Seasonal Decomposition Rates of Broadleaf and Conifer Wood Litter in Far Eastern Tropical Forest Communities

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Introduction
Te process of litter decomposition, also known as litter mineralization, refers to the physical, chemical, and biological processes involved in breaking down litter into simpler chemical elements [1]. Litter decomposition is the most important process in the nutrient cycle to restore soil fertility in most forest ecosystems [2]. Wood is one of the components of litter that takes longer to decompose [3].
Many studies of forest litter decomposition have been conducted, especially in temperate regions [4,5]. However, information on the pattern of litter decomposition, in particular wood litter, among forest communities, and the factors that could potentially determine the rate of the decomposition process are insufcient, unclear, and ambiguous [6]. While low temperatures during winter in temperate regions are reported to halt the activity of decomposing agents [7], temperature changes in the tropics, especially around the equator, are less noticeable throughout the year [8]. Many studies have also shown that the rate of decomposition is directly proportional to rainfall [9,10]. Meanwhile, the facts refect that in the warmest and wettest tropical regions around the equator in the Far East, such as on the Indonesian islands of Sumatera and Kalimantan (Indonesian Borneo), many forest ecosystems where peat accumulates on the forest foor indicate that the decomposition process is not going well [11].
Several studies in temperate climates have also revealed that due to the allelopathic content of leaf litter, the decomposition process in coniferous forests is slower than that in broadleaf forests [12,13]. However, such research in the tropics is lacking, as conifer species are not common in the tropics. As with fne litter, there are multiple factors that have the potential to determine the rate of decomposition of wood litter [7]. Tese factors mutually infuence and may have diferent impacts on litter decomposition rates in certain forest community. Te factors controlling the rate of decomposition may difer in diferent climate regions and diferent forest communities [14], whereas in tropical climates, rainfall is a major determinant of seasonal patterns. Terefore, the rate of decomposition will be diferent in diferent forest types and seasons.
In this study, we compared the rate of decomposition of broadleaf wood with coniferous wood between seasons in three tropical forest communities on Sulawesi Island, Indonesia: secondary broadleaf karst forest, secondary broadleaf lowland forest, and Pinus merkusii Jungh. & de Vriese plantation. We designed a wood decomposition experiment using wood from two species of trees: Anthocephalus macrophyllus (Roxb.) Havil. (jabon) wood as a representative of broadleaf wood and Pinus merkusii (tusam) wood as a representative of coniferous wood. By examining the decomposition of tusam wood outside of Pine forests and broadleaf wood within Pine forests, we intend to fnd out whether tusam wood also decomposes slowly in broadleaf forests, and conversely whether broadleaf wood decomposes slowly in Pine forests. We also intend to examine the intrinsic and extrinsic factors that play a role in the decomposition process of the two wood samples in the three forest communities.
Given that many studies have reported that pine leaves contain allelopathic substances [15,16], we predicted that the diversity of decomposing agents, especially of microorganisms in Pine forests, is lower than that in Karst and Lowland forests. Tis may have implications for the slower rate of wood decomposition in the Pine (P. merkusii) forest compared to broadleaf forests for both jabon wood and tusam wood. However, since no studies report that tusam wood contains allelopathic substances, unlike its leaves, we predicted that there would be no diference in the rate of decomposition between jabon wood and tusam wood either in the Pine forest or broadleaf forest communities. Since soil pH is positively related to the diversity and abundance of microorganisms, especially bacteria [17], we predicted that the rate of decomposition in Karst forests would be the highest among the three studied forests.

Study Site.
We conducted this study in three secondary forests regenerated after shifting cultivation on Sulawesi Island, Indonesia: a 45-year-old secondary karst forest (Karst forest hereafter), a 54-year-old secondary lowland forest (Lowland forest hereafter), and a 58-year-old P. merkusii plantation forest (Pine forest hereafter). Previously, Putra et al. [18] assigned permanent plots of 1 ha in each forest community to analyse the structure and species composition of the forest community (Table 1). We carried out this research in the same plots.
Te three forest communities are in the same climate type (climate type C), characterized by two distinct seasons in a year: the dry and wet seasons [19]. Te dry season normally occurs from May to October and the wet season from November to April. However, due to El Niño and La Niña, the dry season and wet season may be longer or shorter than usual ( Figure 1).

