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Using tree functional diversity to evaluate management impacts in a subtropical forest R. MAESHIRO, B. KUSUMOTO, S. FUJII, T. SHIONO,

AND

Y. KUBOTA 

Faculty of Science, University of the Ryukyus, Nishihara, Okinawa 903-0213 Japan Citation: Maeshiro, R., B. Kusumoto, S. Fujii, T. Shiono, and Y. Kubota. 2013. Using tree functional diversity to evaluate management impacts in a subtropical forest. Ecosphere 4(6):70. http://dx.doi.org/10.1890/ES13-00125.1

Abstract. The trait-based approach has received much research attention as it provides a heuristic framework for evaluating the ecological impacts of anthropogenic activities on communities and ecosystems. In this study, functional diversity (or structure) measures, such as functional richness, functional evenness, functional divergence, and functional composition, were used to examine management impacts on subtropical forests on the Ryukyu Islands of Japan. Functional indices were compared in tandem with taxonomic diversity indices between three forest types with different management histories: intact old-growth forests, secondary forests after clear-cutting, and abandoned Pinus luchuensis plantations. Species diversity indices were not significantly different among the three forest types. In contrast, functional diversity indices were significantly different among intact forests and managed forests. Functional richness and functional evenness were significantly lower in secondary forests than in intact forests and P. luchuensis plantations. Functional divergence was significantly higher in secondary forests and P. luchuensis plantations than in intact forests. These differences suggest that management activities affected niche space and the patterns of niche differentiation among component species in the functional space of managed forests. Community weighted means for each functional trait were also different among the forest types. The managed forests had greater leaf thickness, leaf dry matter content and maximum height, and lower specific leaf area and leaf nitrogen concentration than intact forests. These differences in functional composition of traits suggested potential functional impacts. This study demonstrated the utilization of species functional traits and community functional structure as a tool of natural experiment for assessing impacts of forest management practices on woodland ecosystems. It was also suggested that logging activities that include large-scale clear-cutting or establishment of P. luchuensis plantations may be incompatible with the conservation of natural ecosystem properties in subtropical forests. Key words: biodiversity conservation; ecosystem functioning; forest management; functional composition; functional divergence; functional evenness; functional richness; plantation; secondary forest; species richness. Received 7 April 2013; revised 4 May 2013; accepted 6 May 2013; published 18 June 2013. Corresponding Editor: C. Kwit. Copyright: Ó 2013 Maeshiro et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. http://creativecommons.org/licenses/by/3.0/   E-mail: [email protected]

INTRODUCTION

practices that are based on the retention of original communities and their component organisms is a pressing challenge for forest scientists and managers (Gustafsson et al. 2012). Forest biodiversity has mostly been assessed using taxonomic information such as patterns

The conversion of forests from complex natural ecosystems to simplified managed woodlands is a major cause of biodiversity loss (Butchart et al. 2010). Devising sustainable forest management v www.esajournals.org

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of species richness (e.g., Verburg and van EijkBos 2003, Kubota et al. 2004, Kariuki et al. 2006, Lindenmayer et al. 2006). However, to understand the cascading effects of biodiversity loss during forest conversions and to develop more sustainable management practices, forest ecologists need to determine how individual species contribute to ecosystem properties, such as structure, dynamic processes, and biophysical functioning. Biodiversity assessments should include information on functional and/or life history traits of the species within biological assemblages (He´rault et al. 2005, McGill et al. 2006). Recently, a trait-based approach has received much attention, providing a heuristic framework for evaluating ecological impacts of anthropogenic activities on woodlands (Baraloto et al. 2012, Carre˜no-Rocabado et al. 2012, Katovai et al. 2012). Species-specific functional traits that control plant growth, survival, and reproduction are key biological indicators of the environmental requirements and/or tolerances of individual taxa (Westoby et al. 2002). Among woody plants, leaf and stem traits are core functional traits (Wright et al. 2004, Chave et al. 2009) that drive species assembly processes (Paine et al. 2011), growth dynamics (He´rault et al. 2011), stability (Biswas and Mallik 2011) and carbon and nutrient cycling (Weedon et al. 2009) in forest communities. To understand the response of these ecological processes to environmental factors, it is important to scale-up species traits to community level or ecosystem level metrics (Violle et al. 2007). Functional diversity might be a tool for predicting the functional consequence of species traits in ecosystem level processes (Petchey and Gaston 2006). Also, functional diversity has the potential to be a proxy for quantifying the niche space of a given assemblage and niche differentiation among member species in the functional space (Mouchet et al. 2010). Thus, functional diversity acts as an interface for improved understanding of (1) ecological processes (e.g., environmental filter effects and dispersal limitation) that govern species sorting in a community (Pakeman 2011) and (2) ecosystem functioning in terms of the complementarity of resource use and functional redundancy among component species (Naeem 1998, Dı´az et al. 2007). In fact, functional diversity measures are being rapidly v www.esajournals.org

developed in a multitude of ways that represent functional patterns among component species, such as functional richness, functional evenness, and functional divergence (e.g., Mason et al. 2005, Cornwell et al. 2006, Mouchet et al. 2008). Use of these measures emphasizes the functional composition of taxonomic species diversity and informs the exploration of mechanistic links between biodiversity and ecosystem functioning (Naeem and Wright 2003, Balvanera et al. 2006, Biswas and Mallik 2010). The response of functional diversity (measured as species reassembly) to land use intensification, including forest practices, can be used to evaluate impacts of anthropogenic disturbances on community/ ecosystem properties (Flynn et al. 2009, Mayfield et al. 2010). Clear-cutting of intact forest to establish timber plantations is one of the most drastic procedures used in forest management. In temperate and subtropical forests, planting of coniferous species to replace stands of more diverse hardwoods is a profound anthropogenic disturbance that has raised concerns about the consequences for biodiversity conservation (Emmer et al. 1998, Kanowski et al. 2005). Such silvicultural practices often induce environmental changes and alter patterns of tree species richness and/or ecosystem functioning (Bremer and Farley 2010). Thus, managed forests require ecological restoration for resurrection of their former ecosystem goods and services. The causal relationship between loss of species diversity and loss of ecosystem function in managed forests has been poorly studied, yet a full understanding of this relationship is crucial for determination of the ecological impacts of forestry and for setting restoration goals in management practice. Studies on differences in functional composition and functional diversity among types of forest management may provide snapshot assessments of the influence of species diversity (mediated by speciesspecific functional traits) on critical aspects of ecosystem functioning, such as carbon storage (Baraloto et al. 2012) and nutrient cycling (Mason et al. 2012). The objective of this study was to examine differences in functional diversity and functional composition among forests exposed to different management practices in subtropical evergreen broad-leaved forests on the Ryukyu Islands in 2

