Supplementary Information Contrasting responses of water use efficiency to drought across global terrestrial ecosystems Yuting Yang1,2,*, Huade Guan1,3, Okke Batelaan1,3, Tim R. McVicar2,4, Shilong Piao5, Di Long6, Wei Liang7, Bing Liu8, Zhao Jin7, Craig Simmons1,3 1
School of the Environment, Flinders University, Adelaide, South Australia 5042, Australia
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CSIRO Land and Water, Canberra, ACT 2601, Australia
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National Centre for Groundwater Research and Training, Adelaide, South Australia 5042, Australia 4
Australian Research Council Centre of Excellence for Climate System Science, Sydney, Australia 5
Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China. 6
State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China College of Tourism and Environmental Sciences, Shaanxi Normal University, Xi’an 710062, China 7
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Linze Inland River Basin Research Station, Laboratory of Heihe River Eco-Hydrology and Basin Science, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China *Author to whom correspondence should be addressed; Email:
[email protected]; Tel.: +61-2-62183448; (Surnames are underlined) This supplementary material file includes: Supplementary Figures S1 to S8 Supplementary Tables S1
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Section 1. Global spatial patterns of annual WUE and NDVI.
Supplementary Figure S1 Global distribution of mean annual WUE and NDVI over 19822011. (a) global distribution of mean annual WUE calculated over 1982-2011 based on the MTE data, (b) global distribution of mean annual NDVI over 1982-2011 calculated based on the AVHRR-GIMMS-3g NDVI dataset, and (c) relationship between mean annual WUE and NDVI over 1982-2011. The red solid line in (c) indicates the best linear fit. Note there are no MTE data over Sahara, Greenland and Antarctica regions. Map was drawn using ArcMap 10.2.
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Supplementary Figure S2 Mean (1982-2011) and spatial variability of mean annual WUE for each vegetation type based on the MTE data. The spatial variability of the entire biome class is indicated by the coefficient of variation (CV). The results show that higher WUEs are generally found in forest ecosystems, whereas the spatial variability of WUE is lower in high WUE regions than in low WUE regions. Image was drawn using Excel 2013.
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Section 2. Drought effect on the WUE
Supplementary Figure S3 Relationship between non-detrended annual MTE-WUE and PDSI series over 1982-2011. (a) Spatial distribution of Pearson’s coefficient (r) between nondetrended annual MTE-WUE and PDSI series, (b) boxplot of Pearson’s coefficient between non-detrended annual MTE-WUE and PDSI for each biome, (c) boxplot of Pearson’s coefficient between non-detrended annual MTE-WUE and PDSI for each climate zone. The background colours in (b) indicate different climate zones (red: arid zone; yellow: semiarid/sub-humid zone; green: humid zone). The interpretation of the boxplots is given in Figure 2. Map was drawn using ArcMap 10.2 and boxplots were drawn using R 3.1.2.
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Supplementary Figure S4 Relationship between detrended annual MTE-WUE and WI series over 1982-2011. (a) Spatial distribution of Pearson’s coefficient (r) between detrended annual MTE-WUE and WI series, (b) boxplot of Pearson’s coefficient between detrended annual MTE-WUE and WI for each biome, (c) boxplot of Pearson’s coefficient between detrended annual MTE-WUE and AI for each climate zone. The background colours in (b) indicate different climate zones (red: arid zone; yellow: semi-arid/sub-humid zone; green: humid zone). The interpretation of the boxplots is given in Figure 2. Map was drawn using ArcMap 10.2 and boxplots were drawn using R 3.1.2.
