Long-term environmental data explain better the abundance of the red octopus (Octopus maya) when testing the niche centroid hypothesis

2021 ◽  
Vol 544 ◽  
pp. 151609
Author(s):  
Luis Enrique Ángeles-González ◽  
Enrique Martínez-Meyer ◽  
Carlos Rosas ◽  
Paulina Valeria Guarneros-Narváez ◽  
Jorge A. López-Rocha ◽  
...  
Keyword(s):  
Environmental Data ◽  
Octopus Maya

scholarly journals A low-cost automized anaerobic chamber for long-term growth experiments and sample handling

2020 ◽  
Author(s):  
Achim J. Herrmann ◽  
Michelle M. Gehringer
Keyword(s):  
Environmental Control ◽  
Low Cost ◽  
Environmental Data ◽  
Atmospheric Environment ◽  
Regular Growth ◽  
Continuous Growth ◽  
Sample Handling ◽  
Hand Column ◽  
Oxygen Sensitive

1AbstractThe handling of oxygen sensitive samples and growth of obligate anaerobic organisms requires the stringent exclusion of oxygen, which is omnipresent in our normal atmospheric environment. Anaerobic workstations (aka. Glove boxes) enable the handling of oxygen sensitive samples during complex procedures, or the long-term incubation of anaerobic organisms. Depending on the application requirements, commercial workstations can cost up to 60.000 €. Here we present the complete build instructions for a highly adaptive, Arduino based, anaerobic workstation for microbial cultivation and sample handling, with features normally found only in high cost commercial solutions. This build can automatically regulate humidity, H2 levels (as oxygen reductant), log the environmental data and purge the airlock. It is built as compact as possible to allow it to fit into regular growth chambers for full environmental control. In our experiments, oxygen levels during the continuous growth of oxygen producing cyanobacteria, stayed under 0.03 % for 21 days without needing user intervention. The modular Arduino controller allows for the easy incorporation of additional regulation parameters, such as CO2 concentration or air pressure. This paper provides researchers with a low cost, entry level workstation for anaerobic sample handling with the flexibility to match their specific experimental needs.Specifications table[please fill in right-hand column of the table below]

Dendrometer measurements of arctic-alpine dwarf shrubs and micro-environmental drivers of plant growth - Dataset from long-term alpine ecosystem research in central Norway

Erdkunde ◽  
2021 ◽  
Author(s):  
Jörg Löffler ◽  
Svenja Dobbert ◽  
Roland Pape ◽  
Dirk Wundram
Keyword(s):  
Root Zone ◽  
Monitoring Program ◽  
Growth Patterns ◽  
Environmental Data ◽  
Environmental Drivers ◽  
Horizontal Distance ◽  
Ecosystem Research ◽  
Alpine Ecosystem ◽  
Vegetation Shifts

Here, we present fine-scale measurements of stem diameter variation from three common arctic-alpine dwarf-shrub species monitored in two mountain regions of Central Norway. All three species (Betula nana, Empetrum nigrum ssp. hermaphroditum, and Phyllodoce caerulea) are abundant within the studied regions and highly important contributors to potential future arctic-alpine vegetation shifts. A profound understanding of their radial growth patterns therefore has the potential to yield crucial information regarding climate-growth relations within these ecosystems. We used high-resolution dendrometers (type DRO) to monitor 120 specimens, taking measurements near the shoot base of one major horizontal stem. Along with the shrub growth measurements, we measured on-site micro-environmental data at each studied site, including shoot zone and root zone temperatures as well as soil moisture. All data were recorded at an hourly scale and are presented as daily mean values. The monitoring period spanned five full years (2015 - 2019), with additional data from 2014 and 2020. Data were collected within one of the most continental climate regions of Europe, the Vågå/Innlandet region, and in the oceanic climate region Geiranger/Møre og Romsdal, spanning a steep climate gradient over just ~100 km horizontal distance. Both study regions are characterized by steep elevational gradients and highly heterogeneous micro-topography. The studied sites were chosen to represent these natural conditions using the transect principle. The collection of our original data is subject of our long-term alpine ecosystem monitoring program since 1991, from which numerous publications function as the basis for a recent project on the use of dendrometer data in alpine ecosystem studies.

