Abundance patterns (1984-1987 / 1994-1998) of polychaete worms (Annelida) from an estuarine tidal flat, Pacific, Costa Rica

The objectives of this report are to provide an updated list of the annelid polychaete worm species found at a tropical estuarine intertidal flat, describe long term oscillations of 11 of the species, and the impact of red tides as evidenced by PCA. From 1984 to 1987 (49 dates) 14 sediment cores (17.7 cm2 – 15 cm deep) were collected per date at low tide from a 400 m2 muddy-sand plot in the Gulf of Nicoya estuary (10oN-85oW), Pacific, Costa Rica. All cores were fixed in Rose Bengal stained formalin and sieved thru a 500 micron mesh screen. A total of 43 species of polychaetes were found and distributed among 25 families and 6600 individuals, of which 80% were represented by: Mediomastus californiensis (32.4%), Caraziella calafia (20.3%), Paraprionospio alata (9.2%), Scolotema tetraura (5.9%), Gymnonereis crosslandi (4.9%), Spiophanex duplex (3.8%), and Glycinde armigera (3.5%). M. californiensis was numerically dominant during most of the sampling dates. The Spionidae (6), Phyllodocidae (4), and Nereididae (3) were the more speciose polychaete families. Populations of all species were patchy in space and time. The abundance patterns of 11 species are illustrated for the 1984-1987 data set. These patterns may reflect declining populations at the beginning of 1984 perhaps influenced by the strong 1982-1983 ENSO event. During 1985 red tides may have influenced the abundances of polychaetes as indicated by the results of a PCA. This is the first time that population patterns of nine species of intertidal polychaetes over a three year period, and the impact of red tides on these worms are reported for this region of the eastern Pacific. General Additive Models (GAM) were applied to the abundances of M. californiensis and P. alata found during 1984-1987 and to additional data from 1994 to 1996 (28 dates) The GAM approach confirmed ealier observations of seasonal oscillations of these species during 1984-1987, but these trends were not found during 1994-1998. Previously unnoticed underlying patterns of unknown origin were also detected by the application of GAM. The theoretical framework needed for the interpretation of results from tropical benthic surveys could improve significantly from more long term monitoring. Long term abundance data is essential to evaluate the impacts of anthropogenic activities in estuaries.

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An improved glyoxal retrieval from OMI measurements

Atmospheric Measurement Techniques ◽

10.5194/amt-7-4133-2014 ◽

2014 ◽

Vol 7 (12) ◽

pp. 4133-4150 ◽

Cited By ~ 28

Author(s):

L. M. A. Alvarado ◽

A. Richter ◽

M. Vrekoussis ◽

F. Wittrock ◽

A. Hilboll ◽

...

Keyword(s):

Cross Sections ◽

Anthropogenic Activities ◽

Absorption Cross ◽

Fire Event ◽

Data Set ◽

Polynomial Degree ◽

Temperature Boundary ◽

Sensitivity Tests ◽

Radiative Power ◽

The Impact

Abstract. Satellite observations from the SCIAMACHY, GOME-2 and OMI spectrometers have been used to retrieve atmospheric columns of glyoxal (CHOCHO) with the DOAS method. High CHOCHO levels were found over regions with large biogenic and pyrogenic emissions, and hot-spots have been identified over areas of anthropogenic activities. This study focuses on the development of an improved retrieval for CHOCHO from measurements by the OMI instrument. From sensitivity tests, a fitting window and a polynomial degree are determined. Two different approaches to reduce the interference of liquid water absorption over oceanic regions are evaluated, achieving significant reduction of the number of negative columns over clear water regions. The impact of using different absorption cross-sections for water vapour is evaluated and only small differences are found. Finally, a high-temperature (boundary layer ambient: 294 K) absorption cross-section of nitrogen dioxide (NO2) is introduced in the DOAS retrieval to account for potential interferences of NO2 over regions with large anthropogenic emissions, leading to improved fit quality over these areas. A comparison with vertical CHOCHO columns retrieved from GOME-2 and SCIAMACHY measurements over continental regions is performed, showing overall good consistency. However, SCIAMACHY CHOCHO columns are systematically higher than those obtained from the other instruments. Using the new OMI CHOCHO data set, the link between fires and glyoxal columns is investigated for two selected regions in Africa. In addition, mapped averages are computed for a fire event in Russia between mid-July and mid-August 2010. In both cases, enhanced CHOCHO levels are found in close spatial and temporal proximity to elevated levels of MODIS fire radiative power, demonstrating that pyrogenic emissions can be clearly identified in the new OMI CHOCHO product.

