Georgia 2018 and 2019
2018
Table 2018 1. New Informants
## informant.code gender age community elevation district
## 1 256 F 80 Verona 1260 Sagarejo
## 2 257 M 68 Verona 1260 Sagarejo
## 3 258 F 73 Verona 1260 Sagarejo
## 4 259 F 80 Sig'nag'i 790 Sig'nag'i
## 5 260 M 80 Nukriani 970 Sig'nag'i
## 6 261 F 80 Nukriani 970 Sig'nag'i
## 7 262 F 60 Kvemo Magaro 550 Sig'nag'i
## 8 263 M 60 Kvemo Magaro 550 Sig'nag'i
## 9 264 F 49 Kedeli 720 Sig'nag'i
## 10 265 M 60 Kedeli 720 Sig'nag'i
## 11 266 F 45 Kedeli 720 Sig'nag'i
## 12 267 F 50 Kedeli 720 Sig'nag'i
## 13 268 F 55 Kedeli 720 Sig'nag'i
## 14 269 F 45 Kedeli 720 Sig'nag'i
## 15 270 F 50 Kedeli 720 Sig'nag'i
## 16 271 F 55 Kedeli 720 Sig'nag'i
## 17 272 M 72 Zinobiani 600 Kvareli
## 18 273 M 70 Lagodekhi 450 Lagodekhi
## 19 274 F 40 Akhalsopeli 460 Kvareli
## 20 275 F 50 Akhalsopeli 460 Kvareli
## 21 276 F 55 Akhalsopeli 460 Kvareli
## 22 277 F 55 Akhalsopeli 460 Kvareli
## 23 278 F 66 Satskhene 775 Kvareli
## 24 279 M 62 Chantlikure 400 Kvareli
## 25 280 F 60 Chantlikure 400 Kvareli
## 26 281 F 42 Pona 400 Kvareli
## 27 282 M 63 Sagrasheni 1180 Tetritskaro
## 28 283 M 60 Sagrasheni 1180 Tetritskaro
## 29 284 M 60 Asureti 720 Tetritskaro
## 30 285 M 78 Sagrasheni 350 Tetritskaro
## 31 286 F 74 Sagrasheni 350 Tetritskaro
## 32 287 F 40 Chkhikvta 893 Tetritskaro
## 33 288 M 37 Chkhikvta 893 Tetritskaro
## 34 289 M 79 Tetritskaro 1120 Tetritskaro
## 35 290 F 65 Sagrasheni 350 Tetritskaro
## 36 291 F 65 Sagrasheni 350 Tetritskaro
## 37 292 F 70 Sagrasheni 350 Tetritskaro
## 38 293 F 70 Sagrasheni 350 Tetritskaro
## 39 294 F 70 Sagrasheni 350 Tetritskaro
## 40 295 F 70 Sagrasheni 350 Tetritskaro
## 41 296 F 70 Sagrasheni 350 Tetritskaro
## 42 297 F 55 Sagrasheni 350 Tetritskaro
## 43 298 M 82 Didi magareti 1098 Tetritskaro
## 44 299 F 85 Didi magareti 1098 Tetritskaro
## 45 300 F 55 Kvemo Magaro 500 Sig'nag'iFigure 2018 1. Informants from 2018 ordered by their distance in plants reported (A,B,C) and in uses reported (D,E,F).
Tables 2018 2 and 2018 3. Full fit reports.
