DOI: 10.5061/dryad.3bk3j9kp3
title: Different currencies for calculating resource phenology result in opposite inferences about trophic mismatches

description: Shifts in phenology are among the key responses of organisms to climate
 change. When rates of phenological change differ between interacting
 species they may result in phenological asynchrony. Studies have found
 conflicting patterns concerning the direction and magnitude of changes in
 synchrony, which have been attributed to biological factors. A hitherto
 overlooked additional explanation is differences in the currency used to
 quantify resource phenology, such as abundance and biomass. Studying an
 insectivorous bird, Sanderling, and its prey, we show that the median date
 of cumulative arthropod biomass occurred, on average, 6.9 days after the
 median date of cumulative arthropod abundance. In some years this
 difference could be as large as 21 days. For 23 years, hatch dates of
 Sanderlings became less synchronized with the median date of arthropod
 abundance, but more synchronized with the median date of arthropod
 biomass. The currency-specific trends can be explained by our finding that
 mean biomass per arthropod specimen increased with date. Using a
 conceptual simulation, we show that estimated rates of phenological change
 for abundance and biomass can differ depending on temporal shifts in the
 size distribution of resources. We conclude that studies of trophic
 mismatch based on different currencies for resource phenology can be
 incompatible with each other.
description: To evaluate how our choice of currency for prey phenology will
 affect our perception of a phenological mismatch, we introduce a model
 system: the breeding phenology of an arctic shorebird, Sanderling
 (<em>Calidris alba</em>), and the phenology of their arthropod
 prey. We derive measures of arthropod phenology in terms of abundance and
 biomass (with the latter inferred using allometric length-biomass
 regressions). For this purpose, we analyzed 23 years of arthropod and bird
 data collected at Zackenberg. In addition, we use a simple simulation to
 assess how rates of phenological change are affected by the choice of
 currency for prey phenology. Since 1996 arthropod communities have been
 sampled throughout the snow-free season at Zackenberg, northeast Greenland
 (74°28' N, 20°34' W). To calculate annual seasonal trends in
 arthropod biomass at Zackenberg we first calculated the average number of
 specimens caught per taxonomic group per day per trap. This we did for
 each day of the time window during which a trap was active. These data
 only comprise counts of arthropods but do not contain measurements of the
 length or weight of individual specimens. Therefore, to calculate trends
 in biomass we first allocated a length to each specimen by sampling from
 an additional dataset containing taxon-specific length distributions. Once
 a length was allocated to each specimen, we calculated each specimen’s
 biomass using taxon-specific length-biomass regressions. For each year, we
 then computed daily estimates of total arthropod biomass by summing daily
 biomass estimates of all taxonomic groups and averaging them across all
 active traps. Using this adjusted dataset we then calculated the median
 date of cumulative arthropod numbers and the median date of cumulative
 arthropod biomass for each year. In addition, we assessed hatching dates
 of Sanderlings in Zackenberg by visiting nests or inferred this from egg
 flotation data or chick weights. We then calculated an annual estimate of
 mismatch by subtracting (I) the median date of arthropod abundance, and
 (II) the median date of arthropod biomass from the median hatch date of
 Sanderling chicks. We then assessed trends in the degree and direction of
 mismatch depending on the chosen currency by inspecting the slope of
 linear models. We used case-bootstrapping to calculate 95% quantile
 confidence intervals for all statistics. In addition, we used a simple
 conceptual simulation to assess how rates of phenological change might be
 impacted by the choice of currency when calculating resource
 phenology.
description: This Dryad repository contains five R-scripts (i.e. script 0, I,
 II, II, and IV). Script 0 is automatically sourced in the other scripts
 and does not need to be run manually. Script IV is a standalone script
 that does not require input files. In contrast, scripts I, II, and III
 rely on six data files as input. Five of these input files (i.e. I, III,
 IV, V, and VI) are provided in this Dryad repository. One input file (II)
 is not provided in this Dryad repository due to conflicting licenses. This
 file can be downloaded for free from the Greenland Ecosystem Monitoring
 webpage at the following permanent location https://data.g-e-m.dk/datasets?doi=10.17897/V285-Z265. When downloading this file, the date range needs to be specified as 1996-06-03 to 2020-08-26. All six input files need to be placed in the same working directory as the R-scripts. In addition to these six input files, scripts I, II, and III also require input files that are generated as output in the other R-scripts. It is therefore essential to run all scripts in order of their numbering (from I to III) to generate these output files. Output files are automatically stored in the same working directory as the R-script. For a detailed description of the R-scripts and input files, see the supplemented README.MD file. Meta-data for the output files that are generated in-script can be found in the code of the R-script.
