DOI: 10.5061/dryad.2547d7wwt
title: Data from: Semi-natural habitat, but not aphid amount or continuity, predicts lady beetle abundance across agricultural landscapes

description: The amount of semi-natural habitat surrounding farm fields is a common but
 inconsistent predictor of natural enemy populations and predation
 services. Standard land cover metrics may not accurately capture the
 actual availability of limiting resources for natural enemies and can miss
 important dynamics across space and time. Theory from animal movement and
 landscape ecology predicts that regions with more, spatio-temporally
 continuous resources (i.e. food, shelter) should have larger predator
 populations and enhanced biological control. To test these
 predictions empirically, we designed a study measuring aphids, lady
 beetles, and predation services in agricultural landscapes in Wisconsin,
 USA. In two study years, we sampled lady beetles and aphids in 336 crop
 fields (corn, soybean, alfalfa, and small grains) and adjacent
 semi-natural habitat patches (grasslands and woodlands) across 24 1.5 km
 buffer landscapes at 4–7 time points each, and in one year we assessed
 predation rates with sentinel egg cards. We used aphid counts to model
 habitat-specific aphid phenologies, from which we calculated landscape
 indices of prey amount and continuity. These indices, along with
 semi-natural habitat area, were used to predict lady beetle
 abundance. While there were strong differences in the abundance
 and timing of aphids by habitat, semi-natural habitat amount was still a
 better predictor of lady beetle counts and sentinel egg predation than
 either aphid amount or continuity indices in these landscapes. Synthesis
 and application: Our findings confirm the robust relationship between lady
 beetles and semi-natural habitat in agricultural landscapes, and highlight
 the complexities of measuring fine-scale resource heterogeneity in real
 landscapes. Retaining or adding woodland and grassland patches in
 agricultural landscapes is likely to support larger lady beetle
 populations and enhance predation in crop fields. Our results suggest that
 these habitats may be more important for shelter than prey continuity,
 though this mechanism warrants further investigation. Future work should
 continue to refine experimental methods for the successful integration of
 landscape ecology and animal behavior to support conservation goals.
description: See "Semi-natural habitat, but not aphid amount or
 continuity, predicts lady beetle abundance across agricultural
 landscapes", <em>Journal of Applied Ecology </em>for
 detailed methods<em>.</em>
description: # Data from: Semi-natural habitat, but not aphid amount or continuity,
 predicts lady beetle abundance across agricultural landscapes
 [https://doi.org/10.5061/dryad.2547d7wwt](https://doi.org/10.5061/dryad.2547d7wwt) ## Description of the data and file structure ### **landscape.data.csv** Landscape composition information derived from the USDA cropland data layer ([https://www.nass.usda.gov/Research_and_Science/Cropland/Release/](https://www.nass.usda.gov/Research_and_Science/Cropland/Release/) for 2019 and 2021 using the landscape metrics package (v2.0.0, [https://cran.r-project.org/web/packages/landscapemetrics/index.html](https://cran.r-project.org/web/packages/landscapemetrics/index.html) | Variable name | Variable description | Variable class | Levels / measurement scale | Units  | DateTime format  | | :------------ | :----------------------------------------------------------------------------------------------------------------------------------------------- | :------------- | :------------------------- | :--------- | :--------------- | | landscape | unique identifier for each landscape | factor | 24 levels |   | | | year | year of USDA CDL data used | factor | 2 levels (2019, 2021) |   | yyyy | | scale | extent of circular buffer for landscape data extraction | numeric | 1500 | meters |   | | corn | percentage of the landscape coverd in maize (CDL codes 1, 12, 13, 225, 226, 228, 237) | numeric | 0-100 | percentage | | | soy | percentage of the landscape coverd in soybean (CDL codes 5, 26, 239, 240, 241, 254) | numeric | 0-100 | percentage | | | alfalfa | percentage of the landscape coverd in alalfa (CDL code 36) | numeric | 0-100 | percentage |   | | small.grains | percentage of the landscape coverd in wheat, barley, rye, spelt, and buckwheat (CDL codes 21, 22, 23, 24, 25, 27, 28, 29, 30, 39, 234, 235, 236) | numeric | 0-100 | percentage |   | | grass | percentage of the landscape covered in prairie, herbaceous wetland, pasture, and non-alfalfa hay (CDL codes 37, 58, 59, 60, 61, 87, 176, 195) | numeric | 0-100 | percentage |   | | wood | percentage of the landscape covered in forest (CDL codes 63, 64, 71, 141, 142, 143, 152, 190) | numeric | 