Gut pathogen infections indicate species-specific effects on bumble bees exposed to pesticides inside a tomato greenhouse

Gut parasite infection and pesticide exposure affect bumble bee health and pollination behavior. These stressors are common in commercial tomato greenhouses, where growers deploy bumble bees for pollination. To investigate the effects of these stressors on bumble bee pollination in greenhouses, we sampled commercial bumble bee colonies for the presence of three common gut-parasites (Crithidia, Apicystis, Nosema) within three commercial tomato greenhouses that were sampled during 12-week periods of two growing seasons. We then sampled the nest material of these same colonies to detect and quantify compounds that are active ingredients in pesticides. Using grower-collected data, we monitored tomato anther bruising as a proxy for bee pollination activity, and recorded pesticide applications within the greenhouses. We found that parasite infection prevalence was correlated with total pesticide application and bumble bee colony density, but these relationships were parasite-specific. Crithidia prevalence increased with total pesticide use and decreased with bumble bee colony density. Crithidia infection was also negatively associated correlated with decreased pollination activity. In contrast, Apicystis infection decreased with total pesticide use, but increased with colony density, and was positively associated with pollination activity. We never detected Nosema in any colony. Pollination activity was not directly predicted by pesticide quantity. Nest-compound exposure revealed frequent detection of multiple pesticide compounds. We further found compound-specific associations with pathogen infection probability. Our results highlight that gut parasites, as mediated through pesticide exposure, have important effects on bumble bee pollination, but these effects are pathogen- and pesticide-specific.

Statistical Analyses

Bivariate analyses of pathogen prevelence and anther bruise score in each of the 6 greenhouses over the two sampling seasons

Input data

Crithidia

##                    Predictor Coefficient       SE Odds_Ratio  GLM_P_Value
## 4 total_pesticide_applied_ml    0.000009 0.000001   1.000009 2.666429e-19
## 3            total_fungicide    0.000026 0.000003   1.000026 2.694016e-14
## 2          total_insecticide    0.000005 0.000001   1.000005 2.187339e-09
## 1         avg_hives_in_phase   -0.008975 0.001797   0.991066 5.896558e-07
##   Anova_P_Value Anova_Chi_sqare Pseudo_R2    AIC    BIC
## 4  1.063726e-20           87.04    0.3590 189.28 188.86
## 3  3.652528e-17           70.96    0.2927 205.36 204.95
## 2  1.462365e-09           36.58    0.1509 239.74 239.32
## 1  4.482898e-07           25.47    0.1051 250.85 250.43

## --- BIVARIATE GLM RESULTS ---

##                    Predictor Coefficient       SE Odds_Ratio  GLM_P_Value
## 4 total_pesticide_applied_ml    0.000009 0.000001   1.000009 2.666429e-19
## 3            total_fungicide    0.000026 0.000003   1.000026 2.694016e-14
## 2          total_insecticide    0.000005 0.000001   1.000005 2.187339e-09
## 1         avg_hives_in_phase   -0.008975 0.001797   0.991066 5.896558e-07
##   Anova_P_Value Anova_Chi_sqare Pseudo_R2    AIC    BIC
## 4  1.063726e-20           87.04    0.3590 189.28 188.86
## 3  3.652528e-17           70.96    0.2927 205.36 204.95
## 2  1.462365e-09           36.58    0.1509 239.74 239.32
## 1  4.482898e-07           25.47    0.1051 250.85 250.43

Apicystis

##                    Predictor Coefficient       SE Odds_Ratio  GLM_P_Value
## 1         avg_hives_in_phase    0.026718 0.002609   1.027078 1.285414e-24
## 4 total_pesticide_applied_ml   -0.000005 0.000001   0.999995 1.862461e-05
## 2          total_insecticide   -0.000004 0.000001   0.999996 2.009297e-04
## 3            total_fungicide   -0.000003 0.000004   0.999997 4.041424e-01
##   Anova_P_Value Anova_Chi_sqare Pseudo_R2    AIC    BIC
## 1  1.687339e-27          118.05    0.5522 118.11 117.69
## 4  2.269643e-05           17.95    0.0840 218.22 217.80
## 2  2.036524e-04           13.80    0.0645 222.37 221.95
## 3  3.980740e-01            0.71    0.0033 235.45 235.03

