Appendix A. Trends in agricultural and forestry statistics and relationships of annual NDVI with crop yield and total plantation area.

Trends in agricultural and forestry statistics and relationships of annual NDVI with crop yield and total plantation area

Supplement 1. R code for running PnET-CN simulations for AmeriFlux sites, as in text.

<h2>File List</h2><div> <p><a href="GenPnET-CN_Rcode2014-09-15/README">README</a> (MD5: c3c7b6e8b8c2e42f967dff8c15b6d9e6)</p> <p><a href="GenPnET-CN_Rcode2014-09-15/SiteAndVegParams.RData">SiteAndVegParams.RData</a> (MD5: 86dcf70da2c1e4766cde4a222b78f80b)</p> <p><a href="GenPnET-CN_Rcode2014-09-15/RunSimulations2014-06-11.R">RunSimulations2014-06-11.R</a> (MD5: a7ad23be70e82619e104dbe42746820b)</p> <p><a href="GenPnET-CN_Rcode2014-09-15/AmerifluxToClimateFile.R">AmerifluxToClimateFile.R</a> (MD5: 093dfe9d2ff6e61fd2e1b92615d60a70)</p> <p><a href="GenPnET-CN_Rcode2014-09-15/pnetcn_NewPhenology.R">pnetcn_NewPhenology.R</a> (MD5: 7e069c490ec0321a0572c7f73943e96a)</p> <p><a href="GenPnET-CN_Rcode2014-09-15/pnetcn_NewPhenology_cont.R">pnetcn_NewPhenology_cont.R</a> (MD5: 44d4689a457b964f48e497f9b4d3d0df)</p> <p><a href="GenPnET-CN_Rcode2014-09-15/pnetcn.R">pnetcn.R</a> (MD5: d4168f06879c698f46b12d4dfb748d74)</p> <p><a href="GenPnET-CN_Rcode2014-09-15/spinup_pnetcn_NewPhenology.R">spinup_pnetcn_NewPhenology.R</a> (MD5: a64a22fd94e06389292c8c417d2d75d8)</p> <p><a href="GenPnET-CN_Rcode2014-09-15/spinup_pnetcn.R">spinup_pnetcn.R</a> (MD5: 1dc1a10f75c4e14e8108919e0a2d31a3)</p> <p><a href="GenPnET-CN_Rcode2014-09-15/run_pnetcn.R">run_pnetcn.R</a> (MD5: 204dcd9176dfe57b83474fc4677253d0)</p> <p><a href="GenPnET-CN_Rcode2014-09-15/AllocateMo.R">AllocateMo.R</a> (MD5: 7bd2c8e7c2573b64fddef23878be7be6)</p> <p><a href="GenPnET-CN_Rcode2014-09-15/AllocateYr_NewPhenology.R">AllocateYr_NewPhenology.R</a> (MD5: 68c4686f579ae19453fbdd73fdaca927)</p> <p><a href="GenPnET-CN_Rcode2014-09-15/AllocateYr.R">AllocateYr.R</a> (MD5: 17e49c1aaf9d3d045af11344683eaa45)</p> <p><a href="GenPnET-CN_Rcode2014-09-15/AtmEnviron_NewPhenologyOLD.R">AtmEnviron_NewPhenologyOLD.R</a> (MD5: f9f9ce07b2d1d29b719f58c0c2bf5eec)</p> <p><a href="GenPnET-CN_Rcode2014-09-15/AtmEnviron_NewPhenology.R">AtmEnviron_NewPhenology.R</a> (MD5: 6d11dce44856009c05af514b8960cbf5)</p> <p><a href="GenPnET-CN_Rcode2014-09-15/AtmEnviron.R">AtmEnviron.R</a> (MD5: 6a352d22899c3fe1c10cecd2f2bae41d)</p> <p><a href="GenPnET-CN_Rcode2014-09-15/CalculateYr_NewPhenology.R">CalculateYr_NewPhenology.R</a> (MD5: b0d9d700ba3c9503c8d280a6bd50b0f4)</p> <p><a href="GenPnET-CN_Rcode2014-09-15/CNTrans.R">CNTrans.R</a> (MD5: 