Masahiro Aiba

Plant functional traits have globally consistent effects on competition

Phenotypic traits and their associated trade-offs have been shown to have globally consistent effects on individual plant physiological functions, but how these effects scale up to influence competition, a key driver of community assembly in terrestrial vegetation, has remained unclear. Here we use growth data from more than 3 million trees in over 140,000 plots across the world to show how three key functional traits—wood density, specific leaf area and maximum height—consistently influence competitive interactions. Fast maximum growth of a species was correlated negatively with its wood density in all biomes, and positively with its specific leaf area in most biomes. Low wood density was also correlated with a low ability to tolerate competition and a low competitive effect on neighbours, while high specific leaf area was correlated with a low competitive effect. Thus, traits generate trade-offs between performance with competition versus performance without competition, a fundamental ingredient in the classical hypothesis that the coexistence of plant species is enabled via differentiation in their successional strategies. Competition within species was stronger than between species, but an increase in trait dissimilarity between species had little influence in weakening competition. No benefit of dissimilarity was detected for specific leaf area or wood density, and only a weak benefit for maximum height. Our trait-based approach to modelling competition makes generalization possible across the forest ecosystems of the world and their highly diverse species composition.

BAAD: a biomass and allometry database for woody plants

Understanding how plants are constructed—i.e., how key size dimensions and the amount of mass invested in different tissues varies among individuals—is essential for modeling plant growth, carbon stocks, and energy fluxes in the terrestrial biosphere. Allocation patterns can differ through ontogeny, but also among coexisting species and among species adapted to different environments. While a variety of models dealing with biomass allocation exist, we lack a synthetic understanding of the underlying processes. This is partly due to the lack of suitable data sets for validating and parameterizing models. To that end, we present the Biomass And Allometry Database (BAAD) for woody plants. The BAAD contains 259 634 measurements collected in 176 different studies, from 21 084 individuals across 678 species. Most of these data come from existing publications. However, raw data were rarely made public at the time of publication. Thus, the BAAD contains data from different studies, transformed into standard units and variable names. The transformations were achieved using a common workflow for all raw data files. Other features that distinguish the BAAD are: (i) measurements were for individual plants rather than stand averages; (ii) individuals spanning a range of sizes were measured; (iii) plants from 0.01–100 m in height were included; and (iv) biomass was estimated directly, i.e., not indirectly via allometric equations (except in very large trees where biomass was estimated from detailed sub-sampling). We included both wild and artificially grown plants. The data set contains the following size metrics: total leaf area; area of stem cross-section including sapwood, heartwood, and bark; height of plant and crown base, crown area, and surface area; and the dry mass of leaf, stem, branches, sapwood, heartwood, bark, coarse roots, and fine root tissues. We also report other properties of individuals (age, leaf size, leaf mass per area, wood density, nitrogen content of leaves and wood), as well as information about the growing environment (location, light, experimental treatment, vegetation type) where available. It is our hope that making these data available will improve our ability to understand plant growth, ecosystem dynamics, and carbon cycling in the worlds vegetation.

Robustness of trait distribution metrics for community assembly studies under the uncertainties of assembly processes

Numerous studies have revealed the existence of nonrandom trait distribution patterns as a sign of environmental filtering and/or biotic interactions in a community assembly process. A number of metrics with various algorithms have been used to detect these patterns without any clear guidelines. Although some studies have compared their statistical powers, the differences in performance among the metrics under the conditions close to actual studies are not clear. Therefore, the performances of five metrics of convergence and 16 metrics of divergence under alternative conditions were comparatively analyzed using a suite of simulated communities. We focused particularly on the robustness of the performances to conditions that are often uncertain and uncontrollable in actual studies; e.g., atypical trait distribution patterns stemming from the operation of multiple assembly mechanisms, a scaling of trait-function relationships, and a sufficiency of analyzed traits. Most tested metrics, for either convergence or divergence, had sufficient statistical power to distinguish nonrandom trait distribution patterns without uncertainty. However, the performances of the metrics were considerably influenced by both atypical trait distribution patterns and other uncertainties. Influences from these uncertainties varied among the metrics of different algorithms and their performances were often complementary. Therefore, under the uncertainties of an assembly process, the selection of appropriate metrics and the combined use of complementary metrics are critically important to reliably distinguish nonrandom patterns in a trait distribution. We provide a tentative list of recommended metrics for future studies.

Efficacy of generic allometric equations for estimating biomass: a test in Japanese natural forests

Accurate estimation of tree and forest biomass is key to evaluating forest ecosystem functions and the global carbon cycle. Allometric equations that estimate tree biomass from a set of predictors, such as stem diameter and tree height, are commonly used. Most allometric equations are site specific, usually developed from a small number of trees harvested in a small area, and are either species specific or ignore interspecific differences in allometry. Due to lack of site-specific allometries, local equations are often applied to sites for which they were not originally developed (foreign sites), sometimes leading to large errors in biomass estimates. In this study, we developed generic allometric equations for aboveground biomass and component (stem, branch, leaf, and root) biomass using large, compiled data sets of 1203 harvested trees belonging to 102 species (60 deciduous angiosperm, 32 evergreen angiosperm, and 10 evergreen gymnosperm species) from 70 boreal, temperate, and subtropical natural forests in Japan. The best generic equations provided better biomass estimates than did local equations that were applied to foreign sites. The best generic equations included explanatory variables that represent interspecific differences in allometry in addition to stem diameter, reducing error by 4-12% compared to the generic equations that did not include the interspecific difference. Different explanatory variables were selected for different components. For aboveground and stem biomass, the best generic equations had species-specific wood specific gravity as an explanatory variable. For branch, leaf, and root biomass, the best equations had functional types (deciduous angiosperm, evergreen angiosperm, and evergreen gymnosperm) instead of functional traits (wood specific gravity or leaf mass per area), suggesting importance of other traits in addition to these traits, such as canopy and root architecture. Inclusion of tree height in addition to stem diameter improved the performance of the generic equation only for stem biomass and had no apparent effect on aboveground, branch, leaf, and root biomass at the site level. The development of a generic allometric equation taking account of interspecific differences is an effective approach for accurately estimating aboveground and component biomass in boreal, temperate, and subtropical natural forests.