description: # Different currencies for calculating resource phenology result in
 opposite inferences about trophic mismatches This online supplementary
 information contains five R-scripts and five data files. ## DESCRIPTION OF
 THE DATA AND FILE STRUCTURE ### R-SCRIPTS * (0):
 Versluijs2022_Script_0-AuxilliaryFunctions.R A script containing auxiliary
 functions that are automatically sourced in Script 1 and Script 5. This
 script does not need to be run manually. * (I):
 Versluijs2022_Script_1-ArthropodDataZAC_DataPreparation.R Script with data
 preparation steps for the arthropod dataset from Zackenberg containing
 pitfall data collected from 1996 to 2020. This adjusted data file is
 required as an input file for scripts II and III. * (II):
 Versluijs2022_Script_2-ArthropodDataZAC_AddBiomass_NumbersvsBiomass.R To
 study whether the timing of the yearly arthropod peak at ZAC differs when
 depicted by arthropod numbers versus arthropod biomass, we first need to
 add estimates of biomass to the adjusted Zackenberg arthropod dataset from
 script I, because specimens were only counted and identified. In this
 script, we calculate these biomass estimates and add them to the adjusted
 Zackenberg arthropod pitfall dataset. * (III):
 Versluijs2022_Script_3-Analysis_NumbersvsBiomass.R In this script, we
 analyse how estimates of the timing of the yearly arthropod peak at ZAC
 differ when calculated using arthropod numbers versus arthropod biomass.
 This script continues with the output file from script II. * (IV):
 Versluijs2022_Script_4-Analysis_Simulation.R This script contains a simple
 conceptual simulation to assess how rates of phenological change might be
 impacted by the choice of currency for prey phenology. Note that this
 script can be run independently as it does not depend on input files (or
 output files of other scripts). ### DATA FILE CONTENTS * (I):
 Versluijs2022_Input_1-LengthBiomassRegressions.csv * Allometric
 length-biomass regressions for 27 arthropod families were constructed
 based on pitfall data collected in Zackenberg in 2015 and in Knipovich in
 2018. * taxon: taxonomic group (generally corresponds to family level) *
 n: the number of data points on which each allometric model was fitted
 and, if applicable, depicts in brackets the sample size before averaging
 within different length classes. * Min (mm): Minimum length of specimen in
 [mm] used for fitting the regression * Max (mm): Maximum length of
 specimen in [mm] used for fitting the regression * B0: Intercept parameter
 of allometric length-biomass regression including, if applicable, in
 square brackets include 95% quantile confidence intervals calculated using
 non-parametric case-bootstrapping. * B1: Slope parameter of allometric
 length-biomass regression including, if applicable, in square brackets
 include 95% quantile confidence intervals calculated using non-parametric
 case-bootstrapping. * SF: Duan's smearing factor to correct
 back-transformed predictions for models with a log-transformed response
 variable. * Level: indicates whether the regression was fitted on
 individual level measurements or average values for different length
 classes. * Location: Location where specimens were collected (Knipovich
 (TAY) or Zackenberg (ZAC)) * (II):
 DOWNLOAD_THIS_FILE_YOURSELF_FROM_ONLINE_GEM_PORTAL.csv * IMPORTANT: This
 dataset is NOT provided in this Dryad repository due to conflicting
 licenses. It can be downloaded for free from the online GEM portal
 ([https://data.g-e-m.dk/datasets?doi=10.17897/V285-Z265](https://data.g-e-m.dk/datasets?doi=10.17897/V285-Z265). When downloading this file, the date range needs to be specified as 1996-06-03 to 2020-08-26. * This dataset corresponds to the arthropod emergence dataset collected at Zackenberg. It contains weekly data on arthropod numbers in permanent pitfall and flight-intercept traps at Zackenberg between 1996-06-03 and 2020-08-26. Arthropods have generally been identified to family-level taxonomic resolution. This dataset does not contain any information on each specimen's body length and/or biomass. * Date = Date of sampling * Hour = Start hour of sampling (UTC) * PlotID = Plot ID * Sorter = Name of labworker(s) * Days A = Number of days the traps have been open in section A, or (in 1996) sections A-D combined. For Art1, A refers to the North chamber (2006-13). From 2014 onwards, A refers to the North-South chambers combined. * Days B = Number of days the traps have been open in section B, or (in 1996) sections A-D combined. For Art1, B refers to the South chamber (2006-13). From 2014 onwards, B refers to the East-West chambers combined. * Days C = Number of days the traps have been open in section C, or (in 1996) sections A-D combined. For Art1, C refers to the East chamber (2006-13). * Days D = Number of days the traps have been open in section D, or (in 1996) sections A-D combined. For Art1, D refers to the West chamber (2006-13). * Days E = Number of days the traps have been open in section E. * Days F = Number of days the traps have been open in section F. * Days G = Number of days the traps have been open in section G. * Days H = Number of days the traps have been open in section H. * Phylum = Phylum of the collected arthropod * Order = Order of the collected arthropod * Family = Family or super-family of the collected arthropod * Genus = Genus of the collected arthropod * Species = Species of the collected arthropod * A = The number of collected individuals from section A, or (in 1996) sections A-D combined. For Art1, A refers to the North chamber (2006-13). From 2014 onwards, A refers to the North-South chambers combined. * B = The number of collected individuals from section B, or (in 1996) sections A-D combined. For Art1, B refers to