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Effects of agricultural credit on wheat productivity of small farms in Sindh, Pakistan

Agricultural Finance Review ◽

10.1108/afr-02-2017-0010 ◽

2018 ◽

Vol 78 (5) ◽

pp. 592-610 ◽

Cited By ~ 17

Author(s):

Abbas Ali Chandio ◽

Yuansheng Jiang ◽

Feng Wei ◽

Xu Guangshun

Keyword(s):

Wheat Yield ◽

Considerable Proportion ◽

Small Scale ◽

Small Farms ◽

Short Term ◽

Agricultural Credit ◽

Data Set ◽

Content Type ◽

The Impact

Purpose The purpose of this paper is to evaluate the impact of short-term loan (STL) vs long-term loan (LTL) on wheat productivity of small farms in Sindh, Pakistan. Design/methodology/approach The econometric estimation is based on cross-sectional data collected in 2016 from 18 villages in three districts, i.e. Shikarpur, Sukkur and Shaheed Benazirabad, Sindh, Pakistan. The sample data set consist of 180 wheat farmers. The collected data were analyzed through different econometric techniques like Cobb–Douglas production function and Instrumental variables (two-stage least squares) approach. Findings This study reconfirmed that agricultural credit has a positive and highly significant effect on wheat productivity, while the short-term loan has a stronger effect on wheat productivity than the long-term loan. The reasons behind the phenomenon may be the significantly higher usage of agricultural inputs like seeds of improved variety and fertilizers which can be transformed into the wheat yield in the same year. However, the LTL users have significantly higher investments in land preparation, irrigation and plant protection, which may lead to higher wheat production in the coming years. Research limitations/implications In the present study, only those wheat farmers were considered who obtained agricultural loans from formal financial institutions like Zarai Taraqiati Bank Limited and Khushhali Bank. However, in the rural areas of Sindh, Pakistan, a considerable proportion of small-scale farmers take credit from informal financial channels. Therefore future researchers should consider the informal credits as well. Originality/value This is the first paper to examine the effects of agricultural credit on wheat productivity of small farms in Sindh, Pakistan. This paper will be an important addition to the emerging literature regarding effects of credit studies.

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The colonial exports pattern, institutions and current economic performance

Journal of Economic Studies ◽

10.1108/jes-06-2020-0266 ◽

2020 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Tania El Kallab ◽

Cristina Terra

Keyword(s):

