scholarly journals Roadkill in a time of pandemic: the analysis of wildlife-vehicle collisions reveals the differential impact of COVID-19 lockdown over mammal assemblages

2021 ◽  
Author(s):  
Boštjan Pokorny ◽  
Jacopo Cerri ◽  
Elena Bužan
Keyword(s):  
Wild Boar ◽  
Large Scale ◽  
Time Series Data ◽  
Roe Deer ◽  
Biological Significance ◽  
Additive Models ◽  
Series Data ◽  
Vehicle Collisions ◽  
Related Mortality

Collisions with vehicles are a major anthropogenic cause of mortality for wildlife, with conservation and evolutionary implications. Due to the COVID-19 pandemic, many countries worldwide enforced lockdowns which importantly reduced traffic, and therefore had unprecedented consequences for global wildlife populations. We modeled how the two lockdown periods in spring and autumn 2020 influenced wildlife-vehicle collisions in Slovenia (central Europe), by comparing long-term (for the period 2010–2020) and high-quality time series data on road mortality of seven mammalian species: European roe deer (n = 53,259),red fox (n = 9,889), European badger (n = 5,170), brown hare (n = 5,050), stone marten (n = 4,267), wild boar (n = 1,188), and red deer (n = 1,088). We decomposed 2010–2019 data through autoregressive Bayesian Generalized Additive Models, and then we compared 2020 data to forecasts, aiming to estimate anomalies in number of collisions during both lockdown periods. During the spring lockdown (16 March – 30 April 2020), we observed far less collisions than in the 2010–2019 average as well as in 2020 forecasts, for roe deer and badger. In the autumnal lockdown (20 October – 31 December 2020), we observed significantly less collisions for roe deer and wild boar. Traffic reduction in both lockdown periods had a major impact on roe deer, which in autumn and spring 2020 experienced 270–330 less road-related mortality cases than expected. COVID-19 lockdown reduced traffic-related mortality for the majority of studied species. In some species, this decrease reached a magnitude of biological significance, which can have long-term repercussions on both evolution and management. Obviously, large-scale sanitary policies, imposing a reduction to human mobility, can have large-scale impacts on wildlife. As pandemics may increase in the next decades, we encourage further research exploring the consequences of their enforcement over global change and wildlife conservation and evolution.

Economic Turmoil in Islamic Banking Investment

ETIKONOMI ◽  
2020 ◽  
Vol 19 (2) ◽  
Author(s):  
Budiandru Budiandru ◽  
Sari Yuniarti
Keyword(s):  
Interest Rates ◽  
Stock Price ◽  
Time Series Data ◽  
Series Data ◽  
Islamic Banking ◽  
Vector Error Correction ◽  
Investment Financing ◽  
Vector Error ◽  
Operational Activities

Investment financing is one of the operational activities of Islamic banking to encourage the real sector. This study aims to analyze the effect of economic turmoil on investment financing, analyze the response to investment financing, and analyze each variable's contribution in explaining the diversity of investment financing. This study uses monthly time series data from 2009 to 2020 using the Vector Error Correction Model (VECM) analysis. The results show that the exchange rate, inflation, and interest rates significantly affect Islamic banking investment financing in the long term. The response to investment financing is the fastest to achieve stability when it responds to shocks to the composite stock price index. Inflation is the most significant contribution in explaining diversity in investment financing. Islamic banking should increase the proportion of funding for investment. Customers can have a larger business scale to encourage economic growth, with investment financing increasing.JEL Classification: E22, G11, G24How to Cite:Budiandru., & Yuniarti, S. (2020). Economic Turmoil in Islamic Banking Investment. Etikonomi: Jurnal Ekonomi, 19(2), xx – xx. https://doi.org/10.15408/etk.v19i2.17206.

scholarly journals Assessing Stream-Aquifer Connectivity in a Coastal California Watershed

