Reduced resilience as an early warning signal of forest mortality

Climate-induced forest mortality is being widely observed across the globe. Predicting forest mortality remains challenging because the physiological mechanisms causing mortality are not fully understood and empirical relations between climatology and mortality are subject to change. Here, we show that the temporal loss of resilience, a phenomenon often detected as a system approaches a tipping point, can be used as an early warning signal (EWS) to predict the likelihood of forest mortality directly from remotely sensed vegetation dynamics. We tested the proposed approach on data from Californian forests and found that the EWS can often be detected before reduced greenness, between 6 to 19 months before mortality. The EWS shows a species-specific relation with mortality, and is able to capture its spatio-temporal variations. These findings highlight the potential for such an EWS to predict forest mortality in the near-term.Predicting mortality in forests is challenging because its underlying causes are spatially varied and not well known. Reduced resilience detected from remotely sensed time series of vegetation dynamics can serve as an effective early warning signal to indicate the potential for forest mortality.

[1]  V. Dakos,et al.  Detecting dynamical changes in nonlinear time series using locally linear state‐space models , 2012 .

[2]  B. Choat,et al.  Triggers of tree mortality under drought , 2018, Nature.

[3]  N. McDowell,et al.  Drought predisposes piñon-juniper woodlands to insect attacks and mortality. , 2013, The New phytologist.

[4]  Yaxing Wei,et al.  Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 2 , 2014 .

[5]  S. Carpenter,et al.  Catastrophic shifts in ecosystems , 2001, Nature.

[6]  Atul K. Jain,et al.  Global patterns of drought recovery , 2015, Nature.

[7]  Christopher B. Field,et al.  Tree mortality predicted from drought-induced vascular damage , 2015 .

[8]  Achim Zeileis,et al.  Remotely sensed resilience of tropical forests , 2016 .

[9]  S. Goetz,et al.  Detecting early warning signals of tree mortality in boreal North America using multiscale satellite data , 2018, Global change biology.

[10]  A. Porporato,et al.  An ecohydrological perspective on drought‐induced forest mortality , 2014 .

[11]  Jonah Gabry,et al.  R-squared for Bayesian Regression Models , 2019, The American Statistician.

[12]  Michael Dorman,et al.  A synthesis of radial growth patterns preceding tree mortality , 2017, Global change biology.

[13]  Alan E. Gelfand,et al.  Spatial process modelling for univariate and multivariate dynamic spatial data , 2005 .

[14]  A. Porporato,et al.  Increasing atmospheric humidity and CO2 concentration alleviate forest mortality risk , 2017, Proceedings of the National Academy of Sciences.

[15]  P. Hessburg,et al.  Restoring forest resilience: From reference spatial patterns to silvicultural prescriptions and monitoring , 2013 .

[16]  S. Carpenter,et al.  Early-warning signals for critical transitions , 2009, Nature.

[17]  Marten Scheffer,et al.  What Do You Mean, 'Tipping Point'? , 2016, Trends in ecology & evolution.

[18]  M. Scheffer,et al.  Robustness of variance and autocorrelation as indicators of critical slowing down. , 2012, Ecology.

[19]  L. Guanter,et al.  Satellite chlorophyll fluorescence measurements reveal large‐scale decoupling of photosynthesis and greenness dynamics in boreal evergreen forests , 2016, Global change biology.

[20]  S. Stark,et al.  Continental-scale consequences of tree die-offs in North America: identifying where forest loss matters most , 2018 .

[21]  Yaxing Wei,et al.  Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 3 , 2016 .

[22]  William R. L. Anderegg,et al.  Widespread drought‐induced tree mortality at dry range edges indicates that climate stress exceeds species' compensating mechanisms , 2019, Global change biology.

[23]  A. Latimer,et al.  Long-term climate and competition explain forest mortality patterns under extreme drought. , 2017, Ecology letters.

[24]  D. Mackay,et al.  Plant hydraulics improves and topography mediates prediction of aspen mortality in southwestern USA. , 2017, The New phytologist.

[25]  S. Rambal,et al.  Morphological and phenological shoot plasticity in a Mediterranean evergreen oak facing long-term increased drought , 2011, Oecologia.

[26]  Stephen W Pacala,et al.  Optimal stomatal behavior with competition for water and risk of hydraulic impairment , 2016, Proceedings of the National Academy of Sciences.

[27]  C. Justice,et al.  High-Resolution Global Maps of 21st-Century Forest Cover Change , 2013, Science.

