DOI: 10.5061/dryad.sbcc2frcf
title: The effects of human population density on trophic interactions are contingent upon latitude

description: Aim:  Studies conducted at a global scale are necessary to make
 general conclusions on the effect of urbanization on trophic interactions
 and explore how these effects change along latitudinal gradients. Since
 biotic interactions are more intense at lower latitudes, we predict they
 are less likely to be affected by human impacts than at higher latitudes.
 Therefore, we test the hypothesis that the effect of urbanization
 (quantified by human population density) on trophic interactions,
 specifically insect herbivory and bird predation, decreases with an
 increase in latitude Location:  Global (881 study sties) Time
 period: 2000-2021 Major taxa studied:  Birds, arthropods and
 plants. Methods:  We compiled global data on insect herbivory and
 bird predation from individual studies using similar methodologies, and
 fitted generalized linear mixed models to test the effect of human
 population density, latitude and their interaction on these two response
 variables. Results:  The intensity of herbivory and predation
 decreased with the increase of human population density at lower
 latitudes, remained unaffected at intermediate latitudes, and increased at
 higher latitudes. Main conclusions:  The effect of urbanization
 on the intensities of trophic interactions varies across latitudes, with a
 reversal of the pattern at high vs. low latitudes potentially explained by
 the urban heat island effect, being this pattern consistent across the two
 main trophic interaction.
description: # Title of Dataset *** Data and R codes of "The effects of human
 population density on trophic interactions are contingent upon
 latitude" Authors: Juan A. Hernández-Agüero, Ildefonso
 Ruiz-Tapiador3, Lucas A. Garibaldi4,5, Mikhail V. Kozlov6, Elina
 Mäntylä6,7,8, Marcos E. Nacif4,5, Norma Salinas9 & Luis Cayuela1
 Methodology: Herbivory Insect herbivory data was obtained from the
 literature. Insect herbivory was quantified in the papers used as the
 proportion of leaf area consumed by defoliating insects. It was estimated
 with either image software or visually, as proposed by Alliende (1989).
 Because human population density is changing rapidly, we restricted our
 analysis to data collected since 2000. We extracted the greater part of
 data from a systematic global review (Kozlov et al., 2015), and we
 searched for data published between 2015 and December 2021 in the ISI Web
 of Science on 19 April 2022 with the words “Defoliation” and “Insect
 herbivory [i.e. Defoliation (All Fields) AND insect herbivory (All Fields)
 and 2021 or 2020 or 2019 or 2018 or 2017 or 2016 or 2015 (Publication
 Years)]”. "Defoliation” was used to avoid including other types of
 herbivory such as galler herbivory or miner herbivory, while “insect
 herbivory” was included to avoid papers referring to large herbivorous.
 Galler and miner herbivory were excluded from the search criteria because
 the data paper of Mendes et al., (2021) did not include them. We only
 included data of herbivory on woody plants following the searching
 criteria of Kozlov et al. (2015). From the 131 articles obtained only
 eight used the selected methodology to quantify herbivory, and we also
 included the submitted manuscript by Hernández-Agüero, Ruiz-Tapiador,
 Garibaldi, Kozlov, Nacif et al. (2023) (Figure 1a; Supplementary Material
 Table S1). A list of the data sources (10 sources) is found in
 Supplementary Material Table S1 and a complete list of studies reviewed
 (130 sources) and the justification for exclusion can be found in
 Supplementary material 3. Predation Bird predation on herbivorous insects
 was quantified by attack rates on artificial caterpillars made of odorless
 plasticine, which were placed on a woody plant branch or leaves. Following
 an exposure (from 2 to 64 days), the caterpillars were revisited and bird
 marks were counted following the methodology proposed in Low, Sam,
 McArthur, Posa & Hochuli (2014). We extracted the data from two
 global studies (Roslin et al., 2017; Zvereva et al., 2019) and searched
 for additional studies (published between January 2000 and 23 December of
 2021) in the ISI Web of Science on 19 April 2022, using the keywords
 “bird”, “predation” and “larvae” [i.e. Results for bird (All Fields) AND
 predation (All Fields) AND ( larvae (All Fields) OR caterpillar (All
 Fields)) and 2021 or 2020 or 2019 or 2018 or 2017 or 2016 or 2015 or 2014
 or 2013 or 2012 or 2011 or 2010 or 2009 or 2008 or 2007 or 2006 or 2005 or
 2004 or 2003 or 2002 or 2001 or 2000 (Publication Years)]. Most of the
 studies identified included caterpillars of different colors, except for
 Roslin et al. (2017) which was based only on green-colored caterpillars.
