A multifunctional paper-based supercapacitor with excellent temperature adaptability, plasticity, tensile strength, self-healing, and high thermoelectric effects

Journal of Materials Chemistry A, Journal Year: 2023, Volume and Issue: 11(9), P. 4769 - 4779

Published: Jan. 1, 2023

In recent years, the development of multi-functional supercapacitors with high flexibility and strong environmental adaptability has gradually become a focus attention.

Language: Английский

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PhenoCam: An evolving, open-source tool to study the temporal and spatial variability of ecosystem-scale phenology

Agricultural and Forest Meteorology, Journal Year: 2023, Volume and Issue: 342, P. 109751 - 109751

Published: Oct. 14, 2023

Language: Английский

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Plant phenology shifts under climate warming: a systematic review of recent scientific literature

Environmental Monitoring and Assessment, Journal Year: 2023, Volume and Issue: 196(1)

Published: Dec. 14, 2023

Language: Английский

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Impact of revegetation and agricultural intensification on water storage variation in the Yellow River Basin

Journal of Hydrology, Journal Year: 2024, Volume and Issue: 635, P. 131218 - 131218

Published: April 18, 2024

Language: Английский

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Modelling the seasonal dynamics of Aedes albopictus populations using a spatio-temporal stacked machine learning model

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 30, 2025

Various modelling techniques are available to understand the temporal and spatial variations of phenology species. Scientists often rely on correlative models, which establish a statistical relationship between response variable (such as species abundance or presence-absence) set predominantly abiotic covariates. The choice modeling approach, i.e., algorithm, is itself significant source variability, different algorithms applied same dataset can yield disparate outcomes. This inter-model variability has led adoption ensemble techniques, among stacked generalisation, recently demonstrated its capacity produce robust results. Stacked incorporates predictions from multiple base learners models inputs for meta-learner. meta-learner, in turn, assimilates these generates final prediction by combining information all learners. In our study, we utilized published documenting egg observations Aedes albopictus collected using ovitraps. environmental predictors forecast weekly median number mosquito eggs machine learning model. approach enabled us (i) unearth seasonal egg-laying dynamics Ae. 12 years; (ii) generate spatio-temporal explicit forecasts regions not covered conventional monitoring initiatives. Our work establishes methodological foundation forecasting albopictus, offering flexible framework that be tailored meet specific public health needs related this

Language: Английский

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Seasonal dynamics of detritus flows and decomposition across ecosystem boundaries

Current Biology, Journal Year: 2025, Volume and Issue: unknown

Published: April 1, 2025

Material fluxes are ubiquitous in nature within and across ecosystems, connecting habitats with vastly different characteristics, like forests to rivers lakes.1,2,3 Although individual their cascading effects well known,4,5,6 very few studies address the intra-annual phenology of ecosystem processes, despite pronounced seasonality fluxes. Here, we empirically quantified resolved recalcitrant labile types leaf litter temperate riparian streams a year, representing one most emblematic examples seasonal systems. We variation inputs from terrestrial plants forest floors estimated aquatic decomposition rates year at 6-week intervals. Our data show that autumn pulse is complemented by smaller magnitude but more constant-through-the-year lateral flows stream ecosystems. Decomposition fluctuated seasonally, on phenology, generally higher summer, remained largely constant. Microorganisms were main contributors process both streams. Overall, our work highlights asynchronous seasonally variable changes between detritus initial synchronized availability suggests dominating presence buffers responses concentrated temporal distribution resources.7,8 Investigating such ecological processes borders fine resolutions imperative understand complex system context species' shifts phenologies resource quality.9,10,11.

Language: Английский

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Advancements in Monitoring Tree Phenology Under Global Change: A Comprehensive Review

Forests, Journal Year: 2025, Volume and Issue: 16(5), P. 771 - 771

Published: April 30, 2025

This comprehensive review explores recent advancements in monitoring tree phenology the context of global change. As climate change continues to alter ecosystems worldwide, understanding has become increasingly crucial for predicting ecological responses and informing conservation strategies. examines traditional ground-based observation methods, highlights their strengths limitations, discusses integration modern technologies such as remote sensing, digital cameras, sensor networks. Special attention is given role citizen science initiatives expanding phenological data collection. also addresses challenges posed by monitoring, including shifting patterns complexities. Furthermore, it applications research, ecosystem management, biodiversity conservation. The paper concludes identifying future directions emerging that promise revolutionize emphasizing need interdisciplinary collaboration standardized methodologies enhance our a rapidly changing world.