0-100 | percentage |   | | other | percentage of the landscape in other CDL classes | numeric | 0-100 | percentage | | | developed | percentage of the landscape coverd in barren/developed land (CDL codes 65, 81, 82, 88, 121, 122, 123, 124) | numeric | 0-100 | percentage |   | | water | percentage of the landscape covered in water or ice (83, 92, 111, 112) | numeric | 0-100 | percentage |   | | other.crops | percentage of the landscape covered in other crop types | numeric | 0-100 | percentage |   | | seminatural | percentage of the landscape covered in grassland and woodland | numeric | 0-100 | percentage |   | ### sweep.data.csv Counts of insects (aphids, lady beetle larvae, and lady beetle adults)c ollected in sweep net and vegetation beating samples across all study years and sampling locations, as described in Iuliano et al. 2024, *Journal of Applied Ecology.* Missing values are designated by NA | Variable name | Variable description | Variable class | Levels / measurement scale | Units  | DateTime format  | | :--------------- | :-------------------------------------------------------------------------------------------------- | :------------- | :------------------------------------------------------------------ | :-------------- | :--------------- | | year | year in which sampling occurred | factor | 2 levels (2019, 2021) | | | | landscape | unique identifier for each landscape | factor | 24 levels | | | | patch | unique identifier for each patch (sampling site) within its landscape | factor | 11 levels | | | | site.id | uniqe identifier for each sampling location within year (patch-landscape-year) | factor | 335 levels |   | | | date\_sweep | date on which sweep sampling occurred | date | | | | | round | round of sampling | ordred factor | 7 levels (1-7) | | | | class | land cover class at sampling site | factor | 7 levels (corn, soy, alfalfa, small grains, grass, woodland, other) | | | | vegetation | designation of whether vegetation was present or absent (i.e. bare ground) at the sampling location | factor | 2 levels (yes, no) | | | | temp | temperature in the nearest town at the time of sampling | numeric | continuous | degrees Celcius | | | sun | level of sun exposure during sampling event | factor | 3 levels (sun, part, cloud) | | | | wind  | level of wind during sampling event | factor | 3 levels (low, medium, high) | | | | wet | wetness of vegetation during sampling | factor | 2 levels (dry, wet) | | | | aphid\_sweep | number of aphids counted in 100 (4 x 25) back-and-forth sweep net samples  | numeric | integer | count | | | aphid\_beat | number aphids counted in 4 branch beating samples | numeric | integer | count | | | all.aphids | sum of aphid\_sweep and aphid\_beat | numeric | integer | count | | | A.bit\_sweep | number Anisosticta bitrangularis collected in sweep net samples | numeric | integer | count | | | A.lab\_sweep | number Anatis labiculata collected in sweep net samples | numeric | integer | count | | | B.spp\_sweep | number Brachiacantha spp. collected in sweep net samples | numeric | integer | count | | | C.7\_sweep | number Coccinella septempunctata collected in sweep net samples | numeric | integer | count | | | C.mac\_sweep | number Coleomegilla maculata collected in sweep net samples | numeric | integer | count | | | C.mun\_sweep | number Cycloneda munda collected in sweep net samples | numeric | integer | count | | | C.sti\_sweep | number Chilocorus stigma collected in sweep net samples | numeric | integer | count | | | H.axy\_sweep | number Harmonia axyridis collected in sweep net samples | numeric | integer | count | | | H.bin\_sweep | number Hyperaspis binotata collected in sweep net samples | numeric | integer | count | | | H.con\_sweep | number Hippodamia convergens collected in sweep net samples | numeric | integer | count | | | H.gla\_sweep | number Hippodamia glacialis collected in sweep net samples | numeric | integer | count | | | H.par\_sweep | number Hippodamia parenthesis collected in sweep net samples | numeric | integer | count | | | H.var\_sweep | number Hippodamia varietgata collected in sweep net samples | numeric | integer | count | | | P.14\_sweep | number Propylea quatuordecimpunctata collected in sweep net samples | numeric | integer | count | | | LB.A\_sweep | number of adult lady beetles captured in sweep samples | numeric | integer | count | | | LB.A\_beat | number of adult lady beetles caputred in branch beating samples | numeric | integer | count | | | LB.L\_sweep | number of larval lady beetles captured in sweep samples | numeric | integer | count | | | LB.L\_beat | number of larval lady beetles caputred in branch beating samples | numeric | integer | count | | | all.LB\_sweep | all adult and larval lady beetles captured in sweep samples | numeric | integer | count | | | agro.LB\_sweep | all agrobiont species lady