Wood Decomposition Experiments.
To observe the rate of wood decomposition in each forest community, a decomposition experiment was carried out using two materials: (a) jabon (Anthocephalus macrophyllus; Rubiaceae) wood planks as a representative of broadleaf tree wood and (b) tusam (Pinus merkusii; Pinaceae) wood planks as a representative of coniferous wood. Each wooden plank was made into a square with dimensions of 10 cm on all sides and a thickness of 1.5 cm.
A total of 1,200 wooden planks consisting of 600 jabon planks and 600 tusam wood planks were dried in an oven at 60°C. Te oven-dried wooden planks were weighed individually, and the fgures were recorded as the initial weight. Each wooden plank was tagged with a numbered label made of Dymo tape. Pairs consisting of one jabon wood plank and one tusam wood plank each were connected using a 20 cm long nylon rope, so that there were 600 pairs of jabon wood-tusam wood planks.
At the beginning of the dry season (1-2 May 2019), 100 pairs of jabon wood-tusam wood planks were placed in 50 experimental points and were systematically and evenly distributed in each plot. Tere were two pairs of wooden planks at each experimental point. Te nylon rope connecting each pair of wooden planks was tied to a peg, which was driven into the ground to keep the planks from moving. Once a month, at the beginning of each month, every wood plank sample was monitored, and any changes found were recorded. Hereafter, this frst experiment will be referred to as Wood Plank jabon 1 (WPJ1) and Wood Plank tusam 1 (WPT1) ( Table 2). International Journal of Forestry Research Six months later, at the end of the dry season (1-2 November 2019), 50 pairs of wooden planks (one pair from each point) were collected and brought to the laboratory. Te wooden planks collected from the feld were carefully cleaned of adhering soil using a soft brush and then dried in an oven at 60°C. Te oven-dried weight of each remaining non-biodegradable wood sample (hereafter referred to as WPJ1-6 for jabon planks and WPT1-6 for tusam planks) was recorded according to the tag number as the undecomposed residual weight. When the 50 pairs of planks from each experimental point were collected on 1-2 November 2019, 100 new pairs (two pairs at each point) were placed for a similar experiment, starting in a diferent season: the beginning of the wet season. Hereafter, this second experiment will be referred to as Wood Plank jabon 2 (WPJ2) and Wood Plank tusam 2 (WPT2) ( Table 2).
On 1-2 May 2020 (12 months after the frst experiment placement), the remaining 50 pairs of WPJ1-WPT1 (hereafter referred to as WPJ1-12 and WPT1-12) were collected. At the same time, 50 pairs of WPJ2-WPT2 (hereafter referred to as WPJ2-6 and WPT2-6) were collected. After being cleaned carefully using a soft brush and dried in an oven at 60°C, the remaining wood plank samples that had not been decomposed were weighed individually and recorded as the weight of the undecomposed residue after 12 months for WPJ1-12 and WPT-12, or after six months for WPJ2-6 and WPT2-6.
On 1-2 November 2020 (12 months after being placed in the feld), the remaining 50 pairs of WPJ2 and WPT2 (hereafter referred to as WPJ2-12 and WPT2-12) were collected from the feld and brought to the laboratory, where they were cleaned, dried in the oven, and weighed. Te oven-dried weight was recorded as the remaining weight that had not been decomposed after 12 months. Te same experiment, but with diferent placement periods in the feld, was designed to compare the rate of decomposition between seasons.

