Evaluation of alternative approaches to rainforest restoration on abandoned pasturelands in tropical north Queensland, Australia
- Florentine, Singarayer, Westbrooke, Martin
- Authors: Florentine, Singarayer , Westbrooke, Martin
- Date: 2004
- Type: Text , Journal article
- Relation: Land Degradation & Development Vol. 15, no. 1 (Jan-Feb 2004), p. 1-13
- Full Text:
- Reviewed:
- Description: The lag time for natural recruitment of tropical rainforest species in abandoned pastureland is very long, therefore artificial restoration techniques have been employed to accelerate natural seedling recruitment. The objectives of this study were to investigate: (1) the success/failure of establishment 502 seedlings belonging to 15 species from 11 families planted approximately ten years ago; and (2) the influence of different restoration techniques on enhancing natural recruitment during this period. The study was conducted in the wet tropical rainforest region of northeast Queensland, Australia as a completely randomized block design involving five treatments with two replicates. In each plot, 63 tropical rainforest seedlings from one or a combination of species were planted randomly. Two control plots were laid out where no seedlings were planted. Survival, height and diameter data were taken on the seedlings ten years after planting. Each 11×17 m2 plot was further divided into 187, 1×1 m2 subplots. Within each subplot all seedlings recruited were located and identified. Canopy cover was estimated using belt transects 1 m apart that ran in an east-west direction across the plots. Within each plot the percentage of grass, and the crown cover were estimated using the Braun-Blanquet cover abundance scale. Survival rate of planted seedlings varied across the treatment plots. The survival rate ranged from 65 to 75 per cent for primary-promoter species, 85 to 100 per cent in middle-phase species and 42 to 57 per cent for mature-phase species. No Pilidiostigma tropicum seedlings survived in any treatment. Fourteen species recruited naturally across the treatment plots. A total of 410 seedlings were naturally recruited from 11 different families in the ten-year-old reforested site. The highest natural recruitment (236 seedlings) occurred in Treatment 3, where Omalanthus novo-guineensis seedlings were planted with eight primary-promoter species, followed by 99 in Treatment 5 where a group of primary-promoters, middle phase species and mature-phase species were planted together, 36 in Treatment 4 (Alphitonia petriei planted with eight primary-promoter species), 10 in Treatment 2 where only Omalanthus novo-guineensis seedlings were planted, and 13 in control plots. Grass cover declined with increasing species diversity and increased canopy cover. The results indicate that the diversity of species used in restoration had a major influence on natural recruitment. Copyright © 2004 John Wiley & Sons, Ltd.
- Description: C1
- Description: 2003000714
- Authors: Florentine, Singarayer , Westbrooke, Martin
- Date: 2004
- Type: Text , Journal article
- Relation: Land Degradation & Development Vol. 15, no. 1 (Jan-Feb 2004), p. 1-13
- Full Text:
- Reviewed:
- Description: The lag time for natural recruitment of tropical rainforest species in abandoned pastureland is very long, therefore artificial restoration techniques have been employed to accelerate natural seedling recruitment. The objectives of this study were to investigate: (1) the success/failure of establishment 502 seedlings belonging to 15 species from 11 families planted approximately ten years ago; and (2) the influence of different restoration techniques on enhancing natural recruitment during this period. The study was conducted in the wet tropical rainforest region of northeast Queensland, Australia as a completely randomized block design involving five treatments with two replicates. In each plot, 63 tropical rainforest seedlings from one or a combination of species were planted randomly. Two control plots were laid out where no seedlings were planted. Survival, height and diameter data were taken on the seedlings ten years after planting. Each 11×17 m2 plot was further divided into 187, 1×1 m2 subplots. Within each subplot all seedlings recruited were located and identified. Canopy cover was estimated using belt transects 1 m apart that ran in an east-west direction across the plots. Within each plot the percentage of grass, and the crown cover were estimated using the Braun-Blanquet cover abundance scale. Survival rate of planted seedlings varied across the treatment plots. The survival rate ranged from 65 to 75 per cent for primary-promoter species, 85 to 100 per cent in middle-phase species and 42 to 57 per cent for mature-phase species. No Pilidiostigma tropicum seedlings survived in any treatment. Fourteen species recruited naturally across the treatment plots. A total of 410 seedlings were naturally recruited from 11 different families in the ten-year-old reforested site. The highest natural recruitment (236 seedlings) occurred in Treatment 3, where Omalanthus novo-guineensis seedlings were planted with eight primary-promoter species, followed by 99 in Treatment 5 where a group of primary-promoters, middle phase species and mature-phase species were planted together, 36 in Treatment 4 (Alphitonia petriei planted with eight primary-promoter species), 10 in Treatment 2 where only Omalanthus novo-guineensis seedlings were planted, and 13 in control plots. Grass cover declined with increasing species diversity and increased canopy cover. The results indicate that the diversity of species used in restoration had a major influence on natural recruitment. Copyright © 2004 John Wiley & Sons, Ltd.
