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87 results for “leaf growth”
Size- and environment-driven seedling survival and growth are mediated by leaf functional traits
<p><span>Ecologists usually find that plant demography (e.g., survival and growth) changes along with plant size and environmental gradients, which suggests the effects of ontogeny-related processes and abiotic filtering. However, the role of functional traits underlying the plant size- and environment-demography relationships is usually overlooked. By measuring the individual-level leaf traits of more than 2700 seedlings in a temperate forest, we evaluated how seedling functional traits mediated the size- and environment-demography relationships. First, we found leaves were larger for taller seedlings, leaf economics traits were more conservative in taller seedlings and under high light and low elevation conditions. Then, structural equation modeling showed that a higher survival probability for taller seedlings was indirectly driven by their larger leaf area. Although taller seedlings had lower growth rates, larger and more resource-conservative leaves could promote the growth rate of these tall seedlings. Environmental variables did not appear to influence seedling survival and growth directly but did influence growth indirectly by mediating trait variation. Finally, species-specific variation in traits along with size and environments was associated with the species-specific variation in seedling survival and growth. Our study suggests that, not only plant ontogeny- and environment-related ecological processes, functional traits are also important intermediary agents underlying the usually observed plant size- and environment-demography relationships.</span></p>
Data from: Roads increase population growth rates of a native leaf-cutter ant in Neotropical savannahs
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Size- and environment-driven seedling survival and growth are mediated by leaf functional traits
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Tree_seedling_survival_growth_leaf_traits_in_disturbed_conditions
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Are leaf, stem and hydraulic traits good predictors of individual tree growth? (FUN2FUN project)
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The community-level scaling relationship between leaf nitrogen and phosphorus changes with plant growth, climate and nutrient limitation
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Percent carbon and nitrogen in leaf tissue:Specialization, maintenance of diversity and ecosystem consequences of growth defense trade-offs in a model system, the hyper-diverse willow communities of Cedar Creek
Cedar Creek includes a diversity of habitats, which support an astonishing number of species (15) from a single evolutionary lineage: the willow family (Salicaceae). The physiological tolerances and abiotic mechanisms that maintain natural diversity in this hyper-diverse system are beginning to be understood; the role of biotic interactions, however, remains a major gap in understanding. We hypothesize that insect herbivory plays a critical role in niche partitioning, providing an important explanation for high willow diversity. Using a replicated series of common gardens and insect herbivore manipulations in resource rich and resource poor habitats, we are testing for evolved trade-offs between defense investment and growth rate. We expect specialized plant syndromes to emerge along the continuum from ???herbivore escape??? via fast growth in high resource environments to ???anti-herbivore protection??? via heavy investment in defense in low resource environments. Evolved growth/defense strategies that promote diversity are also likely to have ecosystem consequences due to foliar chemical influences on decomposition and the composition and diversity of the insect communities they support. The proposed research takes advantage of natural diversity, providing an important model system at Cedar Creek.
High-resolution time series of leaf length and leaf thickness of strawberry and tomato measured in a growth chamber
<p>This dataset captures leaf thickness and leaf length of two strawberry plants and one tomato seeding. Leaf thickness measurements are only available of the strawberry plants. Additional data included light intensity data, soil water content (of one plant), relative humidity and temperature data. All sensors were read every second over a period of two weeks.</p>
Data from: In silico study of the role of cell growth factors in photosynthesis using a virtual leaf tissue generator coupled to a microscale photosynthesis gas exchange model
Computational tools that allow in silico analysis of the role of cell growth and division on photosynthesis are scarce. We present a freely available tool that combines a virtual leaf tissue generator and a two-dimensional microscale model of gas transport during C3 photosynthesis. A total of 270 mesophyll geometries were generated with varying degree of growth anisotropy, growth extent and extent of schizogenous airspace formation in the palisade mesophyll. The anatomical properties of the virtual leaf tissue and microscopic cross sections of actual leaf tissue of tomato (Solanum lycopersicum L.) were statistically compared. Model equations for transport of CO2 in the liquid phase of the leaf tissue were discretized over the geometries. The virtual leaf tissue generator produced a leaf anatomy of tomato that was statistically similar to real tomato leaf tissue. The response of photosynthesis to intercellular CO2 predicted by a model that used the virtual leaf tissue geometry compared well with measured values. The results indicate that the light-saturated rate of photosynthesis was influenced by interactive effects of extent and directionality of cell growth and degree of airspace formation through the exposed surface of mesophyll per leaf area. The tool could be used further in investigations of improving photosynthesis and gas exchange in relation to cell growth and leaf anatomy.