the South chamber (2006-13). From 2014 onwards, B refers to the East-West chambers combined. * C = The number of collected individuals from section C, or (in 1996) sections A-D combined. For Art1, C refers to the East chamber (2006-13). * D = The number of collected individuals from section D, or (in 1996) sections A-D combined. For Art1, D refers to the West chamber (2006-13). * E = The number of collected individuals from section E. * F = The number of collected individuals from section F. * G = The number of collected individuals from section G. * H = The number of collected individuals from section H. * Field_remarks = Remarks from the field observer * Sorting_remarks = Remarks from the sorter * General_remarks = General remarks * (III): Versluijs2022_Input_3-ArthropodDataZAC_AddBiomass_PitfallZAC15.csv * Datafile containing Zackenberg 2015 pitfall data. This dataset contains length and dry mass per specimen and is used for random sampling of lengths and/or biomass corresponding to the frequency in which they occur in this dataset. * Area: Location where specimens were collected (Knipovich (TAY) or Zackenberg (ZAC)) * UTM_x: longitude coordinates of trapping location [UTM]. * UTM_y: latitude coordinates of trapping location [UTM]. * sample_ID: identifier for trap * trap_type: type of trap (always yellow pitfall traps) * year: trapping year * month: trapping month * day: trapping day * taxon: taxonomic group (generally corresponds to family level) * order: taxonomic order * length_measured: length measured under stereomicroscope * zoom: zoom-level of stereomicroscope * length_conversion: conversion factor to go from length_measured to length_mm * length_mm: body length of specimen [mm] * length_class: grouping factor for individuals of similar length. If weights could not be measured individually then weights are based on averages for each level of length_class, which are where possible calculated separately for each trap and trapping day. * weight_mg: dry weight of specimen [mg] * weight_level: indicates whether weight measurements were done on an individual level, or weights are based on averages per length_class. * analyzed_at: location and year of lab analysis * identified_by: people/groups responsible for the identification of samples * measurements_by: people responsible for measuring and weighing individuals * Remarks: remarks * (IV): Versluijs2022_Input_4-ArthropodDataZAC_AddBiomass_PitfallTAY18.csv * This data file contains Knipovich 2018 pitfall data; it only contains those taxa that were not present in the Zackenberg 2015 pitfall data (e.g. Tipulidae, Coleoptera). This dataset contains length and dry mass per specimen and is used for random sampling of lengths and/or biomass corresponding to the frequency in which they occur in this dataset. * Area: Location where specimens were collected (Knipovich (TAY) or Zackenberg (ZAC)) * UTM_x: longitude coordinates of trapping location [UTM]. * UTM_y: latitude coordinates of trapping location [UTM]. * sample_ID: identifier for trap * trap_type: type of trap (always yellow pitfall traps) * year: trapping year * month: trapping month * day: trapping day * taxon: taxonomic group (generally corresponds to family level) * order: taxonomic order * length_measured: length measured under stereomicroscope * zoom: zoom-level of stereomicroscope * length_conversion: conversion factor to go from length_measured to length_mm * length_mm: body length of specimen [mm] * length_class: grouping factor for individuals of similar length. If weights could not be measured individually then weights are based on averages for each level of length_class, which are where possible calculated separately for each trap and trapping day. * weight_mg: dry weight of specimen [mg] * weight_level: indicates whether weight measurements were done on an individual level, or weights are based on averages per length_class. * analyzed_at: location and year of lab analysis * identified_by: people/groups responsible for the identification of samples * measurements_by: people responsible for measuring and weighing individuals * Remarks: remarks * (V): Versluijs2022_Input_5-ArthropodDataZAC_AddBiomass_StickyTrapZAC19-21.csv * Datafile containing arthropod sticky trap data collected in Zackenberg in 2019 and 2021. This datafile contains lengths per specimen and is used for random sampling of lengths corresponding to the frequency in which they occur in this dataset. * Sample: unique identifier to the label of the sticky trap * Order: taxonomic order * Family: taxonomic family * Subgroup: taxonomic subgroup (combination of multiple families) * Length_measured: length measured under stereomicroscope * Zoom: zoom level when measuring * length_mm: actual body length of specimen [mm] * Trap_type: Type of sticky trap (Large: ST_Large, or Small: ST_Small) * Bino: model of stereo microscope * Remarks: remarks * (VI): Versluijs2022_Input_6-Analysis_NumbersvsBiomass_SanderlingHatchdates.csv * Datafile with Sanderling hatch dates based on nests and broods found in Zackenberg between 1996 and 2021. * fateID = unique identifier corresponding to the column in our database * NestID = ID of nest or brood * Year = Year in which nest was found * source = hatch date was defined from data obtained during the nesting phase ('nest') or the brood phase ('brood') * hatched = did the nest hatch (i.e. is the exact hatching date known and not estimated) * medianhatchday = hatch date in the day of the year * Remarks = Remarks ## SHARING/ACCESS INFORMATION Dataset number II (i.e. the arthropod emergence dataset for Zackenberg) is not included in this Dryad repository and can be accessed at the following permanent location: [https://doi.org/10.17897/V285-Z265](https://doi.org/10.17897/V285-Z265).