Chemical Analysis of Wooden
Planks. Chemical analysis of the wooden planks was carried out at the Laboratory of Feed Chemistry, Faculty of Animal Husbandry, Hasanuddin University. Te analysis began with 10 g wood samples taken from 10 jabon wood planks and 10 tusam wood planks. Jabon wood samples from 10 planks were mixed and dried.    Te same was done for the tusam wood samples. Each dried sample of jabon wood and tusam wood was then crushed separately to obtain a fne powder sample of each. Te analytical method used was diferent according to the chemical compound to be analysed. Te content of lignin, cellulose, and hemicellulose was analysed using the Van Soest method and the appliance used was Fibertec. Carbohydrate content was analysed using the Luf-Schoorl method and the appliance used was Buret. Polyphenol and tannin contents were analysed using the Folin-Ciocalteu method and the appliance used was UV-Vis spectrophotometer. Te methanol extraction method was used to analyse resin content. As for the determination of N, P, K, Ca, Mg, and Mn, the analytical method used was the atomic absorption spectrophotometer (AAS) method.

Decomposing Agent: Bacteria and Microscopic Fungi.
Decomposing microorganisms, including microscopic fungi and bacteria, were inoculated from rotten wood samples collected randomly from each permanent plot. Te inoculated fungal and bacterial samples were analysed through polymerase chain reaction (PCR) analysis at the Biotechnology Laboratory, Faculty of Forestry, Hasanuddin University. Te results of the PCR analysis were then sent to PT Genetika Science Indonesia for sequencing analysis to determine the fungal and bacterial species. Only the species composition can be analysed, not the abundance of each species. Sampling of wood for microfauna analysis was only done once, during the transition from the dry season to the wet season, with the consideration that PCR analysis will detect the presence of genes for microorganisms that are active in the dry or wet season, or both.

Decomposing Agent: Macroscopic
Fungi. In addition to using the PCR method, the diversity of macroscopic fungi was also surveyed from their visible fruiting bodies, which are commonly called mushrooms (hereafter referred to as macroscopic fungi). Te survey was conducted once per season (i.e., in the dry season and wet season) on 25 subplots measuring 10 m × 10 m that were systematically distributed throughout the permanent plot of each forest community. Surveys in the wet season were carried out within three to fve days after heavy rain. Each species was identifed directly in the feld using several digitally illustrated mushroom guidebooks, and each species name was recorded. Species that could not be identifed in the feld were photographed for identifcation in the laboratory or by a mushroom specialist. As with microscopic fungi, we did not measure the abundance (cover area) of macroscopic fungi. Tis is because diferent fungal species did not grow into mature fruiting bodies simultaneously. In one survey, there were clumps that had just grown to the hyphal knot stage and were expanding their area cover, clumps that were already at the pinhead stage, clumps that had grown into fully developed mushrooms, and clumps that were mostly rotten. Terefore, the fungal colony cover data from the instantaneous survey did not refect the conditions throughout the year.

Decomposing Agent: Macrofauna in the Soil.
Te survey of the diversity and abundance of macrofauna in the soil was carried out using a rectangular sampling ring made of 1.00 mm thick metal plates measuring 20 cm wide × 20 cm long × 10 cm deep. One side of the sampling ring surface was made sharp so that it could be easily plugged into the ground. Te sampling ring was plugged into the ground until the upper sides were fush with the ground. Te soil in the sampling ring was dug up and placed into a plastic pot, and all macrofaunas found in the soil were collected.
Macrofaunas collected from the sample rings were separated by species and placed into small specimen bottles containing 70% ethanol. In each plot, sampling was carried out 10 times, with each sample located near the experimental points. decomposition. Terefore, the thermometer was placed at a height of about 1 m from the ground rather than placing it directly above the ground. It was assumed that the temperature at the ground's surface was not purely the ambient temperature that could potentially afect the rate of decomposition but the temperature created by the decomposition process itself. Monthly maximum and minimum temperatures were recorded on the 1st or 2nd day each month (Figure 1).