15f7ea8951957fe0b5714d3164bcb739)</p> <p><a href="GenPnET-CN_Rcode2014-09-15/Decomp.R">Decomp.R</a> (MD5: 6f851eea37ba654a2434a3a9df4f7160)</p> <p><a href="GenPnET-CN_Rcode2014-09-15/GrowthInit_NewPhenology.R">GrowthInit_NewPhenology.R</a> (MD5: ce50ce5fa8a8282e7ad38ec913c9f948)</p> <p><a href="GenPnET-CN_Rcode2014-09-15/initvars.R">initvars.R</a> (MD5: 8503263de5d593fde793622256556209)</p> <p><a href="GenPnET-CN_Rcode2014-09-15/Leach.R">Leach.R</a> (MD5: 49667570a1eae670cb4121f7ca9bfd64)</p> <p><a href="GenPnET-CN_Rcode2014-09-15/PhenologyNew.R">PhenologyNew.R</a> (MD5: 088b2c1b406fab16c4bc55c27c85a5c6)</p> <p><a href="GenPnET-CN_Rcode2014-09-15/PhenologyNew2.R">PhenologyNew2.R</a> (MD5: 6d881331616e178c4b79d0bda723a934)</p> <p><a href="GenPnET-CN_Rcode2014-09-15/Phenology.R">Phenology.R</a> (MD5: 07f72b99a8e981d76100548247d948f2)</p> <p><a href="GenPnET-CN_Rcode2014-09-15/Photosyn.R">Photosyn.R</a> (MD5: 44755415a892bedc86b0f6bad0f50853)</p> <p><a href="GenPnET-CN_Rcode2014-09-15/SoilResp.R">SoilResp.R</a> (MD5: 018dc6e0d4eb5a5f66bb46179099f74b)</p> <p><a href="GenPnET-CN_Rcode2014-09-15/storeoutput.R">storeoutput.R</a> (MD5: f527f8a285c169bdb53aa518f15880c5)</p> <p><a href="GenPnET-CN_Rcode2014-09-15/StoreYrOutput.R">StoreYrOutput.R</a> (MD5: 984cbf2a2f518b5795c319e48bac1ac4)</p> <p><a href="GenPnET-CN_Rcode2014-09-15/Waterbal.R">Waterbal.R</a> (MD5: c3d9d4516e009b9fad7d08ac488f2abc)</p> <p><a href="GenPnET-CN_Rcode2014-09-15/YearInit_NewPhenology.R">YearInit_NewPhenology.R</a> (MD5: 0e9957a828f64f25495bdca9c409d070)</p> <p><a href="GenPnET-CN_Rcode2014-09-15/YearInit.R">YearInit.R</a> (MD5: ceb4bab739a52b78cfcf7ca411939174)</p> <p><a href="#">Ameriflux/</a></p> <p><a href="#">Daymet/</a></p> <p><a href="GenPnET-CN_Rcode2014-09-15/FluxDataFunctions.R">FluxDataFunctions.R</a> (MD5: ae89d6b9cf4e01ba501941ce12690e4b)</p> </div><h2>Description</h2><div> <p>README - Brief notes to get started</p> <p>SiteAndVegParams.RData – R data structures containing site-specific parameters for the six sites analyzed in the paper</p> <p>RunSimulations2014-06-11.R – Template code for importing AmeriFlux and Daymet data and running simulations with climate files including spinup years (must be modified)</p> <p>AmerifluxToClimateFile.R – Functions needed to import Ameriflux and Daymet data and generate climate files</p> <p>pnetcn_NewPhenology.R - Top level function to run the version of PnET-CN used in the paper (new phenology routine)</p> <p>pnetcn.R - Top level function to run traditional version of PnET-CN (old phenology routine)</p> <p>spinup_pnetcn_NewPhenology.R – Alternative version of top-level function that repeats the climate data from the input climate file an arbitrary number of times for spinup (new phenology routine)</p> <p>pnetcn_NewPhenology_cont.R – Function to continue a simulation starting with spinup data from a previous run (called by spinup_pnetcn_NewPhenology.R)</p> <p>spinup_pnetcn.R - Alternative version of top-level function for traditional version of PnET-CN that repeats the climate data from the input climate file an arbitrary number of times for spinup (old phenology routine)</p> <p>run_pnetcn.R - Functions to run PnET-CN with output as data frames of monthly or annual data instead of as a list containing both formats</p> <p>AllocateMo.R - Monthly allocation routine for PnET-CN</p> <p>AllocateYr_NewPhenology.R - Yearly allocation routine for PnET-CN (with new phenology routine)</p> <p>AllocateYr.R - Yearly allocation routine for PnET-CN (with old phenology routine)</p> <p>AtmEnviron_NewPhenology.R - Environmental calculations for PnET-CN (for new phenology routine)</p> <p>AtmEnviron_NewPhenologyOLD.R – Older version of environmental calculations for PnET-CN, with less data saved to data structure (for new phenology routine)</p> <p>AtmEnviron.R - Environmental calculations for PnET-CN (for old phenology routine)</p> <p>CalculateYr_NewPhenology.R - Calculate yearly output values for PnET-CN (for new phenology routine)</p> <p>CNTrans.R - Carbon and nitrogen translocation routine for PnET-CN</p> <p>Decomp.R - Decompositin routine for PnET-CN</p> <p>GrowthInit_NewPhenology.R – Initialize annual aggregation variables for each year in PnET-CN</p> <p>initvars.R - Initialize internal shared variable structures for PnET-CN</p> <p>Leach.R - Leaching routine for PnET-CN</p> <p>PhenologyNew.R - Functions to calculate phenology for PnET-CN (new phenology routine)</p> <p>PhenologyNew2.R -  Skeleton code for new functions to calculate phenology for PnET-CN that would use alternative (e.g., water-driven) phenology cues for grasslands (new phenology routine - INCOMPLETE)</p> <p>Phenology.R - Functions to calculate phenology for PnET-CN (old phenology routine)</p> <p>Photosyn.R - Photosynthesis routine for PnET-CN</p> <p>SoilResp.R - Soil respiration routine for PnET-CN</p> <p>storeoutput.R - Adds variable values to the returned output structure so that the user may work with them (or save them) at the command line after running PnET-CN</p> <p>StoreYrOutput.R - Routine to save annual results to an output file for PnET-CN (not used)</p> <p>Waterbal.R - Ecosystem water balance routine for PnET-CN</p> </div><p>...</p

