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15 págs.- 6 figuras.- 75 referencias, Archaea represent a diverse group of microorganisms often associated with extreme environments. However, an integrated understanding of biogeographical patterns of the specialist Haloarchaea and the potential generalist ammonia-oxidizing archaea (AOA) across large-scale environmental gradients remains limited. We hypothesize that niche differentiation determines their distinct distributions along environmental gradients. To test the hypothesis, we use a continental-scale research network including 173 dryland sites across northern China. Our results demonstrate that Haloarchaea and AOA dominate topsoil archaeal communities. As hypothesized, Haloarchaea and AOA show strong niche differentiation associated with two ecosystem types mainly found in China's drylands (i.e. deserts vs. grasslands), and they differ in the degree of habitat specialization. The relative abundance and richness of Haloarchaea are higher in deserts due to specialization to relatively high soil salinity and extreme climates, while those of AOA are greater in grassland soils. Our results further indicate a divergence in ecological processes underlying the segregated distributions of Haloarchaea and AOA. Haloarchaea are governed primarily by environmental-based processes while the more generalist AOA are assembled mostly via spatial-based processes. Our findings add to existing knowledge of large-scale biogeography of topsoil archaea, advancing our predictive understanding on changes in topsoil archaeal communities in a drier world., This research was supported by the National Natural Science Foundation of China (Nos. 31700463 and 31770430), National Scientific and Technological Program on Basic Resources Investigation (No. 2019FY102002), Biodiversity Survey and Assessment Project of the Ministry of Ecology and Environment, China (No. 2019HJ2096001006), the Top Leading Talents in Gansu Province to J.D. and the Innovation Base Project of Gansu Province (No. 20190323). J.C.S. was supported by the U.S. Department of Energy-BER program, as part of an Early Career Award to J.C.S. at the Pacific Northwest National Laboratory (PNNL), a multiprogram national laboratory operated by Battelle for the US Department of Energy under Contract DEAC05-76RL01830. M.D.-B. acknowledges support from the Spanish Ministry of Science and Innovation for the I +-D + i project PID2020-115813RA-I00 funded by MCIN/AEI/10.13039/501100011033. M.D.-B. is also supported by a project of the Fondo Europeo de Desarrollo Regional (FEDER) and the Consejería de Transformacion Economica, Industria, Conocimiento y Universidades of the Junta de Andalucía (FEDER Andalucía 2014–2020 Objetivo tematico ‘01 - Refuerzo de la investigacion, el desarrollo tecnologico y la innovacion’) associated with the research project P20_00879 (ANDABIOMA).

The ontogeny of seed plants usually involves a dormant dehydrated state and the breaking of dormancy and germination, which distinguishes it from that of most organisms. Seed germination and seedling establishment are critical ontogenetic stages in the plant life cycle, and both are fueled by respiratory metabolism. However, the scaling of metabolic rate with respect to individual traits remains poorly understood. Here, we tested metabolic scaling theory during seed germination and early establishment growth using a recently developed model and empirical data collected from 41 species. The results show that (i) the mass-specific respiration rate (Rm) was weakly correlated with body mass, mass-specific N content, and mass-specific C content; (ii) Rm conformed to a single Michaelis-Menten curve as a function of tissue water content; and (iii) the central parameters in the model were highly correlated with DNA content and critical enzyme activities. The model offers new insights and a more integrative scaling theory that quantifies the combined effects of tissue water content and body mass on respiratory metabolism during early plant ontogeny.

