diff --git a/01_Extract_data_Project_31.Rmd b/01_Extract_data_Project_31.Rmd
index 53af0e1c4c49e950471de39c91037d5340d932b0..734d443c386affcb82ce15927ef93438db8fb2ec 100755
--- a/01_Extract_data_Project_31.Rmd
+++ b/01_Extract_data_Project_31.Rmd
@@ -335,7 +335,8 @@ The data derive from `r nrow(data.origin)` datasets.
 ```{r}
 soilclim.xylem <- soilclim %>% 
   filter(PlotObservationID %in% plot.sel) %>% 
-  dplyr::select(Elevation=Elevation_median, -Elevation_q2.5, -Elevation_q97.5, -Elevation_DEM.res)
+  dplyr::rename(Elevation=Elevation_median) %>% 
+  dplyr::select(-Elevation_q2.5, -Elevation_q97.5, -Elevation_DEM.res)
 ```
 
 ```{r, echo=F}
diff --git a/_public/01_Extract_data_Project_31.html b/_public/01_Extract_data_Project_31.html
index cb1a2fa120e2fb45ce0fb8f7643599124a3e64ee..c2a51c9749911acece3726714b0ebf045e2f5019 100644
--- a/_public/01_Extract_data_Project_31.html
+++ b/_public/01_Extract_data_Project_31.html
@@ -641,9 +641,9 @@ summary {
 <center>
 <img src="data:image/png;base64,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" title="sPlot Logo" />
 </center>
-<p><strong>Timestamp:</strong> Fri Nov 13 11:53:06 2020<br />
+<p><strong>Timestamp:</strong> Fri Nov 13 17:37:07 2020<br />
 <strong>Drafted:</strong> Francesco Maria Sabatini<br />
-<strong>Version:</strong> 1.0</p>
+<strong>Version:</strong> 1.1</p>
 <p>This report documents the data extraction for <strong>sPlot project proposal #31</strong> - <em>The adaptive value of xylem physiology within and across global ecoregions</em> as requested by Daniel Laughlin and Jesse Robert Fleri</p>
 <pre class="r"><code>library(tidyverse)
 
@@ -790,52 +790,52 @@ SpecificRootLength_mean
 <tbody>
 <tr>
 <td style="text-align:left;">
-Dillenia eximia
+Kunzea ericifolia
 </td>
 <td style="text-align:left;">
-tree
+shrub
 </td>
 <td style="text-align:left;">
-TRUE
+FALSE
 </td>
 <td style="text-align:right;">
 1
 </td>
 <td style="text-align:right;">
-0.6793376
+0.7283649
 </td>
 <td style="text-align:right;">
 NA
 </td>
 <td style="text-align:right;">
-22.639961
+61.990281
 </td>
 <td style="text-align:right;">
 NA
 </td>
 <td style="text-align:right;">
-44.57928
+31.98463
 </td>
 <td style="text-align:right;">
 NA
 </td>
 <td style="text-align:right;">
-10.54365
+10.605079
 </td>
 <td style="text-align:right;">
 NA
 </td>
 <td style="text-align:right;">
-12.4911119
+0.5061563
 </td>
 <td style="text-align:right;">
 NA
 </td>
 <td style="text-align:right;">
-299.8186
+195.2870
 </td>
 <td style="text-align:right;">
-567.8233
+543.5571
 </td>
 <td style="text-align:right;">
 NA
@@ -844,130 +844,130 @@ NA
 NA
 </td>
 <td style="text-align:right;">
-967.6425
+3554.2440
 </td>
 </tr>
 <tr>
 <td style="text-align:left;">
-Neolitsea australiensis
+Epacris paludosa
 </td>
 <td style="text-align:left;">
-tree
+shrub
 </td>
 <td style="text-align:left;">
-TRUE
+FALSE
 </td>
 <td style="text-align:right;">
-7
+1
 </td>
 <td style="text-align:right;">
-0.5792000
+0.6180130
 </td>
