Plant trait networks reveal adaptation strategies in the drylands of China

[1]  Nadejda A. Soudzilovskaia,et al.  The global spectrum of plant form and function: enhanced species-level trait dataset , 2022, Scientific Data.

[2]  K. Niklas,et al.  Leaf and ecosystem water use efficiencies differ in their global-scale patterns and drivers , 2022, Agricultural and Forest Meteorology.

[3]  L. Sack,et al.  Leaf trait network architecture shifts with species-richness and climate across forests at continental scale. , 2022, Ecology letters.

[4]  Laura J. Pollock,et al.  The diversity of biotic interactions complements functional and phylogenetic facets of biodiversity , 2022, Current Biology.

[5]  A. Guo,et al.  Phylogenetic independence in the variations in leaf functional traits among different plant life forms in an arid environment. , 2022, Journal of plant physiology.

[6]  Ying Li,et al.  Differential adaptation of lianas and trees in wet and dry forests revealed by trait correlation networks , 2022, Ecological Indicators.

[7]  Ying Li,et al.  Leaf Trait Networks Based on Global Data: Representing Variation and Adaptation in Plants , 2021, Frontiers in Plant Science.

[8]  Q. Guo,et al.  Impact of climate change on plant species richness across drylands in China: From past to present and into the future , 2021, Ecological Indicators.

[9]  K. Niklas,et al.  Variation in plant carbon, nitrogen, and phosphorus contents across the drylands of China , 2021, Functional Ecology.

[10]  C. Peng,et al.  Quantifying Leaf Trait Covariations and Their Relationships with Plant Adaptation Strategies along an Aridity Gradient , 2021, Biology.

[11]  B. Schmid,et al.  Aridity-driven shift in biodiversity–soil multifunctionality relationships , 2021, Nature Communications.

[12]  Ü. Niinemets,et al.  Global patterns of leaf construction traits and their covariation along climate and soil environmental gradients. , 2021, The New phytologist.

[13]  F. Dijkstra,et al.  Stability of elemental content correlates with plant resistance to soil impoverishment , 2021, Plant and Soil.

[14]  C. Peng,et al.  Leaf Trait Covariation and Its Controls: A Quantitative Data Analysis Along a Subtropical Elevation Gradient , 2021, Journal of Geophysical Research: Biogeosciences.

[15]  P. Zhao,et al.  Leaf stoichiometry is synergistically-driven by climate, site, soil characteristics and phylogeny in karst areas, Southwest China , 2021, Biogeochemistry.

[16]  W. Han,et al.  Patterns of nitrogen and phosphorus stoichiometry among leaf, stem and root of desert plants and responses to climate and soil factors in Xinjiang, China , 2021 .

[17]  Yuan Sun,et al.  Effects of Water and Energy on Plant Diversity along the Aridity Gradient across Dryland in China , 2021, Plants.

[18]  D. J. Ruiz,et al.  A comprehensive quantification of global nitrous oxide sources and sinks , 2020, Nature.

[19]  Jianming Deng,et al.  Convergent Variations in the Leaf Traits of Desert Plants , 2020, Plants.

[20]  S. Niu,et al.  Plant Trait Networks: Improved Resolution of the Dimensionality of Adaptation. , 2020, Trends in ecology & evolution.

[21]  I. Prentice,et al.  Components of leaf-trait variation along environmental gradients. , 2020, The New phytologist.

[22]  R. Solé,et al.  Global ecosystem thresholds driven by aridity , 2020, Science.

[23]  Nadejda A. Soudzilovskaia,et al.  Robustness of trait connections across environmental gradients and growth forms , 2019, Global Ecology and Biogeography.

[24]  Bruno H. P. Rosado,et al.  Multidimensional ecological analyses demonstrate how interactions between functional traits shape fitness and life history strategies , 2019, Journal of Ecology.

[25]  K. Niklas,et al.  Life history strategies drive size‐dependent biomass allocation patterns of dryland ephemerals and shrubs , 2019, Ecosphere.

[26]  Jianwu Tang,et al.  Foliar phosphorus fractions reveal how tropical plants maintain photosynthetic rates despite low soil phosphorus availability , 2019, Functional Ecology.

[27]  B. Blasius,et al.  Trait correlation network analysis identifies biomass allocation traits and stem specific length as hub traits in herbaceous perennial plants , 2018, Journal of Ecology.

[28]  Anne D. Bjorkman,et al.  Global trait–environment relationships of plant communities , 2018, Nature Ecology & Evolution.

[29]  C. Peng,et al.  Quantifying leaf-trait covariation and its controls across climates and biomes. , 2018, The New phytologist.

[30]  Zhiheng Wang,et al.  Effects of contemporary environment and Quaternary climate change on drylands plant diversity differ between growth forms , 2018, Ecography.

[31]  Jingyun Fang,et al.  Patterns of plant carbon, nitrogen, and phosphorus concentration in relation to productivity in China’s terrestrial ecosystems , 2018, Proceedings of the National Academy of Sciences.

[32]  Ü. Niinemets,et al.  Physiological and structural tradeoffs underlying the leaf economics spectrum. , 2017, The New phytologist.

