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Generalized linear mixed models (GLMMs) have been widely used in contemporary ecology studies. However, determination of the relative importance of collinear predictors (i.e. fixed effects) to response variables is one of the challenges in GLMMs. Here, we developed a novel R package, glmm.hp, to decompose marginal R2 explained by fixed effects in GLMMs. The algorithm of glmm.hp is based on the recently proposed approach ‘average shared variance’ i.e. used for multivariate analysis. We explained the principle and demonstrated the use of this package by simulated dataset. The output of glmm.hp shows individual marginal R2s that can be used to evaluate the relative importance of predictors, which sums up to the overall marginal R2. Overall, we believe the glmm.hp package will be helpful in the interpretation of GLMM outcomes.

R is one of the most commonly used analytical tools in the plant sciences. To identify key trends in general reported R use and patterns in photosynthesis research, we explored the frequency of R use in 2966 articles published in the 377 journals with ‘photosynthesis’ in the title from 2010 to 2019 using the Web of Science search. Solutions provided by each R package cited in the articles or online sources was recorded and classified. The percentage of research articles reporting R use increased linearly from 3.6% in 2010 to 12.5% in 2019. The three main categories of R package solutions were ‘general statistical calculations and graph packages’ (G); ‘photosynthesis special-purpose packages’ (S); and ‘genetic and evolutionary packages’ (E). The top five R packages cited were nlme (G), lme4 (G), multcomp (G), plantecophys (S), and ape (E). The increasing popularity of R use in photosynthesis research is due to its user-friendly and abundant open-source codes online for handling specific issues, particularly in fitting photosynthesis models. These findings are limited by the number of articles and online sources, but they reveal a significant increase in usage in photosynthesis research over the past decade and have a bright prospect in the future.

Symbiotic nitrogen (N)-fixing trees can provide large quantities of new N to ecosystems, but only if they are sufficiently abundant. The overall abundance and latitudinal abundance distributions of N-fixing trees are well characterised in the Americas, but less well outside the Americas. Here, we characterised the abundance of N-fixing trees in a network of forest plots spanning five continents, ~5,000 tree species and ~4 million trees. The majority of the plots (86%) were in America or Asia. In addition, we examined whether the observed pattern of abundance of N-fixing trees was correlated with mean annual temperature and precipitation. Outside the tropics, N-fixing trees were consistently rare in the forest plots we examined. Within the tropics, N-fixing trees were abundant in American but not Asian forest plots (~7% versus ~1% of basal area and stems). This disparity was not explained by mean annual temperature or precipitation. Our finding of low N-fixing tree abundance in the Asian tropics casts some doubt on recent high estimates of N fixation rates in this region, which do not account for disparities in N-fixing tree abundance between the Asian and American tropics. Synthesis. Inputs of nitrogen to forests depend on symbiotic nitrogen fixation, which is constrained by the abundance of N-fixing trees. By analysing a large dataset of ~4 million trees, we found that N-fixing trees were consistently rare in the Asian tropics as well as across higher latitudes in Asia, America and Europe. The rarity of N-fixing trees in the Asian tropics compared with the American tropics might stem from lower intrinsic N limitation in Asian tropical forests, although direct support for any mechanism is lacking. The paucity of N-fixing trees throughout Asian forests suggests that N inputs to the Asian tropics might be lower than previously thought.

Tropical and subtropical forest ecosystems play an important role in the global carbon regulation. Although positive relationships between biodiversity and soil organic carbon (SOC) storage have been found in experimental grasslands, biodiversity effects on SOC storage in natural forests remain debated. Based on a large dataset from 523 forest inventory plots across subtropical forests in China, we tested the relationship between biodiversity and SOC storage and examined whether environmental conditions (temperature, precipitation, soil properties) and litter quantity (leaf litter and root biomass) and quality (leaf litter carbon to nitrogen ratio [leaf litter C/N]) had effects on SOC storage. Furthermore, we used linear mixed-effects models to test the relative effects of biodiversity, environmental conditions, and litter quantity and quality on SOC storage. We used structural equation models to test how these variables directly or indirectly affected SOC storage. We found that species diversity, together with climatic factors (mean annual temperature and mean annual precipitation), leaf litter C/N and root biomass determined SOC storage in subtropical forests at a large spatial scale. SOC storage was most strongly affected by climatic factors, followed by leaf litter C/N. Species diversity had both direct and indirect (through root biomass and leaf litter C/N) effects on SOC storage after accounting for environmental conditions. We also found that the positive diversity–SOC storage relationships were stronger in low and medium mean annual precipitation. Our findings highlight that higher species diversity can lead to higher SOC storage and therefore the conservation of biodiversity could play an important role in climate change mitigation.