Human Capital ◽

Economic Development ◽

Resource Curse ◽

Data Set ◽

Content Type ◽

Long Run ◽

French Colonies ◽

Colonial Institutions ◽

The Impact

PurposeThis paper explores the role of colonial heritage on long-term economic development from a resource-curse perspective. The authors investigate the impact of colonial exports on long-term economic development through two channels: (1) a direct impact of the economic dependency on natural resources and (2) an indirect impact via its effect on colonial institutions, which persisted over time and influenced current economic development.Design/methodology/approachTo address this issue, the authors use an original data set on French bilateral trade from 1880 to 1912. The authors use partial least square structural equation modeling (PLS-SEM) in the empirical analysis, so that the authors are able to construct latent variables (LVs) for variables that are not directly observable, such as the quality of institutions.FindingsThe authors find that exports of primary goods to France had a negative impact on colonial institutions and that for French colonies, this impact was driven by minerals exports. Despite its impact on colonial institutions, exports of French colonies had no significant indirect impact on their current institutions. The authors find no significant direct impact of colonial trade on current development for French colonies. Finally, colonial exports of manufactured products had no significant impact on colonial institutions among French colonies and a positive impact among non-French ones.Research limitations/implicationsResearch implications regarding the findings of this paper are, namely, that the relative poor performance within French colonies today cannot be attributed to the extraction of raw materials a century ago. However, human capital and institutional development, instead of exports, are more relatively important for long-term growth. Some limitations in trying to determine the simultaneous relationship among colonial trade, institutions and economic performance are the relation between colonial trade and the extent of extraction from the colonizer, which is hard to quantify, as well as its precise mechanism.Practical implicationsSince the initial institutions set in those former colonies presented a strong persistence in the long run, their governments should focus now on building sound and inclusive political and economic institutions, as well as on investing in human capital in order to foster long-term growth. Once a comprehensive set of institutional and human resources are put in place, the quality and quantity of exports might create a positive spillover on the short-run growth.Social implicationsOne social implication that can be retrieved from this study is the ever-lasting effect of both human capital investment and introduction of inclusive political and economic institutions on the long-run impact of growth.Originality/valueThe paper uses an original primary data set from archival sources to explore the role of colonial heritage on long-term economic development from a resource-curse perspective. It applies a relatively new model partial least squares path modeling (PLS-PM) that allows the construction of LVs for variables that are not directly observable, as well as channeling the impact on growth through both direct and indirect channels. Finally, it allows for the simultaneous multigroup analysis across different colonial groups.

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The impact of burning on lion Panthera leo habitat choice in an African savanna

Current Zoology ◽

10.1093/czoolo/59.3.335 ◽

2013 ◽

Vol 59 (3) ◽

pp. 335-339 ◽

Cited By ~ 12

Author(s):

Stephanie Eby ◽

Anna Mosser ◽

Ali Swanson ◽

Craig Packer ◽

Mark Ritchie

Keyword(s):

National Park ◽

Habitat Choice ◽

Territory Size ◽

Short Term ◽

Data Set ◽

Burned Areas ◽

The Impact ◽

Term Data ◽

Prey Attraction

Abstract Carnivores play a central role in ecosystem processes by exerting top-down control, while fire exerts bottom-up control in ecosystems throughout the world, yet, little is known about how fire affects short-term carnivore distributions across the landscape. Through the use of a long-term data set we investigated the distribution of lions, during the daytime, in relation to burned areas in Serengeti National Park, Tanzania. We found that lions avoid burned areas despite the fact that herbivores, their prey, are attracted to burned areas. Prey attraction, however, likely results from the reduction in cover caused by burning, that may thereby decrease lion hunting success. Lions also do not preferentially utilize the edges of burned areas over unburned areas despite the possibility that edges would combine the benefit of cover with proximity to abundant prey. Despite the fact that lions avoid burned areas, lion territory size and reproductive success were not affected by the proportion of the territory burned each year. Therefore, burning does not seem to reduce lion fitness perhaps because of the heterogeneity of burned areas across the landscape or because it is possible that when hunting at night lions visit burned areas despite their daytime avoidance of these areas.

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Evaluation of a mathematical model of diabetes progression against observations in the Diabetes Prevention Program

AJP Endocrinology and Metabolism ◽

10.1152/ajpendo.00421.2011 ◽

2012 ◽

Vol 303 (2) ◽

pp. E200-E212 ◽

Cited By ~ 16

Author(s):

Thomas Hardy ◽

Eyas Abu-Raddad ◽

Niels Porksen ◽

Andrea De Gaetano

Keyword(s):