Context‐dependent changes in the functional composition of tree communities along successional gradients after land‐use change

Summary Land-use change can modify the functional composition of tree communities, which is an essential determinant of the ecosystem functions. The lack of consensus about the functional responses of tree communities to land-use change is a major uncertainty in the assessments of human impacts on terrestrial ecosystem functions. In this study, we applied a machine-learning method to a large data set consisting of 2574 tree communities across Japan to examine changes in the functional composition of tree communities after land-use change while considering contexts including successional trajectories, forest types and the presence of gymnosperms. Specifically, we hypothesized that functional changes along successional gradients after land-use change can be different in different contexts. Effects of two successional variables (stand age and basal area) on functional composition were highly significant throughout the study region. Changes in functional composition with changes in the two successional variables differed greatly, and the effects of basal area often outweighed those of stand age. Tree communities with small basal area were generally characterized by functional traits related to the resource-acquisitive strategy, that is short adult stature, low leaf mass per unit area, small seeds, low wood density and large leaves, especially when gymnosperms were excluded from the analysis. Decreasing basal area but not decreasing stand age often led to a considerable loss in functional diversity. Despite these general trends, functional changes along successional gradients after land-use change were not necessarily parallel and the opposite patterns were sometimes observed among forest types, traits and taxonomic groups. Synthesis. As a whole, our analyses demonstrate that the functional changes in tree communities after land-use change are highly evident in a given context but can be different under different contexts. These changes in functional composition can trigger variable changes in ecosystem functions such as carbon and nutrient cycling that depend on the context.

Detecting latitudinal and altitudinal expansion of invasive bamboo Phyllostachys edulis and Phyllostachys bambusoides (Poaceae) in Japan to project potential habitats under 1.5°C–4.0°C global warming

Abstract Rapid expansion of exotic bamboos has lowered species diversity in Japans ecosystems by hampering native plant growth. The invasive potential of bamboo, facilitated by global warming, may also affect other countries with developing bamboo industries. We examined past (1975–1980) and recent (2012) distributions of major exotic bamboos (Phyllostachys edulis and P. bambusoides) in areas adjacent to 145 weather stations in central and northern Japan. Bamboo stands have been established at 17 sites along the latitudinal and altitudinal distributional limit during the last three decades. Ecological niche modeling indicated that temperature had a strong influence on bamboo distribution. Using mean annual temperature and sun radiation data, we reproduced bamboo distribution (accuracy = 0.93 and AUC (area under the receiver operating characteristic curve) = 0.92). These results infer that exotic bamboo distribution has shifted northward and upslope, in association with recent climate warming. Then, we simulated future climate data and projected the climate change impact on the potential habitat distribution of invasive bamboos under different temperature increases (i.e., 1.5°C, 2.0°C, 3.0°C, and 4.0°C) relative to the preindustrial period. Potential habitats in central and northern Japan were estimated to increase from 35% under the current climate (1980–2000) to 46%–48%, 51%–54%, 61%–67%, and 77%–83% under 1.5°C, 2.0°C, 3.0°C, and 4.0°C warming levels, respectively. These infer that the risk areas can increase by 1.3 times even under a 1.5°C scenario and expand by 2.3 times under a 4.0°C scenario. For sustainable ecosystem management, both mitigation and adaptation are necessary: bamboo planting must be carefully monitored in predicted potential habitats, which covers most of Japan.

Call for Papers for “Future scenarios for socio-ecological production landscape and seascape”

Core research agendas for sustainability science include the following: (1) co-designing future scenarios and visions with a participatory approach, (2) integrating indigenous and local knowledge (ILK) systems into both scientific knowledge and future scenarios, and (3) the formulation of actions to transform society toward a more sustainable future (Miller et al. 2014; Schneider and Rist 2014; Kishita et al. 2016). In 2016, The Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES) approved a methodological assessment report on scenarios and models of biodiversity and ecosystem services. This report guides experts regarding the use of scenarios and models to perform assessments within IPBES. Moreover, it guides scientists, stakeholders, and decision makers. In this assessment report, ‘‘Scenarios’’ are defined as representations of possible futures for one or more components of a system. In this case, this is achieved with particular emphasis on drivers of change in nature and natural resources, including alternative policy or management options. Furthermore, ‘‘models’’ are defined as qualitative or quantitative descriptions of key components of a system and of the relationships that exist between those components. While IPBES has identified the development of scenarios as a key to aid decision makers in identifying potential impacts of different policy options, it currently lacks studies on substantial long-term-scenario approaches (Kok et al. 2017). IPBES emphasizes the importance of ILK together with the social–ecological dynamics of biodiversity and ecosystem services; therefore, engaging with the substantial diversity of local contexts through participatory processes is essential. To meet this challenge, the authors launched a new project in 2016 named ‘‘Predicting and Assessing Natural Capital and Ecosystem Service (PANCES)’’. The aim of this project is to develop an integrated assessment model of social–ecological systems to predict and assess natural and socio-economic values of natural capital and ecosystem services in Japan under various future scenarios (including differing socio-economic conditions and policy options) (PANCES website: http://pances.net/top/). PANCES also promotes multilevel governance of natural capital to maintain and improve ‘‘inclusive wellbeing’’ and to demonstrate the integrated assessment model at both national and local scales in Japan and beyond.