- Description: C1
- Description: 2003000714
The impact of deforestation and pasture abandonment on soil properties in the wet tropics of Australia
- Rasiah, Velu, Florentine, Singarayer, Williams, B. L., Westbrooke, Martin
- Authors: Rasiah, Velu , Florentine, Singarayer , Williams, B. L. , Westbrooke, Martin
- Date: 2004
- Type: Text , Journal article
- Relation: Geoderma Vol. 120, no. 1-2 (2004), p. 35-45
- Full Text:
- Reviewed:
- Description: Limited information exists on the changes in soil properties, particularly from the wet tropics of Australia, under long-term abandoned pasture, which was previously grazed and was established on deforested tropical rainforest. This information may be help in successful forest reestablishment. The objectives of this study were to assess the cumulative impact deforestation, grazed and abandoned pasture on selected soil physico-chemical properties from (i) an abandoned pastureland and (ii) a recently planted rainforest (PRF), planted in the abandoned pastureland. The experimental site is a field in the Northeast Queensland (NEQ) wet tropical region of Australia. This site was deforested approximately 70 years ago and brought under unfertilized grazed pasture for 30 years. Subsequently the grazed pastureland was abandoned and remains un-grazed for 40 years. A section of the abandoned pastureland was planted, 10 years ago, with native forest species, involving different combinations in five treatments in a completely randomised block design. A nearby undisturbed rainforest is used as the background against which assessment was carried out. Soil samples from 0- to 15-cm depth were collected in July 2000 and analyzed for nitrate-N, ammonium-N, total N, total soil organic C (SOC) and labile-C, pH (in water and CaCl2), electrical conductivity (EC), exchangeable Ca, Mg, Na, K, and Al, and bulk density. Compared to the rainforest, the N and C concentrations of different forms under abandoned pasture and PRF were significantly less, exclusive of the total N under abandoned pasture. More specifically, the SOC under the abandoned pasture was 37,600 mg/kg compared with 74,800 mg/kg under rainforest and 27,000 mg/kg in the PRF. The exchangeable Al under rainforest was 8.5 c molc/kg compared with 42. 4 to 80.2 c molc/kg under abandoned pasture and PRF. In general exchangeable cations (sum of Ca, Mg, K, and Na) under the rainforest were higher than the abandoned pasture. Soil under the abandoned pasture and PRF are more acidic by 0.5 to 1 units than the rainforest. Higher bulk densities under abandoned pasture and PRF led to 0.03% to 0.07% reductions in total porosities. Though we did not anticipate the soil under the abandoned pasture to recover 100% in 30-40 years, the results indicate that 40 years under abandoned pasture or 30 years of abandoned pasture plus 10 years under PRF was not sufficient to bring about substantial improvement in soil properties comparable to the rainforest. This implies the resiliency of tropical soils, in general, to recover from deforestation and cultivation induced degradation is poor. © 2003 Elsevier B.V. All rights reserved.
