scholarly journals Landscape Attributes Best Explain the Population Trend of Wintering Greater White-Fronted Goose (Anser albifrons) in the Yangtze River Floodplain

Land ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 865
Author(s):  
Sheng Chen ◽  
Yong Zhang ◽  
Amaël Borzée ◽  
Tao Liang ◽  
Manyu Zhang ◽  
...  
Keyword(s):  
Time Series Data ◽  
Driving Forces ◽  
Population Decline ◽  
Population Trend ◽  
Series Data ◽  
Suitable Habitat ◽  
Anser Albifrons ◽  
Lower Yangtze ◽  
Yangtze Floodplain ◽  
Landscape Attributes

Biodiversity in the Middle and Lower Yangtze Floodplain has critically decreased during the last several decades, driven by numerous determinants. Hence, identification of primary drivers of animal population decline is a priority for conservation. Analyzing long time-series data is a powerful way to assess drivers of declines, but the data are often missing, hampering effective conservation policymaking. In this study, based on twenty-four years (from 1996 to 2019) of annual maximal count data, we investigated the effects of climate and landscape changes on the increasing population trend of the Greater White-Fronted Goose (Anser albifrons) at a Ramsar site in the Middle and Lower Yangtze Floodplain, China. Our results showed that the availability of a suitable habitat and landscape attributes are the key driving forces affecting the population trend, while the effects of climate factors are weak. Specifically, increasing the area of suitable habitat and alleviating habitat fragmentation through a fishing ban policy may have provided a more suitable habitat to the geese, contributing to the increasing population trend. However, we also observed that the grazing prohibition policy implemented in 2017 at Shengjin Lake may have potentially negatively affected geese abundance, as grazing by larger herbivores may favor smaller geese species by modifying the vegetation community and structure. Based on our results, we suggest several practical countermeasures to improve the habitat suitability for herbivorous goose species wintering in this region.

scholarly journals Data-Driven Recommendations for Establishing Threshold Values for the NIS Trend Indicator in the Mediterranean Sea

Diversity ◽  
2022 ◽  
Vol 14 (1) ◽  
pp. 57
Author(s):  
Marika Galanidi ◽  
Argyro Zenetos
Keyword(s):  
Time Series Data ◽  
Driving Forces ◽  
Eastern Mediterranean ◽  
Time Lag ◽  
Series Data ◽  
Indigenous Species ◽  
Reference Period ◽  
Threshold Values ◽  
Basin Scale ◽  
The Mediterranean

In the present work, we analysed time series data on the introduction of new non-indigenous species (NIS) in the Mediterranean between 1970 and 2017, aiming to arrive at recommendations concerning the reference period and provisional threshold values for the NIS trend indicator. We employed regression analysis and breakpoint structural analysis. Our results confirm earlier findings that the reference conditions differ for the four Mediterranean subregions, and support a shortening of the reporting cycle from six to three years, with a two-year time lag for the ensuing assessment. Excluding Lessepsian fishes and parasites, the reference period, defined as the most recent time segment with stable mean new NIS values, was estimated as 1997–2017 for the eastern Mediterranean, 2012–2017 for the central Mediterranean, 2000–2017 for the Adriatic and 1970–2017 for the western Mediterranean. These findings are interpreted primarily on the basis of a basin scale temperature regime shift in the late 1990s, shifts in driving forces such as shellfish culture, and as a result of intensified research efforts and citizen scientist initiatives targeting NIS in the last decade. The threshold values, i.e., the three-year average new NIS values during the reference period, are indicative and will ultimately depend on the choice of species and pathways to be used in the calculations. This is discussed through the prism of target setting in alignment with specific management objectives.

