DOI: 10.5061/dryad.f4qrfj71v
title: Pan trap and plant-flower visitor observation data for: Multi-species crop mixtures increase insect biodiversity in an intercropping experiment

description: Recent biodiversity declines require action across sectors such as
 agriculture. The situation is particularly acute for arthropods, a
 species-rich taxon providing important ecosystem services. To counteract
 negative consequences of agricultural intensification, creating a less
 hostile agricultural “matrix” through growing crop mixtures can reduce
 harm for arthropods without yield losses. While grassland biodiversity
 experiments showed positive plant biodiversity effects on arthropods,
 experiments manipulating crop diversity and agrochemical input use to
 study arthropods are lacking. Here, we experimentally manipulated crop
 diversity (1–3 species, fallows), crop species (wheat, faba bean, linseed,
 oilseed rape) and agrochemical input (high vs. low) and studied responses
 of arthropod biodiversity. We tested if arthropod responses were affected
 by crop diversity, mixtures and management. Additionally, we measured crop
 biomass. Crop biomass increased with crop diversity under high-input
 mangement, while under low management intensity, biomass was highest in
 two-species mixtures. Increasing crop diversity positively affected
 arthropod abundance and diversity, both under low- and high-input
 management. Crop mixtures containing faba bean, linseed or oilseed rape
 had particularly high arthropod diversity. Mass-flowering crops attracted
 more arthropods than legumes or cereals. Integrating intercropping into
 agricultural systems could increase flower visits by insects up to 15
 million per hectare, thus likely also supporting pollination and
 pest-control ecosystem services. Flower-visitor network complexity
 increased in mixtures containing linseed and faba bean, and under
 low-input management. Intercropping can counteract insect declines in
 farmland by creating beneficial matrix habitat without compromising crop
 yield.
description: The study was conducted as
 part of an intercropping trial near Münster, Germany, in
 2019.<br><br><strong>Flower visitor
 observations</strong>: observations were carried out on monocultures
 of wheat, bean, linseed and their 2- and 3-species mixtures:  Ty(wheat),
 Fu(faba bean), Bi(linseed), TyFu, TyBi, FuBi, TyFuBi and no
 crop.<br><br>Ty = Wheat variety "Tybalt"; Fu = Bean
 variety "Fuego"; Bi = Linseed variety "Bingo".= 8 crop
 mixtures x 2 treatments (high and low) x 4 replicates = 64 plots in
 total.<br><br>on 02.07.2019 (Block 1), <br>on 03.07.2019
 (Block 2), <br>on 03.+04.07.2019 (Block 3),<br>on
 09.+10.07.2019 (Block 4),<br>AND on 10.07.2019 (Block 1 second
 time)<br><br>1 m² of each plot was observed for 15 min, all
 contacts with floral organs were counted as one visit flower cover and
 number of flowering plants per plant species were recorded as well.
 Pollinators were identified as thoroughly as possible, if species
 identification was not possible, the higher level was used (family or
 order)<br><br><strong>Pan traps:</strong> yellow
 pan traps were placed at 4 time points on plots containing the following
 crop mixtures: Ty (wheat), Fu (faba bean), Bi (linseed), Ca (oilseed
 rape), TyFu, TyBi, TyCa, FuBi, FuCa, BiCa, TyFuBi, TyFuCa, nc
 (NoCrop).<br><br>Ty = Wheat variety "Tybalt"; Fu =
 Bean variety "Fuego"; Bi = Linseed variety "Bingo";
 Ca, Oilseed Rape Variety "Campino" = 13 crop mixtures x 2
 treatments (high and low) x 4 replicates = 104 traps per
 round.<br><br>round 1: 28.06.–01.07.2019<br>round 2:
 05.07.–08.07.2019<br>round 3: 12.07.–15.07.2019<br>round 4:
 23.07.–26.07.2019<br><br>Round 3 could not be used, because
 heavy rainfall flooded the trap.
description: All statistical analyses were done using the open-source software
 "R". For convenience, an editor such as RStudio can be used (but
 this is not necessary). R and RStudio are open-source
 softwares and are available for every common operating system. Download R
 from https://posit.co/downloads/ and
 follow the instructions given: open RStudio, and open R
 script (filename.R) via File -&gt; Open file load
 datasets (.txt) using the read.table() command in R R
 executes a command when pressing the button "Run current line or
 section" in the upper left panel.  R version 4.1.2 (2021-11-01) --
 "Bird Hippie" has been used<br clear="none">Copyright (C) 2021 The R Foundation for
 Statistical Computing, Platform: x86_64-w64-mingw32/x64 (64-bit)) <br clear="none">and RStudio (version RStudio 2021.09.2+382
 "Ghost Orchid" Release <br clear="none">(fc9e217980ee9320126e33cdf334d4f4e105dc4f,
 2022-01-04) for Windows<br clear="none">Mozilla/5.0
 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko)
 QtWebEngine/5.12.8 Chrome/69.0.3497.128 Safari/537.36)
 before running the provided code, install and load all required
 packages  <br clear="none">#
 install.packages("packagename") <br clear="none"># Example: <br clear="none">install.packages("bipartite")<br clear="none"># load packages<br clear="none"># Example: <br clear="none">library(bipartite)