Monitoring and Calibration of Long Term Mooring System Design Assumptions Through Use of AIS and Weather Data

2021 ◽  
Author(s):  
Dag Børre Lillestøl ◽  
Odd Torbjørn Kårvand ◽  
Are Torstensen
Keyword(s):  
Low Cost ◽  
Environmental Data ◽  
Weather Data ◽  
Mooring System ◽  
System Behavior ◽  
Original Design ◽  
Actual System ◽  
Early Failures ◽  
And Performance

Abstract This paper outlines an approach on how to improve the mooring integrity of existing long term mooring systems by using existing and commercially available data. It will be demonstrated how the use of AIS and hindcast weather data can be used to increase understanding of mooring systems and to monitor and quantify gaps between "as-designed", "as-installed" and "as-is" of a long term mooring system. Long term moored units have traditionally suffered from many early failures, caused by damages and errors introduced in the installation phase, and costly and unnecessary "late in life" failures. A fact rated high on the agenda of the underwriters. Numerous papers have been written on this topic, but it is only in recent years the industry have started to ensure that systems are inspected to a sufficient degree with respect to the physical condition, taking these learnings into account. However, the second important element, the calibration of the mooring analysis vs. actual vessel and mooring system behavior/performance, have not yet gotten the attention required. Deviations from the intended design are introduced in the installation phase of a mooring system. In addition, the design assumptions will never be fully accurate. The gap between the design assumptions and the actual system will increase over time, and the industry today do not focus on mapping and quantifying the effect of this gap sufficiently. The described method explains how one can introduce a pro-active approach, without installing onboard equipment, but rather utilizing algorithms on existing data and design documentation. This paper focuses on the use of AIS data in combination with historic weather/environmental data and seek to demonstrate how this low-cost method can provide useful information with respect to the mooring system. To emphasize the mapped importance of such calibrations, the July 2021 Edition of the in-service DNV Class Rules, DNVGL-OS-0300, formally introduces requirements to calibration of design assumptions of long term mooring units through use of survey data, service history and actual mooring system behavior in order to ensure a unit's mooring system condition and performance is known in light of the original design assumptions.

scholarly journals Short and Long-Term Effects of Anesthesia in Octopus maya (Cephalopoda, Octopodidae) Juveniles

2020 ◽  
Vol 11 ◽  
Author(s):  
Katina Roumbedakis ◽  
Marina N. Alexandre ◽  
José A. Puch ◽  
Maurício L. Martins ◽  
Cristina Pascual ◽  
...  
Keyword(s):  
Long Term Effects ◽  
Short And Long Term ◽  
Octopus Maya

scholarly journals Perceptions of Similarity Can Mislead Provenancing Strategies—An Example from Five Co-Distributed Acacia Species

Diversity ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 306
Author(s):  
Maurizio Rossetto ◽  
Peter D. Wilson ◽  
Jason Bragg ◽  
Joel Cohen ◽  
Monica Fahey ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
A Priori ◽  
Genetic Data ◽  
Environmental Data ◽  
Specific Data ◽  
Acacia Species ◽  
Simple Observation ◽  
Source Plant ◽  
Species Specific

