DOI: 10.5061/dryad.k3j9kd5jc
title: Raw data and code for: Drivers of nocturnal and diurnal pollinating insect declines in urban landscapes

description: Insect pollinators are essential for the health and resilience of
 terrestrial ecosystems, delivering key ecosystem services in the face of
 anthropogenic disturbance. Urbanisation may be a key threat to pollinator
 diversity and abundance.  However, the scale of the threat
 remains unknown due to an overwhelming research emphasis on bees and a
 lack of comparative studies of hyper-diverse taxa such as nocturnal moths.
 Consequently, the question of which pollinator groups will be more
 affected by urbanisation remains unknown, and the habitat features that
 support key taxa remain controversial. We conducted the first large-scale
 assessment of the negative effects of increasing urbanisation on the
 diversity of bee, hoverfly and nocturnal moths across three cities. We
 report up to a 43\% reduction in species richness along replicated
 urbanisation gradients, suggesting that a wide range of pollinators are
 limited due to abiotic stresses and limited resources in urban
 environments. Landscape mapping indicated that these effects are driven by
 the reduction of tree cover and semi-natural habitat; however, the
 specific landscape drivers were taxon-specific, suggesting that urban
 insect conservation depends on the preservation or expansion of habitat
 features specific to different threatened taxa. In the first empirical
 comparison of three major pollinator taxa, we show that, relative to bees,
 moths and hoverflies are particularly sensitive to urbanisation, and we
 highlight the importance of including these frequently overlooked
 pollinator groups when assessing the biodiversity impacts of environmental
 change.
description: **Raw data and code for: Drivers of nocturnal and diurnal pollinating
 insect declines in urban landscapes** **Description of the data and file
 structure** This repository contains the data and code used to run all
 models featured in the manuscript. It includes 2 datasets. The R script
 conducts the full analysis as described in the manuscript. Including VIF
 examination, model selection, model fitting, and adjusting p-values: Data
 file:  Ellis_et_al_2025/final_data/1_raw_insect_data.csv * **Insect**:
 Taxonomic group of the observed insect (e.g., Bee). * **City**: City where
 the observation was recorded. * **Site**: Unique identifier for the site
 where data was collected. * **Species**: Scientific name of the observed
 species (e.g., *Apis mellifera*). * **Obs**: Count of individuals observed
 during the session. Ellis_et_al_2025/final_data/2_meta_data.csv *
 **MM_250m**: Area (in square meters) of man-made structures within a 250m
 buffer zone. * **Garden_250m**: Area (in square meters) of garden spaces
 within a 250m buffer zone. * **Natural_250m**: Area (in square meters) of
 semi-natural habitats within a 250m buffer zone. * **MM_500m**: Area of
 man-made structures within a 500m buffer zone. * **Garden_500m**: Area of
 garden spaces within a 500m buffer zone. * **Natural_500m**: Area of
 semi-natural habitats within a 500m buffer zone. * **MM_1000m**: Area of
 man-made structures within a 1000m buffer zone. * **Garden_1000m**: Area
 of garden spaces within a 1000m buffer zone. * **Natural_1000m**: Area of
 semi-natural habitats within a 1000m buffer zone.