Leaf size varies by over a 100,000-fold among species worldwide. Although 19th-century plant geographers noted that the wet tropics harbor plants with exceptionally large leaves, the latitudinal gradient of leaf size has not been well quantified nor the key climatic drivers convincingly identified. Here, we characterize worldwide patterns in leaf size. Large-leaved species predominate in wet, hot, sunny environments; small-leaved species typify hot, sunny environments only in arid conditions; small leaves are also found in high latitudes and elevations. By modeling the balance of leaf energy inputs and outputs, we show that daytime and nighttime leaf-to-air temperature differences are key to geographic gradients in leaf size. This knowledge can enrich "next-generation" vegetation models in which leaf temperature and water use during photosynthesis play key roles.

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects.We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives. Geosphere-Biosphere Program (IGBP) and DIVERSITAS, the TRY database (TRY-not an acronym, rather a statement of sentiment; https ://www.try-db.org; Kattge et al., 2011) was proposed with the explicit assignment to improve the availability and accessibility of plant trait data for ecology and earth system sciences. The Max Planck Institute for Biogeochemistry (MPI-BGC) offered to host the database and the different groups joined forces for this community-driven program. Two factors were key to the success of TRY: the support and trust of leaders in the field of functional plant ecology submitting large databases and the long-term funding by the Max Planck Society, the MPI-BGC and the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, which has enabled the continuous development of the TRY database.

A novel framework is presented for the analysis of ecophysiological field measurements and modelling. The hypothesis 'leaves minimise the summed unit costs of transpiration and carboxylation' predicts leaf-internal/ambient CO2 ratios (ci /ca ) and slopes of maximum carboxylation rate (Vcmax ) or leaf nitrogen (Narea ) vs. stomatal conductance. Analysis of data on woody species from contrasting climates (cold-hot, dry-wet) yielded steeper slopes and lower mean ci /ca ratios at the dry or cold sites than at the wet or hot sites. High atmospheric vapour pressure deficit implies low ci /ca in dry climates. High water viscosity (more costly transport) and low photorespiration (less costly photosynthesis) imply low ci /ca in cold climates. Observed site-mean ci /ca shifts are predicted quantitatively for temperature contrasts (by photorespiration plus viscosity effects) and approximately for aridity contrasts. The theory explains the dependency of ci /ca ratios on temperature and vapour pressure deficit, and observed relationships of leaf δ(13) C and Narea to aridity.

wileyonlinelibrary.comnanorods, [ 6,7 ] carbon nanotubes (CNTs), [ 8,9 ] graphene, [ 10,11 ] etc.), have been investigated and developed. Accompany with the development of stimulus-responsive materials, various types of external stimulus, including electric, [ 12,13 ] heat, [14][15][16] light, [ 17,18 ] magnetic, [19][20][21] chemical stimulus, [ 22 ] pneumatic stimulus, [ 23 ] and so forth, have been successfully employed to develop biomimetic or bio-inspired microrobotic systems applying in microjets, [ 16 ] microgrippers, [ 24,25 ] drilling of tissues, [ 26 ] drug and cell delivery, [ 27,28 ] fi xing cancer cells, [ 29 ] artifi cial muscles, [ 30 ] and some other smart microstructures.Because of their ability in wireless/ remote control, low noise, localized driven ability rather than whole-fi eld driven, [ 31 ] light-driven microrobots have attracted more and more attention in novel microbio-robots or micro-motors for biological use. For example, for the minimally invasive medicine applications, the microrobots must exhibit locomotion and controlled interaction with their environment, which should be able to reach a targeted area under the direct supervision and control of an external user. Due to its excellent penetration ability in biological tissues (can be over several centimeters [ 32 ] ), near infrared (nIR) light provides a promising approach to remotely actuate the microrobots in bodies, which may fi nd applications in the development of novel micro-bio-robots or biomimetic micro-motors in vivo and in vitro.Graphene, due to its excellent electrical and thermal conductivity, high surface area, and high fl exibility, has been employed to perform various actuation based on graphene polymeric nanocomposites, that is, stimulated by electrical, [ 33,34 ] electrochemical, [ 11,35 ] and optical energy. [ 10 ] Because of its photothermal effect and high thermal conductivity, graphene and its composites show promising photoresponsive properties. Panchapakesan [ 31 ] reported a large light-induced reversible and elastic response of graphene nanoplatelets (GNPs) polymer composites which is composited with GNPs and polydimethylsiloxane (PDMS), and developed a two-axis submicrometer resolution positioning stage. Wu [ 36 ] developed a bimorph confi guration which was constituted with chemically modifi ed polye thylene (PE) fi lms and a mixture of large-area graphene-chitosan, behaving as a transparent soft actuator that expanded under nIR irradiation. Wang [ 37 ] developed light-driven hand-shape Biomimetic microsystems, which can be driven by various stimuli, are an emerging fi eld in micro/nano-technology and nano-medicine. In this study, a soft and fast-response robotic platform, constituted by PDMS/graphenenanoplatelets composited layer (PDMS/GNPs) and pristine PDMS layer, is presented. Due to the differences in coeffi cient of thermal expansion and Young's modulus of the two layers, the bilayer platform can be driven to bend to the PDMS/GNPs side by light irradiation. The robotic platform (1 mm in width and 7 m...