Leaf traits of global plants reveal the fundamental trade-offs in plant resource acquisition to conservation strategies. However, which leaf traits are consistent, converged, or diverged among herbs, shrubs, and subshrubs in an arid environment remains unclear. In the present study, we evaluated the trade-offs in six leaf functional traits (LFTs): leaf fresh mass (LFM), leaf dry mass (LDM), leaf dry matter content (LDMC), leaf area (LA), specific leaf area (SLA), and leaf thickness (LTh) of 37 desert plant species. LFTs differed between different plant life forms; LFM, LDM, and LA were slightly higher in herbs, LDMC and LTh in shrubs, and SLA in subshrubs. Conversely, the correlations among LFTs were inconsistent in different life forms, which may indicate their different adaptation strategies in an arid environment. Legumes and C

It is commonly believed that climate plays an important role in shaping the patterns of plant species richness. However, it remains unclear how climate may affect plant richness across large spatial scales and also over long-terms, for example across massive arid regions during the Quaternary and into the future. To fill this knowledge gap, we examined the long-term trends in plant species richness across vast drylands in China based on our newly developed climate-species richness models. We first generated optimal random forest models based on the relationships between the current (CUR, 1970–2000) annual, perennial, woody and total species richness and climatic variables. We subsequently hindcasted and forecasted plant species richness in five other periods: last interglacial (LIG, 120,000–140,000 years BP), last glacial maximum (LGM, about 22,000 years BP), mid-Holocene (MH, about 6000 years BP), 2041–2060 (2050), and 2061–2080 (2070). Our results showed that total and herbaceous species richness exhibited similar patterns that were driven by temperature and precipitation. Both groups of species formed a transition zone between arid and semi-arid regions in all periods except LIG. In contrast, woody species richness did not form any transition zone because it was regulated mainly by temperature. Furthermore, the mean richness of herbaceous, woody and all species exhibited gradually increasing trends from LIG to 2070 across drylands in China. On the one hand, herbaceous species were much more sensitive to climate change than woody species. On the other hand, plant species richness in mountain-basin systems and Taklamakan Desert regions were more sensitive to climate change than in meadows and steppes. These results shed new insights into the past and future changes in plant species richness over vast drylands and provide valuable information for future conservation efforts under global warming.

Anthocyanins can help plants adapt and resist adverse environments and have important nutritional and medicinal effects on human beings. However, how environmental factors affect the anthocyanins accumulation of plants and how to improve the anthocyanins content of plants in different soils needs further exploration. Hence, this study aimed to investigate the effects of environmental factors on the accumulation of cyanidin, petunidin, malvidin, and delphinidin in the fruits of Lycium ruthenicum in sandy desert grassland (SS), gravel desert grassland (GD), and saline-alkali desert grassland (SD) in the lower reaches of the Shiyang River Basin. The variable importance screened the key environmental factors affecting anthocyanin accumulation in projection (VIP) and multiple stepwise regressions. The structural equation model (SEM) was established to understand how the climate and soil factors affect the total anthocyanin accumulation. For establishing soil nutrient optimization schemes by partial least squares regression (PLS) and the simplex algorithm used to improve the anthocyanin content in different types of desert grassland. In SS, electrical conductivity (EC) and microbial biomass carbon (SMBC) showed highly significant and positive effects on the content of total anthocyanin, cyanidin, and petunidin. In GD, soil moisture and microbial biomass nitrogen (SNBN) significantly negatively affected total anthocyanin content. In SD, catalase (CAT), phosphatase (PHO), and total potassium (TK) had the greatest impact on total anthocyanin content. It is indicated that the targeted improvement measures are necessary to increase anthocyanin content in the fruit of Lycium ruthenicum.

In response to the problem of crosstalk between cores in the large-capacity multi-core fiber space division multiplexing elastic optical network (SDM-EON), the service transmission quality decreases and the blocking rate increases. The causes of spectrum fragmentation are analyzed, and a defragmentation algorithm for space division multiplexing elastic optical network based on MCDM (Multiple Criteria Decision Making, MCDM) is proposed from the perspective of improving spectrum utilization. The algorithm uses multi-criteria decision-making to defragment the spectrum, so that the defragmentation effect is optimal. Simulation verification is carried out through specific examples, and the results prove that the proposed algorithm has a lower bandwidth blocking rate (35% blocking rate under high load) and request blocking rate (41% under high load). It can effectively improve the network request blocking rate under high network load conditions, and provides a theoretical reference for the processing of the spectrum fragmentation of the elastic optical network under actual conditions.