Data Analyses.
Te decomposition rate is expressed in terms of the decomposition rate constant (k) calculated using the model: where Yl � the lost mass of wood sample, Yt � litter weight at time t (months), Yo � initial litter weight, k � decomposition rate constant, e � natural logarithm, and t � decomposition time [20]. Mean abundance of soil macrofauna and mean value of soil chemical properties were compared between seasons in each forest community and between forest communities using analysis of variance (ANOVA) with Tukey's honest signifcant diference (HSD) method.Te k values between seasons and between forest communities were compared using the independent sample non-parametric K with Kruskal-Wallis as the data were not normally distributed. Te distribution normality of our data was tested using the Shapiro-Wilk test.
Te associations between k of each wood sample and microorganism diversity, k of each wood sample and macrofauna abundance, and k of each wood sample and soil properties were analysed using Pearson's correlation analysis for normally distributed data and Spearman's correlation analysis for non-normally distributed data. All statistical analyses were performed using the R version 4.2.1 application [21].

Comparison in Decomposition Rate between Seasons and between Forests.
Te mean k values varied inter-seasonally and between forest communities. Te mean k value of WPJ1-6 was signifcantly greater than that of WPJ2-6 across forest communities (P � 0.0383; P < 0.001; and P < 0.001, respectively, in Karst, Lowland, and Pine forests; Figure 2 (top left)). Compared with WPT2-6, the mean k value of WPT1-6 was not signifcantly diferent in the Karst forest (P � 0.9204) but was signifcantly smaller in Lowland forests (P � 0.0182) and conversely signifcantly greater in the Pine forests (P � 0.01; Figure 2 (top right)).
Te mean k value of WPJ1-12 was not signifcantly diferent compared to WPJ2-12 in the Karst forest (P � 0.1914). However, in the Lowland forest and Pine forest, the mean k value of WPJ1-12 was signifcantly greater compared to WPJ2-12 (P < 0.001 in Lowland forest and P < 0.001 in Pine forest) (Figure 2 (bottom left)). Tere was no signifcant diference in the mean k value between WPT1-12 and WPT2-12 in all forest communities (P � 0.0672; P � 0.1060; and P � 0.6666, respectively, in the Karst, Lowland, and Pine forests) (Figure 2 (bottom right)).

Decomposition Rate Constants between Diferent Sample
Materials. Te mean k value between jabon wood samples and tusam wood samples varied between forest communities in each season ( Figure 3). However, it was generally noted that in the dry season, the mean k value of jabon wood sample was signifcantly greater than that of tusam wood sample (P < 0.001 in Karst forest and in Pine forest), except in the Lowland forest where there was no signifcant diference (P � 0.3125). During the wet season, the mean k value of jabon wood sample was similar to that of tusam wood sample in the Karst and Pine forests (P � 0.1060 in Karst forest and P � 0.6319 in Pine forest). However, in the Lowland forest, the mean k value of jabon wood sample was signifcantly lower than that of tusam wood sample (P < 0.001).
For the 12-month experiment starting from the dry to the wet season, the mean k value of jabon wood was not signifcantly diferent from that of tusam wood sample in all forest communities (P � 0.2568; P � 0.0830; and P � 9259, respectively, in the Karst, Lowland, and Pine forests), although numerically, the value was higher for jabon. However, in the experiment starting from the wet to the dry season, the mean k value of jabon wood sample was signifcantly smaller than that of tusam wood sample in all forest communities (P � 0.0416; P < 0.001; and P � 0.0340, respectively, in the Karst, Lowland, and Pine forests).