The impacts of China’s FDI on employment in Thailand’s industrial sector

2016 ◽  
Vol 9 (1) ◽  
pp. 60-84 ◽  
Author(s):  
Mathavee Keorite ◽  
Mohamed Moubarak
Keyword(s):  
Time Series Data ◽  
Driving Forces ◽  
Dominant Role ◽  
Government Expenditure ◽  
Impulse Response Function ◽  
Industrial Sector ◽  
Series Data ◽  
Content Type ◽  
Reduction Potentials ◽  
Industrial Sectors

Purpose – This study aims to analyze the effect of inward foreign direct investment (FDI) on new job creation. This study pays attention to factors interrelated to China’s FDI by using the case of Thailand. Design/methodology/approach – Using time series data from 2001 to 2014, this paper explores the driving forces and reduction potentials of employment in Thailand’s industrial sector with consideration for dynamic changes within the vector autoregression model. Findings – The results show that government expenditure plays a dominant role in increasing employment in Thailand’s industrial sector and exports plays a dominant role in decreasing employment in Thailand’s industrial sector. All variables are co-integrated and the analysis of the impulse–response function also turns out to be synchronous. Furthermore, in the short term, exports are more critical than China’s FDI in industrial sectors in reduction potentials of employment in Thailand’s industrial. Practical/implications – Policies should be devised to increase skilled labour and improve the equality of infrastructure in the country to attract more FDI into the economy and for quick adjustment purposes in case of shock to the system. Originality/value – The paper uncovers some important factors influencing employment in Thailand’s industrial sector under study and provides a guide-map for policymakers.

scholarly journals Multiscale monsoon variability during the last two climatic cycles inferred from Chinese loess and speleothem records

2014 ◽  
Vol 10 (6) ◽  
pp. 4623-4646
Author(s):  
Y. Li ◽  
N. Su ◽  
L. Liang ◽  
L. Ma ◽  
Y. Yan ◽  
...  
Keyword(s):  
Grain Size ◽  
North Atlantic ◽  
Time Series Data ◽  
Driving Forces ◽  
East Asian Monsoon ◽  
Series Data ◽  
Chinese Loess ◽  
Ice Volume ◽  
Climatic Cycles ◽  
Monsoon Variability

Abstract. The East Asian Monsoon exhibits a significant variability on timescales ranging from tectonic to centennial as inferred from Chinese loess, stalagmite and marine records. However, the relative contributions and plausible driving forces of the signals at different timescales remain poorly investigated. Here, we spectrally decompose time series data on loess grain size and speleothem δ18O records over the last two climatic cycles and correlate the decomposed components with possible driving parameters including the ice volume, insolation and North Atlantic cooling. Based on the spectral analysis of these two proxies, we tentatively identified six components of the signals corresponding to various forcing of ice volume (> 50 kyr), obliquity (50–30 kyr), precession (30–9 kyr), North Atlantic cooling (9–3 kyr and 3–1 kyr), and a centennial residual. The relative contributions of each component differ significantly between loess grain size and speleothem δ18O records. Glacial and orbital components are dominant in the loess grain size, which implies that both ice volume and insolation have distinctive impacts on the winter monsoon variability in contrast to the predominant precession impact on the summer monsoon patterns. Moreover, the millennial components are evident with variances of 11 and 16% in the loess grain size and speleothem δ18O records, respectively. A comparison of the millennial-scale signals in these two proxies reveals that abrupt changes in the winter and summer monsoons over the last 260 kyr share common features and similar driving forces linked to high-latitude Northern Hemisphere climate.

Transformation in Vegetation and Urban Sprawl in Gotan and Surrounding

2021 ◽  
pp. 111-124
Author(s):  
Rizwan Ahmad ◽  
Ramaraju Sudarshana
Keyword(s):  
Urban Sprawl ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Time Series Data ◽  
Driving Forces ◽  
Landsat Tm ◽  
Series Data ◽  
Monitoring Frequency ◽  
Government Sector

The main driving forces associated with transformation of vegetation cover and urban sprawl, are undoubtedly climate change and human intervention. Finding the truth behind transformation of Gotan, Rajasthan Landsat TM/ETM+ data of the years 1987,1990, 1995, 2000, 2003, 2010, 2015, and 2018 were used. These time series data comprising total of nine scenes were selected to measure the urban and green cover transformation in the past four decades. Landsat TM/ETM+ data were used because it is inexpensive, with high monitoring frequency and covers large areas. The Normalized Difference Vegetation Index (NDVI) of 1987–2018, derived from the remote sensing dataset along with the application of statistical methods and GIS techniques, were used to quantify vegetation cover change. The results show that human-induced factors can explain most variations at sites with significant cover change. It has been a well-known fact that sustainable development presents a system in order to accomplish economic growth, bring about social justice, implement environmental awareness and most certainly the fortification of government sector.