 <td style="text-align:right;">
-0.0024933
+NA
 </td>
 <td style="text-align:right;">
-9.506151
+188.437623
 </td>
 <td style="text-align:right;">
-0.2596111
+NA
 </td>
 <td style="text-align:right;">
-30.23718
+15.30076
 </td>
 <td style="text-align:right;">
-0.3760617
+NA
 </td>
 <td style="text-align:right;">
-15.80171
+8.228136
 </td>
 <td style="text-align:right;">
-0.2652343
+NA
 </td>
 <td style="text-align:right;">
-7.9068383
+0.6297734
 </td>
 <td style="text-align:right;">
-0.4256402
+NA
 </td>
 <td style="text-align:right;">
-376.1127
+368.1810
 </td>
 <td style="text-align:right;">
-844.4782
+686.6200
 </td>
 <td style="text-align:right;">
-6.503023
+NA
 </td>
 <td style="text-align:right;">
-9.313165
+NA
 </td>
 <td style="text-align:right;">
-1656.2206
+1615.6063
 </td>
 </tr>
 <tr>
 <td style="text-align:left;">
-Phyllanthus welwitschianus
+Codia jaffrei
 </td>
 <td style="text-align:left;">
-shrub
+tree
 </td>
 <td style="text-align:left;">
-FALSE
+TRUE
 </td>
 <td style="text-align:right;">
-8
+NA
 </td>
 <td style="text-align:right;">
-0.6753104
+NA
 </td>
 <td style="text-align:right;">
-0.0130232
+NA
 </td>
 <td style="text-align:right;">
-65.281333
+NA
 </td>
 <td style="text-align:right;">
-4.6574508
+NA
 </td>
 <td style="text-align:right;">
-36.61334
+NA
 </td>
 <td style="text-align:right;">
-1.8540340
+NA
 </td>
 <td style="text-align:right;">
-11.23265
+NA
 </td>
 <td style="text-align:right;">
-0.4071654
+NA
 </td>
 <td style="text-align:right;">
-2.0744872
+NA
 </td>
 <td style="text-align:right;">
-0.8694553
+NA
 </td>
 <td style="text-align:right;">
-334.8895
+NA
 </td>
 <td style="text-align:right;">
-657.5239
+NA
 </td>
 <td style="text-align:right;">
-26.904739
+NA
 </td>
 <td style="text-align:right;">
-48.401052
+NA
 </td>
 <td style="text-align:right;">
-4172.6647
+NA
 </td>
 </tr>
 <tr>
 <td style="text-align:left;">
-Platymiscium
+Mortoniella pittieri
 </td>
 <td style="text-align:left;">
 tree
@@ -976,57 +976,57 @@ tree
 TRUE
 </td>
 <td style="text-align:right;">
-183
+NA
 </td>
 <td style="text-align:right;">
-0.7367135
+NA
 </td>
 <td style="text-align:right;">
-0.0570886
+NA
 </td>
 <td style="text-align:right;">
-8.752809
+NA
 </td>
 <td style="text-align:right;">
-0.8330028
+NA
 </td>
 <td style="text-align:right;">
-60.10325
+NA
 </td>
 <td style="text-align:right;">
-5.0651172
+NA
 </td>
 <td style="text-align:right;">
-18.66448
+NA
 </td>
 <td style="text-align:right;">
-6.1165028
+NA
 </td>
 <td style="text-align:right;">
-10.7226177
+NA
 </td>
 <td style="text-align:right;">
-3.1893958
+NA
 </td>
 <td style="text-align:right;">
-492.5852
+NA
 </td>
 <td style="text-align:right;">
-1254.5929
+NA
 </td>
 <td style="text-align:right;">
-40.384016
+NA
 </td>
 <td style="text-align:right;">
-74.824275
+NA
 </td>
 <td style="text-align:right;">
-867.0790
+NA
 </td>
 </tr>
 <tr>
 <td style="text-align:left;">
-Oxandra laurifolia
+Trophis
 </td>
 <td style="text-align:left;">
 tree
@@ -1035,57 +1035,57 @@ tree
