DOI: 10.5061/dryad.t76hdr7xh
title: Configurational crop heterogeneity increases within-field plant diversity

description: 1. Increasing landscape heterogeneity by restoring semi-natural elements
 to reverse farmland biodiversity declines is not always economically
 feasible or acceptable to farmers due to competition for land. We
 hypothesized that increasing the heterogeneity of the crop mosaic itself,
 hereafter referred to as crop heterogeneity, can have beneficial effects
 on within-field plant diversity. 2. Using a unique multi-country dataset
 from a cross-continent collaborative project covering 1451 agricultural
 fields within 432 landscapes in Europe and Canada, we assessed the
 relative effects of compositional and configurational crop heterogeneity
 on within-field plant diversity components. We also examined how these
 relationships were modulated by the position within the field. 3. We found
 strong positive effects of configurational crop heterogeneity on
 within-field plant alpha and gamma diversity in field interiors. These
 effects were as high as the effect of semi-natural cover. In field
 borders, effects of crop heterogeneity were limited to alpha diversity. We
 suggest that a heterogeneous crop mosaic may overcome the high negative
 impact of management practices on plant diversity in field interiors,
 whereas in field borders, where plant diversity is already high, landscape
 effects are more limited. 4. Synthesis and applications. Our study shows
 that increasing configurational crop heterogeneity is beneficial to
 within-field plant diversity. It opens up a new effective and
 complementary way to promote farmland biodiversity without taking land out
 of agricultural production. We therefore recommend adopting manipulation
 of crop heterogeneity as a specific, effective management option in future
 policy measures, perhaps adding to agri-environment schemes, to contribute
 to the conservation of farmland plant diversity.
description: <i>Region and landscape
 selection</i> The study was
 conducted in eight agricultural regions comprising seven regions in Europe
 and one region in eastern Canada (near <i>Ottawa</i>). The
 European regions followed a south-to-north gradient, with four regions in
 France (near <i>Arles</i>, <i>Niort</i>,
 <i>Rennes</i>, <i>Toulouse</i>), one in England
 (centred on <i>Ely</i>, Cambridgeshire), one in Germany (near
 <i>Goettingen</i>) and one in Spain (near
 <i>Lleida</i>; Fig. 1). Within these agricultural regions, we
 selected a total of 432 1 km × 1 km landscapes, with 60 to 90 % of crop
 cover in each. These landscapes represented, by design, uncorrelated
 gradients of compositional crop heterogeneity, assessed by the Shannon
 diversity index of the crop cover types, and of configurational crop
 heterogeneity, assessed by the total length of crop field borders (see
 Pasher et al., 2003 and Sirami et al., 2019 for details). The landscape
 selection process used the most recent remotely sensed data or land cover
 map available for each agricultural region (see Table S1 in Supporting
 Information). While land cover maps were adequate for landscape
 selection, their coarse spatial resolution did not allow for the accurate
 delineation of narrow strips of non-crop covers between fields. Thus, all
 landscapes were digitized from aerial photos to create detailed maps
 delineating all fields managed for agricultural production (including
 crops, and temporary and permanent grasslands), linear semi-natural
 boundaries between crop fields and non-crop patches. Non-crop cover types
 included woodland, open land, wetland and built-up areas. Linear
 semi-natural boundaries included hedgerows, grassy strips and watery
 boundaries such as ditches. These maps were visually validated by field
 crews within each agricultural region before the sampling of the
 vegetation in a given landscape. Based on
 these more accurate and recent maps, several landscape variables were
 calculated. Compositional crop heterogeneity was assessed using the
 Shannon diversity index of agricultural cover types
 (<em>Crop_SHDI</em>). Configurational crop heterogeneity was
 measured as the total field border length (<i>Crop_TBL</i>).