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southern Japan. Patterns of tree species richness were investigated in intact old-growth forests, secondary forests developed after clear-cutting, and Pinus luchuensis plantation forests abandoned after establishment. Functional traits were measured in all tree species. By combining data on species composition and species-specific functional traits, community functional measures were compared among the forest types with different management histories. Specifically, the following question was investigated: do taxonomic species diversity, functional diversity, and/ or functional composition differ between intact forests and managed forests? Finally, the compatibilities between forest management practices and biodiversity conservation were discussed on the basis of functional impacts on community/ ecosystem properties.

such as mowing or thinning. Plantations of P. luchuensis had been created until 1973 in ’1500 ha of the clear-cut areas (Shinohara 1977). The plantations were then abandoned after planting, and are gradually converting to natural forest. Castanopsis sieboldii is the dominant species in the early development stage of the extant subtropical forests. Cinnamomum doederleinii and Planchonella obovata are light requiring pioneer species that dominate in the secondary forest, and Syzygium buxifolium and Aidia canthioides are subordinate species in young secondary stands. In intact oldgrowth forest, Machilus japonica and Quercus miyagii occur in the canopy and subcanopy, and Antidesma japonicum and Ardisia quinquegona occur in the understory.

Measurements of forest structure Eleven plots of 400 m2 were established from 2004 to 2006 in the intact old-growth forest (IF; Fig. 2a), 15 plots in the secondary forest (SF; Fig. 2b), and 15 plots in the plantation forest (PF; Fig. 2c) on a gentle slope approximately 10–270 m above sea level in six areas (Fig. 1). The plots in the secondary forest and plantation forest were .40 years old. These stands were arbitrarily chosen based on the availability of logging records, accessibility, and site conditions (having the same bed rock and soil type). The relatively small plot sizes used in this study were designed to reduce topographical heterogeneity in plots such as small ridges and valleys within a single sampling plot. All trees (including multi-stem sprouts) .2 m tall were tagged within each plot. Heights and diameters at breast height (DBH) were measured to determine whether individual stems had sprouted from other trees.

METHODS Site description The subtropical forests on the Ryukyu Islands in southern Japan are a plant diversity and endemicity hotspot among the world’s floras (Mittermeier et al. 2005). This study was conducted on Iriomote Island (24820 0 N, 123850 0 E) in the southern part of the Ryukyu Islands (Fig. 1). The island is located between the warm temperate and tropical zones and had a mean monthly temperature range of 18.0–28.98C from 1981 to 2010. Typhoons with strong winds (.15 ms1 maximum wind velocity) between June and October and monsoon winds in winter put stress on the forests. The maximum wind velocity on Iriomote Island was 39.1 ms1 from 2000 to 2011. Typhoons also bring frequent heavy rain and precipitation on the island annually varies from 1900 to 4000 mmyr1. The bedrock of most of the island belongs the Iriomote formation consisting of conglomerate, sandstone, and siltstone (Nakagawa et al. 1982). Soil of the forest area is lesshumus yellow or brownish-yellow soil (Kobayashi 1961). Forest cover of the island is shaped by evergreen broad-leaved tree species, which account for 90% of the island area (’26000 ha). A large part of the forest is secondary forest logged once in the past; within the secondary forests, one third of them have been deforested during the last century. The secondary forests had grown after clear-cuts and had no additional treatments v www.esajournals.org

Tree trait measurements To build a database of tree functional traits, leaf and stem traits of tree species on the Ryukyu Islands were determined. Samples from five individuals per species across the islands, including those on Iriomote were collected. Four shoots with leaves were collected from each tree. Using a sickle attached to a 15 m pole, shoots from sun exposed parts in the canopy of each tree were collected. Wood cores for trees were sampled using an increment borer. For smaller trees (,10 cm DBH), parts of stems were 3

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Fig. 1. Iriomote Island on the Ryukyu Islands, southwestern Japan. The sampled plots located in six areas (surrounded by dotted-line) represent three forest types (intact old-growth, secondary forest developed after clear-cutting, and P. luchuensis plantation forest abandoned after planting). The elevation map was drawn using 500 m mesh data.

collected using pruning shears. Overall, 5160 shoots and 1302 wood (or stem) samples for 280 species were collected from the Ryukyu Islands (Okinawa, Amami-Oshima, Yonaguni, Ishigaki, and Iriomote Islands, belonging to same biogeographic region), of which 51 species were sampled in the Iriomote Island, and taken to the laboratory. A suite of eight traits were measured mainly on leaves and stems following the protocols of Cornelissen et al. (2003). These were leaf thickness (lm), leaf area (mm2), leaf dry matter content (mgmg1), specific leaf area (mm2mg1), leaf carbon and nitrogen concentration (%), wood density (gcm3), and maximum height (m). Leaf area and specific leaf area are strongly related to carbon assimilation (Shipley 2002). These traits are important for understanding growth dynamv www.esajournals.org

ics, nutrient cycling and regeneration after disturbance in the subtropical forests. Specific leaf area and wood density are associated with the decomposition rate of litter and coarse woody debris (Santiago 2007, Weedon et al. 2009). For example, thin leaves and low wood density promote faster growth; conversely, thick leaves and dense wood retain nutrients and are indicators of slow growth (Baraloto et al. 2010). Leaf projected area, including and excluding petioles (mm2) was measured with LIA32 software from digital scans prepared with a scanner (Lide-210, Canon Inc., Tokyo, Japan). The laminar area (area without the petiole) was defined as the ‘‘leaf area’’ and used as a functional trait. For P. luchuensis, leaf area was represented by the half circle area of a cross section of a needle. Leaf thickness (lm) was determined for each lamina 4

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Fig. 2. Photographs of the subtropical forest on the Ryukyu Islands in southern Japan. (a) Intact old-growth forest; (b) Secondary forest developed after clear-cutting; (c) abandoned P. luchuensis plantation; and (d) Clearcutting implemented over the watershed scale.

as the mean of three measurements using a digital micrometer (MDC-25PJ, Mitutoyo Corporation, Kanagawa, Japan). The leaves examined were subsequently oven-dried at 708C for at least 2 days and weighed with a microbalance (Mprove AY123, Sartorius Mechatronics Japan, Tokyo, Japan). Specific leaf area was calculated for each leaf as the ratio of leaf surface area to leaf dry mass (including the petiole). Subsequently, the weighed samples were ground and the carbon and nitrogen concentrations determined using a CHN analyzer (JM10, J-Science Lab, Osaka, Japan). In total, 6450 leaves were measured. Wood samples were polished with sand paper, and the bark was removed from stem samples before measuring wood traits. Fresh wood mass was determined. Wood volume was measured in a weighing bottle (40 3 40 mm) v www.esajournals.org

using the volume displacement method, after which samples were oven-dried for at least 72 h at 708C, then weighed. Wood density (gcm3) was determined as the ratio of wood dry mass to wood fresh volume. Information on the potential height (m) of each species was assembled from literature sources (Satake et al. 1982). Mean values of leaf and wood traits were calculated, and a species level dataset was compiled. Finally, the trait dataset of 102 species was extracted from trait database of 280 tree species on the Ryukyu Islands, and was merged with data on species composition in the plots on Iriomote Island.