 TRUE
 </td>
 <td style="text-align:right;">
-1
+160
 </td>
 <td style="text-align:right;">
-0.5884923
+0.5799697
 </td>
 <td style="text-align:right;">
-NA
+0.0778658
 </td>
 <td style="text-align:right;">
-19.187258
+9.840891
 </td>
 <td style="text-align:right;">
-NA
+1.1314241
 </td>
 <td style="text-align:right;">
-89.03682
+50.44614
 </td>
 <td style="text-align:right;">
-NA
+11.1199527
 </td>
 <td style="text-align:right;">
-21.26191
+21.133250
 </td>
 <td style="text-align:right;">
-NA
+6.0488715
 </td>
 <td style="text-align:right;">
-9.2218572
+15.1032393
 </td>
 <td style="text-align:right;">
-NA
+3.8993275
 </td>
 <td style="text-align:right;">
-516.4728
+327.6145
 </td>
 <td style="text-align:right;">
-1013.2987
+801.9136
 </td>
 <td style="text-align:right;">
-NA
+30.6755155
 </td>
 <td style="text-align:right;">
-NA
+50.3768197
 </td>
 <td style="text-align:right;">
-906.8100
+1720.2909
 </td>
 </tr>
 <tr>
 <td style="text-align:left;">
-Flindersia schottiana
+Planchonella glauca
 </td>
 <td style="text-align:left;">
 tree
@@ -1094,57 +1094,57 @@ tree
 TRUE
 </td>
 <td style="text-align:right;">
-45
+NA
 </td>
 <td style="text-align:right;">
-0.5841551
+NA
 </td>
 <td style="text-align:right;">
-0.0097030
+NA
 </td>
 <td style="text-align:right;">
-32.568851
+NA
 </td>
 <td style="text-align:right;">
-1.1659233
+NA
 </td>
 <td style="text-align:right;">
-39.34159
+NA
 </td>
 <td style="text-align:right;">
-1.1731701
+NA
 </td>
 <td style="text-align:right;">
-16.64684
+NA
 </td>
 <td style="text-align:right;">
-4.1421922
+NA
 </td>
 <td style="text-align:right;">
-15.0675958
+NA
 </td>
 <td style="text-align:right;">
-0.6137072
+NA
 </td>
 <td style="text-align:right;">
-814.5528
+NA
 </td>
 <td style="text-align:right;">
-1327.9419
+NA
 </td>
 <td style="text-align:right;">
-18.152491
+NA
 </td>
 <td style="text-align:right;">
-16.305176
+NA
 </td>
 <td style="text-align:right;">
-417.2301
+NA
 </td>
 </tr>
 <tr>
 <td style="text-align:left;">
-Pentas schimperi
+Cotyledon velutina
 </td>
 <td style="text-align:left;">
 shrub
@@ -1153,161 +1153,161 @@ shrub
 FALSE
 </td>
 <td style="text-align:right;">
-12
+1
 </td>
 <td style="text-align:right;">
-0.5994127
+0.3137810
 </td>
 <td style="text-align:right;">
-0.0085421
+NA
 </td>
 <td style="text-align:right;">
-101.582042
+620.284468
 </td>
 <td style="text-align:right;">
-10.6407222
+NA
 </td>
 <td style="text-align:right;">
-37.25850
+21.22847
 </td>
 <td style="text-align:right;">
-5.5948394
+NA
 </td>
 <td style="text-align:right;">
-16.82194
+16.053577
 </td>
 <td style="text-align:right;">
-0.3987059
+NA
 </td>
 <td style="text-align:right;">
-1.5952465
+1.1066924
 </td>
 <td style="text-align:right;">
-1.0000603
+NA
 </td>
 <td style="text-align:right;">
-429.1172
+450.2601
 </td>
 <td style="text-align:right;">
-710.6441
+512.9229
 </td>
 <td style="text-align:right;">
-85.197367
+NA
 </td>
 <td style="text-align:right;">
-81.569313
+NA
 </td>
 <td style="text-align:right;">