 <i>Crop_TBL</i> was the sum of perimeters of all fields within
 the 1 x 1 km landscape minus the length of perimeters artificially created
 by intersection with the limits of the 1 km × 1 km landscape. The
 percentage of semi-natural cover types (<i>Seminat_Cover</i>)
 was calculated as the sum of the proportions of woodland, open land and
 wetland in the landscape. The length of semi-natural boundaries
 (<i>Seminat_bound</i>ary) was calculated as half of the sum of
 the perimeter of woody, grassy and watery boundaries in the
 landscape. <i>Sampling site (field)
 selection</i> Within each
 landscape, we selected three to four sampling sites. Sampling sites were
 fields managed for agricultural production including crops, temporary and
 permanent grasslands. Fields were selected such that at least one
 contained the dominant crop type in the region, the other fields being
 representative of crops present within the focal landscape. Fields were at
 least 200 m apart, at least 50 m away from the border of the 1 km × 1 km
 landscape and at least 50 m away from large non-crop cover type patches
 such as woodland. We selected fields bordered by a similar boundary types
 within each region, i.e. only grassy strips or hedgerows, wherever
 possible. In total, 1451 agricultural fields were sampled. <i>Vegetation sampling</i> Within each
 sampling site, we surveyed within-field plant species along two parallel,
 1 m wide and 50 m long transects, one located on the field border, the
 other within the field interior resulting in 2788 transects surveyed.
 Transects were about 25 m distant from each other. We sampled five plots
 (4 m × 1 m) along each transect, i.e. 20 m² per transect. Note that in
 <i>Ottawa</i>, transects were 2 m wide and the field border
 transect encompassed part of the boundary vegetation. We verified that
 this slight difference in sampling protocol did not affect our
 conclusions. Percentage cover of all vascular plant species was recorded.
 We conducted these plant surveys over two years between 2011 and 2014,
 each sampling site being sampled only within a single year. Surveys were
 conducted once before crop harvesting, except in <i>Ely</i>,
 <i>Goettingen</i> and <i>Ottawa</i> where surveys
 were conducted twice. In those regions, we pooled within-field plant data
 from the two visits per year and retained the total number of plant
 species for each sampled plot. Plant nomenclature followed TaxRef
 (Gargominy et al., 2014). <i>Data
 processing</i> Following
 Whittaker (1972), we used the multiplicative diversity partitioning method
 to assess plant species diversity components where β = γ/α. Gamma
 diversity (γ) was the total number of species across all plots sampled in
 a given transect and alpha (α) diversity was the number of within-field
 plant species present in each plot averaged across the five plots per
 transect. This measure of beta diversity (β) describes variation in plant
 species composition in the whole transect by comparison with an average
 plot.
description: Read-me: Field (column) name
 Description 
 Year       
 Year of point
 count : 2011, 2012, 2013 or 2014 Region  
 Region of point
 count Study site          
 Name of the
 nearest big city Landscape         
 Landscape ID
 sampled (1km²) Field      
 Sampling site ID
 sampled (field) Transect             
 Sampling
 transect (border “B”/center “C” of the field) 
 Gamma 
 Total number of
 species across all plots sampled in a given transect 
 Alpha    
 Number of
 within-field plant species present in each plot averaged across the five
 plots per transect Beta      
 Its was
 calculated as Gamma/Alpha. It describes variation in plant species
 composition in the whole transect by comparison with an average
 plot Crop      
 Crop
 sampled Boundary           
 Type of
 boundary Crop_SHDI        
 Shannon
 diversity index of agricultural cover types within the 1 x 1 km
 landscape Crop_TBL           
 Sum of
 perimeters of all fields within the 1 x 1 km landscape minus the length of
 perimeters artificially created by intersection with the limits of the 1
 km × 1 km landscape Woodland_Cover           Percentage of woodland cover within the 1 x 1 km landscape Open_Cover     Percentage of open cover within the 1 x 1 km landscape Water_Cover    Percentage of water cover within the 1 x 1 km landscape Seminat_Cover Percentage of semi-natural cover within the 1 x 1 km landscape. It was calculated as the sum of the proportions of woodland, open land and wetland in the landscape. Built_area_Cover            Percentage of built area cover within the 1 x 1 km landscape Crop_Cover       Percentage of crop cover within the 1 x 1 km landscape Non_Crop_Cover           Percentage of non crop cover within the 1 x 1 km landscape Bare_ground_boundary_m                Total length of bare ground boundaries within the 1 x 1 km landscape Grassy_boundary_m    Total length of grassy boundaries within the 1 x 1 km landscape Track_boundary_m       Total length of track boundaries within the 1 x 1 km landscape Woody_boundary_m   Total length of woody boundaries within the 1 x 1 km landscape Watery_boundary_m   Total length of water boundaries within the 1 x 1 km landscape Seminat_boundary        Total length of semi-natural boundaries. It was calculated as half of the sum of the perimeter of woody, grassy and watery boundaries in the landscape Total_boundary_m        Total length of boundaries within the 1 x 1 km landscape