https://nova.newcastle.edu.au/vital/access/manager/Index ${session.getAttribute("locale")} 5 https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:47716 Wed 25 Jan 2023 12:40:42 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:5843 Wed 11 Apr 2018 16:38:28 AEST ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:14371 137Cs) technique has been used successfully in many parts of the world to estimate net (ca. 30–50 years) soil redistribution by wind and water erosion and tillage activities. The point‐based technique has hitherto been confined largely to individual fields and hillslopes, particularly in Australia. Its application here to the Australian continent (≈5 km grid) was achieved using geostatistics and nationally coordinated measurements (early 1990s) from ≈200 locations at the ≈1 km scale. A map of the ¹³⁷Cs reference inventory for Australia has been previously established. Sequential indicator co‐simulation of the ¹³⁷Cs inventory and the Australian Soil Classification was used to estimate net (between mid‐1950s and early 1990s) soil redistribution using the Australian Empirical Model. This geostatistical approach showed that nearly five times more soil was lost from cultivated land (−4.29 to +0.17t ha^-1 yr^-1) than from uncultivated (−0.91 to +0.05t ha^-1yr^-1) land in Australia. This information on spatial uncertainty is essential for regional soil management to assess the risk to soil conservation. Soil erosion exceeding a tolerable threshold value (e.g., 0.5 t ha^-1 yr^-1) occurred over 16% of Australia, mainly in cultivated regions (median = −1.26t ha^-1yr^-1). Soil erosion estimates are neglected in carbon balances for greenhouse gas abatement and carbon accounting models. Reliable quantitative data on the recent extent and rates of soil erosion are needed to underpin the selection of effective soil conservation measures, to inform carbon balances and to understand regional soil function for sustainable agricultural systems.]]> Wed 11 Apr 2018 13:01:35 AEST ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:4831 Wed 11 Apr 2018 10:57:25 AEST ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:36833 Wed 08 Jul 2020 15:47:42 AEST ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:43980 Wed 07 Feb 2024 16:38:20 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:41434 Wed 03 Aug 2022 14:19:25 AEST ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:47610 Tue 24 Jan 2023 11:14:52 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:52630 Thu 19 Oct 2023 15:13:48 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:32276 Thu 17 May 2018 15:08:19 AEST ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:37752 Thu 14 Mar 2024 08:41:00 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:39921 Thu 14 Jul 2022 12:15:12 AEST ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:53754 Thu 11 Jan 2024 12:21:40 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:7150 Sat 24 Mar 2018 08:34:15 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:9864 Sat 24 Mar 2018 08:14:32 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:10394 Sat 24 Mar 2018 08:08:45 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:10557 Sat 24 Mar 2018 08:08:22 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:20550 100 m s⁻¹ uprooted approximately 50% of the trees in the study catchment. We use a landscape evolution model with repeated occurrence of the cyclone over a 1000-year simulated period to quantify the effect of pit–mound topography distributions on both sediment transport and landscape evolution by including the fallen trees into the digital elevation model both as a pit–mound and also as a pit–mound and tree trunk. The results show that the inclusion of pit–mound topography substantially reduced erosion for the first 10–15 years of its introduction and adding pit–mound–trunk topography reduced erosion rates even further. The pit–mound and pit–mound–trunk acted as sediment traps, capturing sediment from upslope and storing it in debris dams reducing hillslope connectivity. Model simulations predict average denudation rates for the catchment approximating field measured data. These findings suggest that any tree throw is unlikely to result in landscape instability.]]> Sat 24 Mar 2018 08:02:40 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:20495 Sat 24 Mar 2018 07:59:06 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:18775 Sat 24 Mar 2018 07:51:10 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:25271 Sat 24 Mar 2018 07:38:19 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:26594 Sat 24 Mar 2018 07:34:02 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:27139 Sus scrofa) are recognised as having significant ecological impacts in many areas of the world including northern Australia. The full consequences of the introduction of pigs are difficult to quantify as the impacts may only be detected over the long-term and there is a lack of quantitative information on the impacts of feral pigs globally. In this study the effect of feral pigs is quantified in an undisturbed catchment in the monsoonal tropics of northern Australia. Over a three-year period, field data showed that the areal extent of pig disturbance ranged from 0.3-3.3% of the survey area. The mass of material exhumed through these activities ranged from 4.3tha^-1yr^-1 to 36.0tha^-1yr^-1. The findings demonstrate that large introduced species such as feral pigs are disturbing large areas as well as exhuming considerable volumes of soil. A numerical landscape evolution and soil erosion model was used to assess the effect of this disturbance on catchment scale erosion rates. The modelling demonstrated that simulated pig disturbance in previously undisturbed areas produced lower erosion rates compared to those areas which had not been impacted by pigs. This is attributed to the pig disturbance increasing surface roughness and trapping sediment. This suggests that in this specific environment, disturbance by pigs does not enhance erosion. However, this conclusion is prefaced by two important caveats. First, the long term impact of soil disturbance is still very uncertain. Secondly, modelling results show a clear differentiation between those from an undisturbed environment and those from a post-mining landscape, in which pig disturbance may enhance erosion.]]