scholarly journals Response of Mangrove Carbon Fluxes to Drought Stress Detected by Photochemical Reflectance Index

2021 ◽  
Vol 13 (20) ◽  
pp. 4053
Author(s):  
Yaqing Lu ◽  
Xudong Zhu
Keyword(s):  
Drought Stress ◽  
Temporal Variation ◽  
Temporal Dynamics ◽  
Carbon Fluxes ◽  
Pool Size ◽  
Mean Values ◽  
Photochemical Reflectance Index ◽  
Climate Fluctuations ◽  
Ecosystem Carbon

The photochemical reflectance index (PRI) has been often used as a physiology-based remote sensing indicator of ecosystem carbon fluxes. However, the assessments of PRI in tracking long-term carbon fluxes with climatic anomalies in mangroves are very limited. In this study, four-year (2017–2020) continuous time series measurements from tower-based eddy covariance and spectral systems in a subtropical mangrove were used to explore the ability of PRI in tracking the response of mangrove carbon fluxes to climate fluctuations and drought stress. The results showed that the temporal dynamics of daily PRI and carbon fluxes shared similar variation patterns over the study period, experiencing simultaneously decreasing trends under drought stress. Compared with the first three years, annual mean values of NEE in 2020 decreased by 10.7% and PRI decreased by 29.0%, correspondingly. PRI and carbon fluxes were significantly correlated across diurnal, seasonal, and annual time scales with better fitness under drought stress. Dark-state PRI (PRI0), the constitutive component of PRI variation due to seasonally changing pigment pool size, showed similar temporal variation as PRI in response to drought stress, while delta PRI (ΔPRI), the facultative component of PRI variation due to diurnal xanthophyll cycle, showed no response to drought stress. This study confirms the ability of PRI to track temporal dynamics of mangrove carbon fluxes on both short-term and long-term scales, with the temporal variation of PRI largely affected by the long-term constitutive pigment pool size. This study highlights the potential of PRI to serve as an early and readily detectable indicator to track the response of the mangrove carbon cycle to climatic anomalies such as drought stress.

Frequency of Extremes and its Relation to Climate Fluctuations

1993 ◽  
Vol 24 (1) ◽  
pp. 1-12 ◽  
Author(s):  
I. Krasovskaia ◽  
L. Gottschalk
Keyword(s):  
Climate Change ◽  
Probability Distribution ◽  
Climatic Variables ◽  
Statistical Parameters ◽  
Mean Values ◽  
Climate Fluctuations ◽  
Temperature And Precipitation ◽  
Climate Change Concern ◽  
Runoff Events

Possible consequences of climate change concern both changes in long-term mean values of runoff and changes in frequency and magnitude of extreme runoff events. The physical safety of dams and protection against floods are not sensitive to the moderate changes in mean values but to the frequency and magnitude of extremes. This study presents the results of the analyses of the changes in the behavior of the extreme runoff values due to observed changes of temperature and precipitation. Statistical parameters of the magnitude of floods as well as their intensity have been studied. An attempt is also made to establish regional probability distribution curves for the frequencies of the extreme floods for different patterns of changes in the climatic variables considered.

Effects of Nitrogen Deposition on Ecosystem Carbon Fluxes in Sanjiang Plain Marsh of Northeastern China

2011 ◽  
Vol 71-78 ◽  
pp. 2957-2961
Author(s):  
Jian Bo Wang ◽  
Xiao Ling Fu ◽  
Hong Wei Ni ◽  
Xiao Liang Zhou
Keyword(s):  
Net Primary Productivity ◽  
Ecosystem Respiration ◽  
Growing Season ◽  
Carbon Fluxes ◽  
Sanjiang Plain ◽  
Northeastern China ◽  
Long Term Effects ◽  
Ecosystem Carbon ◽  
Ecosystem Carbon Fluxes