Appendix A. A table showing validation sites collected from published literature, figures showing spatial patterns of precipitation, temperature, solar radiation, and specific humidity trends from 2000 to 2011, and comparison of spatial patterns of WUE in 2010 from Xiao et al. (unpublished manuscript), Jung et al. (2011), and our study.

A table showing validation sites collected from published literature, figures showing spatial patterns of precipitation, temperature, solar radiation, and specific humidity trends from 2000 to 2011, and comparison of spatial patterns of WUE in 2010 from Xiao et al. (unpublished manuscript), Jung et al. (2011), and our study

Proportion of vegetated area in the Mongolian Plateau covered by < − 1 standardized anomalies of EVI and EVI2 during June–July–August (JJA) in summer and January–February (JF) land surface temperature anomalies in winter

<p><b>Table 1.</b>  Proportion of vegetated area in the Mongolian Plateau covered by < − 1 standardized anomalies of EVI and EVI2 during June–July–August (JJA) in summer and January–February (JF) land surface temperature anomalies in winter. Summer droughts of 2001 and 2009 and <em>dzud</em> of 2010 are highlighted in bold. </p> <p><strong>Abstract</strong></p> <p>Climate change has led to more frequent extreme winters (aka, <em>dzud)</em> and summer droughts on the Mongolian Plateau during the last decade. Among these events, the 2000–2002 combined summer drought–<em>dzud</em> and 2010 <em>dzud</em> were the most severe on vegetation. We examined the vegetation response to these extremes through the past decade across the Mongolian Plateau as compared to decadal means. We first assessed the severity and extent of drought using the Tropical Rainfall Measuring Mission (TRMM) precipitation data and the Palmer drought severity index (PDSI). We then examined the effects of drought by mapping anomalies in vegetation indices (EVI, EVI2) and land surface temperature derived from MODIS and AVHRR for the period of 2000–2010. We found that the standardized anomalies of vegetation indices exhibited positively skewed frequency distributions in dry years, which were more common for the desert biome than for grasslands. For the desert biome, the dry years (2000–2001, 2005 and 2009) were characterized by negative anomalies with peak values between −1.5 and −0.5 and were statistically different (<em>P</em> < 0.001) from relatively wet years (2003, 2004 and 2007). Conversely, the frequency distributions of the dry years were not statistically different (<em>p</em> < 0.001) from those of the relatively wet years for the grassland biome, showing that they were less responsive to drought and more resilient than the desert biome. We found that the desert biome is more vulnerable to drought than the grassland biome. Spatially averaged EVI was strongly correlated with the proportion of land area affected by drought (PDSI <− 1) in Inner Mongolia (IM) and Outer Mongolia (OM), showing that droughts substantially reduced vegetation activity. The correlation was stronger for the desert biome (<em>R</em>² = 65 and 60, <em>p</em> < 0.05) than for the IM grassland biome (<em>R</em>² = 53, <em>p</em> < 0.05). Our results showed significant differences in the responses to extreme climatic events (summer drought and <em>dzud</em>) between the desert and grassland biomes on the Plateau.</p

Frequency distributions of standardized MODIS EVI and VIP EVI2 June–July–August ((a)–(d)) anomalies in the grassland biome (2000–2010) for Inner Mongolia (IM) and Outer Mongolia (OM)

<p><strong>Figure 5.</strong> Frequency distributions of standardized MODIS EVI and VIP EVI2 June–July–August ((a)–(d)) anomalies in the grassland biome (2000–2010) for Inner Mongolia (IM) and Outer Mongolia (OM). The distributions of dry years are not statistically different (<em>p</em> < 0.001) from relatively wet years in the grassland biome as compared to the desert biome (note: this may suggest that the grassland ecosystems are more stable than deserts).</p> <p><strong>Abstract</strong></p> <p>Climate change has led to more frequent extreme winters (aka, <em>dzud)</em> and summer droughts on the Mongolian Plateau during the last decade. Among these events, the 2000–2002 combined summer drought–<em>dzud</em> and 2010 <em>dzud</em> were the most severe on vegetation. We examined the vegetation response to these extremes through the past decade across the Mongolian Plateau as compared to decadal means. We first assessed the severity and extent of drought using the Tropical Rainfall Measuring Mission (TRMM) precipitation data and the Palmer drought severity index (PDSI). We then examined the effects of drought by mapping anomalies in vegetation indices (EVI, EVI2) and land surface temperature derived from MODIS and AVHRR for the period of 2000–2010. We found that the standardized anomalies of vegetation indices exhibited positively skewed frequency distributions in dry years, which were more common for the desert biome than for grasslands. For the desert biome, the dry years (2000–2001, 2005 and 2009) were characterized by negative anomalies with peak values between −1.5 and −0.5 and were statistically different (<em>P</em> < 0.001) from relatively wet years (2003, 2004 and 2007). Conversely, the frequency distributions of the dry years were not statistically different (<em>p</em> < 0.001) from those of the relatively wet years for the grassland biome, showing that they were less responsive to drought and more resilient than the desert biome. We found that the desert biome is more vulnerable to drought than the grassland biome. Spatially averaged EVI was strongly correlated with the proportion of land area affected by drought (PDSI <− 1) in Inner Mongolia (IM) and Outer Mongolia (OM), showing that droughts substantially reduced vegetation activity. The correlation was stronger for the desert biome (<em>R</em>² = 65 and 60, <em>p</em> < 0.05) than for the IM grassland biome (<em>R</em>² = 53, <em>p</em> < 0.05). Our results showed significant differences in the responses to extreme climatic events (summer drought and <em>dzud</em>) between the desert and grassland biomes on the Plateau.</p

Area averaged means of June–July–August EVI plotted with the proportion of area covered by < − 1 PDSI in desert ((a), (b)) and grassland ((c), (d)) biomes for Inner Mongolia (IM) and Outer Mongolia (OM)

