A meta-analysis on the effectiveness of post-fire soil erosion mitigation treatments

Author(s):  
Antonio Girona-García ◽  
Diana Vieira ◽  
Joana Silva ◽  
Cristina Fernández ◽  
Peter Robichaud ◽  
...  

<p>Wildfires are considered to be one of the main causes of soil erosion and land degradation processes in fire-prone areas [1], which are expected to increase in the future because of fire patterns shifting worldwide as a consequence of changes in climate and land use [2]. To maintain the sustainability of ecosystems and protect the values at risk downstream from the fire-affected areas, it is vital to mitigate the increased hydrological and erosive response after fires. Despite soil erosion mitigation treatments have been widely applied after wildfires, their effectiveness has only been assessed in local and regional-scale studies, so the obtained conclusions might be heavily influenced by site-specific conditions.</p><p>To overcome this constraint, a meta-analysis was applied on the scientific literature on post-fire soil erosion mitigation treatments indexed in Scopus. The search resulted in 34 publications from which 53 and 222 pairs of treated/untreated observations on post-fire runoff and erosion, respectively, were obtained. The overall effectiveness of mitigation treatments, expressed as effect size, was determined for the runoff and erosion observations, and further analyzed for four different types of treatments (mulching, barriers, seeding, and chemical). The erosion observations concerning mulches were analyzed for differences in effect size between 3 different types of materials (straw, wood, and hydromulch) as well as between different application rates of straw and wood. The erosion observations were also analyzed for the overall effect size of post-fire year, burn severity, rainfall amount and erosivity, and ground cover.</p><p>The results showed that all four types of treatments significantly reduced post-fire soil erosion, but that only the mulch and barrier treatments significantly reduced post-fire runoff. From the 3 different mulch treatments, the straw and wood were significantly more efficient in mitigating erosion than the hydromulch. The different straw and wood mulch application rates also influenced their effectiveness. Straw mulch was less effective at rates below than above 200 g m<sup>-2</sup>, while mulching with wood at high rates (1300 to 1750 g m<sup>-2</sup>) produced more variable outcomes. Results also suggested that the overall effectiveness of the treatments was greatest shortly after fire, in severely burned sites, providing or promoting the development of ground cover over 70%, and with increasing rainfall erosivity.</p><p>It can be concluded that, in overall terms, the application of the studied post-fire erosion mitigation treatments represented a better choice than doing nothing, especially in sites where erosion is high. However, works on this topic are underrepresented outside of the USA, Spain and Portugal. Most of the studies were conducted at hillslope scale and tested mulching and/or barriers, while larger scales and other treatments were neglected. Further efforts are needed in testing, from field and modelling experiments, combinations of existing and/or emerging erosion mitigation treatments to ensure that the most suitable measures are applied after fires.</p><p>[1] Shakesby (2011). Earth-Sci. Revs. 105:71-100. DOI: 10.1016/j.earscirev.2011.01.001</p><p>[2] Andela et al. (2017). Science 356: 1356-1362. DOI: 10.1126/science.aal4108</p>

Agronomy ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1368
Author(s):  
Wenzheng Tang ◽  
Wene Wang ◽  
Dianyu Chen ◽  
Ningbo Cui ◽  
Haosheng Yang ◽  
...  

In order to meet the growing food demand of the global population and maintain sustainable soil fertility, there is an urgent need to optimize fertilizer application amount in agricultural production practices. Most of the existing studies on the optimal K rates for apple orchards were based on case studies and lack information on optimizing K-fertilizer management on a regional scale. Here, we used the method of combining meta-analysis with the K application rate-yield relationship model to quantify and summarize the optimal K rates of the Loess Plateau and Bohai Bay regions in China. We built a dataset based on 159 observations obtained from 18 peer-reviewed literature studies distributed in 15 different research sites and evaluated the regional-scale optimal K rates for apple production. The results showed that the linear plus platform model was more suitable for estimating the regional-scale optimal K rates, which were 208.33 and 176.61 kg K ha−1 for the Loess Plateau and Bohai Bay regions of China, respectively. Compared with high K application rates, the optimal K rates increased K use efficiency by 45.88–68.57%, with almost no yield losses. The optimal K rates also enhanced the yield by 6.30% compared with the low K application rates.


