Pan trap and plant-flower visitor observation data for: Multi-species crop mixtures increase insect biodiversity in an intercropping experiment

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 ..., The study was conducted as part of an intercropping trial near Münster, Germany, in 2019.Flower visitor observations: 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.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.on 02.07.2019 (Block 1), on 03.07.2019 (Block 2), on 03.+04.07.2019 (Block 3),on 09.+10.07.2019 (Block 4),AND on 10.07.2019 (Block 1 second time)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)Pan traps: yellow pan traps were placed at 4 time points o..., 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 -> 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 usedCopyright (C) 2021 The R Foundation for Statistical Computing, Platform: x86_64-w64-mingw32/x64 (64-bit)) and RStudio (version RStudio 2021.09.2+382 \"Ghost Orchid\" Release (fc9e217980ee9320126e33cdf334d4f4e105dc4f, 2022-01-04) for WindowsMozilla/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 runni...

当前全球生物多样性持续衰退，亟需在农业等多个领域开展应对行动。其中，节肢动物（arthropods）作为物种多样性极高的类群，能够提供诸多关键生态系统服务，其生存现状尤为严峻。
为缓解农业集约化带来的负面影响，通过种植作物混播群落构建更为友好的农业生境“基质”，可在保障作物产量不受损的前提下，减轻对节肢动物的危害。
尽管草地生物多样性实验已证实植物多样性对节肢动物具有积极调控作用，但目前仍缺乏通过同时调控作物多样性与农用化学品投入水平，来探究节肢动物响应的田间试验。
本研究通过田间试验，设置了三类调控变量：作物多样性（1~3个物种+休耕地）、作物物种类型（小麦（wheat）、蚕豆（faba bean）、亚麻籽（linseed）、油菜（oilseed rape））以及农用化学品投入水平（高、低两组），并系统探究了节肢动物生物多样性的响应模式。我们验证了节肢动物的响应是否受作物多样性、混播群落结构及田间管理措施的影响，同时还测定了作物生物量。
高投入条件下，作物生物量随多样性提升而增加……本研究于2019年在德国明斯特（Münster）附近的间作试验平台开展。
花访客观测：本试验针对小麦、蚕豆、亚麻籽的单作群落及其2、3物种混播群落开展观测，处理组合包括Ty（小麦）、Fu（蚕豆）、Bi（亚麻籽）、TyFu、TyBi、FuBi、TyFuBi以及无作物对照组。其中Ty为小麦品种“提博尔特（Tybalt）”，Fu为蚕豆品种“福艾戈（Fuego）”，Bi为亚麻籽品种“宾果（Bingo）”。本试验共设置8种作物组合×2种处理（高、低投入）×4次重复，总计64个样地。
观测时间分别为2019年7月2日（样地块1）、2019年7月3日（样地块2）、2019年7月3-4日（样地块3）、2019年7月9-10日（样地块4），以及2019年7月10日（样地块1二次观测）。
每个样地选取1平方米区域进行15分钟的观测，所有接触花器官的昆虫均记为1次访花事件，同时记录各物种的花盖度及开花植株数量。传粉昆虫将尽可能鉴定到物种水平，若无法完成物种鉴定，则记录至更高分类阶元（科或目）。
黄色盘诱捕器（pan traps）试验：黄色盘诱虫碗于4个时间点放置于样地中……
所有统计分析均采用开源软件R（R）完成。为便于操作，可使用RStudio（RStudio）等集成开发环境（非强制要求）。R与RStudio均为开源软件，可适配所有主流操作系统。可从https://posit.co/downloads/下载R并按照指引完成安装：打开RStudio后，通过「文件>打开文件」路径加载R脚本文件（*.R）；使用R中的read.table()命令读取*.txt格式数据集；点击左上角面板的「运行当前行或选区」按钮即可执行R命令。本研究采用的R版本为4.1.2（2021-11-01 —— "Bird Hippie"），版权归2021年统计计算R基金会所有，运行平台为x86_64-w64-mingw32/x64（64位）；同时采用的RStudio版本为2021.09.2+382 "Ghost Orchid" Release（fc9e217980ee9320126e33cdf334d4f4e105dc4f, 2022-01-04），适配Windows系统。在运行分析前……