plants
##
## ***VECTORS
##
## NMDS1 NMDS2 r2 Pr(>r)
## age -0.39954 -0.91671 0.0475 0.347
## elevation 0.06271 -0.99803 0.2843 0.001 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Permutation: free
## Number of permutations: 999
##
## ***FACTORS:
##
## Centroids:
## NMDS1 NMDS2
## genderF 0.0401 0.1993
## genderM -0.0888 -0.4412
## communityAkhalsopeli -0.1111 0.2595
## communityAsureti 0.0516 -0.7234
## communityChantlikure 0.4639 -0.1017
## communityChkhikvta -0.2601 -0.5133
## communityDidi magareti -0.6497 -0.0877
## communityKedeli 0.2818 0.1177
## communityKvemo Magaro 1.0492 0.6398
## communityLagodekhi -0.8937 0.1566
## communityNukriani 2.0520 -0.3185
## communityPona -0.2708 0.1772
## communitySagrasheni -0.2294 0.0772
## communitySatskhene 0.1025 0.3224
## communitySig'nag'i 0.0359 -0.1155
## communityTetritskaro -0.8908 -1.1992
## communityVerona -0.4407 -0.1453
## communityZinobiani -2.2298 -0.9652
## districtKvareli -0.2127 0.0410
## districtLagodekhi -0.8937 0.1566
## districtSagarejo -0.4407 -0.1453
## districtSig'nag'i 0.6815 0.1506
## districtTetritskaro -0.3006 -0.1221
##
## Goodness of fit:
## r2 Pr(>r)
## gender 0.1021 0.009 **
## community 0.6763 0.001 ***
## district 0.2632 0.004 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Permutation: free
## Number of permutations: 999uses
##
## ***VECTORS
##
## NMDS1 NMDS2 r2 Pr(>r)
## age -0.96498 -0.26233 0.2897 0.001 ***
## elevation -0.83861 -0.54473 0.0880 0.146
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Permutation: free
## Number of permutations: 999
##
## ***FACTORS:
##
## Centroids:
## NMDS1 NMDS2
## genderF 0.1666 0.0121
## genderM -0.3690 -0.0267
## communityAkhalsopeli 0.5926 -0.2580
## communityAsureti -0.9054 -0.2803
## communityChantlikure -0.0053 -0.6155
## communityChkhikvta 0.0058 -0.0290
## communityDidi magareti -0.9495 -0.0130
## communityKedeli 0.4908 0.2463
## communityKvemo Magaro -0.0204 0.1647
## communityLagodekhi -0.0727 -0.1659
## communityNukriani -0.0528 -0.0474
## communityPona 0.1022 -0.0626
## communitySagrasheni -0.2401 0.1351
## communitySatskhene 0.6185 -0.5039
## communitySig'nag'i -0.1256 0.4240
## communityTetritskaro -0.1042 -0.0871
## communityVerona -0.2202 -0.4233
## communityZinobiani -0.2029 0.3013
## districtKvareli 0.3197 -0.2809
## districtLagodekhi -0.0727 -0.1659
## districtSagarejo -0.2202 -0.4233
## districtSig'nag'i 0.2596 0.1996
## districtTetritskaro -0.3210 0.0650
##
## Goodness of fit:
## r2 Pr(>r)
## gender 0.1797 0.001 ***
## community 0.6628 0.001 ***
## district 0.3732 0.001 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Permutation: free
## Number of permutations: 999ICF
Table 2018 4. Mean informant consensus across use categories among informant districts, with total number of use reports and taxa.
| District | N.Use.Categories | Total.Use.Reports | Total.Taxa | ICF.mean | ICF.sd |
|---|---|---|---|---|---|
| Kvareli | 5 | 463 | 127 | 0.61 | 0.19 |
| Lagodekhi | 3 | 68 | 58 | 0.10 | 0.14 |
| Sagarejo | 4 | 123 | 42 | 0.76 | 0.16 |
| Sig’nag’i | 4 | 534 | 145 | 0.64 | 0.15 |