<p><strong>Abstract.</strong> Nitrogen content per unit leaf area (<i>N</i><sub><i>area</i></sub>) is a key variable in plant functional ecology and biogeochemistry. <i>N</i><sub><i>area</i></sub> comprises a structural component, which scales with leaf mass per area (LMA), and a metabolic component, which scales with Rubisco capacity. The co-ordination hypothesis, as implemented in LPJ and related global vegetation models, predicts that Rubisco capacity should be directly proportional to irradiance but should decrease with <i>c<sub>i</sub>:c<sub>a</sub></i> and temperature because the amount of Rubisco required to achieve a given assimilation rate declines with both. We tested these predictions using LMA, leaf <i>δ</i><sup>13</sup>C and leaf N measurements on complete species assemblages sampled at sites on a North-South transect from tropical to temperate Australia. Partial effects of mean canopy irradiance, mean annual temperature and <i>c<sub>i</sub>:c<sub>a</sub></i> (from <i>δ</i><sup>13</sup>C) on <i>N</i><sub><i>area</i></sub> were all significant and their directions and magnitudes were in line with predictions. Over 80 % of the variance in community-mean (ln) <i>N</i><sub><i>area</i></sub> was accounted for by these predictors plus LMA. Moreover, <i>N</i><sub><i>area</i></sub> could be decomposed into two components, one proportional to LMA (slightly steeper in N-fixers), the other to predicted Rubisco activity. Trait gradient analysis revealed <i>c<sub>i</sub>:c<sub>a</sub></i> to be perfectly plastic, while species turnover contributed about half the variation in LMA and <i>N</i><sub><i>area</i></sub>. <br><br> Interest has surged in methods to predict continuous leaf-trait variation from environmental factors, in order to improve ecosystem models. Our results indicate that <i>N</i><sub><i>area</i></sub> has a useful degree of predictability, from a combination of LMA and <i>c<sub>i</sub>:c<sub>a</sub></i> – themselves in part environmentally determined – with Rubisco activity, as predicted from local growing conditions. This is consistent with a 'plant-centred' approach to modelling, emphasizing the adaptive regulation of traits. Models that account for biodiversity will also need to partition community-level trait variation into components due to phenotypic plasticity and/or genotypic differentiation within species, versus progressive species replacement, along environmental gradients. Our analysis suggests that variation in <i>N</i><sub><i>area</i></sub> is about evenly split between these two modes.</p>

Fires play an important role in ecosystem dynamics. Long-term controls on global burned area include fuel continuity and moisture, with ignitions and human activity becoming dominant in specific ecosystems. Changes in fuel continuity and moisture are the main drivers of changes of fire globally.

High electrochemical stability and reaction kinetics of Zn anodes are crucial for rechargeable aqueous zinc batteries. Developing low-cost aqueous electrolytes is highly required. In this work, the fundamental principles to improve Zn anodes are systematically revealed in low-cost 1 M ZnSO 4 -based aqueous electrolytes using trace polymer additives with different polarities. The functional polymer additive could rearrange the "Zn 2+ −H 2 O−SO 4 2− −polymer" bonding network accordingly and reconstruct the space charge region of Zn anodes, resulting in distinctive cycling stability and reaction kinetics. Polymers with moderate polarity, such as polyacrylamide, exhibit synergic enhancement as the "smoother" and "thruster" for Zn 2+ toward Zn anodes, with which Zn anodes run over 1300 h with Coulombic efficiency >99.65% under 2 mA cm −2 , 2 mAh cm −2 , showing uniform Zn deposition with minimal impact on reaction kinetics. This work provides useful insights on designing low-cost and high-performance aqueous electrolytes through functional electrolyte additives.

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