- Description: C1
- Description: 2003000713
- Authors: Rasiah, Velu , Florentine, Singarayer , Williams, B. L. , Westbrooke, Martin
- Date: 2004
- Type: Text , Journal article
- Relation: Geoderma Vol. 120, no. 1-2 (2004), p. 35-45
- Full Text:
- Reviewed:
- Description: Limited information exists on the changes in soil properties, particularly from the wet tropics of Australia, under long-term abandoned pasture, which was previously grazed and was established on deforested tropical rainforest. This information may be help in successful forest reestablishment. The objectives of this study were to assess the cumulative impact deforestation, grazed and abandoned pasture on selected soil physico-chemical properties from (i) an abandoned pastureland and (ii) a recently planted rainforest (PRF), planted in the abandoned pastureland. The experimental site is a field in the Northeast Queensland (NEQ) wet tropical region of Australia. This site was deforested approximately 70 years ago and brought under unfertilized grazed pasture for 30 years. Subsequently the grazed pastureland was abandoned and remains un-grazed for 40 years. A section of the abandoned pastureland was planted, 10 years ago, with native forest species, involving different combinations in five treatments in a completely randomised block design. A nearby undisturbed rainforest is used as the background against which assessment was carried out. Soil samples from 0- to 15-cm depth were collected in July 2000 and analyzed for nitrate-N, ammonium-N, total N, total soil organic C (SOC) and labile-C, pH (in water and CaCl2), electrical conductivity (EC), exchangeable Ca, Mg, Na, K, and Al, and bulk density. Compared to the rainforest, the N and C concentrations of different forms under abandoned pasture and PRF were significantly less, exclusive of the total N under abandoned pasture. More specifically, the SOC under the abandoned pasture was 37,600 mg/kg compared with 74,800 mg/kg under rainforest and 27,000 mg/kg in the PRF. The exchangeable Al under rainforest was 8.5 c molc/kg compared with 42. 4 to 80.2 c molc/kg under abandoned pasture and PRF. In general exchangeable cations (sum of Ca, Mg, K, and Na) under the rainforest were higher than the abandoned pasture. Soil under the abandoned pasture and PRF are more acidic by 0.5 to 1 units than the rainforest. Higher bulk densities under abandoned pasture and PRF led to 0.03% to 0.07% reductions in total porosities. Though we did not anticipate the soil under the abandoned pasture to recover 100% in 30-40 years, the results indicate that 40 years under abandoned pasture or 30 years of abandoned pasture plus 10 years under PRF was not sufficient to bring about substantial improvement in soil properties comparable to the rainforest. This implies the resiliency of tropical soils, in general, to recover from deforestation and cultivation induced degradation is poor. © 2003 Elsevier B.V. All rights reserved.
- Description: C1
- Description: 2003000713
Assessment of error sources in measurements of field pH : Effect of operator experience, test kit differences, and time-of-day
- Robinson, Nathan, Norng, Sorn, Rees, David, Benke, Kurt, Davey, Michelle
- Authors: Robinson, Nathan , Norng, Sorn , Rees, David , Benke, Kurt , Davey, Michelle
- Date: 2018
- Type: Text , Journal article
- Relation: Communications in Soil Science and Plant Analysis Vol. 49, no. 3 (2018), p. 269-285
- Full Text:
- Reviewed:
- Description: Various methods exist to measure soil pH, and while there is general agreement between the existing published laboratory and field-based methods, the latter are subject to uncertainties including test kit reliability, accuracy, precision, and environmental factors. The contribution of this study is to quantify three uncertainties that affect the conversion between field pH and laboratory pH measurements, namely operator experience, choice of test kit, and the time-of-day for measurement. Soil samples from western Victoria, representing the pH range 4.5–10.0, were used in a randomized complete block design with 10 assessors split into two groups representing experienced and inexperienced users. Statistical analysis of laboratory and field pH was based on using the Maximum Likelihood Functional Relationship (MLFR) to determine if there was any bias between the two methods. Significant differences were found between experienced and inexperienced users, and between test kits. © 2017 Taylor & Francis.
- Authors: Robinson, Nathan , Norng, Sorn , Rees, David , Benke, Kurt , Davey, Michelle
- Date: 2018
- Type: Text , Journal article
- Relation: Communications in Soil Science and Plant Analysis Vol. 49, no. 3 (2018), p. 269-285
- Full Text:
- Reviewed:
- Description: Various methods exist to measure soil pH, and while there is general agreement between the existing published laboratory and field-based methods, the latter are subject to uncertainties including test kit reliability, accuracy, precision, and environmental factors. The contribution of this study is to quantify three uncertainties that affect the conversion between field pH and laboratory pH measurements, namely operator experience, choice of test kit, and the time-of-day for measurement. Soil samples from western Victoria, representing the pH range 4.5–10.0, were used in a randomized complete block design with 10 assessors split into two groups representing experienced and inexperienced users. Statistical analysis of laboratory and field pH was based on using the Maximum Likelihood Functional Relationship (MLFR) to determine if there was any bias between the two methods. Significant differences were found between experienced and inexperienced users, and between test kits. © 2017 Taylor & Francis.
Development of pedotransfer functions by machine learning for prediction of soil electrical conductivity and organic carbon content
- Benke, Kurt, Norng, Sorn, Robinson, Nathan, Chia, K., Rees, David, Hopley, J.
- Authors: Benke, Kurt , Norng, Sorn , Robinson, Nathan , Chia, K. , Rees, David , Hopley, J.
- Date: 2020
- Type: Text , Journal article
- Relation: Geoderma Vol. 366, no. (2020), p.