<p><strong>Figure 6.</strong> Area averaged means of June–July–August EVI plotted with the proportion of area covered by < − 1 PDSI in desert ((a), (b)) and grassland ((c), (d)) biomes for Inner Mongolia (IM) and Outer Mongolia (OM). Linear regression of July–August EVI with the proportion of area covered by < − 1 PDSI in desert (e) and grassland (f) biomes for Inner Mongolia (IM) and Outer Mongolia (OM).</p> <p><strong>Abstract</strong></p> <p>Climate change has led to more frequent extreme winters (aka, <em>dzud)</em> and summer droughts on the Mongolian Plateau during the last decade. Among these events, the 2000–2002 combined summer drought–<em>dzud</em> and 2010 <em>dzud</em> were the most severe on vegetation. We examined the vegetation response to these extremes through the past decade across the Mongolian Plateau as compared to decadal means. We first assessed the severity and extent of drought using the Tropical Rainfall Measuring Mission (TRMM) precipitation data and the Palmer drought severity index (PDSI). We then examined the effects of drought by mapping anomalies in vegetation indices (EVI, EVI2) and land surface temperature derived from MODIS and AVHRR for the period of 2000–2010. We found that the standardized anomalies of vegetation indices exhibited positively skewed frequency distributions in dry years, which were more common for the desert biome than for grasslands. For the desert biome, the dry years (2000–2001, 2005 and 2009) were characterized by negative anomalies with peak values between −1.5 and −0.5 and were statistically different (<em>P</em> < 0.001) from relatively wet years (2003, 2004 and 2007). Conversely, the frequency distributions of the dry years were not statistically different (<em>p</em> < 0.001) from those of the relatively wet years for the grassland biome, showing that they were less responsive to drought and more resilient than the desert biome. We found that the desert biome is more vulnerable to drought than the grassland biome. Spatially averaged EVI was strongly correlated with the proportion of land area affected by drought (PDSI <− 1) in Inner Mongolia (IM) and Outer Mongolia (OM), showing that droughts substantially reduced vegetation activity. The correlation was stronger for the desert biome (<em>R</em>² = 65 and 60, <em>p</em> < 0.05) than for the IM grassland biome (<em>R</em>² = 53, <em>p</em> < 0.05). Our results showed significant differences in the responses to extreme climatic events (summer drought and <em>dzud</em>) between the desert and grassland biomes on the Plateau.</p

Standardized anomalies of EVI2, white sky albedo and EVI in 2001 ((a), (c), (e)) and 2009 ((b), (d), (f)) summer droughts (June–July–August)

<p><strong>Figure 2.</strong> Standardized anomalies of EVI2, white sky albedo and EVI in 2001 ((a), (c), (e)) and 2009 ((b), (d), (f)) summer droughts (June–July–August). Negative VI anomalies ((a), (e) and (b), (f)), correlate with positive albedo anomalies ((c) and (d)) respectively.</p> <p><strong>Abstract</strong></p> <p>Climate change has led to more frequent extreme winters (aka, <em>dzud)</em> and summer droughts on the Mongolian Plateau during the last decade. Among these events, the 2000–2002 combined summer drought–<em>dzud</em> and 2010 <em>dzud</em> were the most severe on vegetation. We examined the vegetation response to these extremes through the past decade across the Mongolian Plateau as compared to decadal means. We first assessed the severity and extent of drought using the Tropical Rainfall Measuring Mission (TRMM) precipitation data and the Palmer drought severity index (PDSI). We then examined the effects of drought by mapping anomalies in vegetation indices (EVI, EVI2) and land surface temperature derived from MODIS and AVHRR for the period of 2000–2010. We found that the standardized anomalies of vegetation indices exhibited positively skewed frequency distributions in dry years, which were more common for the desert biome than for grasslands. For the desert biome, the dry years (2000–2001, 2005 and 2009) were characterized by negative anomalies with peak values between −1.5 and −0.5 and were statistically different (<em>P</em> < 0.001) from relatively wet years (2003, 2004 and 2007). Conversely, the frequency distributions of the dry years were not statistically different (<em>p</em> < 0.001) from those of the relatively wet years for the grassland biome, showing that they were less responsive to drought and more resilient than the desert biome. We found that the desert biome is more vulnerable to drought than the grassland biome. Spatially averaged EVI was strongly correlated with the proportion of land area affected by drought (PDSI <− 1) in Inner Mongolia (IM) and Outer Mongolia (OM), showing that droughts substantially reduced vegetation activity. The correlation was stronger for the desert biome (<em>R</em>² = 65 and 60, <em>p</em> < 0.05) than for the IM grassland biome (<em>R</em>² = 53, <em>p</em> < 0.05). Our results showed significant differences in the responses to extreme climatic events (summer drought and <em>dzud</em>) between the desert and grassland biomes on the Plateau.</p