-6680.3624
+2530.9735
 </td>
 </tr>
 <tr>
 <td style="text-align:left;">
-Ditaxis catamarcensis
+Mitrephora teysmannii
 </td>
 <td style="text-align:left;">
-shrub
+tree
 </td>
 <td style="text-align:left;">
-NA
+TRUE
 </td>
 <td style="text-align:right;">
-NA
+3
 </td>
 <td style="text-align:right;">
-NA
+0.7483330
 </td>
 <td style="text-align:right;">
-NA
+0.0090990
 </td>
 <td style="text-align:right;">
-NA
+20.357402
 </td>
 <td style="text-align:right;">
-NA
+0.5531617
 </td>
 <td style="text-align:right;">
-NA
+94.16796
 </td>
 <td style="text-align:right;">
-NA
+3.9737192
 </td>
 <td style="text-align:right;">
-NA
+19.631506
 </td>
 <td style="text-align:right;">
-NA
+0.5069761
 </td>
 <td style="text-align:right;">
-NA
+12.5924995
 </td>
 <td style="text-align:right;">
-NA
+0.5909462
 </td>
 <td style="text-align:right;">
-NA
+493.0227
 </td>
 <td style="text-align:right;">
-NA
+1171.1943
 </td>
 <td style="text-align:right;">
-NA
+14.5568411
 </td>
 <td style="text-align:right;">
-NA
+17.6612858
 </td>
 <td style="text-align:right;">
-NA
+1268.6842
 </td>
 </tr>
 <tr>
 <td style="text-align:left;">
-Sideritis pusilla
+Neisosperma mianum
 </td>
 <td style="text-align:left;">
-shrub
+tree
 </td>
 <td style="text-align:left;">
-FALSE
+TRUE
 </td>
 <td style="text-align:right;">
-1
+NA
 </td>
 <td style="text-align:right;">
-0.4451498
+NA
 </td>
 <td style="text-align:right;">
 NA
 </td>
 <td style="text-align:right;">
-63.553638
+NA
 </td>
 <td style="text-align:right;">
 NA
 </td>
 <td style="text-align:right;">
-29.81245
+NA
 </td>
 <td style="text-align:right;">
 NA
 </td>
 <td style="text-align:right;">
-18.76373
+NA
 </td>
 <td style="text-align:right;">
 NA
 </td>
 <td style="text-align:right;">
-0.4582831
+NA
 </td>
 <td style="text-align:right;">
 NA
 </td>
 <td style="text-align:right;">
-374.2586
+NA
 </td>
 <td style="text-align:right;">
-544.4329
+NA
 </td>
 <td style="text-align:right;">
 NA
@@ -1316,12 +1316,12 @@ NA
 NA
 </td>
 <td style="text-align:right;">
-713.5340
+NA
 </td>
 </tr>
 <tr>
 <td style="text-align:left;">
-Erythrina sandwicensis
+Oxandra
 </td>
 <td style="text-align:left;">
 tree
@@ -1330,175 +1330,175 @@ tree
 TRUE
 </td>
 <td style="text-align:right;">
-3
+508
 </td>
 <td style="text-align:right;">
-0.3473648
+0.7439664
 </td>
 <td style="text-align:right;">
-0.0041953
+0.0279287
 </td>
 <td style="text-align:right;">
-5.449391
+46.542459
 </td>
 <td style="text-align:right;">
-0.2433384
+11.2841074
 </td>
 <td style="text-align:right;">
-83.52936
+66.58668
 </td>
 <td style="text-align:right;">
-0.5031719
+3.3169535
 </td>
 <td style="text-align:right;">
-13.11726
+11.912526
 </td>
 <td style="text-align:right;">
-0.1739220
+1.9821599
 </td>
 <td style="text-align:right;">
-8.4680174
+14.3297582
 </td>
 <td style="text-align:right;">
-0.8741256
+2.5364250
 </td>
 <td style="text-align:right;">
-309.1997
+489.8337
 </td>
 <td style="text-align:right;">
-1009.0911
+1049.0371
 </td>