- Full Text:
- Reviewed:
- Description: The pedotransfer function is a mathematical model used to convert direct soil measurements into known and unknown soil properties. It provides information for modelling and simulation in soil research, hydrology, environmental science and climate change impacts, including investigating the carbon cycle and the exchange of carbon between soils and the atmosphere to support carbon farming. In particular, the pedotransfer function can provide input parameters for landscape design, soil quality assessment and economic optimisation. The objective of the study was to investigate the feasibility of using a generalised pedotransfer function derived with a machine learning method to predict soil electrical conductivity (EC) and soil organic carbon content (OC) for different regional locations in the state of Victoria, Australia. This strategy supports a unified approach to the interpolation and population of a single regional soils database, in contrast to a range of pedotransfer functions derived from local databases with measurement sets that may have limited transferability. The pedotransfer function generation was based on a machine learning algorithm incorporating the Generalized Linear Mixed Model with interactions and nested terms, with Residual Maximum Likelihood estimation, and a predictor-frequency ranking system with step-wise reduction of predictors to evaluate the predictive errors in reduced models. The source of the data was the Victorian Soil Information System (VSIS), which is a database administered for soil information and mapping purposes. The database contains soil measurements and information from locations across Victoria and is a repository of historical data, including monitoring studies. In total, data from 93 projects were available for inputs to modelling and analysis, with 5158 samples used to derive predictors for EC and 1954 samples used to derive predictors for OC. Over 500 models were tested by systematically reducing the number of predictors from the full model. Five-fold cross-validation was used for estimation of model mean-squared prediction error (MSPE) and mean-absolute percentage error (MAPE). The results were statistically significant with only a gradual reduction in error for the top-ranked 50 models. The prediction errors (MSPE and MAPE) of the top ranked model for EC are 0.686 and 0.635, and 0.413 and 0.474 for OC respectively. The four most frequently occurring predictors both for EC and OC prediction across the full set of models were found to be soil depth, pH, particle size distribution and geomorphological mapping unit. The possible advantages and disadvantages of this approach were discussed with respect to other machine learning approaches. © 2020 Elsevier B.V.
- Authors: Benke, Kurt , Norng, Sorn , Robinson, Nathan , Chia, K. , Rees, David , Hopley, J.
- Date: 2020
- Type: Text , Journal article
- Relation: Geoderma Vol. 366, no. (2020), p.
- Full Text:
- Reviewed:
- Description: The pedotransfer function is a mathematical model used to convert direct soil measurements into known and unknown soil properties. It provides information for modelling and simulation in soil research, hydrology, environmental science and climate change impacts, including investigating the carbon cycle and the exchange of carbon between soils and the atmosphere to support carbon farming. In particular, the pedotransfer function can provide input parameters for landscape design, soil quality assessment and economic optimisation. The objective of the study was to investigate the feasibility of using a generalised pedotransfer function derived with a machine learning method to predict soil electrical conductivity (EC) and soil organic carbon content (OC) for different regional locations in the state of Victoria, Australia. This strategy supports a unified approach to the interpolation and population of a single regional soils database, in contrast to a range of pedotransfer functions derived from local databases with measurement sets that may have limited transferability. The pedotransfer function generation was based on a machine learning algorithm incorporating the Generalized Linear Mixed Model with interactions and nested terms, with Residual Maximum Likelihood estimation, and a predictor-frequency ranking system with step-wise reduction of predictors to evaluate the predictive errors in reduced models. The source of the data was the Victorian Soil Information System (VSIS), which is a database administered for soil information and mapping purposes. The database contains soil measurements and information from locations across Victoria and is a repository of historical data, including monitoring studies. In total, data from 93 projects were available for inputs to modelling and analysis, with 5158 samples used to derive predictors for EC and 1954 samples used to derive predictors for OC. Over 500 models were tested by systematically reducing the number of predictors from the full model. Five-fold cross-validation was used for estimation of model mean-squared prediction error (MSPE) and mean-absolute percentage error (MAPE). The results were statistically significant with only a gradual reduction in error for the top-ranked 50 models. The prediction errors (MSPE and MAPE) of the top ranked model for EC are 0.686 and 0.635, and 0.413 and 0.474 for OC respectively. The four most frequently occurring predictors both for EC and OC prediction across the full set of models were found to be soil depth, pH, particle size distribution and geomorphological mapping unit. The possible advantages and disadvantages of this approach were discussed with respect to other machine learning approaches. © 2020 Elsevier B.V.
