A new simulator to determine thermal disturbance and recovery processes during wellbore drilling: Experimental validation with a scaled-down wellbore prototype

2020 ◽  
Vol 135 ◽  
pp. 104359
Author(s):  
R. Molina-Rodea ◽  
J.A. Wong-Loya ◽  
P.J. Valades-Pelayo
2022 ◽  
Vol 8 ◽  
Author(s):  
Richard Grainger ◽  
David Raubenheimer ◽  
Victor M. Peddemors ◽  
Paul A. Butcher ◽  
Gabriel E. Machovsky-Capuska

Multisensor biologging provides a powerful tool for ecological research, enabling fine-scale observation of animals to directly link physiology and movement to behavior across ecological contexts. However, applied research into behavioral disturbance and recovery following human interventions (e.g., capture and translocation) has mostly relied on coarse location-based tracking or unidimensional approaches (e.g., dive profiles and activity/energetic metrics) that may not resolve behaviors and recovery processes. Biologging can improve insights into both disturbed and natural behavior, which is critical for management and conservation initiatives, although challenges remain in objectively identifying distinct behavioral modes from complex multisensor datasets. Using white sharks (Carcharodon carcharias) released from a non-lethal catch-and-release shark bite mitigation program, we explored how combining multisensor biologging (video, depth, accelerometers, gyroscopes, and magnetometers), track reconstruction and behavioral state modeling using hidden Markov models (HMMs) can improve our understanding of behavioral processes and recovery. Biologging tags were deployed on eight white sharks, recording their continuous behaviors, movements, and environmental context (habitat, interactions with other organisms/objects) for periods of 10–87 h post-release. Dive profiles and tailbeat analysis (as a standard, activity-based method for assessing recovery) indicated an immediate “disturbed” period of offshore movement, displaying rapid tailbeats and an average tailbeat-derived recovery period of 9.7 h, with evidence of smaller individuals having longer recoveries. However, further integrating magnetometer-derived headings, track reconstruction and HMM modeling revealed a cryptic shift to diurnal clockwise-counterclockwise circling behavior, which we argue represents compelling new evidence for hypothesized unihemispheric sleep amongst elasmobranchs. By simultaneously providing critical information toward conservation-focused shark management and understudied aspects of shark behavior, our study highlights how integrating multisensor information through HMMs can improve our understanding of both post-release and natural behavior, especially in species that are difficult to observe directly.


2003 ◽  
Vol 79 (2) ◽  
pp. 242-246 ◽  
Author(s):  
M Isabel Ramírez ◽  
Joaquín G Azcárate ◽  
Laura Luna

Since the monarch butterfly overwintering habitat was discovered in the mountainous fir forests in central Mexico three presidential decrees have been issued (1980, 1986, 2001) to protect it. But these forests are the source of livelihood for many local people, whose activities (wood extraction and clearance for subsistence farming) represent a major threat to the forests, and thus to the butterfly population. This study identifies important deforestation, disturbance, and recovery processes caused by human activities in the protected areas and their surroundings. Contrary to our expectations, the protected areas have been most negatively affected by human activities, whereas areas devoted to multiple uses have been more adequately preserved. Key words: monarch butterfly habitat, deforestation, forest disturbance, protected areas


2014 ◽  
Vol 31 (7) ◽  
pp. 785-797 ◽  
Author(s):  
J. W. Hayes ◽  
K. A. Shearer ◽  
E. O. Goodwin ◽  
J. Hay ◽  
C. Allen ◽  
...  

2017 ◽  
pp. 17 ◽  
Author(s):  
S. Martínez ◽  
E. Chuvieco ◽  
I. Aguado ◽  
J. Salas

<p>The main objective of this study is to take a close look at post-fire recovery patterns in forestry areas under different burn severity conditions. We also investigate the time that forestry ecosystems take to recover their pre-fire condition. In this context, this study analyses both the level of severity in Uncastillo forest wildfire (7.664ha), one of the greatest occurred in Spain in 1994, and the pattern of natural recovery in the following decades (until 2014) using annual Landsat time series (sensors TM&amp;ETM+). Burn severity has been estimated by means of PROSPECT and GeoSAIL radiative transfer models following methodologies described in De Santis and Chuvieco (2009). On the other hand, recovery processes have been assessed from spectral profiles using the LandTrendr model (Landsat-based Detection of Trends in Disturbance and Recovery) (Kennedy et al., 2010). Results contribute to a further understanding of the post-fire evolution in forestry areas and to develop effective strategies for sustainable forest management.</p>


2015 ◽  
Vol 53 (01) ◽  
Author(s):  
L Spomer ◽  
CGW Gertzen ◽  
D Häussinger ◽  
H Gohlke ◽  
V Keitel

2018 ◽  
Vol 138 (8) ◽  
pp. 651-658 ◽  
Author(s):  
Keisuke Shirasaki ◽  
Naotaka Okada ◽  
Kenichiro Sano ◽  
Hideki Iwatsuki

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