[33]  P. Bellingham,et al.  Root traits are multidimensional: specific root length is independent from root tissue density and the plant economic spectrum , 2016 .

[34]  Benjamin L Turner,et al.  Variation in wood nutrients along a tropical soil fertility gradient. , 2016, The New phytologist.

[35]  Hendrik Poorter,et al.  Leaf Mass per Area (LMA) and Its Relationship with Leaf Structure and Anatomy in 34 Mediterranean Woody Species along a Water Availability Gradient , 2016, PloS one.

[36]  Jianping Huang,et al.  Accelerated dryland expansion under climate change , 2016 .

[37]  Ian J. Wright,et al.  Global effects of soil and climate on leaf photosynthetic traits and rates , 2015 .

[38]  Atul K. Jain,et al.  The dominant role of semi-arid ecosystems in the trend and variability of the land CO2 sink , 2015, Science.

[39]  Xin‐rong Li,et al.  Nutrient levels within leaves, stems, and roots of the xeric species Reaumuria soongorica in relation to geographical, climatic, and soil conditions , 2015, Ecology and evolution.

[40]  Christophe Pélabon,et al.  Integrated phenotypes: understanding trait covariation in plants and animals , 2014, Philosophical Transactions of the Royal Society B: Biological Sciences.

[41]  P. Reich.  The world‐wide ‘fast–slow’ plant economics spectrum: a traits manifesto , 2014 .

[42]  Franz Rebele.  Differential succession towards woodland along a nutrient gradient , 2013 .

[43]  D. Hertel,et al.  Management alters interspecific leaf trait relationships and trait‐based species rankings in permanent meadows , 2013 .

[44]  Kelly K. Caylor,et al.  Dryland ecohydrology and climate change: critical issues and technical advances , 2012 .

[45]  Peter B. Reich,et al.  Global quantification of contrasting leaf life span strategies for deciduous and evergreen species in response to environmental conditions , 2012 .

[46]  B. Kloareg,et al.  Evolution and diversity of plant cell walls: from algae to flowering plants. , 2011, Annual review of plant biology.

[47]  F. Schreiber,et al.  Centrality Analysis Methods for Biological Networks and Their Application to Gene Regulatory Networks , 2008, Gene regulation and systems biology.

[48]  J. Liu,et al.  Trade-Offs between the Metabolic Rate and Population Density of Plants , 2008, PloS one.

[49]  C. Violle,et al.  Let the concept of trait be functional , 2007 .

[50]  Eric Garnier,et al.  Components of nutrient residence time and the leaf economics spectrum in species from Mediterranean old‐fields differing in successional status , 2007 .

[51]  Jing Liu,et al.  Plant mass–density relationship along a moisture gradient in north‐west China , 2006 .

[52]  E. Garnier,et al.  A structural equation model to integrate changes in functional strategies during old-field succession. , 2006, Ecology.

[53]  M. Lechowicz,et al.  Alternative Designs and the Evolution of Functional Diversity , 2005, The American Naturalist.

[54]  William G. Lee,et al.  Modulation of leaf economic traits and trait relationships by climate , 2005 .

[55]  H. Tian,et al.  Pools and distributions of soil phosphorus in China , 2005 .

[56]  Sean C. Thomas,et al.  The worldwide leaf economics spectrum , 2004, Nature.

[57]  Z. Oltvai,et al.  Network biology: understanding the cell's functional organization , 2004, Nature Reviews Genetics.

[58]  David D. Ackerly,et al.  FUNCTIONAL STRATEGIES OF CHAPARRAL SHRUBS IN RELATION TO SEASONAL WATER DEFICIT AND DISTURBANCE , 2004 .

[59]  U. Alon.  Biological Networks: The Tinkerer as an Engineer , 2003, Science.

[60]  A. Barabasi,et al.  Hierarchical Organization of Modularity in Metabolic Networks , 2002, Science.

[61]  Hod Lipson,et al.  ON THE ORIGIN OF MODULAR VARIATION , 2002, Evolution; international journal of organic evolution.

[62]  H. Heilmeier,et al.  Internal leaf anatomy and photosynthetic resource-use efficiency: interspecific and intraspecific comparisons. , 2001, Tree physiology.

[63]  H. Mooney,et al.  Estimation of tissue construction cost from heat of combustion and organic nitrogen content , 1987 .

[64]  U. Niinemets.  Is there a species spectrum within the world-wide leaf economics spectrum? Major variations in leaf functional traits in the Mediterranean sclerophyll Quercus ilex. , 2015, The New phytologist.

[65]  P. Reich,et al.  Biomass allocation to leaves, stems and roots: meta-analyses of interspecific variation and environmental control. , 2012, The New phytologist.

[66]  H. Poorter,et al.  INTERSPECIFIC VARIATION IN RELATIVE GROWTH RATE : ON ECOLOGICAL CAUSES AND PHYSIOLOGICAL CONSEQUENCES , 2003 .

[67]  H. Poorter,et al.  The fate of acquired carbon in plants: chemical composition and construction costs , 1997 .