1 Background

This document has several purposes:

2 Data background

The fungal records come from national efforts in Austria and Switzerland to compile fungal collection data from a variety of sources. Detailed information about these datasets can be found on their respective webpages: Switzerland; Austria. Collections in these databases come from a variety of sources, including mycologist collections, systematic surveys, and herbarium records. We used records between the 114 to 2599 meters in elevation (masl). We analyse altitudinal changes in fruiting patterns of 5606 fungal observations from the 118 most intensively collected species from the Austrian and Suisse national fungal record datasets between 1960 and 2010 CE. We restricted our analyses to Agaricomycetes, i.e. to basidiomycete species producing annual or perennial macroscopic fruit bodies. Only observations with proper annotation of date and geographical coordinates were included.

3 Exploratory

Maps of all data.

Figure 3.1: Map of all collections.

Map of all collections.

Figure 3.2: Map of all collections.

Zoomed in on one region; all collections.

Figure 3.3: Zoomed in on one region; all collections.



Example map of one species, Amanita muscaria:
Amanita muscaria all collections.

Figure 3.4: Amanita muscaria all collections.

Amanita muscaria zoomed in.

Figure 3.5: Amanita muscaria zoomed in.

4 Methods

4.1 Statistical Models

We fit linear mixed models, where the response was mean elevation of mushroom collection for each species in each year, and the primary predictor was elevation. We fit several different forms allowing for different error structures:

4.1.1 BRMS Models

We used two different models for how elevation of mushroom collection may be changing over time (years).

m2: Intercept & slope varies by species
\(Elevation = (1 + year|species) + year\)

m3: Intercept varies by species; slope varies by nutritional group
\(Elevation = (1|species) + year + (year|nut)\)

where \(nut\) is the species’ nutritional mode.

We fit these models using the ‘brms’ package in R1.

Example ‘brms’ code:

# Intercept varies by species; slope varies by nutritional
# group

# Set model fomula
m3 <- bf(elev ~ (1 | species) + year + (year | nut))

# Fit model
fit_m3 <- brm(m3, data = dat.sp, control = list(adapt_delta = 0.99, 
    max_treedepth = 12), cores = 3, chains = 3, iter = 5000)

5 Results

5.1 Nutritional groups

Model 3: Random intercept varies by species; slope varies by nutritional group
\(Elevation = (1|species) + year + (year|nut)\)

  • Significant trends in elevation as a function of year for each of the three nutritional groups.
Table 5.1: Table of m3-estimated responses to year (betas) for the three nutritional groups. Bayesian p-values (pval) calculated as the probability that the effect is greater or less than zero.
group beta.mean beta.sd Q1.year Q5.year Q50.year Q95.year Q99.year pval
Ecm 0.0101653 0.0011076 0.0075149 0.0083432 0.0101631 0.0119436 0.0127502 0.000000
Sapro_Litter_Soil 0.0112313 0.0016096 0.0074719 0.0085765 0.0112361 0.0138824 0.0149790 0.000000
Sapro_Wood 0.0021925 0.0015451 -0.0013039 -0.0003330 0.0021927 0.0047303 0.0058072 0.077942
Estimated elevation over time (m3)

Figure 5.1: Estimated elevation over time (m3)

5.2 Species-level

Model 2: Random intercept varies by species; slope varies by species
\(Elevation = (1 = year | species) + year\)

Species-specific slopes:

Figure 2 from manuscript. Species-specific slopes

Figure 5.2: Figure 2 from manuscript. Species-specific slopes

Species’ trends over time are related to their distributional characteristics (Fig. 5.3).
Figure 3 from manuscript.

Figure 5.3: Figure 3 from manuscript.

6 Effects of sampling effort

A basic challenge that potentially confounds estimates of trends over time is that collection effort has also increased through time (Fig. 6.1). We outline here three lines of evidence suggesting that this increase in sampling over time has not biased the estimation of the trend in altitude.

