DOI: 10.5061/dryad.6djh9w18f
title: Nocturnal insect communities altered by land-use change contribute little to coffee pollination in the Western Ghats, India

description: Wild insects pollinate numerous agricultural crops, but the role of
 nocturnal pollinators, while increasingly acknowledged, remains poorly
 understood. We examined nocturnal insect communities and pollination in
 agroforests of robusta coffee (Coffea canephora) – a crop that exhibits
 floral traits suggestive of nocturnal pollination – in India’s Western
 Ghats mountains. Specifically, we (1) compared nocturnal insect
 communities of a shaded robusta coffee agroforest and a nearby secondary
 tropical rainforest using light screens, and (2) assessed nocturnal and
 diurnal pollination of coffee using floral exclosure experiments in the
 agroforest and in a former coffee agroforest located within the secondary
 rainforest. Nocturnal pollinators visiting light screens were 21% fewer in
 the agroforest than the rainforest, mainly due to reduced numbers of
 Lepidoptera, Coleoptera, and Diptera in the former. Lepidoptera and
 Coleoptera differed in genus richness and composition between habitats,
 with the agroforest having fewer Lepidoptera and more Coleoptera genera
 than the rainforest. Coffee pollination success was largely attributable
 to diurnal pollinators in both the agroforest and rainforest. While
 nocturnal pollination effects were absent in the agroforest, we found some
 evidence of nocturnal pollination in the secondary rainforest, where
 coffee flowers accessible to diurnal and nocturnal pollinators had higher
 pollination success (60%) than flowers accessible to diurnal pollinators
 alone (46%). In summary, the nocturnal insect community of coffee
 agroforestry, which is distinct from the rainforest community, contributes
 little to coffee pollination. However, a greater contribution of nocturnal
 pollination under less intensive coffee cultivation is a possibility that
 warrants further exploration.
description: <strong>Study site:</strong> <br> This study
 was conducted at a robusta coffee farm and a secondary tropical rainforest
 in the Sakleshpur Taluk, Karnataka State, located in the Western Ghats
 biodiversity hotspot, southern India. 
 <strong>Insect sampling:</strong><br> Nocturnal
 insects were sampled using light screens, which comprised a vertical white
 3.24 m<sup>2</sup> square screen illuminated by four
 ultraviolet LEDs, two blue LEDs, and one green and white LED (Fig. 1a),
 following Brehm (2017). Light screens were set up at dusk (1800 h) and
 nocturnal insects were inventoried between 2330 and 0130 h. The timing of
 data collection was determined based on a pilot study in the rainforest
 comprising 12 screens monitored hourly from 1830 to 0630 h, in which
 insect accumulation was observed to peak during 2330–0130 h. We compared
 the nocturnal flying insect communities of the robusta coffee agroforest
 and secondary tropical rainforest during March–April 2022.  
 <strong>Pollinator exclusion
 experiments:</strong><br> The experiment comprised the
 following treatments: (1) complete insect exclusion (Negative control),
 (2) pollinator exclusion by day (0630–1830h) and open at night
 (1830–0630h; Night - accessible), (3) pollination exclusion by night and
 open in the day (Day - accessible), and (4) no exclusion (Positive
 control).  <strong>Statistical
 analysis:</strong> <br> All data analyses and visualizations
 were performed using R version 4.2.2 (R Core Team, 2022). We compared
 light screen encounter rates of nocturnal pollinators between the
 agroforest and rainforest using generalized linear models (GLM) from the R
 package MASS (Ripley et al., 2023). We compared
 Lepidoptera and Coleoptera taxonomic diversity at the genus level between
 coffee agroforest and rainforest, standardized for coverage, using the R
 package iNEXT (Chao et al., 2014; T. C. Hsieh et al., 2022).
