A model quantifying global vegetation resistance and resilience to short‐term climate anomalies and their relationship with vegetation cover

Aim In order to mitigate the ecological, economical and social consequences of future climate change, we must understand and quantify the response of vegetation to short-term climate anomalies. There is currently no model that quantifies vegetation resistance and resilience at a global scale while simultaneously taking climate variability into account. The goals of this study were therefore to develop a standardized indicator of short-term vegetation resilience and resistance to drought and temperature anomalies, and to improve our understanding of vegetation resistance and resilience in drought-sensitive areas by linking metrics of vegetation stability to the percentage of tree cover, non-tree vegetation and bare soil. Location Global. Methods The deviation of vegetation behaviour from expectations was quantified using anomalies in the normalized difference vegetation index (NDVI) and modelled as a function of (1) past NDVI anomalies, (2) an instantaneous drought indicator and (3) temperature anomalies. Metrics of resistance and resilience were then extracted from the model and related to the percentages of bare soil, non-tree vegetation and tree cover. Results Comparisons of the globally derived resilience and resistance metrics showed low resilience and low resistance to drought in semi-arid areas, low resistance to negative temperature anomalies in high-latitude areas, and low resistance to positive temperature anomalies in the Sahel and Australia. In drought-sensitive areas, resilience was highest for vegetation types with 3–20% bare soil and 5–15% tree cover. Main conclusions Our ARx model is the first to simultaneously derive vegetation resistance and resilience metrics at a global scale, explicitly taking into account the spatial variability of short-term climate anomalies and data reliability. Its results highlight the impact of tree cover, non-tree vegetation and bare soil on vegetation resilience.

[1]  R. Deo,et al.  A continent under stress: interactions, feedbacks and risks associated with impact of modified land cover on Australia's climate , 2009 .

[2]  J. Norman,et al.  The global distribution of cultivable lands: current patterns and sensitivity to possible climate change , 2002 .

[3]  Jadunandan Dash,et al.  Remote sensing of vegetation cover dynamics and resilience across southern Africa , 2014, Int. J. Appl. Earth Obs. Geoinformation.

[4]  D. Tilman.  Biodiversity: Population Versus Ecosystem Stability , 1995 .

[5]  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.

[6]  C. Field.  Managing the risks of extreme events and disasters to advance climate change adaption , 2012 .

[7]  P. Maisongrande,et al.  Woody plant richness and NDVI response to drought events in Catalonian (northeastern Spain) forests. , 2007, Ecology.

[8]  Hongyan Liu,et al.  Global patterns of NDVI-indicated vegetation extremes and their sensitivity to climate extremes , 2013 .

[9]  C. Tucker,et al.  Climate-Driven Increases in Global Terrestrial Net Primary Production from 1982 to 1999 , 2003, Science.

[10]  K. Hoberg,et al.  Global overview , 2014, Nature.

[11]  William J. Bond,et al.  What Limits Trees in C4 Grasslands and Savannas , 2008 .

[12]  C. S. Holling,et al.  STABILITY OF SEMI-ARID SAVANNA GRAZING SYSTEMS , 1981 .

[13]  Makiko Sato,et al.  GISS analysis of surface temperature change , 1999 .

[14]  S. Running,et al.  Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data , 2002 .

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

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

[17]  Yi Y. Liu,et al.  Global vegetation biomass change (1988–2008) and attribution to environmental and human drivers , 2013 .

[18]  W. Verstraeten,et al.  A near-infrared narrow-waveband ratio to determine Leaf Area Index in orchards , 2008 .

[19]  S. Vicente‐Serrano,et al.  A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index , 2009 .

[20]  Michael Notaro,et al.  Response of the mean global vegetation distribution to interannual climate variability , 2008 .

[21]  W. Verstraeten,et al.  A comparison of time series similarity measures for classification and change detection of ecosystem dynamics , 2011 .

[22]  D. Mueller‐Dombois,et al.  Ecology of Tropical and Subtropical Vegetation. , 1972 .

[23]  Ruth J. Mitchell,et al.  Ecosystem stability and resilience: a review of their relevance for the conservation management of lowland heaths , 2000 .

[24]  Ranga B. Myneni,et al.  Recent trends in Inner Asian forest dynamics to temperature and precipitation indicate high sensitivity to climate change , 2012 .

[25]  B. Holben.  Characteristics of maximum-value composite images from temporal AVHRR data , 1986 .

[26]  Jennifer N. Hird,et al.  Noise reduction of NDVI time series: An empirical comparison of selected techniques , 2009 .

[27]  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.

[28]  I. Prentice,et al.  Relationships among fire frequency, rainfall and vegetation patterns in the wet–dry tropics of northern Australia: an analysis based on NOAA‐AVHRR data , 2005 .

[29]  M. Scheffer,et al.  Global Resilience of Tropical Forest and Savanna to Critical Transitions , 2011, Science.

[30]  Jan Verbesselt,et al.  Assessing intra-annual vegetation regrowth after fire using the pixel based regeneration index , 2011 .

[31]  T. Vesala,et al.  Reduction of ecosystem productivity and respiration during the European summer 2003 climate anomaly: a joint flux tower, remote sensing and modelling analysis , 2007 .

[32]  Ben Somers,et al.  How to measure ecosystem stability? An evaluation of the reliability of stability metrics based on remote sensing time series across the major global ecosystems , 2014, Global change biology.

[33]  Martin Kappas,et al.  Assessment of vegetation vulnerability to ENSO warm events over Africa , 2010, Int. J. Appl. Earth Obs. Geoinformation.

[34]  Jan Verbesselt,et al.  A pixel based regeneration index using time series similarity and spatial context , 2010 .

[35]  Tiziana Simoniello,et al.  Estimation of vegetation cover resilience from satellite time series , 2008 .

[36]  D. Roy,et al.  An overview of MODIS Land data processing and product status , 2002 .

[37]  Jorge E. Pinzón,et al.  Evaluating and Quantifying the Climate-Driven Interannual Variability in Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) at Global Scales , 2013, Remote. Sens..

[38]  Ranga B. Myneni,et al.  Drought and spring cooling induced recent decrease in vegetation growth in Inner Asia , 2013 .

[39]  T. Stocker,et al.  Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of IPCC Intergovernmental Panel on Climate Change , 2012 .

[40]  Edwin W. Pak,et al.  An extended AVHRR 8‐km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data , 2005 .

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

[42]  S. Ganguly,et al.  Amazon forests did not green‐up during the 2005 drought , 2009 .

[43]  Kelly K. Caylor,et al.  Dynamic response of grass cover to rainfall variability: implications for the function and persistence of savanna ecosystems , 2005 .

[44]  P. Jones,et al.  Representing Twentieth-Century Space-Time Climate Variability. Part II: Development of 1901-96 Monthly Grids of Terrestrial Surface Climate , 2000 .

[45]  J. Townshend,et al.  Global Percent Tree Cover at a Spatial Resolution of 500 Meters: First Results of the MODIS Vegetation Continuous Fields Algorithm , 2003 .

[46]  L. Telesca,et al.  Intra-annual dynamical persistent mechanisms in mediterranean ecosystems revealed SPOT-VEGETATION time series , 2008 .

[47]  Mark A. Friedl,et al.  Drought-induced vegetation stress in southwestern North America , 2010 .