\documentclass[10pt]{article}

\usepackage{fullpage}
\usepackage{setspace}
\usepackage{parskip}
\usepackage{titlesec}
\usepackage[section]{placeins}
\usepackage{xcolor}
\usepackage{breakcites}
\usepackage{lineno}
\usepackage{hyphenat}





\PassOptionsToPackage{hyphens}{url}
\usepackage[colorlinks = true,
            linkcolor = blue,
            urlcolor  = blue,
            citecolor = blue,
            anchorcolor = blue]{hyperref}
\usepackage{etoolbox}
\makeatletter
\patchcmd\@combinedblfloats{\box\@outputbox}{\unvbox\@outputbox}{}{%
  \errmessage{\noexpand\@combinedblfloats could not be patched}%
}%
\makeatother


\usepackage{natbib}




\renewenvironment{abstract}
  {{\bfseries\noindent{\abstractname}\par\nobreak}\footnotesize}
  {\bigskip}

\titlespacing{\section}{0pt}{*3}{*1}
\titlespacing{\subsection}{0pt}{*2}{*0.5}
\titlespacing{\subsubsection}{0pt}{*1.5}{0pt}


\usepackage{authblk}


\usepackage{graphicx}
\usepackage[space]{grffile}
\usepackage{latexsym}
\usepackage{textcomp}
\usepackage{longtable}
\usepackage{tabulary}
\usepackage{booktabs,array,multirow}
\usepackage{amsfonts,amsmath,amssymb}
\providecommand\citet{\cite}
\providecommand\citep{\cite}
\providecommand\citealt{\cite}
% You can conditionalize code for latexml or normal latex using this.
\newif\iflatexml\latexmlfalse
\providecommand{\tightlist}{\setlength{\itemsep}{0pt}\setlength{\parskip}{0pt}}%

\AtBeginDocument{\DeclareGraphicsExtensions{.pdf,.PDF,.eps,.EPS,.png,.PNG,.tif,.TIF,.jpg,.JPG,.jpeg,.JPEG}}

\usepackage[utf8]{inputenc}
\usepackage[ngerman,english]{babel}



\usepackage{float}








\begin{document}

\title{Not our cup of tea: the Tea Bag Index (Kueskamp et al. 2013) for
assessing decomposition is problematic in most environments, due to
macrofauna}



\author[1]{Paul Eggleton}%
\author[2]{Hannah Griffiths}%
\author[3]{Louise Ashton}%
\author[2]{Stephanie Law}%
\author[4]{T.A.  Evans}%
\author[2]{Kate Parr}%
\affil[1]{Natural History Museum}%
\affil[2]{University of Liverpool}%
\affil[3]{University of Hong Kong}%
\affil[4]{University of Western Australia}%


\vspace{-1em}



  
  \date{June 18, 2024}


\begingroup
\let\center\flushleft
\let\endcenter\endflushleft
\maketitle
\endgroup





\selectlanguage{english}
\begin{abstract}
1. The Tea Bag Index (Keuskamp et al. 2013) has been developed to allow
worldwide comparable data on litter decomposition and has become an
important part of several citizen science projects. This commentary
shows that it is unsuitable for assessing total decomposition in most
environments as it does not account for the role of macrofauna in the
decomposition process. 2. Tea bags were placed following the
standardised protocol in old growth forest in Borneo (Sabah, East
Malaysia). 3. The results shows that more than half of the bags were
attacked by termites and they tended to remove the majority of the tea,
rendering the Tea Bag Index incalculable. 4. The Tea Bag Index can
measure the microbial component of decay, but will significantly
underestimate total decay rates in most environments. This method will
not give an accurate estimate of decomposition in most biomes.%
\end{abstract}%



\sloppy


\textbf{Introduction}

Decomposition is a vital part of ecosystem functioning, contributing
fundamentally to nutrient cycling (Bazzaz 1998). It is recognised as one
of the most important ecological processes (Krishna \& Mohan 2017), and
so measuring it accurately is important; for this purpose it is
necessary to find standardised methods, and the easier the method, the
more widely it can be used.

The Tea Bag Index was proposed by (Keuskamp \emph{et al.} 2013) as a
standardised protocol to quantify microbial decomposition. It is a
simple and attractive idea. Using just two different types of
commercially available tea bags, bags are deployed for 90 days and, from
their final weight, a measure of decomposition, known as the Tea Bag
Index (TBI), is calculated. The method is intended for researchers and
other interested people without a background in decomposition research,
and is perfectly suited to citizen science projects
(http://www.teatime4science.org/ , www.spotteron.com/teabagindex). The
method has now been widely used across numerous countries and has formed
the basis for a various scientific publications (Ogden 2017; Becker \&
Kuzyakov 2018).