Total collections over time

Figure 6.1: Total collections over time

6.2 Has the proportion of collections made at high elevation, in a year, increased over time?

Another plausible expectation if there is a spurious increase in elevation with increased sampling would be that the proportion of collections made at high elevation would be expected to increase with greater collection efforts. This does not seem to be the case (Fig. 6.3), suggesting that greater collection effort did not necessarily mean more collection effort at high elevation relative to lower elevations.

Proportion of collections above mean elevation as a function of collection effort.

Figure 6.3: Proportion of collections above mean elevation as a function of collection effort.

6.3 Null model

We also used a null model approach to examine the likelihood of obtaining a spurious positive altitudinal trend over time. We randomized the years of collections, within each species, 1000 times and ran mixed effects models using lmer function in the lme4 package in R: \(lmer(elev \sim (1 |species) + year, data=dat.rand)\). By decoupling the elevation of collection from the years of collection, while maintaining the skewed sampling intensity through time, significant trends in elevation through time would suggest spurious trends due to the sampling. We found 75 of the 1000 randomizations (7.5%) produced a significant slope (p<0.05). The p-value calculated from the raw data was << 0.001, and lower than all randomized runs. The fact that the p-value for the estimated slope is significantly lower than all of the simulated datasets suggests that increased sampling intensity through time is not causing the significant trend.

Left: Distribution of slopes estimated from null models, along with true slope (blue). Right: Distribution of p-values from randomized null model. In green are model runs with p < 0.05. Blue line represents the p-value calculated on the raw dataset (p<0.001).

Figure 6.4: Left: Distribution of slopes estimated from null models, along with true slope (blue). Right: Distribution of p-values from randomized null model. In green are model runs with p < 0.05. Blue line represents the p-value calculated on the raw dataset (p<0.001).