Standardized anomalies (summer June–July–August 2010) of MODIS-derived EVI, (MOD13A3) on the Mongolian Plateau, as compared to the decadal mean overlaid with terrestrial ecoregion (WWF) biome boundaries: desert (I), grassland (II) and forest (III)

<p><strong>Figure 1.</strong> Standardized anomalies (summer June–July–August 2010) of MODIS-derived EVI, (MOD13A3) on the Mongolian Plateau, as compared to the decadal mean overlaid with terrestrial ecoregion (WWF) biome boundaries: desert (I), grassland (II) and forest (III).</p> <p><strong>Abstract</strong></p> <p>Climate change has led to more frequent extreme winters (aka, <em>dzud)</em> and summer droughts on the Mongolian Plateau during the last decade. Among these events, the 2000–2002 combined summer drought–<em>dzud</em> and 2010 <em>dzud</em> were the most severe on vegetation. We examined the vegetation response to these extremes through the past decade across the Mongolian Plateau as compared to decadal means. We first assessed the severity and extent of drought using the Tropical Rainfall Measuring Mission (TRMM) precipitation data and the Palmer drought severity index (PDSI). We then examined the effects of drought by mapping anomalies in vegetation indices (EVI, EVI2) and land surface temperature derived from MODIS and AVHRR for the period of 2000–2010. We found that the standardized anomalies of vegetation indices exhibited positively skewed frequency distributions in dry years, which were more common for the desert biome than for grasslands. For the desert biome, the dry years (2000–2001, 2005 and 2009) were characterized by negative anomalies with peak values between −1.5 and −0.5 and were statistically different (<em>P</em> < 0.001) from relatively wet years (2003, 2004 and 2007). Conversely, the frequency distributions of the dry years were not statistically different (<em>p</em> < 0.001) from those of the relatively wet years for the grassland biome, showing that they were less responsive to drought and more resilient than the desert biome. We found that the desert biome is more vulnerable to drought than the grassland biome. Spatially averaged EVI was strongly correlated with the proportion of land area affected by drought (PDSI <− 1) in Inner Mongolia (IM) and Outer Mongolia (OM), showing that droughts substantially reduced vegetation activity. The correlation was stronger for the desert biome (<em>R</em>² = 65 and 60, <em>p</em> < 0.05) than for the IM grassland biome (<em>R</em>² = 53, <em>p</em> < 0.05). Our results showed significant differences in the responses to extreme climatic events (summer drought and <em>dzud</em>) between the desert and grassland biomes on the Plateau.</p

Frequency distributions of standardized MODIS EVI and VIP EVI2 June–July–August ((a)–(d)) anomalies in the desert biome (2000–2010) for Inner Mongolia (IM) and Outer Mongolia (OM)