 We used Non-Metric Dimensional Scaling (NMDS) to visually
 represent the dissimilarity of Lepidoptera and Coleoptera genus-level
 composition between agroforest and rainforest habitats. We performed a
 three-dimensional ordination based on the Bray-Curtis dissimilarity index
 using the metaMDS function in the ‘vegan’ R package (Oksanen et al.,
 2022). For the pollination exclusion experiments, we
 used generalized linear mixed-effects models (GLMM) with a binomial error
 distribution to compare pollination success (a binary variable) across the
 different exclusion treatments and controls. We ran separate models for
 the 2022 experiment in the coffee agroforest and the 2023 one in abandoned
 coffee bushes within the rainforest. Each model comprised the exclusion
 treatments and controls as fixed effects and bush ID as a random effect.
 GLMMs were run using the ‘lme4’ R package (Bates et al., 2015).
description: # Nocturnal insect communities altered by land-use change contribute
 little to coffee pollination in the Western Ghats, India
 [https://doi.org/10.5061/dryad.6djh9w18f](https://doi.org/10.5061/dryad.6djh9w18f) This dataset contains data and codes for measuring the abundance, diversity and composition of nocturnal insects in coffee plantations and tropical secondary rainforest. It also contains data on pollination experiment and codes to investigate the effect of nocturnal insects in pollinating coffee in actively managed (coffee agroforestry) and abandoned coffee plantations (now secondary rainforest). Kindly refer the following publication for details [https://doi.org/10.1016/j.agee.2025.109966 ](https://doi.org/10.1016/j.agee.2025.109966 "Persistent link using digital object identifier") ## Description of the data and file structure Data, codes and their file structure **order_abundance.csv** contains insect counts (number of individual) of corresponding insect order that were sampled using light screen in two vegetation types (coffee agroforestry and rainforest) from the study region. This data was analysed using generalised linear model using the code '*Abundance_orderwise.R*'   Each row in the dataset represents insect counts from individual light traps, categorized by insect order. *Variables (Columns)* : * date: This refers to the starting date of the insect observation. Since observations began at 18:00 hrs and continued until 01:00 hrs the following day, the recorded date corresponds to the evening when the observation commenced. * vegetation_type: Indicates the type of vegetation in which the insect observation was conducted. * trapid: Unique id provided to each light screen * Trap: On each observation date, two light traps were deployed. Trap A refers to the first trap that was set up, followed by Trap B, which was established 15 minutes later. The observation also followed the same sequence. * order: Corresponding insect order that was observed. Four focal insect orders were Hymenoptera, Coleoptera, Lepidoptera  and Diptera. * Count: The number of individual insects recorded belonging to corresponding insect order on a specific light screen during the observation. **lepidf.csv** and **beetledf.csv** contain data frames of insect abundance, with insect genera as columns and observational sites (stations) as rows. The files represent observations from the insect orders Lepidoptera and Coleoptera, respectively. This data was used to measure the community composition (using Non-metric dimensional scaling) of the insects.This dataset was analysed using codes '*NMDS_Lepidoptera.R*' and '*NMDS_Coleoptera.R*'.  *Variables:*  * Station: Unique id for the sites\ * v_type : The vegetation type of the corresponding station. \ The remaining columns have genera names (as column names)  and respective individual counts from corresponding sites.    **sites.csv** provide site : vegetation type mapping which was used in NMDS analysis '*NMDS_Lepidoptera.R*' and '*NMDS_Coleoptera.R*'. *Variables:* * trap: station id (Unique id for the sites)\ * site: vegetation type **pollination_experiment.csv** are the datasets used to run the Generalised linear mixed models to estimate the pollination success of nocturnal insect using the codes '*pollination_success.R*'.\ Each row in the dataset contains pollen tube data from a single style of the coffee flower, which was collected and examined under a microscope.  \ *Variables:* \ * date: The date of examination under microscope. \ * specimen_id: A unique identity number assigned to each coffee plant that was included in the experiment.\ * lower_stylar: Number of pollen tubes observed in lower stylar region of the corresponding style. \ * treatment_name: Corresponding treatment type of the style. \ * habitat: type of the habitat (coffee agroforest or secondary rainforest)\ * remarks: This field contains information about styles that were damaged during collection or processing and subsequently discarded from analysis. All data analyses and visualizations were performed using R version 4.2.2 [(R Core Team 2022)](https://www.zotero.org/google-docs/?tWGujK)