7 Species tables

Table 7.1: Summary of species trends; same as graphed in figure 2. N.pos = number of positive trends; N.pos.signif=number of significant positive trends (p < 0.1)
nut.habitat N.pos N.pos.signif N.neg N.neg.signif
Ecm 47 26 9 0
Sapro_Litter_Soil 26 15 3 1
Sapro_Wood 20 7 13 1
Table 7.2: Table of species information.
species N elev.mean elev.range nut.habitat
Agaricus sylvicola 1099 619.4 2140 Sapro_Litter_Soil
Amanita citrina 1504 563.2 1799 Ecm
Amanita excelsa 1712 671.1 2082 Ecm
Amanita muscaria 2380 860.2 2235 Ecm
Amanita pantherina 1000 621.4 2015 Ecm
Amanita phalloides 1285 494.9 2029 Ecm
Amanita rubescens 3545 664.2 2170 Ecm
Amanita vaginata 1459 698.3 2245 Ecm
Bjerkandera adusta 1928 540.4 2014 Sapro_Wood
Boletus edulis 2449 825.5 2195 Ecm
Boletus erythropus 1633 720.5 2082 Ecm
Boletus subtomentosus 1703 624.0 2347 Ecm
Cantharellus cibarius 3533 724.0 2285 Ecm
Chroogomphus rutilus 967 741.6 2314 Ecm
Clavulina coralloides 1253 728.2 2123 Ecm
Clitocybe gibba 1968 745.8 2347 Sapro_Litter_Soil
Clitocybe nebularis 1984 638.3 1968 Sapro_Litter_Soil
Clitopilus prunulus 2107 733.1 2277 Sapro_Litter_Soil
Coprinellus micaceus 1072 535.7 1815 Sapro_Wood
Coprinus comatus 1078 676.1 2119 Sapro_Litter_Soil
Cortinarius caperatus 945 1013.4 2308 Ecm
Craterellus cornucopioides 1133 545.6 2052 Ecm
Craterellus tubaeformis 1600 759.4 1986 Ecm
Cystoderma amianthinum 1256 904.8 2442 Sapro_Litter_Soil
Daedalea quercina 1091 443.1 2133 Sapro_Wood
Daedaleopsis confragosa 1479 563.4 2152 Sapro_Wood
Entoloma rhodopolium 1057 661.7 2008 Sapro_Litter_Soil
Fomes fomentarius 1208 583.3 1780 Sapro_Wood
Fomitopsis pinicola 4011 792.2 2388 Sapro_Wood
Fuscoporia ferruginosa 989 577.6 2196 Sapro_Wood
Galerina marginata 1232 802.2 2698 Sapro_Wood
Gymnopilus penetrans 1333 694.5 2254 Sapro_Wood
Gymnopus androsaceus 1025 890.3 2452 Sapro_Litter_Soil
Gymnopus confluens 1726 787.9 2044 Sapro_Litter_Soil
Gymnopus dryophilus 1722 675.1 2298 Sapro_Litter_Soil
Gymnopus perforans 1090 945.9 2293 Sapro_Litter_Soil
Gymnopus peronatus 1234 591.3 2010 Sapro_Litter_Soil
Hydnum repandum 2185 731.0 2009 Ecm
Hygrophorus agathosmus 1008 979.3 2198 Ecm
Hygrophorus eburneus 952 630.2 1701 Ecm
Hymenopellis radicata 2245 539.3 1757 Sapro_Wood
Hypholoma capnoides 1482 820.0 2288 Sapro_Wood
Hypholoma fasciculare 3420 575.8 2190 Sapro_Wood
Hypholoma lateritium 1161 534.6 1981 Sapro_Wood
Imleria badia 2169 684.7 2177 Ecm
Inocybe geophylla 1953 789.2 2457 Ecm
Inocybe rimosa 1350 720.8 2388 Ecm
Kuehneromyces mutabilis 1640 694.9 2225 Sapro_Wood
Laccaria amethystina 2228 714.8 2172 Ecm
Laccaria laccata 1019 854.1 2462 Ecm
Laccaria tetraspora 1695 703.1 2697 Ecm
Lactarius blennius 1182 654.1 1890 Ecm
Lactarius deterrimus 2411 891.2 2208 Ecm
Lactarius pallidus 1003 682.7 1526 Ecm
Lactarius piperatus 1104 528.8 1792 Ecm
Lactarius quietus 1012 438.4 2107 Ecm
Lactarius rufus 1055 969.3 2370 Ecm
Lactarius salmonicolor 1349 767.8 2515 Ecm
Lactarius scrobiculatus 1327 1020.5 2193 Ecm
Lactarius vellereus 1097 580.4 1561 Ecm
