Learning Science during Teatime: Using a Citizen Science Approach to Collect Data on Litter Decomposition in Sweden and Austria

Sandén, Taru; Spiegel, Heide; Wenng, Hannah; Schwarz, Michael P.; Sarneel, Judith M.

doi:10.3390/su12187745

Cited by 13 publications

(11 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Section: Litter Decompositionsupporting

confidence: 89%

“…Our results support both previous global (Keuskamp et al, 2013) and local (Sandén et al, 2020) studies on litter decomposition based on the Tea Bag Index methodology. The decomposition rates we calculated were similar to those reported for the Pannonian environmental zone by Sandén et al (2020), which reflects the fact that most of our present sites are in the Pannonian environmental zone. The stabilization factors were somewhat higher, 0.20 compared to 0.14, than for the Pannonian environmental zone in Sandén et al (2020), possibly due to the nature of urban soils in our study compared to croplands, grasslands and forests in the other study.…”

Section: Litter Decompositionsupporting

confidence: 89%

“…The decomposition rates we calculated were similar to those reported for the Pannonian environmental zone by Sandén et al (2020), which reflects the fact that most of our present sites are in the Pannonian environmental zone. The stabilization factors were somewhat higher, 0.20 compared to 0.14, than for the Pannonian environmental zone in Sandén et al (2020), possibly due to the nature of urban soils in our study compared to croplands, grasslands and forests in the other study. Interestingly, our results on stabilization factors agree well with Duddigan et al (2020) who studied Tea Bag Index in domestic gardens in the United Kingdom, even though the climatic factors were quite different to our sites.…”

Section: Litter Decompositionsupporting

confidence: 87%

“…These challenges can be overcome with the appropriate mindset, determination and curiosity (van Dijk-Wesselius et al, 2020), which should be backed up by superiors. Measuring litter decomposition with the Tea Bag Index (Keuskamp et al, 2013) as part of the teaching curriculum has successfully been used in school settings in Sweden and Austria, with the involvement of motivated teachers (Sandén et al, 2020). Showing teachers that their intelligence, knowledge and creativity are appreciated by and included in the project promotes beneficial participatory cooperation that can be sustained longterm (Wildschut, 2017).…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

TeaTime4Schools: Using Data Mining Techniques to Model Litter Decomposition in Austrian Urban School Soils

et al. 2021

Self Cite

View full text Add to dashboard Cite

Litter decomposition plays a pivotal role in the global carbon cycle, but is difficult to measure on a global scale, especially by citizen scientists. Here, citizen scientists, i.e., school students with their teachers, used the globally applied and standardized Tea Bag Index (TBI) method to collect data on litter decomposition in urban areas in Austria. They also sampled soils to investigate the linkages between litter decomposition and soil attributes. For this study, 54 sites were selected from the school experiments and assembled into a TBI dataset comprising litter decomposition rates (k), stabilization factors (S), as well as soil and environmental attributes. An extensive pre-processing procedure was applied to the dataset, including attribute selection and discretization of the decomposition rates and stabilization factors into three categories each. Data mining analyses of the TBI data helped reveal trends in litter decomposition. We generated predictive models (classification trees) that identified the soil attributes governing litter decomposition. Classification trees were developed for both of the litter decomposition parameters: decomposition rate (k) and stabilization factor (S). The main governing factor for both decomposition rate (k) and stabilization factor (S) was the sand content of the soils. The data mining models achieved an accuracy of 54.0 and 66.7% for decomposition rates and stabilization factors, respectively. The data mining results enhance our knowledge about the driving forces of litter decomposition in urban soils, which are underrepresented in soil monitoring schemes. The models are very informative for understanding and describing litter decomposition in urban settings in general. This approach may also further encourage participatory researcher-teacher-student interactions and thus help create an enabling environment for cooperation for further citizen science research in urban school settings.

show abstract

Section: Litter Decompositionsupporting

confidence: 89%

Section: Litter Decompositionsupporting

confidence: 89%

Section: Litter Decompositionsupporting

confidence: 87%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

TeaTime4Schools: Using Data Mining Techniques to Model Litter Decomposition in Austrian Urban School Soils

et al. 2021

Self Cite

View full text Add to dashboard Cite

show abstract

“…2. The results are well within the range of summer data previously reported from Austria (Buchholz et al, 2017;Keuskamp et al, 2013;Sandén et al, 2020) (Sandén et al, 2021). However, to the best of our knowledge, we are the first ones to 200 report data during four seasons.…”

