Context matters: the landscape matrix determines the population genetic structure of temperate forest herbs across Europe

Abstract

Context: Plant populations in agricultural landscapes are mostly fragmented and their functional connectivity often depends on seed and pollen dispersal by animals. However, little is known about how the interactions of seed and pollen dispersers with the agricultural matrix translate into gene flow among plant populations.

Objectives: We aimed to identify effects of the landscape structure on the genetic diversity within, and the genetic differentiation among, spatially isolated populations of three temperate forest herbs. We asked, whether different arable crops have different effects, and whether the orientation of linear landscape elements relative to the gene dispersal direction matters.

Methods: We analysed the species' population genetic structures in seven agricultural landscapes across temperate Europe using microsatellite markers. These were modelled as a function of landscape composition and configuration, which we quantified in buffer zones around, and in rectangular landscape strips between, plant populations.

Results: Landscape effects were diverse and often contrasting between species, reflecting their association with different pollen- or seed dispersal vectors. Differentiating crop types rather than lumping them together yielded higher proportions of explained variation. Some linear landscape elements had both a channelling and hampering effect on gene flow, depending on their orientation.

Conclusions: Landscape structure is a more important determinant of the species' population genetic structure than habitat loss and fragmentation per se. Landscape planning with the aim to enhance the functional connectivity among spatially isolated plant populations should consider that even species of the same ecological guild might show distinct responses to the landscape structure.

Supplementary information: The online version contains supplementary material available at 10.1007/s10980-021-01376-7.

Keywords: Arable crops; Dispersal vectors; Functional connectivity; Genetic differentiation; Genetic diversity; Linear landscape elements.

Fig. 1

Overview on the study design. The seven 5 × 5 km² landscape windows (a) are spread across temperate Europe from North France (A) over Belgium (B), West Germany (C), East Germany (D), and South Sweden (E) up to Central Sweden (F) and Estonia (G). In each agricultural landscape, we surveyed up to six populations of each species, here exemplified for Polygonatum multiflorum in East Germany (b). See Supp. Inf. 1 for detailed land-use maps of each landscape window, including locations of all sampled populations. The landscape surrounding the populations was analysed at the node level, i.e., in buffer zones of distances between 125 and 2000 m (c), and at the link level, i.e. in landscape strips between populations with width-to-length ratios between 1:7 and 2:3 (d). For linear landscape elements within buffer zones and landscape strips, we calculated not only the total length (t), but also the parallel (p) and orthogonal (o) length component in relation to the gene dispersal direction

Fig. 2

Visualization of landscape effects (cf. Tables 2 and 3) on population genetic variables of Anemone nemorosa, Oxalis acetosella and Polygonatum multiflorum. Shown are those effects, which are directly related to our hypotheses and therefore discussed in the main text. Panels display the partial slopes and residuals as well as the 95% confidence band. All variables are scaled in standard deviation units. Colours of partial residuals represent the different landscape windows: France (Fra), Belgium (Be), West Germany (GeW), East Germany (GeE), South Sweden (SwS), Central Sweden (SwC), and Estonia (Est). Population genetic variables are allelic richness (A_r), expected (H_e) and observed heterozygosity (H_o), inbreeding index (F), and genetic differentiation (D_PS). The landscape metrics ARABLE, FOREST, MAIZE, RAPE, and SETTLE refer to the percent cover of arable land, deciduous forest, maize, oilseed rape and settlement area, respectively. LWOOD and LROAD refer to the relative length of hedgerows/tree lines and roads, respectively. pcSETTLE is a principal component reflecting settlement area, road density and edge density (cf. Table 2). pcARABvsGRASS is a principal component reflecting the trade-off between arable land (cereals and oilseed rape) on the one hand and grassland on the other hand (cf. Table 2). Numbers or ratios added to the variable names correspond to the most influential buffer distance in meters or the most influential width-to-length radio of the landscape strips, respectively

Fig. 3

Visualizations of interactive effects (cf. Tables 2 and 3) of landscape metrics (x- and y-axis) on population genetic variables of Anemone nemorosa, Oxalis acetosella and Polygonatum multiflorum as heatmap. Only the area covered by the values of both explanatory variables (overlaid as points) is plotted. All variables are scaled in standard deviation units. Population genetic variables are measures of genetic differentiation (D_PS and G’’_ST) and observed heterozygosity (H_O). The landscape metrics FOREST and RAPE refer to the percent cover of deciduous forest and oilseed rape, respectively. LROAD, LWATER and LWOOD refer to the relative length of roads, water courses and hedgerows/treelines, respectively. The prefix O:P refers to orthogonal-to-parallel length ratio. pcARABvsGRASS is a principal component reflecting the trade-off between arable land (cereals and oilseed rape) on the one hand and grassland on the other hand (cf. Table 3). Numbers or ratios added to the variable names correspond to the most influential buffer distance in meters or the most influential width-to-length radio of the landscape strips, respectively