Elucidating climatic controls of polynomial trends in interannual variations of northern ecosystem productivities

2021 ◽  
Author(s):  
Wenxin Zhang ◽  
Hongxiao Jin ◽  
Sadegh Jamali ◽  
Zheng Duan ◽  
Mousong Wu ◽  
...  
Keyword(s):  
Climate Change ◽  
Spatial Patterns ◽  
Plant Phenology ◽  
Ecosystem Productivity ◽  
Polynomial Trend ◽  
Non Linear ◽  
Climatic Drivers ◽  
Polynomial Trends ◽  
Permanent Wetland ◽  
Linear Trends

<p>Rapid warming in northern high latitudes during the past two decades may have profound impacts on the structures and functioning of ecosystems. Understanding how ecosystems respond to climatic change is crucial for the prediction of climate-induced changes in plant phenology and productivity. Here we investigate spatial patterns of polynomial trends in ecosystem productivity for northern (> 30 °N) biomes and their relationships with climatic drivers during 2000–2018. Based on a moderate resolution (0.05°) of satellite data and climate observations, we quantify polynomial trend types and change rates of ecosystem productivities using plant phenology index (PPI), a proxy of gross primary productivity (GPP), and a polynomial trend identification scheme (Polytrend). We find the yearly-integrated PPI (PPI<sub>INT</sub>) shows a high degree of agreement with an OCO-2-based solar‐induced chlorophyll fluorescence GPP product (GOSIF-GPP) for distinct spatial patterns of trend types of ecosystem productivities. The averaged slope for linear trends of GPP is found positive across all the biomes, among which deciduous broadleaved and evergreen needle-leaved forests show the highest and lowest rates respectively. The evergreen needle-leaved forests, low shrub, and permanent wetland show linear trends in PPI<sub>INT</sub> over more than 50% of the covered area and permanent wetland also shows a large fraction of the area with the quadratic and cubic trends. Spatial patterns of linear trends for growing season sum of temperature, precipitation, and photosynthetic active radiation have been quantified. Based on the partial correlations between PPI<sub>INT</sub> and climate drivers, we found that there is a consistent shift of dominant drivers from temperature or radiation to precipitation across all the biomes except the permeant wetland when the trend type of ecosystem productivity changes from linear to non-linear. This may imply precipitation changes in recent years may determine the linear or non-linear responses of ecosystem productivity to climate change. Our results highlight the importance of understanding how changes in climatic drivers may affect the overall responses of ecosystems productivity. Our findings will facilitate the sustainable management of ecosystems accounting for the resilience of ecosystem productivity and phenology to future climate change.</p>

scholarly journals Multi-scale modeling of the response of runoff to climate change

2014 ◽  
Vol 18 (5) ◽  
pp. 1511-1516
Author(s):  
Chong-Li Di ◽  
Xiao-Hua Yang ◽  
Xing-Hui Xia ◽  
Xiao-Juan Chen ◽  
Jian-Qiang Li
Keyword(s):  
Climate Change ◽  
Time Scales ◽  
Yellow River ◽  
Linear Trend ◽  
Linear Regression Analysis ◽  
Annual Runoff ◽  
Reconstruction Methods ◽  
Non Linear ◽  
Precipitation And Temperature ◽  
Linear Trends

With global warming, climate change has tremendously changed the hydrological processes. To discover the non-linear trend of the natural runoff and its response to precipitation and temperature in the Yellow River Basin, the non-linear relationships among the runoff, precipitation and temperature are analyzed by the wavelet decomposition and reconstruction methods, partial correlation analysis and multiple linear regression analysis. The main findings of this study are: (1) The annual natural runoff, precipitation and temperature have the similar periods (27-year, 12-year), which indicates that the periodicity of the natural annual runoff has closely relationship with the regional climate change. (2) The annual runoff, precipitation and temperature exhibit five patterns non-linear variations at five time scales (1, 2, 4, 8, 16 years), that is to say, their non-linear trends are scale-dependent with time. (3) The annual natural runoff has a significant positive correlation with the precipitation and has a negative correlation with temperature. In addition, the runoff variation is more sensitive to change in precipitation than the change in temperature at all the five time scales. (4) Although the runoff and the climate change factors have non-linear trends at different time scales, the runoff has linear correlation with the temperature and the precipitation, especially at a large time scale.

scholarly journals Respiration of Russian soils: climatic drivers and response to climate change

