The native plant restoration industry, as a matter of urgency, requires accurate, powerful and practical provenance information to guide seed collection strategies. Current published guidelines (e.g. Mortlock 1999, 2000) are an important contribution, but can be in error for individual species. Ultimately, a rapid yet powerful genetic approach can best generate the required guidelines within realistic timeframes. We suggest that the combination of the efficiency of AFLP with a minimal sampling approach and data analysis by multivariate spatial autocorrelation is, in principle, capable of filling this need.
delineation of provenance
For a total sample of genotypes, spatial autocorrelation analysis addresses the question ‘Are genotypes in closer physical proximity any more similar than those with greater physical separation?’. For Dryandra lindleyana, Lomandra hermaphrodita and Bossiaea ornata, a spatial autocorrelation analysis of multilocus AFLP data has identified a positive genetic correlation between individuals, significantly greater than r permuted over all samples, at the smallest distance classes of 20 km, 13 km and 15 km, respectively, within the sampled jarrah forest distribution. Additionally, ‘patch’ size diameter, interpreted here as the distance where the correlogram goes from positively significant to non-significant, was 26 km, 20 km and 20 km, respectively. It follows that the radii of the patch size was 13 km, 10 km and 10 km, respectively. The radius of the patch size is here interpreted as the maximum provenance distance to delineate the seed collection locality from the revegetation site. Beyond these distances, no significant genetic structure was observed. These correlograms are examples of a stabilizing profile (Diniz-Filho & Telles 2002). Stabilizing profiles indicate that there is a combination of high and low genetic divergence between samples at the larger distance classes, due to the stochasticity of the evolutionary processes involved (Epperson 1993).
Somewhat surprisingly, no evidence for genetic structuring was found for Lechenaultia biloba at any distance class, suggesting a broad provenance encompassing the entire sampled area. Alternatively, significant genetic structuring may be found at a spatial scale below the resolution of the current study, suggesting that a provenance distance lies below the resolution of the current sampling. Indeed, this might be expected given the life-history characteristics of L. biloba, which is known to generate very little seed, is characteristically long-lived, highly successful at re-sprouting after a fire and exhibits a marked ability to form clones. Poor sexual reproduction may in part contribute to low genetic variation and an absence of detectable population structuring at the scales assessed in this study. The apparent absence of genetic structure over this spatial scale may be a consequence of fewer polymorphic markers than detected for the other species, and therefore a reduction in power to detect a positive relationship where present. The number of markers generated is due to a number of variables, and includes the amount of variation present within the species, the size of the genome, and the primer pairs used. However, the weakness of any relationship suggests that even with more markers, a positive relationship between genetic distance and geographical distance at this scale appears unlikely. We are currently conducting further studies to address these issues, through an assessment of clonality and genetic divergence among populations.
These results have important practical implications. The estimated provenance distances for Dryandra lindleyana, Lomandra hermaphrodita and Bossiaea ornata are approximately half those currently applied by the revegetation practitioners who commissioned this work. Past experience has shown that it will be extremely difficult for the mining companies to collect sufficient seed in these relatively small areas to successfully revegetate at the necessary scale (c. 500 ha year−1). In the early 1990s, both Alcoa and Worsley recognized the importance of conserving genetic diversity in its restored mines and drew up seed collecting zones for each mine. No genetic information was available at that time so the boundaries of these seed provenances were selected, conservatively, and based on practical boundaries. For Alcoa, the boundaries were about 20 km radius from each mine. The Huntly seed collection zone for example is approximately 900 km2. For Worsley, the areas agreed with government from which seed is collected are up to 30 km from the mine. The results of this study, if applied strictly, would reduce the collecting zone for Lomandra hermaphrodita, for example, to 314 km2. Availability of seed is affected by many factors, especially burning history and it is already difficult to collect sufficient seed of many species in the current seed collecting zones. Also the possible impact of more intense seed collecting in smaller areas needs to be considered. The geographical extent of each mine is also larger than the smaller of these zones. All of these factors need to be addressed when reviewing seed collection provenance.
We have defined a local provenance distance on the basis of an assumed linear connection between the significantly positive distance class and the subsequent non-significant distance class, which may be in error. A more conservative approach is to interpret the upper limit of the largest significantly positive distance class as the provenance distance (Diniz-Filho & Telles 2002). These diameters were 20 km, 13 km and 15 km (radii of 10 km, 6·5 km and 7·5 km) for Dryandra lindleyana, Lomandra hermaphrodita and Bossiaea ornata, respectively. This was the smallest distance class in each case, which was determined by the intensity of sampling and the minimum criterion of at least 30 pairs of individuals in each distance class. This smallest distance class is clearly arbitrary and suggests that at least two smallest significant distance classes be a minimum criterion for the application of this definition of provenance.
Alternatively, patch size is determined from the first x-intercept (Diniz-Filho & Telles 2002; Escudero et al. 2003). However, in a profile that stabilizes close to r = 0, the exact intercept can be ambiguous. For example, the correlogram for Lomandra hermaphrodita with equal distance classes at 13 km, shows a near intercept at 26 km, significantly smaller than the actual intercept at 42 km. Re-analysing with equal distance classes of 14 km shows a first x-intercept of 21 km. Re-analysing with equal distance class sizes of 15 km, 17 km and 19 km revealed first x-intercepts and distances where the correlograms go from significant to not significant to be similar (but not identical) to those of the original correlogram.