Data from: Improving predictions of tropical tree survival and growth by incorporating measurements of whole leaf allocation
<p><span><span><span><span><span><span><span><span><span><span><span>1. Individual-level demographic outcomes should be predictable upon the basis of traits. However, linking traits to tree performance has proven challenging likely due to a failure to consider physiological traits (i.e., hard-traits) and the failure to integrate organ-level and whole plant-level trait information. </span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span>2. Here, we modeled the survival rate and relative growth rate of trees while considering crown allocation, hard-traits, and local-scale biotic interactions, and compared these models to more traditional trait-based models of tree performance. </span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span>3. We found that an integrative trait, total tree-level photosynthetic mass (estimated by multiplying specific leaf area and crown area) results in superior models of tree survival and growth. These models had a lower AIC than those including the effect of initial tree size or any other combination of the traits considered. Survival rates were positively related to higher values of crown area and photosynthetic mass, while relative growth rates were negatively related to the photosynthetic mass. Relative growth rates were negatively related to a neighbourhood crowding index. Furthermore, none of the hard-traits used in this study provided an improvement in tree performance models. </span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span>4. <i>Synthesis</i>. Overall, our results highlight that models of tree performance can be greatly improved by including crown area information to generate a better understanding of plant responses to their environment. Additionally, the role of the hard-traits in improving models of tree performance is likely dependent upon the level of stress (e.g. drought stress), micro-environmental conditions, or short-term climatic variations that a particular forest experiences.</span></span></span></span></span></span></span></span></span></span></span></p>
Data from: Altered leaf elemental composition with climate change is linked to reductions in photosynthesis, growth and survival in a semiarid shrubland
Climate change will increase heat and drought stress in many dryland areas, which could reduce soil nutrient availability for plants and aggravate nutrient limitation of primary productivity. Any negative impacts of climate change on foliar nutrient contents would be expected to negatively affect the photosynthetic capacity, water use efficiency and overall fitness of dryland vegetation. We conducted a four-year manipulative experiment using open top chambers and rainout shelters to assess the impacts of warming (~2ºC, W), rainfall reduction (~30%, RR) and their combination (W+RR) on the nutrient status and ecophysiological performance of six native shrub species of contrasting phylogeny in a semiarid ecosystem. Leaf nutrient status and gas exchange were assessed yearly, whereas biomass production and survival were measured at the end of the study. Warming (W and W+RR) advanced shoot growth phenology and reduced foliar macro- (N, P, K) and micronutrient (Cu, Fe, Zn) concentrations (by 8-18% and 14-56%, respectively), net photosynthetic rate (32%), aboveground biomass production (28-39%) and survival (23-46%). Decreased photosynthesis and growth in W and W+RR plants was primarily linked to enhanced nutritional constraints on carbon fixation. Poor leaf nutrient status in W and W+RR plants partly decoupled carbon assimilation from water flux and led to drastic reductions in water use efficiency (WUEi; ~41%) across species. The RR treatment moderately decreased foliar macro- and micronutrients (6-17%, except for Zn) and biomass production (22%). The interactive impacts of warming and rainfall reduction (W+RR treatment) on plant performance were generally smaller than expected from additive single‐factor effects. Synthesis: Large decreases in plant nutrient pool size and productivity combined with increased mortality during hotter droughts will reduce vegetation cover and nutrient retention capacity, thereby disrupting biogeochemical processes and accelerating dryland degradation with impending climate change. Increased macro- and micronutrient co-limitation of photosynthesis with forecasted climate change conditions may offset any gains in WUEi and productivity derived from anthropogenic CO2 elevation, thereby increasing dryland vegetation vulnerability to drought stress in a warmer and drier climate. The generalized reduction in leaf nutrient contents with warming compromises plant nutritional quality for herbivores, with potential cascading negative effects across trophic levels.