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 416
Author(s):  
Bwalya Malama ◽  
Devin Pritchard-Peterson ◽  
John J. Jasbinsek ◽  
Christopher Surfleet
Keyword(s):  
Time Series ◽  
Spectral Analysis ◽  
Water Level ◽  
Time Series Data ◽  
Series Data ◽  
Low Permeability ◽  
Pumping Tests ◽  
Stream Flows ◽  
The Impact

We report the results of field and laboratory investigations of stream-aquifer interactions in a watershed along the California coast to assess the impact of groundwater pumping for irrigation on stream flows. The methods used include subsurface sediment sampling using direct-push drilling, laboratory permeability and particle size analyses of sediment, piezometer installation and instrumentation, stream discharge and stage monitoring, pumping tests for aquifer characterization, resistivity surveys, and long-term passive monitoring of stream stage and groundwater levels. Spectral analysis of long-term water level data was used to assess correlation between stream and groundwater level time series data. The investigations revealed the presence of a thin low permeability silt-clay aquitard unit between the main aquifer and the stream. This suggested a three layer conceptual model of the subsurface comprising unconfined and confined aquifers separated by an aquitard layer. This was broadly confirmed by resistivity surveys and pumping tests, the latter of which indicated the occurrence of leakage across the aquitard. The aquitard was determined to be 2–3 orders of magnitude less permeable than the aquifer, which is indicative of weak stream-aquifer connectivity and was confirmed by spectral analysis of stream-aquifer water level time series. The results illustrate the importance of site-specific investigations and suggest that even in systems where the stream is not in direct hydraulic contact with the producing aquifer, long-term stream depletion can occur due to leakage across low permeability units. This has implications for management of stream flows, groundwater abstraction, and water resources management during prolonged periods of drought.

The Classic Maya Collapse: Testing Class Conflict Hypotheses

1980 ◽  
Vol 45 (2) ◽  
pp. 246-267 ◽  
Author(s):  
Robert L. Hamblin ◽  
Brian L. Pitcher
Keyword(s):  
Large Scale ◽  
Time Series Data ◽  
Classic Maya ◽  
Class Conflict ◽  
Series Data ◽  
Geographical Patterns ◽  
Historical Societies ◽  
Testing Class ◽  
Lowland Area ◽  
Maya Collapse

Several lines of archaeological evidence are presented in this paper to suggest the existence of class warfare among the Classic Maya and of issues that historically have been associated with class conflict. This evidence indicates that class warfare may have halted the rule of the monument-producing, or Classic, elites and precipitated the depopulation of the lowland area. The theory is evaluated quantitatively by testing for time-related mathematical patterns that have been found to characterize large-scale conflicts in historical societies. The information used in the evaluation involves the time series data on the duration of rule by Classic elites as inferred from the production of monuments with Long Count dates at a sample of 82 ceremonial centers. The analyses confirm that the Maya data do exhibit the temporal and geographical patterns predicted from the class conflict explanation of the Classic Maya collapse. Alternative predictions from the other theories are considered but generally not found to be supported by these data.

Welfare Use in Japan: Trends and Determinants

2007 ◽  
pp. 88
Author(s):  
Wataru Suzuki ◽  
Yanfei Zhou
Keyword(s):  
Time Series ◽  
Longitudinal Data ◽  
Time Series Data ◽  
Positive Impact ◽  
Series Data ◽  
Negative Effects ◽  
Long Time ◽  
Welfare Use ◽  
The Impact

This article represents the first step in filling a large gap in knowledge concerning why Public Assistance (PA) use recently rose so fast in Japan. Specifically, we try to address this problem not only by performing a Blanchard and Quah decomposition on long-term monthly time series data (1960:04-2006:10), but also by estimating prefecturelevel longitudinal data. Two interesting findings emerge from the time series analysis. The first is that permanent shock imposes a continuously positive impact on the PA rate and is the main driving factor behind the recent increase in welfare use. The second finding is that the impact of temporary shock will last for a long time. The rate of the use of welfare is quite rigid because even if the PA rate rises due to temporary shocks, it takes about 8 or 9 years for it to regain its normal level. On the other hand, estimations of prefecture-level longitudinal data indicate that the Financial Capability Index (FCI) of the local government2 and minimum wage both impose negative effects on the PA rate. We also find that the rapid aging of Japan's population presents a permanent shock in practice, which makes it the most prominent contribution to surging welfare use.