[28]  M. Scheffer,et al.  Early warning signals also precede non-catastrophic transitions , 2013 .

[29]  N. McDowell,et al.  A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests , 2010 .

[30]  A. Porporato,et al.  Langevin equations from time series. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[31]  G. Katul,et al.  Increased resin flow in mature pine trees growing under elevated CO2 and moderate soil fertility. , 2012, Tree physiology.

[32]  A. Ives,et al.  Seeing the forest and the trees: multilevel models reveal both species and community patterns , 2012 .

[33]  K. Trenberth,et al.  A Global Dataset of Palmer Drought Severity Index for 1870–2002: Relationship with Soil Moisture and Effects of Surface Warming , 2004 .

[34]  N. McDowell,et al.  Mechanisms Linking Drought, Hydraulics, Carbon Metabolism, and Vegetation Mortality1[W] , 2011, Plant Physiology.

[35]  Peter A. Troch,et al.  Temperature sensitivity of drought-induced tree mortality portends increased regional die-off under global-change-type drought , 2009, Proceedings of the National Academy of Sciences.

[36]  N. McDowell,et al.  Mechanisms of plant survival and mortality during drought: why do some plants survive while others succumb to drought? , 2008, The New phytologist.

[37]  A. Sala,et al.  Physiological mechanisms of drought-induced tree mortality are far from being resolved. , 2010, The New phytologist.

[38]  M. Scheffer,et al.  Slowing down as an early warning signal for abrupt climate change , 2008, Proceedings of the National Academy of Sciences.

[39]  S. Carpenter,et al.  Methods for Detecting Early Warnings of Critical Transitions in Time Series Illustrated Using Simulated Ecological Data , 2012, PloS one.

[40]  P. Brando,et al.  Forest health and global change , 2015, Science.

[41]  Marianne E. Porter,et al.  Differential tree mortality in response to severe drought: evidence for long‐term vegetation shifts , 2005 .

[42]  Jeff Dean,et al.  Time Series , 2009, Encyclopedia of Database Systems.

[43]  Andrew O. Finley,et al.  spBayes for Large Univariate and Multivariate Point-Referenced Spatio-Temporal Data Models , 2013, 1310.8192.

[44]  J. Abatzoglou,et al.  Drought characteristics' role in widespread aspen forest mortality across Colorado, USA , 2013, Global change biology.

[45]  P. Brodrick,et al.  Remotely sensed predictors of conifer tree mortality during severe drought , 2017 .

[46]  J. Abatzoglou.  Development of gridded surface meteorological data for ecological applications and modelling , 2013 .

[47]  K. Price,et al.  Regional vegetation die-off in response to global-change-type drought. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[48]  S. Carpenter,et al.  Generic Indicators of Ecological Resilience: Inferring the Chance of a Critical Transition , 2015 .

[49]  M. G. Ryan,et al.  Evaluating theories of drought-induced vegetation mortality using a multimodel-experiment framework. , 2013, The New phytologist.

[50]  Sergi Munné-Bosch,et al.  Die and let live: leaf senescence contributes to plant survival under drought stress. , 2004, Functional plant biology : FPB.

[51]  S. Carpenter,et al.  Resilience indicators: prospects and limitations for early warnings of regime shifts , 2015, Philosophical Transactions of the Royal Society B: Biological Sciences.

[52]  Sergio M. Vicente-Serrano,et al.  To die or not to die: early warnings of tree dieback in response to a severe drought , 2015 .

[53]  James S. Clark,et al.  The impacts of increasing drought on forest dynamics, structure, and biodiversity in the United States , 2016, Global change biology.

[54]  Sergio M. Vicente-Serrano,et al.  Response of vegetation to drought time-scales across global land biomes , 2012, Proceedings of the National Academy of Sciences.

[55]  Peter H. Singleton,et al.  Tamm Review: Management of mixed-severity fire regime forests in Oregon, Washington, and Northern California , 2016 .

[56]  L. Anderegg,et al.  Testing early warning metrics for drought‐induced tree physiological stress and mortality , 2019, Global change biology.

[57]  Karin Ackermann,et al.  Bayesian Forecasting And Dynamic Models Springer Series In Statistics , 2016 .

[58]  N. McDowell,et al.  The interdependence of mechanisms underlying climate-driven vegetation mortality. , 2011, Trends in ecology & evolution.

[59]  A. Taylor,et al.  Widespread Increase of Tree Mortality Rates in the Western United States , 2009, Science.