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opencc-zeroDec 2018View details →

Data from: Functional diversity promotes phytoplankton resource use efficiency

1.Understanding the relationship between biodiversity and ecosystem functioning (BEF) is a central topic in ecology. Multi‐traits based functional diversity has been proposed to improve mechanistic understanding of the BEF relationship; however, how trait‐based functional diversity affects ecosystem functioning and processes has rarely been addressed in aquatic ecosystems. 2.Here, we examined the causal relationships between three phytoplankton functional diversity indices (FAD2, FDc, FRic) and Shannon diversity index versus resource use efficiency for nitrogen (RUEN), phosphorus (RUEP), and silicate (RUESi), with monthly long‐term datasets from the marine (Western English Channel, 2000 ‐ 2014) and freshwater (Lake Kasumigaura, 1984 ‐ 2012) ecosystems. 3.We employed Convergent Cross Mapping (CCM), a novel method developed for identifying causality for nonlinear dynamical systems; this is in contrast to linear approaches that cannot distinguish causality from correlation. CCM found that FDc is the most robust functional diversity index among the selected functional diversity indices (FAD2, FDc, FRic) in predicting phytoplankton resource use efficiency and exhibited a much stronger causal effect than the Shannon index. 4.Furthermore, scenario exploration analysis indicates that most causal effects from phytoplankton diversity indices on resource use efficiency (RUEN, RUEP, and RUESi) are on average positive, and FDc exhibited the most consistent positive causal effects on phytoplankton resource efficiency in both marine and freshwater ecosystems. Thus, increasing FDc can enhance phytoplankton resource use efficiency in aquatic ecosystems. 5.Synthesis. Our results show significant causal effects of functional diversity on phytoplankton resource use efficiency in both marine and freshwater ecosystems. Among all selected functional diversity indices, FDc is the most robust functional diversity index in promoting phytoplankton resource efficiency. Our study provides empirical evidences in natural aquatic systems that trait‐based functional diversity represents better species niche partitioning than the Shannon index and thereafter enhances resource use efficiency. This finding can improve our understanding on trophic transfer and nutrient cycling in aquatic ecosystems.

opencc-zeroDec 2016View details →

Data from: How a generalist bee achieves high efficiency of pollen collection on diverse floral resources

Bees foraging for floral rewards are one of our most thoroughly studied examples of generalist foraging ecology. Generalist bees rely considerably on instrumental (associative) learning to acquire routines that allow them to collect nectar efficiently from diverse plant species. Although such bees must also collect pollen from diverse species, few studies have examined if and how high efficiency is achieved. We characterized how generalist bumble bees (Bombus impatiens) foraged effectively for pollen from diverse floral resources, by manipulating the presence of pollen and anther cues, in a series of experiments using pollen-bearing live flowers, flowers of a sterile pollenless horticultural hybrid, and artificial flowers. We show that generalist bumble bees exhibit flexible and effective pollen collection by switching between 2 routines: "scrabbling" when pollen is abundant and "sonicating" when pollen is scarce. Efficient switching between these behaviors is regulated by the interplay of 2 ubiquitous floral cues: chemical anther cues stimulating pollen collection behavior and mechanical pollen cues suppressing sonication (and eliciting scrabbling). Flexible pollen collection behavior is functional: When pollen on anthers was scarce, bees collected it at a greater rate by sonicating than scrabbling. This mechanism of behavioral flexibility likely allows generalist bees to handle diverse anther morphologies efficiently and may have facilitated the recurrent evolution of plant species that conceal pollen rewards via pored floral morphology. Whereas effective nectar foraging relies heavily on associative learning of unique routines for each flower type, a weighing of 2 types of cues regulates the flexible pollen collection mechanism we describe.

zenodo32/100

Data of the Paper: Stateful Depletion and Scheduling of Containers on Cloud Nodes for Efficient Resource Usage