Mathematical Model ◽

Prevention Program ◽

Diabetes Prevention ◽

Diabetes Prevention Program ◽

Diabetes Incidence ◽

Cell Protection ◽

Data Set ◽

Diabetes Progression ◽

The Impact

The seminal publication of the Diabetes Prevention Program (DPP) results in 2002 has provided insight into the impact of major therapies on the development of diabetes over a time span of a few years. In the present work, the publicly available DPP data set is used to calibrate and evaluate a recently developed mechanistic mathematical model for the long-term development of diabetes to assess the model's ability to predict the natural history of disease progression and the effectiveness of preventive interventions. A general population is generated from which virtual subject samples corresponding to the DPP enrollment criteria are selected. The model is able to reproduce with good fidelity the observed time courses of both diabetes incidence and average glycemia, under realistic hypotheses on evolution of disease and efficacy of the studied therapies, for all treatment arms. Model-based simulations of the long-term evolution of the disease are consistent with the transient benefits observed with conventional therapies and with promising effects of radical improvement of insulin sensitivity (as by metabolic surgery) or of β-cell protection. The mechanistic diabetes progression model provides a credible tool by which long-term implications of antidiabetic interventions can be evaluated.

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Planning chemotherapy based schistosomiasis control: validation of a mathematical model using data on Schistosoma haematobium from Pemba, Tanzania

Epidemiology and Infection ◽

10.1017/s0950268899003167 ◽

1999 ◽

Vol 123 (3) ◽

pp. 487-497 ◽

Cited By ~ 11

Author(s):

M.-S. CHAN ◽

A. MONTRESOR ◽

L. SAVIOLI ◽

D. A. P. BUNDY

Keyword(s):

Mathematical Model ◽

Control Programme ◽

School Level ◽

Data Set ◽

Urinary Schistosomiasis ◽

Control Programmes ◽

United Republic Of Tanzania ◽

Using Data ◽

The Impact

A mathematical model, based on a deterministic differential equation framework, has been developed to predict the impact of community chemotherapy programmes for human schistosomiasis. Here, this model is validated using data collected from a long-term control programme for urinary schistosomiasis on the island of Pemba, Zanzibar, United Republic of Tanzania, initiated in 1986 and still ongoing, in which schoolchildren were offered praziquantel chemotherapy every 6 months. Prevalence of infection and blood in urine were monitored in all the schools (total 26000 children from 60 schools) and more detailed data were collected in selected evaluation schools. Model predictions were run by using the initial prevalence as input. The predictions were very close to the observed decreases in prevalence and in prevalence of blood in urine. The correspondence improved further when the data were combined, going from single school level to district, and when the entire data set was combined. The accuracy of the predictions suggests that this model could be used as a tool to predict the consequences of chemotherapy control programmes. It is currently in press as a Windows software package under the name of ‘EpiSchisto’.

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Long-Term Patterns in the Wader Usage of an Intertidal Flat in the Oosterschelde (Sw Netherlands) and the Impact of the Closure of an Adjacent Estuary

Journal of Applied Ecology ◽

10.2307/2404070 ◽

1989 ◽

Vol 26 (2) ◽

pp. 419 ◽

Cited By ~ 14

Author(s):

R. H. D. Lambeck ◽

A. J. J. Sandee ◽

L. De Wolf

Keyword(s):

Intertidal Flat ◽

The Impact

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Bitcoin Cost Prediction using Deep Neural Network Technique

International Journal of Scientific Research in Computer Science Engineering and Information Technology ◽

10.32628/cseit19521 ◽

2019 ◽

pp. 96-101

Keyword(s):

Market Price ◽

Real Life ◽

Cost Prediction ◽

Historical Trends ◽

Data Set ◽

Price Prediction ◽

Crypto Currency ◽

Long Term Prediction ◽

The Impact

The accusative of this paper is to predict the bitcoin price accurately by taking various parameters into consideration which affects the bitcoin value. Here multi-layer perceptron algorithms under deep learning are used to predict the price of crypto-currency. Many researchers have analysed the crypto-currency features in many ways such as, market price prediction, the impact of cryptocurrency in real life. It has the ability to make long-term prediction of the exchange price in crypto-currencies particularly in US dollar, based on historical trends. The bitcoin cost prediction is done based on the data set which consists of 13 features relating to the crypto-currency price recorded daily over the period of particular range.