Data analysis The differences in taxonomic composition among plots were graphically evaluated through 5

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detrended correspondence analysis (DCA). The significance of compositional differences among the forest types studied was determined by permuted analysis of variance (Oksanen et al. 2012). To explore the forest type preference of species, indicator species values were calculated (Dufrˆene and Legendre 1997). Significant associations with each of the forest types were tested using the probabilities of obtaining as great an indicator value as observed over 1000 iterations (P). Measures of taxonomic and functional diversity were calculated for each plot based on species relative abundance and functional trait data for each tree species. Taxonomic diversity was represented by species richness, Shannon’s diversity index, Simpson’s diversity index, and Fisher’s a. Functional diversity was expressed as functional richness, functional evenness, and functional divergence. Functional richness represents a multidimensional space (convex hull volume) occupied by a species assemblage (Cornwell et al. 2006), functional evenness represents the regularity of the partitioning distribution of functional space among component species (Ville´ger et al. 2008), and functional divergence represents divergence from the center of the functional trait space (Mouchet et al. 2010). Therefore, functional richness indicates the amount of niche space, and functional evenness and functional divergence indicate the pattern of niche differentiation among species in trait space. A community-weighted mean value was calculated for each of eight functional traits (Violle et al. 2007, Dı´az et al. 2007). This is the mean of trait values in a plot weighted by the relative abundances of species. These functional diversity indices, especially functional richness, depend on species richness (Mouchet et al. 2010). To account for these dependences, the observed values of the functional richness, functional evenness, and functional divergence were transformed to standardized effect sizes (SES) by using the null distributions of random communities. The null distributions were generated by randomization, keeping species richness per plot, frequency of species occurrence and the total abundance of species in the whole plots across the three forest types. First, the species occurrence (presence/ absence) matrix was randomized using quasiv www.esajournals.org

swap and trial swap algorithms to satisfy the requirements for independence and equidistribution of the matrices (Miklos and Podani 2004). Then, on the randomized matrix, species abundances were redistributed among the plots in which the species were present. The whole procedure was repeated 1000 times, leading to simulated datasets to compute the functional diversity indices. The SES for each plot was calculated as the observed value minus the mean of the null distribution divided by the standard deviation of the null distribution. The influences of forest types on taxonomic diversity, SES of functional diversity indices, and the community weighted mean of each trait were tested using generalized linear mixed models and generalized linear models, assuming species richness was Poisson distributed with log-link function, and the others were normally distributed with identity link function. In the analyses, community weighted means of leaf dry matter content, leaf carbon concentration, and leaf nitrogen concentration were angular-transformed. In the model, the three forest types were set as a categorical factor, in which intact oldgrowth forest was set as the reference level; therefore, the estimated parameter of intact forest corresponded to the intercept of the model. To remove the effects of inherent environmental or spatial factors, elevation and geographic location of the plots were also included as covariates. The effect of geographic locations was treated as random effects that alleviate the effect of spatial autocorrelation among plots, in which the plots were pooled into six areas (Fig. 1). To specify the best-performing model structure and test the significance of these factors, a two step analyses based on the log-likelihood ratio and Akaike’s information criterion (AIC) (Zuur et al. 2009) was adopted. First, the likelihood ratio test was conducted to determine the basic model structure: fixed-effect model incorporating forest types and elevation, or mixed-effect model incorporating the fixed effects and location groups (random effects). In this step, these two models were not significantly different to each other (except for community weighted mean of leaf thickness), but the fixed-effect models showed a relatively better fit in terms of AIC (Appendix: Table A1). Therefore, the fixed-effect model (generalized linear model) was chosen to 6

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MAESHIRO ET AL. Table 1. Number of stems, species, species showing a significant preference for each forest type (intact oldgrowth, secondary forest developed after clearcutting, and P. luchuensis plantation forest abandoned after planting).

Forest type

No. stems

No. species

No. species showing forest type preference

Intact Secondary Plantation

3500 7014 4842

82 77 74

10 19 15

different among the three forest types (Fig. 4 and Appendix: Table A3). Functional diversity indices were significantly different among intact forests and managed forests (Fig. 4 and Appendix: Table A3). Functional richness and functional evenness were significantly lower in secondary forests than in intact forests and P. luchuensis plantations. Functional divergence was significantly higher in secondary forests and P. luchuensis plantations than in intact forests. Community weighted means of functional traits for all component species were also significantly different among forest types (Fig. 5 and Appendix: Table A3). Leaf thickness, leaf dry matter content, and maximum height were all significantly higher in secondary and plantation forests, and specific leaf area and leaf nitrogen concentration was significantly lower in secondary and plantation forests than in intact forest.

Notes: Forest type preference was analyzed using an indicator species value (Dufrˆene and Legendre 1997). Significant associations with each of the forest types were tested using the probabilities of obtaining as great an indicator value as observed over 1000 iterations.

examine the influence of forest types and elevation on taxonomic and functional indices. Finally, model-selection was conducted based on AIC. Statistical significance of the effects of the covariates were evaluated by the Wald test (a ¼ 0.05). All analyses and graphics were performed in the R environment for statistical computing (R Development Core Team 2012) using the vegan (Oksanen et al. 2012), nlme (Pinheiro et al. 2013) and FD packages (Laliberte´ and Shipley 2011).

DISCUSSION Indices of species diversity, functional diversity, and functional composition were used as a tool of natural experiment for assessing the potential impacts of clear-cutting and plantation establishment on a subtropical island. The

RESULTS In total, 3500 stems belonging to 82 species were inventoried in intact forests, 7014 stems belonging to 77 species in secondary forests, and 4842 stems belonging to 74 species in abandoned plantation forests (Table 1). The DCA ordination plots based on species composition revealed a gradient in the pattern of species assembly associated with management practices (Fig. 3). Significant forest type preferences were found for 44 species: 19 positively associated with secondary forests, 15 with plantation forests, and 10 with intact forests (Table 1 and Appendix: Table A2). The effect of elevation on species diversity, functional diversity indices, and community weighted means for traits was generally not evident; i.e., elevation was not selected in the best model based on AIC, or the coefficient of elevation was statistically not significant (Appendix: Table A3). Species diversity indices were not significantly v www.esajournals.org

Fig. 3. Detrended correspondence analysis (DCA) ordination plot of species abundances in subtropical forests on Iriomote Island in the Ryukyu Islands. Filled triangles, filled circles, and plus signs indicate intact old-growth forest, secondary forest developed after clear-cutting, and abandoned P. luchuensis plantation, respectively.