This is the online artifact containing the code, data and evaluation log of the experiment performed for the research paper accepted at IEEE QRS 2022 with the title:  Stateful Depletion and Scheduling of Containers on Cloud Nodes for Efficient Resource Usage Abstract: Container scheduling is a fundamental part of today’s service and cloud-based applications. Schedulers operate at different levels depending on how much control the system developers have. On the one hand, container orchestration managers such as Google Kubernetes manage the scheduling of containers to different nodes. On the other hand, serverless managers, such as Google Autopilot, take care of the underlying infrastructure automatically, and developers do not need to manage the nodes. However, when it comes to container depletion, i.e., removing the assigned cloud resources to an idle container, current scheduling technologies have limitations. In this paper, we propose our approach to managing cloud resource usage when containers are idle efficiently. For this purpose, we deplete idle containers statefully, i.e., propose a novel manager that monitors idle containers, saves their state, and efficiently depletes them. This manager reconstructs a depleted container using the saved state when reconstruction is needed. In our approach, we suggest an Infrastructure as Code component to automate the creation of new nodes if a depleted container cannot be scheduled on the same node, e.g., because of being overloaded. We provide an analytical model for the stateful depletion of containers and their rescheduling and empirically evaluate the accuracy of our model. For this purpose, we ran an experiment on a private cloud infrastructure and Google Cloud Platform. Our model has a low error rate of 4.28% averaged over public and private clouds.

opencc-by-4.0Dec 2022View details →

zenodo32/100

Wyniki zawarte w Energy-Efficient OFDM Radio Resource Allocation Optimization With Computational Awareness: A Survey

This resource contains the results included in Energy-Efficient OFDM Radio Resource Allocation Optimization With Computational Awareness: A Survey

opencc-by-4.0Aug 2022View details →

publicApr 2019View details →

Data from: Functional diversity promotes phytoplankton resource use efficiency

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publicFeb 2016View details →

Data from: Convergence in resource use efficiency across trees with differing hydraulic strategies in response to ecosystem precipitation manipulation

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publicJun 2016View details →

Data from: Rehabilitating the cyanobacteria – niche partitioning, resource use efficiency, and phytoplankton community structure during diazotrophic cyanobacterial blooms

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publicMar 2017View details →

Data from: How a generalist bee achieves high efficiency of pollen collection on diverse floral resources

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publicAug 2020View details →

Data from RACE: Resource Aware Cost-Efficient Scheduler for Cloud Fog Environment

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publicSep 2018View details →

Data from: Increase in light interception cost and metabolic mass component of leaves are coupled for efficient resource use in the high altitude vegetation

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opencc-by-4.0Jun 2020View details →

Data of paper "Predicting Transverse Mixing Efficiency Downstream of a River Confluence by Pouchoulin et al. (Water Resources Research)"

Here is the dataset of velocity (ADCP) & conductivity (CTD) masured over the three surveys and at each cross-section of the Soane Rhone confluence at Lyon (France), as presented by "Pouchoulin et al. Predicting Transverse Mixing Efficiency Downstream of a River Confluence, Water Ressources Research"

opencc-zeroJan 2021View details →

Data from: Intraspecific variations in leaf traits, productivity, and resource use efficiencies in the dominant species of subalpine evergreen coniferous and deciduous broad-leaved forests along the altitudinal gradient

Many studies have reported intraspecific variations in leaf functional traits, but their contribution to plant performance and ecosystem function are poorly understood. We studied altitudinal gradients of intraspecific variations in leaf traits, productivity, and resource use efficiency in the dominant species of subalpine evergreen coniferous and deciduous broad-leaved forests in Japan. We addressed three hypotheses, which are exclusive to each other. 1) Leaf traits vary along the leaf economics spectrum (LES). Plants that grow at lower and higher altitudes have fast- and slow-return strategies, respectively, which improve productivity or resource use efficiency in the respective habitat. 2) Leaf trait variations are not consistent with the LES, but they contribute to improving productivity or resource use efficiency in the respective habitat. 3) Leaf trait variations do not contribute to improving productivity or resource use efficiency at higher altitudes. On the studied mountain range, Fagus crenata, a deciduous broad-leaved tree, and Abies mariesii, an evergreen conifer, are the dominant species at lower and higher altitudes, respectively. In F. crenata, leaf mass per area (LMA) and nitrogen concentrations were higher at higher altitudes. The net assimilation rate and light use efficiency during the growing season were greater at higher altitudes, which compensated for the shorter growing season in terms of annual productivity. In A. mariesii, the LMA was lower and the leaf life span was unchanged at higher altitudes. Productivity and resource use efficiency decreased with altitude. We conclude that F. crenata improves its productivity and resource use efficiency at higher altitudes by altering its leaf functional traits (Hypothesis 2), whereas alterations to leaf traits in A. mariesii are not associated with any improvement at higher altitudes (Hypothesis 3), which may result from the negative impact of environmental stress. Hence, the ecological significance of altitude to leaf trait variations depends on species and environment.

