Complexity confers stability: Climate variability, vegetation response and sand transport on longitudinal sand dunes in Australia’s deserts

Hesse, Paul; Telfer, Matt W.; Farebrother, Will

doi:10.1016/j.aeolia.2017.02.003

Cited by 29 publications

(43 citation statements)

References 51 publications

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“…Shrubs were easily delineated from the high-resolution image orthomosaics (figure 2; electronic supplementary material, figure S1). The transects from the digital terrain models appeared to accurately characterize the dune cross-sections (electronic supplementary material, figure S3) and were consistent in both height and width with the descriptions and cross-section of nearby dunes given by Hesse & Simpson [17] and Hesse et al [18]. Absolute accuracy is difficult to ascertain rsif.royalsocietypublishing.org J. R. Soc.…”

Section: Dune Characterizationmentioning

confidence: 55%

“…Figure 4 shows the effect of these terms on the metric predictions (easiest way to interpret smooth terms by shrubs, not only do the dune crests become more permanently vegetated, but we speculate that the threshold for switching states is lifted high enough that they are pushed into alternate stable state. We note that the dunes inside the dingo fence are in the far southeastern range of the dunes described by the existing literature, and their higher than average shrub cover has not been previously explored in a purely geomorphological context [17,18].…”

Section: Linking Ecology and Geomorphologymentioning

confidence: 83%

“…We propose that more permanently vegetated dune crests [18] and skimming flow wind regimes [20] act to push dunes inside the dingo fence towards an alternate stable state within the bi-stable state model [19]. This alternate state would have a much higher threshold for switching to an active state (via climatic forcing).…”

Section: High Shrub Density Leads To New Stable Statementioning

confidence: 99%

“…This could include measuring aeolian and sedimentary processes that are unable to be surveyed via drones, particularly sediment transport potential and sediment characteristics. Grain size distribution is likely to change with changing stabilization and wind flow regimes [14,16,18], so has the potential to impact geomorphological processes. The additional survey effort at individual dunes would also facilitate the additional time required to set up additional GPS equipment and capture enough GPS data to apply high-accuracy corrections.…”

Section: Limitations and Further Researchmentioning

confidence: 99%

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Linking trophic cascades to changes in desert dune geomorphology using high-resolution drone data

Lyons

Mills

Gordon

et al. 2018

J. R. Soc. Interface.

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Vegetation cover is fundamental in the formation and maintenance of geomorphological features in dune systems. In arid Australia, increased woody shrub cover has been linked to removal of the apex predator (Dingoes, ) via subsequent trophic cascades. We ask whether this increase in shrubs can be linked to altered physical characteristics of the dunes. We used drone-based remote sensing to measure shrub density and construct three-dimensional models of dune morphology. Dunes had significantly different physical characteristics either side of the 'dingo-proof fence', inside which dingoes are systematically eradicated and shrub density is higher over vast spatial extents. Generalized additive models revealed that dunes with increased shrub density were higher, differently shaped and more variable in height profile. We propose that low shrub density induces aeolian and sedimentary processes that result in greater surface erosion and sediment transport, whereas high shrub density promotes dune stability. We speculate that increased vegetation cover acts to push dunes towards an alternate stable state, where climatic variation no longer has a significant effect on their morphodynamic state within the bi-stable state model. Our study provides evidence that anthropogenically induced trophic cascades can indirectly lead to large-scale changes in landscape geomorphology.