 <td style="text-align:right;">
-2.017808
+25.3409824
 </td>
 <td style="text-align:right;">
-20.160225
+46.4265455
 </td>
 <td style="text-align:right;">
-1643.9625
+1158.0969
 </td>
 </tr>
 <tr>
 <td style="text-align:left;">
-Cytisus filipes
+Rhus typhina
 </td>
 <td style="text-align:left;">
-shrub
+tree
 </td>
 <td style="text-align:left;">
-FALSE
+TRUE
 </td>
 <td style="text-align:right;">
-1
+61
 </td>
 <td style="text-align:right;">
-0.3918256
+0.4527526
 </td>
 <td style="text-align:right;">
-NA
+0.0069034
 </td>
 <td style="text-align:right;">
-64.145759
+53.477904
 </td>
 <td style="text-align:right;">
-NA
+5.7865638
 </td>
 <td style="text-align:right;">
-70.33197
+90.87015
 </td>
 <td style="text-align:right;">
-NA
+6.9805694
 </td>
 <td style="text-align:right;">
-17.32879
+16.845202
 </td>
 <td style="text-align:right;">
-NA
+4.3542703
 </td>
 <td style="text-align:right;">
-1.4899027
+6.3294372
 </td>
 <td style="text-align:right;">
-NA
+2.1204912
 </td>
 <td style="text-align:right;">
-557.8850
+1441.3973
 </td>
 <td style="text-align:right;">
-733.0138
+1983.9657
 </td>
 <td style="text-align:right;">
-NA
+110.9144264
 </td>
 <td style="text-align:right;">
-NA
+116.2715236
 </td>
 <td style="text-align:right;">
-446.3924
+757.1311
 </td>
 </tr>
 <tr>
 <td style="text-align:left;">
-Gaultheria phillyreifolia
+Abies nephrolepis
 </td>
 <td style="text-align:left;">
-shrub
+tree
 </td>
 <td style="text-align:left;">
-NA
+TRUE
 </td>
 <td style="text-align:right;">
-NA
+27
 </td>
 <td style="text-align:right;">
-NA
+0.3512129
 </td>
 <td style="text-align:right;">
-NA
+0.0114178
 </td>
 <td style="text-align:right;">
-NA
+407.180257
 </td>
 <td style="text-align:right;">
-NA
+33.9504526
 </td>
 <td style="text-align:right;">
-NA
+13.67868
 </td>
 <td style="text-align:right;">
-NA
+0.4732980
 </td>
 <td style="text-align:right;">
-NA
+9.892645
 </td>
 <td style="text-align:right;">
-NA
+1.5514761
 </td>
 <td style="text-align:right;">
-NA
+33.9981397
 </td>
 <td style="text-align:right;">
-NA
+5.3546088
 </td>
 <td style="text-align:right;">
-NA
+712.9564
 </td>
 <td style="text-align:right;">
-NA
+1296.2292
 </td>
 <td style="text-align:right;">
-NA
+35.6846481
 </td>
 <td style="text-align:right;">
-NA
+38.7653154
 </td>
 <td style="text-align:right;">
-NA
+2597.8812
 </td>
 </tr>
 <tr>
 <td style="text-align:left;">
-Tilia europaea
+Iryanthera
 </td>
 <td style="text-align:left;">
 tree
@@ -1507,57 +1507,57 @@ tree
 TRUE
 </td>
 <td style="text-align:right;">
-4
+872
 </td>
 <td style="text-align:right;">
-0.4558695
+0.5788963
 </td>
 <td style="text-align:right;">
-0.0190405
+0.0214108
 </td>
 <td style="text-align:right;">
-88.081677
+11.691323
 </td>
 <td style="text-align:right;">
-5.8414605
+2.6742994
 </td>
 <td style="text-align:right;">
-54.53532
+69.60219
 </td>
 <td style="text-align:right;">
-0.5138064
+10.3527934
 </td>
 <td style="text-align:right;">
-21.92167
+11.394669
 </td>
 <td style="text-align:right;">
-0.2783723
+1.7863227