 Because prey colors can influence attack rates (Hernández-Agüero, Polo,
 García, Simón, Ruiz-Tapiador et al., 2020) and colour preferences by birds
 can change latitudinally, we selected only green caterpillar data, which
 does not show changes in preference by predators along latitudinal
 gradients (Zvereva et al., 2019). Our search identified 217 publications,
 among which only 11 studies shared similar methods to those of Roslin et
 al. (2017) and Zvereva et al. (2019) and provide raw data on green
 plasticine models; we also included the submitted manuscript article by
 Hernández-Agüero et al. (2023) (Figure 1b; Supplementary Material Table
 S2). A list of the data sources (16 sources) is found in Supplementary
 Material Table S2 and a complete list of studies reviewed (320 sources)
 and the justification for exclusion can be found in Supplementary material
 3. To account for differences across studies in the length of the study
 period, we estimated the probability of a caterpillar to be attacked over
 one day (henceforth probability of bird predation) as: P (X=1)=1-P
 (X=0)=〖1-[1-(N/T)]〗^((1/t) ) where P (X≥1) is the probability of having
 one or more caterpillars attacked by birds, N is the number of attacked
 caterpillars, T is the total number of caterpillars used per period, and t
 is the period length in days. Human population We used the Gridded
 Population of the World (GPWv4 2020) dataset, at 1 km spatial resolution,
 to estimate human population density at each study site. One site was
 consider when has unique coordinates. To do so, we created a 10 km radius
 buffer at each site with the ‘st\_buffer’ function of the ‘sf’ package
 (Pebesma, 2018). This buffer size has been used in other studies to
 investigate the effects of human impact on vertebrate and plant species
 (Kim, Mizuno & Kobayashi, 2003; Pautasso, 2007) and is highly
 correlated (r ≥ 0.7) with values of population density obtained at smaller
 (e.g. 5 km radius buffer) and larger (e.g. 25 or 40 km radius buffer)
 scales (Supplementary Material Figure S1 and Figure S2). We then cropped
 the rasterized GPWv4 dataset with our site buffer of 10 km using the
 ‘crop’ function of the R package ‘raster’ (Hijmans, 2020) and created a
 new raster object using our buffered coordinates and the GPWv4 cropped
 dataset with the ‘mask’ function. Finally, we extracted the total human
 population at every site with the ‘extract’ function and then human
 population density per km2 was calculated by dividing by the area in km2.
 Correlation tests were made between the data obtained for HPD and other
 common used index to measure urbanization (i.e. proportion of “built
 area”). Built area data was obtained from Dynamic World V1 (Brown et al.,
 2022) Data analyses We used generalized linear mixed models (GLMM) with a
 beta error distribution and a logit link function to investigate the
 effects of human population and latitude on bird predation and insect
 herbivory. Beta is a family of continuous probability distributions
 defined on the interval [0,1], and therefore appropriate for the type of
 response variables we are modelling in this study. We used the natural
 logarithm of human population, absolute (i.e. unsigned) latitude and their
 interaction as predictors. In the GLMMs for herbivory, we included the
 following random factors: i) site, which accounted for potential spatial
 autocorrelation (there were from 1 to 49 data per site); and ii) plant
 species nested within genus, which accounted for differences in
 palatability and plant defenses against herbivory among plant taxa. In the
 GLMMs for bird predation, we included site as random factor (there were
 from 1 to 12 data per location). All GLMMs were fitted using maximum
 likelihood with the function ‘mixed\_model’ of the R package ‘glmmTMB’
 (Brooks, Kristensen, van Benthem, Magnusson, Berg et al., 2017). For both
 herbivory and predation, alternative models were compared using the Akaike
 information criterion (AIC) to select the explanatory variables (i.e.