Customization of the OSSEM model for application to annual data from the Talar aquifer, Northern Iran

2015 ◽  
Vol 15 (3) ◽  
pp. 656-666
Author(s):  
Nazila Sedaei ◽  
Abolghasem Akbari ◽  
Leila Sedaei ◽  
Jonathan Peter Cox
Keyword(s):  
Time Series ◽  
Water Resources ◽  
Water Deficit ◽  
Time Series Data ◽  
Driving Forces ◽  
Anthropogenic Activities ◽  
Government Support ◽  
Series Data ◽  
Annual Data ◽  
Water Resource System

There are several principal driving forces behind the damaging coastal water resources depletion in many countries, including: high population growth, degrading water resources due to overexploitation and contamination, lack of awareness among local beneficiaries regarding sustainable management, and deficient government support and enforcement of conservation programs. To ensure a water resource system is productive in coastal areas, holistic and comprehensive management approaches are required. To address the aforementioned issues, a combined methodology which considers anthropogenic activities, together with environmental problems defined as the Overall Susceptibility Socio-Ecological System Environmental Management (OSSEM) has been investigated. The OSSEM model has been applied successfully in Spain based upon daily time series data. This research is ground breaking in that it integrates the OSSEM model in a geographic information system (GIS) environment to assess the groundwater contamination based on annual time series data and the assessment of system management by means of an overall susceptibility index (OSI). Centered on OSI indicators, the renewal, salinization and water deficit potentials in the Talar aquifer were estimated to be 4.89%, 4.61%, and 3.99%, respectively. This data demonstrates a high susceptibility in terms of environmental pollution, salinization, and water deficit.

CONSANGUINEOUS MARRIAGE IN JORDAN: AN UPDATE

2017 ◽  
Vol 50 (4) ◽  
pp. 573-578 ◽  
Author(s):  
M. Mazharul Islam ◽  
Faisal M. Ababneh ◽  
MD Hasinur Rahaman Khan
Keyword(s):  
Time Series Data ◽  
Driving Forces ◽  
Economic Status ◽  
Family Health ◽  
Secondary Level ◽  
Consanguineous Marriage ◽  
Series Data ◽  
Level Of Education ◽  
Age At Marriage ◽  
Rural Place

SummaryThis study examined the recent level, trends and determinants of consanguineous marriage in Jordan using time-series data from the Jordan Population and Family Health Surveys (JPFHSs). According to the 2012 JPFHS, 35% of all marriages were consanguineous in Jordan in 2012. There has been a declining trend in consanguinity in the country, with the rate decreasing from a level of 57% in 1990. Most consanguineous marriage in 2012 were first cousin marriages, constituting 23% of all marriages and 66% of all consanguineous marriages. The data show that women with a lower age at marriage, older marriage cohort, larger family size, less than secondary level of education, rural place of residence, no employment, no exposure to mass media, a monogamous marriage, a husband with less than higher level of education and lower economic status, and those from the Badia region, were more likely to have a consanguineous marriage. Increasing age at marriage, level of education, urbanization and knowledge about the health consequences of consanguinity, and the ongoing socioeconomic and demographic transition in the country, will be the driving forces for further decline in consanguinity in Jordan.

scholarly journals Investment, Poverty and Growth Nexus in Pakistan: Empirical Evidence from ARDL Modeling Approach to Co-Integration

2020 ◽  
Vol 4 (1) ◽  
pp. 1-1
Author(s):  
Hina Ali ◽  
Imran Sharif
Keyword(s):  
Time Series Data ◽  
Driving Forces ◽  
Growth Effect ◽  
Series Data ◽  
Short Term ◽  
Modeling Approach ◽  
Long Run ◽  
Short Run ◽  
Adf Test