## --- BIVARIATE GLM RESULTS ---

##                    Predictor Coefficient       SE Odds_Ratio  GLM_P_Value
## 1         avg_hives_in_phase    0.026718 0.002609   1.027078 1.285414e-24
## 4 total_pesticide_applied_ml   -0.000005 0.000001   0.999995 1.862461e-05
## 2          total_insecticide   -0.000004 0.000001   0.999996 2.009297e-04
## 3            total_fungicide   -0.000003 0.000004   0.999997 4.041424e-01
##   Anova_P_Value Anova_Chi_sqare Pseudo_R2    AIC    BIC
## 1  1.687339e-27          118.05    0.5522 118.11 117.69
## 4  2.269643e-05           17.95    0.0840 218.22 217.80
## 2  2.036524e-04           13.80    0.0645 222.37 221.95
## 3  3.980740e-01            0.71    0.0033 235.45 235.03

Anther bruise score

## --- BIVARIATE GLM & CAR::ANOVA RESULTS ---

##                    Predictor Coefficient       SE GLM_P_Value Anova_P_Value
## 6                   api_prop    0.772536 0.206787      0.0202        0.0002
## 5                 crith_prop   -0.391316 0.152361      0.0621        0.0102
## 4 total_pesticide_applied_ml   -0.000001 0.000001      0.1754        0.1000
## 1         avg_hives_in_phase    0.002197 0.001494      0.2153        0.1413
## 2          total_insecticide   -0.000001 0.000001      0.3345        0.2729
## 3            total_fungicide   -0.000001 0.000002      0.5132        0.4735
##   Anova_Chi_sqare R_Squared    AIC    BIC
## 6           13.96    0.7772 -10.95 -11.58
## 5            6.60    0.6225  -7.79  -8.41
## 4            2.71    0.4034  -5.04  -5.67
## 1            2.16    0.3510  -4.54  -5.16
## 2            1.20    0.2311  -3.52  -4.14
## 3            0.51    0.1138  -2.67  -3.29

##                    Predictor Coefficient       SE GLM_P_Value Anova_P_Value
## 6                   api_prop    0.772536 0.206787      0.0202        0.0002
## 5                 crith_prop   -0.391316 0.152361      0.0621        0.0102
## 4 total_pesticide_applied_ml   -0.000001 0.000001      0.1754        0.1000
## 1         avg_hives_in_phase    0.002197 0.001494      0.2153        0.1413
## 2          total_insecticide   -0.000001 0.000001      0.3345        0.2729
## 3            total_fungicide   -0.000001 0.000002      0.5132        0.4735
##   Anova_Chi_sqare R_Squared    AIC    BIC
## 6           13.96    0.7772 -10.95 -11.58
## 5            6.60    0.6225  -7.79  -8.41
## 4            2.71    0.4034  -5.04  -5.67
## 1            2.16    0.3510  -4.54  -5.16
## 2            1.20    0.2311  -3.52  -4.14
## 3            0.51    0.1138  -2.67  -3.29

Figure 2

Figure 3

Pesticide residue analysis

Fisher’s Exact Test and ChiSquare Analysis

## 
##  Fisher's Exact Test for Count Data with simulated p-value (based on
##  1e+05 replicates)
## 
## data:  contingency_table
## p-value = 0.5132
## alternative hypothesis: two.sided

## 
##  Chi-squared test for given probabilities with simulated p-value (based
##  on 1e+05 replicates)
## 
## data:  applied_only$Detected
## X-squared = 7.086, df = NA, p-value = 0.4101

##               Chemical Detected Expected
## 1         Azoxystrobin        2     1.55
## 4  Chlorantraniliprole        6     7.75
## 5         Chlorfenapyr        4     4.65
## 7       Difenoconazole        4     1.55
## 10          Flonicamid        1     1.55
## 11           Fluopyram        5     3.10
## 15         Propamocarb        5     7.75
## 17        Pyrimethanil        4     3.10

Wax chemical analyses

###(1)does exposure to a particular chemical correlate with parasite infection?