2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Liansheng Larry Tang ◽  
Michael Caudy ◽  
Faye Taxman

Multiple meta-analyses may use similar search criteria and focus on the same topic of interest, but they may yield different or sometimes discordant results. The lack of statistical methods for synthesizing these findings makes it challenging to properly interpret the results from multiple meta-analyses, especially when their results are conflicting. In this paper, we first introduce a method to synthesize the meta-analytic results when multiple meta-analyses use the same type of summary effect estimates. When meta-analyses use different types of effect sizes, the meta-analysis results cannot be directly combined. We propose a two-step frequentist procedure to first convert the effect size estimates to the same metric and then summarize them with a weighted mean estimate. Our proposed method offers several advantages over existing methods by Hemming et al. (2012). First, different types of summary effect sizes are considered. Second, our method provides the same overall effect size as conducting a meta-analysis on all individual studies from multiple meta-analyses. We illustrate the application of the proposed methods in two examples and discuss their implications for the field of meta-analysis.


2017 ◽  
Vol 9 (2) ◽  
pp. 1
Author(s):  
Yousef Ogla Almarshad

This paper reviewed the effects of educational leadership on students' academic outcomes during the past decade. 14 studies were found and included with the computation of 16 effect size statistics. This research evaluated the effect of three different types of leadership, instructional, transformational and distributed, on students' academic achievement. The study found no discernable differences with respect to the type of leadership on students' academic outcomes.Discernable leadership was found to be the most influential leadership style on students' academic achievement. This finding confirms earlier arguments suggesting that if leaders are more engaged in the business of teaching and learning of their students, the academic performance of schools pupils become better. In light of earlier reviews of leadership effects on students' outcomes, this study shows that the influence of leadership on academic measures differs from its effects on non-academic outcomes including social, psychological and political characteristics.


2009 ◽  
Vol 13 (10) ◽  
pp. 1907-1920 ◽  
Author(s):  
M. Angulo-Martínez ◽  
M. López-Vicente ◽  
S. M. Vicente-Serrano ◽  
S. Beguería

Abstract. Rainfall erosivity is a major causal factor of soil erosion, and it is included in many prediction models. Maps of rainfall erosivity indices are required for assessing soil erosion at the regional scale. In this study a comparison is made between several techniques for mapping the rainfall erosivity indices: i) the RUSLE R factor and ii) the average EI30 index of the erosive events over the Ebro basin (NE Spain). A spatially dense precipitation data base with a high temporal resolution (15 min) was used. Global, local and geostatistical interpolation techniques were employed to produce maps of the rainfall erosivity indices, as well as mixed methods. To determine the reliability of the maps several goodness-of-fit and error statistics were computed, using a cross-validation scheme, as well as the uncertainty of the predictions, modeled by Gaussian geostatistical simulation. All methods were able to capture the general spatial pattern of both erosivity indices. The semivariogram analysis revealed that spatial autocorrelation only affected at distances of ~15 km around the observatories. Therefore, local interpolation techniques tended to be better overall considering the validation statistics. All models showed high uncertainty, caused by the high variability of rainfall erosivity indices both in time and space, what stresses the importance of having long data series with a dense spatial coverage.


1999 ◽  
Vol 84 (3) ◽  
pp. 719-725 ◽  
Author(s):  
John A. Wagner ◽  
Jeffrey A. LePine

Stimulated by recent debate, this study investigated whether prior research supports the statement that different forms of participation have different effects on performance and satisfaction in the workplace. Using a collection of 75 correlations drawn from published analyses, a meta-analysis using random effects procedures indicated that relationships between participation and performance reported in the research literature are similar in size and direction across different types of participation. Meta-analytic results also indicated similarity in the size and direction of relationships between participation and satisfaction across different forms of participation and suggested that effect size statistics published in research on participation and performance are generally similar to those reported in studies of participation and satisfaction. These findings differ from the results of another recent meta-analysis and from those of several previous literature reviews but support the primary conclusions of an earlier meta-analytic assessment.


2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Anmin Fu ◽  
Yulin Cai ◽  
Tao Sun ◽  
Feng Li

Great efforts have been made to curb soil erosion and restore the natural environment to Inner Mongolia in China. The purpose of this study is to evaluate the impact of returning farmland to the forest on soil erosion on a regional scale. Considering that rainfall erosivity also has an important impact on soil erosion, the effect of land use and land cover change (LUCC) on soil erosion was evaluated through scenario construction. Firstly, the universal soil loss equation (USLE) model was used to evaluate the actual soil erosion (2001 and 2010). Secondly, two scenarios (scenario 1 and scenario 2) were constructed by assuming that the land cover and rainfall-runoff erosivity are fixed, respectively, and soil erosion under different scenarios was estimated. Finally, the effect of LUCC on soil erosion was evaluated by comparing the soil erosion under actual situations with the hypothetical scenarios. The results show that both land use/cover change and rainfall-runoff erosivity change have significant effects on soil erosion. The land use and land cover change initiated by the ecological restoration projects have obviously reduced the soil erosion in this area. The results also reveal that the method proposed in this paper is helpful to clarify the influencing factors of soil erosion.