Stress–strain relationship of sandstone under confining pressure with repetitive impact
- Wang, Shiming, Xiong, Xianrui, Liu, Yunsi, Zhou, Jian, Khandelwal, Manoj
- Authors: Wang, Shiming , Xiong, Xianrui , Liu, Yunsi , Zhou, Jian , Khandelwal, Manoj
- Date: 2021
- Type: Text , Journal article
- Relation: Geomechanics and Geophysics for Geo-Energy and Geo-Resources Vol. 7, no. 2 (2021), p.
- Full Text:
- Reviewed:
- Description: Abstract: A series of triaxial repetitive impact tests were conducted on a 50-mm-diameter split Hopkinson pressure bar testing device to reveal the characteristics of dynamic stress–strain of sandstone under confining pressure, and the confining pressure in this study was set as 5 and 10 MPa. The results showed that sandstone is very sensitive to confining pressure and strain rate. As the confining pressure and strain rate increases, the dynamic strength, critical strain and absorbed energy also increases, however with the increases in number of impacts, they decrease. With impact numbers increases, the stress–strain curve of sandstone gradually transits from a Class I to a Class II. The dynamic statistical damage constitutive model used in the paper can describe the dynamic response of sandstone under confining pressure with repetitive impact. Various influencing factors, such as material characteristics, confining pressure, strain rate and damage on the dynamic mechanical behavior of sandstone are also fully considered in the model. The damage curve changes from concave to convex as the F/ F increase. When the F/ F exceed 0.5, the damage curve appears convex, and the damage is obvious. By comparing with the variation of the reflected wave waveform with the impact numbers, it is found that damage evolution law of the rock under confining pressure with the impact numbers is similar to that of the reflected wave waveform with the impact numbers, can reflect the damage degree of the rock specimen without other auxiliary equipment, which has been verified. Article Highlights: The stress-strain curve of sandstone under confining pressure with repeated impact changes from Class I to Class II, and it will become less obvious as the confining pressure increases.The constitutive model used in the article can well describe the dynamic mechanical properties, strain rate effect and its turning point of rock under confining pressure with repeated impact.The damage curve changes from concave to convex, and the damage evolution law is similar to that of the reflected wave waveform with the impact numbers. © 2021, The Author(s), under exclusive licence to Springer Nature Switzerland AG. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Manoj Khandelwal” is provided in this record**
- Authors: Wang, Shiming , Xiong, Xianrui , Liu, Yunsi , Zhou, Jian , Khandelwal, Manoj
- Date: 2021
- Type: Text , Journal article
- Relation: Geomechanics and Geophysics for Geo-Energy and Geo-Resources Vol. 7, no. 2 (2021), p.
- Full Text:
- Reviewed:
- Description: Abstract: A series of triaxial repetitive impact tests were conducted on a 50-mm-diameter split Hopkinson pressure bar testing device to reveal the characteristics of dynamic stress–strain of sandstone under confining pressure, and the confining pressure in this study was set as 5 and 10 MPa. The results showed that sandstone is very sensitive to confining pressure and strain rate. As the confining pressure and strain rate increases, the dynamic strength, critical strain and absorbed energy also increases, however with the increases in number of impacts, they decrease. With impact numbers increases, the stress–strain curve of sandstone gradually transits from a Class I to a Class II. The dynamic statistical damage constitutive model used in the paper can describe the dynamic response of sandstone under confining pressure with repetitive impact. Various influencing factors, such as material characteristics, confining pressure, strain rate and damage on the dynamic mechanical behavior of sandstone are also fully considered in the model. The damage curve changes from concave to convex as the F/ F increase. When the F/ F exceed 0.5, the damage curve appears convex, and the damage is obvious. By comparing with the variation of the reflected wave waveform with the impact numbers, it is found that damage evolution law of the rock under confining pressure with the impact numbers is similar to that of the reflected wave waveform with the impact numbers, can reflect the damage degree of the rock specimen without other auxiliary equipment, which has been verified. Article Highlights: The stress-strain curve of sandstone under confining pressure with repeated impact changes from Class I to Class II, and it will become less obvious as the confining pressure increases.The constitutive model used in the article can well describe the dynamic mechanical properties, strain rate effect and its turning point of rock under confining pressure with repeated impact.The damage curve changes from concave to convex, and the damage evolution law is similar to that of the reflected wave waveform with the impact numbers. © 2021, The Author(s), under exclusive licence to Springer Nature Switzerland AG. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Manoj Khandelwal” is provided in this record**
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