| Tetritskaro | 8 | 887 | 145 | 0.79 | 0.14 |
Important plants
Table 2018 5: Top plants by UV
## # A tibble: 6 x 5
## Scientific.name CIinf CIcom Du UV
## <chr> <dbl> <dbl> <dbl> <dbl>
## 1 Anethum graveolens L. 1.11 1.1 0.249 0.978
## 2 Cucumis sativus L. 1 1 0 0.956
## 3 Brassica oleracea L. 1 1 0 0.933
## 4 Lycopersicum esculentum L. 1 1 0 0.933
## 5 Chenopodium album L. 1 1 0 0.844
## 6 Malus orientalis Uglizk. 1 1 0 0.8Table 2018 6: Top plants by Du
## # A tibble: 6 x 5
## Scientific.name CIinf CIcom Du UV
## <chr> <dbl> <dbl> <dbl> <dbl>
## 1 Quercus iberica M. Bieb 1.32 1.36 1.54 0.556
## 2 Fagus orientalis Lipsky 1.33 1.3 1.44 0.533
## 3 Sorbus aucuparia K. Koch 1 1 0.974 0.178
## 4 Cydonia oblonga L. 1.11 1.2 0.898 0.222
## 5 Morus alba L. 1.11 1.2 0.898 0.222
## 6 Stellaria media (L.) Vill. 1 1.5 0.721 0.267Table 2018 7: Top plants by CiInf
## # A tibble: 6 x 5
## Scientific.name CIinf CIcom Du UV
## <chr> <dbl> <dbl> <dbl> <dbl>
## 1 Hyppomarathum(crispum (Pers.) Boiss. 2 2 0.693 0.133
## 2 Sambucus nigra L. 2 2 0.693 0.0889
## 3 Rumex sp. 1.44 1.67 0.613 0.444
## 4 Sambucus ebulus L. 1.39 1.25 0.627 0.556
## 5 Fagus orientalis Lipsky 1.33 1.3 1.44 0.533
## 6 Quercus iberica M. Bieb 1.32 1.36 1.54 0.556Regional comparion
Table 2018 8 and 2018 9: Distinctive Plants
Plants not found in Kakheti and mentioned by >25% of Kartli informants
## # A tibble: 7 x 3
## Scientific.name Kartli_informants Kartli_percent
## <chr> <int> <dbl>
## 1 Thymus sp. 14 0.778
## 2 Polygonatum glaberrimum C. Koch. 9 0.5
## 3 Satureja hortensis L. 8 0.444
## 4 Serratula quinquefolia Bieb. ex Willd. 8 0.444
## 5 Heracleum sosnowskyi Manden 7 0.389
## 6 Chaerophyllum bulbosum L. 6 0.333
## 7 Lycium barbarum L. 5 0.278Plants not found in Kartli and mentioned by >25% of Kakheti informants
## # A tibble: 12 x 3
## Scientific.name Kakheti_informants Kakheti_percent
## <chr> <int> <dbl>
## 1 Smilax excelsa L. 17 0.630
## 2 Tilia caucasica Rupr. 14 0.519
## 3 Taraxacum officinale Wigg. 10 0.370
## 4 Castanea sativa Mill. 9 0.333
## 5 Lamium album L. 9 0.333
## 6 Rumex sp. 9 0.333
## 7 Solanum melogena L. 8 0.296
## 8 Sorbus aucuparia K. Koch 8 0.296
## 9 Dryopteris filix-mas (L.) Schott. 7 0.259
## 10 Humulus lupulus L. 7 0.259
## 11 Rumex acetosa L. 7 0.259
## 12 Spinaca oleracea L. 7 0.259Table 2018 10 and 2018 11: Common plants used for different purposes
Plant-use combinations in which species exists in both places, but species-use is not found in Kakheti, but mentioned by >25% of Kartli informants
## # A tibble: 6 x 4
## # Groups: Scientific.name [6]
## Scientific.name Use.Category Kartli_informan… Kartli_percent
## <chr> <chr> <int> <dbl>
## 1 Ailanthus altissima (Mil… utensils and t… 8 0.444
## 2 Picea orientalis (L.) Pe… food 8 0.444
## 3 Pinus sosnowskyi Nakai food 8 0.444
## 4 Stellaria media (L.) Vil… food 8 0.444
## 5 Carpinus caucasica Gross… fuel 7 0.389
## 6 Carpinus orientalis Mill. fuel 5 0.278Plant-use combinations in which species exists in both places, but species-use is not found in Kartli, but mentioned by >25% of Kakheti informants
