scholarly journals Habitat selection and 3D space use partitioning of resident juvenile hawksbill sea turtles in a small Caribbean bay

2021 ◽  
Vol 168 (8) ◽  
Author(s):  
J. K. Matley ◽  
L. K. Johansen ◽  
N. V. Klinard ◽  
S. T. Eanes ◽  
P. D. Jobsis

AbstractUnderstanding how aquatic animals select and partition resources provides relevant information about community dynamics that can be used to help manage conservation efforts. The critically endangered hawksbill sea turtle (Eretmochelys imbricata) spends an extended part of its juvenile development in coastal waters. A strong proclivity to remain resident in small areas, often in high density, raises questions about how juveniles partition resources including selection of habitat and spatial overlap among conspecifics. Using between 36 and 41 acoustic receivers in the 1.5 km2 study site, this study quantified day-and-night habitat selection, as well as 2D and 3D space use of 23 juvenile hawksbills within two adjacent Caribbean foraging grounds—Brewers Bay and Hawksbill Cove, St. Thomas, US Virgin Islands—between 2015 and 2018. We found that coral reef, rock, and the artificial dolosse forming an airport runway, were the most strongly selected habitats based on resource selection indices. Individual activity spaces in 2D and 3D were both larger during the day compared to night, although the same parts of the bay were used by each individual during both periods. The 3D approach also showed deeper space use during the day. Weekly comparisons of activity space between individuals showed limited overlap (mean 95% UD overlap; day: 0.15 (2D) and 0.07 (3D), night: 0.11 (2D) and 0.03 (3D)), suggesting some degree of resource partitioning or territoriality. Results from this study provide relevant space use information for resource management of juvenile hawksbills, in which many populations are facing habitat degradation and population declines.

2020 ◽  
Author(s):  
Thiago C. Dias ◽  
Jared A. Stabach ◽  
Qiongyu Huang ◽  
Marcelo B. Labruna ◽  
Peter Leimgruber ◽  
...  

AbstractHuman activities are changing landscape structure and function globally, affecting wildlife space use, and ultimately increasing human-wildlife conflicts and zoonotic disease spread. Capybara (Hydrochoerus hydrochaeris) is a conflict species that has been implicated in the spread and amplification of the most lethal tick-borne disease in the world, the Brazilian spotted fever (BSF). Even though essential to understand the link between capybaras, ticks and the BSF, many knowledge gaps still exist regarding the effects of human disturbance in capybara space use. Here, we analyzed diurnal and nocturnal habitat selection strategies of capybaras across natural and human-modified landscapes using resource selection functions (RSF). Selection for forested habitats was high across human- modified landscapes, mainly during day- periods. Across natural landscapes, capybaras avoided forests during both day- and night periods. Water was consistently selected across both landscapes, during day- and nighttime. This variable was also the most important in predicting capybara habitat selection across natural landscapes. Capybaras showed slightly higher preferences for areas near grasses/shrubs across natural landscapes, and this variable was the most important in predicting capybara habitat selection across human-modified landscapes. Our results demonstrate human-driven variation in habitat selection strategies by capybaras. This behavioral adjustment across human-modified landscapes may be related to BSF epidemiology.


2015 ◽  
Vol 97 (2) ◽  
pp. 473-482 ◽  
Author(s):  
Rebecca J. Welch ◽  
Craig J. Tambling ◽  
Charlene Bissett ◽  
Angela Gaylard ◽  
Konrad Müller ◽  
...  

Abstract Human/carnivore conflicts are common across the globe, and with a growing human population, this conflict is likely to increase as the space available to large carnivores is reduced. In South Africa, many small (< 400 km 2 ), fenced protected areas have reintroduced persecuted carnivores, such as brown hyenas ( Hyaena brunnea ). These reserves have great potential to conserve brown hyena populations; consequently, understanding the limitations that small, fenced reserves impose on space use patterns is needed. We investigated the home range (95% fixed kernel utilization distributions) and landscape determinants of habitat selection using resource selection functions for 10 brown hyenas in 3 separate fenced reserves. Home range sizes were consistently smaller in 2 of the reserves when compared to the third. Considerable variation in the selection of habitat features exists among individual brown hyenas and reserves. The most important landscape determinant driving brown hyena space use was distance to roads, with brown hyenas observed closer to roads when compared to random locations within their ranges. If this relationship with roads holds outside of protected areas, it could represent a considerable threat to the species. Thus, obtaining a better understanding of the influence of roads on brown hyenas represents an important focus for future research.


PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0248763
Author(s):  
Jocelyn L. Aycrigg ◽  
Adam G. Wells ◽  
Edward. O. Garton ◽  
Buck Magipane ◽  
Glen E. Liston ◽  
...  

Arctic and boreal environments are changing rapidly, which could decouple behavioral and demographic traits of animals from the resource pulses that have shaped their evolution. Dall’s sheep (Ovis dalli dalli) in northwestern regions of the USA and Canada, survive long, severe winters and reproduce during summers with short growing seasons. We sought to understand the vulnerability of Dall’s sheep to a changing climate in Lake Clark National Park and Preserve, Alaska, USA. We developed ecological hypotheses about nutritional needs, security from predators, energetic costs of movement, and thermal shelter to describe habitat selection during winter, spring, and summer and evaluated habitat and climate variables that reflected these hypotheses. We used the synoptic model of animal space use to estimate parameters of habitat selection by individual females and calculated likelihoods for ecological hypotheses within seasonal models. Our results showed that seasonal habitat selection was influenced by multiple ecological requirements simultaneously. Across all seasons, sheep selected steep rugged areas near escape terrain for security from predators. During winter and spring, sheep selected habitats with increased forage and security, moderated thermal conditions, and lowered energetic costs of movement. During summer, nutritional needs and security influenced habitat selection. Climate directly influenced habitat selection during the spring lambing period when sheep selected areas with lower snow depths, less snow cover, and higher air temperatures. Indirectly, climate is linked to the expansion of shrub/scrub vegetation, which was significantly avoided in all seasons. Dall’s sheep balance resource selection to meet multiple needs across seasons and such behaviors are finely tuned to patterns of phenology and climate. Direct and indirect effects of a changing climate may reduce their ability to balance their needs and lead to continued population declines. However, several management approaches could promote resiliency of alpine habitats that support Dall’s sheep populations.


2018 ◽  
Vol 100 (1) ◽  
pp. 239-248
Author(s):  
Christopher R Anthony ◽  
Dana M Sanchez

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Chunlei Xia ◽  
Longwen Fu ◽  
Zuoyi Liu ◽  
Hui Liu ◽  
Lingxin Chen ◽  
...  

Video tracking based biological early warning system achieved a great progress with advanced computer vision and machine learning methods. Ability of video tracking of multiple biological organisms has been largely improved in recent years. Video based behavioral monitoring has become a common tool for acquiring quantified behavioral data for aquatic risk assessment. Investigation of behavioral responses under chemical and environmental stress has been boosted by rapidly developed machine learning and artificial intelligence. In this paper, we introduce the fundamental of video tracking and present the pioneer works in precise tracking of a group of individuals in 2D and 3D space. Technical and practical issues suffered in video tracking are explained. Subsequently, the toxic analysis based on fish behavioral data is summarized. Frequently used computational methods and machine learning are explained with their applications in aquatic toxicity detection and abnormal pattern analysis. Finally, advantages of recent developed deep learning approach in toxic prediction are presented.


2019 ◽  
Vol 83 (3) ◽  
pp. 705-713 ◽  
Author(s):  
Brian W. Moser ◽  
Edward O. Garton

2019 ◽  
Vol 132 (2) ◽  
pp. 126-139 ◽  
Author(s):  
Tera L. Edkins ◽  
Christopher M. Somers ◽  
Mark C. Vanderwel ◽  
Miranda J. Sadar ◽  
Ray G. Poulin

Pituophis catenifer sayi (Bullsnake) is a sparsely studied subspecies of conservation concern in Canada. Basic ecological information is lacking for P. c. sayi, which reaches its northern range limit in western Canada. To address this gap, we used radio-telemetry to examine space use and habitat selection in three populations of Bullsnakes in disjunct river valley systems (Frenchman, Big Muddy, and South Saskatchewan River Valleys) across their Saskatchewan range. Bullsnakes in two valleys used up to three times more space, travelled 2.5-times farther from overwintering sites, and had lower home range overlap than the third population. Landscape-level habitat selection was flexible, with snakes in all populations using both natural and human-modified habitats most frequently. Fine-scale habitat selection was also similar among populations, with Bullsnakes selecting sites within 1 m of refuges, regardless of whether they were natural or anthropogenic. Based on these results, Bullsnakes are flexible in their broad scale habitat use, as long as they are provided with fine scale refuge sites. The distribution of key seasonal resources appears to ultimately determine space use and habitat selection by Bullsnakes, regardless of the geographic location of the population.


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