Relationships between biodiversity and multiple ecosystem functions (that is, ecosystem multifunctionality) are context-dependent. Both plant and soil microbial diversity have been reported to regulate ecosystem multifunctionality, but how their relative importance varies along environmental gradients remains poorly understood. Here, we relate plant and microbial diversity to soil multifunctionality across 130 dryland sites along a 4,000 km aridity gradient in northern China. Our results show a strong positive association between plant species richness and soil multifunctionality in less arid regions, whereas microbial diversity, in particular of fungi, is positively associated with multifunctionality in more arid regions. This shift in the relationships between plant or microbial diversity and soil multifunctionality occur at an aridity level of ∼0.8, the boundary between semiarid and arid climates, which is predicted to advance geographically ∼28% by the end of the current century. Our study highlights that biodiversity loss of plants and soil microorganisms may have especially strong consequences under low and high aridity conditions, respectively, which calls for climate-specific biodiversity conservation strategies to mitigate the effects of aridification.

In order to reduce the blocking rate of wavelength routing DWDM optical network and improve the wavelength resource utilization, this paper proposes a deep learning optical network routing algorithm based on wavelength continuity supervision (DL-RWA). In this algorithm, wavelength continuity is taken as the key parameter, and the data set is created by supervised learning. After the deep neural network (DNN) is constructed, the data set is used to train it, and the network parameters are adjusted, so that the algorithm can select the routing and wavelength assignment (RWA) scheme with the best wavelength continuity according to the real-time situation of the dynamic network. The simulation results show that compared with the traditional KSP + FF routing algorithm, DL-RWA algorithm can effectively enhance the routing effect and improve the network environment when dealing with the long correlation traffic model (IP traffic simulation).

Plants need water and energy for their growth and reproduction. However, how water and energy availability influence dryland plant diversity along the aridity gradient in water-limited regions is still lacking. Hence, quantitative analyses were conducted to evaluate the relative importance of water and energy to dryland plant diversity based on 1039 quadrats across 184 sites in China’s dryland. The results indicated that water availability and the water–energy interaction were pivotal to plant diversity in the entire dryland and consistent with the predictions of the water–energy dynamic hypothesis. The predominance of water limitation on dryland plant diversity showed a weak trend with decreasing aridity, while the effects of energy on plants were found to be significant in mesic regions. Moreover, the responses of different plant lifeforms to water and energy were found to vary along the aridity gradient. In conclusion, the study will enrich the limited knowledge about the effects of water and energy on plant diversity (overall plants and different lifeforms) in the dryland of China along the aridity gradient.

In order to effectively reduce the blocking rate of optical networks, a spectrum defragmentation algorithm in elastic optical networks is proposed This paper mainly studies the spectrum defragmentation, designs a spectrum defragmentation algorithm based on Multiple Criteria Decision Making (MCDM), and USES Delphi programming tool to simulate and verify it. The results show that this algorithm can effectively reduce the blocking rate of the network while improving the spectrum utilization.

The extent to which key factors at the global scale influence plant biomass allocation patterns remains unclear. Here, we provide a theory about how biotic and abiotic factors influence plant biomass allocation and evaluate its predictions using a large global database for forested communities. Our analyses confirm theoretical predictions that temperature, precipitation, and plant height and density jointly regulate the quotient of leaf biomass and total biomass, and that they have a much weaker effect on shoot (leaf plus stem) biomass fractions at a global scale. Moreover, biotic factors have larger effects than abiotic factors. Climatic variables act equally on shoot and root growth, and differences in plant body size and age, as well as community species composition, which vary with climate in ways that drown out the variations in biomass fractions. The theory and data presented here provide mechanistic explanations of why climate has little effect on biomass fractions.