2021 ◽  
Vol 217 ◽  
pp. 103611
Author(s):  
Antonio Girona-García ◽  
Diana C.S. Vieira ◽  
Joana Silva ◽  
Cristina Fernández ◽  
Peter R. Robichaud ◽  
...  

2011 ◽  
Vol 2011 ◽  
pp. 1-10 ◽  
Author(s):  
Rachna Agarwal ◽  
Chandra Bhushan Tripathi

CSF tau and Aβ42 are considered as important markers to diagnose Alzheimer’s disease in early stages. Hence, it is important to assess their status in different types of dementia. The main objective of this study was to assess whether these CSF biomarkers can be used to make the differential diagnosis of AD. In the present study, articles published from 1998 till 2009 were taken and meta-analysis was performed to clarify the consistency in trends of biomarkers- CSF tau and Aβ42in AD and other dementias and whether the same can be used as diagnostic biomarkers for its early diagnosis. 11 out of 60 for CSF tau and 07 out of 40 for CSF Aβ42, dementia case-control studies were selected for final analysis. Descriptive statistics shows that median effect size (raw mean difference) of CSF tau was 429 pg/mL (range: 32 to 910 pg/mL) in AD whereas in Dementia due to other causes (DOC) studies it was 69 pg/mL (range: −53 to 518 pg/mL). Similarly the median effect size of CSF Aβ42levels was −442 pg/mL (range: −652 to −41.200 pg/mL) whereas in DOC studies it was −193 pg/mL (range: −356 to −33 pg/mL).


Land ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 604
Author(s):  
Yonghua Zhao ◽  
Li Liu ◽  
Shuaizhi Kang ◽  
Yong Ao ◽  
Lei Han ◽  
...  

The Loess Plateau of China suffers from severe erosion, which results in a great variety of economic and ecological problems. For scientific control of soil erosion, the key questions urgently to be addressed in this paper are: (1) Which are the driving factors under diverse geomorphological types? (2) Do these driving factors operate independently or by interacting? (3) Which zones under diverse geomorphological types suffer from severe erosion and need more attention? In this paper, the RUSLE model was applied here to demonstrate the spatio-temporal variations in soil erosion from 2010 to 2017 in Yan’an City, and the Geo-detector model proved to be a useful tool to solve the questions mentioned above. The results showed that the average erosion modulus in Yan’an City decreased by 1927.36 t/km2·a from 2010 to 2017. The intensity of soil erosion in the northern Baota District, central Ganquan County, Luochuan County, Ansai County, and Zhidan County decreased to varying degrees. The effect size of driving factors affecting soil erosion varied significantly in diverse geomorphological types. The effect size of interaction between land-use types and vegetation coverage, land-use types and slope, slope and precipitation was higher than that of a single factor. High-risk zones with severe erosion were closer to cultivated land and forest land with steep slopes (>25°) in the mid-elevation hills of Yan’an City. Additionally, based on the specificity of the study area, the Geo-detector model performed better in a relatively flat region, and factors with macroscopic spatial distributions weaken its explanatory power on soil erosion on a regional scale. Based on data selection, data of different accuracy sparked the issue of “data coupling”, which led to the enormous deviation of model results in mid-elevation plains. Results from our analysis provide insights for a more ecologically sound development of Yan’an City and provide references for the scientific use of the Geo-detector model.


2009 ◽  
Vol 6 (1) ◽  
pp. 417-453 ◽  
Author(s):  
M. Angulo-Martínez ◽  
M. López-Vicente ◽  
S. M. Vicente-Serrano ◽  
S. Beguería

Abstract. Rainfall erosivity is a major causal factor of soil erosion, and it is included in many prediction models. Maps of rainfall erosivity indices are required for assessing soil erosion at the regional scale. In this study a comparison is made between several techniques for mapping the rainfall erosivity indices: i) the RUSLE R factor and ii) the average EI30 index of the erosive events over the Ebro basin (NE Spain). A spatially dense precipitation data base with a high temporal resolution (15 min) has been used. Global, local and geostatistical interpolation techniques were employed to produce maps of the rainfall erosivity indices, as well as mixed methods (regression plus local interpolation). To determine the reliability of the maps several goodness-of-fit and error statistics were computed, using a cross-validation scheme. All methods represented correctly the spatial patterns of both erosivity indices, but the mixed approaches tended to be better overall considering the validation statistics. Additionally, they allowed identifying statistically significant relationships between rainfall erosivity and other geographical variables, as elevation and distance to the water bodies. All models had a relatively high uncertainty, caused by the high variability of rainfall erosivity indices both in time and space, what stresses the importance of using the longest data series available with a good spatial coverage.


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