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Fig. 4. Estimated values (points) and standard error (bars) of taxonomic diversity and the standardized effect sizes (SES) of functional diversity among intact old-growth forest (IF), secondary forest (SF), and abandoned P. luchuensis plantation (PF), derived from generalized linear models including forest types as a categorical factor. IF was set as the reference level; the estimated parameter of intact forest corresponded to the intercept of the model. For SF and PF, significant differences from IF were tested by the Wald test and represented by * P , 0.05; ** P , 0.01; *** P , 0.001.

forest types with different management histories, rather than environmental conditions such as elevation and geographic locations of each plot. The hypothesis was supported, and this suggests that management practices affected functional

patterns of functional diversity among the forests studied contrasted with those of species diversity. Differences in functional diversity and community weighted means of functional traits between the studied plots were better explained by the v www.esajournals.org

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Fig. 5. Estimated values (points) and standard errors (bars) of community weighted means for each functional trait in intact old-growth forest (IF), secondary forest (SF), and abandoned P. luchuensis plantation (PF), derived generalized linear model including forest types as a categorical factor. IF was set as the reference level; the estimated parameter of intact forest corresponded to the intercept of the model. For SF and PF, significant differences from IF were tested by the Wald test and represented by * P , 0.05; ** P , 0.01; *** P , 0.001.

diversity and some functional composition, mediated through the shift of co-occurrence patterns among component species during forest regeneration. The differences in functional diversity measures and functional composition provide insight v www.esajournals.org

into the ways in which anthropogenic management disturbances impact community assembly and ecosystem functioning, respectively. Niche space and niche differentiation that shape community assemblies are controlled by ecological processes including dispersal limitation and 9

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environmental filtering associated with species traits (Keddy 1992, Jabot et al. 2008, Mouchet et al. 2010). The lower functional richness suggests that environmental changes following clearcutting or plantation establishment resulted in constraints (e.g., limited dispersal and postdispersal environmental filtering) on the regeneration of some species with specific traits (Katovai et al. 2012). The contraction of functional evenness in secondary forests indicates greater functional dominance of species having typical traits of slow growth. The high functional divergence in the managed forests indicates that species abundance distribution tends to weight on the outer margins of functional space (Ville´ger et al. 2008). These results suggest species replacement associated with functional traits; functional niche space in the subtropical forests was potentially more evenly filled by a range of species in intact forests, but the pattern of niche differentiation may be modified by silvicultural activities. Predicting the connection between functional traits and relevant ecosystem functioning is challenging (Hillebrand and Matthiessen 2009). To overcome this difficulty, Suding et al. (2008) proposed a trait-based response-and-effect framework, allowing for experimental tests of logging and silvicultural impacts on community performance (Carre˜no-Rocabado et al. 2012). Nevertheless, a natural experiment approach that does not require long-term experiments is still a conventional way to infer anthropogenic impacts (Baraloto et al. 2012, Katovai et al. 2012). The differences in the community weighted mean for a functional trait between forest types with different management histories is informative for considering the shifts of the dominant trait value in a community (Baraloto et al. 2012). Greater leaf thickness and wood density found in managed forests suggest that clear-cutting and plantation establishment may have affected growth dynamics in the forests (Fujii et al. 2009). Forest practices often promote the dominance of pioneer species with low wood density and high specific leaf area and leaf nitrogen concentration (Baraloto et al. 2012, Carren˜ oRocabado et al. 2012), but the subtropical forest demonstrated a converse trend. Indeed, most of the tree species that had a significant preference with secondary forests or plantation forests are v www.esajournals.org

small leaved drought/wind tolerant species with a slow growth rate (Kubota et al. 2004), which suggests drought stress in the managed forests. Such particular traits of locally abundant species that can regenerate after practices may slow some key biogeochemical processes such as carbon cycling from leaf litter and woody debris in the forest ecosystem (Xu and Hirata 2002, Carre˜no-Rocabado et al. 2012). Ecologically based timber harvesting that includes retention forestry, reduced impact logging, and natural disturbance-based management attempts to achieve compatibility among timber production, biodiversity and ecosystem function (Perera et al. 2004, Drever et al. 2006, Rosenvald and L˜ohmus 2008). The development of tractable indicators that evaluate associated impacts (i.e., the extent to which ecosystem properties of managed forests depart from those of natural forests) will be an essential first step toward implementation of these new or alternative forestry procedures. On the basis of assuming causal relationships between biodiversity, habitat heterogeneity, and ecosystem function, taxonomic species diversities in woodlands have often have been used to assess logging impacts. Several studies found no differences in species diversity between unlogged and logged forests (Verburg and van Eijk-Bos 2003, Kariuki et al. 2006, Berry et al. 2008), thereby arguing for compatibility between forest management practices and biodiversity conservation. However, the contrasting patterns of species diversity and functional diversity in the subtropical forest of this study suggest that the compatibility may not be evaluated appropriately by taxonomic diversity measures alone. The departure of functional diversity and functional composition in managed forests compared with those in intact forests was clear, and suggest that the present management practices may be incompatible with the conservation of ecosystem properties. This viewpoint is largely consistent with research in tropical forests of Guyana (Baraloto et al. 2012). Namely, there were no differences in functional richness or functional divergence among selectively logged and unlogged forests of Guyana, but unlogged forests had much lower functional evenness values. A slight difference in the performances of functional diversity indices between studies may reflect a difference in 10

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logging practices and a difference in functional redundancy between the two forest types (subtropical vs. tropical). In the Ryukyu subtropical forest, clear-cutting and establishment of P. luchuensis plantations have been implemented at the watershed scale (2–30 ha harvesting grain) (Fig. 2d). These induce soil erosion (Itˆo 1995), and have led to substantial changes in soil nutrients/ properties (Xu et al. 2001, Xu and Hirata 2002, Kubota et al. 2005). Such strong anthropogenic disturbances seem likely to be responsible for the patterns in functional diversity and functional composition observed in this study, even though species diversity was maintained. Importantly, species richness in the Ryukyu subtropical forest was lower (102 species) than in the Guyanese tropical forest (473 species) as found by Baraloto et al. (2012). This suggests low functional redundancy due to the small species pool (Naeem 1998), and the potential for functional impacts by large-scale management practices.