Does Public Debt Service Expenditure Crowd-Out Economic Growth? Empirical Evidence from an African Developing Country

2019 ◽  
Vol 64 (3) ◽  
pp. 23-38
Author(s):  
Talknice Saungweme ◽  
Nicholas M. Odhiambo
Keyword(s):  
Economic Growth ◽  
Public Debt ◽  
Time Series Data ◽  
Policy Formulation ◽  
Debt Service ◽  
Series Data ◽  
Long Run ◽  
Short Run ◽  
The Impact

Abstract This paper contributes to the ongoing debate on the impact of public debt service on economic growth; and it provides an evidence-based approach to public policy formulation in Zimbabwe. The empirical analysis was performed by applying the autoregressive distributed lag (ARDL) technique to annual time-series data from 1970 to 2017. The study findings reveal that the impact of public debt service on economic growth in Zimbabwe is negative in the short run but positive in the long run. The results are suggestive of the existence of a crowding-out effect of public debt service in Zimbabwe in the short run and a crowding-in effect in the long run. In view of these findings, the government should consider fiscal and financial policies that promote a constant supply of long-term finance, long-term fixed investments, and extension of a government securities maturity structure so as to ensure sustainable short- and long-term public debt service expenditures. The study further recommends the strengthening of non-distortionary revenue mobilisation reforms to reduce market distortions and boost domestic investment.

scholarly journals Beyond the implications of Grand Ethiopian Renaissance Dam filling policies

2021 ◽  
Vol 7 (3) ◽  
pp. 313-330
Author(s):  
Abay Yimere ◽  
◽  
Engdawork Assefa ◽  
Keyword(s):  
Time Series Data ◽  
Water Levels ◽  
Series Data ◽  
Future Climate Change ◽  
Policy Debate ◽  
International Treaty ◽  
Term Operation ◽  
Operating Level ◽  
Minimum Operating

<abstract> <p>The Grand Ethiopian Renaissance Dam (GERD) in Ethiopia and High Aswan Dam (HAD) in Egypt both operate on the Nile River, independent of a governing international treaty or agreement. As a result, the construction of the GERD, the Earth's eighth largest dam, ignited a furious debate among Ethiopia, Sudan, and Egypt on its filling policies and long-term operation. Ethiopia and Egypt's stance on the Nile River's water resources, combined with a nationalistic policy debate on the GERD's filling policies and long-term operation, has severely affected progress toward reaching agreeable terms before the first round of GERD filling was completed. These three countries continue to debate on the terms of agreement for the second round of GERD filling, scheduled to start by July 2021. We examined the GERD filling strategy for five- and six-year terms using time series data for the periods 1979–1987 and 1987–1992 to combine analyses for dry and wet seasons and investigate the potential impacts of filling the GERD above the downstream HAD using four HAD starting water levels. A model calibrated using MIKE Hydro results shows that during both five- and six-year terms of future GERD filling, Egypt would not need to invoke the HAD's minimum operating level. We pursued a narrative approach that appeals to both a technical and non-technical readership, and our results show the urgent need for cooperation at both policy and technical levels to mitigate and adapt to future climate change through the development of climate-proof agreements. Moreover, the results call for the riparian countries to move away from the current nationalistic policy debate approach and pursue a more cooperative, economically beneficial, and climate adaptive approach.</p> </abstract>

scholarly journals Evidence Graphs: Supporting Transparent and FAIR Computation, with Defeasible Reasoning on Data, Methods and Results

