scholarly journals Spatial aggregation of fruits explains food selection in a neotropical primate (Alouatta pigra)

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
John F. Aristizabal ◽  
Simoneta Negrete-Yankelevich ◽  
Rogelio Macías-Ordóñez ◽  
Colin A. Chapman ◽  
Juan C. Serio-Silva

AbstractThe availability and spatial distribution of food resources affect animal behavior and survival. Black howler monkeys (Alouatta pigra) have a foraging strategy to balance their nutrient intake that involves mixing their consumption of leaves and fruits. The spatial aggregation of food items should impact this strategy, but how it does so is largely unknown. We quantified how leaf and fruit intake combined (here termed food set selection) was spatially aggregated in patches and how food aggregation varied across seasons. Using variograms we estimated patch diameter and with Generalized Least Square models determined the effect of food spatial aggregation on food selection. Only fruits were structured in patches in the season of highest availability (dry-season). The patches of food set selection had a diameter between 6.9 and 14 m and were explained by those of mature fruit availability which were between 18 and 19 m in diameter. Our results suggest that the spatial pattern of food selection is influenced by patches of large fruit-bearing trees, not by particular species. Fruit also occur along spatial gradients, but these do not explain food selection, suggesting that howlers maximize food intake in response to local aggregation of fruit that are limiting during certain seasons. We demonstrate how the independent spatial modelling of resources and behavior enables the definition of patches and testing their spatial relationship.

Primates ◽  
2010 ◽  
Vol 51 (4) ◽  
pp. 279-284 ◽  
Author(s):  
Sarie Van Belle ◽  
Aimee E. Kulp ◽  
Robyn Thiessen-Bock ◽  
Marisol Garcia ◽  
Alejandro Estrada

2011 ◽  
Vol 57 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Sarie Van BELLE ◽  
Alejandro Estrada ◽  
Karen B. Strier

Abstract We investigated the social relationships among adult females in two multimale-multifemale groups of black howler monkeys Alouatta pigra during a 14-month study in Palenque National Park, Mexico. Based on over 900 focal hours and over 5400 scan samples recording neighboring group members, we found that females very rarely engaged in agonistic interactions and no dominance hierarchy could be discerned. Relationships among resident females were primarily affiliative, but females of one study group spent a higher proportion of time in close proximity and engaged in affiliative interactions with one another at higher rates than females in the other study group. The strength of female relationships increased with the birth of an infant. Although no females immigrated during the study period, the temporary association of three extragroup females with our study groups implies that the social system of black howler monkeys is more dynamic than previously suggested. These findings suggest that female black howler monkeys behave more similarly to female red howler monkeys A. seniculus than to female mantled howler monkeys A. palliata.


Primates ◽  
1983 ◽  
Vol 24 (2) ◽  
pp. 290-296 ◽  
Author(s):  
Robert H. Horwich ◽  
Kris Gebhard

2011 ◽  
Vol 73 (9) ◽  
pp. 909-919 ◽  
Author(s):  
Noriko Nakamura ◽  
Katherine R. Amato ◽  
Paul Garber ◽  
Alejandro Estrada ◽  
Roderick I. Mackie ◽  
...  

2019 ◽  
Vol 277 ◽  
pp. 02007
Author(s):  
Qingzhi Zhang ◽  
Panfeng Wu ◽  
Xiaohui Du ◽  
Hualiang Sun ◽  
Lijia Yu

With the extensive application of deep learning in the field of human rehabilitation, skeleton based rehabilitation recognition is becoming more and more concerned with large-scale bone data sets. The key factor of this task is the two intra frame representations of the combined co-and the inter-frame. In this paper, an inter frame representation method based on RNN is proposed. Pointtion of each joint is joint-coded they are assembled into semantic both spatial and temporal domains.we introduce a global spatial aggregation which is able to learn superior joint co features over local aggregation.


2014 ◽  
Vol 155 (4) ◽  
pp. 652-664 ◽  
Author(s):  
Katherine R. Amato ◽  
Steven R. Leigh ◽  
Angela Kent ◽  
Roderick I. Mackie ◽  
Carl J. Yeoman ◽  
...  

1999 ◽  
Vol 87 (2) ◽  
pp. 181-190 ◽  
Author(s):  
Linde E.T Ostro ◽  
Scott C Silver ◽  
Fred W Koontz ◽  
Truman P Young ◽  
Robert H Horwich

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