scholarly journals The Response of Net Primary Production to Climate Change: A Case Study in the 400 mm Annual Precipitation Fluctuation Zone in China

2019 ◽  
Vol 16 (9) ◽  
pp. 1497 ◽  
Author(s):  
Yang Li ◽  
Yaochen Qin
Keyword(s):  
Climate Change ◽  
Correlation Analysis ◽  
Primary Production ◽  
Correlation Coefficient ◽  
Land Surface ◽  
Partial Correlation ◽  
Net Primary Production ◽  
Annual Precipitation ◽  
The Future ◽  
Total Study Area

The regions in China that intersect the 400 mm annual precipitation line are especially ecologically sensitive and extremely vulnerable to anthropogenic activities. However, in the context of climate change, the response of vegetation Net Primary Production (NPP) in this region has not been scientifically studied in depth. NPP suffers from the comprehensive effect of multiple climatic factors, and how to eliminate the effect of interfering variables in the correlation analysis of NPP and target variables (temperature or precipitation) is the major challenge in the study of NPP influencing factors. The correlation coefficient between NPP and target variable was calculated by ignoring other variables that also had a large impact on NPP. This increased the uncertainty of research results. Therefore, in this study, the second-order partial correlation analysis method was used to analyze the correlation between NPP and target variables by controlling other variables. This can effectively decrease the uncertainty of analysis results. In this paper, the univariate linear regression, coefficient of variation, and Hurst index estimation were used to study the spatial and temporal variations in NPP and analyze whether the NPP seasonal and annual variability will persist into the future. The results show the following: (i) The spatial distribution of NPP correlated with precipitation and had a gradually decreasing trend from southeast to northwest. From 2000 to 2015, the NPP in the study area had a general upward trend, with a small variation in its range. (ii) Areas with negative partial correlation coefficients between NPP and precipitation are consistent with the areas with more abundant water resources. The partial correlation coefficient between the NPP and the Land Surface Temperature (LST) was positive for 52.64% of the total study area. Finally, the prediction of the persistence of NPP variation into the future showed significant differences on varying time scales. On an annual scale, NPP was predicted to persist for 46% of the study area. On a seasonal scale, NPP in autumn was predicted to account for 49.92%, followed by spring (25.67%), summer (13.40%), and winter (6.75%).

scholarly journals Correlating Capsaicinoid Levels and Physicochemical Proper-ties of Kimchi and Its Perceived Spiciness

Foods ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 86
Author(s):  
So-Ra Yoon ◽  
Yun-Mi Dang ◽  
Su-Yeon Kim ◽  
Su-Yeon You ◽  
Mina K. Kim ◽  
...  
Keyword(s):  
Correlation Analysis ◽  
Physicochemical Properties ◽  
Correlation Coefficient ◽  
Partial Correlation ◽  
Sugar Content ◽  
Amino Acid Content ◽  
Titratable Acidity ◽  
Free Sugar ◽  
Partial Correlation Analysis ◽  
The Relationship

Capsaicinoid content, among other factors, affects the perception of spiciness of commercial kimchi. Here, we investigated whether the physicochemical properties of kimchi affect the spicy taste of capsaicinoids perceived by the tasting. High-performance liquid chromatography (HPLC) was used to evaluate the capsaicinoid content (mg/kg) of thirteen types of commercial kimchi. The physicochemical properties such as pH, titratable acidity, salinity, free sugar content, and free amino acid content were evaluated, and the spicy strength grade was determined by selected panel to analyze the correlation between these properties. Panels were trained for 48 h prior to actual evaluation by panel leaders trained for over 1000 h according to the SpectrumTM method. Partial correlation analysis was performed to examine other candidate parameters that interfere with the sensory evaluation of spiciness and capsaicinoid content. To express the specific variance after eliminating the effects of other variables, partial correlations were used to estimate the relationships between two variables. We observed a strong correlation between spiciness intensity ratings and capsaicinoid content, with a Pearson’s correlation coefficient of 0.78 at p ≤ 0.001. However, other specific variables may have influenced the relationship between spiciness intensity and total capsaicinoid content. Partial correlation analysis indicated that the free sugar content most strongly affected the relationship between spiciness intensity and capsaicinoid content, showing the largest first-order partial correlation coefficient (rxy/z: 0.091, p ≤ 0.01).

scholarly journals Desertification in Forest, Range and Desert Landuses of Tehran Province, Under the Impact of Climate Change

2016 ◽  
Author(s):  
Hadi Eskandari Dameneh ◽  
Moslem Borji ◽  
Hassan Khosravi ◽  
Ali Salajeghe
Keyword(s):  
Climate Change ◽  
Primary Production ◽  
Net Primary Production ◽  
Degradation Process ◽  
Early Warning Systems ◽  
Land Uses ◽  
Emission Scenarios ◽  
Desert Ecosystems ◽  
Tehran Province ◽  
The Impact