## 
## Approx TRUE prevalence for *.Exposed (ignoring NA):
## A.Exposed B.Exposed C.Exposed D.Exposed E.Exposed F.Exposed G.Exposed H.Exposed 
##     1.000     0.667     0.667     1.000     0.833     0.333     0.833     1.000 
## I.Exposed J.Exposed K.Exposed L.Exposed M.Exposed N.Exposed O.Exposed P.Exposed 
##     0.667     1.000     0.667     0.333     0.500     0.167     0.500     0.333 
## Q.Exposed R.Exposed S.Exposed T.Exposed U.Exposed V.Exposed W.Exposed 
##     0.500     0.167     0.333     0.167     0.167     0.167     0.167

## 
## ----
## Fitting for chemical B
## Formula: cbind(crith_pos_b, crith_neg_b) ~ B.Exposed + (1 | greenhouse)
## 
## ----
## Fitting for chemical C
## Formula: cbind(crith_pos_b, crith_neg_b) ~ C.Exposed + (1 | greenhouse)

## 
## ----
## Fitting for chemical E
## Formula: cbind(crith_pos_b, crith_neg_b) ~ E.Exposed + (1 | greenhouse)
## 
## ----
## Fitting for chemical F
## Formula: cbind(crith_pos_b, crith_neg_b) ~ F.Exposed + (1 | greenhouse)
## 
## ----
## Fitting for chemical G
## Formula: cbind(crith_pos_b, crith_neg_b) ~ G.Exposed + (1 | greenhouse)

## 
## ----
## Fitting for chemical I
## Formula: cbind(crith_pos_b, crith_neg_b) ~ I.Exposed + (1 | greenhouse)

## 
## ----
## Fitting for chemical K
## Formula: cbind(crith_pos_b, crith_neg_b) ~ K.Exposed + (1 | greenhouse)
## 
## ----
## Fitting for chemical L
## Formula: cbind(crith_pos_b, crith_neg_b) ~ L.Exposed + (1 | greenhouse)
## 
## ----
## Fitting for chemical M
## Formula: cbind(crith_pos_b, crith_neg_b) ~ M.Exposed + (1 | greenhouse)
## 
## ----
## Fitting for chemical N
## Formula: cbind(crith_pos_b, crith_neg_b) ~ N.Exposed + (1 | greenhouse)
## 
## ----
## Fitting for chemical O
## Formula: cbind(crith_pos_b, crith_neg_b) ~ O.Exposed + (1 | greenhouse)
## 
## ----
## Fitting for chemical P
## Formula: cbind(crith_pos_b, crith_neg_b) ~ P.Exposed + (1 | greenhouse)
## 
## ----
## Fitting for chemical Q
## Formula: cbind(crith_pos_b, crith_neg_b) ~ Q.Exposed + (1 | greenhouse)
## 
## ----
## Fitting for chemical R
## Formula: cbind(crith_pos_b, crith_neg_b) ~ R.Exposed + (1 | greenhouse)
## 
## ----
## Fitting for chemical S
## Formula: cbind(crith_pos_b, crith_neg_b) ~ S.Exposed + (1 | greenhouse)
## 
## ----
## Fitting for chemical T
## Formula: cbind(crith_pos_b, crith_neg_b) ~ T.Exposed + (1 | greenhouse)
## 
## ----
## Fitting for chemical U
## Formula: cbind(crith_pos_b, crith_neg_b) ~ U.Exposed + (1 | greenhouse)
## 
## ----
## Fitting for chemical V
## Formula: cbind(crith_pos_b, crith_neg_b) ~ V.Exposed + (1 | greenhouse)
## 
## ----
## Fitting for chemical W
## Formula: cbind(crith_pos_b, crith_neg_b) ~ W.Exposed + (1 | greenhouse)