2021 ◽  
Author(s):  
Sadnan Al Manir ◽  
Justin Niestroy ◽  
Maxwell Adam Levinson ◽  
Timothy Clark
Keyword(s):  
Time Series ◽  
Large Scale ◽  
Time Series Data ◽  
Predictive Analytics ◽  
Defeasible Reasoning ◽  
Series Data ◽  
Inference Rules ◽  
Deep Networks ◽  
Evidence Graph ◽  
Over Time

Introduction: Transparency of computation is a requirement for assessing the validity of computed results and research claims based upon them; and it is essential for access to, assessment, and reuse of computational components. These components may be subject to methodological or other challenges over time. While reference to archived software and/or data is increasingly common in publications, a single machine-interpretable, integrative representation of how results were derived, that supports defeasible reasoning, has been absent. Methods: We developed the Evidence Graph Ontology, EVI, in OWL 2, with a set of inference rules, to provide deep representations of supporting and challenging evidence for computations, services, software, data, and results, across arbitrarily deep networks of computations, in connected or fully distinct processes. EVI integrates FAIR practices on data and software, with important concepts from provenance models, and argumentation theory. It extends PROV for additional expressiveness, with support for defeasible reasoning. EVI treats any com- putational result or component of evidence as a defeasible assertion, supported by a DAG of the computations, software, data, and agents that produced it. Results: We have successfully deployed EVI for very-large-scale predictive analytics on clinical time-series data. Every result may reference its own evidence graph as metadata, which can be extended when subsequent computations are executed. Discussion: Evidence graphs support transparency and defeasible reasoning on results. They are first-class computational objects, and reference the datasets and software from which they are derived. They support fully transparent computation, with challenge and support propagation. The EVI approach may be extended to include instruments, animal models, and critical experimental reagents.

scholarly journals THE TESTING OF MONEY NEUTRALITY IN ECONOMIC GROWTH OF INDONESIA

2017 ◽  
Vol 1 (1) ◽  
pp. 12
Author(s):  
Muammil Sun’an ◽  
Amran Husen
Keyword(s):  
Economic Growth ◽  
Time Series Data ◽  
Output Growth ◽  
Broad Sense ◽  
Series Data ◽  
Analysis Tool ◽  
Real Sector ◽  
Short Term ◽  
Correction Model

<p>This study aim is to test the money neutrality in a narrow sense (M1) and a broad sense (M2) to the growth of output (GDP) in Indonesia, both in short term and long term. This research uses quarterly time series data at 2010 - 2016 periods. The analysis tool used is Error Correction Model (ECM). The results show that short-term money supply (M1 and M2) affect on output growth. However, in the long term, only money circulation in a broad sense (M2) affects on output growth, which also means that money is not neutral because it affects the real sector (GDP).</p><p> <strong>Keywords:</strong> M1, M2, Population, Capital, and Economic Growth.</p>

scholarly journals The impact of bank-specific and macroeconomic variables on profitability of Islamic rural bank in Indonesia

2019 ◽  
Vol 5 (3) ◽  
Author(s):  
Muhammad Sanusi
Keyword(s):  
Banking Sector ◽  
Time Series Data ◽  
Series Data ◽  
Estimation Model ◽  
Policy Makers ◽  
Vector Error Correction ◽  
Macroeconomic Variables ◽  
Vector Error ◽  
The Impact

This paper investigates the impact of bank-specific and macroeconomic variables on the profitability of Islamic rural bank (BPRS) in Indonesia. Using monthly time series data from January 2010 - December 2018. The estimation model used is a vector error correction model to analyze the long-term and short-term relationships between bank-specific and macroeconomic variables on the profitability of Islamic rural bank. The results showed that CAR and LnTA had a significant positive relationship, while NPF, BOPO and IPI had a negative and significant relationship to the profitability of Islamic rural banks. But FDR and Inflation variables are not significantly related to the profitability of Islamic rural bank. The results leave implications for policy makers, investors and banking sector managers. Based on evidence that bank profitability is more influenced by internal banks (as specific as banks), this research can help Islamic rural banks to help them understand which factors are important to be analyzed to obtain higher profitability.

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