Convergence is commonly caused by environmental filtering, severe climatic conditions and local disturbance. The basic aim of the present study was to understand the pattern of leaf traits across diverse desert plant species in a common garden, in addition to determining the effect of plant life forms (PLF), such as herb, shrub and subshrub, phylogeny and soil properties on leaf traits. Six leaf traits, namely carbon (C), nitrogen (N), phosphorus (P), potassium (K), &delta, 13C and leaf water potential (LWP) of 37 dominant desert plant species were investigated and analyzed. The C, N, K and &delta, 13C concentrations in leaves of shrubs were found higher than herbs and subshrubs, however, P and LWP levels were higher in the leaves of subshrubs following herbs and shrubs. Moreover, leaf C showed a significant positive correlation with N and a negative correlation with &delta, 13C. Leaf N exhibited a positive correlation with P. The relationship between soil and plant macro-elements was found generally insignificant but soil C and N exhibited a significant positive correlation with leaf P. Taxonomy showed a stronger effect on leaf C, N, P and &delta, 13C than soil properties, explaining &gt, 50% of the total variability. C3 plants showed higher leaf C, N, P, K and LWP concentration than C4 plants, whereas C4 plants had higher &delta, 13C than C3 plants. Legumes exhibited higher leaf C, N, K and LWP than nonlegumes, while nonlegumes had higher P and &delta, 13C concentration than legumes. In all the species, significant phylogenetic signals (PS) were detected for C and N and nonsignificant PS for the rest of the leaf traits. In addition, these phylogenetic signals were found lower (K-value &lt, 1), and the maximum K-value was noted for C (K = 0.35). The plants of common garden evolved and adapted themselves for their survival in the arid environment and showed convergent variations in their leaf traits. However, these variations were not phylogenetics-specific. Furthermore, marks of convergence found in leaf traits of the study area were most likely due to the environmental factors.

In order to meet the higher requirements of 5G and iot technologies on the operation, maintenance, management and control of optical communication transmission network in the future, low-cost optical transmission network simulation system is urgently needed to realize the rapid improvement of maintenance staff's operation and maintenance ability. In response to this problem, this paper adopts a hardware functions software implementation method, under the guidance of design ideas such as versatility, uniformity, standardization, authenticity and openness, based on a combination of software and hardware architecture, to develop a low-cost simulation network management system and simulation optical transmission network with complete functions and strong expandability. It can provide support for the intelligent management, application, teaching and training of optical transmission network equipment.

Due to the complex terrain and changeable natural environment, the traditional manual inspection mode with low efficiency and many difficulties has been more and more difficult to meet the needs of lean management of line operation and maintenance. This paper analyzes the characteristics of traditional manual inspection mode, discusses the advantages of introducing UAV for patrol inspection, and finally analyzes the efficiency of UAV manual collaborative inspection. In this paper, the unmanned aerial vehicle (UAV) and manual collaborative inspection mode is proposed to improve the level of optical cable line operation and maintenance.

Aiming at the problem that the upper layer applications of 5G technology and Internet of Things in the future require low blocking rates for optical network service connections, this paper proposes a static wavelength routing assignment method based on improved K shortest path and genetic algorithm. Based on the idea of adding alternative supplementary path to each link of shortest path, a new and improved method of K shortest path is proposed. On this basis, a static routing and wavelength allocation method based on genetic algorithm is proposed to realize the optimal resource allocation of static traffic flow connection establishment request set. Simulation results show that the proposed algorithm can solve the static routing and wavelength assignment problem well.

Plant metabolism determines the structure and dynamics of ecological systems across many different scales. The metabolic theory of ecology quantitatively predicts the scaling of metabolic rate as a function of body size and temperature. However, the role of tissue water content has been neglected even though hydration significantly affects metabolism, and thus ecosystem structure and functioning. Here, we use a general model based on biochemical kinetics to quantify the combined effects of water content, body size and temperature on plant metabolic rates. The model was tested using a comprehensive dataset from 205 species across 10 orders of magnitude in body size from seeds to mature large trees. We show that water content significantly influences mass-specific metabolic rates as predicted by the model. The scaling exponents of whole-plant metabolic rate vs body size numerically converge onto 1.0 after water content is corrected regardless of body size or ontogenetic stage. The model provides novel insights into how water content together with body size and temperature quantitatively influence plant growth and metabolism, community dynamics and ecosystem energetics.