## # A tibble: 2 x 4
## # Groups: Scientific.name [2]
## Scientific.name Use.Category Kakheti_informants Kakheti_percent
## <chr> <chr> <int> <dbl>
## 1 Sambucus ebulus L. food 8 0.296
## 2 Rosa sp. food 7 0.259Do areas surveyed in 2018 have less plant use then areas surveyed before 2018?
Yes:
## # A tibble: 2 x 3
## period `Plants/Informant (mean)` `Plant-uses/Informant (mean)`
## <chr> <dbl> <dbl>
## 1 2013-2017 58.1 62.7
## 2 2018 41.1 42.4Figure 2018 2 and 2018 3: Number of plant-uses reported by each informant in 2018 vs. 2013-2017 studies
(scatterplot) 
(boxplot) 
2019
Table 2019 1. 2019 Informants
## informant.code gender age community elevation district
## 1 301 M 70 Merisi 736 Keda
## 2 302 M 50 Merisi 736 Keda
## 3 303 F 50 Merisi 736 Keda
## 4 304 M 36 Uchkhiti 400 Keda
## 5 305 F 40 Uchkhiti 400 Keda
## 6 306 F 50 Uchkhiti 400 Keda
## 7 307 F 40 Uchkhiti 400 Keda
## 8 308 M 55 Dologani 160 Keda
## 9 309 F 50 Dologani 160 Keda
## 10 310 F 53 Dologani 160 Keda
## 11 311 M 57 Chvana 549 Shuakhevi
## 12 312 M 70 Gogadzeebi 1335 Shuakhevi
## 13 313 M 46 Gogadzeebi 1335 Shuakhevi
## 14 314 F 63 Gogadzeebi 1335 Shuakhevi
## 15 315 F 60 Gogadzeebi 1335 Shuakhevi
## 16 316 F 35 Gogadzeebi 1335 Shuakhevi
## 17 317 F 76 Center 420 Shuakhevi
## 18 318 F 52 Chvana 549 Shuakhevi
## 19 319 M 55 Chvana 549 Shuakhevi
## 20 320 F 45 Chvana 549 Shuakhevi
## 21 321 M 35 Chvana 549 Shuakhevi
## 22 322 M 42 Tsivadzeebi 475 Shuakhevi
## 23 323 F 95 Tsivadzeebi 475 Shuakhevi
## 24 324 M 64 Tsivadzeebi 475 Shuakhevi
## 25 325 F 59 Tsivadzeebi 475 Shuakhevi
## 26 326 F 49 Gomarduli 11230 Shuakhevi
## 27 327 F 78 Gomarduli 11230 Shuakhevi
## 28 328 M 72 Gomarduli 11230 Shuakhevi
## 29 329 M 82 Gomarduli 11230 Shuakhevi
## 30 330 F 69 Fushrukauli 11230 Khulo
## 31 331 M 76 Fushrukauli 11230 Khulo
## 32 332 F 44 Skhalta 800 Khulo
## 33 333 M 83 Fachkha 1172 Khulo
## 34 334 M 48 Fachkha 1172 Khulo
## 35 335 M 40 Fachkha 1172 Khulo
## 36 336 F 59 Samikao 320 Tsalenjikha
## 37 337 F 73 Samikao 320 Tsalenjikha
## 38 338 M 63 Samikao 320 Tsalenjikha
## 39 339 F 53 Napichkhovo 244 Chkhorots'q'u
## 40 340 F 50 Napichkhovo 244 Chkhorots'q'u
## 41 341 M 72 Napichkhovo 244 Chkhorots'q'u
## 42 342 F 66 Napichkhovo 244 Chkhorots'q'u
## 43 343 M 80 Napichkhovo 244 Chkhorots'q'u
## 44 344 M 55 Napichkhovo 244 Chkhorots'q'u
## 45 345 M 91 Mukhuri 260 Chkhorots'q'u
## 46 346 M 55 Mukhuri 260 Chkhorots'q'u
## 47 347 F 65 Etseri 320 Tsalenjikha
## 48 348 M 35 Etseri 320 Tsalenjikha
## 49 349 M 42 Muzhava, Sashonio 320 Chkhorots'q'u
## 50 350 F 40 Muzhava, Sashonio 320 Chkhorots'q'u
## 51 351 F 40 Muzhava, Sashonio 320 Chkhorots'q'u
## 52 352 M 67 Samikao 300 Tsalenjikha
## 53 353 M 84 Skuri 375 Tsalenjikha
## 54 354 M 57 Skuri 375 Tsalenjikha
## 55 355 M 55 Skuri 375 Tsalenjikha
## 56 356 M 65 Mukhuri 375 Tsalenjikha
## 57 357 M 55 Mukhuri 375 Tsalenjikha
## 58 358 F 70 Gakhara 400 Tsalenjikha
## 59 359 M 80 Salkhino 400 Martvili
## 60 360 M 75 Salkhino 400 Martvili
## 61 361 F 75 Salkhino 400 Martvili
## 62 362 F 45 Jikhashkari 300 Chkhorotsku
## 63 363 F 70 Jikhashkari 300 Chkhorotsku
## 64 364 M 70 Jikhashkari 300 Chkhorotsku
## 65 365 M 45 Jikhashkari 300 Chkhorotsku
## 66 366 F 66 Lentekhi 755 Lentekhi
## 67 367 M 83 Shkedi 1300 Lentekhi
## 68 368 F 40 Shkedi 1300 Lentekhi
## 69 369 F 70 Shkedi 1300 Lentekhi
## 70 370 M 53 Shkedi 1300 Lentekhi
## 71 371 F 77 Shkedi 1300 Lentekhi
## 72 372 M 53 Tsana 1800 Lentekhi
## 73 373 M 55 Tsana 1800 Lentekhi
## 74 374 F 80 Leusheri 1300 Lentekhi
## 75 375 F 77 Leusheri 1300 Lentekhi
## 76 376 M 25 Leusheri 1300 LentekhiFigure 2019 1. Informants from 2019 ordered by their 2019distance in plants reported (A,B,C) and in uses reported (D,E,F). 