ACKNOWLEDGMENTS We thank K. Yasuda and T. Oosako for help with the fieldwork and Timo Kuuluvainen for suggestions to improve the manuscript. We sincerely acknowledge Charles Kwit and anonymous referees for constructive and insightful comments. This study was partly supported by grants from the Foundations of the World Wildlife Fund 2002-2003 and Nature Conservation Society of Japan in 2004. The study is a contribution to the Iriomote Project of the Research Institute for Humanity and Nature. Financial support was also provided by the Japan Society for the Promotion of Science (grant nos. 21310025, 21247006, and 24651037).

LITERATURE CITED Balvanera, P., A. B. Pfisterer, N. Buchmann, J. S. He, T. Nakashizuka, D. Raffaelli, and B. Schmid. 2006. Quantifying the evidence for biodiversity effects on ecosystem functioning and services. Ecology Letters 9:1146–1156. Baraloto, C., C. E. T. Paine, L. Poorter, J. Beauchene, D. Bonal, A. M. Domenach, B. He´rault, S. Pati˜no, J. C. Roggy, and J. Chave. 2010. Decoupled leaf and stem economics in rain forest trees. Ecology Letters 13:1338–1347. Baraloto, C., B. He´rault, C. E. T. Paine, H. Massot, L. Blanc, D. Bonal, J.-F. Molino, E. A. Nicolini, and D. Sabatier. 2012. Contrasting taxonomic and functional responses of a tropical tree community to selective logging. Journal of Applied Ecology 49:861–870. Berry, N. J., O. L. Phillips, R. C. Ong, and K. C. Hamer. 2008. Impacts of selective logging on tree diversity across a rainforest landscape: the importance of spatial scale. Landscape Ecology 23:915–929. Biswas, S. R., and A. U. Mallik. 2010. Disturbance effects on species diversity and functional diversity in riparian and upland plant communities. Ecology 91:28–35. Biswas, S. R., and A. U. Mallik. 2011. Species diversity and functional diversity relationship varies with disturbance intensity. Ecosphere 2:art52. Bremer, L. L., and K. A. Farley. 2010. Does plantation forestry restore biodiversity or create green deserts? A synthesis of the effects of land-use transitions on plant species richness. Biodiversity and Conservation 19:3893–3915. Butchart, S. H. M., et al. 2010. Global biodiversity: indicators of recent declines. Science 328:1164– 1168. Carre˜no-Rocabado, G., M. Pe˜na-Claros, F. Bongers, A. Alarco´n, J.-C. Licona, and L. Poorter. 2012. Effects of disturbance intensity on species and functional

CONCLUSIONS This study in a subtropical forest demonstrated the usefulness and importance of functional traits and functional diversity for assessing impacts of forest management practices on woodland ecosystems. Forest management in this region has traditionally been directed toward increasing timber production and short-term profitability. The departure of functional diversity and functional composition from unmanaged forests is a trait-based tractable indicator for assessing the functional impacts of land-use change. This may be effective to devise sustainable management practices that would minimize detrimental effects on the preservation of the subtropical forest on the Ryukyu Islands. To better understand the multifunctional roles of forests, patterns of functional diversity and functional traits should be further studied across different systems such as temperate and boreal forests with low species richness. Evaluating functional shifts among tree species as affected by management practices will contribute to the development of restoration goals for degraded forests and alternative forest management schemes that are compatible with the retention of ecosystem properties, such as biodiversity. v www.esajournals.org

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MAESHIRO ET AL. diversity in a tropical forest. Journal of Ecology 100:1453–1463. Chave, J., D. Coomes, S. Jansen, S. L. Lewis, N. G. Swenson, and A. E. Zanne. 2009. Towards a worldwide wood economics spectrum. Ecology Letters 12:351–366. Cornelissen, J. H. C., et al. 2003. A handbook of protocols for standardised and easy measurement of plant functional traits worldwide. Australian Journal of Botany 51:335–380. Cornwell, W. K., D. W. Schwilk, and D. D. Ackerly. 2006. A trait-based test for habitat filtering: convex hull volume. Ecology 87:1465–1471. Dı´az, S., S. Lavorel, F. de Bello, F. Que´tier, K. Grigulis, and T. M. Robson. 2007. Incorporating plant functional diversity effects in ecosystem service assessments. Proceedings of the National Academy of Sciences USA 104:20684–20689. Drever, C. R., G. Peterson, C. Messier, Y. Bergeron, and M. Flannigan. 2006. Can forest management based on natural disturbances maintain ecological resilience? Canadian Journal of Forest Research 36:2285–2299. Dufrˆene, M., and P. Legendre. 1997. Species assemblages and indicator species: The need for a flexible asymmetrical approach. Ecological Monographs 67:345–366. Emmer, I. M., J. Fanta, A. T. Kobus, A. Kooijman, and J. Sevink. 1998. Reversing borealization as a means to restore biodiversity in Central-European mountain forests—an example from the Krkonoˇse Mountains, Czech Republic. Biodiversity and Conservation 7:229–247. Flynn, D. F. B., M. Gogol-Prokurat, T. Nogeire, N. Molinari, B. T. Richers, B. B. Lin, N. Simpson, M. M. Mayfield, and F. DeClerck. 2009. Loss of functional diversity under land use intensification across multiple taxa. Ecology Letters 12:22–33. Fujii, S., Y. Kubota, and T. Enoki. 2009. Resilience of stand structure and tree species diversity in subtropical forest degraded by clear logging. Journal of Forest Research 14:373–387. Gustafsson, L., et al. 2012. Retention forestry to maintain multifunctional forests: a world perspective. BioScience 62:633–645. He´rault, B., O. Honnay, and D. Thoen. 2005. Evaluation of the ecological restoration potential of plant communities in Norway spruce plantations using a life-trait based approach. Journal of Applied Ecology 42:536–545. He´rault, B., B. Bachelot, L. Poorter, V. Rossi, F. Bongers, J. Chave, C. E. T. Paine, F. Wagner, and C. Baraloto. 2011. Functional traits shape ontogenetic growth trajectories of rain forest tree species. Journal of Ecology 99:1431–1440. Hillebrand, H., and B. Matthiessen. 2009. Biodiversity in a complex world: consolidation and progress in