This study analyzes the nexus of investment, poverty and growth in Pakistan. It will develop comprehensive macro economic model of Pakistan economy with the desire of amplification and provided that a long-term result for the determined investment-poverty-growth discrepancy veterans. The significant level of investment and sustained economic growth may be the major driving forces for poverty decrease in Pakistan. The level of investment also assists the poor through a direct allocation influence as well as tortuous growth effect, in both the long run and short run. To detect the long term and short term effects of economic development, poverty and investment, an ARDL modeling approach to co- integration is functional, which is the suitable technique  in excess of method of integration after examining the stationary level of the data through ADF Test. The bound testing approach is exploited for cointegration to analyze the presence of long term association amid variables and ECM models are verbalized for short term analysis. The model is predictable with time-series data from 1972 to 2013 confine mutually the long-run and short-run forceful goods of the economy. The model is subjected to a sequence of strategy situation  that assesses a mixture of options for government to recover the prolific ability of the economy, thus attain continued hasten growth and a decrease in  Pakistan`s poverty. JEL Classification Codes: G12, G 14

scholarly journals Assessment of OSCAT winds for coastal circulation on the north western continental shelf of India

2014 ◽  
Vol XL-8 ◽  
pp. 1073-1077
Author(s):  
M. Salim ◽  
K. Nagendra ◽  
S. Bansal ◽  
R. K. Nayak ◽  
M. S. Rao ◽  
...  
Keyword(s):  
Continental Shelf ◽  
Annual Cycle ◽  
Time Series Data ◽  
Driving Forces ◽  
Circulation Model ◽  
Series Data ◽  
Coastal Circulation ◽  
Tracer Transport ◽  
The North ◽  
Wind Driven Currents

Winds and tides are the major driving forces of the circulation in the coastal and marginal seas. Data Interpolating Variation Analysis (DIVA) method is used to generate spatial and time series data of sea surface winds for the period 2010–2013 at daily time scale from the OSCAT observations. Validity and consistency of the data were examined against the in situ observations and ECMWF re-analysis at different time scales. Amplitude of semi-annual cycle of OSCAT winds in the coastal domain is 30 % larger than the ECMWF winds while the amplitude of annual cycle of OSCAT winds is 20 % smaller than the ECMWF winds. On the open oceans, intensity of respective semi-annual cycles are mostly similar while annual cycle of OSCAT wind is 20 % smaller than the ECMWF winds. Wind driven currents over the western continental shelf of India were simulated by forcing OSCAT and ECMWF winds to a coastal circulation model. It is observed that the mean seasonal circulations from both the simulations are identical spatial pattern however the magnitude of simulated currents based on OSCAT winds are much stronger than ECMWF wind forcing. These currents used in a lagrangian tracer transport code to model the oil-spill events occurred in this region. It revealed that OSCAT based ocean currents has performed better in simulating the trajectory than the ECMWF wind driven currents.

Graphical Exploratory Data Analysis for Categorical Longitudinal and Time Series Data

2013 ◽  
Author(s):  
Stephen J. Tueller ◽  
Richard A. Van Dorn ◽  
Georgiy Bobashev ◽  
Barry Eggleston
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Exploratory Data Analysis ◽  
Time Series Data ◽  
Series Data ◽  
Exploratory Data

Some statistical and CI models to predict chaotic high-frequency financial data

2020 ◽  
Vol 39 (5) ◽  
pp. 6419-6430
Author(s):  
Dusan Marcek
Keyword(s):  
Time Series Data ◽  
Moving Average ◽  
Methodological Approach ◽  
Back Propagation ◽  
Large Data ◽  
Series Data ◽  
Data Set ◽  
Training Time ◽  
Optimal Population ◽  
Forecast Time

To forecast time series data, two methodological frameworks of statistical and computational intelligence modelling are considered. The statistical methodological approach is based on the theory of invertible ARIMA (Auto-Regressive Integrated Moving Average) models with Maximum Likelihood (ML) estimating method. As a competitive tool to statistical forecasting models, we use the popular classic neural network (NN) of perceptron type. To train NN, the Back-Propagation (BP) algorithm and heuristics like genetic and micro-genetic algorithm (GA and MGA) are implemented on the large data set. A comparative analysis of selected learning methods is performed and evaluated. From performed experiments we find that the optimal population size will likely be 20 with the lowest training time from all NN trained by the evolutionary algorithms, while the prediction accuracy level is lesser, but still acceptable by managers.

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