Ecological restoration requires balancing levels of genetic diversity to achieve present-day establishment as well as long-term sustainability. Assumptions based on distributional, taxonomic or functional generalizations are often made when deciding how to source plant material for restoration. We investigate this assumption and ask whether species-specific data is required to optimize provenancing strategies. We use population genetic and environmental data from five congeneric and largely co-distributed species of Acacia to specifically ask how different species-specific genetic provenancing strategies are based on empirical data and how well a simple, standardized collection strategy would work when applied to the same species. We find substantial variability in terms of patterns of genetic diversity and differentiation across the landscape among these five co-distributed Acacia species. This variation translates into substantial differences in genetic provenancing recommendations among species (ranging from 100% to less than 1% of observed genetic variation across species) that could not have been accurately predicted a priori based on simple observation or overall distributional patterns. Furthermore, when a common provenancing strategy was applied to each species, the recommended collection areas and the evolutionary representativeness of such artificially standardized areas were substantially different (smaller) from those identified based on environmental and genetic data. We recommend the implementation of the increasingly accessible array of evolutionary-based methodologies and information to optimize restoration efforts.

scholarly journals Quality Control and Pre-Analysis Treatment of the Environmental Datasets Collected by an Internet Operated Deep-Sea Crawler during Its Entire 7-Year Long Deployment (2009–2016)

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2991
Author(s):  
Damianos Chatzievangelou ◽  
Jacopo Aguzzi ◽  
Martin Scherwath ◽  
Laurenz Thomsen
Keyword(s):  
Electrical Conductivity ◽  
Quality Control ◽  
Data Acquisition ◽  
Deep Sea ◽  
Analysis Data ◽  
Environmental Data ◽  
Depth Processing ◽  
Technological Advances ◽  
Scientific Results

Deep-sea environmental datasets are ever-increasing in size and diversity, as technological advances lead monitoring studies towards long-term, high-frequency data acquisition protocols. This study presents examples of pre-analysis data treatment steps applied to the environmental time series collected by the Internet Operated Deep-sea Crawler “Wally” during a 7-year deployment (2009–2016) in the Barkley Canyon methane hydrates site, off Vancouver Island (BC, Canada). Pressure, temperature, electrical conductivity, flow, turbidity, and chlorophyll data were subjected to different standardizing, normalizing, and de-trending methods on a case-by-case basis, depending on the nature of the treated variable and the range and scale of the values provided by each of the different sensors. The final pressure, temperature, and electrical conductivity (transformed to practical salinity) datasets are ready for use. On the other hand, in the cases of flow, turbidity, and chlorophyll, further in-depth processing, in tandem with data describing the movement and position of the crawler, will be needed in order to filter out all possible effects of the latter. Our work evidences challenges and solutions in multiparametric data acquisition and quality control and ensures that a big step is taken so that the available environmental data meet high quality standards and facilitate the production of reliable scientific results.

Development and Implementation of a Risk Based Prioritization Methodology for MAOP Reconfirmation of Gas Transmission Facilities

2016 ◽  
Author(s):  
Wytze Sloterdijk ◽  
Martin Hommes ◽  
Roelof Coster ◽  
Troy Rovella ◽  
Sarah Herbison
Keyword(s):  
Oil And Gas ◽  
Environmental Data ◽  
Operating Pressure ◽  
Line Pipe ◽  
Relative Significance ◽  
Coherent Risk ◽  
Relative Risks ◽  
Short And Long Term ◽  
Selection Of

As part of Pacific Gas and Electric Company’s (PG&E) on-going commitment to public safety, the company has begun a comprehensive engineering validation of its gas transmission facilities that will ultimately support the reconfirmation of maximum allowable operating pressure (MAOP) for these assets. In addition to 6,750 miles of line pipe, PG&E’s gas transmission system contains over 500 station facilities. Since this set of facilities is not only large but diverse, and the validation effort for these facilities is expected to be an extensive, multi-year process, a methodology for the prioritization of the facilities needed to be developed to facilitate planning of the process for the efficient mitigation of risk. As a result, DNV GL was retained to develop and implement a risk-based prioritization methodology to prioritize PG&E’s gas transmission facilities for the engineering validation and MAOP reconfirmation effort. Ultimately, a weighted multiple criteria decision analysis (MCDA) approach was selected and implemented to generate the prioritization. This MCDA approach consisted of the selection of relevant criteria (threats) and the weighting of these criteria according to their relative significance to PG&E’s facilities. Relevant criteria selected for inclusion in the analysis include factors that are important in order to assess both the short- and long-term integrity of the facility as a whole as well as the integrity of features for which design records cannot be located. The criteria selected encompass stable threats, time-dependent threats, as well as environmental impact. Enormous amounts of data related to design, operations, maintenance history and meteorological and seismic activity in addition to other environmental data were evaluated with this newly developed methodology to assess the relative risks of the facilities. Pilot field visits were performed to validate the selection of the various criteria and to confirm the outcome of the analysis. The novelty of this approach lies in the prioritization of facilities in a coherent risk-based manner. The described approach can be used by operators of oil and gas facilities, either upstream, midstream or downstream.

