Appendix A

Pesticides and land cover heterogeneity affect functional group and taxonomic diversity of arthropods in rice agroecosystems

Agriculture, Ecosystems & Environment

Cornelia Sattler, Andros T. Gianuca, Oliver Schweiger, Markus Franzén, Josef Settele

Corresponding author: Cornelia Sattler

Cornelia.Sattler@ufz.de

UFZ - Helmholtz Centre for Environmental Research,

Department of Community Ecology,

Theodor-Lieser-Straße 4,

D-06120 Halle, Germany

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Table A.1

Field size (m²), land cover types (in %), and land cover heterogeneity (Shannon index, H’) for each rice field (R1-R10) in Hai Duong (VN1) and Vinh Phuc (VN2) within a 300 m radius. Field ID size bare soil forest fruit meadow/grassland rice vegetable water crops compacted surface sealed surface H’VN1 R2 652.07 0 0 0.15 1.47 96.31 1.32 0.74 0 0 0 0.202VN1 R3 637.27 0 0 3.78 7.6 70.63 2.05 2.87 0 7.38 5.7 1.102VN1 R4 283.96 0 4.57 8.88 10.58 47.73 3.07 19.89 0 3.87 1.41 1.561VN1 R5 1129.12 4.03 0 6.45 8.76 47.64 2.81 16.58 0 3.4 10.33 1.621VN1 R6 1883.9 5.76 0 5.63 3.16 67.87 0.94 10.65 0 1.57 4.42 1.184VN1 R7 760.84 4.68 0 0.84 4.39 75.55 4.23 2.22 0 5.51 2.56 1.005VN1 R8 197.66 0.14 0 8.81 2.39 50.86 0.4 2.46 0 32.59 2.35 1.223VN1 R9 589.27 1.79 0 23.29 4.56 42.06 3.62 1.9 0 17.15 5.63 1.576VN1 R10 511.94 1.95 0 18.67 2.97 56.98 1.26 0 0 15.62 2.55 1.254VN2 R1 97.7 1.13 9.69 24.56 4.53 42.54 3.99 0.46 0 11.61 1.48 1.591VN2 R2 394 0.17 15.75 13.51 17.94 29.27 3.66 0.24 0.41 14.9 4.15 1.814VN2 R3 185.77 0.27 3.52 19.55 9.59 47.24 11.16 0.29 0 8.26 0.13 1.508VN2 R4 166.98 0 9.48 19.94 8.65 39.45 6.18 2.84 5.05 7.94 0.46 1.774VN2 R5 202.76 0.07 22.24 51.86 8.18 7.69 2.88 0.81 0.27 5.82 0.19 1.416VN2 R6 404.3 0.33 31.95 35.39 10.12 7.86 2.59 5.97 0.27 5.37 0.15 1.628VN2 R7 583.13 0 1.85 6.53 1.77 60.31 2.21 5.19 12.82 8.59 0.72 1.376VN2 R8 158.16 1.19 0 29.47 7.09 43.12 0.21 4.05 0 11.92 2.95 1.464VN2 R9 130.83 0 0.95 16.94 8.87 55.78 0 4.99 0 10.1 2.38 1.355VN2 R10 407.66 1.86 1.99 21.96 12.94 33.09 1.97 11.05 1.75 9.22 4.17 1.859

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Table A.2

Ecosystem types included in the respective land cover type. Land cover types were recorded within a 300 m radius around each rice field. Land cover types are according to Burkhard et al. (2015).

No. Land cover types Ecosystem types included

1 bare soil bare rock, sand etc.

2 forest principally trees, also shrubs, bushes and storey

3 fruit fruit trees, banana plantations, coconut trees, etc.

4 meadow/grassland grass cover mainly for grazing

5 rice permanently irrigated rice fields

6 vegetable potato, eggplant, pepper, pumpkin etc. plantations

7 water lakes, rivers, and ponds

8 crops agricultural areas not covered by types 1-6

9 compacted surface unpaved roads, compacted soil surface

10 sealed surface houses and other buildings, streets, etc.

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Table A.3

Assigned taxa into functional groups. Total numbers of specimens sampled using blow vac (BV) and sweep net (SN) in both study regions (Hai Duong and Vinh Phuc). Not all specimens were identified to the lowest taxon shown here and therefore some orders were listed with specimens even if there are families or species within this group identified and listed.