2021 ◽  
pp. 147314
Author(s):  
Liudmila Mukhortova ◽  
Dmitry Schepaschenko ◽  
Elena Moltchanova ◽  
Anatoly Shvidenko ◽  
Nikolay Khabarov ◽  
...  
Keyword(s):  
Climate Change ◽  
Climatic Drivers

Selection of models to describe the temperature-dependent development of Neoleucinodes elegantalis (Lepidoptera: Crambidae) and its application to predict the species voltinism under future climate conditions

2021 ◽  
pp. 1-9
Author(s):  
Hevellyn Talissa dos Santos ◽  
Cesar Augusto Marchioro
Keyword(s):  
Climate Change ◽  
Linear Model ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Temperature Dependent ◽  
Dependent Development ◽  
Degree Day ◽  
Non Linear ◽  
The Impact

Abstract The small tomato borer, Neoleucinodes elegantalis (Guenée, 1854) is a multivoltine pest of tomato and other cultivated solanaceous plants. The knowledge on how N. elegantalis respond to temperature may help in the development of pest management strategies, and in the understanding of the effects of climate change on its voltinism. In this context, this study aimed to select models to describe the temperature-dependent development rate of N. elegantalis and apply the best models to evaluate the impacts of climate change on pest voltinism. Voltinism was estimated with the best fit non-linear model and the degree-day approach using future climate change scenarios representing intermediary and high greenhouse gas emission rates. Two out of the six models assessed showed a good fit to the observed data and accurately estimated the thermal thresholds of N. elegantalis. The degree-day and the non-linear model estimated more generations in the warmer regions and fewer generations in the colder areas, but differences of up to 41% between models were recorded mainly in the warmer regions. In general, both models predicted an increase in the voltinism of N. elegantalis in most of the study area, and this increase was more pronounced in the scenarios with high emission of greenhouse gases. The mathematical model (74.8%) and the location (9.8%) were the factors that mostly contributed to the observed variation in pest voltinism. Our findings highlight the impact of climate change on the voltinism of N. elegantalis and indicate that an increase in its population growth is expected in most regions of the study area.

Detecting Climate Fingerprints in Southern Ocean Carbon using a Biogeochemical Ocean Model

2021 ◽  
Author(s):  
Rebecca Wright ◽  
Corinne Le Quéré ◽  
Erik Buitenhuis ◽  
Dorothee Bakker
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Southern Ocean ◽  
Observational Data ◽  
Ecosystem Dynamics ◽  
Global Ocean ◽  
Subsurface Waters ◽  
Climatic Drivers ◽  
Ocean Carbon ◽  
And Storage

<p>The Southern Ocean plays an important role in the uptake, transport and storage of carbon by the global oceans. These properties are dominated by the response to the rise in anthropogenic CO<sub>2</sub> in the atmosphere, but they are modulated by climate variability and climate change. Here we explore the effect of climate variability and climate change on ocean carbon uptake and storage in the Southern Ocean. We assess the extent to which climate change may be distinguishable from the anthropogenic CO<sub>2</sub> signal and from the natural background variability. We use a combination of biogeochemical ocean modelling and observations from the GLODAPv2020 database to detect climate fingerprints in dissolved inorganic carbon (DIC).</p><p>We conduct an ensemble of hindcast model simulations of the period 1920-2019, using a global ocean biogeochemical model which incorporates plankton ecosystem dynamics based on twelve plankton functional types. We use the model ensemble to isolate the changes in DIC due to rising anthropogenic CO<sub>2</sub> alone and the changes due to climatic drivers (both climate variability and climate change), to determine their relative roles in the emerging total DIC trends and patterns. We analyse these DIC trends for a climate fingerprint over the past four decades, across spatial scales from the Southern Ocean, to basin level and down to regional ship transects. Highly sampled ship transects were extracted from GLODAPv2020 to obtain locations with the maximum spatiotemporal coverage, to reduce the inherent biases in patchy observational data. Model results were sampled to the ship transects to compare the climate fingerprints directly to the observational data.</p><p>Model results show a substantial change in DIC over a 35-year period, with a range of more than +/- 30 µmol/L. In the surface ocean, both anthropogenic CO<sub>2</sub> and climatic drivers act to increase DIC concentration, with the influence of anthropogenic CO<sub>2</sub> dominating at lower latitudes and the influence of climatic drivers dominating at higher latitudes. In the deep ocean, the anthropogenic CO<sub>2</sub> generally acts to increase DIC except in the subsurface waters at lower latitudes, while climatic drivers act to decrease DIC concentration. The combined fingerprint of anthropogenic CO<sub>2</sub> and climatic drivers on DIC concentration is for an increasing trend at the surface and decreasing trends in low latitude subsurface waters. Preliminary comparison of the model fingerprints to observational ship transects will also be presented.</p>

scholarly journals Plant Phenology and Its Anthropogenic and Natural Influencing Factors in Densely Populated Areas During the Economic Transition Period of China