The approach is ingenious. It uses two types of teabags: rooibos and
green tea. The aim was to develop a method that will allow a single
placement of teabags and enable the decay constant \emph{k} to be
calculated for the slower decaying tea. The theory behind this is well
established -- there is, in every decaying piece of plant material, a
slow (``refractory'') and a fast (``labile'') decomposing fraction
which, under ideal conditions, will all decay (i.e. those under
conditions of highest decomposition). Not all of the labile fraction of
the rooibos tea will decay, slowed due toa larger recalcitrant fraction
in the rooibos tea than in the green tea. The labile fraction has been
estimated chemically, as 0.842 in green tea and 0.552 in rooibos tea
(see Keuskamp et al. 2013). Under most natural conditions, not even all
of the labile fraction of the green tea will have decomposed; a measure
of this is S, the stabilisation factor. S is calculated by assessing the
proportion of the potential labile fraction that remains. Assuming that
the rooibos tea shows a similar rate of loss of the labile fraction to
the green tea, but that that fraction is a smaller proportion of the
total, then proportional loss of the labile fraction per unit time of
the rooibos tea can be calculated, and therefore \emph{k} , the
decomposition rate calculated\emph{.} The measures \emph{k} and S are
then used as the ``Tea Bag Indices''. Figure 3 in Keuskamp et al. (2013)
shows these two estimates for sites across a range of habitats from rain
forest to deserts with higher values in rain forest and lower values in
desert.

Determing the Tea Bag Index relies on the important assumption that all
agents of decomposition (i.e. microbe and invertebrates) are included in
the assay. However, this may not be the case in all circumstances. In
colder temperate and boreal regions fungal decay is by the far the most
important factor in dead plant decay, but in hotter and wetter, more
tropical, regions, a large portion of decomposition is carried out by
macrofauna (especially termites; (Cornwell \emph{et al.} 2009);
(Handa\emph{et al.} 2014; Griffiths \emph{et al.} 2019). In temperate
regions invertebrates such as earthworms, woodlice and millipedes also
play an important role, albeit secondary to microbes (Wall \emph{et al.}
2008; Smith \emph{et al.} 2009).

Furthermore, termites need special consideration for two reasons. First,
they are dominant decomposers in many habitats between 45\selectlanguage{ngerman}° north and
south (Tuma, Eggleton \& Fayle In press).Second, termites can chew
through many materials, including plastics (Lenz \emph{et al.} 2012),
and so may gain access to the tea leaves in the bags (i.e. chew the bags
open -- this is true for all types of litter bags). When this happens,
the termites frequently consume all the contents of the tea bags;
consequently the resulting data will have more zeros than those expected
due to microbial decomposition alone. Under these conditions, it is
impossible to calculate the real rate of `\emph{k} ', as noted by
Keuskamp et al. 2013 for samples left for 12 months . Additionally, the
assumption that the recalcitrant fraction is essentially untouched is
violated by termites (or other invertbrates that gain access) because
they may remove a large proportion of tea, of both fractions. Therefore,
in the presence of termites, removal of the tea from the bag will appear
as the total decay of the tea by microbial agents, resulting in type I
statistical errors. With these concerns in mind, here, we test the Tea
Bag method to assess its performance in Bornean tropical rain forest (a
hot and humid environment) with a high density of termites
(Ashton\emph{et al.} 2019).

\textbf{Methods}

We conducted the experiment in the Maliau Basin Protected Area in a
region of lowland old growth dipterocarp forest in Bornean Malaysia (the
area is described in (Griffiths \emph{et al.} 2018) and in
(Ashton\emph{et al.} 2019). In order to test the method, we buried 60
green tea bags and 60 rooibos tea bags (of a known weight) at random
within the forest at a depth of 8 cm as recommended by Keuskamp et al.
(2013). We collected 20 of each type sacrifically at 7, 14 and 60 days.
We weighed each of the bags after collection and noted if they had been
chewed opened by macrofauna. We left them out for 60 days rather than
the recommended 90 days as our preliminary work showed that by 90 days
most of the bags had holes in them and many were emptied. Keuskamp et al
2031 recommended reducing incubation time in ``extreme sites\ldots{}
with extremely high k values (e.g. sites with high temperature and
precipitation like site 13 in their study -- which was rainforest in
Panama).