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Section: Dune Characterizationmentioning

confidence: 55%

Section: Linking Ecology and Geomorphologymentioning

confidence: 83%

Section: High Shrub Density Leads To New Stable Statementioning

confidence: 99%

Section: Limitations and Further Researchmentioning

confidence: 99%

See 2 more Smart Citations

Linking trophic cascades to changes in desert dune geomorphology using high-resolution drone data

Lyons

Mills

Gordon

et al. 2018

J. R. Soc. Interface.

View full text Add to dashboard Cite

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“…Despite a growing body of work on vegetated linear dune surface processes (e.g. Wiggs et al, 1995Wiggs et al, , 1996Telfer, 2011;Craddock et al, 2015;Hesse et al, 2017) and the geochronology of linear dune deposits (e.g. Telfer and Hesse, 2013;Hesse, 2016;Thomas and Bailey, 2017), linear dune formation remains a poorly understood process.…”

Section: Introductionmentioning

confidence: 99%

Deep learning for dune pattern mapping with the AW3D30 global surface model

Shumack

Hesse

Farebrother

2020

Earth Surf Processes Landf

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In this paper we present a deep learning (U‐Net)‐based workflow for classifying linear dune landforms based on the discrete Laplacian convolution of a new global elevation dataset, the AW3D30 digital surface model. Crest vectors were then derived for landscape pattern analysis. The U‐Net crest classification model was trained and evaluated on sample data from dunefields across the Australian continent. The resulting crest vectors and dune defect placement were then evaluated in typical semi‐arid and arid dune landscapes in eastern central Australia where high‐resolution (5 m horizontal) digital elevation models are available (for three out of our four study sites) as a reference dataset. The method was applied to quantify dune pattern metrics for the entire Simpson Desert dunefield, Australia. The U‐Net does a very good job of segmenting dune crests, even where dunes are less clear in the Laplacian map (intersection over union score ≈ 0.68). When crest vectors and dune defects (network nodes) were derived, the defect predictions were typically correct (0.4 to 0.79 correctness) but incomplete (0.02 to 0.64 completeness). Much of the residual error was traced to the resolution of the input data. Through the application to the Simpson Desert, we nevertheless demonstrated that our method can effectively be used for regional‐scale dune pattern analysis. Furthermore, we suggest that the combination of morphological filtering and a convolutional neural network could readily be adapted to target other geomorphic features, such as channel networks or geological lineaments. © 2020 John Wiley & Sons, Ltd.

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The response of vegetation cover and dune activity to rainfall, drought and fire observed by multitemporal satellite imagery

Fisher

Hesse

2019

Earth Surf Processes Landf

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The stable longitudinal dunes in the northern Simpson Desert, Australia, were observed in satellite imagery to become more active after vegetation cover was reduced by fire and drought. Subsequent rainfall events also resulted in significant vegetation regrowth and dune stabilization. These switches between more active and stable conditions have not been previously described in the largely vegetated dune fields of central Australia. The observations, made on 12 dune sites, relied on high spatial resolution satellite imagery to observe dune crest activity, and seasonal Landsat fractional cover imagery to observe vegetation cover changes. The non‐photosynthetic vegetation (NPV) component of the fractional vegetation cover images revealed significant changes in hummock grass cover on the dunes between 1988 and 2018, with a positive relationship with the three‐year cumulative rainfall, disrupted by two periods of patchy burning. Only those sites that had burnt became active, and only after vegetation cover had remained low (NPV < 16%) during the ‘Millennium Drought’. There is no threshold in vegetation cover, below which dune crests become active, but active dune features require four‐years of low NPV cover (< 16%) to develop. The large rainfall event that ended the drought increased NPV cover, stabilizing the dunes. Similar hummock grass covered dunes are present across large areas of the arid zone, and are likely to respond in similar ways, given that fire and drought are common occurrences in Australia. © 2019 John Wiley & Sons, Ltd. © 2019 John Wiley & Sons, Ltd.

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Complexity confers stability: Climate variability, vegetation response and sand transport on longitudinal sand dunes in Australia’s deserts

Cited by 29 publications

References 51 publications

Linking trophic cascades to changes in desert dune geomorphology using high-resolution drone data

Linking trophic cascades to changes in desert dune geomorphology using high-resolution drone data

Deep learning for dune pattern mapping with the AW3D30 global surface model

The response of vegetation cover and dune activity to rainfall, drought and fire observed by multitemporal satellite imagery

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