scholarly journals Boosting soil citizen-science using Tea Bag Index method towards soil security in Australia

Soil Security ◽  
2021 ◽  
Vol 5 ◽  
pp. 100016
Author(s):  
Vanessa Pino ◽  
Alex McBratney ◽  
Eugenia O'Brien ◽  
Wartini Ng
Soil Research ◽  
2020 ◽  
Vol 58 (4) ◽  
pp. 371
Author(s):  
Betânia Guedes Souza e Brito ◽  
Maria das Dores Magalhães Veloso ◽  
Judith M. Sarneel ◽  
Luiz Alberto Dolabela Falcão ◽  
Juliana Martins Ribeiro ◽  
...  

Decomposition of plant litter is a crucial process in carbon and nutrient cycling in all ecosystems, but our understanding of drivers of this process in Brazilian Cerrado (savanna) ecosystems is limited. We determined the decomposition rate and the stabilisation factor in areas of cerrado sensu stricto and palm swamp (vereda) in Bonito de Minas, Minas Gerais, south-eastern Brazil. These two major Cerrado ecosystems differ markedly in environmental conditions, but primarily in water and soil conditions. We used the standardised Tea Bag Index method, characterised soil parameters, and microbial activity to evaluate the decomposition process between these ecosystems. We found higher decomposition rates in the palm swamp compared to cerrado sensu stricto, possibly due to higher soil temperature and humidity conditions and higher microbial biomass.


2020 ◽  
Author(s):  
Christian Schneider ◽  
Susanne Döhler ◽  
Luise Ohmann ◽  
Ute Wollschläger

<p>Citizen science approaches are still relatively rare in soil sciences. However, the Tea Bag Index (TBI) has been successfully implemented in projects all over the world.</p><p>Our citizen science project “Expedition ERDreich – Mit Teebeuteln den Boden erforschen” (EE) aims to upscale open soil data by applying the TBI as well as other soil assessment methods all over Germany. Beside the strong focus on creating awareness for soils and its functions we want to answer the following questions:</p><ol><li> <p>Is it possible to upscale citizen science projects to obtain large quantities of open soil data?</p> </li> <li> <p>Are soil datasets from citizen science projects of sufficient quality to be used in soil science and for soil modeling?</p> </li> </ol><p>The project will combine aspects of co-production as well as environmental education. Co-production means, soil data will individually be compiled by citizen scientists with the support of a team of scientists from a network of project partners. While conducting various soil assessments and experiments participating citizen scientists will be given background information and guidance meant to educate and to raise awareness about soils and soil quality.</p><p>We are aiming to involve a broad spectrum of citizens from various backgrounds, for example school children, students, farmers, forest owners, gardeners, municipal administrations, and of course soil scientists.</p><p>Within the project citizen scientists will submit turnover data from their location, together with information on the sampling sites, as well as information on soil properties like pH value, soil texture, and soil color. This information will be complemented with climatic and geo-scientific co-variables by the scientific project team.</p><p>So far we identified the following main challenges:</p><ul><li> <p>How can citizens from various backgrounds and in various geographical locations be addressed and involved in the project?</p> </li> <li> <p>How do we get high quality soil data while still teaching soil awareness?</p> </li> <li> <p>How do we address the complexity of soils in soil education?</p> </li> <li> <p>How do we manage the quality of data and identify potential errors?</p> </li> <li> <p>How do we communicate data management procedures to keep the project as transparent as possible?</p> </li> <li> <p>What and how can we give back an added value to citizen scientists?</p> </li> </ul><ul><li> <p>How do we involve citizen scientists in the scientific progress beyond collecting data and beyond the current projects timeframe?</p> </li> </ul>


2019 ◽  
Vol 35 (1) ◽  
pp. 126-136 ◽  
Author(s):  
Tour Liu ◽  
Tian Lan ◽  
Tao Xin

Abstract. Random response is a very common aberrant response behavior in personality tests and may negatively affect the reliability, validity, or other analytical aspects of psychological assessment. Typically, researchers use a single person-fit index to identify random responses. This study recommends a three-step person-fit analysis procedure. Unlike the typical single person-fit methods, the three-step procedure identifies both global misfit and local misfit individuals using different person-fit indices. This procedure was able to identify more local misfit individuals than single-index method, and a graphical method was used to visualize those particular items in which random response behaviors appear. This method may be useful to researchers in that it will provide them with more information about response behaviors, allowing better evaluation of scale administration and development of more plausible explanations. Real data were used in this study instead of simulation data. In order to create real random responses, an experimental test administration was designed. Four different random response samples were produced using this experimental system.


1990 ◽  
Vol 137 (1) ◽  
pp. 27 ◽  
Author(s):  
P.C. Kendall ◽  
M.J. Robertson ◽  
P.W.A. McIlroy ◽  
S. Ritchie ◽  
M.J. Adams

1990 ◽  
Vol 137 (1) ◽  
pp. 21 ◽  
Author(s):  
M.S. Stern ◽  
P.C. Kendall ◽  
P.W.A. McLlroy

2015 ◽  
Vol 77 (08/09) ◽  
Author(s):  
L Del Savio ◽  
A Buyx ◽  
B Prainsack
Keyword(s):  

2019 ◽  
Vol 41 (6) ◽  
pp. 963-1000
Author(s):  
Minsu Park ◽  
Younghee Noh
Keyword(s):  

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