Language: Английский

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Poleward shifts in the maximum of spring phenological responsiveness of Ginkgo biloba to temperature in China

New Phytologist, Journal Year: 2023, Volume and Issue: 240(4), P. 1421 - 1432

Published: Aug. 26, 2023

Global warming is advancing the timing of spring leaf-out in temperate and boreal plants, affecting biological interactions global biogeochemical cycles. However, spatial variation phenological responsiveness to climate change within species remains poorly understood. Here, we investigated phenology temperature (RSP; days at a given temperature) 2754 Ginkgo biloba twigs trees distributed across subtropical regions China from 24°N 44°N. We found nonlinear effect mean annual on RSP, with highest response rate c. 12°C lower rates warmer or colder temperatures due declines winter chilling accumulation. then predicted maxima RSP under current future scenarios, that are currently most responsive central China, which corresponds species' main distribution area. Under high-emission scenario, predict 4-degree latitude shift maximum toward higher latitudes over rest century. The identification gradients shifts expected represent new mechanistic insights can inform models ecosystem functioning.

Language: Английский

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Bioclimatic predictors of forest structure, composition and phenology in the Paraguayan Dry Chaco

Journal of Tropical Ecology, Journal Year: 2024, Volume and Issue: 40

Published: Jan. 1, 2024

Abstract One of the largest remnants tropical dry forest is South American Gran Chaco. A quarter this biome in Paraguay, but there have been few studies Paraguayan The Chaco flora diverse structure, function, composition and phenology. Fundamental ecological questions remain biome, such as what bioclimatic factors shape Chaco’s composition, structure In study, we integrated inventories from permanent plots with monthly high-resolution NDVI PlanetScope historical climate data WorldClim to identify predictors We found that variables related precipitation were correlated stem density Pielou evenness index, while temperature-related basal area. best predictor phenology (NDVI variation) was lagged by 1 month followed temperature 2 months. period most water stress, phenological response correlates diversity, height area, showing links dominance tree size. Our results indicate even if ecology function Dry Forest characterised limitation, has a moderating effect limiting growth influencing leaf flush deciduousness.

Language: Английский

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Impacts of terrain on land surface phenology derived from Harmonized Landsat 8 and Sentinel-2 in the Tianshan Mountains, China

GIScience & Remote Sensing, Journal Year: 2023, Volume and Issue: 60(1)

Published: Aug. 1, 2023

Knowledge of terrain impacts on land surface phenology (LSP) is crucial for understanding the responses mountainous ecosystems to environmental changes. While effects factors LSP spatial patterns have been observed vary across regions due their different climate and conditions, specific elevations are still largely unclear, especially in with diverse hydrothermal such as Tianshan Mountains located arid semiarid region. Here, we investigated relationships between metrics (i.e. elevation aspect) Xinjiang, China. Our analysis utilized reflectance at a 30 m resolution from Harmonized Landsat 8 Sentinel-2 dataset 2021 2022. We focused two metrics, vegetation greenup (GU20) maturity (GU90), which were estimated using 20% 90% thresholds seasonal amplitude enhanced index (EVI) time series, respectively. modeled ordinary least square (OLS) linear regression entire study region then applied geographically weighted (GWR) 2.5 km bandwidth explore local variations. results suggest that, large scale, played primary role controlling variations both overshadowing aspect. However, when examined scale GWR, aspect emerged an important factor, south-facing aspects associated earlier dates GU20 GU90 most regions. Furthermore, found that influences varied elevations. The explanatory power was stronger middle (approximately 2000–3000 m) than lower (<2000 higher (>3000 In addition, sensitivities demonstrated varying above 2000 m. findings highlight controls elevations, particular emphasis phenological aspect-induced climatic differences.

Language: Английский

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