The correlation between primary producer diversity and the productivity (or biomass) of ecosystems is one of the most important and broadly studied relationship in ecology. Ecologists have discussed this relationship from two fundamentally different perspectives. Historically, productivity has been viewed as driver of species diversity. Recently, many studies have demonstrated that diversity can also control, rather than responds to, the production of biomass. These contrasting points of view have led to the debate about whether species diversity is the cause or the consequence of community productivity. Multivariate productivity-diversity hypothesis has been put forward to reconciling this debate. This hypothesis state that: (i) the environmental factors are the direct driver of species that can coexist within an area; (ii) the biomass of the area is directly influenced by the environmental factors that limit production; (iii) the environmental factors indirectly influenced biomass of the area via influencing the species number to coexist within the area that affects how efficiently environmental resources are converted into biomass. To date, empirical support for this hypothesis is scarce, especially for structurally complex terrestrial ecosystems. In this study, we modified multivariate productivity- diversity hypothesis to accommodate complex vertical structure of forest ecosystems, and used structural equation modeling and data from a large evergreen broad-leaved forest dynamic plot (24 hm2 in area) in subtropical China to understand the causal relationships among environmental factors, species richness, dominance and aboveground biomass. Trees were grouped into tow functional groups (overstorey and understorey) in order to improve the ability to detecting the diversity effect. The final model explained 30% and 58% of the variation in aboveground biomass of overstorey and understorey, respectively. Dominance was the most important factor in explaining the variation of aboveground biomass of overstorey, while both species richness and environment factors were the most important factors in explaining the variation of aboveground biomass of understorey. Consistent with the predictions of multivariate productivity-diversity hypothesis, (i) aboveground biomass were directly influenced by the environmental factors in both overstorey and understorey; (ii) environmental factors directly influence tree dominance and species richness of overstorey, but only directly influence species richness of understorey; (iii) environmental factors indirectly influence aboveground biomass of overstorey by influencing dominant, while indirectly influence aboveground biomass of understorey by influencing species richness. Interestingly, species richness was only important to explaining variation in aboveground biomass of understorey. This may be attributed to the low light condition in understorey, which may alleviative competition among trees of understorey. To our knowledge, this study provides the first empirical evidence supporting the multivariate productivity-diversity hypothesis in forest ecosystem thus contributes to extending the generality of this framework. Our result also highlights both dominant species and higher species richness is required to maximizing forest biomass.

Forests play a vital role in regulation of the global carbon cycle. Mechanistically understanding how their ecosystem functioning relates to biodiversity is necessary for predicting the consequences of biodiversity loss and for setting conservation priorities. Here, we test whether carbon stocks in a subtropical evergreen broad-leaved forest in China are more strongly influenced by plant functional diversity (FD), as would be predicted by the ‘niche complementarity hypothesis’, or by community-weighted mean (CWM) functional trait values, as would be predicted by the ‘mass ratio hypothesis’. Using data from a 24-ha plot subdivided into 400 m2 quadrats, we determined relationships of aboveground carbon (AGC) and topsoil (1–10 cm) organic carbon (SOC) to topographic variables, stem density, CWM and FD of six functional traits hypothesized to influence carbon stocks. After accounting for topographic variables and tree stem density, boosted regression tree models revealed that CWMs were the dominant driving factors for both AGC and SOC, whereas FD had negligible effects. AGC and SOC were influenced by different functional traits, with AGC responding most strongly to CWM values for wood density and maximum tree height, and SOC responding most strongly to elevation, indicating that these carbon stocks are shaped by different underlying mechanisms. Our results support the mass ratio hypothesis but not the niche complementarity hypothesis. Our study implies that, when it comes to maximizing forest carbon storage, conservation priorities should focus on protection of species with traits associated to high carbon stocks.

Taylor's law says that the variance of population density of a species is proportional to a power of mean population density. Density–mass allometry says that mean population density is proportional to a power of mean biomass per individual. These power laws predict a third, variance–mass allometry: the variance of population density of a species is proportional to a power of mean biomass per individual. We tested these laws using 10 censuses of New Zealand mountain beech trees in 250 plots over 30 years at spatial scales from 5 m to kilometers. We found that: 1) a single-species forest not disrupted by humans obeyed all three laws; 2) random sampling explained the parameters of Taylor's law at a large spatial scale in 8 of 10 censuses, but not at a fine spatial scale; 3) larger spatial scale increased the exponent of Taylor's law and decreased the exponent of variance–mass allometry (this is the first empirical demonstration that the latter exponent depends on spatial scale), but affected the exponent of density–mass allometry slightly; 4) despite varying natural disturbance, the three laws varied relatively little over the 30 years; 5) self-thinning and recruiting plots had significantly different intercepts and slopes of density–mass allometry and variance–mass allometry, but the parameters of Taylor's law were not usually significantly affected; and 6) higher soil calcium was associated with higher variance of population density in all censuses but not with a difference in the exponent of Taylor's law, while elevation above sea level and soil carbon-to-nitrogen ratios had little effect on the parameters of Taylor's law. In general, the three laws were remarkably robust. When their parameters were influenced by spatial scale and environmental factors, the parameters could not be species-specific indicators. We suggest biological mechanisms that may explain some of these findings.

