DOI: 10.5061/dryad.83bk3j9xb
title: Data from: Insects in the city: Determinants of a contained aquatic microecosystem across an urbanized landscape

description: Cities can have profound impacts on ecosystems, yet our understanding of
 these impacts is currently limited. First, the effects of socioeconomic
 dimensions of human society are often overlooked. Second, correlative
 analyses are common, limiting our causal understanding of mechanisms.
 Third, most research has focused on terrestrial systems, ignoring aquatic
 systems that also provide important ecosystem services. Here we compare
 the effects of human population density and low-income prevalence on the
 macroinvertebrate communities and ecosystem processes within water-filled
 artificial tree holes. We hypothesized that these human demographic
 variables would affect tree holes in different ways via changes in
 temperature, water nutrients, and the local tree hole environment. We
 recruited community scientists across Greater Vancouver (Canada) to
 provide host trees and tend 50 tree holes over 14 weeks of colonization.
 We quantified tree hole ecosystems in terms of aquatic invertebrates,
 litter decomposition, and chlorophyll-a. We compiled potential explanatory
 variables from field measurements, satellite images, or census databases.
 Using structural equation models, we showed that invertebrate abundance
 was affected by low-income prevalence but not human population density.
 This was driven by cosmopolitan species of Ceratopogonidae (Diptera) with
 known associations to anthropogenic containers. Invertebrate diversity and
 abundance were also affected by environmental factors, such as
 temperature, elevation, water nutrients, litter quantity, and exposure. By
 contrast, invertebrate biomass, chlorophyll-a, and litter decomposition
 were not affected by any measured variables. In summary, this study shows
 that some urban ecosystems can be largely unaffected by human population
 density. Our study also demonstrates the potential of using artificial
 tree holes as a standardized, replicated habitat for studying
 urbanization. Finally, by combining community science and urban ecology,
 we were able to involve our local community in this pandemic research
 pivot.  This abstract is quoted from the original article
 "Insects in the city: Determinants of a contained aquatic
 microecosystem across an urbanized landscape" in Ecology (2023) by DS
 Srivastava et al.
description: These methods are quoted in
 abbreviated form from the original article [please also see README.md file
 for details on each script and data file, including description of every
 variable]: We
 installed 73 artificial tree holes (hereafter tree holes) throughout
 Greater Vancouver, specifically the cities of Vancouver, Abbottsford,
 Burnaby, Chilliwack, Delta, Maple Ridge, New Westminster, North Vancouver,
 Port Moody, Richmond, Surrey, and West Vancouver. We constructed
 artificial tree holes from black plastic buckets (950 ml, height: 12.2cm,
 diameter:11.5cm). Near the rim, we drilled 1-cm holes for water overflow
 and covered these with 1mm mesh to prevent loss of insects and litter
 (Figure 2a). We attached each tree hole to a deciduous tree with a cable
 tie, about 1.3 m above ground, before adding leaf litter and bottled
 spring water. The leaf litter consisted of dried (60°C for two days) and
 pre-weighed <em>Acer</em> <em>macrophyllum</em>
 (Sapindaceae) leaves collected in November 2020, both loose (2.50 g) and
 in a 0.5 mm mesh leaf bag (0.200 g). We filled each tree hole with ~750 ml
 spring water (Western FamilyTM). Community scientists were instructed to
 monitor water level in the tree holes during the experiment, topping up
 tree holes when they became half-empty with extra bottles of water (same
 brand) that we provided. We also added an iButtonTM temperature logger
 (Maxim Integrated, San Jose, CA, USA; models DS1921G, DS1921Z, and
 DS1922L) wrapped in ParafilmTM (Beemis Company, Neenah, WI, USA) and
 programmed it to collect data every hour for 85 days. We added a small
 stick to assist ovipositing insects to perch or pupating insects to