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How COVID-19 Have Changed Crowdfunding: Evidence From GoFundMe

10.20944/preprints202107.0136.v1 ◽

2021 ◽

Author(s):

Junda Wang ◽

Xupin Zhang ◽

Jiebo Luo

Keyword(s):

Racial Disparity ◽

Computational Approach ◽

Long Term Effects ◽

Data Set ◽

Unique Data ◽

The Past ◽

Before And After ◽

The Impact ◽

Shed Light

While the long-term effects of COVID-19 are yet to be determined, its immediate impact on crowdfunding is nonetheless significant. This study takes a computational approach to more deeply comprehend this change. Using a unique data set of all the campaigns published over the past two years on GoFundMe, we explore the factors that have led to the successful funding of a crowdfunding project. In particular, we study a corpus of crowdfunded projects, analyzing cover images and other variables commonly present on crowdfunding sites. Furthermore, we construct a classifier and a regression model to assess the significance of features based on XGBoost. In addition, we employ counterfactual analysis to investigate the causality between features and the success of crowdfunding. More importantly, sentiment analysis and the paired sample t-test are performed to examine the differences in crowdfunding campaigns before and after the COVID-19 outbreak that started in March 2020. First, we note that there is significant racial disparity in crowdfunding success. Second, we find that sad emotion expressed through the campaign's description became significant after the COVID-19 outbreak. Considering all these factors, our findings shed light on the impact of COVID-19 on crowdfunding campaigns.

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Long-term variability of solar irradiance and its implications for photovoltaic power in West Africa

10.5194/egusphere-egu2020-19283 ◽

2020 ◽

Author(s):

Ina Neher ◽

Susanne Crewell ◽

Stefanie Meilinger ◽

Uwe Pfeifroth ◽

Jörg Trentmann

Keyword(s):

West Africa ◽

Solar Irradiance ◽

Dry Season ◽

Negative Trend ◽

Annual Data ◽

Positive Trend ◽

Data Set ◽

Data Record ◽

The Impact

West Africa is one of the least developed regions in the world regarding the energy availability and energy security. Located close to the equator West Africa receives high amounts of global horizontal irradiance (GHI). Thus, solar power and especially photovoltaic (PV) systems seem to be a promising solution to provide electricity with low environmental impact. To plan and to dimension a PV power system climatological data for global horizontal irradiance (GHI) and its variability need to be taken into account. However, ground based measurements of irradiances are not available continuously and cover only a few discrete locations.Data records of surface irradiance based on satellite measurements have the advantage of covering wide spatial regions and being available over long time periods. The European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility on Climate Monitoring (CM SAF) provides the Surface Solar Radiation Data Set-Heliosat, Edition 2.1 (SARAH-2.1), a 35 year long climate data record in an half hourly resolution, covering the whole of Africa and Europe. In this study, the SARAH-2.1 data record (1983-2017) is used to analyze the impact of 35 years atmospheric variability and trend on GHI and PV yields over West Africa (defined as the region from 3&#176;N to 20&#176;N and 20&#176;W to 16&#176;E). The trend and the variability of solar irradiance is analyzed separately for the wet and dry season as well as for annual data. Furthermore, a simplified model provides high-resolution potential PV yields. According to the SARAH-2.1 data record, solar irradiance is largest (with up to 300 W/m 2 daily average) in the Sahara and the Sahel zone with a positive trend (up to 5 W/m2/decade). Whereas, the solar irradiance is lower in southern West Africa with a negative trend (up to -5 W/m2/decade). The positive trend is mostly connected to the dry season, while the negative trend occurs during the wet season. PV yields show a strong meridional gradient with lowest values around 4 kWh/kWp in southern West Africa and reach more than 5 kWh/kWp in the Sahara and Sahel zone.This poster will discuss the long-term trend and variability analysis of solar irradiance and highlight the implications for photovoltaic-based power systems in West Africa.

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