Deciduous forest responses to temperature, precipitation, and drought imply complex climate change impacts

Significance Autumnal phenological shifts (leaf senescence and dormancy) because of climate change bring substantial impacts on community and ecosystem processes (e.g. altered C and N cycling and phenological mismatches) and the fall foliage ecotourism industry. However, the understanding of the environmental control of autumn phenology has changed little over the past 60 y. We found that cold, frost, wet, and high heat-stress lead to earlier dormancy dates across temperate deciduous forest communities, whereas moderate heat- and drought-stress delayed dormancy. Divergent future responses of fall dormancy timing were predicted: later for northern regions and earlier for southern areas. Our findings improve understanding of autumn phenology mechanisms and suggests complex interactions among environmental conditions affecting autumn phenology now and in the future. Changes in spring and autumn phenology of temperate plants in recent decades have become iconic bio-indicators of rapid climate change. These changes have substantial ecological and economic impacts. However, autumn phenology remains surprisingly little studied. Although the effects of unfavorable environmental conditions (e.g., frost, heat, wetness, and drought) on autumn phenology have been observed for over 60 y, how these factors interact to influence autumn phenological events remain poorly understood. Using remotely sensed phenology data from 2001 to 2012, this study identified and quantified significant effects of a suite of environmental factors on the timing of fall dormancy of deciduous forest communities in New England, United States. Cold, frost, and wet conditions, and high heat-stress tended to induce earlier dormancy of deciduous forests, whereas moderate heat- and drought-stress delayed dormancy. Deciduous forests in two eco-regions showed contrasting, nonlinear responses to variation in these explanatory factors. Based on future climate projection over two periods (2041–2050 and 2090–2099), later dormancy dates were predicted in northern areas. However, in coastal areas earlier dormancy dates were predicted. Our models suggest that besides warming in climate change, changes in frost and moisture conditions as well as extreme weather events (e.g., drought- and heat-stress, and flooding), should also be considered in future predictions of autumn phenology in temperate deciduous forests. This study improves our understanding of how multiple environmental variables interact to affect autumn phenology in temperate deciduous forest ecosystems, and points the way to building more mechanistic and predictive models.

[1]  Q. Ge,et al.  The effect of climate change on the fall foliage vacation in China , 2013 .

[2]  J. Silander,et al.  Estimating uncertainty in daily weather interpolations: a Bayesian framework for developing climate surfaces , 2014 .

[3]  Jeffrey S. Dukes,et al.  Changing climate, changing forests: the impacts of climate change on forests of the northeastern United States and eastern Canada , 2012 .

[4]  P. Dijkwel,et al.  Hormonal regulation of leaf senescence through integration of developmental and stress signals , 2013, Plant Molecular Biology.

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

[6]  G. Schwarz.  Estimating the Dimension of a Model , 1978 .

[7]  R. M. Rivero,et al.  Delayed leaf senescence induces extreme drought tolerance in a flowering plant , 2007, Proceedings of the National Academy of Sciences.

[8]  Adrian E. Raftery,et al.  Bayesian Model Averaging: A Tutorial , 2016 .

[9]  G. Casella,et al.  The Bayesian Lasso , 2008 .

[10]  Arthur E. Hoerl,et al.  Ridge Regression: Biased Estimation for Nonorthogonal Problems , 2000, Technometrics.

[11]  Damaris Zurell,et al.  Collinearity: a review of methods to deal with it and a simulation study evaluating their performance , 2013 .

[12]  Pierre Vollenweider,et al.  Linking stress with macroscopic and microscopic leaf response in trees: new diagnostic perspectives. , 2007, Environmental pollution.

[13]  J. Caspersen,et al.  Interspecific variation in sapling mortality in relation to growth and soil moisture , 2001 .

[14]  C. Körner,et al.  Responses of deciduous forest trees to severe drought in Central Europe. , 2005, Tree physiology.

[15]  Andrew D. Richardson,et al.  Predicting Climate Change Impacts on the Amount and Duration of Autumn Colors in a New England Forest , 2013, PloS one.

[16]  Christian Körner,et al.  Phenology Under Global Warming , 2010, Science.

[17]  B. Cook,et al.  Divergent responses to spring and winter warming drive community level flowering trends , 2012, Proceedings of the National Academy of Sciences.

[18]  S. I. Rosenthal,et al.  Photosynthetic decline and pigment loss during autumn foliar senescence in western larch (Larix occidentalis). , 1997, Tree physiology.

[19]  Jerry Melillo,et al.  The seasonal timing of warming that controls onset of the growing season. , 2014, Global change biology.

[20]  Hsin-I Wu,et al.  A model comparison for daylength as a function of latitude and day of year , 1995 .

[21]  Elizabeth R. Ellwood,et al.  Forecasting phenology under global warming , 2010, Philosophical Transactions of the Royal Society B: Biological Sciences.

[22]  W. Larcher.  Physiological Plant Ecology: Ecophysiology and Stress Physiology of Functional Groups , 1995 .

[23]  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.

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

[25]  Marcel Abendroth.  Physiological Plant Ecology Ecophysiology And Stress Physiology Of Functional Groups , 2016 .

[26]  Stefan Jansson,et al.  The Control of Autumn Senescence in European Aspen1[W][OA] , 2009, Plant Physiology.

[27]  Olavi Junttila,et al.  Tree seasonality in a warming climate , 2013 .

[28]  Annette Menzel,et al.  Responses of leaf colouring in four deciduous tree species to climate and weather in Germany , 2006 .