> Sat 24 Mar 2018 07:33:01 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:30066 −1 yr⁻¹, which was similar to the Gerlach trough measurements, and we demonstrated that the soil erosion rates depended on rainfall characteristics and human disturbances due to tillage, harvest trampling, and compaction by heavy machinery. Data from the SUM in the young vineyard showed 62.5 Mg ha⁻¹ yr⁻¹ of soil loss, which is a consequence of severe soil disturbance during the planting of the new vineyard. Finally, to prove the reliability data, RUSLE showed higher soil loss in the young vineyards (19.46 Mg ha⁻¹ yr⁻¹) than in the old ones (11.28 Mg ha⁻¹ yr⁻¹).]]> Sat 24 Mar 2018 07:31:20 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:31066 Sus scrofa) are recognised as having significant environmental impacts. Here, we quantify the effect of feral pigs in a catchment (undisturbed by Europeans) in the monsoonal tropics of northern Australia. Field data collected over a 5-year period showed that the areal extent of pig disturbance ranged from 0·3 to 3·3% of the survey area (average 1·2%, σ = 0·9%). Mass of exhumed material was considerable and ranged from 4·3 to 36·0 Mg ha⁻¹ y⁻¹ (average 10·9 Mg ha⁻¹ y⁻¹). The excavations produce surface roughness which acts as sediment traps. Over the 5-year study period, there was no evidence to suggest that pigs produce any rill or gully erosion. There does not appear to be any relationship between rainfall amount and area disturbed or volume of material exhumed. However, a significant positive relationship was observed between number of disturbances and rainfall. The location of any disturbance appears to be random and has no relationship with topography or geomorphic attributes such as slope, upslope contributing area or wetness indices derived from a high-resolution digital elevation model of the site. While pigs are disturbingly relatively large volumes of soil, there is no clear evidence to support any increase in local erosion and soil structural change may be occurring slowly and only be observable over the long term.]]> Sat 24 Mar 2018 07:24:09 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:4912 Sat 24 Mar 2018 07:22:58 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:3204 Sat 24 Mar 2018 07:21:56 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:3401 Sat 24 Mar 2018 07:21:41 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:3425 Sat 24 Mar 2018 07:21:36 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:3464 Sat 24 Mar 2018 07:20:31 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:3159 Sat 24 Mar 2018 07:18:14 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:3175 Sat 24 Mar 2018 07:18:11 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:3179 Sat 24 Mar 2018 07:18:10 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:37512 Mon 25 Jan 2021 14:45:20 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:37706 -1 year^-1. Erosion processes were evaluated at the erosion production (Eocene marly formations) and sedimentation zones (Quaternary terraces). The results of these models may be useful to address soil and water management in this region and to assess the impact of a river dam that will be built in the basin.]]> Mon 22 Mar 2021 10:35:52 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:40728 Mon 18 Jul 2022 11:48:21 AEST ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:40599 Mon 08 Aug 2022 15:32:18 AEST ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:38539 -1 yr^-1) compare well with independently determined erosion rates using ¹³⁷Cs (2.1 to 3.4 t ha^-1 yr^-1). We also investigate field measured and modelled soil organic carbon movement using the LEM in relation to predicted erosion and deposition patterns and find that erosion and deposition patterns are related to the spatial patterns of SOC. This is the first time that a DEM based LEM has been shown to provide reliable prediction of not just soil erosion but also SOC. The results demonstrate that the majority of SOC is being transported in the near surface soil layer (top 2 cm) and that turnover at greater depths is slower and does not correspond with any modelled patterns. The modelled erosion and deposition suggests that on average 0.06 t ha^-1 yr^-1 of SOC is exported by erosion from the hillslope assuming a good vegetation cover. However if the hillslope is subjected to disturbance (i.e. tillage, overgrazing) then the site will export 0.46 t ha^-1 yr^-1of SOC. Laboratory results using flume suggest that there was no enrichment of SOC in the eroded sediment. The methods outlined here provide a new approach to quantify the dynamic movement of sediment and SOC at both the hillslope and catchment scale.]]> Fri 29 Oct 2021 14:14:00 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:39223 −1year⁻¹and 4.4 t ha⁻¹year⁻¹, respectively. These were found to closely match erosion rates estimated using the environmental tracer137Cs (2.7–4.8 t ha⁻¹year⁻¹. However, erosion and deposition estimated at individual points along the hillslopewas not well correlated with¹³⁷Cs at the same position due to the temporal averag-ing of the model and microtopography. Sensitivity analysis showed the model wasmore sensitive to parameterisation than sub-DEM-scale topography. This placesconfidence in the model’s ability to estimate erosion and deposition across an entirehillslope and catchment on decadal time scales. We also highlight the robustnessand flexibility of the calibration methods.]]> Fri 27 May 2022 11:51:25 AEST ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:48734 Fri 23 Jun 2023 12:47:54 AEST ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:50085 Fri 14 Jul 2023 11:48:17 AEST ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:46855 Fri 02 Dec 2022 09:27:23 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:34028 Fri 01 Feb 2019 13:10:56 AEDT ]]>