It has widely been demonstrated that nitrogen (N) addition enhances plant growth and net primary productivity of terrestrial ecosystems. Moreover, N enrichment could have a profound impact on ecosystem carbon fluxes, especially in the regions where N is deficient. However, there is still debate on how N affects net ecosystem CO2 exchange (NEE). A field experiment manipulating N has been conducted in Calamagrostis anagustifolia community of Sanjiang Plain marsh of northeastern China from 2009 to 2010. N was added at a rate of 5 and 10gN m -2 yr -1with NH4NO3. The results for the 2 yr showed that gross ecosystem productivity (GEP) was higher than ecosystem respiration, leading to net carbon(C)sink (measured by NEE) over the growing season in the study site. Furthermore, low nitrogen (LN) and high nitrogen (HN) addition all significantly stimulated growing-season NEE, on average, by 22 and 36%, respectively. It’s indicated that air temperature plays a major role in regulating ecosystem net C exchange and their responses to climatic change in Sanjiang Plain of northern China. we need long-term field studies to predict the long-term effects of N deposition on ecosystem processes.

Comparative Study of effectiveness of mobilization with movement (MWM) and End range mobilization (ERM) techniques in frozen shoulder

2018 ◽  
Vol 4 (4) ◽  
pp. 519-522
Author(s):  
Jeyakumar S ◽  
Jagatheesan Alagesan ◽  
T.S. Muthukumar
Keyword(s):  
Range Of Motion ◽  
Frozen Shoulder ◽  
Type I ◽  
Mean Values ◽  
Functional Activities ◽  
Group A ◽  
The Mean ◽  
Group B

Background: Frozen shoulder is disorder of the connective tissue that limits the normal Range of motion of the shoulder in diabetes, frozen shoulder is thought to be caused by changes to the collagen in the shoulder joint as a result of long term Hypoglycemia. Mobilization is a therapeutic movement of the joint. The goal is to restore normal joint motion and rhythm. The use of mobilization with movement for peripheral joints was developed by mulligan. This technique combines a sustained application of manual technique “gliding” force to the joint with concurrent physiologic motion of joint, either actively or passively. This study aims to find out the effects of mobilization with movement and end range mobilization in frozen shoulder in Type I diabetics. Materials and Methods: 30 subjects both male and female, suffering with shoulder pain and clinically diagnosed with frozen shoulder was recruited for the study and divided into two groups with 15 patients each based on convenient sampling method. Group A patients received mobilization with movement and Group B patients received end range mobilization for three weeks. The outcome measurements were SPADI, Functional hand to back scale, abduction range of motion using goniometer and VAS. Results: The mean values of all parameters showed significant differences in group A as compared to group B in terms of decreased pain, increased abduction range and other outcome measures. Conclusion: Based on the results it has been concluded that treating the type 1 diabetic patient with frozen shoulder, mobilization with movement exercise shows better results than end range mobilization in reducing pain and increase functional activities and mobility in frozen shoulder.

Seasonal and interannual variability in13C composition of ecosystem carbon fluxes in the U.S. Southern Great Plains

Tellus B ◽  
2011 ◽  
Vol 63 (2) ◽  
Author(s):  
Margaret S. Torn ◽  
Sebastien C. Biraud ◽  
Christopher J. Still ◽  
William J. Riley ◽  
Joe A. Berry
Keyword(s):  
Interannual Variability ◽  
Great Plains ◽  
Carbon Fluxes ◽  
Southern Great Plains ◽  
Seasonal And Interannual Variability ◽  
Ecosystem Carbon ◽  
Ecosystem Carbon Fluxes ◽  
The U.S

Economic conditions and perceptions of immigrants as an economic threat in Europe: Temporal dynamics and mediating processes

2021 ◽  
pp. 002071522199352
Author(s):  
Boris Heizmann ◽  
Nora Huth
Keyword(s):  
Temporal Dynamics ◽  
European Social Survey ◽  
Primary Objective ◽  
Conflict Theory ◽  
Economic Conditions ◽  
Political Climate ◽  
Short Term ◽  
Economic Threat ◽  
Party Positions