opencc-zeroDec 2017View details →

Data from: Metaecosystem dynamics of marine phytoplankton alters resource use efficiency along stoichiometric gradients

Metaecosystem theory addresses the link between local (within habitats) and regional (between habitats) dynamics by simultaneously analyzing spatial community ecology and abiotic matter flow. Here, we experimentally address how spatial resource gradients and connectivity affect resource use efficiency (RUE) and stoichiometry in marine phytoplankton at local and regional scales. We created gradostat metaecosystems consisting of five linearly interconnected patches, which either were arranged in countercurrent gradients of nitrogen (N) and phosphorus (P) supply or with a uniform spatial distribution of nutrients, and which had either low or high connectivity. Gradient metaecosystems were characterized by higher remaining N and P concentrations (and N:P ratios) than uniform ones, a difference reduced by higher connectivity. The position of the patch in the gradient strongly constrained elemental stoichiometry, local biovolume production and RUE. Expectedly, algal C:N, biovolume and N-specific RUE decreased towards the N-rich end of gradient metaecosystem, whereas the opposite was observed for most of the gradient for C:P, N:P and P-specific RUE. However, at highest N:P supply, unexpectedly low C:P, N:P, and P-specific RUE values were found, indicating that the low availability of P inhibited efficient use of N and biovolume production. Consequently, gradient metaecosystems had lower overall biovolume at the regional scale, but higher dissimilarity in species composition. Thus, the performance of phytoplankton in metaecosystems strongly depended on the stoichiometry of resource supply and spatial connectivity between patches.

opencc-zeroDec 2015View details →

Data from: Fruiting strategies of perennial plants: a resource budget model to couple mast seeding to pollination efficiency and resource allocation strategies

Masting, a breeding strategy common in perennial plants, is defined by seed production that is highly variable over years and synchronized at the population level. Resource budget models (RBMs) proposed that masting relies on two processes: (i) the depletion of plant reserves following high fruiting levels, which leads to marked temporal fluctuations in fruiting; and (ii) outcross pollination that synchronizes seed crops among neighboring trees. We revisited the RBM approach to examine the extent to which masting could be impacted by the degree of pollination efficiency, by taking into account various logistic relationships between pollination success and pollen availability. To link masting to other reproductive traits, we split the reserve depletion coefficient into three biological parameters related to resource allocation strategies for flowering and fruiting. While outcross pollination is considered to be the key mechanism that synchronizes fruiting in RBMs, our model counterintuitively showed that intense masting should arise under low-efficiency pollination. When pollination is very efficient, medium-level masting may occur, provided that the costs of female flowering (relative to pollen production) and of fruiting (maximum fruit set and fruit size) are both very high. Our work highlights the powerful framework of RBMs, which include explicit biological parameters, to link fruiting dynamics to various reproductive traits and to provide new insights into the reproductive strategies of perennial plants.

opencc-by-4.0Oct 2023View details →

IMPROVING THE MECHANISM OF INCREASING THE SYNERGIC EFFICIENCY OF THE USE OF LAND AND WATER RESOURCES IN AGRICULTURE

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opencc-by-4.0Dec 2023View details →

EFFECTIVE USE OF ENERGY RESOURCES AND SAVING THEM IS THE GUARANTEE OF ECONOMIC EFFICIENCY OF INDUSTRIAL ENTERPRISES.

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opencc-by-4.0May 2024View details →

CONSUMPTION MANAGEMENT OF FUEL AND ENERGY RESOURCES - THE BASIS OF ENERGY EFFICIENCY

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publicFeb 2016View details →

Data from: Fruiting strategies of perennial plants: a resource budget model to couple mast seeding to pollination efficiency and resource allocation strategies

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