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Correction: Spatial and seasonal determinants of arthropod community composition across an agro-ecosystem landscape

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Publication: FACETS
7 February 2025
Ref: FACETS 9:1–15 (2024) | https://doi.org/10.1139/facets-2023-0051
This article was originally published with mismatched figure legends for Figs. 3, 4, 5, 6, 7, and 8.  This has been corrected and figures now display with their correct corresponding legends.        
Fig. 1.
Fig. 1. Map of the study sites in southern Ontario. Landcover data were obtained from the 2019 Annual Crop Inventory, which classifies landcover types from satellite images with 30 m spatial resolution using decision tree algorithms (Agriculture and Agri-Food Canada 2020). Mapping is based on a Lambert projection with longitude/latitude coordinate system.
Fig. 2.
Fig. 2. Distribution of arthropod BINs (Barcode Index Number; a species proxy) for (A) the top six most species-rich orders of arthropods across all samples and (B) among sample periods pooled across all traps.
Fig. 3.
Fig. 3. Scatter-plots of all standardized variables used in the structural equation models (A = Δ arthropod community, B = Δ plant community, C = Δ space, D = Δ time, E = Δ canopy cover, F = Δ agricultural extent, G = Δ plant species richness, H = Δ weather PCA1, I = Δ weather PCA 2, J = Δ weather PCA 3, and J = Δ weather PCA 4.
Fig. 4.
Fig. 4. Path analysis of standardized variables influencing spatiotemporal Sørensen dissimilarity of arthropod community composition. Only significant paths are shown. Values correspond to standardized path coefficients, and values towards or away from variable groups (e.g., weather) represent the sum of the absolute values of standard path coefficients for each variable within those groups (including direct and indirect effects). Arrow thickness is proportionate to the magnitude of the standardized path coefficients.
Fig. 5.
Fig. 5. Partial regression plots for the effect of all variables in the path analysis on spatiotemporal arthropod Sørensen dissimilarity. PC1–PC4 are principal components of the weather variables. All variables are standardized.
Fig. 6.
Fig. 6. Path analysis of variables influencing spatiotemporal Sørensen dissimilarity of arthropod community composition. PC1–4 are principal components of the weather variables. Values correspond to standardized path coefficients. Only significant paths are shown. Arrow thickness is proportionate to the magnitude of the standardized path coefficients.
Fig. 7.
Fig. 7. Regression-based variance partitioning results for the effect of distances in environment, space, and time on arthropod Sørensen dissimilarities. Numbers are adjusted R2 values and the results showing the relative effects of plant community attributes, weather, and agricultural extent across the local landscape are conditional on the effects of space and time.
Fig. 8.
Fig. 8. Partial regression plots for the effect of all variables (except Δ plant community) in the path analysis on spatiotemporal arthropod Sørensen dissimilarity. PC1–PC4 are principal components of the weather variables. All variables are standardized.

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cover image FACETS
FACETS
Volume 10January 2025
Pages: 1 - 7

History

Received: 5 December 2024
Accepted: 5 December 2024
Version of record online: 7 February 2025

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P. Burgess
Department of Integrative Biology, University of Guelph, Guelph, ON N1G 2W1, Canada
G.S. Betini
Department of Integrative Biology, University of Guelph, Guelph, ON N1G 2W1, Canada
A. Cholewka
Department of Integrative Biology, University of Guelph, Guelph, ON N1G 2W1, Canada
J.R. deWaard
Centre for Biodiversity Genomics, University of Guelph, Guelph, ON N1G 2W1, Canada
School of Environmental Sciences, University of Guelph, Guelph, ON N1G 2W1, Canada
S. deWaard
Centre for Biodiversity Genomics, University of Guelph, Guelph, ON N1G 2W1, Canada
C. Griswold
Department of Integrative Biology, University of Guelph, Guelph, ON N1G 2W1, Canada
P.D.N. Hebert
Department of Integrative Biology, University of Guelph, Guelph, ON N1G 2W1, Canada
Centre for Biodiversity Genomics, University of Guelph, Guelph, ON N1G 2W1, Canada
A. MacDougall
Department of Integrative Biology, University of Guelph, Guelph, ON N1G 2W1, Canada
K.S. McCann
Department of Integrative Biology, University of Guelph, Guelph, ON N1G 2W1, Canada
J. McGroarty
Department of Integrative Biology, University of Guelph, Guelph, ON N1G 2W1, Canada
E. Miller
Department of Integrative Biology, University of Guelph, Guelph, ON N1G 2W1, Canada
K. Perez
Centre for Biodiversity Genomics, University of Guelph, Guelph, ON N1G 2W1, Canada
S. Ratnasingham
Department of Integrative Biology, University of Guelph, Guelph, ON N1G 2W1, Canada
Centre for Biodiversity Genomics, University of Guelph, Guelph, ON N1G 2W1, Canada
C. Reisiger
Department of Integrative Biology, University of Guelph, Guelph, ON N1G 2W1, Canada
D. Steinke
Department of Integrative Biology, University of Guelph, Guelph, ON N1G 2W1, Canada
Centre for Biodiversity Genomics, University of Guelph, Guelph, ON N1G 2W1, Canada
E. Wright
Department of Integrative Biology, University of Guelph, Guelph, ON N1G 2W1, Canada
E. Zakharov
Department of Integrative Biology, University of Guelph, Guelph, ON N1G 2W1, Canada
Centre for Biodiversity Genomics, University of Guelph, Guelph, ON N1G 2W1, Canada
Department of Integrative Biology, University of Guelph, Guelph, ON N1G 2W1, Canada

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