DOI: 10.5061/dryad.dncjsxm90
title: Data from: Landscape management can foster pollinator richness in fragmented high-value habitats

description: Pollinator diversity is declining due to habitat loss, low habitat
 quality, limited habitat connectivity, and intensification of agriculture
 in remaining high-value habitats within human-dominated landscapes, such
 as calcareous grasslands. Options to increase the local area of protected
 habitats are often limited. Therefore, we asked how local habitat quality
 as well as agri-environmental schemes (AES) and configuration of the
 surrounding landscape can contribute to the preservation of pollinator
 diversity. We sampled bees, butterflies, and hoverflies in 40 calcareous
 grasslands in Germany and assessed the effects of calcareous grassland
 area, quality and connectivity, agricultural configuration, and AES on
 species richness and abundance. While calcareous grassland area was an
 important predictor for bee and butterfly species richness, with strongest
 effects sizes for endangered species, local flower resources and nesting
 sites, and landscape characteristics such as small field size, high
 proportion of organic fields and connectivity with other grasslands
 significantly enhanced pollinator richness with responses differing among
 the three studied taxa. In contrast to expectations, AES flowering fields
 did not benefit pollinator communities in grasslands. We conclude that
 improving local habitat quality in combination with targeted landscape
 management are effective measures to promote pollinator richness in highly
 fragmented protected grassland.
description: # Landscape management can foster pollinator richness in fragmented
 high-value habitats
 [https://doi.org/10.5061/dryad.dncjsxm90](https://doi.org/10.5061/dryad.dncjsxm90) ## Description of the data and file structure Data and code for the manuscript: "Landscape management can foster pollinator richness in fragmented high-value habitats" DOI: 10.1098/rspb.2024.2686 ### Files and variables #### File: Biegerl\_data\_Rcode\_ProceedingsB.zip **Description:**  File 1: **Biegerl_R_code_ProceedingsB.Rmd**: R script with the analyses to reproduce the results in this study. File 2: **Landscape_data.csv**: Dataset with the response variable (pollinators species richness and abundance) and the predictors used in this study: Variables: Site_ID = Calcareous grassland/Study site identifier long = Longitude lat = Latitude region = Region of study site (Lower or Upper Franconia) WB_abun = Solitary bee abundance WB_spec = Solitary bee species richness WB_abun_endang =  Endangered Solitary bee abundance (according to the Red List of Bavaria) WB_spec_endang =  Endangered Solitary bee species richness BB_abun = Bumblbebee abundance BB_spec = Bumblebee species richness SF_abun = Hoverfly abundance (SF = syrphid fly) SF_spec = Hoverfly species richness BF_abun =  Butterfly abundance BF_spec = Butterfly species richness BF_abun_endang = Endangered Butterfly abundance BF_spec_endang = Endangered Butterfly species richness habitat_area = Area/size of study site/calcareous grassland in ha habitat connec = Cover of calacareous grassland in a 2 km radius around study site (excluding study site area itself) in % annualcrop_cover = Cover of annual crop fields in a 2 km radius around study site in % organic_farming = Cover of organic farming in relation to the total annual crop cover in % (2 km radius) flowering_fields = Cover of flowering fields in relation to the total annual crop cover in % (2 km radius) mean_field_size = Mean size of annual crop fields in a 2 km radius around study site in ha flower_cover_bee = Cover of flowers on bee/hoverfly transect in % flower_cover_butter = Cover of flowers on butterfly transect in % nesting_sites = Cover of potential nesting sites for solitary bees on bee/hoverfly transect in % flower_diversity_bee = Richness/Number of flowering plant species on the bee/hoverfly transect flower_div_butter = Richness/Number of flowering plant species on the butterfly transect annual_mean_temperature = Mean annual temperature from 1970 to 2010 in Celsius Missing values = NA File 3: **DAG_data.csv**: Dataset with the response variable (pollinators species richness and abundance) and the predictors used in this study: Variables: Region = Region of study site (Lower (0) or Upper (1) Franconia) Wild pollinator richness/abundance = Solitary bee abundance (example for pollinator species richness and abundance) Calcareous grassland area = Area/size of study site/calcareous grassland in ha Habitat connectivity =  Cover of calcareous grassland in a 2 km radius around study site Annual crop cover = Cover of annual crop fields in a 2 km radius around study site in % Organic farming = Cover of organic farming in relation to the total annual crop cover in % (2 km radius) Flowering fields = Cover of flowering fields in relation to the total annual crop cover in % (2 km radius) Mean field size = Mean size of annual crop fields in a 2 km radius around study site in ha Nesting resources = Cover of potential nesting sites for solitary bees on bee/hoverfly transect in % Flower resources = Richness/Number of flowering plant species (example for Flower resources) MAT = Mean annual temperature from 1970 to 2010 in Celsius Missing values = NA ## Code/software R version and list of R packages used for the analyses and plots: We used R version 4.3.1 and RStudio version 2023.06.2 marginaleffects package v 0.20.1 (Arel-Bundock et al. 2024) modelsummary package v 2.1.0 (Arel-Bundock et al. 2024) DHARMa package v 0.4.6 (Hartig & Lohse 2022) performance package v 0.11.0 (Lüdecke et al. 2024) MASS package (Venables & Ripley 2002) tidyverse package v 2.0.0 (Wickham et al. 2023) ggeffects package v 1.6.0 (Lüdecke et al. 2024) ggplot2 package v 3.5.1 (Wickham et al. 2024) DAGitty package v 0.3-4 (Textor et al. 2023) car package v 3.1-3 (Fox et al. 2024) ncf package v 1.3-2 (Bjornstadt & Cai 2022)