 emerge. We installed
 all tree holes 21–28 March 2021. We visited all tree holes 17–30 May 2021,
 to collect data on water chemistry (pH, chlorophyll-a concentration),
 light availability (canopy cover), potential oviposition cues (host tree
 diameter, nearby standing water), and potential source populations
 (distance to water bodies). We measured water pH directly using a
 calibrated OaktonⓇ pH 450
 pH meter. To estimate chlorophyll-a concentration, we extracted 25 mL of
 water, filtered it through a glass microfiber (0.7 μm) filter, and froze
 the filters.  In the lab, we extracted chlorophyll-a on filters with
 90%-acetone. We used a Trilogy Laboratory Fluorometer (Turner Designs, San
 Jose, CA, USA) to determine chlorophyll-a concentration following Wasmund
 et al. (2006). To measure canopy cover, we took a photograph directly up
 by placing a smartphone flat on the tree hole and then used ImageJTM to
 differentiate open sky from any obstructing cover. We searched within 30m
 of tree holes for sources of persistent standing water, such as buckets,
 birdbaths, and tires holding &gt;400 mL water. We retrieved tree holes 1–10 July
 2021, in the same order as installation, standardizing the experimental
 duration to 14 weeks (± 4 days). Once in the lab, we measured water pH as
 before, turbidity with a portable Turner AquaflorⓇ fluorometer, and froze
 a 5mL volume of water for later nutrient analysis. To analyse nutrients
 NO<sub>2</sub><sup>-</sup>,
 NO<sub>3</sub><sup>-</sup>,
 NH<sub>4</sub><sup>+</sup>, and
 PO<sub>4</sub><sup>-3</sup>, we loaded water
 samples onto 96-well plates with standards corresponding to the nutrient
 of interest. We then added the relevant reagents to all wells and compared
 the absorbance of the samples to standards using a SpectraMax M2e
 spectrophotometer (Molecular Devices, San Jose, CA, USA). We averaged two
 measurements per sample. As
 NO<sub>2</sub><sup>-</sup>, NO<sub>3</sub><sup>-</sup>, and NH<sub>4</sub><sup>+</sup> represent three steps of the dissolved inorganic nitrogen (DIN) cycle, we summed their concentrations in a single measure of DIN. We retrieved the remaining leaf fragments in litter bags with tweezers, washing biofilm from them before drying (two days at 60°C) and determining their combined mass. Decomposition was quantified as the percent dry mass lost. We also collected all loose debris in tree holes manually and by filtering through a pre-weighted Fisherbrand™ Fluted Qualitative Circled Filter Paper before drying and determining dry mass. We recorded the total volume of water present in each tree hole. Finally, we searched tree hole contents for macroscopic (&gt;1mm) invertebrates in small aliquots in white trays. We sorted invertebrates into morphospecies, preserved them in 70% ethanol, and later identified them to family or genus level with identification keys. We used allometric equations to estimate dry body mass of invertebrates from body length (mm), either at the individual (species &gt; 10 mm) or species level (<em>hellometry</em> R package, P. Rogy). We preserved a few voucher specimens in 95% ethanol for DNA barcoding to unambiguously assign species identities. For DNA extraction, we used QIAGEN® DNeasy Blood & Tissue Kit. We amplified the barcoding region of the mitochondrial Cytochrome Oxidase I (COI) gene with the universal primers LCO 1490 and HCO 2198 (Folmer et al. 1994). PCR products were sequenced by Psomagen, Inc. The chromatograms were assembled with Geneious Prime® v. 2022.2.2, and the resulting sequences were compared with GenBank and BOLD databases.
description: R version 4.2.0 (2022-04-22 ucrt) Versions of
 R packages used are indicated at the end of archived R scripts under the
 comment #Session Info.
description: # Title of Dataset: --- Data from: "Insects in the city: Determinants
 of a contained aquatic microecosystem across an urbanized
 landscape"" ## Description of the Data and file structure This
 readme file describes the (1) R scripts and (2) datafiles included in this
 repository. All scripts use R version 4.2.0 (2022-04-22 ucrt) and detailed
 package information is found at the end of scripts under #Session Info.
