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71.
Modelling seasonal dynamics of secondary growth in R
Jernej Jevšenak, Jožica Gričar, Sergio Rossi, Peter Prislan, 2022, izvirni znanstveni članek

Povzetek: The monitoring of seasonal radial growth of woody plants addresses the ultimate question of when, how and why trees grow. Assessing the growth dynamics is important to quantify the effect of environmental drivers and understand how woody species will deal with the ongoing climatic changes. One of the crucial steps in the analyses of seasonal radial growth is to model the dynamics of xylem and phloem formation based on increment measurements on samples taken at relatively short intervals during the growing season. The most common approach is the use of the Gompertz equation, while other approaches, such as general additive models (GAMs) and generalised linear models (GLMs), have also been tested in recent years. For the first time, we explored artificial neural networks with Bayesian regularisation algorithm (BRNNs) and show that this method is easy to use, resistant to overfitting, tends to yield s-shaped curves and is therefore suitable for deriving temporal dynamics of secondary tree growth. We propose two data processing algorithms that allow more flexible fits. The main result of our work is the XPSgrowth() function implemented in the radial Tree Growth (rTG) R package, that can be used to evaluate and compare three modelling approaches: BRNN, GAM and the Gompertz function. The newly developed function, tested on intra-seasonal xylem and phloem formation data, has potential applications in many ecological and environmental disciplines where growth is expressed as a function of time. Different approaches were evaluated in terms of prediction error, while fitted curves were visually compared to derive their main characteristics. Our results suggest that there is no single best fitting method, therefore we recommend testing different fitting methods and selection of the optimal one.
Ključne besede: artificial neural networks, cambium, generalized additive model, Gompertz function, growing season, intra-annual time series
Objavljeno v DiRROS: 21.07.2022; Ogledov: 37; Prenosov: 37
.pdf Celotno besedilo (1,11 MB)
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Early-warning signals of individual tree mortality based on annual radial growth
Maxime Cailleret, Vasilis Dakos, Steven Jansen, Elisabeth M.R. Robert, Tuomas Aakala, Mariano M. Amoroso, Joe A. Antos, Christof Bigler, Harald Bugmann, Marco Caccianaga, Katarina Čufar, Tom Levanič, 2019, izvirni znanstveni članek

Povzetek: Tree mortality is a key driver of forest dynamics and its occurrence is projected to increase in the future due to climate change. Despite recent advances in our understanding of the physiological mechanisms leading to death, we still lack robust indicators of mortality risk that could be applied at the individual tree scale. Here, we build on a previous contribution exploring the differences in growth level between trees that died and survived a given mortality event to assess whether changes in temporal autocorrelation, variance, and synchrony in time-series of annual radial growth data can be used as early warning signals of mortality risk. Taking advantage of a unique global ring-width database of 3065 dead trees and 4389 living trees growing together at 198 sites (belonging to 36 gymnosperm and angiosperm species), we analyzed temporal changes in autocorrelation, variance, and synchrony before tree death (diachronic analysis), and also compared these metrics between trees that died and trees that survived a given mortality event (synchronic analysis). Changes in autocorrelation were a poor indicator of mortality risk. However, we found a gradual increase in interannual growth variability and a decrease in growth synchrony in the last %20 years before mortality of gymnosperms, irrespective of the cause of mortality. These changes could be associated with drought-induced alterations in carbon economy and allocation patterns. In angiosperms, we did not find any consistent changes in any metric. Such lack of any signal might be explained by the relatively high capacity of angiosperms to recover after a stress-induced growth decline. Our analysis provides a robust method for estimating early-warning signals of tree mortality based on annual growth data. In addition to the frequently reported decrease in growth rates, an increase in inter-annual growth variability and a decrease in growth synchrony may be powerful predictors of gymnosperm mortality risk, but not necessarily so for angiosperms.
Ključne besede: tree mortality, ring-width, forest, growth, resilience indicators, drought, biotic agents, variance
Objavljeno v DiRROS: 20.07.2022; Ogledov: 68; Prenosov: 55
.pdf Celotno besedilo (2,19 MB)
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75.
Skupni izobraževalni model o prilagoditvenih načrtih : poročilo aktivnosti 12 delovnega sklopa 3.2 projekta ECO-SMART
Liliana Vižintin, Suzana Škof, 2022, elaborat, predštudija, študija