Chemical Traits of Sample Wood Experiment.
Te chemical content varies in a complex manner between wood samples. Te content of carbohydrates, lignins, and tannins in the jabon wood samples was greater than that in the tusam wood samples (Table 3). Alternatively, the content of cellulase, hemicellulose, resin, and polyphenols in jabon wood samples was lower than that in the tusam wood samples. Te content of N, Ca, P, Mg, and K was greater in jabon wood samples than in tusam wood samples, while the content of Mn was lower in jabon wood samples than in tusam wood samples.
Unfortunately, the diference in chemical traits between the two wood samples could not be statistically analysed, as the data lack replication. To analyse the chemical traits of

Diversity of Decomposing Bacteria and Fungi vs. Decomposition Rate Constant.
Trough PCR analysis of rotted wood samples collected from the plots, the identities of microscopic bacterial and fungal species could be discerned, but not their abundance. As predicted, there were fewer microbial species in the Pine forest than in the broadleaf forests (Karst and Lowland). A total of six bacterial species were confrmed in the three forest communities studied. Among them, four species were found in the Karst forest, two in the Lowland forest, and two in the Pine forest (Table 4). Burkholderia cepacia was confrmed in the Karst and Pine forests, and Burkholderia cenocepacia was confrmed in the Lowland and Pine forests. Tree species (Bacillus cereus, Burkholderia sp., and Burkholderia ubonensis) were specialists in the Karst forest. Bacillus thuringiensis was a specialist in the Lowland forest. Meanwhile, no specialist bacterial species were found in the Pine forest. Tere were ten confrmed microscopic fungal species in the three forest communities. Among them, only one species (Talaromyces pinophilus) was found in all forest communities; two species (Trichoderma virens and Aspergillus aculeatus) were found only in Karst forests; three species (Penicillium pinophilum, Trichoderma sp., and Aspergillus sp.) were found only in Lowland forests; two species (Penicillium citrinum and Cladosporium tenuissimum) were found only in Pine forests; and two other species (Aspergillus terreus and Aspergillus japonicus) were found in Karst and Lowland forests (Table 4).
For macroscopic fungi, we found a total of 130 species across forest communities: 65 species in Karst forest (7 in the dry season, 48 in the wet season, and 10 shared in both seasons), 67 in Lowland forest (12 in the dry season, 41 in the wet season, and 14 shared in both seasons), and 42 species in Pine forest (10 in the dry season, 29 in the wet season, and 3 shared in both seasons) (Figure 4). Of the 65 species found in the Karst forest, 39 species were specialists in this forest community. In the Lowland forest, 32 of the 67 species found were specialists only in this forest community. Meanwhile, 24 of 42 species found in the Pine forest were specialists only in this forest community. In all forest communities, macroscopic fungal species were more diverse in the wet season than in the dry season.
Te mean number of macroscopic fungi species per 100 m 2 (sub-plot) during the dry season was the highest in the Lowland forest (3.88 ± 0.28), the second highest in the Karst forest (2.20 ± 0.28), and the lowest in the Pine forest (1.32 ± 0.28) (P < 0.001). In the wet season, the mean number of macroscopic fungi species per 100 m 2 was similar between the Karst forest (7.20 ± 0.61) and Lowland forest (7.84 ± 0.61) but signifcantly lower in the Pine forest (3.64 ± 0.61) (P < 0.001). Correlation analyses only detected a signifcant association between the number of species of bacteria and the k of the 12-month experiment on tusam wood (WPT2-12).

Decomposing Agent Macrofauna vs. Decomposition Rate
Constant. Trough observations using rectangular sampling rings and pitfall traps, 39 species of macrofauna were found in the soil and on the forest foor, including termites, ants, cockroaches, centipedes, earthworms, and the larvae of several insect species. In Table 5, only the seven dominant species potentially associated with wood decomposition, such as feeding on wood or utilising rotted wood as a nest, were listed. Odontotermes sp. (termites) was the most common macrofauna species caught in the rectangular sampling ring, while Odontomachus sp. was the most common macrofauna species caught in the pitfall traps. ANOVA analysis with Tukey's HSD method showed that Odontotermes sp. was caught more in the dry season, while Eudrilus eugeniae, Willowsia sp., and Xyleborus sp. were more caught in the wet season. Other species did not show signifcant diferences in abundance between seasons.
Correlation analysis showed that the mean value of k only signifcantly correlated with the abundance of several macrofauna species in a particular season. For the macrofauna caught from rectangular sampling rings, a signifcant association was only noted in the dry season between mean k value of WPJ1-6 and the abundance of Odontotermes sp. (P � 0.0364). However, for the macrofauna caught by pitfall trap, signifcant correlations were noted only in the 12month experiments started in the dry season toward the wet season between WPJ1-12 and Solenopsis geminata (P < 0.001), between WPJ1-12 and Ips sp. (P � 0.0398), and between WPT1-12 and Odontomachus sp. (P � 0.0188).