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Supplementary Figure S5 Relationship between non-detrended annual MTE-WUE and WI series over 1982-2011. (a) Spatial distribution of Pearson’s coefficient (r) between nondetrended annual MTE-WUE and WI series, (b) boxplot of Pearson’s coefficient between non-detrended annual MTE-WUE and WI for each biome, (c) boxplot of Pearson’s coefficient between non-detrended annual MTE-WUE and WI for each climate zone. The background colours in (b) indicate different climate zones (red: arid zone; yellow: semiarid/sub-humid zone; green: humid zone). The interpretation of the boxplots is given in Figure 2. Map was drawn using ArcMap 10.2 and boxplots were drawn using R 3.1.2. 6
Supplementary Table S1 Descriptions of the flux sites used in this study including site number, site identifier (Site ID), latitude (Lat), Longitude (Lon), mean wetness index during the data period (Mean WI), climate zone (based on Mean WI), correlation coefficient between annual WUE and WI (r) and the p-value, and references (Ref). Site Number 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45
Site ID
Lat (oN)
Lon (oE)
BW-Ma1 CA-NS1 CA-NS3 CA-NS6 CA-NS7 CA-SF3 ES_Lma US-FR2 US-SRM US-Wkg US_Me5 AU-Tum AU-How BE_Vie CA-Man CA-Mer CA-NS2 CA-NS5 CA-Qfo CA-SF2 DE_Geb DE_Hai DE_Kli DE-Tha ES_ES1 ES_ES2 ES_VDA FI-Hyy FR-LBr FR_Pue FR-Hes HU_Bug HU_Mat IL-Yat IT_LMa IT_PT1 IT_Ren IT_Sro IT-Amp IT-Cpz IT-MBo IT-Ro1 IT-Ro2 NL-Ca1 PT-Esp
-19.92 55.88 55.91 55.92 56.64 54.09 39.94 29.95 31.82 31.74 44.44 -35.66 -12.49 50.31 55.88 45.41 55.91 55.86 49.69 54.25 51.10 51.08 50.89 50.96 39.35 39.28 42.15 61.85 44.72 43.74 48.67 46.69 47.85 31.34 45.58 45.20 46.59 43.73 41.90 41.71 46.02 42.41 42.39 51.97 38.64
23.56 -98.48 -98.38 -98.96 -99.95 -106.00 -5.77 -98.00 -110.87 -109.94 -121.57 148.15 131.15 6.00 -98.48 -75.52 -98.52 -98.49 -74.34 -105.88 10.91 10.45 13.52 13.57 -0.32 -0.32 1.45 24.29 -0.77 3.60 7.06 19.60 19.73 35.05 7.15 9.06 11.43 10.28 13.61 12.38 11.05 11.93 11.92 4.93 -8.60
Biome Type Savanna Shrub ENF Shrub Shrub Shrub Shrub Savanna Savanna Grass Savanna EBF Savanna MF ENF Wetland ENF ENF ENF ENF Crop DBF Crop ENF ENF Crop Grass ENF ENF EBF DBF Grass Grass ENF Grass DBF ENF ENF Grass EBF Grass DBF DBF Grass EBF 7
Mean WI 0.07 0.11 0.12 0.16 0.16 0.11 0.18 0.12 0.09 0.07 0.15 0.57 0.43 0.54 0.21 0.50 0.21 0.22 0.64 0.21 0.58 0.53 0.45 0.52 0.22 0.22 0.58 0.31 0.38 0.40 0.51 0.28 0.31 0.25 0.27 0.32 0.49 0.28 0.42 0.31 0.55 0.28 0.31 0.45 0.22
Climate Zone Arid Arid Arid Arid Arid Arid Arid Arid Arid Arid Arid Sub-humid Semi-arid Sub-humid Semi-arid Sub-humid Semi-arid Semi-arid Sub-humid Semi-arid Sub-humid Sub-humid Semi-arid Sub-humid Semi-arid Semi-arid Sub-humid Semi-arid Semi-arid Semi-arid Sub-humid Semi-arid Semi-arid Semi-arid Semi-arid Semi-arid Semi-arid Semi-arid Semi-arid Semi-arid Sub-humid Semi-arid Semi-arid Semi-arid Semi-arid
r
p-value
Ref
-0.748 -0.955 0.413 0.329 -0.989 -0.999 -0.998 -0.995 -0.546 -0.337 -0.994 0.104 0.937 0.228 0.394 0.608 0.436 0.928 0.567 0.034 -0.043 0.866 0.784 0.504 0.287 -0.238 0.325 0.754 0.244 -0.132 -0.251 0.476 0.994 0.952 0.644 0.951 0.951 -0.425 0.619 -0.152 0.944 0.809 0.362 0.714 0.751
0.462 0.191 0.489 0.671 0.096 0.027 0.037 0.064 0.642 0.781 0.07 0.868 0.019 0.556 0.44 0.184 0.566 0.0721 0.433 0.978 0.973 0.012 0.426 0.138 0.5 0.847 0.789 0.031 0.56 0.777 0.551 0.424 0.069 0.048 0.167 0.2 0.085 0.401 0.266 0.7 0.056 0.024 0.764 0.286 0.459
2 3 3 3 4 5 6 7 8 9 10 11 12 13 14 15 3 3 16 5 17 18 19 20 21 21 22 23 24 25 26 27 27 28 29 30 31 32 22 33 34 35 36 37 38
46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95