Tables 2019 2 and 2019 3. Full fit reports.
plants
##
## ***VECTORS
##
## NMDS1 NMDS2 r2 Pr(>r)
## age -0.99798 -0.06361 0.0163 0.566
## elevation 0.19499 -0.98081 0.1534 0.004 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Permutation: free
## Number of permutations: 999
##
## ***FACTORS:
##
## Centroids:
## NMDS1 NMDS2
## genderF 0.1477 0.0736
## genderM -0.1330 -0.0663
## communityCenter 0.3893 0.2807
## communityChvana 0.6000 0.0864
## communityDologani -0.4326 0.8706
## communityEtseri -1.7369 0.8876
## communityFachkha 0.2455 -0.2357
## communityFushrukauli 0.6554 -0.7345
## communityGakhara -2.7578 -1.0325
## communityGogadzeebi 0.4575 -0.3347
## communityGomarduli -0.1383 -0.8706
## communityJikhashkari 0.6759 0.8785
## communityLentekhi 0.4835 0.1008
## communityLeusheri 1.1069 -0.6238
## communityMerisi -0.4122 -0.0160
## communityMukhuri -0.3109 0.8434
## communityMuzhava, Sashonio 1.4972 0.2368
## communityNapichkhovo -1.6830 0.1966
## communitySalkhino 0.2028 0.3162
## communitySamikao -0.7684 0.2334
## communityShkedi 0.3724 -1.0485
## communitySkhalta 0.1454 -0.5886
## communitySkuri 0.0887 0.6116
## communityTsana -0.3054 -1.7343
## communityTsivadzeebi 0.5580 0.5323
## communityUchkhiti 0.1271 -0.0603
## districtChkhorots'q'u -0.6566 0.3400
## districtChkhorotsku 0.6759 0.8785
## districtKeda -0.2026 0.2323
## districtKhulo 0.3654 -0.4608
## districtLentekhi 0.4596 -0.9529
## districtMartvili 0.2028 0.3162
## districtShuakhevi 0.3871 -0.1218
## districtTsalenjikha -0.7222 0.4195
##
## Goodness of fit:
## r2 Pr(>r)
## gender 0.0162 0.316
## community 0.7425 0.001 ***
## district 0.3320 0.001 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Permutation: free
## Number of permutations: 999uses
##
## ***VECTORS
##
## NMDS1 NMDS2 r2 Pr(>r)
## age -0.69850 -0.71561 0.0545 0.144
## elevation -0.92595 0.37764 0.0073 0.751
## Permutation: free
## Number of permutations: 999
##
## ***FACTORS:
##
## Centroids:
## NMDS1 NMDS2
## genderF 0.0020 0.0827
## genderM -0.0018 -0.0744
## communityCenter -0.4509 0.0206
## communityChvana -0.0781 0.1560
## communityDologani 0.6692 0.8557
## communityEtseri 0.1552 0.0922
## communityFachkha -0.4727 0.0504
## communityFushrukauli 0.0657 0.4590
## communityGakhara -1.2476 -1.2144
## communityGogadzeebi -0.1631 0.1879
## communityGomarduli -0.1262 -0.1691
## communityJikhashkari -0.3403 -0.0590
## communityLentekhi -0.2042 0.7079
## communityLeusheri 0.5855 -0.4200
## communityMerisi -0.4627 0.0654
## communityMukhuri 0.0272 -0.3244
## communityMuzhava, Sashonio 0.8569 0.1551
## communityNapichkhovo 0.6203 -0.4469
## communitySalkhino -0.0160 -0.1886
## communitySamikao 0.4896 0.2815
## communityShkedi -0.2277 -0.1289
## communitySkhalta -0.3869 -0.0034
## communitySkuri 0.2130 -0.2954
## communityTsana -0.3524 -0.0558
## communityTsivadzeebi -0.6332 0.1418
## communityUchkhiti -0.1533 0.2385
## districtChkhorots'q'u 0.5379 -0.2527
## districtChkhorotsku -0.3403 -0.0590
## districtKeda 0.0006 0.3717
## districtKhulo -0.2789 0.1776
## districtLentekhi -0.0265 -0.1189
## districtMartvili -0.0160 -0.1886
## districtShuakhevi -0.2471 0.0858
## districtTsalenjikha 0.1787 -0.1270
##
## Goodness of fit:
## r2 Pr(>r)
## gender 0.0171 0.279
## community 0.8239 0.001 ***
## district 0.3122 0.001 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Permutation: free
## Number of permutations: 999ICF
Table 2019 4. Mean informant consensus across use categories among informant districts, with total number 2019of use reports and taxa.
| District | N.Use.Categories | Total.Use.Reports | Total.Taxa | ICF.mean | ICF.sd |
|---|---|---|---|---|---|
| Chkhorots’q’u | 10 | 499 | 129 | 0.79 | 0.17 |
| Chkhorotsku | 4 | 184 | 44 | 0.78 | 0.01 |
| Keda | 8 | 538 | 94 | 0.89 | 0.10 |
| Khulo | 6 | 413 | 96 | 0.83 | 0.17 |
| Lentekhi | 8 | 584 | 126 | 0.78 | 0.16 |
| Martvili | 5 | 158 | 54 | 0.72 | 0.06 |
| Shuakhevi | 7 | 1375 | 167 | 0.77 | 0.16 |
| Tsalenjikha | 9 | 420 | 135 | 0.71 | 0.21 |
Important plants
Table 2019 5: Top plants by UV
## # A tibble: 6 x 5
## Scientific.name CIinf CIcom Du UV
## <chr> <dbl> <dbl> <dbl> <dbl>
## 1 Pyrus communis L. 1 1 0 2.78
## 2 Malus orientalis Uglizk. 1 1 0 1.97
## 3 Vitis vinifera L. 1 1.06 0.0510 1.47
## 4 Phaseolus vulgaris L. 1 1 0 1.04
## 5 Capsicum annuum L. 1 1 0 0.974
## 6 Prunus divaricata Ledeb. 1.12 1.28 0.439 0.908Table 2019 6: Top plants by Du
## # A tibble: 6 x 5
## Scientific.name CIinf CIcom Du UV
## <chr> <dbl> <dbl> <dbl> <dbl>
## 1 Rhododendron ponticum L. 1.2 1.2 1.24 0.237
## 2 Rhododendron luteum Sweet 1 1 1.06 0.118
## 3 Quercus petrea ssp iberica (Steven ex M. Bieb.)… 1 1.5 1.00 0.0921
## 4 Tilia caucasica Rupr. 1.34 1.4 0.872 0.592
## 5 Sambucus ebulus L. 1.59 1.7 0.773 0.671
## 6 Chenopodium album L. 1 1 0.693 0.158Table 2019 7: Top plants by CiInf
## # A tibble: 6 x 5
## Scientific.name CIinf CIcom Du UV
## <chr> <dbl> <dbl> <dbl> <dbl>
## 1 Eucalyptus saligna Sm. 2 2 0.693 0.0789
## 2 Phyllitis scolopendrium (L.) Newman 2 2 0.693 0.0789
## 3 Trifolium sp. 2 2 0.693 0.0789
## 4 Cryptomeria japonica (Thunb. ex L. f.) D. Don 2 2 0.693 0.0526
## 5 Cannabis sativa L. 1.86 2 0.662 0.211
## 6 Sambucus ebulus L. 1.59 1.7 0.773 0.671Regional comparion
Table 2019 8 and 2019 9: Distinctive Plants
Plants not found in Samegrelo & Kvemo Svaneti and mentioned by >20% of Adjara informants