## 
## ================ PRIMARY EFFECTS (X.Exposed TRUE vs FALSE) ================

##           term estimate       OR      LCL      UCL     SE chemical
##  N.ExposedTRUE   -3.057  0.04702 0.008834   0.2503 0.8531        N
##  C.ExposedTRUE    2.050  7.76914 1.550368  38.9324 0.8223        C
##  E.ExposedTRUE   -2.515  0.08088 0.009134   0.7162 1.1128        E
##  F.ExposedTRUE   -2.050  0.12871 0.025685   0.6450 0.8223        F
##  G.ExposedTRUE   -2.515  0.08088 0.009134   0.7162 1.1128        G
##  R.ExposedTRUE    2.515 12.36387 1.396264 109.4816 1.1128        R
##  T.ExposedTRUE    2.515 12.36387 1.396264 109.4816 1.1128        T
##  U.ExposedTRUE    2.515 12.36387 1.396264 109.4816 1.1128        U
##  V.ExposedTRUE    2.515 12.36387 1.396264 109.4816 1.1128        V
##  W.ExposedTRUE    2.515 12.36387 1.396264 109.4816 1.1128        W
##  I.ExposedTRUE    1.824  6.19896 1.032816  37.2061 0.9143        I
##  B.ExposedTRUE   -1.575  0.20703 0.029684   1.4438 0.9910        B
##  K.ExposedTRUE   -1.575  0.20703 0.029684   1.4438 0.9910        K
##  P.ExposedTRUE    1.575  4.83033 0.692589  33.6882 0.9910        P
##  M.ExposedTRUE   -1.385  0.25021 0.038317   1.6339 0.9574        M
##  O.ExposedTRUE   -1.385  0.25021 0.038317   1.6339 0.9574        O
##  Q.ExposedTRUE    1.385  3.99661 0.612040  26.0977 0.9574        Q
##  S.ExposedTRUE    1.522  4.58347 0.639354  32.8585 1.0050        S
##  L.ExposedTRUE   -1.371  0.25391 0.032853   1.9625 1.0434        L
##                                                         formula converged
##  cbind(crith_pos_b, crith_neg_b) ~ N.Exposed + (1 | greenhouse)      TRUE
##  cbind(crith_pos_b, crith_neg_b) ~ C.Exposed + (1 | greenhouse)      TRUE
##  cbind(crith_pos_b, crith_neg_b) ~ E.Exposed + (1 | greenhouse)      TRUE
##  cbind(crith_pos_b, crith_neg_b) ~ F.Exposed + (1 | greenhouse)      TRUE
##  cbind(crith_pos_b, crith_neg_b) ~ G.Exposed + (1 | greenhouse)      TRUE
##  cbind(crith_pos_b, crith_neg_b) ~ R.Exposed + (1 | greenhouse)      TRUE
##  cbind(crith_pos_b, crith_neg_b) ~ T.Exposed + (1 | greenhouse)      TRUE
##  cbind(crith_pos_b, crith_neg_b) ~ U.Exposed + (1 | greenhouse)      TRUE
##  cbind(crith_pos_b, crith_neg_b) ~ V.Exposed + (1 | greenhouse)      TRUE
##  cbind(crith_pos_b, crith_neg_b) ~ W.Exposed + (1 | greenhouse)      TRUE
##  cbind(crith_pos_b, crith_neg_b) ~ I.Exposed + (1 | greenhouse)      TRUE
##  cbind(crith_pos_b, crith_neg_b) ~ B.Exposed + (1 | greenhouse)      TRUE
##  cbind(crith_pos_b, crith_neg_b) ~ K.Exposed + (1 | greenhouse)      TRUE
##  cbind(crith_pos_b, crith_neg_b) ~ P.Exposed + (1 | greenhouse)      TRUE
##  cbind(crith_pos_b, crith_neg_b) ~ M.Exposed + (1 | greenhouse)      TRUE
##  cbind(crith_pos_b, crith_neg_b) ~ O.Exposed + (1 | greenhouse)      TRUE
##  cbind(crith_pos_b, crith_neg_b) ~ Q.Exposed + (1 | greenhouse)      TRUE
##  cbind(crith_pos_b, crith_neg_b) ~ S.Exposed + (1 | greenhouse)      TRUE
##  cbind(crith_pos_b, crith_neg_b) ~ L.Exposed + (1 | greenhouse)      TRUE
##       z   p_value p_FDR_BH
##  -3.584 0.0003388 0.006437
##   2.493 0.0126591 0.045268
##  -2.260 0.0238242 0.045268
##  -2.493 0.0126593 0.045268
##  -2.260 0.0238242 0.045268
##   2.260 0.0238251 0.045268
##   2.260 0.0238251 0.045268
##   2.260 0.0238251 0.045268
##   2.260 0.0238251 0.045268
##   2.260 0.0238251 0.045268
##   1.995 0.0460126 0.079476
##  -1.589 0.1119932 0.151992
##  -1.589 0.1119932 0.151992
##   1.589 0.1119943 0.151992
##  -1.447 0.1478607 0.156075
##  -1.447 0.1478607 0.156075
##   1.447 0.1478570 0.156075
##   1.515 0.1298004 0.156075
##  -1.314 0.1889202 0.188920