2022 ◽  
Vol 9 ◽  
Author(s):  
Peijun Ju ◽  
Wenchao Yan ◽  
Jianliang Liu ◽  
Xinwei Liu ◽  
Liangfeng Liu ◽  
...  
Keyword(s):  
Climate Change ◽  
Economic Transition ◽  
Transition Period ◽  
Growing Season ◽  
Plant Phenology ◽  
Future Research ◽  
Urban Management ◽  
Climate Factors ◽  
Natural Ecosystems ◽  
The Impact

As a sensitive, observable, and comprehensive indicator of climate change, plant phenology has become a vital topic of global change. Studies about plant phenology and its responses to climate change in natural ecosystems have drawn attention to the effects of human activities on phenology in/around urban regions. The key factors and mechanisms of phenological and human factors in the process of urbanization are still unclear. In this study, we analyzed variations in xylophyta phenology in densely populated cities during the fast urbanization period of China (from 1963 to 1988). We assessed the length of the growing season affected by the temperature and precipitation. Temperature increased the length of the growing season in most regions, while precipitation had the opposite effect. Moreover, the plant-growing season is more sensitive to preseason climate factors than to annual average climate factors. The increased population reduced the length of the growing season, while the growing GDP increased the length of the growing season in most regions (8 out of 13). By analyzing the impact of the industry ratio, we found that the correlation between the urban management of emerging cities (e.g., Chongqing, Zhejiang, and Guizhou) and the growing season is more significant, and the impact is substantial. In contrast, urban management in most areas with vigorously developed heavy industry (e.g., Heilongjiang, Liaoning, and Beijing) has a weak and insignificant effect on plant phenology. These results indicate that different urban development patterns can influence urban plant phenology. Our results provide some support and new thoughts for future research on urban plant phenology.

scholarly journals How to deal with non-linear pathways towards energy futures

2019 ◽  
Vol 28 (3) ◽  
pp. 20-26
Author(s):  
Stefan Vögele ◽  
Witold-Roger Poganietz ◽  
Philip Mayer
Keyword(s):  
Policy Advice ◽  
Linear Extrapolation ◽  
Energy Futures ◽  
The Past ◽  
Non Linear ◽  
Simplifying Assumptions ◽  
Novel Approaches ◽  
The Creation ◽  
Linear Trends

Energy scenarios currently in use for policy advice are based on a number of simplifying assumptions. This includes, in particular, the linear extrapolation of trends. However, this approach ignores the fact that central variables were highly dynamic in the past. For an assessment of energy futures and the specification of measures, novel approaches are necessary which can implement non-linear trends. In this paper, we show how cross-impact balance (CIB) analysis can be applied to map dynamic trends. Using a small CIB model, we highlight the need for novel approaches in the creation and evaluation of energy futures and the possible contribution of CIB analysis.

scholarly journals Predicting Climate Change Using Response Theory: Global Averages and Spatial Patterns

2016 ◽  
Vol 166 (3-4) ◽  
pp. 1036-1064 ◽  
Author(s):  
Valerio Lucarini ◽  
Francesco Ragone ◽  
Frank Lunkeit
Keyword(s):  
Climate Change ◽  
Spatial Patterns ◽  
Response Theory

A New Interpretation of Depth—Age Profiles

2003 ◽  
Vol 14 (4) ◽  
pp. 407-414
Author(s):  
P. D. Townsend ◽  
R. Parish ◽  
A. P. Rowlands
Keyword(s):  
Climate Change ◽  
Characteristic Feature ◽  
Environmental Changes ◽  
Curve Shape ◽  
Non Linear ◽  
Depth Scale ◽  
New Interpretation

Dosimetry and other techniques provide depth–age profiles in materials as diverse as sediments and ice. A frequent characteristic feature of these plots is a non-linear curve with a foreshortened depth scale. Whilst the age analyses from the dosimetry do not present a problem, many authors have made subsequent assumptions on the basis of the curve shape with respect to climate and environmental changes. Such claims should be strongly questioned, as by using a model which includes the effects of compaction, most of the original curves transform into linear plots corresponding to constant depositional rates. The corrections and the implications for models of climate change are discussed.

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