This article addresses the extent to which economic downturns influence the perception of immigrants as an economic threat and through which channels this occurs. Our primary objective is an investigation of the specific mechanisms that connect economic conditions to the perception of immigrants as a threat. We therefore also contribute to theoretical discussions based on group threat and realistic group conflict theory by exposing the dominant source of competition relevant to these relationships. Furthermore, we investigate whether people react more sensitive to short-term economic dynamics within countries than to the long-term economic circumstances. Our database comprises all waves of the European Social Survey from 2002 to 2017. The macro-economic indicators we use include GDP per capita, unemployment, and national debt levels, covering the most salient economic dimensions. We furthermore control for the country’s migration situation and aggregate party positions toward cultural diversity. Our results show that the dynamic short-term developments of the economy and migration within countries are of greater relevance for perceived immigrant threat than the long-term situation. In contrast, the long-term political climate appears to be more important than short-term changes in the aggregate party positions. Further mediation analyses show that objective economic conditions influence anti-immigrant attitudes primarily through individual perceptions of the country’s economic performance and that unemployment rates are of primary importance.

scholarly journals Global soil moisture data derived through machine learning trained with in-situ measurements

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Sungmin O. ◽  
Rene Orth
Keyword(s):  
Machine Learning ◽  
Soil Moisture ◽  
Large Scale ◽  
Short Term Memory ◽  
Temporal Dynamics ◽  
Soil Moisture Data ◽  
Wide Range ◽  
Global Soil

AbstractWhile soil moisture information is essential for a wide range of hydrologic and climate applications, spatially-continuous soil moisture data is only available from satellite observations or model simulations. Here we present a global, long-term dataset of soil moisture derived through machine learning trained with in-situ measurements, SoMo.ml. We train a Long Short-Term Memory (LSTM) model to extrapolate daily soil moisture dynamics in space and in time, based on in-situ data collected from more than 1,000 stations across the globe. SoMo.ml provides multi-layer soil moisture data (0–10 cm, 10–30 cm, and 30–50 cm) at 0.25° spatial and daily temporal resolution over the period 2000–2019. The performance of the resulting dataset is evaluated through cross validation and inter-comparison with existing soil moisture datasets. SoMo.ml performs especially well in terms of temporal dynamics, making it particularly useful for applications requiring time-varying soil moisture, such as anomaly detection and memory analyses. SoMo.ml complements the existing suite of modelled and satellite-based datasets given its distinct derivation, to support large-scale hydrological, meteorological, and ecological analyses.

scholarly journals Acute symptoms of mild to moderate COVID-19 are highly heterogeneous across individuals and over time

2021 ◽  
Author(s):  
Thomas L Rodebaugh ◽  
Madelyn R Frumkin ◽  
Angela M Reiersen ◽  
Eric J Lenze ◽  
Michael S Avidan ◽  
...  
Keyword(s):  
Temporal Dynamics ◽  
Survey Methods ◽  
Clinical Care ◽  
Clinical Deterioration ◽  
Symptom Profiles ◽  
Fluctuating Course ◽  
The Common ◽  
Symptom Changes ◽  
Over Time

Abstract Background The symptoms of COVID-19 appear to be heterogenous, and the typical course of these symptoms is unknown. Our objectives were to characterize the common trajectories of COVID-19 symptoms and assess how symptom course predicts other symptom changes as well as clinical deterioration. Methods 162 participants with acute COVID-19 responded to surveys up to 31 times for up to 17 days. Several statistical methods were used to characterize the temporal dynamics of these symptoms. Because nine participants showed clinical deterioration, we explored whether these participants showed any differences in symptom profiles. Results Trajectories varied greatly between individuals, with many having persistently severe symptoms or developing new symptoms several days after being diagnosed. A typical trajectory was for a symptom to improve at a decremental rate, with most symptoms still persisting to some degree at the end of the reporting period. The pattern of symptoms over time suggested a fluctuating course for many patients. Participants who showed clinical deterioration were more likely to present with higher reports of severity of cough and diarrhea. Conclusion The course of symptoms during the initial weeks of COVID-19 is highly heterogeneous and is neither predictable nor easily characterized using typical survey methods. This has implications for clinical care and early-treatment clinical trials. Additional research is needed to determine whether the decelerating improvement pattern seen in our data is related to the phenomenon of patients reporting long-term symptoms, and whether higher symptoms of diarrhea in early illness presages deterioration.