Soil Properties vs. Decomposition Rate Constant.
Among the examined soil properties, C, N, P, K, and CEC values were consistently higher in the dry season than in the wet season across forest communities (Table 6). Correlation analysis showed no signifcant relationship between any of the 11 soil properties examined and the mean k value of the two wood samples over the six-month experiment. Tis insignifcant relationship occurred across forest communities both in the dry season and the rainy season.. For a 12month experiment starting from the onset of the dry season, a signifcant correlation was found only between Na and the

Discussion
Our study aimed to determine the diferences in the k value of jabon wood (broadleaf ) and tusam wood (conifer) between two seasons and three forest communities. In addition, we intended to investigate the factors associated with   International Journal of Forestry Research diferences in k value. Although statistical analyses showed a sporadic pattern of mean k value between seasons, in general, there was a trend that for the jabon wood sample (WPJ), the mean k value in the dry season was higher than that in the wet season, and vice versa for tusam wood (WPT), for which the mean k value in the dry season was lower than that in the wet season. Te jabon wood's higher mean k value in the dry season than in the wet season can be explained by the results of correlation analysis, which shows a signifcant association between the abundance of Odontotermes sp. and jabon wood mean k values in the dry season (WPJ1-6). Several previous studies, however, reported conficting results regarding the correlation between the season and Odontotermes sp.
attacks. While Cheik et al. [47] reported the benefcial impact of Odontotermes spp. on water infltration in soil, several other studies found that the foraging activity of this termite species was lower in the hot-wet season [48,49], although the abundance of workers was positively correlated with relative humidity [48]. Te declining population of Odontotermes sp. during the wet season at the study site is thought to be related to the increase in the population of several ant species that often function as predators, such as Odontomachus sp., Solenopsis geminata, and Paratrechina longicornis.
Te opposite trend was shown by tusam wood which shows a higher mean k value in the wet season than in the dry season. Tusam wood distinctly contains more  hemicellulose (9.68%) than jabon wood (3.97%). Hemicellulose signifcantly increases the water absorption behaviour and wettability of wood so that it can potentially reduce wood's resistance to microorganisms [50,51]. Other studies also reported that the abundance of decomposing microorganisms was greater in humid and warm environmental conditions [52]. Tis study showed a signifcant positive correlation between the mean k value of WPT2-12 and the number of species of bacteria. In addition, this study showed that the number of species of macroscopic fungi was greater in the wet season than in the dry season. Unfortunately, we do not have data about the diference in the diversity of microscopic fungi between seasons. Data that are not normally distributed and the insignifcant diference of mean k values between the 12month experiment starting at the onset of the dry season and the onset of the wet season, in particular for tusam wood samples, implies that the diference in the initial conditions of the decomposition process does not afect the process throughout the year. Wood that begins with a faster decomposition process in the dry season does not decompose faster in the following wet season. Conversely, wood that begins with a slower decomposition process in the wet season does not decompose more slowly in the following dry season. Te presence of a suitable decomposing agent at a time seems to have a more signifcant efect on the rate of decomposition than the climatic conditions at the start of the wood decomposition process. Tis fnding suggests that diferent woods may be favoured by diferent decomposing agents, each of which has diferent seasonal abundance patterns. Te macrofauna Odontotermes sp. had a stronger infuence than microorganisms in determining the rate of wood decomposition during the early process of decomposition (see also [53]). In a longer decomposition process, physical environmental factors can infuence microbial activity more efectively than macrofauna either directly or indirectly [54].