Leccinum scabrum 1018 667.7 1738 Ecm
Lentinus ciliatus 905 641.1 2168 Sapro_Wood
Lepiota cristata 1172 649.5 2425 Sapro_Litter_Soil
Lepista nuda 1594 625.5 2328 Sapro_Litter_Soil
Leucocybe connata 944 908.0 2389 Sapro_Litter_Soil
Lycoperdon perlatum 2811 665.5 2391 Sapro_Litter_Soil
Lycoperdon pyriforme 1861 691.1 2277 Sapro_Wood
Macrolepiota procera 1771 596.9 2234 Sapro_Litter_Soil
Marasmius oreades 988 637.2 2048 Sapro_Litter_Soil
Marasmius rotula 995 520.8 2095 Sapro_Wood
Megacollybia platyphylla 2262 565.4 1620 Sapro_Wood
Mycena epipterygia 1677 872.1 2298 Sapro_Litter_Soil
Mycena galericulata 2018 658.2 2107 Sapro_Wood
Mycena galopus 1726 853.3 2389 Sapro_Litter_Soil
Mycena pura 3485 753.5 2390 Sapro_Litter_Soil
Mycena rosea 962 557.2 1510 Sapro_Litter_Soil
Mycena sanguinolenta 1013 704.6 2298 Sapro_Litter_Soil
Mycetinis alliaceus 959 644.2 2359 Sapro_Litter_Soil
Panellus stipticus 1406 542.3 2088 Sapro_Wood
Paralepista flaccida 1354 570.6 2284 Sapro_Litter_Soil
Paxillus involutus 1654 709.1 2333 Ecm
Pluteus cervinus 2275 568.5 2317 Sapro_Wood
Polyporus varius 1190 703.0 2155 Sapro_Wood
Postia caesia 1061 727.6 2103 Sapro_Wood
Psathyrella candolleana 1223 512.8 2317 Sapro_Litter_Soil
Rhodocollybia butyracea 2253 733.3 2282 Sapro_Litter_Soil
Russula cyanoxantha 3573 584.0 2170 Ecm
Russula delica 904 803.8 2491 Ecm
Russula emetica 1095 937.8 2214 Ecm
Russula fellea 914 628.3 2059 Ecm
Russula foetens 1140 657.6 2104 Ecm
Russula integra 1527 875.9 2656 Ecm
Russula nigricans 1685 604.7 2145 Ecm
Russula ochroleuca 1841 732.2 2062 Ecm
Russula olivacea 1550 662.5 2222 Ecm
Russula queletii 1451 927.2 1976 Ecm
Russula rosea 1051 486.0 1551 Ecm
Russula vesca 1712 621.4 2234 Ecm
Schizophyllum commune 2419 556.3 2157 Sapro_Wood
Schizopora paradoxa 1355 535.5 2307 Sapro_Wood
Stereum hirsutum 2979 526.4 2274 Sapro_Wood
Stereum sanguinolentum 1025 753.2 2247 Sapro_Wood
Strobilurus esculentus 929 764.4 2321 Sapro_Litter_Soil
Suillellus luridus 1502 668.5 2106 Ecm
Suillus granulatus 984 707.2 2298 Ecm
Suillus grevillei 1930 851.6 2370 Ecm
Suillus viscidus 1008 1051.9 2329 Ecm
Tapinella atrotomentosa 1138 621.8 1994 Sapro_Wood
Trametes gibbosa 1766 535.0 1714 Sapro_Wood
Trametes hirsuta 2248 663.7 2303 Sapro_Wood
Trametes versicolor 3734 585.4 2152 Sapro_Wood
Trichaptum abietinum 1977 719.7 2229 Sapro_Wood
Tricholoma saponaceum 1179 867.0 2227 Ecm
Tricholoma terreum 1017 702.7 2254 Ecm
Tricholoma vaccinum 932 1059.8 2163 Ecm
Tricholomopsis rutilans 1708 693.8 2283 Sapro_Wood
Tubaria furfuracea 1045 512.3 2163 Sapro_Litter_Soil
Xerocomellus chrysenteron 2535 563.6 1716 Ecm
Table 7.3: Table of species-specific trends. Bayesian p-values (pval) calculated as the probability that the effect is greater or less than zero.
species beta.mean beta.sd species.Q5.year species.Q50.year species.Q95.year pval
Agaricus sylvicola 0.0125040 0.0064274 0.0016541 0.0124347 0.0231632 0.0259
Amanita citrina 0.0067914 0.0064793 -0.0037718 0.0068225 0.0177457 0.1473
Amanita excelsa 0.0191923 0.0063671 0.0086752 0.0191018 0.0296852 0.0013