Abstract. Persistence of widespread degradation in arid and semi-arid region of Iran necessitates using of monitoring and evaluation systems with appropriate accuracy to determine the degradation process and adoption of early warning systems; because after transition from some thresholds, effective reversible function of ecosystems will not be very easy. This paper tries to monitor the degradation and desertification trends in three land uses including range, forest and desert lands affected by climate change in Tehran province for 2000s and 2030s. For assessing climate changes of Mehrabad synoptic stations the data of two emission scenarios including A2 and B2 were used using statistical downscaling techniques and data generated by SDSM model. The index of net primary production resulting from MODIS satellite images was employed as an indicator of destruction from 2001 to 2010. The results showed that temperature is the most effective driver force which alters the net primary production in rangeland, forest and desert ecosystems of Tehran province. On the basis of monitoring findings under real conditions, in the 2000s, over 60 % of rangelands and 80 % of the forests have been below the average production in the province. On the other hand, the long-term average changes of NPP in rangeland and forests indicated the presence of relatively large areas of these land uses with production rate lower than the desert. The results also showed that, assuming the existence of circumstances of each emission scenarios, the desertification status will not improve significantly in the rangelands and forests of Tehran province.

scholarly journals Using Terrestrial Laser Scanning to Characterize Peatland Microtopography and Assess Tree Growth Responses to Elevated Temperature and CO2

2020 ◽  
Author(s):  
Jake D. Graham
Keyword(s):  
Elevated Temperature ◽  
Environmental Change ◽  
Primary Production ◽  
Tree Growth ◽  
Land Surface ◽  
Net Primary Production ◽  
Growth Responses ◽  
Aboveground Net Primary Production ◽  
Response To Temperature ◽  
Northern Peatlands

Northern peatlands are a major terrestrial carbon (C) store, with an annual sink of 0.1 Pg C yr-1 and a total storage estimate of 547 Pg C. Northern peatlands are also major contributors of atmospheric methane, a potent greenhouse gas. The microtopography of peatlands helps modulate peatland carbon fluxes; however, there is a lack of quantitative characterizations of microtopography in the literature. The lack of formalized schemes to characterize microtopography makes comparisons between studies difficult. Further, many land surface models do not accurately simulate peatland C emissions, in part because they do not adequately represent peatland microtopography and hydrology. The C balance of peatlands is determined by differences in C influxes and effluxes, with the largest being net primary production and heterotrophic respiration, respectively. Tree net primary production at a treed bog in northern Minnesota represented about 13% of C inputs to the peatland, and marks tree aboveground net primary production (ANPP) as an important pathway for C to enter peatlands. Tree species Picea mariana (Black spruce) and Larix Laricina (Tamarack) are typically found in wooded peatlands in North America, and are widely distributed in the North American boreal zone. Therefore, understanding how these species will respond to environmental change is needed to make predictions of peatland C budgets in the future. As the climate warms, peatlands are expected to increase C release to the atmosphere, resulting in a positive feedback loop. Further, climate warming is expected to occur faster in northern latitudes compared to the rest of the globe. The Spruce and Peatland Responses Under Changing Environments (SPRUCE; https://mnspruce.ornl.gov/) manipulates temperature and CO2 concentrations to evaluate the in-situ response of a peatland to environmental change and is located in Minnesota, USA. In this dissertation, I documented surface roughness metrics for peatland microtopography in SPRUCE plots and developed three explicit methods for classifying frequently used microtopographic classes (microforms) for different scientific applications. Subsequently I used one of these characterizations to perform a sensitivity analysis and improve the parameterization of microtopography in a land surface model that was calibrated at the SPRUCE site. The modeled outputs of C from the analyses ranged from 0.8-34.8% when microtopographical parameters were allowed to vary within observed ranges. Further, C related outputs when using our data-driven parameterization differed from outputs when using the default parameterization by -7.9 - 12.2%. Finally, I utilized TLS point clouds to assess the effect elevated temperature and CO2 concentrations had on P. mariana and L. laricina after the first four years of SPRUCE treatments. I observed that P. mariana growth (aboveground net primary production) had a negative response to temperature initially, but the relationship became less pronounced through time. Conversely, L. laricina had no growth response to temperature initially, but developed a positive relationship through time. The divergent growth responses of P. mariana and L. laricina resulted in no detectable change in aboveground net primary production at the community level. Results from this dissertation help improve how peatland microtopography is represented, and improves understanding of how peatland tree growth will respond to environmental change in the future.

Net Primary Production in the Shortgrass Steppe

2008 ◽  
Author(s):  
William K. Lauenroth ◽  
Daniel G. Milchunas
Keyword(s):  
Global Change ◽  
Primary Production ◽  
Net Primary Production ◽  
Regional Scale ◽  
Ecosystem Dynamics ◽  
Shortgrass Steppe ◽  
Annual Precipitation ◽  
Mean Annual Precipitation ◽  
Spatial And Temporal Patterns ◽  
Temporal And Spatial