###(2) does the amount of a particular chemical correlate with parasite infection

results table for wax resdiue analysis

##          term      estimate           SE           OR        LCL        UCL
## 1      A.Bin2   0.768486730    0.6140065 2.156500e+00 0.64730096  7.1844387
## 2  A.Bin3plus  -0.862659339    0.3030477 4.220382e-01 0.23302210  0.7643751
## 3  B.Bin3plus  -0.080406966    0.3578340 9.227407e-01 0.45760509  1.8606666
## 4      C.Bin2  -0.437641666    0.4728288 6.455571e-01 0.25554186  1.6308245
## 5  C.Bin3plus  -0.066547642    0.4623342 9.356183e-01 0.37805865  2.3154653
## 6      D.Bin2   0.004969945    0.3403944 1.004982e+00 0.51572021  1.9584058
## 7  D.Bin3plus  -0.618066887    0.5008634 5.389854e-01 0.20194881  1.4385091
## 8  E.Bin3plus  -0.654744442    0.3538430 5.195748e-01 0.25969070  1.0395366
## 9      F.Bin2 -16.035091063 2728.0220779 1.086547e-07 0.00000000        Inf
## 10 F.Bin3plus   1.565496290    0.5614872 4.785049e+00 1.59201673 14.3821950
## 11     G.Bin2  -0.864985110    0.3186166 4.210578e-01 0.22549388  0.7862284
## 12 G.Bin3plus  -0.917229547    0.4815075 3.996247e-01 0.15552219  1.0268622
## 13     H.Bin2  -0.205507406    0.2753976 8.142341e-01 0.47460296  1.3969089
## 14 H.Bin3plus  -0.050599015    0.4804603 9.506598e-01 0.37072900  2.4377754
## 15 I.Bin3plus   0.163489131    0.4110619 1.177613e+00 0.52614552  2.6357182
## 16     J.Bin2  -0.526628039    0.3154905 5.905931e-01 0.31823093  1.0960600
## 17 J.Bin3plus  -0.428832678    0.4414473 6.512689e-01 0.27415724  1.5471091
## 18     K.Bin2  -1.101065323    0.3770600 3.325167e-01 0.15880325  0.6962535
## 19 L.Bin3plus  -0.809241100    0.7137388 4.451958e-01 0.10990451  1.8033772
## 20 M.Bin3plus  -0.760255741    0.5118124 4.675468e-01 0.17146269  1.2749132
## 21     O.Bin2  -0.697040334    0.3781065 4.980572e-01 0.23737467  1.0450187
## 22 O.Bin3plus -19.748164865  512.0000022 2.651435e-09 0.00000000        Inf
## 23     P.Bin2  -0.951467396    0.4530515 3.861739e-01 0.15890765  0.9384715
## 24 P.Bin3plus  18.838708412 4591.4806745 1.518963e+08 0.00000000        Inf
## 25 Q.Bin3plus   0.655996556    0.4168751 1.927062e+00 0.85123784  4.3625503
## 26     S.Bin2  -0.562480028    0.4889873 5.697942e-01 0.21852006  1.4857466
## 27 S.Bin3plus  -1.363875312    0.5812479 2.556681e-01 0.08183091  0.7987954
##    chemical                               stage
## 1         A Stage2_crith_Bin_0_1_2_3plus_vs_0-1
## 2         A Stage2_crith_Bin_0_1_2_3plus_vs_0-1
## 3         B Stage2_crith_Bin_0_1_2_3plus_vs_0-1
## 4         C Stage2_crith_Bin_0_1_2_3plus_vs_0-1
## 5         C Stage2_crith_Bin_0_1_2_3plus_vs_0-1
## 6         D Stage2_crith_Bin_0_1_2_3plus_vs_0-1
## 7         D Stage2_crith_Bin_0_1_2_3plus_vs_0-1
## 8         E   Stage2_crith_Bin_0_1_2_3plus_vs_2
## 9         F Stage2_crith_Bin_0_1_2_3plus_vs_0-1
## 10        F Stage2_crith_Bin_0_1_2_3plus_vs_0-1
## 11        G Stage2_crith_Bin_0_1_2_3plus_vs_0-1
## 12        G Stage2_crith_Bin_0_1_2_3plus_vs_0-1
## 13        H Stage2_crith_Bin_0_1_2_3plus_vs_0-1
## 14        H Stage2_crith_Bin_0_1_2_3plus_vs_0-1
## 15        I Stage2_crith_Bin_0_1_2_3plus_vs_0-1
## 16        J Stage2_crith_Bin_0_1_2_3plus_vs_0-1
## 17        J Stage2_crith_Bin_0_1_2_3plus_vs_0-1
## 18        K Stage2_crith_Bin_0_1_2_3plus_vs_0-1
## 19        L Stage2_crith_Bin_0_1_2_3plus_vs_0-1
## 20        M   Stage2_crith_Bin_0_1_2_3plus_vs_2
## 21        O Stage2_crith_Bin_0_1_2_3plus_vs_0-1
## 22        O Stage2_crith_Bin_0_1_2_3plus_vs_0-1
## 23        P Stage2_crith_Bin_0_1_2_3plus_vs_0-1
## 24        P Stage2_crith_Bin_0_1_2_3plus_vs_0-1
## 25        Q Stage2_crith_Bin_0_1_2_3plus_vs_0-1
## 26        S Stage2_crith_Bin_0_1_2_3plus_vs_0-1
## 27        S Stage2_crith_Bin_0_1_2_3plus_vs_0-1