 </td>
 <td style="text-align:right;">
-32.2072947
+18.2076192
 </td>
 <td style="text-align:right;">
-11.1902462
+2.6997193
 </td>
 <td style="text-align:right;">
-332.8352
+615.3043
 </td>
 <td style="text-align:right;">
-695.6468
+1615.3044
 </td>
 <td style="text-align:right;">
-6.060288
+38.6066697
 </td>
 <td style="text-align:right;">
-17.853047
+102.6116320
 </td>
 <td style="text-align:right;">
-2722.3237
+1203.0586
 </td>
 </tr>
 <tr>
 <td style="text-align:left;">
-Astrocasia peltata
+Licaria pucheri
 </td>
 <td style="text-align:left;">
 tree
@@ -1616,66 +1616,66 @@ NA
 </tr>
 <tr>
 <td style="text-align:left;">
-Erythroxylum hondense
+Ficus palmata
 </td>
 <td style="text-align:left;">
 shrub
 </td>
 <td style="text-align:left;">
-NA
+TRUE
 </td>
 <td style="text-align:right;">
-NA
+3
 </td>
 <td style="text-align:right;">
-NA
+0.4166359
 </td>
 <td style="text-align:right;">
-NA
+0.0059615
 </td>
 <td style="text-align:right;">
-NA
+17.196187
 </td>
 <td style="text-align:right;">
-NA
+5.9575747
 </td>
 <td style="text-align:right;">
-NA
+43.09359
 </td>
 <td style="text-align:right;">
-NA
+1.5349340
 </td>
 <td style="text-align:right;">
-NA
+18.205922
 </td>
 <td style="text-align:right;">
-NA
+0.4136751
 </td>
 <td style="text-align:right;">
-NA
+11.8499790
 </td>
 <td style="text-align:right;">
-NA
+0.4458733
 </td>
 <td style="text-align:right;">
-NA
+298.8537
 </td>
 <td style="text-align:right;">
-NA
+572.8625
 </td>
 <td style="text-align:right;">
-NA
+11.1446281
 </td>
 <td style="text-align:right;">
-NA
+10.4592304
 </td>
 <td style="text-align:right;">
-NA
+1377.5573
 </td>
 </tr>
 <tr>
 <td style="text-align:left;">
-Duguetia surinamensis
+Santalum paniculatum
 </td>
 <td style="text-align:left;">
 tree
@@ -1684,57 +1684,57 @@ tree
 TRUE
 </td>
 <td style="text-align:right;">
-69
+2
 </td>
 <td style="text-align:right;">
-0.8236290
+0.7417319
 </td>
 <td style="text-align:right;">
-0.0162819
+0.0000636
 </td>
 <td style="text-align:right;">
-24.385029
+19.537087
 </td>
 <td style="text-align:right;">
-1.2262742
+0.9933779
 </td>
 <td style="text-align:right;">
-134.87025
+24.31650
 </td>
 <td style="text-align:right;">
-4.7318346
+0.0772736
 </td>
 <td style="text-align:right;">
-13.52768
+5.509882
 </td>
 <td style="text-align:right;">
-2.3291569
+0.0290659
 </td>
 <td style="text-align:right;">
-16.4117221
+4.9944134
 </td>
 <td style="text-align:right;">
-1.7789890
+0.0294042
 </td>
 <td style="text-align:right;">
-591.9557
+240.6449
 </td>
 <td style="text-align:right;">
-1289.1331
+616.3328
 </td>
 <td style="text-align:right;">
-21.840571
+0.0361808
 </td>
 <td style="text-align:right;">
-39.750879
+0.9732207
 </td>
 <td style="text-align:right;">
-789.2354
+554.3731
 </td>
 </tr>
 <tr>
 <td style="text-align:left;">
-Nolina bigelovii
+Diospyros cinnabarina
 </td>
 <td style="text-align:left;">
 tree
@@ -1743,116 +1743,116 @@ tree
 TRUE
 </td>
 <td style="text-align:right;">
-1
+2
 </td>
 <td style="text-align:right;">