[29]  Richard B Primack,et al.  Global warming and flowering times in Thoreau's Concord: a community perspective. , 2008, Ecology.

[30]  L. Band,et al.  Divergent phenological response to hydroclimate variability in forested mountain watersheds , 2014, Global change biology.

[31]  Sylvain Delzon,et al.  Responses of canopy duration to temperature changes in four temperate tree species: relative contributions of spring and autumn leaf phenology , 2009, Oecologia.

[32]  R. A. Garcia,et al.  Multiple Dimensions of Climate Change and Their Implications for Biodiversity , 2014, Science.

[33]  H. Zou,et al.  Regularization and variable selection via the elastic net , 2005 .

[34]  R. Proulx,et al.  Fall synchrony between leaf color change and brook trout spawning in the Laurentides Wildlife Reserve (Québec, Canada) as potential environmental integrators , 2013 .

[35]  H. Nam,et al.  Leaf senescence. , 2007, Annual review of plant biology.

[36]  J. Berger,et al.  Optimal predictive model selection , 2004, math/0406464.

[37]  J. Abatzoglou,et al.  A comparison of statistical downscaling methods suited for wildfire applications , 2012 .

[38]  G. Yohe,et al.  A globally coherent fingerprint of climate change impacts across natural systems , 2003, Nature.

[39]  R. M. Samish.  Dormancy in Woody Plants , 1954 .

[40]  J. Fridley.  Extended leaf phenology and the autumn niche in deciduous forest invasions , 2012, Nature.

[41]  S. Welch,et al.  Genetic and physiological bases for phenological responses to current and predicted climates , 2010, Philosophical Transactions of the Royal Society B: Biological Sciences.

[42]  Robert O. Teskey,et al.  A severe drought: impact on tree growth, phenology, net photosynthetic rate and water relations. , 1979 .

[43]  Yan Xu,et al.  Heat-induced Leaf Senescence and Hormonal Changes for Thermal Bentgrass and Turf-type Bentgrass Species Differing in Heat Tolerance , 2007 .

[44]  A. Miller‐Rushing,et al.  Forecasting phenology: from species variability to community patterns. , 2012, Ecology letters.

[45]  J. Vahala,et al.  Physiological and ultrastructural responses of birch clones exposed to ozone and drought stress , 1998 .

[46]  P. Rinne,et al.  Shoot meristems of deciduous woody perennials: self-organization and morphogenetic transitions. , 2014, Current opinion in plant biology.

[47]  Maria E. Eriksson,et al.  The dynamic nature of bud dormancy in trees: environmental control and molecular mechanisms. , 2012, Plant, cell & environment.

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

[49]  John A. Silander,et al.  Spatial and interspecific variability in phenological responses to warming temperatures , 2009 .

[50]  Otso Ovaskainen,et al.  Community-level phenological response to climate change , 2013, Proceedings of the National Academy of Sciences.

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

[52]  Ülo Niinemets,et al.  Responses of forest trees to single and multiple environmental stresses from seedlings to mature plants: Past stress history, stress interactions, tolerance and acclimation , 2010 .

[53]  M. Weih.  Genetic and environmental variation in spring and autumn phenology of biomass willows (Salix spp.): effects on shoot growth and nitrogen economy. , 2009, Tree physiology.

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

[55]  Hideyuki Doi,et al.  Latitudinal patterns in the phenological responses of leaf colouring and leaf fall to climate change in Japan , 2008 .

[56]  A. S. Duque,et al.  Abiotic Stress Responses in Plants: Unraveling the Complexity of Genes and Networks to Survive , 2013 .

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

[58]  H. Akaike,et al.  Information Theory and an Extension of the Maximum Likelihood Principle , 1973 .

[59]  Maria A. Terres,et al.  Modeling daily flowering probabilities: expected impact of climate change on Japanese cherry phenology , 2014, Global change biology.

[60]  Hao Helen Zhang,et al.  Consistent Group Identification and Variable Selection in Regression With Correlated Predictors , 2013, Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America.

[61]  Otávio J. B. Brustolini,et al.  The Molecular Chaperone Binding Protein BiP Prevents Leaf Dehydration-Induced Cellular Homeostasis Disruption , 2014, PloS one.

[62]  J. O'keefe,et al.  Phenology of a northern hardwood forest canopy , 2006 .

[63]  Shilong Piao,et al.  Variation in leaf flushing date influences autumnal senescence and next year’s flushing date in two temperate tree species , 2014, Proceedings of the National Academy of Sciences.

[64]  A. Naor,et al.  The effects of temperature and drought on autumnal senescence and leaf shed in apple under warm, east mediterranean climate , 2014, Trees.

[65]  N. Breda,et al.  Temperate forest trees and stands under severe drought: a review of ecophysiological responses, adaptation processes and long-term consequences , 2006 .

[66]  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.

[67]  A. Strahler,et al.  Monitoring vegetation phenology using MODIS , 2003 .

[68]  Adrian E. Raftery,et al.  Bayesian model averaging: a tutorial (with comments by M. Clyde, David Draper and E. I. George, and a rejoinder by the authors , 1999 .

[69]  I. Chuine,et al.  A unified model for budburst of trees. , 2000, Journal of theoretical biology.

[70]  D. Dragoni,et al.  Trends in fall phenology across the deciduous forests of the Eastern USA , 2012 .

[71]  J. S. Rao,et al.  Spike and slab variable selection: Frequentist and Bayesian strategies , 2005, math/0505633.