Leaf life span is an important plant trait associated with interspecific variation in leaf, organismal, and ecosystem processes. We hypothesized that intraspecific variation in gymnosperm needle traits with latitude reflects both selection and acclimation for traits adaptive to the associated temperature and moisture gradient. This hypothesis was supported, because across 127 sites along a 2,160-km gradient in North America individuals of Picea glauca, Picea mariana, Pinus banksiana, and Abies balsamea had longer needle life span and lower tissue nitrogen concentration with decreasing mean annual temperature. Similar patterns were noted for Pinus sylvestris across a north-south gradient in Europe. These differences highlight needle longevity as an adaptive feature important to ecological success of boreal conifers across broad climatic ranges. Additionally, differences in leaf life span directly affect annual foliage turnover rate, which along with needle physiology partially regulates carbon cycling through effects on gross primary production and net canopy carbon export. However, most, if not all, global land surface models parameterize needle longevity of boreal evergreen forests as if it were a constant. We incorporated temperature-dependent needle longevity and %nitrogen, and biomass allocation, into a land surface model, Community Atmosphere Biosphere Land Exchange, to assess their impacts on carbon cycling processes. Incorporating realistic parameterization of these variables improved predictions of canopy leaf area index and gross primary production compared with observations from flux sites. Finally, increasingly low foliage turnover and biomass fraction toward the cold far north indicate that a surprisingly small fraction of new biomass is allocated to foliage under such conditions.
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http://dx.doi.org/10.1073/pnas.1216054110 | DOI Listing |
Vascular
December 2024
Department of Vascular Surgery, Student Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran.
Objectives: Basilic vein transposition (BVT) surgery is a crucial option for vascular access in hemodialysis patients when other alternatives are unavailable. One of the primary complications affecting the long-term function of arteriovenous fistulas (AVFs) is the development of pseudoaneurysms, often caused by repeated punctures at the same site. This study aims to evaluate whether increasing the length of the basilic vein available for cannulation during the second stage of BVT surgery reduces the risk of puncture-related pseudoaneurysms, thereby improving fistula longevity and functionality.
View Article and Find Full Text PDFAsian J Androl
September 2024
Global Andrology Forum, Moreland Hills, OH 44022, USA.
Int J Health Policy Manag
August 2024
School of Pharmacy, National Taiwan University, Taipei, Taiwan.
Background: To evaluate the impact of reimbursement criteria change on the utilization pattern of anti-vascular endothelial growth factor (anti-VEGF) among patients with wet age-related macular degeneration (wAMD) and diabetic macular edema (DME) separately in Taiwan.
Methods: An interrupted time series analysis (ITSA) was performed using Taiwan's National Health Insurance (NHI) database, and patients with wAMD or DME diagnosis at the first injection of anti-VEGF agents was identified from 2011 to 2019. The outcome of interest was treatment gaps between injections of anti-VEGF.
Vet Sci
May 2024
Comparative Theriogenology, Department of Veterinary Clinical Sciences, College of Veterinary Medicine, Center for Reproductive Biology, Washington State University, Pullman, WA 99163, USA.
Med Phys
July 2024
Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California, USA.
Background: 3D neural network dose predictions are useful for automating brachytherapy (BT) treatment planning for cervical cancer. Cervical BT can be delivered with numerous applicators, which necessitates developing models that generalize to multiple applicator types. The variability and scarcity of data for any given applicator type poses challenges for deep learning.
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