In order to examine how effective the method is in tropical rain forest,
we investigated the relationship between weight loss, the time that the
bags were left out, and whether the bags had holes in them (i.e. opened
by macrofauna). We expressed this as a \% mass loss per bag, which was
logit transformed for analysis (following (Warton \& Hui 2011) so that
we could use standard Gaussian linear models. Using R (R core team,
2013), we also tested the following full-interaction model, using
the\emph{lm} command:

\emph{lg \textasciitilde{} days\_gnd * hole\_tbN * type\_tbN}

Where lg = logistic transformed mass-loss data; days\_gnd = number of
days the tea bags were left in the ground; hole\_tbn = the presence of
holes in the tea bag; type\_tbN = the type of tea used (G or R).

\textbf{Results and Discussion}

After 60 days on the forest floor, we found that just over half of the
bags of both tea types had been chewed through by macrofauna: 31
{[}52\%{]} of the rooibos tea and 30 bags {[}50\%{]} of the green tea.
In our model the only significant terms were the type of tea (rooibos or
green) and the interaction between the state of the bags (opened or
unopened) and the tea type (see Table 1 for model outputs). There was no
significant effect of time on the decomposition rate. This meant that
generally green tea decomposed more rapidly than the rooibos tea.
However, where the bags were opened, rooibos tea showed a greater
response than in green tea, where the open and closed bags had very
similar decay slopes (Table 1, Fig 1). This serves to illustrate that
the major problem with the TBI in the tropics is with the rooibos tea
bags, which were commonly attacked by macrofauna (probably predominantly
termites) and the contents often completely removed. In our study, more
than half of the rooibos tea bags were chewed open, and more than 10\%
were emptied. A similar proportion of green tea bags were chewed open,
but none of them were emptied. It seems that macrofauna, at least in
this context, prefer rooibos tea to green tea.

It is possible to estimate the two tea bag parameters in a subset of
bags without holes (i.e. estimate from the undamaged bags, estimating
microbial and mesofaunal decomposition only); the values here were S =
0.242 and \emph{k} = 0.053. This \emph{k} value from Bornean rainforst
is higher than any values in the original teabag paper, including the
tropical rain forest site in Panama (S = 0.06, k = 0.0392; Keuskamp et
al. 2013 site 13, Table S1). This is, however, a measure of microbial
decay only, as the macrofauna were specifically excluded. Keuskamp et
al. 2013 could not calculate the standard deviation for their Panama
site, `due to overdispersion' of data. It is possible that holded
teabags, empty of tea, may have contributed to this overdispersion.

However, it is difficult to assess projects that have used the TBI in
the exact way it was recommended, as the method specifically excludes
bags that have been chewed. Therefore they are self-selected for
microbial and mesofauna decay and explicitly exlude any macrofauna
decay.

If the aim is to quantify microbial decomposition it is therefore
possible if only undamaged bags are used. However, sufficient bags need
to be buried so that one can afford to ignore damaged ones. We suggest
that given half of the bags were damaged at least twice as many are
needed (\textgreater{}40 in this case for every period, giving a total
of 120). Furthermore, the incubation time (ie the time the tea bags are
left out) should be reduced to 60 days, as by 90 days many of the
teabags would be likely to be chewed by termites (note we recorded
50\%).

The TBI is a valuable idea but our results show it can only give an
accurate idea of \textbf{total} decomposition rates in the few locations
where invertebrate decomposition is negligible and there is
overwhelmingly microbial decomposition (e.g. boreal areas). It works as
a measure of microbial decomposition alone in all locations provided the
bags are not damaged. Unfortunately, the TBI does not incorporate a
measure for including the effects of larger decomposers.

We see no easy way to incorporate the contribution of macrofauna
(particularly termites) to decomposition processes using the TBI,
without also putting tea bags into macroinvertebrate litter bags made
with mesh strong enough to withstand termite attack (such as stainless
steel mesh or nylon; (Yates \& Grace 1999; Lenz \emph{et al.} 2012) .
Other papers that use small and large mesh sizes to exclude or include
macrofauna may suffer the same issue (eg (Handa \emph{et al.} 2014)) if
the small sized mesh material is not strong enough, then some samples
may (are likely) to be attacked by termites.

This is because of the very high stochasticity that termites, in
particular, contribute to the process. The problem becomes one of
modelling two different simultaneous processes: one an exponential decay
process and the other potentially a binomial process (either the bags
are opened or they are not). There are other more costly methods, in
both time and expertise, that produce robust total decomposition results
and assess the contribution of all decomposer organisms, such as using
leaf litter and wood decomposition assays and mesh to include/exclude
invertebrates (e.g. (Smith \emph{et al.} 2009; Davies \emph{et
al.}2013). However, these methods are not in the spirit of the TBI (see
Fig 1), which was designed to produce a quick, simple estimate of two
meaningful parameters.