v www.esajournals.org

functional biodiversity research. Ecology Letters 12:1405–1419. Itˆo, Y. 1995. Forests of Yanbaru, Okinawa: why could we not conserve its nature of outstanding universal value? Iwanami Shoten, Tokyo, Japan. Jabot, F., R. S. Etienne, and J. Chave. 2008. Reconciling neutral community models and environmental filtering: theory and an empirical test. Oikos 117:1308–1320. Kanowski, J., C. P. Catterall, and G. W. WardellJohnson. 2005. Consequences of broadscale timber plantations for biodiversity in cleared rainforest landscapes of tropical and subtropical Australia. Forest Ecology and Management 208:359–372. Kariuki, M., R. M. Kooyman, R. G. B. Smith, G. Wardell-Johnson, and J. K. Vanclay. 2006. Regeneration changes in tree species abundance, diversity and structure in logged and unlogged subtropical rainforest over a 36-year period. Forest Ecology and Management 236:162–176. Katovai, E., A. L. Burley, and M. M. Mayfield. 2012. Understory plant species and functional diversity in the degraded wet tropical forests of Kolombangara Island, Solomon Islands. Biological Conservation 145:214–224. Keddy, P. A. 1992. Assembly and response rules: two goals for predictive community ecology. Journal of Vegetation Science 3:157–164. Kobayashi, T. 1961. Studies on the soils of Iriomote Island, Yaeyama, Ryukyus. Bulletin of the Faculty of Agriculture, Kagoshima University 10:108–168. Kubota, Y., K. Katsuda, and K. Kikuzawa. 2005. Secondary succession and effects of clear-logging on diversity in the subtropical forests on Okinawa Island, southern Japan. Biodiversity and Conservation 14:879–901. Kubota, Y., H. Murata, and K. Kikuzawa. 2004. Effects of topographic heterogeneity on tree species richness and stand dynamics in a subtropical forest in Okinawa Island, southern Japan. Journal of Ecology 92:230–240. Laliberte´, E., and B. Shipley. 2011. FD: measuring functional diversity from multiple traits, and other tools for functional ecology. R package version 1.01.1. http://cran.r-project.org/web/packages/FD/FD. pdf Lindenmayer, D. B., J. F. Franklin, and J. Fischer. 2006. General management principles and a checklist of strategies to guide forest biodiversity conservation. Biological Conservation 131:433–445. Mason, N. W. H., D. Mouillot, W. G. Lee, and J. B. Wilson. 2005. Functional richness, functional evenness and functional divergence: the primary components of functional diversity. Oikos 111:112–118. Mason, N. W. H., S. J. Richardson, D. A. Peltzer, F. de Bello, D. A. Wardle, and R. B. Allen. 2012. Changes

12

June 2013 v Volume 4(6) v Article 70

MAESHIRO ET AL. in coexistence mechanisms along a long-term soil chronosequence revealed by functional trait diversity. Journal of Ecology 100:678–689. Mayfield, M. M., S. P. Bonser, J. W. Morgan, I. Aubin, S. McNamara, and P. A. Vesk. 2010. What does species richness tell us about functional trait diversity? Predictions and evidence for responses of species and functional trait diversity to land-use change. Global Ecology and Biogeography 19:423– 431. McGill, B. J., B. J. Enquist, E. Weiher, and M. Westoby. 2006. Rebuilding community ecology from functional traits. Trends in Ecology and Evolution 21:178–185. Miklos, I., and J. Podani. 2004. Randomization of presence–absence matrices: comments and new algorithms. Ecology 85:86–92. Mittermeier, R. A., P. R. Gil, M. Hoffman, J. Pilgrim, T. Brooks, C. G. Mittermeier, J. Lamoreux, and G. A. B. Da Fonseca. 2005. Hotspots revisited: Earth’s biologically richest and most endangered terrestrial ecoregions. Conservation International, Washington, D.C., USA. Mouchet, M., F. Guilhaumon, S. Ville´ger, N. W. H. Mason, J. A. Tomasini, and D. Mouillot. 2008. Towards a consensus for calculating dendrogrambased functional diversity indices. Oikos 117:794– 800. Mouchet, M. A., S. Ville´ger, N. W. H. Mason, and D. Mouillot. 2010. Functional diversity measures: an overview of their redundancy and their ability to discriminate community assembly rules. Functional Ecology 24:867–876. Naeem, S. 1998. Species redundancy and ecosystem reliability. Conservation Biology 12:39–45. Naeem, S., and J. P. Wright. 2003. Disentangling biodiversity effects on ecosystem functioning: deriving solutions to a seemingly insurmountable problem. Ecology Letters 6:567–579. Nakagawa, H., N. Doi, M. Shirao, and Y. Araki. 1982. Geology of Ishigaki-jima and Iriomote-jima Yaeyama Gunto, Ryukyu Islands. Contributions from the Institute of Geology and Paleontology Tohoku University 84:1–22. Oksanen, J., F. G. Blanchet, R. Kindt, P. Legendre, P. R. Minchin, R. B. O’Hara, G. L. Simpson, P. Solymos, M. H. H. Stevens, and H. Wagner. 2012. vegan: Community ecology package: R package version 2.1-13/r2115. http://CRAN.R-project.org/ package¼vegan Paine, C. E. T., C. Baraloto, J. Chave, and B. He´rault. 2011. Functional traits of individual trees reveal ecological constraints on community assembly in tropical rain forests. Oikos 120:720–727. Pakeman, R. J. 2011. Functional diversity indices reveal the impacts of land use intensification on plant community assembly. Journal of Ecology 99:1143–

v www.esajournals.org

1151. Perera, A. H., L. J. Buse, and M. G. Weber. 2004. Emulating natural forest landscape disturbances: Concepts and applications. Columbia University Press, New York, New York, USA. Petchey, O. L., and K. J. Gaston. 2006. Functional diversity: back to basics and looking forward. Ecology Letters 9:741–758. Pinheiro, J., D. Bates, S. DebRoy, and D. Sarkar. 2013. nlme: linear and nonlinear mixed effects models. R Package version 3.1-96. http://cran.r-roject.org/ web/packages/nlme/index.html R Development Core Team. 2012. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.r-project.org/ Rosenvald, R., and A. L˜ohmus. 2008. For what, when, and where is green-tree retention better than clearcutting? A review of the biodiversity aspects. Forest Ecology and Management 255:1–15. Santiago, L. S. 2007. Extending the leaf economic spectrum to decomposition: evidence from a tropical forest. Ecology 88:1126–1131. Satake, Y., G. Oi, S. Kitamura, T. Kanri, and T. Tominari. 1982. Wild flowers of Japan. Heibonsya, Tokyo, Japan. Shinohara, T. 1977. Studies on the administration and management of the Okinawa National Forest after the Second World War. The Science Bulletin of the College of Agriculture, University of the Ryukyus 24:567–581. Shipley, B. 2002. Trade-offs between net assimilation rate and specific leaf area in determining relative growth rate: relationship with daily irradiance. Functional Ecology 16:682–689. Suding, K. N., S. Lavorel, F. S. Chapin, J. H. C. Cornelissen, S. Dı´az, E. Garnier, D. Goldberg, D. U. Hooper, S. T. Jackson, and M.-L. Navas. 2008. Scaling environmental change through the community-level: a trait-based response-and-effect framework for plants. Global Change Biology 14:1125–1140. Verburg, R., and C. van Eijk-Bos. 2003. Effects of selective logging on tree species diversity, composition and plant functional type patterns in a Bornean rain forest. Journal of Vegetation Science 14:99–110. Ville´ger, S., N. W. H. Mason, and D. Mouillot. 2008. New multidimensional functional diversity indices for a multifaceted framework in functional ecology. Ecology 89:2290–2301. Violle, C., M. L. Navas, D. Vile, E. Kazakou, C. Fortunel, I. Hummel, and E. Garnier. 2007. Let the concept of trait be functional! Oikos 116:882–892. Weedon, J. T., W. K. Cornwell, J. H. C. Cornelissen, A. E. Zanne, C. Wirth, and D. A. Coomes. 2009. Global meta-analysis of wood decomposition rates:

13

June 2013 v Volume 4(6) v Article 70

MAESHIRO ET AL. a role for trait variation among tree species. Ecology Letters 12:45–56. Westoby, M., D. S. Falster, A. T. Moles, P. A. Vesk, and I. J. Wright. 2002. Plant ecological strategies: some leading dimensions of variation between species. Annual Review of Ecology and Systematics 33:152– 159. Wright, I. J., et al. 2004. The worldwide leaf economics spectrum. Nature 428:821–827. Xu, X. N., and E. Hirata. 2002. Forest floor mass and litterfall in Pinus luchuensis plantations with and

without broad-leaved trees. Forest Ecology and Management 157:165–173. Xu, X. N., E. Hirata, Y. Tokashiki, T. Enoki, and T. Shinohara. 2001. Differences of soil properties between evergreen broad-leaved and pine forests in northern Okinawa Island, Japan. Japanese Journal of Forest Environment 43:1–8. Zuur, A. F., E. N. Ieno, N. J. Walker, A. A. Saveliev, and G. M. Smith. 2009. Mixed effects models and extensions in ecology with R. Springer Science þ Business Media, New York, New York, USA.

SUPPLEMENTAL MATERIAL APPENDIX Table A1. Akaike information criteria (AIC) and results of log-likelihood ratio test between fixed- and mixedeffect models for explaining each response variable. Both models include a category variable of forest types (intact old-growth forest, secondary forest, and abandoned P. luchuensis plantation) and elevation as a fixed explanatory variable. Mixed-effect models include geological locations (six areas) as a random effect. Fixed-effect model

Mixed-effect model

Response variable

df

AIC

Log-L

df

AIC

Log-L

L-ratio

P

Species richness Simpson’s diversity index Shannon’s diversity index Fisher’s a Functional richness Functional evenness Functional divergence Leaf thickness Leaf area Specific leaf area Leaf dry matter content Leaf carbon concentration Leaf nitrogen concentration Wood density Maximum height

5 5 5 5 5 5 5 5 5 5 5 5 5 5 5

269 228 19 176 136 136 123 120 114 647 351 153 139 137 255

129.3 108.8 4.5 83.0 62.9 63.0 56.6 170.5 318.5 71.8 73.7 132.3 146.0 74.6 65.5

6 6 6 6 6 6 6 6 6 6 6 6 6 6 6

270 230 21 178 136 137 125 120 114 648 347 155 138 137 255

129.0 108.8 4.5 83.1 62.2 62.3 56.6 167.4 318.1 71.7 74.4 133.3 146.3 75.1 65.3

0.80 0.00 0.00 0.00 1.41 1.47 0.00 6.15 0.81 0.05 1.42 1.86 0.64 1.09 0.35

0.37 1.00 1.00 1.00 0.23 0.22 1.00 0.01 0.37 0.82 0.23 0.17 0.42 0.30 0.55

Note: Abbreviations are: Log-L, log likelihood; L-ratio, Likelihood ratio.

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MAESHIRO ET AL. Table A2. Tree species composition for the three forest types: old-growth forest (IF), secondary forest (SF), and abandoned P. luchuensis plantation (PF). The number of observed stems for each species and the indicator species value (Dufrˆene and Legendre 1997) are shown. Significant associations with each of the forest types were tested using the probabilities of obtaining as great an indicator value as observed over 1000 iterations (P). Species

IF

SF

PF

Preferred type

Indicator value

P

Actinodaphne acuminata Aidia canthioides Antidesma japonicum Archidendron lucidum Ardisia quinquegona Ardisia sieboldii Bridelia insulata Callicarpa japonica Callicarpa oshimensis Camellia japonica Camellia lutchuensis Camellia sasanqua Castanopsis sieboldii Celtis boninensis Cinnamomum doederleinii Cinnamomum tenuifolium Cleyera japonica Daphniphyllum teijsmannii Dendropanax trifidus Diospyros egbert-walkeri Diospyros maritima Diospyros oldhamii Diplospora dubia Distylium racemosum Elaeocarpus japonicus Elaeocarpus zollingeri Euonymus carnosus Euonymus lutchuensis Eurya emarginata Eurya osimensis Eurya sakishimensis Ficus ampelas Ficus benguetensis Ficus erecta Ficus microcarpa Ficus superba Ficus variegata Ficus virgata Fraxinus griffithii Garcinia subelliptica Gardenia jasminoides Glochidion rubrum Glochidion zeylanicum Helicia cochinchinensis Hydrangea chinensis Idesia polycarpa Ilex goshiensis Ilex integra Ilex liukiuensis Ilex maximowicziana Ilex rotunda Ilex warburgii Itea oldhamii Lasianthus hirsutus Ligustrum japonicum Macaranga tanarius Machilus japonica Machilus thunbergii Magnolia compressa Mallotus japonicus Mallotus paniculatus Melanolepis multiglandulosa Melicope triphylla Meliosma arnottiana

7 150 99 53 514 319 22 8 3 0 54 0 290 1 5 0 0 8 15 11 10 0 49 84 26 33 0 81 0 3 3 3 25 37 1 2 1 17 0 3 7 15 22 3 44 0 37 0 57 7 1 26 1 1 1 0 96 74 14 16 5 2 0 4

4 574 0 32 0 399 35 0 30 56 19 10 814 0 114 2 8 35 29 94 56 0 270 228 178 72 1 65 0 3 3 0 1 36 0 1 0 1 4 7 34 9 19 0 0 0 217 1 258 30 20 17 11 0 0 3 1 186 10 0 4 0 1 18

