scholarly journals Selection of Commercial-Off-the-Shelf Antistatic Coating and Its Applicability for Space-Use Solar Arrays

Author(s):  
Minoru IWATA ◽  
Akitoshi TAKAHASHI ◽  
Musashi SAKAMOTO ◽  
Mengu CHO ◽  
Ryo MURAGUCHI
2019 ◽  
Vol 182 (1) ◽  
pp. 63
Author(s):  
James C. Doyle ◽  
David W. Sample ◽  
Lindsey Long ◽  
Timothy R. Van Deelen

2010 ◽  
Vol 74 (2) ◽  
pp. 219-227 ◽  
Author(s):  
Floris M. van Beest ◽  
Leif Egil Loe ◽  
Atle Mysterud ◽  
Jos M. Milner

2012 ◽  
Vol 57 (3) ◽  
pp. 245-250 ◽  
Author(s):  
Christof Janko ◽  
Wolfgang Schröder ◽  
Stefan Linke ◽  
Andreas König

2020 ◽  
Author(s):  
Samantha Nicole Smith ◽  
Max Dolton Jones ◽  
Benjamin Michael Marshall ◽  
Surachit Waengsothorn ◽  
George A. Gale ◽  
...  

AbstractAnimal movement and resource use are tightly linked. Investigating these links to understand how animals utilize space and select habitats is especially relevant in areas that have been affected by habitat fragmentation and agricultural conversion. We set out to explore the space use and habitat selection of Burmese pythons (Python bivittatus) in a patchy land use matrix dominated by agricultural crops and human settlements. We used radio telemetry to record daily locations of seven Burmese pythons over the course of our study period of approximately 22 months. We created dynamic Brownian Bridge Movement Models (dBBMMs) for all individuals, using occurrence distributions to estimate extent of movements and motion variance to reveal temporal patterns. Then we used integrated step selection functions to determine whether individual movements were associated with particular landscape features (aquatic agriculture, forest, roads, settlements, terrestrial agriculture, water), and whether there were consistent associations at the population level. Our dBBMM estimates suggested that Burmese pythons made use of small areas (98.97 ± 35.42 ha), with low mean individual motion variance characterized by infrequent moves and long periods at a single location. At both the individual and population level, Burmese pythons in the agricultural matrix were associated with aquatic environments. Only one individual showed a strong avoidance for human settlements which is troublesome from a human-wildlife conflict angle, especially as Burmese pythons have been observed entering human settlements and consuming livestock in our study site. Our study is one of the first to contribute to the knowledge of Burmese python ecology in their native range as the majority of studies have focused on invasive populations.


2020 ◽  
Vol 8 (1) ◽  
Author(s):  
Michael L. Wysong ◽  
Bronwyn A. Hradsky ◽  
Gwenllian D. Iacona ◽  
Leonie E. Valentine ◽  
Keith Morris ◽  
...  

2018 ◽  
Vol 179 (2) ◽  
pp. 247-260 ◽  
Author(s):  
Carolyn A. Eckrich ◽  
Matthew J. Warren ◽  
Darren A. Clark ◽  
Philip J. Milburn ◽  
Scott J. Torland ◽  
...  

2021 ◽  
Vol 9 ◽  
Author(s):  
Helena Rheault ◽  
Charles R. Anderson ◽  
Maegwin Bonar ◽  
Robby R. Marrotte ◽  
Tyler R. Ross ◽  
...  

Understanding how animals use information about their environment to make movement decisions underpins our ability to explain drivers of and predict animal movement. Memory is the cognitive process that allows species to store information about experienced landscapes, however, remains an understudied topic in movement ecology. By studying how species select for familiar locations, visited recently and in the past, we can gain insight to how they store and use local information in multiple memory types. In this study, we analyzed the movements of a migratory mule deer (Odocoileus hemionus) population in the Piceance Basin of Colorado, United States to investigate the influence of spatial experience over different time scales on seasonal range habitat selection. We inferred the influence of short and long-term memory from the contribution to habitat selection of previous space use within the same season and during the prior year, respectively. We fit step-selection functions to GPS collar data from 32 female deer and tested the predictive ability of covariates representing current environmental conditions and both metrics of previous space use on habitat selection, inferring the latter as the influence of memory within and between seasons (summer vs. winter). Across individuals, models incorporating covariates representing both recent and past experience and environmental covariates performed best. In the top model, locations that had been previously visited within the same season and locations from previous seasons were more strongly selected relative to environmental covariates, which we interpret as evidence for the strong influence of both short- and long-term memory in driving seasonal range habitat selection. Further, the influence of previous space uses was stronger in the summer relative to winter, which is when deer in this population demonstrated strongest philopatry to their range. Our results suggest that mule deer update their seasonal range cognitive map in real time and retain long-term information about seasonal ranges, which supports the existing theory that memory is a mechanism leading to emergent space-use patterns such as site fidelity. Lastly, these findings provide novel insight into how species store and use information over different time scales.


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