Amanita muscaria 0.0167718 0.0062265 0.0065680 0.0167641 0.0271308 0.0035
Amanita pantherina 0.0058421 0.0065618 -0.0048133 0.0058107 0.0161903 0.1866
Amanita phalloides 0.0024620 0.0062742 -0.0076900 0.0024947 0.0127849 0.3474
Amanita rubescens 0.0067378 0.0063066 -0.0032585 0.0065715 0.0169262 0.1427
Amanita vaginata 0.0039884 0.0064331 -0.0066362 0.0039052 0.0144055 0.2676
Bjerkandera adusta -0.0036434 0.0069253 -0.0154016 -0.0034641 0.0073117 0.2994
Boletus edulis 0.0150061 0.0062326 0.0050392 0.0149901 0.0251428 0.0080
Boletus erythropus 0.0121844 0.0064923 0.0014886 0.0121837 0.0227563 0.0303
Boletus subtomentosus 0.0106022 0.0063478 0.0003546 0.0106030 0.0212095 0.0474
Cantharellus cibarius 0.0167492 0.0064222 0.0067004 0.0166721 0.0274074 0.0046
Chroogomphus rutilus 0.0054210 0.0064880 -0.0051982 0.0053870 0.0161821 0.2017
Clavulina coralloides 0.0016017 0.0063325 -0.0091057 0.0018142 0.0117779 0.4002
Clitocybe gibba 0.0089613 0.0062220 -0.0009884 0.0088644 0.0193854 0.0749
Clitocybe nebularis 0.0185963 0.0065974 0.0078475 0.0184981 0.0295016 0.0024
Clitopilus prunulus 0.0128490 0.0063878 0.0024228 0.0128735 0.0233556 0.0221
Coprinellus micaceus -0.0017552 0.0066427 -0.0124808 -0.0018299 0.0089694 0.3958
Coprinus comatus 0.0155111 0.0063607 0.0050155 0.0155144 0.0261739 0.0074
Cortinarius caperatus 0.0276489 0.0065748 0.0168952 0.0275982 0.0382291 0.0000
Craterellus cornucopioides -0.0050491 0.0065364 -0.0157121 -0.0050907 0.0055661 0.2199
Craterellus tubaeformis 0.0060970 0.0063381 -0.0044163 0.0060423 0.0164075 0.1680
Cystoderma amianthinum 0.0286408 0.0064738 0.0181919 0.0285850 0.0396474 0.0000
Daedalea quercina -0.0037622 0.0064379 -0.0143858 -0.0038093 0.0066359 0.2795
Daedaleopsis confragosa 0.0042519 0.0064649 -0.0063276 0.0042697 0.0148573 0.2554
Entoloma rhodopolium 0.0047403 0.0067948 -0.0063458 0.0047761 0.0159562 0.2427
Fomes fomentarius -0.0047912 0.0068673 -0.0160974 -0.0048854 0.0067422 0.2427
Fomitopsis pinicola 0.0042427 0.0063833 -0.0065676 0.0044820 0.0143480 0.2531
Fuscoporia ferruginosa -0.0021135 0.0070349 -0.0137314 -0.0021893 0.0093665 0.3819
Galerina marginata 0.0121603 0.0070987 0.0004769 0.0122119 0.0238757 0.0434
Gymnopilus penetrans 0.0093254 0.0066129 -0.0015748 0.0092799 0.0202474 0.0792
Gymnopus androsaceus 0.0115907 0.0065777 0.0006810 0.0114448 0.0224540 0.0390
Gymnopus confluens 0.0101412 0.0065580 -0.0009460 0.0102318 0.0205576 0.0610
Gymnopus dryophilus -0.0017683 0.0065268 -0.0126349 -0.0015032 0.0084486 0.3932
Gymnopus perforans 0.0131425 0.0062039 0.0028994 0.0131041 0.0231736 0.0171
Gymnopus peronatus 0.0007459 0.0067531 -0.0105086 0.0007593 0.0122275 0.4560
Hydnum repandum 0.0078313 0.0062379 -0.0022135 0.0077914 0.0182734 0.1047
Hygrophorus agathosmus 0.0250630 0.0067145 0.0140132 0.0250041 0.0361126 0.0001
Hygrophorus eburneus -0.0044737 0.0067789 -0.0155006 -0.0045683 0.0068422 0.2546
Hymenopellis radicata -0.0035710 0.0063116 -0.0140485 -0.0033825 0.0066271 0.2858