  Hai Duong Vinh Phuc

Functional groups/Taxa BV SN BV SN

Decomposer (detritivore/scavenger) 2847 26887 6462 96466

Coleoptera

Anthicidae 1

Collembola 1411 317 781 47

Diplopoda 1

Diptera

Nematocera 1435 26570 5681 96418

Fungivore 3 4 16 35

Coleoptera

Corylophidae 3 4 1 26

Mycetophagidae 15 9

Herbivore 398 3255 1122 14922

Coleoptera

Chrysomelidae 19 109 37 233

Curculionidae 3 21 14 85

Elateridae 1 2 5

Diptera

Brachycera

Chloropidae 47 336 40 595

Anatrichus erinaceus 14 191 28 512

Psilidae

Ephydridae 62 286 390 2019

Muscidae 10

Tephritidae 21 42 45 167

Hemiptera

Delphacidae 54 676 141 2047

Nilaparvata Iugens 1 46 8 61

Sogatella furcifera 8 304 68 1039

Meenoplidae 2 9 9 16

Cicadellidae 15 86 49 483

Cicadulina bipunctata 2 10

Empoascanara spec. 12 205

Hecalus spec. 1

Nephotettix spec. 2 20 20 208

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Recilia dorsalis 3 6 9

Coreidae 1 7 4 32

Lygaeidae 3

Miridae 5 26 2 11

Tingidae 1

Pentatomidae 15 81 3 68

Eysarcoris ventralis 1

Nezara spec. 6

Aleyrodidae 1 29 1 2

Aphididae 50 109 23 127

Hymenoptera

Apocrita

Apidae

Apis cerana 1

Halictidae 1 2 2

Symphyta 1 1 8

Isoptera

Lepidoptera 20 121 22 239

Orthoptera

Acrididae 4 55 19 396

Pyrgomorphidae 18

Tetrigidae 15 2 42

Phasmatodea 1 2

Psocoptera 1 21 2 84

Thysanoptera 52 648 173 6181

Parasitoid 182 2059 192 2287

Diptera

Brachycera

Tachinidae 20 180 5 117

Phoridae 23 207 10 219

Sciomyzidae

Sepedon spec. 58 1003 27 435

Hymenoptera

Ceraphronoidea

Ceraphronidae 16 3 40

Megaspilidae 1 5 1

Chalcidoidea

Aphelinidae 2 43 2 162

Chalcididae 4 6

Elasminae 1 1

Encyrtidae 44 6 82

Eulophidae 6 57 27 377

Eurytomidae 2 2 18

Mymaridae 34 154 33 62

Pteromalidae 1 15 5 34

Trichogrammatidae 1 6 3 5

Chrysidoidea

Bethylidae 5

Dryinidae 5 1 10

Cynipoidea

Figitidae 5 20 1 48

Evanioidea

Evaniidae 4 2

Ichneumonoidea

Braconidae 10 127 22 312

Ichneumonidae 5 16 9 128

Platygastroidea

Platygastridae 2 4

Scelionidae 12 118 27 182

Baeus spec. 3 2

Macroteleia spec. 1

Proctotrupoidea

Diapriidae 4 22 9 38

Proctotrupidae 1

Predator 576 2414 1239 3092

Araneae 158 327 54 48

Araneidae 29 566 47 416

Tetragnathidae

Tetragnatha spec. 9 93 15 325

Lycosidae 11 8 75 13

Oxyopidae 1 7 3 77

Salticidae 4 14 10 76

Thomisidae 3 9

Clubionidae 26 29 59 44

Coleoptera

Carabidae 13 17 36 61

Dytiscidae 1 2 2 6

Coccinellidae 1 14 2 15

Staphylinidae 135 307 118 198

Dermaptera 1

Diptera

Brachycera

Dolichopodidae 53 558 119 952

Hybotidae 2 1 8 182

Ephydridae

Ochthera sauteri 9 287 13 315

Syrphidae 5 8

Heteroptera

Corixidae 6 11

Gerridae

Limnogonus spec. 1 12

Veliidae

Microvelia spec. 73 3 631 1

Geocoridae 1

Miridae

Cyrtorhinus lividipennis 1 7 16

Reduviidae 6

Saldidae 11

Hymenoptera

Apocrita

Crabronidae 1 2

Vespoidae

Formicidae 7 52 7 79

Vespidae 1

Mesostigmata

Gamasina 33 31

Neuroptera 1

Odonata 3 81 8 214

Orthoptera

Gryllidae 6 1 17

Indifferent 46 103 3 61

Coleoptera 3 6 1 2

Diptera 33 5 1

Brachycera 7 82 3

Stratiomyidae 5

Tabanidae 6 4

Ephemeroptera 3 3 9

Orthoptera

Tettigoniidae 1 2 3733

Table A.4

Global models of functional group diversity. The global models include all predictor variable a priory considered before selection of candidate models. Each model is separated by blow vac (BV) and sweep net (SN) as well as sampling days (35 and 50 days after transplanting). Global models show the estimate, standard error (SE), t-value and p-value of the intercept and predictor variables for each model.

