest , 2009 .

[97]  Robert Pless,et al.  The global network of outdoor webcams: properties and applications , 2009, GIS.

[98]  H. Wanner,et al.  Tree phenology and carbon dioxide fluxes - use of digital photography for process-based interpretation at the ecosystem scale , 2009 .

[99]  Julien Boé,et al.  Modelling interannual and spatial variability of leaf senescence for three deciduous tree species in France. , 2009 .

[100]  Josep Peñuelas,et al.  Phenology Feedbacks on Climate Change , 2009, Science.

[101]  C. Augspurger,et al.  Leaf phenology in 22 North American tree species during the 21st century , 2009 .

[102]  Hella Ellen Ahrends,et al.  Quantitative phenological observations of a mixed beech forest in northern Switzerland with digital photography , 2008 .

[103]  Tilden Meyers,et al.  The 2007 Eastern US Spring Freeze: Increased Cold Damage in a Warming World , 2008 .

[104]  M. Hutchinson,et al.  Potential Impacts of Climate Change on the Distribution of North American Trees , 2007 .

[105]  Donald F. Holecek,et al.  A profile of the fall foliage tourism market , 2007 .

[106]  H. Mooney,et al.  Shifting plant phenology in response to global change. , 2007, Trends in ecology & evolution.

[107]  Adrian J. Ivakhiv Colouring Cape Breton “Celtic” : Topographies of Culture and Identity in Cape Breton Island , 2007 .

[108]  Klemen Bergant,et al.  Modelling of weather variability effect on fitophenology , 2006 .

[109]  Vivek K. Arora,et al.  A parameterization of leaf phenology for the terrestrial ecosystem component of climate models , 2005 .

[110]  J. Zimmerman,et al.  Changes in Patterns of Understory Leaf Phenology and Herbivory following Hurricane Damage , 2004 .

[111]  D. Easterling,et al.  Temporal variations in frost‐free season in the United States: 1895–2000 , 2004 .

[112]  I. Chuine,et al.  Scaling phenology from the local to the regional level: advances from species‐specific phenological models , 2000 .

[113]  David O. Deppong,et al.  The Role of Apical Dominance in Paradormancy of Temperate Woody Plants: A Reappraisal , 1999 .

[114]  T. Letchford,et al.  Photosynthesis, water and nitrogen use efficiencies of four paper birch (Betula papyrifera) populations grown under different soil moisture and nutrient regimes , 1998 .

[115]  S. Running,et al.  A continental phenology model for monitoring vegetation responses to interannual climatic variability , 1997 .

[116]  C. Tsallis,et al.  Generalized simulated annealing , 1995, cond-mat/9501047.

[117]  Koen Kramer,et al.  Selecting a model to predict the onset of growth of Fagus sylvatica , 1994 .

[118]  M. Cannell,et al.  Date of budburst of fifteen tree species in Britain following climatic warming , 1989 .

[119]  G. Farquhar,et al.  Foliar stage in wheat correlates better to photothermal time than to thermal time , 1989 .

[120]  M. Cannell,et al.  Thermal time, chill days and prediction of budburst in Picea sitchensis , 1983 .

[121]  J. Cayford,et al.  Forest Regions of Canada , 1974 .

[122]  Jen-Yu Wang,et al.  A Critique of the Heat Unit Approach to Plant Response Studies , 1960 .

[123]  D. Civco,et al.  Species‐specific spring and autumn leaf phenology captured by time‐lapse digital cameras , 2018 .

[124]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[125]  C. Augspurger,et al.  Reconstructing patterns of temperature, phenology, and frost damage over 124 years: spring damage risk is increasing. , 2013, Ecology.

[126]  Yang Xiang,et al.  Generalized Simulated Annealing for Global Optimization: The GenSA Package , 2013, R J..

[127]  P. Duinker,et al.  Modelling the effects of climate change and timber harvest on the forests of central Nova Scotia, Canada , 2012, Annals of Forest Science.

[128]  L. Joyce,et al.  High-resolution interpolation of climate scenarios for Canada derived from general circulation model simulations , 2011 .

[129]  Annette Menzel,et al.  Trends of spring time frost events and phenological dates in Central Europe , 2003 .

[130]  Peter M. Cox,et al.  Description of the "TRIFFID" Dynamic Global Vegetation Model , 2001 .

[131]  Heikki Hänninen,et al.  Modelling bud dormancy release in trees from cool and temperate regions. , 1990 .

[132]  Thomas A. Hockin Government in Canada , 1975 .