In summary, the TBI can work well to assess the microbial contribution
to decomposition where no (or few) bags are opened by macrofauna, such
as in boreal locations, but the method risks seriously underestimating
total (microbial + macrofauna) decomposition in most habitats.
(Wall\emph{et al.} 2008) present a global map showing the areas where
macrofauna (not always termites) are important in dead plant
decomposition processes, althoughthis figure significantly downplays the
effect of macrofauna (especially termites) in savannas, grasslands and
other drier areas (Bignell \& Eggleton 2000). Wall et al. 2008 used moth
balls (active ingredient naphthalene) to exclude invertebrates. As with
any insecticidal active ingredient, it has variable effects on different
species of insect\ldots{}

Termites appear to manufacture naphthalene (possibly secreted by
themselves, but more likely via microbes(Chen \emph{et al.} 1998)). So
the treatement would have a reduced effect on termites.

While Keuskamp et al. (2013) do specifically state that macrofauna are
excluded they make no other comment about the errors that this might
introduce. We believe that any method that ignores the contribution of
macrofauna to plant decomposition cannot be recommended as a global
method. It may still be useful for estimating purely-microbial effects
but it cannot yield measures that include all decay agents.

Data accessibility: the data for this paper has been deposited in DRYAD,
doi: TBA

Table 1\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
Variable & Estimate & Std. Error & t-value\tabularnewline
\midrule
\endhead
intercept & -0.703 & 0.123 & -5.696***\tabularnewline
Number of days & 0.006 & 0.004 & 1.61 n.s.\tabularnewline
Presence of holes & 0.042 & 0.186 & 0.83 n.s.\tabularnewline
Type of tea & -0.774 & 0.175 & -4.427***\tabularnewline
Days*holes & 0.000 & 0.006 & 0.983 n.s.\tabularnewline
Days*type & 0.006 & 0.006 & 0.315 n.s.\tabularnewline
Type*holes & 0.661 & 0.264 & 2.505*\tabularnewline
Days*holes*type & -0.009 & 0.008 & 0.2625n.s.\tabularnewline
\bottomrule
\end{longtable}

Table 1. Result of fully interactive linear model testing the effect our
focal variables on the mass lost from rooibos and green tea bags.
Asterix indicate significant effects * \emph{P} \textless{} 0.05,,
***P\textless{}0.001 and n.s. non-significant.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

Figure 1. The significant effect of the interaction between holes in
teabags (triangles are teabags without holes, circles are those with
holes) and tea type (green tea = green points, rooibos = orange points).
Lines display fitted values from linear model outputs. Green lines are
green tea, organe lines are rooibos, dashed lines are teabags with
holes, and solid lines are those without. The ribbons show standard
errors around model fitted values. There is clear difference in the
response to having holes of the two types of tea: The green tea shows
little difference between opened (ie chewed open) and unopened (ie
intact) bags; the rooibos clearly shows more decomposition when the bags
have holes.

\textbf{References}

Ashton, L.A., Griffiths, H.M., Parr, C.L., Evans, T.A., Didham, R.K.,
Hasan, F., Teh, Y.A., Tin, H.S., Vairappan, C.S. \& Eggleton, P. (2019)
Termites mitigate the effects of drought in tropical
rainforest.\emph{Science,} \textbf{363,} 174.

Bazzaz, F. (1998) Tropical forests in a future climate: Changes in
biological diversity and impact on the global carbon
cycle.\emph{Climatic Change,} \textbf{39,} 317-336.

Becker, J.N. \& Kuzyakov, Y. (2018) Teatime on Mount Kilimanjaro:
Assessing climate and land-use effects on litter decomposition and
stabilization using the Tea Bag Index. \emph{Land Degradation \&
Development,} \textbf{29,} 2321-2329.

Bignell, D. \& Eggleton, P. (2000) Termites in Ecosystems. \emph{DE
Bignell - Termites: evolution, sociality, symbioses, ecology, 2000} .
Kluwer Academic Publishers.

Chen, J., Henderson, G., Grimm, C.C., Lloyd, S.W. \& Laine, R.A. (1998)
Termites fumigate their nests with naphthalene.
\emph{Nature,}\textbf{392,} 558-559.

Cornwell, W.K., Cornelissen, J.H.C., Allison, S.D., Bauhus, J.,
Eggleton, P., Preston, C.M., Scarff, F., Weedon, J.T., Wirth, C. \&
Zanne, A.E. (2009) Plant traits and wood fates across the globe: rotted,
burned, or consumed? \emph{Global Change Biology,}
\textbf{15,}2431-2449.