Hypholoma capnoides 0.0159295 0.0065379 0.0052629 0.0158871 0.0266743 0.0074
Hypholoma fasciculare 0.0071288 0.0064144 -0.0034728 0.0070768 0.0177979 0.1332
Hypholoma lateritium 0.0040147 0.0066978 -0.0072253 0.0040945 0.0150416 0.2744
Imleria badia 0.0105831 0.0063884 0.0003403 0.0105364 0.0208866 0.0488
Inocybe geophylla -0.0022115 0.0066247 -0.0134775 -0.0020854 0.0087289 0.3693
Inocybe rimosa -0.0038310 0.0064148 -0.0147045 -0.0037656 0.0066563 0.2752
Kuehneromyces mutabilis 0.0093551 0.0067114 -0.0015832 0.0094548 0.0204767 0.0817
Laccaria amethystina 0.0118900 0.0063465 0.0016554 0.0118858 0.0219903 0.0305
Laccaria laccata 0.0096713 0.0081999 -0.0038673 0.0096136 0.0232104 0.1191
Laccaria tetraspora 0.0108153 0.0063715 0.0002392 0.0108496 0.0211353 0.0448
Lactarius blennius -0.0071774 0.0064550 -0.0179265 -0.0071742 0.0033918 0.1331
Lactarius deterrimus 0.0195963 0.0060709 0.0099117 0.0196665 0.0295749 0.0006
Lactarius pallidus -0.0069274 0.0068129 -0.0180615 -0.0068574 0.0041902 0.1546
Lactarius piperatus 0.0008352 0.0065618 -0.0098678 0.0008872 0.0115073 0.4494
Lactarius quietus 0.0014279 0.0066091 -0.0095797 0.0014549 0.0122512 0.4145
Lactarius rufus 0.0224784 0.0064694 0.0119816 0.0223308 0.0329554 0.0003
Lactarius salmonicolor -0.0078852 0.0075741 -0.0204640 -0.0077001 0.0042248 0.1489
Lactarius scrobiculatus 0.0172229 0.0065185 0.0062310 0.0171430 0.0281271 0.0041
Lactarius vellereus 0.0002604 0.0065015 -0.0103951 0.0001702 0.0111996 0.4840
Leccinum scabrum 0.0128495 0.0064909 0.0022045 0.0128286 0.0232407 0.0239
Lentinus ciliatus 0.0071100 0.0063999 -0.0032657 0.0069907 0.0174920 0.1333
Lepiota cristata 0.0000601 0.0065513 -0.0106357 0.0001516 0.0107758 0.4963
Lepista nuda 0.0109370 0.0063670 0.0007536 0.0109315 0.0214464 0.0429
Leucocybe connata 0.0065472 0.0073690 -0.0056993 0.0066761 0.0184293 0.1871
Lycoperdon perlatum 0.0056001 0.0063036 -0.0050074 0.0055831 0.0159872 0.1872
Lycoperdon pyriforme 0.0043178 0.0063013 -0.0059459 0.0042920 0.0147497 0.2466
Macrolepiota procera 0.0076994 0.0064117 -0.0027277 0.0074974 0.0186753 0.1149
Marasmius oreades 0.0060553 0.0063148 -0.0043484 0.0060765 0.0165639 0.1688
Marasmius rotula -0.0036733 0.0065350 -0.0145253 -0.0035145 0.0070397 0.2870
Megacollybia platyphylla -0.0008410 0.0068825 -0.0120751 -0.0008136 0.0105556 0.4514
Mycena epipterygia 0.0195882 0.0066907 0.0085853 0.0195144 0.0308220 0.0017
Mycena galericulata 0.0070802 0.0064924 -0.0035519 0.0070552 0.0178067 0.1377
Mycena galopus 0.0199317 0.0065985 0.0091136 0.0198510 0.0309711 0.0013
Mycena pura 0.0143445 0.0066630 0.0037478 0.0141050 0.0255304 0.0157
Mycena rosea 0.0005582 0.0082602 -0.0129491 0.0007088 0.0138870 0.4731
Mycena sanguinolenta 0.0108618 0.0067334 0.0001941 0.0106352 0.0221353 0.0534
Mycetinis alliaceus -0.0100775 0.0073206 -0.0221849 -0.0099944 0.0017998 0.0843
Panellus stipticus 0.0057230 0.0067279 -0.0053028 0.0057404 0.0169123 0.1975
Paralepista flaccida 0.0084811 0.0067394 -0.0024657 0.0084444 0.0197036 0.1041
Paxillus involutus 0.0127754 0.0061295 0.0025738 0.0127328 0.0228897 0.0186