-0.3974529
+0.6610894
 </td>
 <td style="text-align:right;">
-NA
+0.0035850
 </td>
 <td style="text-align:right;">
-31.073291
+14.580362
 </td>
 <td style="text-align:right;">
-NA
+0.9772326
 </td>
 <td style="text-align:right;">
-17.02055
+55.77311
 </td>
 <td style="text-align:right;">
-NA
+1.9367853
 </td>
 <td style="text-align:right;">
-19.86053
+11.881875
 </td>
 <td style="text-align:right;">
-NA
+0.1371734
 </td>
 <td style="text-align:right;">
-1.1087419
+10.9291313
 </td>
 <td style="text-align:right;">
-NA
+0.7287004
 </td>
 <td style="text-align:right;">
-388.3643
+431.2067
 </td>
 <td style="text-align:right;">
-749.1778
+1151.1902
 </td>
 <td style="text-align:right;">
-NA
+12.7213760
 </td>
 <td style="text-align:right;">
-NA
+14.2037536
 </td>
 <td style="text-align:right;">
-2435.8136
+1452.2787
 </td>
 </tr>
 <tr>
 <td style="text-align:left;">
-Drypetes
+Protium altsonii
 </td>
 <td style="text-align:left;">
-NA
+tree
 </td>
 <td style="text-align:left;">
 TRUE
 </td>
 <td style="text-align:right;">
-3
+39
 </td>
 <td style="text-align:right;">
-0.7221564
+0.6128564
 </td>
 <td style="text-align:right;">
-0.0292078
+0.0255524
 </td>
 <td style="text-align:right;">
-33.585934
+12.230485
 </td>
 <td style="text-align:right;">
-2.7312624
+0.9091390
 </td>
 <td style="text-align:right;">
-48.57965
+43.51911
 </td>
 <td style="text-align:right;">
-1.6676046
+2.2129142
 </td>
 <td style="text-align:right;">
-11.35004
+14.697606
 </td>
 <td style="text-align:right;">
-0.2093386
+2.1798936
 </td>
 <td style="text-align:right;">
-16.9021891
+20.4438840
 </td>
 <td style="text-align:right;">
-5.2380642
+1.7465118
 </td>
 <td style="text-align:right;">
-385.6425
+404.9270
 </td>
 <td style="text-align:right;">
-1007.3347
+971.3543
 </td>
 <td style="text-align:right;">
-4.931223
+13.3303058
 </td>
 <td style="text-align:right;">
-32.358909
+26.8407913
 </td>
 <td style="text-align:right;">
-3019.2382
+765.7623
 </td>
 </tr>
 <tr>
 <td style="text-align:left;">
-Casearia obliqua
+Litsea glutinosa
 </td>
 <td style="text-align:left;">
 tree
@@ -1861,102 +1861,102 @@ tree
 TRUE
 </td>
 <td style="text-align:right;">
-18
+6
 </td>
 <td style="text-align:right;">
-0.6995384
+0.5487119
 </td>
 <td style="text-align:right;">
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 <td style="text-align:left;">
-Zygia unifoliolata
+Anabasis elatior
 </td>
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 shrub
 </td>
 <td style="text-align:left;">
-NA
+FALSE
 </td>
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-NA
+1
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-NA
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-NA
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-NA
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-NA
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-NA
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-NA
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-NA