Joint Distribution of Environmental Condition at Five European Offshore Sites for Design of Combined Wind and Wave Energy Devices

2015 ◽  
Vol 137 (3) ◽  
Author(s):  
Lin Li ◽  
Zhen Gao ◽  
Torgeir Moan
Keyword(s):  
Renewable Energy ◽  
Wave Energy ◽  
Environmental Data ◽  
Offshore Wind ◽  
Response Analysis ◽  
Energy Devices ◽  
Joint Distributions ◽  
Wave Parameters ◽  
Extreme Response

The design of wind turbines requires information about joint data for wind and wave conditions. Moreover, combining offshore wind and wave energy facilities is a potential way to reduce the cost of offshore wind farms. To design combined offshore renewable energy concepts, it is important to choose sites where both wind and wave energy resources are substantial. This paper deals with joint environmental data for five European offshore sites which serve as basis for the analysis and comparison of combined renewable energy concepts developed in the EU FP7 project—MARINA Platform. The five sites cover both shallow and deep water, with three sites facing the Atlantic Ocean and two sites in the North Sea. The long-term joint distributions of wind and wave parameters are presented for these sites. Simultaneous hourly mean wind and wave hindcast data from 2001 to 2010 are used as a database. The joint distributions are modeled by fitting analytical distributions to the hindcast data. The long-term joint distributions can be used to estimate the wind and wave power output from each combined concept and to estimate the fatigue lifetime of the structure. The marginal distributions of wind and wave parameters are also provided. Based on the joint distributions, contour surfaces are established for combined wind and wave parameters for which the probability of exceedance corresponds to a return period of 50 years. The design points on the 50-year contour surfaces are suggested for extreme response analysis of combined concepts.

The Course of Intellectual Development in Preterm and Fullterm Children: An 8-year Longitudinal Study

1996 ◽  
Vol 19 (3) ◽  
pp. 491-516 ◽  
Author(s):  
Magda Kalmár
Keyword(s):  
Intellectual Development ◽  
Environmental Data ◽  
Biomedical Data ◽  
Contributing Factors ◽  
Long Term Outcomes ◽  
Long Term Follow Up ◽  
Preterm Group

A total of 55 preterm children born at low to moderate risk and a comparison group of 100 healthy fullterm children were studied until they reached 8 years of age. Perinatal biomedical data and environmental data were considered as potential contributors to developmental outcome. The Budapest Binet intelligence quotients (IQs) were used as outcome measures. The mean IQs for both groups fell within the normal range at each measurement point. However, the differential patterns of IQ development in the preterm and term group underscore the significance of the age variable. Instead of a gradually declining impact of prematurity, the age effect resulted in a complex pattern. The considerable intra-group variability within the preterm group and the correlates of outcome suggest that biological hazards related to birth may have subtle long-term influences. Variables tapping the quality of home environment, however, clearly outweighed the perinatal risk factors in their ability to predict long-term outcomes. The results suggest a transaction between the two spheres of contributing factors. Long-term follow-up studies with multiple measurement points are essential if we are to understand the developmental implications of premature birth.

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