Soil microbes exert critical control over ecosystem functions by regulating organic matter decomposition and nutrient cycling. Diverse methods have been adopted to estimate the soil microbial biomass carbon (Cmic) and nitrogen (Nmic), largely based on fumigation and respiration or biomarkers, such as phospholipids and ATP. Although soil microbial DNA is also an important biomarker, whether this biomarker can be used to estimate Cmic and Nmic at a large scale in arid and semi-arid regions that remains unclear. To explore this, the 124 soil samples collected from 28 different vegetation/microhabitat types in diverse ecosystems (i.e., desert, cropland, typical steppe, meadow steppe and forest) across arid and semi-arid regions in northern China; then, the strong linear relationships were developed among soil microbial DNA concentrations with the Cmic and Nmic contents estimated by the classic chloroform fumigation-extraction (CFE) method. The results showed that the soil microbial DNA concentrations were linearly related to the observed Cmic (r = 0.99) and Nmic (r = 0.97) across the diverse vegetation types, although soil microbial biomass presented an enormous fluctuation. Moreover, based on the above-mentioned coefficients of the linear relationship, it was further inferred that the mean proportions of carbon and nitrogen elements in DNA were 0.99% and 3.70% for Cmic and Nmic, respectively, when assuming the G-C base-pair proportion is 50% in double-stranded DNA. In conclusion, the study proved that soil microbial DNA as a powerful indicator may provide convenient and efficient estimates for Cmic and Nmic in arid and semi-arid systems. Although this method still needs to be further improved and examined at a larger scale, it provides a good addition to the already existing methods to determine microbial biomass.

With the continuous development of optical communication technology, the structure of optical network is becoming more and more complex, and complex network theory can analyze the nature of the actual system. From the angle of self-organizing criticality, the “sand pile” model of intelligent optical network is constructed, the model parameters are designed, and the self-organized critical model of intelligent optical network is established. Finally, the computer algorithm is designed according to the model, and the critical value of the whole network load is solved. The research shows that there is a quantitative relationship between the critical value of network load and the number of the betweenness, which has a certain guiding significance for improving the processing ability of key nodes and optimizing the network security.

Firstly, UAV is proposed to be used in optical cable route inspection, which is the main promotion direction of optical cable route inspection in the future. Then, an improved ant colony algorithm is proposed to solve the path planning problem of UAV, and the feasibility is verified by simulation.

Nutrient resorption plays an important role in plant ecology because it plays a key role in nutrient conservation strategies of plants. However, our current knowledge about the patterns of nutrient resorption among herbaceous species at a global scale is still inadequate. Here, we present a meta-analysis using a global dataset of nitrogen (N) and phosphorus (P) resorption efficiency spanning 521 observations and 248 herbaceous species. This analysis shows that the N resorption efficiency (NRE) and P resorption efficiency (PRE) across all herbaceous plant groups are 54.7 % and 64.5 %, respectively. Across all species, NRE, PRE and N : P resorption ratios (NRE : PRE) vary statistically significantly at a global scale, i.e., NRE, PRE and NRE : PRE increase with increasing latitude but decrease with increasing mean annual temperature (MAT) and mean annual precipitation (MAP). For different functional groups, similar patterns of NRE, PRE and NRE : PRE with respect to latitude, MAT and MAP are observed. Our study are very important complementary to global-scale studies of nutrient resorption and also can inform attempts to model biogeochemical cycling at a global scale.

Nutrient resorption plays an important role in ecology because it has a profound effect on subsequent plant growth. However, our current knowledge about patterns of nutrient resorption, particularly among herbaceous species, at a global scale is still inadequate. Here, we present a meta-analysis using a global dataset of nitrogen (N) and phosphorus (P) resorption efficiency encompassing 227 perennial herbaceous species. This analysis shows that the N and P resorption efficiency (NRE and PRE, respectively), and N:P resorption ratios (NRE:PRE) across all herbaceous plant groups are 59.4%, 67.5%, and 0.89, respectively. Across all species, NRE, PRE, and NRE:PRE, exhibited different patterns along climatic and soil nutrient gradients. i.e., NRE decreases with increasing mean annual precipitation (MAP) and soil N, PRE increases with aridity index (AI) but decreases with MAP and soil P, and NRE:PRE decreases with increasing potential evapotranspiration (PET), AI, and soil N:P. NRE, PRE, and NRE:PRE also differed betweenin functional species group (graminoids vs. forbs). Soil nutrient level was the largest contributor to the total variations in NRE, PRE, and NRE:PRE, while climate and herbaceous types had relatively smaller effects on NRE, PRE, and NRE:PREspecies groups and soil nutrient levels. Collectively, these trends can inform attempts to model biogeochemical cycling at a global scale.