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 </td>
 <td style="text-align:right;">
 NA
@@ -1965,7 +1965,7 @@ NA
 NA
 </td>
 <td style="text-align:right;">
-NA
+2705.0498
 </td>
 </tr>
 </tbody>
@@ -4895,7 +4895,8 @@ NA
 <h1>4 Extract climate and soils data</h1>
 <pre class="r"><code>soilclim.xylem &lt;- soilclim %&gt;% 
   filter(PlotObservationID %in% plot.sel) %&gt;% 
-  dplyr::select(Elevation=Elevation_median, -Elevation_q2.5, -Elevation_q97.5, -Elevation_DEM.res)</code></pre>
+  dplyr::rename(Elevation=Elevation_median) %&gt;% 
+  dplyr::select(-Elevation_q2.5, -Elevation_q97.5, -Elevation_DEM.res)</code></pre>
 <table class="table table-striped table-hover table-condensed table-responsive" style="width: auto !important; margin-left: auto; margin-right: auto;">
 <caption>
 Example of climatic and soil variables for 20 randomly selected plots. All values represent the mean in a circle centered on the plot coordinates, having a radius equal to the plot’s location uncertainty (capped to 50 km for computing reasons). Standard deviation (sd) is also reported for each climatic and soil variable.
@@ -4903,110 +4904,3575 @@ Example of climatic and soil variables for 20 randomly selected plots. All value
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+bio04
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@@ -5085,14 +8551,14 @@ sessionInfo()</code></pre>
 ## [17] rlang_0.4.8        readxl_1.3.1       rstudioapi_0.11    rmarkdown_2.5     
 ## [21] labeling_0.4.2     webshot_0.5.2      munsell_0.5.0      broom_0.7.0       
 ## [25] compiler_3.6.3     modelr_0.1.6       xfun_0.19          pkgconfig_2.0.3   
-## [29] htmltools_0.5.0    tidyselect_1.1.0   codetools_0.2-18   fansi_0.4.1       
-## [33] crayon_1.3.4       dbplyr_2.0.0       withr_2.3.0        jsonlite_1.7.1    
-## [37] gtable_0.3.0       lifecycle_0.2.0    DBI_1.1.0          magrittr_1.5      
-## [41] units_0.6-7        scales_1.1.1       KernSmooth_2.23-18 cli_2.1.0         
-## [45] stringi_1.5.3      farver_2.0.3       fs_1.5.0           xml2_1.3.2        
-## [49] ellipsis_0.3.1     generics_0.1.0     vctrs_0.3.4        tools_3.6.3       
-## [53] glue_1.4.2         maps_3.3.0         hms_0.5.3          yaml_2.2.1        
-## [57] colorspace_1.4-1   classInt_0.4-3     rvest_0.3.6        haven_2.3.1</code></pre>
+## [29] htmltools_0.5.0    tidyselect_1.1.0   fansi_0.4.1        crayon_1.3.4      
+## [33] dbplyr_2.0.0       withr_2.3.0        jsonlite_1.7.1     gtable_0.3.0      
+## [37] lifecycle_0.2.0    DBI_1.1.0          magrittr_1.5       units_0.6-7       
+## [41] scales_1.1.1       KernSmooth_2.23-18 cli_2.1.0          stringi_1.5.3     
+## [45] farver_2.0.3       fs_1.5.0           xml2_1.3.2         ellipsis_0.3.1    
+## [49] generics_0.1.0     vctrs_0.3.4        tools_3.6.3        glue_1.4.2        
+## [53] maps_3.3.0         hms_0.5.3          yaml_2.2.1         colorspace_1.4-1  
+## [57] classInt_0.4-3     rvest_0.3.6        haven_2.3.1</code></pre>
 </div>