##                                                              formula reference
## 1  cbind(crith_pos_b, crith_neg_b) ~ BinCollapsed + (1 | greenhouse)       0-1
## 2  cbind(crith_pos_b, crith_neg_b) ~ BinCollapsed + (1 | greenhouse)       0-1
## 3  cbind(crith_pos_b, crith_neg_b) ~ BinCollapsed + (1 | greenhouse)       0-1
## 4  cbind(crith_pos_b, crith_neg_b) ~ BinCollapsed + (1 | greenhouse)       0-1
## 5  cbind(crith_pos_b, crith_neg_b) ~ BinCollapsed + (1 | greenhouse)       0-1
## 6  cbind(crith_pos_b, crith_neg_b) ~ BinCollapsed + (1 | greenhouse)       0-1
## 7  cbind(crith_pos_b, crith_neg_b) ~ BinCollapsed + (1 | greenhouse)       0-1
## 8  cbind(crith_pos_b, crith_neg_b) ~ BinCollapsed + (1 | greenhouse)         2
## 9  cbind(crith_pos_b, crith_neg_b) ~ BinCollapsed + (1 | greenhouse)       0-1
## 10 cbind(crith_pos_b, crith_neg_b) ~ BinCollapsed + (1 | greenhouse)       0-1
## 11 cbind(crith_pos_b, crith_neg_b) ~ BinCollapsed + (1 | greenhouse)       0-1
## 12 cbind(crith_pos_b, crith_neg_b) ~ BinCollapsed + (1 | greenhouse)       0-1
## 13 cbind(crith_pos_b, crith_neg_b) ~ BinCollapsed + (1 | greenhouse)       0-1
## 14 cbind(crith_pos_b, crith_neg_b) ~ BinCollapsed + (1 | greenhouse)       0-1
## 15 cbind(crith_pos_b, crith_neg_b) ~ BinCollapsed + (1 | greenhouse)       0-1
## 16 cbind(crith_pos_b, crith_neg_b) ~ BinCollapsed + (1 | greenhouse)       0-1
## 17 cbind(crith_pos_b, crith_neg_b) ~ BinCollapsed + (1 | greenhouse)       0-1
## 18 cbind(crith_pos_b, crith_neg_b) ~ BinCollapsed + (1 | greenhouse)       0-1
## 19 cbind(crith_pos_b, crith_neg_b) ~ BinCollapsed + (1 | greenhouse)       0-1
## 20 cbind(crith_pos_b, crith_neg_b) ~ BinCollapsed + (1 | greenhouse)         2
## 21 cbind(crith_pos_b, crith_neg_b) ~ BinCollapsed + (1 | greenhouse)       0-1
## 22 cbind(crith_pos_b, crith_neg_b) ~ BinCollapsed + (1 | greenhouse)       0-1
## 23 cbind(crith_pos_b, crith_neg_b) ~ BinCollapsed + (1 | greenhouse)       0-1
## 24 cbind(crith_pos_b, crith_neg_b) ~ BinCollapsed + (1 | greenhouse)       0-1
## 25 cbind(crith_pos_b, crith_neg_b) ~ BinCollapsed + (1 | greenhouse)       0-1
## 26 cbind(crith_pos_b, crith_neg_b) ~ BinCollapsed + (1 | greenhouse)       0-1
## 27 cbind(crith_pos_b, crith_neg_b) ~ BinCollapsed + (1 | greenhouse)       0-1
##               z     p_value converged   p_FDR_BH
## 1   1.251593762 0.210717929      TRUE 0.41888915
## 2  -2.846612115 0.004418717      TRUE 0.04476119
## 3  -0.224704658 0.822209041      TRUE 0.99672631
## 4  -0.925581715 0.354663399      TRUE 0.53199510
## 5  -0.143938407 0.885549107      TRUE 0.99672631
## 6   0.014600547 0.988350863      TRUE 0.99672631
## 7  -1.234003011 0.217201782      TRUE 0.41888915
## 8  -1.850381280 0.064258615      TRUE 0.19576701
## 9  -0.005877918 0.995310127     FALSE 0.99672631
## 10  2.788124619 0.005301415     FALSE 0.04476119
## 11 -2.714814662 0.006631287      TRUE 0.04476119
## 12 -1.904912438 0.056791454      TRUE 0.19576701
## 13 -0.746220883 0.455533995      TRUE 0.64733778
## 14 -0.105313617 0.916126959      TRUE 0.99672631
## 15  0.397723843 0.690833760      TRUE 0.93262558
## 16 -1.669236025 0.095070613      TRUE 0.25669066
## 17 -0.971424421 0.331336972      TRUE 0.52624107
## 18 -2.920133302 0.003498817      TRUE 0.04476119
## 19 -1.133805748 0.256876039      TRUE 0.43347832
## 20 -1.485418816 0.137432914      TRUE 0.30922406
## 21 -1.843502559 0.065255668     FALSE 0.19576701
## 22 -0.038570634 0.969232715     FALSE 0.99672631
## 23 -2.100130716 0.035717344     FALSE 0.16072805
## 24  0.004102970 0.996726313     FALSE 0.99672631
## 25  1.573604396 0.115578936      TRUE 0.28369375
## 26 -1.150295852 0.250022039      TRUE 0.43347832
## 27 -2.346460662 0.018952667      TRUE 0.10234440