Davies, A.B., Van Rensburg, B.J., Eggleton, P. \& Parr, C.L. (2013)
Interactive Effects of Fire, Rainfall, and Litter Quality on
Decomposition in Savannas: Frequent Fire Leads to Contrasting
Effects.\emph{Ecosystems,} \textbf{16,} 866-880.

Griffiths, H., Ashton, L., Walker, A., Hasan, F., Evans, T., Eggleton,
P. \& Parr, C. (2018) Ants are the major agents of resource removal from
tropical rainforests. \emph{Journal of Animal Ecology,}
\textbf{87,}293-300.

Griffiths, H.M., Ashton, L.A., Evans, T.A., Parr, C.L. \& Eggleton, P.
(2019) Termites can decompose more than half of deadwood in tropical
rainforest. \emph{Current Biology,} \textbf{29,} R118-R119.

Handa, I.T., Aerts, R., Berendse, F., Berg, M.P., Bruder, A.,
Butenschoen, O., Chauvet, E., Gessner, M.O., Jabiol, J., Makkonen, M.,
McKie, B.G., Malmqvist, B., Peeters, E.T.H.M., Scheu, S., Schmid, B.,
van Ruijven, J., Vos, V.C.A. \& H\selectlanguage{ngerman}ättenschwiler, S. (2014) Consequences
of biodiversity loss for litter decomposition across
biomes.\emph{Nature,} \textbf{509,} 218-221.

Keuskamp, J.A., Dingemans, B.J.J., Lehtinen, T., Sarneel, J.M. \&
Hefting, M.M. (2013) Tea Bag Index: a novel approach to collect uniform
decomposition data across ecosystems. \emph{Methods in Ecology and
Evolution,} \textbf{4,} 1070-1075.

Krishna, M.P. \& Mohan, M. (2017) Litter decomposition in forest
ecosystems: a review. \emph{Energy, Ecology and Environment,}\textbf{2,}
236-249.

Lenz, M., Creffield, J.W., Evans, T.A., Kard, B., Vongkaluang, C.,
Sornnuwat, Y., Lee, C.-Y., Yoshimura, T. \& Tsunoda, K. (2012)
Resistance of polyamide and polyethylene cable sheathings to termites in
Australia, Thailand, USA, Malaysia and Japan: A comparison of four field
assessment methods. \emph{International Biodeterioration \&
Biodegradation,} \textbf{66,} 53-62.

Ogden, L.E. (2017) Brewing Big Data: The Tea-Bag
Index.\emph{BioScience,} \textbf{67,} 680-680.

Smith, J., Potts, S.G., Woodcock, B.A. \& Eggleton, P. (2009) The impact
of two arable field margin management schemes on litter
decomposition.\emph{Applied Soil Ecology,} \textbf{41,} 90-97.

Tuma, J., Eggleton, P. \& Fayle, T. (In press) Ant-termite interaction:
an important but under-explored ecological linkage. \emph{Biological
Reviews} .

Wall, D.H., Bradford, M.A., St. John, M.G., Trofymow, J.A.,
Behan-Pelletier, V., Bignell, D.E., Dangerfield, J.M., Parton, W.J.,
Rusek, J., Voigt, W., Wolters, V., Gardel, H.Z., Ayuke, F.O., Bashford,
R., Beljakova, O.I., Bohlen, P.J., Brauman, A., Flemming, S., Henschel,
J.R., Johnson, D.L., Jones, T.H., Kovarova, M., Kranabetter, J.M.,
Kutny, L.E.S., Lin, K.-C., Maryati, M., Masse, D., Pokarzhevskii, A.,
Rahman, H., SabarÁ, M.G., Salamon, J.-A., Swift, M.J., Varela, A.,
Vasconcelos, H.L., White, D.O.N. \& Zou, X. (2008) Global decomposition
experiment shows soil animal impacts on decomposition are
climate-dependent. \emph{Global Change Biology,} \textbf{14,} 2661-2677.

Warton, D.I. \& Hui, F.K.C. (2011) The arcsine is asinine: the analysis
of proportions in ecology. \emph{Ecology,} \textbf{92,} 3-10.

Yates, R. \& Grace, J. (1999) TERMITE RESISTANT CONSTRUCTION AND
BUILDING MATERIALS. \emph{Proceedings of the 3rd International
Conference on Urban Pests,} \textbf{3,} 399-406.

\selectlanguage{english}
\FloatBarrier
\end{document}