beeltes caputed in sweep samples | numeric | integer | count | | | native.LB\_sweep | all native species lady beeltes caputed in sweep samples | numeric | integer | count | | | intro.LB\_sweep | all introduced species lady beeltes caputed in sweep samples | numeric | integer | count | | ### card.data.csv Counts of adult lady beetles collected on yellow sticky cards across all study years and sampling locations, as described in Iuliano et al. 2024, *Journal of Applied Ecology*. Missing values are designated by NA | Variable name | Variable description | Variable class | Levels / measurement scale | Units  | DateTime format  | | :------------ | :----------------------------------------------------------------------------- | :------------- | :----------------------------------------------------------- | :----- | :--------------- | | year | year in which sampling occurred | factor | 2 levels (2019, 2021) | | | | landscape | unique identifier for each landscape | factor | 24 levels | | | | patch | unique identifier for each patch (sampling site) within its landscape | factor | 11 levels | | | | site.id | uniqe identifier for each sampling location within year (patch-landscape-year) | factor | 335 levels |   | | | date\_card | date on which stick card was collected | date | | | | | round | round of sampling in which sticky card was collected | ordred factor | 7 levels (1-7) | | | | class | land cover class at sampling site | factor | 6 levels (corn, soy, alfalfa, small grains, grass, woodland) | | | | A.bit\_card | number Anisosticta bitrangularis counted on the sticky card | numeric | integer | count | | | A.lab\_card | number Anatis labiculata counted on the sticky card | numeric | integer | count | | | B.spp\_card | number Brachiacantha spp. counted on the sticky card | numeric | integer | count | | | C.qua\_card | number Calvia quatuordecimguttata counted on the sticky card | numeric | integer | count | | | C.7\_card | number Coccinella septempunctata counted on the sticky card | numeric | integer | count | | | C.mac\_card | number Coleomegilla maculata counted on the sticky card | numeric | integer | count | | | C.mun\_card | number Cycloneda munda counted on the sticky card | numeric | integer | count | | | C.sti\_card | number Chilocorus stigma counted on the sticky card | numeric | integer | count | | | H.axy\_card | number Harmonia axyridis counted on the sticky card | numeric | integer | count | | | H.bin\_card | number Hyperaspis binotata counted on the sticky card | numeric | integer | count | | | H.con\_card | number Hippodamia convergens counted on the sticky card | numeric | integer | count | | | H.gla\_card | number Hippodamia glacialis counted on the sticky card | numeric | integer | count | | | H.par\_card | number Hippodamia parenthesis counted on the sticky card | numeric | integer | count | | | H.var\_card | number Hippodamia varietgata counted on the sticky card | numeric | integer | count | | | P.14\_card | number Propylea quatuordecimpunctata counted on the sticky card | numeric | integer | count | | | all.LB | number of adult lady beetles captured in sweep samples | numeric | integer | count | | | agro.LB | all agrobiont species lady beeltes caputed in sweep samples | numeric | integer | count | | | native.LB | all native species lady beeltes caputed in sweep samples | numeric | integer | count | | | intro.LB | all introduced species lady beeltes caputed in sweep samples | numeric | integer | count | | ### egg.data.csv Sentinel egg predation experiment data, as described in Iuliano et al. 2024, *Journal of Applied Ecology*. Missing values are designated by NA. | Variable name | Variable description | Variable class | Levels / measurement scale | Units  | DateTime format  | | :------------ | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :------------- | :----------------------------------------------------------- | :--------- | :--------------- | | card.id | unique identifier for each sentinel egg card | factor | 328 levels | | | | landscape | unique identifier for each landscape | factor | 24 levels | | | | patch | unique identifier for each patch (sampling site) within its landscape | factor | 11 levels | | | | site.id | uniqe identifier for each sampling location within year (patch-landscape-year) | factor | 335 levels | | | | class | land cover class at sampling site | factor | 6 levels (corn, soy, alfalfa, small grains, grass, woodland) | | | | data.set | date on which egg card was set | date | | | mm/dd/yyyy | | data.collect | date on which egg card was collected | date | | | mm/dd/yyyy | | egg.start | number of eggs initially counted on the card,including damaged eggs | numeric | integer | count | | | damaged.start | number of damaged eggs initially counted on the card (not counted for cards 1-84) | numeric | integer | count | | | egg.end | number of eggs counted on the card at the conclusion of the experiment,including damaged eggs | numeric | integer | count | | | damaged.end | number of damaged eggs counted on the card at the conclusion of the experiment | numeric | integer | count | | | eggs.predated | number of eggs with evidence of predation, calcuated as the number of eggs removed (eggs.start - eggs.end) plus the number of damaged eggs (damaged.end) minus the number of initial damaged eggs (damaged.start) | numeric | integer | count | | | prop.predated | proportion of eggs with evidence of predation (eggs.predated/eggs.start) | numeric | 0-1 | proportion | | ## Code/Software ### iuliano.2024JAE.Rmd R workflow for completing analysis described in Iuliano et al. 2024, *Journal of Applied Ecology*. Created using RStudio v2023.09.1+494 and R v4.3.1 #### packages | wec | 0.4-1 | [https://cran.r-project.org/web/packages/wec/index.html](https://cran.r-project.org/web/packages/wec/index.html) | | :----------- | :------ | :------------------------------------------------------------------------------------------------------------------------------------------------------- | | GGally | 2.1.2 | [https://cran.r-project.org/web/packages/GGally/index.html](https://cran.r-project.org/web/packages/GGally/index.html) | | ggeffects | 1.3.2 | [https://cran.r-project.org/web/packages/ggeffects/index.html](https://cran.r-project.org/web/packages/ggeffects/index.html) | | ggpubr | 0.6.0 | [https://cran.r-project.org/web/packages/ggpubr/index.html](https://cran.r-project.org/web/packages/ggpubr/index.html) | | emmeans | 1.8.9 | [https://cran.r-project.org/web/packages/emmeans/index.html](https://cran.r-project.org/web/packages/emmeans/index.html) | | visreg | 2.7.0 | [https://cran.r-project.org/web/packages/visreg/index.html](https://cran.r-project.org/web/packages/visreg/index.html) | | rr2 | 1.1.1 | [https://cran.r-project.org/web/packages/rr2/index.html](https://cran.r-project.org/web/packages/rr2/index.html) | | sjPlot | 2.8.15 | [https://cran.r-project.org/web/packages/sjPlot/index.html](https://cran.r-project.org/web/packages/sjPlot/index.html) | | lme4 | 1.1-35 | [https://cran.r-project.org/web/packages/lme4/index.html](https://cran.r-project.org/web/packages/lme4/index.html) | | Matrix | 1.6-1.1 | [https://cran.r-project.org/web/packages/Matrix/index.html](https://cran.r-project.org/web/packages/Matrix/index.html) | | DHARMa | 0.4.6 | [https://cran.r-project.org/web/packages/DHARMa/index.html](https://cran.r-project.org/web/packages/DHARMa/index.html) | | glmmTMB | 1.1.8 | [https://cran.r-project.org/web/packages/glmmTMB/index.html](https://cran.r-project.org/web/packages/glmmTMB/index.html) | | mgcViz | 0.1.11 | [https://cran.r-project.org/web/packages/mgcViz/index.html](https://cran.r-project.org/web/packages/mgcViz/index.html) | | qgam | 1.3.4 | [https://cran.r-project.org/web/packages/qgam/index.html](https://cran.r-project.org/web/packages/qgam/index.html) | | mgcv | 1.8-42 | [https://cran.r-project.org/web/packages/mgcv/index.html](https://cran.r-project.org/web/packages/mgcv/index.html) | | nlme | 3.1-162 | [https://cran.r-project.org/web/packages/nlme/index.html](https://cran.r-project.org/web/packages/nlme/index.html) | | RColorBrewer | 1.1-3 | [https://cran.r-project.org/web/packages/RColorBrewer/index.html](https://cran.r-project.org/web/packages/RColorBrewer/index.html) | | lubridate | 1.9.3 | [https://cran.r-project.org/web/packages/lubridate/vignettes/lubridate.html](https://cran.r-project.org/web/packages/lubridate/vignettes/lubridate.html) | | forcats | 1.0.0 | [https://cran.r-project.org/web/packages/forcats/index.html](https://cran.r-project.org/web/packages/forcats/index.html) | | stringr | 1.5.0 | [https://cran.r-project.org/web/packages/stringr/index.html](https://cran.r-project.org/web/packages/stringr/index.html) | | dplyr | 1.1.3 | [https://cran.r-project.org/web/packages/dplyr/vignettes/dplyr.html](https://cran.r-project.org/web/packages/dplyr/vignettes/dplyr.html) | | purrr | 1.0.2 | [https://cran.r-project.org/web/packages/purrr/index.html](https://cran.r-project.org/web/packages/purrr/index.html) | | readr | 2.1.4 | [https://cran.r-project.org/web/packages/readr/index.html](https://cran.r-project.org/web/packages/readr/index.html) | | tidyr | 1.3.0 | [https://cran.r-project.org/web/packages/tidyr/index.html](https://cran.r-project.org/web/packages/tidyr/index.html) | | tibble | 3.2.1 | [https://cran.r-project.org/web/packages/tibble/index.html](https://cran.r-project.org/web/packages/tibble/index.html) | | ggplot2 | 3.4.4 | [https://cran.r-project.org/web/packages/ggplot2/index.html](https://cran.r-project.org/web/packages/ggplot2/index.html) | | tidyverse | 2.0.0 | [https://cran.r-project.org/web/packages/tidyverse/index.html](https://cran.r-project.org/web/packages/tidyverse/index.html) |