A land classification protocol for pollinator ecology research: An urbanization case study

Abstract

Land-use change is one of the most important drivers of widespread declines in pollinator populations. Comprehensive quantitative methods for land classification are critical to understanding these effects, but co-option of existing human-focussed land classifications is often inappropriate for pollinator research. Here, we present a flexible GIS-based land classification protocol for pollinator research using a bottom-up approach driven by reference to pollinator ecology, with urbanization as a case study. Our multistep method involves manually generating land cover maps at multiple biologically relevant radii surrounding study sites using GIS, with a focus on identifying land cover types that have a specific relevance to pollinators. This is followed by a three-step refinement process using statistical tools: (i) definition of land-use categories, (ii) principal components analysis on the categories, and (iii) cluster analysis to generate a categorical land-use variable for use in subsequent analysis. Model selection is then used to determine the appropriate spatial scale for analysis. We demonstrate an application of our protocol using a case study of 38 sites across a gradient of urbanization in South-East England. In our case study, the land classification generated a categorical land-use variable at each of four radii based on the clustering of sites with different degrees of urbanization, open land, and flower-rich habitat. Studies of land-use effects on pollinators have historically employed a wide array of land classification techniques from descriptive and qualitative to complex and quantitative. We suggest that land-use studies in pollinator ecology should broadly adopt GIS-based multistep land classification techniques to enable robust analysis and aid comparative research. Our protocol offers a customizable approach that combines specific relevance to pollinator research with the potential for application to a wide range of ecological questions, including agroecological studies of pest control.

Keywords: GIS; agricultural pest control; anthropogenic stressors; bees; land classification; land‐use change; pollinator; urbanization.

Figure 1

Overview of the multistep protocol presented for land classification in pollinator ecology research

Figure 2

Location of 38 sites in SE England for which land classification was carried out using the protocol presented here

Figure 3

Illustration of the steps involved in manually generating a land cover map for a 750 m radius around a study site in QGIS, using an example site in the suburban region to the southwest of London, UK. (a) The first step involves drawing polygons around each land cover patch at a set scale (1:5,000 m in agricultural areas or 1:2,500 m in built‐up areas) to split the data layer into a series of features representing each patch. (b) Each patch is visually classified to one of 80 land cover classes; for color legend, see Appendix S1. (c) The buffer is clipped to multiple radii representing different spatial scales at which the study taxon may interact with the surrounding land based on ecology of the organism

Figure 4

Land cover maps at a 750 m radius (inset circles) were generated for 38 sites in South‐East England; four representative sites across a gradient of urbanization are shown (large inset circles). Yellow circles indicate locations of sites

Figure 5

Eigenvector scores on principal components that captured approximately 85% of the variation in a principal component analysis (PCA) performed on land‐use variables classified at each of four radii around each study site (two‐letter codes). The clustering of the land‐use types generated from subsequent cluster analysis (Figure 6) is illustrated in the grouping of PC scores, shown here separated by shaded boxes (determined by the later cluster analysis). For example, at the 500 m radius (b), the “City” cluster (far left) is typified by a positive score on PC1 and neutral score on PC2, “Village” by positive to neutral PC1 and negative PC2, and “Agricultural” (far right) by negative PC1 and PC2. Inset circles show land cover maps at the relevant radius for representative sites for each group

Figure 6

Cluster dendrograms of land use of 38 sites at a 750, 500, 250 and 100 m radii. Cluster analyses using Ward's method were performed on a set of principal components describing land use to group sites into categorical land‐use types (red boxes), which were given descriptive names from the landscape to the local scale. At the terminus of each branch, the two‐letter site name is given with an image of the GIS land cover map (see Appendix S1 for color legend)