scholarly journals MEG signatures of long-term effects of agreement and disagreement with the majority

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
A. Gorin ◽  
V. Klucharev ◽  
A. Ossadtchi ◽  
I. Zubarev ◽  
V. Moiseeva ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Social Influence ◽  
Temporal Dynamics ◽  
Peer Group ◽  
Long Term Effects ◽  
Learning Mechanisms ◽  
Source Imaging ◽  
The Face ◽  
First Session

AbstractPeople often change their beliefs by succumbing to an opinion of others. Such changes are often referred to as effects of social influence. While some previous studies have focused on the reinforcement learning mechanisms of social influence or on its internalization, others have reported evidence of changes in sensory processing evoked by social influence of peer groups. In this study, we used magnetoencephalographic (MEG) source imaging to further investigate the long-term effects of agreement and disagreement with the peer group. The study was composed of two sessions. During the first session, participants rated the trustworthiness of faces and subsequently learned group rating of each face. In the first session, a neural marker of an immediate mismatch between individual and group opinions was found in the posterior cingulate cortex, an area involved in conflict-monitoring and reinforcement learning. To identify the neural correlates of the long-lasting effect of the group opinion, we analysed MEG activity while participants rated faces during the second session. We found MEG traces of past disagreement or agreement with the peers at the parietal cortices 230 ms after the face onset. The neural activity of the superior parietal lobule, intraparietal sulcus, and precuneus was significantly stronger when the participant’s rating had previously differed from the ratings of the peers. The early MEG correlates of disagreement with the majority were followed by activity in the orbitofrontal cortex 320 ms after the face onset. Altogether, the results reveal the temporal dynamics of the neural mechanism of long-term effects of disagreement with the peer group: early signatures of modified face processing were followed by later markers of long-term social influence on the valuation process at the ventromedial prefrontal cortex.

scholarly journals A 16-year prospective cohort study to evaluate effects of long-term fluctuations in obesity indices of prediabetics on the incidence of future diabetes

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shahla Safari ◽  
Maryam Abdoli ◽  
Masoud Amini ◽  
Ashraf Aminorroaya ◽  
Awat Feizi
Keyword(s):  
High Risk ◽  
Transition Probabilities ◽  
Clinical Settings ◽  
High Tendency ◽  
Mean Values ◽  
Latent Markov Model ◽  
Term Evaluation ◽  
Obesity Indices

AbstractThis study aimed to evaluate the patterns of changes in obesity indices over time in prediabetic subjects and to classify these subjects as either having a low, moderate, and high risk for developing diabetes in the future. This study was conducted among 1228 prediabetics. The patterns of changes in obesity indices based on three measurements including first, mean values during the follow-up period, and last visit from these indices were evaluated by using the latent Markov model (LMM). The mean (standard deviation) age of subjects was 44.0 (6.8) years and 73.6% of them were female. LMM identified three latent states of subjects in terms of change in all anthropometric indices: a low, moderate, and high tendency to progress diabetes with the state sizes (29%, 45%, and 26%), respectively. LMM showed that the probability of transitioning from a low to a moderate tendency to progress diabetes was higher than the other transition probabilities. Based on a long-term evaluation of patterns of changes in obesity indices, our results reemphasized the values of all five obesity indices in clinical settings for identifying high-risk prediabetic subjects for developing diabetes in future and the need for more effective obesity prevention strategies.

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