RU-Fyo SE-Fla SE-Nor UK-Esa UK-Gri US-Wi4 US-ARM US-Aud US-Bkg US-Blo US-Bo1 US-FPe US-Ha1 US-Ho1 US-Me2 US-MMS US-Ne1 US-Ne3 US-Ton US-UMB US-Var US-WCr US_Bar US_IB2 US_NR1 US_SP3 US_SP1 US_Ro1 US_Ro3 US_So4 US-Syv AT-Neu BE_Bra CA-Qcu CH-Oe1 DE_Meh DE-Wet FI_Kaa FI_Sod FR_Lq1 FR_Lq2 IE_Ca1 IE_Dri IT_Non NL-Loo SE-Deg US_SP2 US-Goo US-PFa VU-Coc
56.46 64.11 60.09 55.91 56.61 46.74 36.61 31.59 44.35 38.90 40.01 48.31 42.54 45.20 44.45 39.32 41.17 41.18 38.43 45.56 38.41 45.81 44.06 41.81 40.03 29.75 29.74 44.71 44.72 33.37 46.24 47.12 51.31 49.27 47.29 51.28 50.45 69.14 67.36 45.64 45.64 52.86 51.99 44.69 52.17 64.18 29.76 34.25 45.95 -15.44
32.92 19.46 17.48 -2.86 -3.80 -91.16 -97.49 -110.51 -96.84 -120.63 -88.29 -105.10 -72.17 -68.74 -121.56 -86.41 -96.48 -96.44 -120.97 -84.71 -120.95 -90.08 -71.29 -88.24 -105.55 -82.16 -82.22 -93.09 -93.09 -116.62 -89.35 11.32 4.52 -74.04 7.73 10.66 11.46 27.30 26.64 2.74 2.74 -6.92 -8.75 11.09 5.74 19.56 -82.24 -89.87 -90.27 167.19
ENF ENF ENF Crop ENF MF Crop Grass Grass ENF Crop Grass DBF ENF ENF DBF Crop Crop Savanna DBF Grass DBF DBF Crop ENF EBF EBF Crop Crop Savanna MF Grass MF ENF Grass Grass ENF Wetland ENF Grass Grass Crop Grass DBF ENF Grass Savanna Grass MF EBF
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0.41 0.33 0.40 0.31 0.57 0.24 0.22 0.31 0.37 0.35 0.38 0.38 0.55 0.43 0.25 0.39 0.28 0.24 0.22 0.31 0.50 0.45 0.53 0.56 0.26 0.43 0.34 0.51 0.46 0.36 0.31 1.15 0.66 0.70 0.78 0.68 0.69 0.75 0.70 1.11 1.09 0.73 0.88 0.72 0.68 0.78 0.65 0.89 1.04 0.73
Semi-arid Semi-arid Semi-arid Semi-arid Sub-humid Semi-arid Semi-arid Semi-arid Semi-arid Semi-arid Semi-arid Semi-arid Sub-humid Semi-arid Semi-arid Semi-arid Semi-arid Semi-arid Semi-arid Semi-arid Semi-arid Semi-arid Sub-humid Sub-humid Semi-arid Semi-arid Semi-arid Sub-humid Semi-arid Semi-arid Semi-arid Humid Humid Humid Humid Humid Humid Humid Humid Humid Humid Humid Humid Humid Humid Humid Humid Humid Humid Humid
0.052 0.191 0.809 0.482 0.94 0.993 -0.322 0.81 0.995 0.654 -0.331 0.431 0.392 0.07 0.635 0.516 0.726 0.083 0.446 0.564 -0.072 0.433 0.578 0.319 0.38 0.763 -0.097 0.718 0.771 0.859 0.187 -0.335 0.427 -0.573 0.202 -0.555 0.192 -0.331 -0.31 -0.175 -0.008 0.036 0.965 -0.488 0.108 0.671 -0.252 0.405 0.345 0.505
0.912 0.809 0.1 0.68 0.005 0.067 0.688 0.1 0.064 0.056 0.35 0.469 0.233 0.859 0.562 0.484 0.276 0.917 0.376 0.322 0.892 0.271 0.607 0.681 0.312 0.11 0.903 0.49 0.439 0.343 0.813 0.665 0.291 0.313 0.798 0.62 0.757 0.52 0.55 0.888 0.995 0.997 0.168 0.512 0.752 0.251 0.63 0.499 0.503 0.495
39 40 41 42 43 44 45 46 47 48 49 47 50 51 52 53 54 54 55 56 55 57 58 59 60 61 61 62 62 63 64 65 66 16 67 68 69 70 71 22 22 72 73 74 75 76 62 77 78 79
Section 3 Relative sensitivity of GPP and ET to drought
Supplementary Figure S6 Spatial distribution of relative sensitivity of annual (a) GPP and (b) ET to changes in PDSI based on detrended MTE data. Results show that the higher GPP sensitivity is generally located in global semi-arid and sub-humid regions (i.e., the Great Plain of North America, Northern Mexico, western part to the Pampas Steppe, south-eastern part to the Amazon Basin, mid-latitude of Euro-Asia, and the areas surrounding the Congo Basin) and higher ET sensitivity in global arid regions (i.e., the mid- and eastern Asia, southeastern corner of Africa and majority of central- and western Australia). Our results also show a negative relationship between GPP (or ET) and PDSI in global energy-limited environments (i.e., tropical rainforests and boreal ecosystems). Maps were drawn using ArcMap 10.2.
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Supplementary Figure S7 Relative sensitivities of GPP and ET to changes in wetness index at 19 flux sites (site detail is provided in Table S1), at which the WUE-WI relationship are significant (p
