Diel, lunar and seasonal vertical migration in the deep western Gulf of Mexico evidenced from a long-term data series of acoustic backscatter

2021 ◽  
pp. 102562
Author(s):  
Laura Ursella ◽  
Sara Pensieri ◽  
Enric Pallàs-Sanz ◽  
Sharon Z. Herzka ◽  
Roberto Bozzano ◽  
...  
Keyword(s):  
Gulf Of Mexico ◽  
Vertical Migration ◽  
Acoustic Backscatter ◽  
Data Series ◽  
Term Data

scholarly journals Lead, zinc, and chromium concentrations in acidic headwater streams in Sweden explained by chemical, climatic, and land-use variations

2012 ◽  
Vol 9 (11) ◽  
pp. 4323-4335 ◽  
Author(s):  
B. J. Huser ◽  
J. Fölster ◽  
S. J. Köhler
Keyword(s):  
Land Use ◽  
Predictive Power ◽  
Prediction Models ◽  
Headwater Streams ◽  
Data Series ◽  
Seasonal Differences ◽  
Metal Concentrations ◽  
Lead Zinc ◽  
Term Data

Abstract. Long-term data series (1996–2009) for eleven acidic headwater streams (< 10 km2) in Sweden were analyzed to determine factors controlling concentrations of trace metals. In-stream chemical data as well climatic, flow, and deposition chemistry data were used to develop models predicting concentrations of chromium (Cr), lead (Pb), and zinc (Zn). Data were initially analyzed using partial least squares to determine a set of variables that could predict metal concentrations across all sites. Organic matter (as absorbance) and iron related positively to Pb and Cr, while pH related negatively to Pb and Zn. Other variables such as conductivity, manganese, and temperature were important as well. Multiple linear regression was then used to determine minimally adequate prediction models which explained an average of 35% (Cr), 52% (Zn), and 72% (Pb) of metal variation across all sites. While models explained at least 50% of variation in the majority of sites for Pb (10) and Zn (8), only three sites met this criterion for Cr. Investigation of variation between site models for each metal revealed geographical (altitude), chemical (sulfate), and land-use (silvaculture) influences on predictive power of the models. Residual analysis revealed seasonal differences in the ability of the models to predict metal concentrations as well. Expected future changes in model variables were applied and results showed the potential for long-term increases (Pb) or decreases (Zn) for trace metal concentrations at these sites.

scholarly journals Analysis of Trends in the FireCCI Global Long Term Burned Area Product (1982–2018)

Fire ◽  
2021 ◽  
Vol 4 (4) ◽  
pp. 74
Author(s):  
Gonzalo Otón ◽  
José Miguel C. Pereira ◽  
João M. N. Silva ◽  
Emilio Chuvieco
Keyword(s):  
Time Series ◽  
Temporal Trends ◽  
European Space Agency ◽  
Eastern Africa ◽  
Burned Area ◽  
Data Series ◽  
Short Term ◽  
The Impact ◽  
Term Data

We present an analysis of the spatio-temporal trends derived from long-term burned area (BA) data series. Two global BA products were included in our analysis, the FireCCI51 (2001–2019) and the FireCCILT11 (1982–2018) datasets. The former was generated from Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m reflectance data, guided by 1 km active fires. The FireCCILT11 dataset was generated from Land Long-Term Data Record data (0.05°), which provides a consistent time series for Advanced Very High Resolution Radiometer images, acquired from the NOAA satellite series. FireCCILT11 is the longest time series of a BA product currently available, making it possible to carry out temporal analysis of long-term trends. Both products were developed under the FireCCI project of the European Space Agency. The two datasets were pre-processed to correct for temporal autocorrelation. Unburnable areas were removed and the lack of the FireCCILT11 data in 1994 was examined to evaluate the impact of this gap on the BA trends. An analysis and comparison between the two BA products was performed using a contextual approach. Results of the contextual Mann-Kendall analysis identified significant trends in both datasets, with very different regional values. The long-term series presented larger clusters than the short-term ones. Africa displayed significant decreasing trends in the short-term, and increasing trends in the long-term data series, except in the east. In the long-term series, Eastern Africa, boreal regions, Central Asia and South Australia showed large BA decrease clusters, and Western and Central Africa, South America, USA and North Australia presented BA increase clusters.

scholarly journals Government expenditure in New Zealand since 1935: a preliminary reassessment

2017 ◽  
Vol 13 (2) ◽  
Author(s):  
Matthew Gibbons
Keyword(s):  
New Zealand ◽  
Comparative Studies ◽  
Government Expenditure ◽  
Data Series ◽  
Optimal Size ◽  
Economic Issue ◽  
Size Of Government ◽  
Expenditure Data ◽  
Term Data

The optimal size of government is an important political and economic issue. However, because no long-term government expenditure series has official standing, New Zealand is often a missing case in comparative studies of government expenditure (Castles, 1998). Although government expenditure data is available from 1972 on Treasury’s website (New Zealand Treasury, 2016), the most widely used data before 1972 is a ‘consolidated’ long-term data series, on Statistics New Zealand’s website, which uses data from a number of sources and is published with strong disclaimers. 

