Preliminary Field Data on Group Size, Diet and Activity in the Alaotran Gentle Lemur Hapalemur griseus alaotrensis

1998 ◽  
Vol 69 (5) ◽  
pp. 325-330 ◽  
Author(s):  
Thomas Mutschler ◽  
Anna T. Feistner ◽  
Caroline M. Nievergelt
2001 ◽  
Vol 52 (8) ◽  
pp. 1113 ◽  
Author(s):  
William F. Herrnkind ◽  
Michael J. Childress ◽  
Kari L. Lavalli

Caribbean spiny lobsters show strikingly coordinated queuing behaviour and resting, outward-facing radial formations, especially during mass migrations when large numbers cross shelter-poor substrate in daylight. The close association of individual lobsters during these behaviours could be due to chance or some benefit of association such as dilution (and associated selfish-herd effects), group vigilance, cooperative defence, and/or drag reduction during migration. To infer probable beneficial functions, we examined the frequency distributions of individuals and groups using a seven-year set of field data and additional behavioural observations in large seawater enclosures. Group size distributions were not significantly aggregated in dens during the non-migratory period but became highly aggregated during migration. The group size distributions of lobsters initially leaving dens and those observed moving in the open were statistically different from one another, indicating that group sizes at each of these steps in the migration are not simply the result of previous group sizes. The distribution of group sizes suggests that, during movement in the open, dilution, vigilance, cooperative defence, and/or drag reduction may all favour the formation of queues. During resting in the open, dilution, vigilance, and cooperative defence may continue to favour individuals that remain in formation within the group.


Mathematics ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 415
Author(s):  
Yong-Chao Su ◽  
Cheng-Yu Wu ◽  
Cheng-Hong Yang ◽  
Bo-Sheng Li ◽  
Sin-Hua Moi ◽  
...  

Cost–benefit analysis is widely used to elucidate the association between foraging group size and resource size. Despite advances in the development of theoretical frameworks, however, the empirical systems used for testing are hindered by the vagaries of field surveys and incomplete data. This study developed the three approaches to data imputation based on machine learning (ML) algorithms with the aim of rescuing valuable field data. Using 163 host spider webs (132 complete data and 31 incomplete data), our results indicated that the data imputation based on random forest algorithm outperformed classification and regression trees, the k-nearest neighbor, and other conventional approaches (Wilcoxon signed-rank test and correlation difference have p-value from < 0.001–0.030). We then used rescued data based on a natural system involving kleptoparasitic spiders from Taiwan and Vietnam (Argyrodes miniaceus, Theridiidae) to test the occurrence and group size of kleptoparasites in natural populations. Our partial least-squares path modelling (PLS-PM) results demonstrated that the size of the host web (T = 6.890, p = 0.000) is a significant feature affecting group size. The resource size (T = 2.590, p = 0.010) and the microclimate (T = 3.230, p = 0.001) are significant features affecting the presence of kleptoparasites. The test of conformation of group size distribution to the ideal free distribution (IFD) model revealed that predictions pertaining to per-capita resource size were underestimated (bootstrap resampling mean slopes <IFD predicted slopes, p < 0.001). These findings highlight the importance of applying appropriate ML methods to the handling of missing field data.


2001 ◽  
Vol 39 (1) ◽  
pp. 83-92 ◽  
Author(s):  
Cheryl Fimbel ◽  
Amy Vedder ◽  
Ellen Dierenfeld ◽  
Felix Mulindahabi

2008 ◽  
Author(s):  
Mark Levine ◽  
Rachel Best ◽  
Paul Taylor

1968 ◽  
Vol 8 (1, Pt.1) ◽  
pp. 79-82 ◽  
Author(s):  
Harold B. Gerard ◽  
Roland A. Wilhelmy ◽  
Edward S. Conolley
Keyword(s):  

Sign in / Sign up

Export Citation Format

Share Document