Climate warming benefits plant growth but net carbon uptake: Simulation of Alaska tundra and needle leaf forest using LPJ-GUESS
<p><span>Climate warming has important effects on Arctic vegetation, but the roles of Arctic vegetation as a carbon sink or source in the future remain largely unknown. In this study, we selected the tundra and needle leaf forest areas in Alaska to examine vegetation growth and carbon exchange using the LPJ-GUESS model. We used flux site data to verify the accuracy of GPP and NEE simulated with climate variables, then simulated GPP and NEE from 1992 to 2014 and GPP and NEE from 2020 to 2100 under different climate scenarios, and compared the GPP and LAI simulated by the model with those under future scenarios. </span>We used LPJ-GUESS model to explore the importance of climate variables on GPP and NEE.</p>
Improving intra- and inter-annual GPP predictions by using individual-tree inventories and leaf growth dynamics
<p>Carbon sequestration is a key ecosystem service provided by forests. Inventory data based on individual trees are considered to be the most accurate method for estimating forest productivity. However, estimations of forest photosynthesis itself from inventory data remains understudied, particularly when considering the growth and development of individual trees under the background of global change. Here, we used the leaf growth process with phenology and non-structural carbohydrates (NSC) storage to revise an individual-tree based carbon model, FORCCHN. This model couples leaf development and biomass to quantify gross primary productivity (GPP) in the forests, where growth is decoupled from photosynthesis in daily step. The model was initialized with inventory-based forest data rather than the more widely used satellite-based data. We tested the model against measured aboveground woody biomass, growth of leaf biomass, daily gross ecosystem exchange (GEE), and yearly GEE at five representative forest sites in the Northern Hemisphere. We also compared the results from the original model and the revised model at five forest sites. Including leaf growth dynamics and inventory-based initialization improved the predicted performance (r2) of GPP by an average of 33%. Synthesis and applications. Our results suggest that the appropriate vegetation data sources (i.e. inventory or satellite selection) and the effective predictions of the growth process should be considered when developing future carbon cycle models and forest carbon estimation options. Applying and improving such carbon models to evaluate carbon sequestration is an important part of forest carbon sink management.</p>
Census data of growth, mortality and size stage transitions of nests of leaf-cutting ant species before and after fires
<p>We hypothesized that fires will affect more the species that build external, easily flammable thatch mounds with superficial fungal gardens (<i>Acromyrmex lobicornis</i>) than colonies that build subterranean nests in the less-flammable bare-ground (<i>Acromyrmex striatus</i>). We use a stochastic matrix demographic model parameterized with 4 years of data in pre and post fire scenarios. This data set contain all the census data which from we build the matrix models.</p>
Data from: In silico study of the role of cell growth factors in photosynthesis using a virtual leaf tissue generator coupled to a microscale photosynthesis gas exchange model
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Data from: Improving predictions of tropical tree survival and growth by incorporating measurements of whole leaf allocation
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Data from: Altered leaf elemental composition with climate change is linked to reductions in photosynthesis, growth and survival in a semiarid shrubland
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Census data of growth, mortality and size stage transitions of nests of leaf-cutting ant species before and after fires
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Climate warming benefits plant growth but net carbon uptake: Simulation of Alaska tundra and needle leaf forest using LPJ-GUESS
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Improving intra- and inter-annual GPP predictions by using individual-tree inventories and leaf growth dynamics
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.