Model Predictor Variables Estimate SE t value p valueIntercept 2.236222 0.19893 11.241 0.09329

BV 35 Land cover heterogeneity -0.00236 0.10124 -0.02300 0.98168Number of pesticide applications -0.30479 0.09595 -3.177 0.00587Intercept 2.8894 0.17540 16.477 8.75e-07

BV 50 Land cover heterogeneity -0.10930 0.13890 -0.78700 0.44300Number of pesticide applications -0.29370 0.16780 -1.751 0.10800Intercept 1.99444 0.09088 21.946 0.00000

SN 35 Land cover heterogeneity 0.20246 0.09376 2.159 0.04672Number of pesticide applications -0.32767 0.09405 -3.484 0.00859Intercept 2.6543 0.28690 9.251 0.10900

SN 50 Land cover heterogeneity -0.21620 0.13510 -1.600 0.13000Number of pesticide applications -0.13020 0.13180 -0.98800 0.33900

Table A.5

Global models of taxonomic diversity. The global models include all predictor variable a priory considered before selection of candidate models. Each model is separated by blow vac (BV) and sweep net (SN) as well as sampling days (35 and 50 days after transplanting). Global models show the estimate, standard error (SE), t-value and p-value of the intercept and predictor variables for each model.

Model Predictor Variables Estimate SE t-value p-valueIntercept 4.52775 0.65979 6.862 0.1768

BV 35 Land cover heterogeneity 0.08397 0.42654 0.197 0.8468  Number of pesticide applications -1.06945 0.38819 -2.755 0.0177

Intercept 6.4703 0.6295 10.278 3.48e-08BV 50 Land cover heterogeneity 0.4460 0.6816 0.654 0.5228  Number of pesticide applications -1.6866 0.6816 -2.474 0.0258

Intercept 3.1267 0.3232 9.676 0.00001SN 35 Land cover heterogeneity 0.5628 0.3152 1.786 0.0949  Number of pesticide applications -0.9100 0.2913 -3.124 0.0081

Intercept 4.5940 1.1646 3.945 0.1682SN 50 Land cover heterogeneity 0.2158 0.3090 0.698 0.5059  Number of pesticide applications -0.5169 0.2142 -2.414 0.0552

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Figure A.1

Non-significant relationship between functional group diversity (a-c) and taxonomic diversity (d-f) with land cover heterogeneity for blow vac (BV) and for sweep net data (SN) at 35 and 50 days after transplanting. Alpha diversity is based on the exponential Shannon entropy and expressed as effective numbers of functional groups. Pesticides were measured as number of pesticide applications. Land cover heterogeneity is based on Shannon index (H’).

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Table A.6

Global Model of functional group diversity. The global models include insecticide applications and land cover heterogeneity as predictor variable. Each model is separated by blow vac (BV) and sweep net (SN) as well as sampling days (35 and 50 days after transplanting). Global models show the estimate, standard error (SE), t-value and p-value of the intercept and predictor variables for each model.Model Predictor Variables Estimate SE t-value p-value

Intercept 2.2477 0.1298 17.323 1.14e-07BV 35 Land cover heterogeneity 0.1394 0.1045 1.334 0.2009 Number of insecticide applications -0.2141 0.1114 -1.922 0.0726

Intercept 2.8821 0.2038 14.140 8.82e-07BV 50 Land cover heterogeneity -0.0312 0.1469 -0.212 0.835 Number of insecticide applications -0.2315 0.1568 -1.476 0.16

Intercept 1.9976 0.1505 13.273 7.50e-07SN 35 Land cover heterogeneity 0.2578 0.1132 2.278 0.037 Number of insecticide applications -0.1375 0.1208 -1.138 0.272

Intercept 2.6543 0.351 7.561 0.0965SN 50 Land cover heterogeneity -0.1527 0.1391 -1.098 0.2899 Number of insecticide applications -0.1205 0.1218 -0.989 0.3392

Table A.7

Global Model of taxonomic diversity. The global models include insecticide applications and land cover heterogeneity as predictor variable. Each model is separated by blow vac (BV) and sweep net (SN) as well as sampling days (35 and 50 days after transplanting). Global models show the estimate, standard error (SE), t-value and p-value of the intercept and predictor variables for each model.

Model Predictor Variables Estimate SE t-value p-valueIntercept 4.5508 0.4333 10.502 1.38e-08

BV 35 Land cover heterogeneity 0.1021 0.4761 0.214 0.833  Number of insecticide applications -0.3103 0.4761 -0.652 0.524

Intercept 6.4703 0.7466 8.667 3.17e-07BV 50 Land cover heterogeneity 0.4460 0.797 -0.063 0.951

  Number of insecticide applications 0.1083 0.797 0.136 0.894Intercept 3.1324 0.3615 8.666 5.75e-05

SN 35 Land cover heterogeneity 0.3679 0.3936 0.935 0.366  Number of insecticide applications -0.3800 0.3934 -0.966 0.35

Intercept 4.59010 1.33117 3.448 0.198SN 50 Land cover heterogeneity 0.00463 0.40724 0.011 0.991

  Number of insecticide applications 0.27323 0.38981 0.701 0.495

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