Given the results of Chapter 4, more research into the temporal component of genetic variation would be insightful. Additional research into factors determining the detection of any short term temporal genetic variation would also be useful, for example, scale, sample size and the magnitude of genetic differentiation.
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The relative importance of spatial and temporal processes influencing genetic variation will change with spatial scale. This has been acknowledged by several authors who have
highlighted, mostly with reference to various spatial scales, that sampling should take place at the scale at which possible processes structuring genetic variation are likely to operate (Cushman and Landguth, 2010b; Manel et al., 2010). The need for appropriate sampling regimes at an appropriate spatial scale has been empirically demonstrated by Murphy et
al.(2010), who reported that, for western toads (Bufo boreas), factors related to connectivity
provision varied in importance with spatial scale. Appropriate temporal scales for sampling should be given further consideration.
As two aspects of scale, several authors have suggested that grain size and the extent of sampling in landscape genetic studies are influential in the detection of landscape genetic patterns (Figure 6.4) (Anderson et al. 2010; Cushman and Landguth, 2010b). The grain describes the smallest unit of sampling, whereas the extent describes the total area sampled (Anderson et al., 2010). These two aspects of spatial scale can be translated to temporal scales; grain would describe the smallest unit of sampling in space and extent could relate to the length of time over which sampling occurs. Both of these were shown to have an effect on landscape genetic analyses by Cushman and Landguth (2010b), when spatial genetic patterns across a landscape were simulated and the grain and extent of sampling altered to determine the effect on the pattern–process interaction. These two aspects in a temporal context should be considered in future landscape genetics studies.
Figure 6.4 Schematic taken from Anderson et al. (2010) illustrating the difference between a) grain and b) spatial extent. The dotted lines show the grain of sampling and the solid line shows the extent for a sequence of sampling scales.
125 The exact influence of a mismatch between the temporal scale of sampling and the scale of processes structuring genetic variation is largely unknown (Anderson et al., 2010; Cushman and Landguth, 2010b) but it could have various non-intuitive effects on the detection of patterns in genetic variation. For example, there could be a point at which a spatial process (such as geographical separation) is overwhelmingly dominant, leading to it being solely responsible for an uppermost level of hierarchical genetic structure, resulting in temporal variation by short term processes not being detected. Additionally, Manel et al. (2010) suggested that inadequate sampling at the appropriate scales could alter the noise to signal ratio, meaning that genetic patterns would be less obvious and difficult to interpret. Other outcomes of a sampling-process scale mismatch are possible and further work would be needed to identify the effect of temporal variation on detecting both spatial and temporal genetic variation patterns at different scales.
Additional factors that could affect the possibility of detecting temporal variation in genetic structure are sample size and the extent of genetic differentiation between populations. Smith and Wang (2014) recently used simulations to demonstrate that the ability of Bayesian-
clustering software to detect subtle genetic clusters was influenced by these two factors. Adequate sampling, guided by Smith and Wang’s (2014) study, at the appropriate grain would improve the chance of detecting patterns but it could be helpful if future studies could acknowledge temporal differentiation in investigations about appropriate sample sizes. To gain a more comprehensive understanding of the relative importance of temporal and spatial genetic variation and factors determining the detection of a temporal component to genetic variation, additional landscape genetic field studies at multiple spatial and temporal scales could be insightful. For demonstration purposes, further simulation studies are also likely to be helpful since noise can be more readily controlled and variables can be altered easily, without the need for time and cost intensive field sampling at multiple scales.
6.4.3 Relative effects of agricultural processes on genetic variation
The possible role of agricultural disturbance in altering spatial genetic structure was discussed in Chapter 4, since the shift in spatial arrangement of individuals occurred alongside the harvesting of crops. Initially, it would be useful to introduce a control site to address this definitively.
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If agricultural disturbance was one of the main drivers behind the temporal variation in spatial genetic structure observed in Chapter 4, it would be interesting to compare the relative disturbance effects of different agricultural management processes, such as ploughing, harvesting, sowing, and application of pesticides and fertiliser. It would also be insightful to examine the extent to which different features of adequate field margins can offset temporal variation, for example, margin width.
In Chapter 4, the fate of cluster A, B and C differed and it would be interesting to determine the extent to which temporal variation in population structure is random or deterministic. If it was partly deterministic, then factors predicting the outcome of disturbance would be worth investigating. This research would be challenging and costly since intensive sampling at multiple field sites would be required in order to compare different treatments. The timing of agricultural processes would also need to be tightly controlled on a large scale so that the effect of disturbance processes acting on a larger scale, did not affect the genetic structure of the field site being examined.