Ključne besede: obalna območja, ekosistemske storitve, čezmejno sodelovanje, Natura 2000
Objavljeno v DiRROS: 20.07.2022; Ogledov: 44; Prenosov: 24
.pdf Celotno besedilo (1,88 MB)
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Proteolytically activated CRAC effectors through designed intramolecular inhibition
Vid Jazbec, Roman Jerala, Mojca Benčina, 2022, izvirni znanstveni članek

Ključne besede: STIM1, Orai, TEV protease, PPV protease, calcium signaling, coiled-coil peptides
Objavljeno v DiRROS: 20.07.2022; Ogledov: 78; Prenosov: 54
.pdf Celotno besedilo (5,32 MB)
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79.
Synoptic risk assessment of groundwater contamination from landfills
Sonja Cerar, Luka Serianz, Katja Koren, Joerg Prestor, Nina Mali, 2022, izvirni znanstveni članek

Povzetek: Waste management in Europe has improved in recent years, reducing the amount of waste disposed at landfills. However, there are still many landfills in the countries. It is well known that landfills that do not have measures in place to control leachate entering groundwater can contaminate groundwater long after the landfill is closed. Collecting monitoring results from all landfills allows permitting and management agencies to improve action plans. This relies on a synoptic risk assessment that allows prioritization and milestones to be set for required actions. The developed method of synoptic risk assessment is based on a conceptual model of the landfill and the results of chemical groundwater monitoring tested at 69 landfills in Slovenia. The study confirms that most landfills have a direct or indirect impact on groundwater quality. All landfills were classified into three priority classes on the basis of the synoptic risk assessment. The results show that a total of 24 landfills have a clearly pronounced impact on groundwater. A total of 31 landfills have a less pronounced impact due to the favorable natural attenuation capacity of the soil or the technically appropriate design of the landfill itself. A total of 14 landfills have a less pronounced or negligible impact on groundwater.
Ključne besede: conceptual model, synoptic risk assessment, landfill, groundwater, chemical analysis
Objavljeno v DiRROS: 19.07.2022; Ogledov: 66; Prenosov: 48
.pdf Celotno besedilo (3,09 MB)
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80.
The effect of menstrual cycle on perceptual responses in athletes : a systematic review with meta-analysis
Ana Carolina Paludo, Armin Paravlić, Kristýna Dvořáková, Marta Gimunová, 2022, pregledni znanstveni članek

Povzetek: This article aimed to investigate the effects of menstrual cycle phases on perceptual responses in athletes by means of systematic review and meta-analysis. The search was conducted in the PubMed, Web of Science, and Sport Discus databases considering articles with two or more menstrual phases for comparison. The PECO criteria were used for the keywords “menstrual cycle,” “athletes,” and “perceptual responses” with their respective entry terms. Of 1.165 records identified, 14 articles were available for the final evaluation, while eight articles were eligible for a meta-analysis. The perceptual responses evaluated in the studies were: motivation, competitiveness, sleep quality, stress, muscle soreness, fatigue, perceived effort, mood, menstrual symptoms, perceived endurance, and readiness. The meta-analysis was conducted for perceived effort only. The results showed that the level of perceived exertion does not differ two phases of the menstrual cycle (MD = 3.03, Q = 1.58, df = 1, p = 0.209), whereas RPE was 19.81 ± 0.05 and 16.27 ± 0.53 at day 1–5 and day 19–24, respectively. Two studies found statistically significant changes in motivation and competitiveness during the cycle, with better outcomes in ovulatory phase compared to follicular and luteal. One study found an increase in mood disturbance in the pre-menstrual phase (vs. mid-cycle); one decreased vigor in the menstrual phase (vs. luteal); one increased the menstrual symptoms in the follicular phase (vs. ovulation), and one study reported increased fatigue and decreased sleep quality on luteal phase (vs. follicular). The remaining studies and variables were not affected by the menstrual cycle phase. Based on the results from the studies selected, some perceptual responses are affected in different menstrual cycle phases. A “favorable” subjective response in athletes was noticed when the ovarian hormones present an increase in concentration levels compared to phases with lower concentration. Different perceptual variables and methodological approaches limit the generalization of the conclusion.
Ključne besede: athletes, female, behavior, menstrual cycle, hormones, perceptual responses
Objavljeno v DiRROS: 19.07.2022; Ogledov: 49; Prenosov: 49
.pdf Celotno besedilo (922,63 KB)
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