Simple method to detect year-to-year variability of blooming phenology of Cerasus × yedoensis by digital camera.

Int J Biometeorol

Research and Development Center for Global Change, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), 3173-25 Showa-machi, Kanazawa-ku, Yokohama, Kanagawa, 236-0001, Japan.

Published: December 2018

The year-to-year variability of the blooming phenology of cherry trees is important as a proxy climate indicator and strongly affects cultural ecosystem services. Observation of blooming phenology at multiple points requires a simple and flexible approach. We examined changes in the canopy gap fraction extracted from binarized upward images taken periodically beneath a Cerasus × yedoensis 'Somei-yoshino' tree. The gap fraction decreased rapidly after the start of bloom, reached a minimum value at full bloom, and began to increase again, but then decreased rapidly during leaf flush. These changes reflect the phenology of blooming and leaf flush after flower drop of 'Somei-yoshino'. These characteristics allow detection of the year-to-year variability of the bloom and leaf-flush phenology of cherry and other deciduous tree species that show the same patterns.

Download full-text PDF

Source
http://dx.doi.org/10.1007/s00484-018-1620-5DOI Listing

Publication Analysis

Top Keywords

year-to-year variability
12
blooming phenology
12
variability blooming
8
cerasus yedoensis
8
phenology cherry
8
gap fraction
8
decreased rapidly
8
leaf flush
8
phenology
5
simple method
4

Similar Publications

Thrips tabaci is the main thrips species affecting onion and related species. It is a cryptic species complex comprising three phylogenetic groups characterized by different reproductive modes (thelytoky or arrhenotoky) and host plant specialization. Thrips tabaci populations vary widely in genetic diversity, raising questions about the factor(s) that drive this diversity.

View Article and Find Full Text PDF

Purpose: Chat Generative Pre-Trained Transformer (ChatGPT) may have implications as a novel educational resource. There are differences in opinion on the best resource for the Orthopaedic In-Training Exam (OITE) as information changes from year to year. This study assesses ChatGPT's performance on the OITE for use as a potential study resource for residents.

View Article and Find Full Text PDF

Designing a sector-coupled European energy system robust to 60 years of historical weather data.

Nat Commun

December 2024

Department of Mechanical and Production Engineering, Aarhus University, Katrinebjergvej 89F, 8200, Aarhus N, Denmark.

As energy systems transform to rely on renewable energy and electrification to mitigate climate change, they encounter stronger year-to-year variability in energy supply and demand. Yet, most infrastructure planning relies on a single weather year, risking a potential lack of robustness. In this paper, we optimize capacity layouts for a European energy system under net-zero CO emissions for 62 different weather years.

View Article and Find Full Text PDF

Background: Hyperglycemic emergencies (HGEs) are the major deadliest acute complications of diabetes. HGEs have reached an alarming stage and increased year-to-year leading to increased morbidity, hospitalization, and mortality. Despite HGEs causing this increased healthcare, psychological, social, and economic burden, studies conducted to address this burden and its predictive factors remain limited.

View Article and Find Full Text PDF

Lightning is a major source of wildfire ignition in the western United States (WUS). We build and train convolutional neural networks (CNNs) to predict the occurrence of cloud-to-ground (CG) lightning across the WUS during June-September from the spatial patterns of seven large-scale meteorological variables from reanalysis (1995-2022). Individually trained CNN models at each 1° × 1° grid cell ( = 285 CNNs) show high skill at predicting CG lightning days across the WUS (median AUC = 0.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!