Tropical and subtropical forest ecosystems play an important role in the global carbon regulation. Despite increasing evidence for effects of biodiversity (species diversity, functional diversity and functional dominance), stand structural attributes, stand age and environmental conditions (climate and topography) on tree carbon storage, the relative importance of these drivers at large scale is poorly understood. It is also still unclear whether biodiversity effects on tree carbon storage work through niche complementarity (i.e. increased tree carbon storage due to interspecific resource partitioning) or through the mass-ratio effect (tree carbon storage regulated by dominant traits within communities). Here we analyze tree carbon storage and its drivers using data of 480 plots sampled across subtropical forests in China. We use multiple regression models to test the relative effects of biodiversity, stand structural attributes, stand age and environmental conditions on tree carbon storage, and use a partial least squares path model to test how these variables directly and/or indirectly affect tree carbon storage. Our results show that tree carbon storage is most strongly affected by stand age, followed by climate, biodiversity and stand structural attributes. Stand age and climate had both direct and indirect (through species diversity, functional dominance and stand structural attributes) effects. We find that tree carbon storage correlates with both species diversity and functional dominance after stand age and environmental drivers are accounted for. Our results suggest that niche complementarity and the mass-ratio effect, not necessarily mutually exclusive, both play a role in maintaining ecosystem functioning. Our results further indicate that biodiversity conservation might be an effective way for enhancing tree carbon storage in natural, species-rich forest ecosystems.

Aim Early in their evolution, angiosperms evolved a diversity of leaf form far greater than that of any other group of land plants. Some of this diversity evolved in response to varying climate. Our aim is to test the global relationship between leaf form in woody dicot angiosperms and the climate in which they live.

Restoring the functions of disturbed forest to mitigation climate change is a main topic of policy makers. Better understanding of factors that directly influence post- disturbance forest biomass recovery is urgently needed to guide forest restoration and management. In this study, we examine changes in forest stand structure, wood density and biomass of forests recovering from different anthropogenic disturbances that represent forest land-use types in sub- tropical China: plantation, twice-logged and once-logged secondary forests, and compare them with undisturbed old- growth forest. Stand structure and wood density in all dis- turbed forests were evidently different from that of old- growth forest, even after 50-year regrowth. Forest biomass increased along plantation, twice-logged, once-logged and old-growth forests, with total living biomass (TLB) ranging from 150.8 ± 4.6 to 278.4 ± 1.5 Mg ha -1 , aboveground biomass from 111.8 ± 4.2 to 204.1 ± 1.5 Mg ha -1 and coarse-root biomass from 33.0 ± 0.9 to 71.0 ± 0.8 Mg ha -1 . However, fine-root biomass was highest in plan- tation (5.99 ± 0.52 Mg ha -1 ) and lowest in once-logged forest (3.35 ± 0.19 Mg ha -1 ). Both changes in stand structure and functional trait (wood density) directly deter- mine forest biomass recovery according to the result that 10.6,35.5and8.2 %ofvariationinTLBoverthedisturbance gradient were independently explained by basal area (\20 cmdiameter),basal area(C20 cmdiameter)andwood density,respectively.Ourresultssuggestthatrecoveryforest structure to the state associated with undisturbed forests will lead to large carbon sink in disturbed forests. In addition, trait-based managing approach should not be overlooked when maximizing carbon storage is a major management objective.

Climate is widely recognised as an important determinant of the latitudinal diversity gradient. However, most existing studies make no distinction between direct and indirect effects of climate, which substantially hinders our understanding of how climate constrains biodiversity globally. Using data from 35 large forest plots, we test hypothesised relationships amongst climate, topography, forest structural attributes (stem abundance, tree size variation and stand basal area) and tree species richness to better understand drivers of latitudinal tree diversity patterns. Climate influences tree richness both directly, with more species in warm, moist, aseasonal climates and indirectly, with more species at higher stem abundance. These results imply direct limitation of species diversity by climatic stress and more rapid (co-)evolution and narrower niche partitioning in warm climates. They also support the idea that increased numbers of individuals associated with high primary productivity are partitioned to support a greater number of species.