0 110 0 62 0 104 84 0 20 2 1 0 145 0 15 0 0 79 2 18 46 1 30 21 40 38 5 4 43 3 15 2 55 120 2 0 7 12 56 0 191 70 39 0 0 1 44 0 116 117 20 1 85 0 0 1 9 319 0 0 3 5 47 76

IF SF IF IF IF IF PF IF SF SF IF SF SF IF SF SF SF PF SF SF SF PF SF SF SF SF PF IF PF IF PF IF PF PF PF IF PF IF PF SF PF PF PF IF IF PF SF SF SF PF PF IF PF IF IF SF IF PF IF IF IF PF PF PF

0.19 0.65 0.91 0.40 1.00 0.46 0.53 0.27 0.33 0.58 0.57 0.20 0.60 0.09 0.62 0.13 0.20 0.51 0.30 0.59 0.29 0.07 0.74 0.50 0.70 0.43 0.17 0.50 0.53 0.11 0.23 0.12 0.33 0.54 0.08 0.07 0.22 0.17 0.68 0.13 0.65 0.38 0.27 0.18 0.64 0.07 0.65 0.07 0.57 0.70 0.29 0.30 0.58 0.09 0.09 0.05 0.68 0.53 0.12 0.45 0.09 0.09 0.59 0.61

0.08 0.00 0.00 0.12 0.00 0.09 0.01 0.02 0.11 0.00 0.00 0.10 0.00 0.27 0.00 0.32 0.12 0.03 0.17 0.00 0.41 1.00 0.00 0.01 0.00 0.09 0.18 0.02 0.00 0.43 0.11 0.39 0.10 0.01 0.76 0.49 0.09 0.30 0.00 0.47 0.01 0.40 0.68 0.08 0.00 1.00 0.00 1.00 0.00 0.00 0.16 0.15 0.00 0.25 0.26 0.83 0.00 0.00 0.41 0.00 0.95 0.61 0.00 0.01

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MAESHIRO ET AL. Table A2. Continued. Species

IF

SF

PF

Preferred type

Indicator value

P

Microtropis japonica Morella rubra Morus australis Myrsine seguinii Nageia nagi Neolitsea aciculata Neolitsea sericea Osmanthus insularis Osmanthus marginatus Pinus luchuensis Planchonella obovata Podocarpus macrophyllus Psychotria rubra Putranjiva matsumurae Pyrenaria virgata Quercus miyagii Rhaphiolepis indica Rhododendron latoucheae Sarcandra glabra Saurauia tristyla Schefflera heptaphylla Styrax japonica Symplocos cochinchinensis Symplocos glauca Symplocos liukiuensis Symplocos nakaharae Symplocos prunifolia Syzygium buxifolium Syzygium jambos Tarenna gracilipes Ternstroemia gymnanthera Tetradium glabrifolium Toxicodendron succedaneum Trema orientalis Turpinia ternata Vaccinium wrightii Wendlandia formosana Zanthoxylum ailanthoides

23 10 0 44 0 18 20 3 45 0 0 7 360 5 15 122 22 63 1 5 75 84 20 9 0 0 3 71 0 10 2 1 23 2 15 0 48 4

76 15 0 175 1 31 4 0 365 0 97 17 564 2 165 124 171 18 0 0 27 136 53 20 8 8 63 639 74 0 72 0 45 0 1 9 14 0

17 61 1 4 0 7 0 0 83 339 47 1 342 0 13 7 354 1 0 0 81 280 97 3 0 0 18 303 139 0 17 7 65 0 83 39 147 0

SF PF PF SF SF SF IF IF SF PF SF SF SF IF SF IF PF IF IF IF IF PF PF SF SF SF SF SF PF IF SF PF PF IF PF PF PF IF

0.49 0.27 0.07 0.63 0.07 0.23 0.16 0.09 0.72 1.00 0.54 0.33 0.38 0.21 0.50 0.51 0.64 0.37 0.09 0.18 0.49 0.46 0.44 0.30 0.13 0.20 0.39 0.62 0.17 0.18 0.63 0.11 0.43 0.09 0.48 0.33 0.35 0.09

0.03 0.33 1.00 0.00 1.00 0.46 0.33 0.27 0.00 0.00 0.00 0.05 0.64 0.10 0.01 0.02 0.00 0.01 0.27 0.06 0.07 0.17 0.12 0.11 0.35 0.09 0.04 0.00 0.22 0.08 0.00 0.40 0.07 0.26 0.01 0.05 0.19 0.25

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MAESHIRO ET AL. Table A3. Estimated parameters in the best fit models for explaining taxonomic diversity, the standardized effect sizes (SES) of functional diversity, and community weighted means of each trait. The best-fit models were selected using Akaike’s information criteria (AIC) in generalized linear models (GLMs). Leaf dry matter content, and carbon and nitrogen concentration were angular-transformed. Poisson distribution was used for analyzing species richness and normal distribution for the others. Full-models include elevation as a covariate and three forest types as a categorical factor: old-growth forest (IF), secondary forest (SF), and abandoned P. luchuensis plantation (PF). IF was set as the reference level; the estimated parameter of intact forest corresponded to the intercept of the model. The parameters for SF and PF indicate differences from IF. Figures in parentheses indicate standard error. Statistical significance of the parameters was evaluated by the Wald test and represented by *** P , 0.001; ** P , 0.01;* P , 0.05. Response variable

IF

SF

PF

Species richness Simpson’s diversity index Shannon’s diversity index Fisher’s a SES of functional richness SES of functional evenness SES of functional divergence Leaf thickness Leaf area Specific leaf area Leaf dry matter content Leaf carbon concentration Leaf nitrogen concentration Wood density Maximum height

3.593 (0.026) 13.072 (0.544) 2.933 (0.033) 10.177 (0.268) 0.365 (0.303) 0.092 (0.311) 1.215 (0.256) 255.530 (7.367) 3652.068 (402.997) 13.699 (0.392) 0.915 (0.008) 0.756 (0.002) 0.129 (0.001) 0.558 (0.007) 6.927 (0.326)

0.970** (0.399) 0.892** (0.410) 1.305*** (0.337) 30.193** (9.906) 702.789 (541.892) 2.994*** (0.517) 0.047*** (0.010) 0.007** (0.002) 0.008*** (0.001) 0.055*** (0.010) 1.466** (0.429)

0.201 (0.399) 0.153 (0.410) 1.585*** (0.337) 41.034*** (9.803) 514.478 (536.281) 2.260*** (0.517) 0.027** (0.010) 0.002 (0.002) 0.004** (0.001) 0.017 (0.010) 1.231** (0.429)

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Elevation

0.549 (0.272)

17

6.328 (4.148) 314.472 (226.936)

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