scholarly journals Tree phenology responses to warming: spring forward, fall back?

2011 ◽  
Vol 31 (5) ◽  
pp. 469-471 ◽  
Author(s):  
D. A. Way
Keyword(s):  
Tree Phenology

Fig tree phenology, thermal sum, and productivity in intensive pruning system in two crop cycles in the semiarid region of Piauí

Fruits ◽  
2021 ◽  
Vol 76 (5) ◽  
pp. 223-229
Author(s):  
A. Carvalho Miranda ◽  
◽  
T.Y.L. Evangelista ◽  
F.A. Campelo Monte Júnior ◽  
E. Sousa Cavalcante ◽  
...  
Keyword(s):  
Semiarid Region ◽  
Tree Phenology ◽  
Thermal Sum ◽  
Fig Tree

scholarly journals Quantifying and Visualizing Campus Tree Phenology

CourseSource ◽  
2019 ◽  
Vol 6 ◽  
Author(s):  
Nathan Emery ◽  
Caleb Trujillo ◽  
Andrew Jarosz ◽  
Tammy Long
Keyword(s):  
Tree Phenology

Living on the edge: Fig tree phenology at the northern range limit of monoecious Ficus in China

2014 ◽  
Vol 57 ◽  
pp. 135-141 ◽  
Author(s):  
Lu-Shui Zhang ◽  
Stephen G. Compton ◽  
Hui Xiao ◽  
Qian Lu ◽  
Yan Chen
Keyword(s):  
Range Limit ◽  
Tree Phenology ◽  
Northern Range Limit ◽  
Fig Tree

Performance of tree phenology models along a bioclimatic gradient in Sweden

2013 ◽  
Vol 266 ◽  
pp. 103-117 ◽  
Author(s):  
Cecilia Olsson ◽  
Kjell Bolmgren ◽  
Johan Lindström ◽  
Anna Maria Jönsson
Keyword(s):  
Tree Phenology

WINTREE: A COMPUTER PROGRAM FOR CALCULATING CHILL AND ANTHESIS UNITS USED IN MODELLING FRUIT TREE PHENOLOGY

1999 ◽  
pp. 245-252
Author(s):  
R. Rojas-Martinez ◽  
S.D. Seeley ◽  
J.L. Anderson ◽  
J.W. Frisby ◽  
J.I. del Real-Laborde
Keyword(s):  
Computer Program ◽  
Fruit Tree ◽  
Tree Phenology

Detecting mismatches of bird migration stopover and tree phenology in response to changing climate

Oecologia ◽  
2015 ◽  
Vol 178 (4) ◽  
pp. 1227-1238 ◽  
Author(s):  
Jherime L. Kellermann ◽  
Charles van Riper
Keyword(s):  
Bird Migration ◽  
Changing Climate ◽  
Tree Phenology

scholarly journals Optimal Nutrient Concentration Ranges of ‘Hass’ Avocado Cauliflower Stage Inflorescences—Potential Diagnostic Tool to Optimize Tree Nutrient Status and Increase Yield

HortScience ◽  
2017 ◽  
Vol 52 (12) ◽  
pp. 1707-1715 ◽  
Author(s):  
Salvatore Campisi-Pinto ◽  
Yusheng Zheng ◽  
Philippe E. Rolshausen ◽  
David E. Crowley ◽  
Ben Faber ◽  
...  
Keyword(s):  
Nutrient Concentration ◽  
Fruit Set ◽  
Fruit Size ◽  
Nutrient Status ◽  
Persea Americana ◽  
Nutrient Concentrations ◽  
Full Bloom ◽  
Nutrient Analysis ◽  
Tree Phenology ◽  
Hass Avocado

Optimizing ‘Hass’ avocado (Persea americana Mill.) tree nutrient status is essential for maximizing productivity. Leaf nutrient analysis is used to guide avocado fertilization to maintain tree nutrition. The goal of this research was to identify a ‘Hass’ avocado tissue with nutrient concentrations predictive of yields greater than 40 kg of fruit per tree. This threshold was specified to assist the California avocado industry to increase yields to ≈11,200 kg·ha−1. Nutrient concentrations of cauliflower stage inflorescences (CSI) collected in March proved better predictors of yield than inflorescences collected at full bloom (FBI) in April, fruit pedicels (FP) collected at five different stages of avocado tree phenology from the end of fruit set in June through April the following spring when mature fruit enter a second period of exponential growth, or 6-month-old spring flush leaves (LF) from nonbearing vegetative shoots collected in September (California avocado industry standard). For CSI tissue, concentrations of seven nutrients, nitrogen (N), phosphorus (P), potassium (K), magnesium (Mg), sulfur (S), zinc (Zn), and copper (Cu) were predictive of trees producing greater than 40 kg of fruit annually. Conditional quantile sampling and frequency analysis were used to identify optimum nutrient concentration ranges (ONCR) for each nutrient. Optimum ratios between nutrient concentrations and yields greater than 40 kg per tree were also derived. The high nutrient concentrations characterizing CSI tissue suggest current fertilization practices (timing or amounts) might be causing nutrient imbalances at this stage of avocado tree phenology that are limiting productivity, a possibility that warrants further investigation. Because CSI samples can be collected 4–6 weeks before full bloom, nutritional problems can be addressed before they affect flower retention and fruit set to increase current crop yield, fruit size, and quality. Thus, CSI nutrient analysis warrants further research as a potential supplemental or alternative tool for diagnosing ‘Hass’ avocado tree nutrient status and increasing yield.

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