Plant biomass allocation patterns are important to understanding and predicting ecosystem carbon cycles and other important ecological processes. Consequently, many attempts have been made to study these patterns. However, most studies focus on data from species in temperate forests to the neglect of data from desert species adapted to arid conditions. We hypothesize that different life history strategies drive or at least participate in different plant biomass allocation patterns, as, for example, the life history differences between desert ephemeral and shrub species. We tested this hypothesis using field data gathered directly from the entire desert vegetation in Northwestern China. When the data from each of the two species groups are pooled, ephemeral and shrub species manifest different scaling relationships between above- and belowground biomass, unlike the isometric scaling relationships typically reported for forest tree species. The observed scaling relationships are sensitive to water stress and temperature gradients. The scaling exponents numerically decrease with increasing drought stress, and relatively more biomass is allocated to shoot growth in ephemeral species (presumably to rapidly complete their life history). In the case of shrubs, the numerical value of the scaling exponent is insensitive to rainfall, presumably because these species allocate more biomass to root growth to access belowground water. However, the scaling exponent is significantly sensitive to temperature, which also regulates root growth. Moreover, for the two species groups, root-shoot ratios are jointly regulated by precipitation and temperature. The different biomass allocation patterns appear to result from different life histories that maximize either competition among neighboring plants, or escaping damage from drought and low temperatures. These findings show how overall body size and life histories jointly regulate biomass allocation patterns under different extreme conditions and provide insights into estimating the dry carbon content in dryland ecosystems.

Based on the Miller model, we develop an analytical model for the GaN-based metal–ferroelectric–semiconductor field-effect transistors (MFSFETs). In this article, we investigate the effects of ferroelectric film on the maximum drain current, transconductance and memory window of GaN MFSFET at the different hierarchical thickness values of 10, 30, 50, 100, 200 and 300 nm, as well as the polarisation influence. The results indicate that the thickness of ferroelectric film is one of the critical parameters, and certain trade-off should be made for various potential applications. Moreover, the advantages of GaN MFSFET are also investigated in detail, compared with the conventional GaN metal–oxide–semiconductor field-effect transistor under the conditions of similar design. Our results of simulation shows that GaN MFSFETs hold the numerous advantages in electrical characteristics, such as the maximal drain current reaching 69 mA, and the threshold voltage and the subthreshold slope as low as 1.5 V and 58 mV/de...

There is general agreement that competition for resources results in a tradeoff between plant mass, M , and density, but the mathematical form of the resulting thinning relationship and the mechanisms that generate it are debated. Here, we evaluate two complementary models, one based on the space-filling properties of canopy geometry and the other on the metabolic basis of resource use. For densely packed stands, both models predict that density scales as M −3/4 , energy use as M 0 , and total biomass as M 1/4 . Compilation and analysis of data from 183 populations of herbaceous crop species, 473 stands of managed tree plantations, and 13 populations of bamboo gave four major results: ( i ) At low initial planting densities, crops grew at similar rates, did not come into contact, and attained similar mature sizes; ( ii ) at higher initial densities, crops grew until neighboring plants came into contact, growth ceased as a result of competition for limited resources, and a tradeoff between density and size resulted in critical density scaling as M −0.78 , total resource use as M −0.02 , and total biomass as M 0.22 ; ( iii ) these scaling exponents are very close to the predicted values of M −3/4 , M 0 , and M 1/4 , respectively, and significantly different from the exponents suggested by some earlier studies; and ( iv ) our data extend previously documented scaling relationships for trees in natural forests to small herbaceous annual crops. These results provide a quantitative, predictive framework with important implications for the basic and applied plant sciences.