Key to letters desingated to each chemical compound

Pesticide names and corresponding letters used in analyses

Compound	Letter
Chlorantraniliprole	A
chlorfenapyr	B
difenoconazole	C
fluopyram	D
hexythiazox	E
myclobutanil	F
Propamocarb	G
Pyraclostrobin	H
Pyrimethanil	I
Pyriproxyfen	J
Spirotetramat	K
azoxystrobin	L
bifenazate	M
diphenylamine	N
Fenpyroximate	O
boscalid	P
chlozolinate	Q
flonicamid	R
Picoxystrobin	S
spinetoram	T
Spinosyn A	U
Spinosyn D	V
trifloxystrobin	W

##  BinCollapsed  prob    SE  df asymp.LCL asymp.UCL
##  0-1          0.456 0.149 Inf    0.2050     0.732
##  2            0.218 0.118 Inf    0.0674     0.519
## 
## Confidence level used: 0.95 
## Intervals are back-transformed from the logit scale

##  contrast  odds.ratio   SE  df null z.ratio p.value
##  (0-1) / 2       3.01 1.13 Inf    1   2.920  0.0035
## 
## Tests are performed on the log odds ratio scale

##  BinCollapsed  prob    SE  df asymp.LCL asymp.UCL .group
##  2            0.218 0.118 Inf    0.0674     0.519  a    
##  0-1          0.456 0.149 Inf    0.2050     0.732   b   
## 
## Confidence level used: 0.95 
## Intervals are back-transformed from the logit scale 
## Tests are performed on the log odds ratio scale 
## significance level used: alpha = 0.05 
## NOTE: If two or more means share the same grouping symbol,
##       then we cannot show them to be different.
##       But we also did not show them to be the same.

code format for figure 4