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The plant economics spectrum describes the trade-off between plant resource acquisition and storage, and sheds light on plant responses to environmental changes. However, the data used to construct the plant economics spectrum comes mainly from seed plants, thereby neglecting vascular non-seed plant lineages such as the ferns. To address this omission, we evaluated whether a fern economics spectrum exists using leaf and root traits of 23 fern species living under three subtropical forest conditions differing in light intensity and nutrient gradients. The fern leaf and root traits were found to be highly correlated and formed a plant economics spectrum. Specific leaf mass and root tissue density were found to be on one side of the spectrum (conservative strategy), whereas photosynthesis rate, specific root area, and specific root length were on the other side of the spectrum (acquisitive strategy). Ferns had higher photosynthesis and respiration rates, and photosynthetic nitrogen-use efficiency under high light conditions and higher specific root area and lower root tissue density in high nutrient environments. However, environmental changes did not significantly affect their resource acquisition strategies. Thus, the plant economics spectrum can be broadened to include ferns, which expands its phylogenetic and ecological implications and utility.

Premise Photosynthetic light-response (PLR) curves for leaves are important components of models related to carbon fixation in forest ecosystems, linking the Mitscherlich equation and Michaelis-Menten equation to traits of the leaf economics spectrum (LES). However, models do not consider changes in leaf habits (i.e., evergreen and deciduous) and within-canopy shading variation in these PLR curves. Methods Here, we measured the PLR curves in sun and shade leaves of 44 evergreen and 31 deciduous species to examine the relationships between variables of the Mitscherlich equation and Michaelis-Menten equation, leaf nitrogen (N) and phosphorus (P) content, and leaf mass per area (LMA). Results Small changes were caused by different leaf habits and shade variations in relationships linking variables of the two equations to leaf N and P content and LMA. Values of the scaling exponents for PLR curve parameters did not differ regardless of canopy position and leaf habit (P > 0.05). The PLR curves in species with different leaf habits (i.e., evergreen and deciduous) at different canopy positions could be predicted using the general allometric relations between leaf traits and PLR parameters in the two equations. For photosynthetic photon flux densities from 0 to 2000 μmol m-2 s-1 , approximately 71% (Mitscherlich equation) and 70% (Michaelis-Menten equation) of the net assimilation rates could be predicted. Conclusions These findings indicate that leaf net assimilation rates can be predicted through the large available data for LES traits. Incorporation of values for these traits available in the LES databases into ecosystem models of forest productivity and carbon fixation warrants further investigation.

Understanding the scaling between leaf size and leafing intensity (leaf number per stem size) is crucial for comprehending theories about the leaf costs and benefits in the leaf size–twig size spectrum. However, the scaling scope of leaf size versus leafing intensity changes along the twig leaf size variation in different leaf habit species remains elusive. Here, we hypothesize that the numerical value of scaling exponent for leaf mass versus leafing intensity in twig is governed by the minimum leaf mass versus maximum leaf mass (M min versus M max) and constrained to be ≤−1.0. We tested this hypothesis by analyzing the twigs of 123 species datasets compiled in the subtropical mountain forest. The standardized major axis regression (SMA) analyses showed the M min scaled as the 1.19 power of M max and the ‐α (−1.19) were not statistically different from the exponents of M min versus leafing intensity in whole data. Across leaf habit groups, the M max scaled negatively and isometrically with respect to leafing intensity. The pooled data's scaling exponents ranged from −1.14 to −0.96 for M min and M max versus the leafing intensity based on stem volume (LIV). In the case of M min and M max versus the leafing intensity based on stem mass (LIM), the scaling exponents ranged from −1.24 to −1.04. Our hypothesis successfully predicts that the scaling relationship between leaf mass and leafing intensity is constrained to be ≤−1.0. More importantly, the lower limit to scaling of leaf mass and leafing intensity may be closely correlated with M min versus M max. Besides, constrained by the maximum leaf mass expansion, the broad scope range between leaf size and number may be insensitive to leaf habit groups in subtropical mountain forest., Our hypothesis successfully predicts that the scaling relationship between leaf mass and leafing intensity is constrained to be ≤−1.0. The broad scope range between leaf size and number may not be sensitive to leaf habit groups in the subtropical mountain forest.