Net primary production (NPP), the amount of carbon or energy fixed by green plants in excess of their respiratory needs, is the fundamental quantity upon which all heterotrophs and the ecosystem processes they are associated with depend. Understanding NPP is therefore a prerequisite to understanding ecosystem dynamics. Our objectives for this chapter are to describe the current state of our knowledge about the temporal and spatial patterns of NPP in the shortgrass steppe, to evaluate the important variables that control NPP, and to discuss the future of NPP in the shortgrass steppe given current hypotheses about global change. Most of the data available for NPP in the shortgrass steppe are for aboveground net primary production (ANPP), so most of our presentation will focus on ANPP and we will deal with belowground net primary production (BNPP) as a separate topic. Furthermore, our treatment of NPP in this chapter will ignore the effects of herbivory, which will be covered in detail in chapter 16. Our approach will be to start with a regional-scale view of ANPP in shortgrass ecosystems and work toward a site-scale view. We will begin by briefly placing ANPP in the shortgrass steppe in its larger context of the central North American grassland region. We will then describe the regional-scale patterns and controls on ANPP, and then move to the site-scale patterns and controls on ANPP. At the site scale, we will describe both temporal and spatial dynamics, and controls on ANPP as well as BNPP. We will then discuss relationships between spatial and temporal patterns in ANPP and end the chapter with a short, speculative section on how future global change may influence NPP in the shortgrass steppe. Temperate grasslands in central North America are found over a range of mean annual precipitation from 200 to 1200 mm.y–1 and mean annual temperatures from 0 to 20 oC (Lauenroth et al., 1999). The widely cited relationship between mean annual precipitation and average annual ANPP allows us to convert the precipitation gradient into a production gradient (Lauenroth, 1979; Lauenroth et al., 1999; Noy-Meir, 1973; Rutherford, 1980; Sala et al., 1988b).

Impact of climate change on net primary production (NPP) in south Iran

2020 ◽  
Vol 192 (6) ◽  
Author(s):  
Zahra Azhdari ◽  
Elham Rafeie Sardooi ◽  
Ommolbanin Bazrafshan ◽  
Hossein Zamani ◽  
Vijay P. Singh ◽  
...  
Keyword(s):  
Climate Change ◽  
Primary Production ◽  
Net Primary Production ◽  
Impact Of Climate Change

Drought responses of Amazon forests under climate change: Separating the roles of soil moisture and canopy responses

2020 ◽  
Author(s):  
Hao-wei Wey ◽  
Kim Naudts ◽  
Julia Pongratz ◽  
Julia Nabel ◽  
Lena Boysen
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Land Surface ◽  
Net Primary Production ◽  
Leaf Phenology ◽  
Future Climate Change ◽  
Surface Model ◽  
Litter Production ◽  
Direct Effects ◽  
Climatic Effects

<p>The Amazon forests are one of the largest ecosystem carbon pools on Earth. While more frequent and prolonged droughts have been predicted under future climate change there, the vulnerability of Amazon forests to drought has yet remained largely uncertain, as previous studies have shown that few land surface models succeeded in capturing the vegetation responses to drought. In this study, we present an improved version of the land surface model JSBACH, which incorporates new formulations of leaf phenology and litter production based on intensive field measurement from the artificial drought experiments in the Amazon. Coupling the new JSBACH with the atmospheric model ECHAM, we investigate the drought responses of the Amazon forests and the resulting feedbacks under RCP8.5 scenario. The climatic effects resulted from (1) direct effects including declining soil moisture and stomatal responses, and (2) soil moisture-induced canopy responses are separated to give more insights, as the latter was poorly simulated. Preliminary results show that for net primary production and soil respiration, the direct effects and canopy responses have similar spatial patterns with the magnitude of the latter being 1/5 to 1/3 of the former. In addition, declining soil moisture enhances rainfall in Northern Amazon and suppresses rainfall in the south, while canopy responses have negligible effects on rainfall. Based on our findings, we suggest cautious interpretation of results from previous studies. To address this uncertainty, better strategy in modeling leaf phenology such as implemented in this study should be adopted.</p>

Correlation Analysis Based on the Performance and Structural Parameters of Woven Fabrics for Bedding

2013 ◽  
Vol 796 ◽  
pp. 240-244
Author(s):  
Xun Ke Sun ◽  
Tao Qiu ◽  
Mei Jun Chen ◽  
Cen Feng
Keyword(s):  
Correlation Analysis ◽  
Correlation Coefficient ◽  
Performance Indicators ◽  
Partial Correlation ◽  
Structural Parameters ◽  
Scientific Evidence ◽  
Woven Fabrics ◽  
Main Factors ◽  
Spss Software ◽  
Partial Correlation Coefficient

Typical woven fabrics for bedding were selected from the market in this paper. Based on test and analysis results of the structural parameters, the relevant performance indicators were measured in consideration of mechanical properties,comfort and style of fabrics, and the test data were systematically integrated and the relevant quantitative data were ultimately obtained. Meanwhile, Fabric Assurance Tester was used to determine the style of the fabrics and tested indicators were chosen, following with normalized statistics and processing. In addition, SPSS software was applied for the correlation analysis between fabric properties and structural parameters through the correlation and partial correlation analysis.According to the results of correlation coefficient,partial correlation coefficient, the paper revealed the intrinsic link between the fabric’s structural parameters and its properties. As to the main factors of the structural parameters which greatly affect the performance of the fabrics, they will provide scientific evidence for the design and development of fabric.

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