As predicted, this study revealed that the highest mean k value of the two species of wood samples was recorded in the Karst forest and the lowest in the Pine forest, except for WPT1-6. Tis fnding suggests that, just as in temperate regions [55,56], the litter decomposition rate in the Pine forest in the tropics is also slower than that in broadleaf forests. Several previous studies have reported microbes' critical role in wood decomposition, especially fungi [57,58]. In this study, diferences in mean k value between forest communities are proportional to diferences in the number of microbial species, especially macroscopic fungi, between forest communities. In addition, among soil chemical properties, pH and C were signifcantly lower in the Pine forest compared to the Karst and Lowland forests. However, correlation analyses showed that the disparity in the number of microbial species between forest communities was statistically not related to diferences in mean k value among forest communities. Tis may be due to the insufcient number of variables analysed, in which only three forest communities were compared.
Lower k value in Pine forests occurred for both tusam and jabon wood samples. Kimura et al. [15] succeeded in isolating two main inhibitors determined by spectral data, namely, 9α,13β-epidioxyabeit-8(14)en-18-oic acid and abscisic acid-β-D-glucopyranosyl ester, from the foliage of red pine (Pinus densifora). Tus, it can be assumed that the slow decomposition of tusam wood in Pine forests is not caused by intrinsic factors, but rather by extrinsic factors, one of which can be allelopathic substances contained in pine leaf litter on the forest foor.
While we can generally draw trends, statistical analysis of these studies showed sporadic and sometimes conficting results. Tis would not likely be due to the insufcient number of replicates, considering that each treatment consisted of 50 replicates, with a total sample size of 1,200 wooden planks. Te data disparity from one place to another is sometimes very high, which has implications for datasets that are not normally distributed. Tese results are in accordance with a previous study by Powers et al. [59], which states that the factors that infuence the decomposition process are complex and may vary by site. Each of several previous studies reported various factors that afected the litter decomposition process, ranging from UV radiation and visible light [60]; mesofauna [59]; macrofauna, earthworms, and arthropod abundance [61]; wood substrate quality [58]; tree species, temperature, and precipitation [62]; bacterial species [63]; and rainfall [9]. Trough very complex interaction patterns, all of these decomposing agents and environmental factors play a role in the decomposition of litter. In the tropics, this pattern of interactions can be more complex and mutual due to the high diversity of decomposing agents at the microenvironmental level, and this leads to diferences in k values, even within the same forest community. Between two forest communities that do not difer in macro-and microclimatic conditions, biodiversity, or specimen richness, the communities of decomposing agents on the forest foor can difer signifcantly [64].

Conclusion
Although there is a tendency for the k value of jabon wood to be higher during the dry season than the rainy season, and vice versa for tusam wood, and a tendency for the k value of both wood samples to be higher in the broadleaf forest than in Pine forest, the data show high disparity even within the same season and forest community. Te results of the statistical analysis show that most of the data are not normally distributed. Tis is due to the high diversity of decomposing agents and environmental factors in the tropics, where they work in very complex reciprocal associations. Environmental factors such as rainfall and soil chemistry can afect the k value directly and individually or indirectly and collectively through the activity of decomposing agents at diferent levels. Te results of many controlled experimental studies conducted in the laboratory may be able to show how a single decomposing agent afects the rate of decomposition, but this may not be the case in the feld. Terefore, feld research on various forest communities in the tropics is still needed to determine the accumulative working patterns of decomposing agents and the infuence International Journal of Forestry Research of environmental factors on the rate of decomposition of wood litter.

Data Availability
Te data used to support the fndings of this study are available from the corresponding author upon request.

Disclosure
Te funder had no role in the research design, in data collection, in data analysis and interpretation, in writing the manuscript, and in the decision to publish the results.

Conflicts of Interest
Te authors declare that they have no conficts of interest.