Premise of study Leaf area and dry mass are crucial for plant metabolic performance. The "diminishing returns" hypothesis predicts that leaf area will scale less than one with respect to leaf dry mass, indicating that the cost of light interception increases with leaf area. However, it remains unclear whether and how this scaling relationship varies among species growing in different environments. Methods More than 2000 measurements from five bamboo species adapted to high and low light and growing at different elevations in Wuyi Mountains, Southeast China, were used to explore how the leaf area vs. dry mass scaling relationship was affected by light and elevation. Key results The data indicate that (1) the normalization constants for leaf area vs. dry mass were positively but not significantly correlated with increasing leaf size and that (2) the scaling exponents remained numerically invariant among all five bamboo species, with a common slope of 0.85. Standardized major axis (SMA) analyses and comparisons of 95% confidence intervals also showed that the numerical values of the scaling exponents did not differ regardless of elevation and were similar between shaded and unshaded adapted species, whereas the numerical values of the normalization constants increased with decreasing light. Conclusions The data collected for all five bamboo species are consistent with the "diminishing returns" hypothesis, i.e., the scaling exponents governing the leaf area vs. dry mass scaling relationship are less than one within and across species and are insensitive to light conditions or elevation.

 Premise of the study: Empirical studies and theory indicate that respiration rates ( R ) of small plants scale nearly isometrically with both leaf biomass ( M L ) and total plant biomass ( M T ). These predictions are based on angiosperm species and apply only across a small range of body mass. Whether these relationships hold true for different plants, such as conifers, remains unclear .  Methods: We tested these predictions using the whole-plant maintenance respiration rates and the biomass allocation patterns of the seedlings of two conifer tree species and two angiosperm tree species. Model Type II regression protocols were used to compare the scaling exponents ( α ) and normalization constants ( β ) across all four species and within each of the four species.  Key results: The data show that the scaling exponents varied among the four species and that all differed signifi cantly from isometry. For conifers, scaling exponents for R vs. M T , and R and M L were numerically smaller than those of the broadleaved angiosperm species. However, across the entire data set, R scaled isometrically with M L and with M T as predicted by the West, Brown, and Enquist (WBE) theory. We also observed higher respiration rates for small conifer seedlings compared to compa- rably sized angiosperm seedlings.  Conclusions: Our data add credence to the view that the R vs. M scaling relationship differs among species, and that in general, the numerical values of this interspecifi c scaling relationship will depend on the species pooled in the analysis and on the range of body sizes within the data set.

Forest biomass plays a key role in the global carbon cycle. In the present study, a general allometric model was derived to predict the relationships among the stem biomass MS, aboveground biomass MA and total biomass MT, based on previously developed scaling relationships for leaf, stem and root standing biomass. The model predicted complex scaling exponents for MT and/or MA with respect to MS. Because annual biomass accumulation in the stem, root and branch far exceeded the annual increase in standing leaf biomass, we can predict that MT∝MA∝MSas a simple result of the model. Although slight variations existed in different phyletic affiliations (i.e. conifers versus angiosperms), empirical results using Model Type II (reduced major axis) regression supported the model's predictions. The predictive formulas among stem, aboveground and total biomass were obtained using Model Type I (ordinary least squares) regression to estimate forest biomass. Given the low mean percentage prediction errors for aboveground (and total biomass) based on the stem biomass, the results provided a reasonable method to estimate the biomass of forests at the individual level, which was insensitive to the variation in local environmental conditions (e.g. precipitation, temperature, etc.).

For more than a century, ecologists have concentrated on competition as a crucial process for community organization. However, more recent experimental investigations have uncovered the striking influence of positive interactions on the organization of plant communities. Complex combinations of competition and positive interactions operating simultaneously among plant species seem to be widespread in nature. In the present paper, we reviewed the mechanism and ecological importance of positive interactions in plant communities, emphasizing the certainties and uncertainties that have made it an attractive area of research. Positive interactions, or facilitation, occur when one species enhances the survival, growth, or richness of another. The importance of facilitation in plant organization increases with abiotic stress and the relative importance of competition decreases. Only by combining plant interactions and the many fields of biology can we fully understand how and when the positive interactions occur. (Managing editor: Ya-Qin Han)