 Missing data in data files are indicated as NA. All data files are in .csv
 format meaning that , is used as the separator. ## (1) Scripts ###
 01\_invert\_biomass\_script.R: this script converts invertebrate
 abundances into biomasses using the length:mass relationships and average
 per capit mass relationships embedded/predicted by the hellometry R
 package. Input: inverts_clean.csv Output: invert_biomass.csv ###
 02\_data\_imputation\_compilation.R: this script imputes some missing
 numeric environmental data, and then combines the full environmental
 dataset with invertebrate summary metrics. Input: compiled_raw_data.csv,
 inverts_clean.csv, invert_biomass.csv Output: clean_data.csv,
 species_composition.csv ### 03\_dag\_piecewise.R: this script conducts
 several piecewise structural equation models, and outputs the path
 coefficients as well as local and global tests of significance. Input:
 clean_data.csv Output: Summary_table_est.rtf, Summary_table_est.csv ###
 04\_plots\_tables.R: the script carries on from the 03 script, creating
 the PCA biplots and partial residual plots for the manuscript. Input:
 03_dag_piecewise.R objects Output: PCA_local_variables.pdf, resfig.jpeg,
 resfig.pdf, Table_summary_SEM.pdf, Summary_table_est.csv,
 Table_fit_SEM.pdf, Summary_table_fit.csv # (2) Data files ## Variables in
 inverts\_biomass.csv Treehole.Number: a unique 2 digit code for each tree
 hole, synonymous with the variable treehole_id in other files (character
 variable) Order: Taxonomic order, if known, of the invertebrate
 morphospecies Family: Taxonomic family, if known, of the invertebrate
 morphospecies Sub.family: Taxonomic subfamily, if known, of the
 invertebrate morphospecies Genus: Taxonomic genus, if known, of the
 invertebrate morphospecies species: Code for the invertebrate
 morphospecies status: alive or dead size: the body length class of the
 invertebrate, either as a category (small, medium, large, unknown) or
 numerical (in millimeters in all cases) abundance: number of individual
 invertebrates corresponding to a particular combination of
 Treehole.Number, size, species, stage and status drymass.mg: predicted dry
 mass of invertebrate individual, obtained from hellometry package based on
 species taxonomy, length and stage (see inverts_clean.csv) ## Variables in
 inverts\_clean.csv Treehole.Number: a unique 2 digit code for each tree
 hole, synonymous with the variable treehole_id in other files (character
 variable) Order: Taxonomic order, if known, of the invertebrate
 morphospecies Family: Taxonomic family, if known, of the invertebrate
 morphospecies Sub.family: Taxonomic subfamily, if known, of the
 invertebrate morphospecies Genus: Taxonomic genus, if known, of the
 invertebrate morphospecies species: Code for the invertebrate
 morphospecies status: alive or dead size: the body length class of the
 invertebrate, either as a category (small, medium, large, unknown) or
 numerical (in millimeters in all cases) abundance: number of individual
 invertebrates corresponding to a particular combination of
 Treehole.Number, size, species, stage and status Species: Latin binomial
 of the invertebrate morphospecies, if known from DNA barcoding
 (Ceratopogonidae sp. A = BOLD:ACR0360 , Ceratopogonidae sp. C
 =BOLD:AAN5169, Clogmia albipunctata = BOLD:AAE5173). If identification to
 species level was not possible, a morphospecies code is assigned starting
 with the known family or order and ending in a capital letter (e.g.
 Cecidomyiidae sp. A). Stage: stage that the aquatic invertebrate was
 sampled, either larva or pupa ## Variables in species composition.csv:
 This file has 18 columns, 47 rows. Variables are treehole_id (a unique 2
 digit code for each tree hole) and abundance of each of 17 morphospecies
 (these 17 column names are the 17 morphospecies listed in the species
 variable in inverts_clean.csv). ## Variables in compiled\_raw\_data.csv,
 clean\_data.csv: treehole_id: a unique 2 digit code for each tree hole
 (character variable) water_body: presence of freshwater within 500m of
 tree hole, noted on Google Earth (binary: 0 = absence, 1 = presence)
 standing_water: sources of persistent standing water (&gt;400 ml water),
 within 30m of tree holes, (binary: 0 = absence, 1 = presence)
 log_circumference_cm: circumference (units: cm, log transformed) of host
 tree at ca. 1.3m aboveground pH: water pH of treehole measured using a
 calibrated Oakton pH 450 pH meter, experiment end canopy_sqrt: canopy
 openness as percentage of sky not obscured, square root transformed
 volume_ml: final water volume in treehole (ml) log_water_volume_ml: final
 water volume in treehole (ml, log-transformed) turbidity: tree hole water
 turbidity at end of experiment, with a portable fluorometer
 log_litter_available_g: loose litter in the tree hole at end of
 experiment, dried (units = g, log-transformed) percent_low_income:
 proportion of the 18-64 year old population in a low-income household,
 defined as a household in the lower quartile of adjusted (i.e. multiplied
 by square root of household size) household after-tax income, extracted at
 level of dissemination area from 2016 Canada Census pop_dens_km2: human
 residents per square km, extracted at level of dissemination area from
 2016 Canada Census elevation_m: elevation (m a.s.l.) extracted from