 fixed effects). Models with a difference in AIC &gt; 2 indicated that
 the worst model could be omitted. Following Nakagawa & Schielzeth
 (2013), we estimated the R2 of all plausible linear or mixed models. This
 allowed two components of R2 to be calculated: (1) a marginal R2 (R2m)
 that only considers the variability explained by fixed effects; and (2) a
 conditional R2 (R2c) that accounts for the variability supported by both
 fixed and random effects. Model residuals were explored using a
 simulation-based approach to create readily interpretable scaled
 (quantile) residuals for the fitted GLMMs (Hartig, 2019). Moran’s index
 was used to estimate spatial autocorrelation in model residuals both for
 proportion of herbivory and probability of predation. To test for
 significance of spatial autocorrelation, this index was compared with a
 null model random distribution using the ‘spdep’ package (Bivand &
 Wong, 2018). When spatial autocorrelation in model residuals was
 significant, we re-fitted the model including a spatial autocorrelation
 function with exponential correlation structure. This uses an Euclidean
 distance matrix based on site coordinates (Brooks et al., 2017). We
 repeated all the analyses with human population density calculated at
 different buffer sizes (i.e. 1, 5, 10, 15, 20, 25, 30, 35 and 40 km radius
 buffer) to ensure that the spatial scales were not affecting our results
 (Supplementary Material Table S3 and Table S4). Finally, mean annual
 temperature between 1970-2000 in each study site was estimated using
 WorldClim database obtained with the function ‘getData’ from ‘raster’
 package for every coordinate. Correlation tests were made using the
 function ‘corrgram’ from ‘corrgram’ package (Wright, 2021) between the
 temperature and the absolute latitude. \#\# Description of the data and
 file structure 03-07-2023.R This is the main R script of the paper.
 calculacion.R This is the secondary R script of the paper. It is a
 function to calculate human population density. It is needed to run
 03-07-2023.R herbivory2022.csv this is the herbivory dataset to be used in
 03-07-2023.R "site": is the study site named by the authors of
 the original paper "lat": is the latitude (epsg 6933)
 "long": is the longitude (epsg 6933) "Country": is the
 Country (in english) where the study was made "Species": is the
 plant species in which herbivory was evaluated "Genus": is the
 Plant Genus in which herbivory was evaluated "pop": is the human
 population 10 km arround the study site "source": is the
 reference of the paper from which the data was obtained
 "logpop": is the logarithm 10 of the human population 10 km
 arround each study site "abslat": is the absolute latitude (epsg
 6933) "HPopulation": is the human population density per
 squarekm "percentage": is the mean percentage of defoliation
 Green.png This image created by Inés M. Alonso-Crespo is needed to create
 one of the figures of the paper in 03-07-2023.R predation2022.csv this is
 the predation dataset to be used in 03-07-2023.R "Site": is the
 study site named by the authors of the original paper
 "SiteYear": is the study site named by the authors of the
 original paper and the year in which the experiment was made
 "lat": is the latitude (epsg 6933) "long": is the
 longitude (epsg 6933) "Population": is the human population 10
 km arround the study site "Source": is the reference of the
 paper from which the data was obtained "Hpopulation": is the
 human population 10 km arround the study site "dat": is the
 number of days since the placement of the plasticine caterpillars and the
 evaluation of damage "Damaged": is the number of caterpillars
 damaged "Placed": is the number of caterpillars placed
 "Rate": is the rate of caterpillars damaged
 "Probability": is the probability of a caterpillar to be damaged
 one day "Hpopkm": is the human population density per km square
 "logHpopkm": is the logartihm of the human population density
 per km square "abslat": is the absolute latitude (epsg 6933)
 Defol.png This image created by Inés M. Alonso-Crespo is needed to create
 one of the figures of the paper in 03-07-2023.R \#\# Sharing/Access
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