<p><strong>Figure 4.</strong> Frequency distributions of standardized MODIS EVI and VIP EVI2 June–July–August ((a)–(d)) anomalies in the desert biome (2000–2010) for Inner Mongolia (IM) and Outer Mongolia (OM). Positively skewed drought years (2000–2001, 2005, 2009) are characterized by the majority of negative anomalies with peak values between −1.5 and −0.5 std. and are statistically different (<em>p</em> < 0.001) from relatively wet years (2003, 2004, 2007). VIP EVI2 is based on a longer-term mean (1981–2010) than MODIS EVI.</p> <p><strong>Abstract</strong></p> <p>Climate change has led to more frequent extreme winters (aka, <em>dzud)</em> and summer droughts on the Mongolian Plateau during the last decade. Among these events, the 2000–2002 combined summer drought–<em>dzud</em> and 2010 <em>dzud</em> were the most severe on vegetation. We examined the vegetation response to these extremes through the past decade across the Mongolian Plateau as compared to decadal means. We first assessed the severity and extent of drought using the Tropical Rainfall Measuring Mission (TRMM) precipitation data and the Palmer drought severity index (PDSI). We then examined the effects of drought by mapping anomalies in vegetation indices (EVI, EVI2) and land surface temperature derived from MODIS and AVHRR for the period of 2000–2010. We found that the standardized anomalies of vegetation indices exhibited positively skewed frequency distributions in dry years, which were more common for the desert biome than for grasslands. For the desert biome, the dry years (2000–2001, 2005 and 2009) were characterized by negative anomalies with peak values between −1.5 and −0.5 and were statistically different (<em>P</em> < 0.001) from relatively wet years (2003, 2004 and 2007). Conversely, the frequency distributions of the dry years were not statistically different (<em>p</em> < 0.001) from those of the relatively wet years for the grassland biome, showing that they were less responsive to drought and more resilient than the desert biome. We found that the desert biome is more vulnerable to drought than the grassland biome. Spatially averaged EVI was strongly correlated with the proportion of land area affected by drought (PDSI <− 1) in Inner Mongolia (IM) and Outer Mongolia (OM), showing that droughts substantially reduced vegetation activity. The correlation was stronger for the desert biome (<em>R</em>² = 65 and 60, <em>p</em> < 0.05) than for the IM grassland biome (<em>R</em>² = 53, <em>p</em> < 0.05). Our results showed significant differences in the responses to extreme climatic events (summer drought and <em>dzud</em>) between the desert and grassland biomes on the Plateau.</p

Standardized anomalies of June–July–August (JJA) TRMM rainfall and PDSI in 2001 ((a), (c)) and 2009 ((b), (d)) summer droughts relative to the growing season mean for 2000–2010

<p><strong>Figure 3.</strong> Standardized anomalies of June–July–August (JJA) TRMM rainfall and PDSI in 2001 ((a), (c)) and 2009 ((b), (d)) summer droughts relative to the growing season mean for 2000–2010.</p> <p><strong>Abstract</strong></p> <p>Climate change has led to more frequent extreme winters (aka, <em>dzud)</em> and summer droughts on the Mongolian Plateau during the last decade. Among these events, the 2000–2002 combined summer drought–<em>dzud</em> and 2010 <em>dzud</em> were the most severe on vegetation. We examined the vegetation response to these extremes through the past decade across the Mongolian Plateau as compared to decadal means. We first assessed the severity and extent of drought using the Tropical Rainfall Measuring Mission (TRMM) precipitation data and the Palmer drought severity index (PDSI). We then examined the effects of drought by mapping anomalies in vegetation indices (EVI, EVI2) and land surface temperature derived from MODIS and AVHRR for the period of 2000–2010. We found that the standardized anomalies of vegetation indices exhibited positively skewed frequency distributions in dry years, which were more common for the desert biome than for grasslands. For the desert biome, the dry years (2000–2001, 2005 and 2009) were characterized by negative anomalies with peak values between −1.5 and −0.5 and were statistically different (<em>P</em> < 0.001) from relatively wet years (2003, 2004 and 2007). Conversely, the frequency distributions of the dry years were not statistically different (<em>p</em> < 0.001) from those of the relatively wet years for the grassland biome, showing that they were less responsive to drought and more resilient than the desert biome. We found that the desert biome is more vulnerable to drought than the grassland biome. Spatially averaged EVI was strongly correlated with the proportion of land area affected by drought (PDSI <− 1) in Inner Mongolia (IM) and Outer Mongolia (OM), showing that droughts substantially reduced vegetation activity. The correlation was stronger for the desert biome (<em>R</em>² = 65 and 60, <em>p</em> < 0.05) than for the IM grassland biome (<em>R</em>² = 53, <em>p</em> < 0.05). Our results showed significant differences in the responses to extreme climatic events (summer drought and <em>dzud</em>) between the desert and grassland biomes on the Plateau.</p