We have simulated the capacitance versus voltage characteristics (C-V) of metal-ferroelectric-gallium nitride (GaN metal-ferroelectric-semiconductor) structures and found useful design rules for improving the devices' performance. The thickness effects of ferroelectric film on the C-V are studied. When the ferroelectric Pb(Zr, Ti)O3 thickness is no more than 100 nm, the GaN metal-ferroelectric-semiconductor structures can approach inversion just under 5?V, which is the generally applied voltage used in semiconductor-based integrated circuits. This marked improvement of C-V behaviors is mainly due to the high dielectric constant and large polarization of the ferroelectric gate oxide. Copyright (C) 2011 John Wiley & Sons, Ltd.

Keyword: DDoS detection; destination IP entropy; unexpected traffic; membership function Abstract. Put forward a DDoS (Distributed Deny of Service) attack detection algorithm based on IP entropy model. Through the establishment of destination IP Entropy model, setting flow and entropy threshold with membership function, checking conditions of DDoS attacks step by step. The experimental results show that the algorithm can accurately detect DDoS attacks, and it can accurately distinguish DDoS flow and unexpected traffic, which has improved the detection rate and detection efficiency.

Simultaneous and accurate measurements of whole-plant instantaneous carbon-use efficiency (ICUE) and annual total carbon-use efficiency (TCUE) are difficult to make, especially for trees. One usually estimates ICUE based on the net photosynthetic rate or the assumed proportional relationship between growth efficiency and ICUE. However, thus far, protocols for easily estimating annual TCUE remain problematic. Here, we present a theoretical framework (based on the metabolic scaling theory) to predict whole-plant annual TCUE by directly measuring instantaneous net photosynthetic and respiratory rates. This framework makes four predictions, which were evaluated empirically using seedlings of nine Picea taxa: (i) the flux rates of CO(2) and energy will scale isometrically as a function of plant size, (ii) whole-plant net and gross photosynthetic rates and the net primary productivity will scale isometrically with respect to total leaf mass, (iii) these scaling relationships will be independent of ambient temperature and humidity fluctuations (as measured within an experimental chamber) regardless of the instantaneous net photosynthetic rate or dark respiratory rate, or overall growth rate and (iv) TCUE will scale isometrically with respect to instantaneous efficiency of carbon use (i.e., the latter can be used to predict the former) across diverse species. These predictions were experimentally verified. We also found that the ranking of the nine taxa based on net photosynthetic rates differed from ranking based on either ICUE or TCUE. In addition, the absolute values of ICUE and TCUE significantly differed among the nine taxa, with both ICUE and temperature-corrected ICUE being highest for Picea abies and lowest for Picea schrenkiana. Nevertheless, the data are consistent with the predictions of our general theoretical framework, which can be used to access annual carbon-use efficiency of different species at the level of an individual plant based on simple, direct measurements. Moreover, we believe that our approach provides a way to cope with the complexities of different ecosystems, provided that sufficient measurements are taken to calibrate our approach to that of the system being studied.

We introduce a theoretical framework that predicts the optimum planting density and maximal yield for an annual crop plant. Two critical parameters determine the trajectory of plant growth and the optimal density, , where canopies of growing plants just come into contact, and competition: ( i ) maximal size at maturity, , which differs among varieties due to artificial selection for different usable products; and ( ii ) intrinsic growth rate, g , which may vary with variety and environmental conditions. The model predicts ( i ) when planting density is less than , all plants of a crop mature at the same maximal size, , and biomass yield per area increases linearly with density; and ( ii ) when planting density is greater than , size at maturity and yield decrease with −4/3 and −1/3 powers of density, respectively. Field data from China show that most annual crops, regardless of variety and life form, exhibit similar scaling relations, with maximal size at maturity, , accounting for most of the variation in optimal density, maximal yield, and energy use per area. Crops provide elegantly simple empirical model systems to study basic processes that determine the performance of plants in agricultural and less managed ecosystems.