Pluteus cervinus 0.0070600 0.0067496 -0.0038508 0.0069571 0.0181002 0.1478
Polyporus varius -0.0095144 0.0066956 -0.0205787 -0.0095178 0.0016806 0.0777
Postia caesia 0.0103304 0.0066537 -0.0005657 0.0102983 0.0214788 0.0603
Psathyrella candolleana -0.0088869 0.0071067 -0.0209626 -0.0088407 0.0028237 0.1056
Rhodocollybia butyracea 0.0119435 0.0068277 0.0005877 0.0119931 0.0231915 0.0401
Russula cyanoxantha 0.0011152 0.0064758 -0.0093802 0.0009878 0.0118882 0.4316
Russula delica -0.0041074 0.0065190 -0.0150382 -0.0040845 0.0062959 0.2643
Russula emetica 0.0233659 0.0065683 0.0128386 0.0232630 0.0341163 0.0002
Russula fellea -0.0069205 0.0066136 -0.0179273 -0.0068472 0.0035718 0.1477
Russula foetens 0.0138884 0.0062955 0.0036856 0.0137520 0.0240671 0.0137
Russula integra 0.0121160 0.0064003 0.0014768 0.0122918 0.0224658 0.0292
Russula nigricans 0.0073275 0.0064094 -0.0033004 0.0073616 0.0177618 0.1265
Russula ochroleuca 0.0086748 0.0066183 -0.0020490 0.0087175 0.0194520 0.0950
Russula olivacea 0.0104911 0.0064941 0.0000079 0.0103634 0.0215191 0.0531
Russula queletii 0.0147696 0.0065012 0.0041356 0.0146277 0.0252272 0.0115
Russula rosea 0.0036673 0.0065760 -0.0072597 0.0036669 0.0144069 0.2885
Russula vesca 0.0054235 0.0064064 -0.0050267 0.0054685 0.0159678 0.1986
Schizophyllum commune -0.0002998 0.0068912 -0.0116036 -0.0002678 0.0110546 0.4826
Schizopora paradoxa 0.0000036 0.0067657 -0.0111241 0.0000595 0.0110081 0.4998
Stereum hirsutum -0.0061287 0.0066198 -0.0170428 -0.0059471 0.0046649 0.1773
Stereum sanguinolentum 0.0055483 0.0072133 -0.0061797 0.0057312 0.0173632 0.2209
Strobilurus esculentus 0.0074448 0.0065695 -0.0032559 0.0074387 0.0183146 0.1286
Suillellus luridus 0.0071193 0.0063243 -0.0033795 0.0072590 0.0172651 0.1301
Suillus granulatus 0.0049298 0.0063768 -0.0053657 0.0049523 0.0152618 0.2197
Suillus grevillei 0.0159245 0.0060955 0.0059354 0.0159259 0.0259009 0.0045
Suillus viscidus 0.0149435 0.0066124 0.0040939 0.0148833 0.0257525 0.0119
Tapinella atrotomentosa 0.0090161 0.0064621 -0.0016310 0.0090689 0.0196302 0.0815
Trametes gibbosa -0.0045781 0.0065575 -0.0151407 -0.0046910 0.0064612 0.2425
Trametes hirsuta 0.0011001 0.0065810 -0.0097515 0.0010701 0.0119944 0.4336
Trametes versicolor -0.0037092 0.0066612 -0.0145113 -0.0037830 0.0075705 0.2888
Trichaptum abietinum 0.0034603 0.0069163 -0.0079690 0.0036250 0.0145826 0.3084
Tricholoma saponaceum 0.0193450 0.0064555 0.0086686 0.0192058 0.0299019 0.0014
Tricholoma terreum 0.0032116 0.0063306 -0.0069261 0.0032884 0.0136232 0.3060
Tricholoma vaccinum 0.0300529 0.0067025 0.0191205 0.0300232 0.0410196 0.0000
Tricholomopsis rutilans 0.0109742 0.0062108 0.0006529 0.0109835 0.0209850 0.0386
Tubaria furfuracea 0.0029498 0.0067974 -0.0080710 0.0030044 0.0140197 0.3322
Xerocomellus chrysenteron 0.0054785 0.0065868 -0.0055611 0.0055671 0.0163637 0.2028

  1. Paul-Christian Bürkner (2017). brms: An R Package for Bayesian Multilevel Models Using Stan. Journal of Statistical Software, 80(1), 1-28. doi:10.18637/jss.v080.i01↩