Consequently, a robust delineation of patch size distance by spatial autocorrelation analysis, as opposed to merely identifying the existence of genetic spatial structure, is tenuous because it is dependent on the properties of sampling and analysis. Our results showed no significant genetic structuring beyond the smallest distance classes, suggesting that sampling of populations at larger distances is inefficient. Additionally, a more precise provenance distance, or the suggestion of a very narrow provenance distance, could not be adequately resolved due to limited sampling at these smaller distances. Increased sampling should lead to a finer division of the continuous space into more discrete distance classes, more than one significant distance class in the presence of structure, greater stability in the shape of the correlogram and the delineation of patch size, as well as reducing the error around r. We are currently conducting further research to more carefully assess an appropriate minimal sampling strategy, given that an ultimate objective is to expeditiously generate provenance information for many species. However, the results of this study suggest that future sampling will be more efficient by doubling sampling intensity at the smaller geographical scales and reducing the maximum distance between sample locations to approximately 60 km. The variation in correlograms generated from genetic data from different AFLP primer pairs is another way of assessing the robustness of a single correlogram. Further discussion of the limitations and benefits of spatial autocorrelation in the context of identifying operational units across continuous populations can be found in Diniz-Filho & Telles (2002).
Spatial genetic variation is highly scale dependent, and conclusions drawn from spatial autocorrelation (and indeed any spatial analysis) are in the context of the scale of sampling and the spatial limits of the study, rather than in an absolute sense (Heywood 1991; Escudero et al. 2003). For example, spatial autocorrelation has been typically used to identify relationships between genetic and geographical distance over much smaller (metres rather than kilometres) scales (Smouse & Peakall 1999; Gonzalez-Martinez et al. 2002; Miyamoto, Kuramoto & Yamada 2002). Patch size on this scale is often interpreted as an isolation by distance effect due to the restricted dispersal of seed and pollen (Hardy & Vekemans 1999). It is therefore likely that a patch size in metres rather than kilometres may be found following a spatial autocorrelation analysis over a scale of tens to hundreds of metres for the four species studied here. Similarly, reducing the spatial limits of this study will probably reduce the patch size. Consequently, there are intriguing issues regarding the identification, and biological significance, of patch size over different scales, and the consequences for provenance, that require further research and a balance between practical outcomes and conservation in achieving best practise in native plant community restoration. New tools for the spatial analysis of genetic diversity for plant conservation and restoration (Escudero et al. 2003) offer novel opportunities for addressing these issues.
While we have interpreted our results in the context of delineating a local genetic provenance, it is important to qualify the interpretation of these results. Genetic similarity between any two populations within the local provenance distance cannot necessarily be assumed. This may especially be so if a species is distributed over an environmental mosaic (e.g. variation in substrate, aspect and altitude). In this case, habitat matching may be critical, and should be applied in conjunction with these genetic results. To identify whether any two specific populations are genetically differentiated, then a suitably large sample of plants per population is required. This has been our principal approach to provenance delineation to date (Krauss et al. 2000). However, the approach adopted here, where individual samples from many sites over a wide geographical range were analysed, is a compromise that provides a rapid and cost effective assessment of the general relationship between genetic distance and geographical distance for a first assessment of genetic provenance delineation. This approach is open to the criticisms levelled at a simple geographical distance approach. However, in a relatively homogeneous environment, such as the jarrah forest within which this study was conducted, such an approach is justifiable, especially when used with careful habitat matching within the delineated provenance distance. While we have not specifically addressed the causes of the significant spatial structure detected for three of four species, there were no obvious edaphic differences between sampled population sites. The importance of a significant east–west rainfall gradient (1200–740 mm) warrants further attention.
Beyond the practical issues associated with delineating provenance, there may be occasions where strict adherence to the local genetic provenance is undesirable (Lesica & Allendorf 1999; Wilkinson 2001). For example, Wilkinson (2001) questions the importance of using material of the local provenance in areas such as Europe and North America, which have been severely impacted by Quaternary climate change resulting in a dynamic recent vegetation history. Although the Quaternary history of the jarrah forest has not been studied in detail, the impacts of Quaternary climate change have been much less severe in south-west Australia, with no glaciation, generally cooler and drier conditions, but still significant winter rainfall during glacial maxima (Williams et al. 1998; Kershaw et al. 2003), suggesting a persistence of the sclerophyllous jarrah forest within much of its current range. Practical restoration provides a novel and powerful opportunity to assess these and other issues associated with the use of non-local provenance material (Holl et al. 2003). For example, we are now in a position to assess the consequences of using local vs. non-local seed, as defined in this study, as part of mine-site revegetation that will in turn provide the opportunity to assess the utility of the approach and results from this study.
While further research is required in a provenance context to address these issues, the continuation of the rapid delivery of provenance information to the native plant restoration industry, to achieve best practice in restoration and conservation objectives, is critical. Despite the problems discussed, the approach outlined here is an important and novel contribution to this objective.