Section: Soil Chemical Characteristics and Tea Bag Indexsupporting

confidence: 92%

Pairing litter decomposition with microbial community structures using the Tea Bag Index (TBI)

Daebeler

Petrová

Kinz³

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

Abstract. Including information about soil microbial communities into global decomposition models is critical for predicting and understanding how ecosystem functions may shift in response to global change. Here we combined a standardised litter bag method for estimating decomposition rates, Tea Bag Index (TBI), with high-throughput sequencing of the microbial communities colonising the plant litter in the bags. Together with students of the Federal College for Viticulture and Fruit Growing, Klosterneuburg, Austria, acting as citizen scientists, we used this approach to investigate the diversity of prokaryotes and fungi colonising recalcitrant (rooibos) and labile (green tea) plant litter buried in three different soil types and during four seasons with the aim of (i) comparing litter decomposition [decomposition rates (k) and stabilisation factors (S)] between soil types and seasons, (ii) comparing the microbial communities colonising labile and recalcitrant plant litter between soil types and seasons (iii) correlating microbial diversity and taxa relative abundance patterns of colonisers with litter decomposition rates (k)and stabilisation factors (S). Stabilisation factor (S), but not decomposition rate (k), correlated with the season and was significantly lower in the summer. This finding highlights the necessity to include colder seasons in the efforts of determining decomposition dynamics in order to quantify nutrient cycling in soils accurately. With our approach, we further showed selective colonisation of plant litter by fungal and prokaryotic taxa sourced from the soil. The community structures of these microbial colonisers differed most profoundly between summer and winter, and rooibos litter was generally a stronger selector than green tea litter. Moreover, this study indicates an equal, if not higher, importance of fungal versus prokaryotic degraders for recalcitrant and labile plant litter decomposition. Our results collectively demonstrate the importance of analysing decomposition dynamics over multiple seasons and isolating the effect of the active component of the microbial community.

show abstract

Effects of initial leaching for estimates of mass loss and microbial decomposition—Call for an increased nuance

Lind

Harbicht

Bergman

et al. 2022

Ecology and Evolution

View full text Add to dashboard Cite

Decomposition is essential to carbon, nutrient, and energy cycling among and within ecosystems. Several methods have been proposed for studying litter decomposition by using a standardized and commercially available substrate. One of these methods is the Tea Bag Index (TBI) which uses tea bags (green and rooibos tea) incubated for ~90 days. The TBI is now applied all over the globe, but despite its usefulness and wide application, the TBI (as well as other methods) does not explicitly account for the differences in potential loss of litter mass due to initial leaching in habitats with large differences in moisture. We, therefore, studied the short‐term mass losses (3–4 h) due to initial leaching under field and laboratory conditions for green and rooibos tea using the TBI and contextualized our findings using existing long‐term mass loss (90 days) in the field for both aquatic and terrestrial environments. For both tea litter types, we found a fast initial leaching rate, which could be mistaken for decomposition through microbial activity. This initial leaching was higher than the hydrolyzable fraction given in the description of the TBI. We also found that leaching increased with increasing temperature and that leaching in terrestrial environments with high soil moisture (>90%) is almost as large as in aquatic environments. When comparing our findings to long‐term studies, we found that up to 30–50% of the mass loss of green tea reported as decomposition could be lost through leaching alone in high moisture environments (>90% soil moisture and submerged). Not accounting for such differences in initial leaching across habitats may lead to a systematic overestimation of the microbial decomposition in wet habitats. Future studies of microbial decomposition should adjust their methods depending on the habitat, and clearly specify the type of decomposition that the study focuses on.

show abstract

Learning Science during Teatime: Using a Citizen Science Approach to Collect Data on Litter Decomposition in Sweden and Austria

Cited by 13 publications

References 47 publications

TeaTime4Schools: Using Data Mining Techniques to Model Litter Decomposition in Austrian Urban School Soils

TeaTime4Schools: Using Data Mining Techniques to Model Litter Decomposition in Austrian Urban School Soils

Pairing litter decomposition with microbial community structures using the Tea Bag Index (TBI)

Effects of initial leaching for estimates of mass loss and microbial decomposition—Call for an increased nuance

Contact Info

Product

Resources

About