Restoration of soils post-mining requires key solutions to complex issues through which the disturbance of topsoil incorporating soil microbial communities can result in a modification to ecosystem function. This research was in collaboration with Iluka Resources at the Jacinth-Ambrosia (J-A) mineral sand mine located in a semi-arid chenopod shrubland in southern Australia. At J-A, assemblages of microorganisms and microflora inhabit at least half of the soil surfaces and are collectively known as biocrusts. This research encompassed a polyphasic approach to soil microbial community profiling focused on "biobanking" viable cyanobacteria in topsoil stockpiles to facilitate rehabilitation. We found that cyanobacterial communities were compositionally diverse topsoil microbiomes. There was no significant difference in cyanobacterial community structure across soil types. As hypothesised, cyanobacteria were central to soil microprocesses, strongly supported by species richness and diversity. Cyanobacteria were a significant component of all three successional stages with 21 species identified from 10 sites. Known nitrogen-fixing cyanobacteria Symploca, Scytonema, Porphyrosiphon, Brasilonema, Nostoc, and Gloeocapsa comprised more than 50 % of the species richness at each site and 61 % of the total community richness. In the first study of its kind, we have described the response of cyanobacteria to topsoil stockpiling at various depths and ages. Cyanobacteria are moderately resilient to stockpiling at depth and over time, with average species richness greatest in the top 10 cm of the stockpiles of all ages and more viable within the first 6 weeks, indicating poten-tial for biocrust re-establishment. In general, the resilience of cyanobacteria to burial in topsoil stockpiles in both the short and long term was significant; however, in an arid environment recolonisation and community diversity could be impeded by drought. Biocrust re-establishment during mine rehabilitation relies on the role of cyanobacteria as a means of early soil stabilisation. At J-A mine operations do not threaten the survival of any of the organisms we studied. Increased cyanobacterial biomass is likely to be a good indicator and reliable metric for the re-establishment of soil microprocesses.
Effective grazing management in Australia’s semi-arid rangelands requires monitoring landscape conditions and identifying sustainable and productive practice through understanding the interactions of environmental factors and management of soil health. Challenges include extreme rainfall variability, intensifying drought, and inherently nutrient-poor soils. We investigated the impacts of grazing strategies on landscape function—specifically soil health—as the foundation for productive pastures, integrating the heterogenous nature of grass tussocks and the interspaces that naturally exist in between them. At Wambiana—a long-term research site in north-eastern Australia—we studied two soil types, two stocking rates (high, moderate), and resting land from grazing during wet seasons (rotational spelling). Rotational spelling had the highest biocrust (living soil cover), in interspaces and under grass tussocks. Biocrusts were dominated by cyanobacteria that binds soil particles, reduces erosion, sequesters carbon, fixes nitrogen, and improves soil fertility. Rotational spelling with a moderate stocking rate emerged as best practice at these sites, with adjustment of stocking rates in line with rainfall and soil type recommended. In drought-prone environments, monitoring the presence and integrity of biocrusts connects landscape function and soil health. Biocrusts that protect and enrich the soil will support long-term ecosystem integrity and economic profitability of cattle production in rangelands.
A new approach to vegetation sample selection, classification and mapping is described that accounts for rare and restricted vegetation communities. The new method (data-informed sampling and mapping: D-iSM) builds on traditional preferential sampling and was developed to guide conservation and land-use planning. It combines saturation coverage of vegetation point data with a preferential sampling design to produce locally accurate vegetation classifications and maps. Many existing techniques rely entirely or in part on random sampling, modelling against environmental variables, or on assumptions that photo-patterns detected through aerial photographic interpretation or physical landscape features can be attributed to a specific vegetation type. D-iSM uses ground data to inform both classification and mapping phases of a project. The approach is particularly suited to local- and regional-scale situations where disputes between conservation and development often lead to poor planning decisions, as well as in circumstances where highly restricted vegetation types occur within a wider mosaic of more common communities. Benefits of the D-iSM approach include more efficient and more representative floristic sampling, more realistic and repeatable classifications, increased user accuracy in vegetation mapping and increased ability to detect and map rare vegetation communities. Case studies are presented to illustrate the method in real-world classification and mapping projects.
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