DOI: 10.5061/dryad.t76hdr8d4
title: Data from: Vegetation biomass and landscape context shape web-building spider dietary niche breadth in urban vacant lots

description: Legacy cities often encompass large numbers of vacant land parcels that
 can be managed as green spaces to promote biodiversity and provide
 ecosystem services. We aimed to understand how the frequency of mowing and
 the extent of landscape fragmentation surrounding a vacant lot habitat
 influenced predator diets and shaped predator communities. We focused on a
 group of small web-building spiders, as their dispersal success can be
 influenced by landscape variables, and their establishment is sensitive to
 local management intensity. We hypothesized that reduced landscape
 fragmentation and mowing frequency would sustain a species-rich and
 abundant community of these generalist predators by supporting a high
 dietary niche breadth and reducing exploitative competition, measured as
 dietary niche overlap. There are two sets of raw data: pitfall trap counts
 per location with environmental data, and hand-collected/aspirated records
 of Linyphiidae and Tetragnathidae spiders with associated diet records
 from barcoding. Abundance metrics in further sheets are summed from the
 pitfall data per site (Linyphiidae or 'Liny' is always an
 abbreviation for the abundance of Linyphiidae and Tetragnathidae spiders
 together).  Sampling data includes site name/abbreviation/number,
 treatment (control or meadow), date collected, and percent and proportion
 of impervious surface in a 500m buffer surrounding a site (calculated in
 ArcGIS Pro). Vegetative data includes biomass (grams), community
 weighted mean (cwm), vegetation height (cm), and community weighted mean
 number of blooms. Biomass was calculated using both weight in grams and
 the comparative yield method (Haydock & Shaw 1975); the values
 represent the estimated biomass per site. The same is true of vegetation
 height and blooms; we collected data and then conducted a community
 weighted means method to analyze their presence and characteristics for
 the whole plot.
description: # Vegetation biomass and landscape context influence web-building spider
 diets within urban vacant lots. The dataset contents include count data,
 local vegetation variables, temporal variables, site information, diet
 information, and bipartite metrics. These data were used to create
 generalized linear models in R, carry out mean testing, non-metric
 multidimensional scaling with a PERMANOVA and dispersion analysis, and
 calculate bipartite metrics. ## Data and file structure description The
 Excel spreadsheet contains raw data from pitfall catches, which were
 aggregated to get abundance data for web-building spiders (noted as
 Linyphiidae in the sheets for ease of reading, but include selected
 Tetragnathids). The csv files were brought into R for analysis. There are
 two sets of original data used in the project: raw pitfall catches and raw
 diet data. The pitfall catches are any spider found in our pitfall traps;
 these numbers were used to calculate abundance and Linpyhiidae abundance.
 Raw diet data were used to obtain the bipartite variables, which were
 z-value transformed with null models (process in molEcoCodev-final R
 script by F. Sivakoff). We also tested if our focal spiders were
 exercising niche partitioning (NMDS) with the raw diet data, if aspirating
 led to more prey detection than hand collecting with raw diet data and
 collection method, and what environmental variables (if any) influenced
 how many spiders had detectable prey. Datasets include | File |
 Description | Notes | | --------------------------------------- |
 -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Pitfall\_Spiders\_raw\_dryad.xlsx | Raw data containing site code (Column A), sampling information (Columns B–C), species data (Columns D–I), and any comments on the vial (Column J). Male/female/immature are Columns F–H. | Linyphiidae abundance `Spiderzscores.csv` is the summed Linyphiidae and Tetragnathidae spiders by site. | | freqWeb\_v2.csv | Aspirated/hand-collected spiders with prey species abundance summed per site. | | | site\_info\_v2.csv | Site numbers and the management treatment (control or garden). | | | NMDSfr.csv | Aspirated/hand-collected spiders with prey species abundance, spiders in individual rows. All spiders with no detected prey were removed from this analysis; this sheet does not include them. | | | spiderzscores.csv | Includes site data (Columns A–B), bipartite metrics (Columns C–H), vegetative variables (Column I), summed abundances (Columns J–M), and imperviousness (Column N). | Liny denotes Linyphiidae, which actually represents the Linyphiidae and Tetragnathidae spiders referred to as "web-building spiders" in the manuscript. *Cwm* = community weighted mean; biomass is estimated in grams; height in cm. | | ProportionSpiderswPreyDetected.csv | Includes site information (Columns A–B), average number of prey per species per site (Columns D–G), vegetation data (Columns H–K), percent and proportions of all species without prey per site (Columns M–O), abundance (Columns P–Q), and proportion of all species with and without prey without *C. emertoni* (Columns R–S). | *Cwm* = community weighted means (methods in the manuscript). | | SpiderCollectionMethodData5\_14\_25.csv | Includes site/sample information (Columns A–E), sampling method (Column F), spider information (Columns G–H), gut content analysis information (Columns I–M), and prey information (Columns N–AP). | | ## Sharing/Access information Please contact Ellen Danford ([eedanford@aol.com](mailto:eedanford@aol.com)) with questions. ## Code/Software We used R Studio 4.4.3 to upload and run these files. GLM_MeansTesting: This file is a script that runs generalized linear models to compare group means, explains the steps, and produces a clean report with both text and results. molEcoCodev_-_final: t creates site-specific spider–prey networks, computes ecological indices, compares them to null models to assess significance, and then tests management effects statistically.