## # A tibble: 12 x 3
## Scientific.name Adjara_informants Adjara_percent
## <chr> <int> <dbl>
## 1 Rubus caesius L. 23 0.657
## 2 Polygonum carneum C. Koch 20 0.571
## 3 Quercus dschorochensis C. Koch 16 0.457
## 4 Nicotiana tabacum L. 14 0.4
## 5 Campanula lactiflora M. Bieb. 13 0.371
## 6 Helichrysum graveolens (M.Bieb.) Sweet 13 0.371
## 7 Prunus cerasus L. 13 0.371
## 8 Prunus x domestica L. 11 0.314
## 9 Aruncus vulgaris Raf. 10 0.286
## 10 Begonia rex Putz. 10 0.286
## 11 Satureja laxiflora K. Koch 10 0.286
## 12 Crocus sativus L. 9 0.257Plants not found in Adjara and mentioned by >20% of Samegrelo & Kvemo Svaneti informants
## # A tibble: 9 x 3
## Scientific.name SamKvem_informants SamKvem_percent
## <chr> <int> <dbl>
## 1 Rhododendron caucasicum Pall. 13 0.317
## 2 Euphorbia sp. 10 0.244
## 3 Helleborus caucasicus R. Br. 10 0.244
## 4 Hypericum sp. 10 0.244
## 5 Phytolacca americana L. 10 0.244
## 6 Taraxacum officinale Wigg. 10 0.244
## 7 Cyclamen vernum Sweet 9 0.220
## 8 Setaria italica (L.) P. Beauv. 9 0.220
## 9 Solidago canadensis L. 9 0.220Table 2019 10 and 2019 11: Common plants used for different purposes
Plant-use combinations in which species exists in both places, but species-use is not found in Samegrelo & Kvemo Svaneti, but mentioned by >10% of Adjara informants.
## # A tibble: 7 x 4
## # Groups: Scientific.name [7]
## Scientific.name Use.Category Adjara_informants Adjara_percent
## <chr> <chr> <int> <dbl>
## 1 Sambucus ebulus L. food 22 0.629
## 2 Prunus divaricata Ledeb. medicinal 10 0.286
## 3 Chelidonium majus L. medicinal 6 0.171
## 4 Rubus idaeus L. medicinal 5 0.143
## 5 Sambucus nigra L. medicinal 5 0.143
## 6 Juniperus sp. cultural 4 0.114
## 7 Urtica dioica L. medicinal 4 0.114Plant-use combinations in which species exists in both places, but species-use is not found in Adjara, but mentioned by >10% of Samegrelo & Kvemo Svaneti informants.
## # A tibble: 7 x 4
## # Groups: Scientific.name [7]
## Scientific.name Use.Category SamKvem_informan… SamKvem_percent
## <chr> <chr> <int> <dbl>
## 1 Zea mays L. animal food 8 0.195
## 2 Ruscus colchicus Yeo animal food 7 0.171
## 3 Chenopodium album L. animal food 6 0.146
## 4 Corylus avellana L. utensils and too… 6 0.146
## 5 Apium graveolens L. medicinal 5 0.122
## 6 Berberis vulgaris L. medicinal 5 0.122
## 7 Tilia caucasica Rupr. medicinal 5 0.122Do areas surveyed in 2019 have less plant use then areas surveyed before 2018?
Yes:
## # A tibble: 2 x 3
## period `Plants/Informant (mean… `Plant-use Combinations/Informant (me…
## <chr> <dbl> <dbl>
## 1 2013-2017 58.1 62.7
## 2 2019 44.0 45.8Figure 2019 2 and 2019 3: Number of plant-uses reported by each informant in 2019 vs. 2013-2017 studies
(scatterplot) 
(boxplot) 