The size distribution of trees in natural forests is a fundamental attribute of forest structure. Previous attempts to model tree size distributions using simple functions (such as power or Weibull functions) have had limited success, typically overestimating the number of large stems observed. We describe a model which assumes that the dominant mortality process is asymmetric competition when trees are smaller, and size-independent processes (e.g. disturbance) when trees are larger. This combination of processes leads to a size distribution which takes the form of a power distribution in the small tree phase and a Weibull distribution in the large tree phase. Analyses of data from four large-scale ( 24 ha each) subtropical and temperate forest plots totalling 99 ha and approximately 0.4 million trees provide support for this model in two respects: (a) the combined function provided unbiased predictions and (b) power-law functions fitted to small trees had exponents that deviated from the universal exponent of 22 predicted by metabolic scaling theory, gradually decreasing from subtropical evergreen to temperate deciduous forests along the latitudinal gradient.

Though coarse root biomass is an important part in biomass of forest ecosystems, few studies were found in subtropical area. In this study, whole digging method was used to determine the biomass of coarse root (diameter>2 mm) of 175 trees of 8 species in subtropical evergreen forests. The 8 species includes Castanopsis fargesii , Castanopis sclerophylla , Schima superba , Pinus massoniana , Cunninghamia lanceolata , Liquidambar formosana , Sassafras tzumu , Alniphyllum fortunei . Also, the lost roots during excavation were corrected by developing scaling relationship between biomass of root and diameter. Then, four kinds of allometric models for each species and combined trees were fitted to link stem diameter at breast height (dbh) and height ( H ) to coarse root biomass. The results showed that all the scaling relationship between biomass of root and diameter of roots were significant ( P P R 2 values than the height-coarse root biomass. The results also indicate that dbh is an adequate estimator for coarse root biomass of subtropical evergreen trees. The results in this study provide important information to estimate the coarse root biomass in subtropical evergreen forests.

With the full survey data for a 24-ha subtropical evergreen broad-leaved forest dynamics plot, we evaluated spatial variation in forest structure characteristics (basal area and aboveground biomass), and calculated the minimal sample size and total sampling area necessary to estimate the forest structure characteristics within 20% (±10%) of the observed values with 95% probability for particular quadrat sizes by using a computer program that is designed to simulate the sampling process by allowing different sized quadrats to be randomly located within the sampling region. We found that (1) based on the 600 20 m×20 m subplots, basal area and aboveground biomass displayed a high degree of variation, with respective coefficients of variation of 27% and 31%; (2) based on the computer simulation analysis, the variability of basal area and aboveground biomass decreased with increasing quadrat size. The number of quadrats required to achieve the specified degree of precision dropped sharply with the increase of quadrat size. However, the total sampling area increased with increasing quadrat size, suggesting that using several small quadrats across the sampling area is more efficient than using fewer larger quadrats. Results of this study are valuable for evaluating the reliability of previous research and may assist researchers in designing effective sampling strategies for future field surveys, particularly in subtropical evergreen broad-leaved forests in China.

Question: Do tree and shrub species in an evergreen broadleaf forest show similar habitat associations across different life stages?

The subtropical forest biome occupies about 25% of China, with species diversity only next to tropical forests. Despite the recognized importance of subtropical forest in regional carbon storage and cycling, uncertainties remain regarding the carbon storage of subtropical forests, and few studies have quantified within-site variation of biomass, making it difficult to evaluate the role of these forests in the global and regional carbon cycles. Using data for a 24-ha census plot in east China, we quantify aboveground biomass, characterize its spatial variation among different habitats, and analyse species relative contribution to the total aboveground biomass of different habitats. The average aboveground biomass was 223.0 Mg ha(-1) (bootstrapped 95% confidence intervals [217.6, 228.5]) and varied substantially among four topographically defined habitats, from 180.6 Mg ha(-1) (bootstrapped 95% CI [167.1, 195.0]) in the upper ridge to 245.9 Mg ha(-1) (bootstrapped 95% CI [238.3, 253.8]) in the lower ridge, with upper and lower valley intermediate. In consistent with our expectation, individual species contributed differently to the total aboveground biomass of different habitats, reflecting significant species habitat associations. Different species show differently in habitat preference in terms of biomass contribution. These patterns may be the consequences of ecological strategies difference among different species. Results from this study enhance our ability to evaluate the role of subtropical forests in the regional carbon cycle and provide valuable information to guide the protection and management of subtropical broad-leaved forest for carbon sequestration and carbon storage.