 latitude-longitude location on Geogle Earth green_gray_ratio_500m: ratio
 of the area of impermeable grey surfaces (e.g. roads, buildings) from
 permeable green surfaces (e.g. forests, fields, lawns, parks) in a 500m
 circle centered on tree hole, from Google Earth green_gray_ratio_100m:
 ratio of the area of impermeable grey surfaces (e.g. roads, buildings)
 from permeable green surfaces (e.g. forests, fields, lawns, parks) in a
 100m circle centered on tree hole, from Google Earth circumference_cm:
 circumference (units: cm) of host tree at ca. 1.3m aboveground latitude:
 latitude of tree hole, in decimal degree notation, North is positive
 Longitude: longitude of tree hole, in decimal degree notation, East is
 positive T_phmeter_C: temperature recorded by the pH meter at experiment
 midpoint avg_min_temp_C: mean daily minimum temperature (unit = degrees
 C), measured every hour for first 85 days of experiment, mix of raw and
 kriged values as defined by kriged variable avg_mean_temp_C: mean daily
 mean temperature (unit = degrees C), measured every hour for first 85 days
 of experiment, mix of raw and kriged values as defined by kriged variable
 avg_max_temp_C: mean daily maximum temperature (unit = degrees C),
 measured every hour for first 85 days of experiment, mix of raw and kriged
 values as defined by kriged variable kriged_min_var: variation in kriged
 value for avg_min_temp_C (in degrees C, 0 if data raw and not kriged)
 kriged_mean_var: variation in kriged value for avg_mean_temp_C (in degrees
 C, 0 if data raw and not kriged) kriged_max_var: variation in kriged value
 for avg_max_temp_C (in degrees C, 0 if data raw and not kriged) kriged:
 temperature data in tree hole is either raw as collected by iButtonTM
 temperature loggers (Maxim Integrated, San Jose, CA, USA; models DS1921G,
 DS1921Z, and DS1922L) (kriged = 0) or kriged based on latitude, longitude
 and elevation (kriged =1). mean_po4_umolL: at end of experiment,
 concentration in tree hole water of PO4 (-) in micromoles per liter
 mean_nh4_umolL: at end of experiment, concentration in tree hole water of
 NH4 (+) in micromoles per liter mean_no2_umolL: at end of experiment,
 concentration in tree hole water of NO2 (-) in micromoles per liter
 mean_no3_umolL: at end of experiment, concentration in tree hole water of
 NO3 (-) in micromoles per liter chlorophyll_ugL: at midpoint of
 experiment, concentration in tree hole water of chlorophyll-a in
 micrograms per liter, as determined with a Trilogy Laboratory Fluorometer
 following Wasmund et al. (2006). Water was first filtered it through a
 glass microfiber (0.7 micrometer), frozen and then extracted on filters
 with 90% acetone fine_litter_g: remaining litter in fine 0.5 mm mesh
 litter bag at end of experiment, initial mass was 0.200 g coarse_litter_g:
 remaining litter in coarse 5 mm mesh litter bag (10cm x 28cm) at end of
 experiment, initial mass was 0.500 g loose_coarse_litter_g: coarse litter
 in the tree hole (collected with a 850 micron mesh) that was not in a
 litter bag, either from litter added at the start of experiment (2g), or
 from a coarse mesh letter bag that opened (see coarse_bag_open variable),
 or natural leaf fall loose_fine_litter_g: the same origin as
 loose_coarse_litter_g, but composed of fragments that passed through the
 850 micron mesh but were capture on Fisherbrand Fluted Qualitative Circled
 Filter Paper coarse_bag_open: binary variable indicating if coarse litter
 bag opened (1) or not (0) during the experiment; this was a problem
 specific to coarse bags due to weak glue fine_bag_open: binary variable
 indicating if fine litter bag opened (1) or not (0) during the experiment;
 rare as fine mesh bags were heat sealed bags_out: binary variable
 indicating if litter bags were pulled out (1) or not (0) during the
 experiment by wildlife litter_available_for_insects_g: this variable
 combines the litter loose in the tree hole (loose_coarse_litter_g +
 loose_fine_litter_g) as well as any litter that was still in coarse mesh
 litter bags (coarse_litter_g) as insects can pass through the coarse mesh
 perc_dec_coarse: percent of initial 0.500g litter lost from intact coarse
 mesh bags over the experiment; NA otherwise perc_dec_fine: percent of
 initial 0.200g litter lost from intact fine mesh bags over the experiment;
 NA otherwise treehole_dry: a binary variable (0 = with water, 1 = without
 water) indicating if the tree hole was with or without water when
 collected notes: information on tree hole status at end of experiment all
 variables starting with string origin: indicates if the original raw value
 of that variable for that treehole used (raw), or if the variable was
 missing and estimated through kriging (kriged) or multivariate/univariate
 methods (impute). Simpson: Simpsons diversity index for invertebrates
 Shannon: Shannon diversity index for invertebrates (results similar to
 Simpsons so not presented in manuscript) Abundance: total number of living
 invertebrates invert.drymass.mg: total biomass of invertebrates Dead:
 total number of dead invertebrates no2_bin: bins of NO2 from Wang et al.
 2013 Atmospheric Environment 64:312319, manually extracted. ##
 Sharing/access Information Links to other publicly accessible locations of
 the data: Was data derived from another source? Yes (population density
 and percent low income) If yes, list
 source(s):