Trends, drivers, and lessons from a long-term data series of the Asturian (northern Spain) gooseneck barnacle territorial use rights system

2017 ◽  
Vol 93 (1) ◽  
pp. 35-51 ◽  
Author(s):  
Antonella Rivera ◽  
Stefan Gelcich ◽  
Lucía García-Flórez ◽  
José Luis Acuña
Keyword(s):  
Data Series ◽  
Northern Spain ◽  
Gooseneck Barnacle ◽  
Term Data

scholarly journals An update on the uncertainties of water vapor measurements using Cryogenic Frostpoint Hygrometers

2016 ◽  
Author(s):  
Holger Vömel ◽  
Tatjana. Naebert ◽  
Ruud Dirksen ◽  
Michael Sommer
Keyword(s):  
Water Vapor ◽  
Data Series ◽  
Climate Variables ◽  
Stratospheric Water Vapor ◽  
Tropospheric Measurements ◽  
Long Time ◽  
Climate Series ◽  
Term Data ◽  
Better Than

Abstract. Long time series of observations of essential climate variables in the troposphere and stratosphere are often impacted by inconsistencies in instrumentation and ambiguities in the interpretation of the data. To reduce these problems of long term data series all measurements should include an estimate of their uncertainty and a description of their sources. Here we present an update of the uncertainties for tropospheric and stratospheric water vapor observations using the Cryogenic Frostpoint Hygrometer (CFH). The largest source of measurement uncertainty is the controller stability, which is discussed here in detail. We describe a method to quantify this uncertainty for each profile based on the measurements. We also show the importance of a manufacturer independent ground check, which is an essential tool to continuously monitor the uncertainty introduced by instrument variability. A small bias, which has previously been indicated in lower tropospheric measurements, is described here in detail and has been rectified. Under good conditions the total from all sources of uncertainty of frostpoint or dewpoint measurements using the CFH can be better than 0.2 K. Systematic errors, which are most likely to impact long term climate series are verified to be less than 0.1 K.

Morlet wavelet and autocorrelation analysis of long-term data series of the Kis-Balaton water protection system (KBWPS)

2010 ◽  
Vol 36 (10) ◽  
pp. 1469-1477 ◽  
Author(s):  
József Kovács ◽  
István Gábor Hatvani ◽  
János Korponai ◽  
Ilona Székely Kovács
Keyword(s):  
Morlet Wavelet ◽  
Protection System ◽  
Data Series ◽  
Water Protection ◽  
Autocorrelation Analysis ◽  
Term Data

Coordination of long-term data management in the Gulf of Mexico: Lessons learned and recommendations from two years of cross-agency collaboration

Shore & Beach ◽  
2020 ◽  
pp. 17-22
Author(s):  
Kathryn Keating ◽  
Melissa Gloekler ◽  
Nancy Kinner ◽  
Sharon Mesick ◽  
Michael Peccini ◽  
...  
Keyword(s):  
Gulf Of Mexico ◽  
Data Management ◽  
Management Practices ◽  
Collaborative Work ◽  
Lessons Learned ◽  
The Many ◽  
Diverse Data ◽  
The University ◽  
Term Data

This paper presents a summary of collaborative work, lessons learned, and suggestions for next steps in coordinating long-term data management in the Gulf of Mexico in the years following the Deepwater Horizon oil spill (DWH). A decade of increased research and monitoring following the DWH has yielded a vast amount of diverse data collected from response and assessment efforts as well as ongoing restoration efforts. To maximize the benefits of this data through proper management and coordination, a cross-agency and organization Long-Term Data Management (LTDM) working group was established in 2017 with sponsorship from NOAA’s Office of Response and Restoration (OR&R) and NOAA’s National Marine Fisheries Service Restoration Center (NMFS RC) and facilitated by the University of New Hampshire’s Coastal Response Research Center. This paper will describe the LTDM working group’s efforts to foster collaboration, data sharing, and best data management practices among the many state, federal, academic and non-governmental entities working to restore and improve the coastal environment in the Gulf following the DWH. Through collaborative workshops and working groups, participants have helped to characterize region-specific challenges, identify areas for growth, leverage existing connections, and develop recommended actions for stakeholders at all organizational levels who share an interest in data coordination and management activities.

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