Article (Scientific journals)
Bonobo nest site selection and the importance of predictor scales in primate ecology
Serckx, Adeline; Huynen, Marie-Claude; Beudels-Jamar, R. C. et al.
2016In American Journal of Primatology, 78 (12), p. 1326-1343
Peer Reviewed verified by ORBi
 

Files


Full Text
serckx2016.pdf
Publisher postprint (2.08 MB)
Download

All documents in ORBi are protected by a user license.

Send to



Details



Keywords :
Pan paniscus; Primates
Abstract :
[en] The role of spatial scale in ecological pattern formation such as the geographical distribution of species has been a major theme in research for decades. Much progress has been made on identifying spatial scales of habitat influence on species distribution. Generally, the effect of a predictor variable on a response is evaluated over multiple, discrete spatial scales to identify an optimal scale of influence. However, the idea to identify one optimal scale of predictor influence is misleading. Species-environment relationships across scales are usually sigmoid increasing or decreasing rather than humped-shaped, because environmental conditions are generally highly autocorrelated. Here, we use nest count data on bonobos (Pan paniscus) to build distribution models which simultaneously evaluate the influence of several predictors at multiple spatial scales. More specifically, we used forest structure, availability of fruit trees and terrestrial herbaceous vegetation (THV) to reflect environmental constraints on bonobo ranging, feeding and nesting behaviour, respectively. A large number of models fitted the data equally well and revealed sigmoidal shapes for bonobo-environment relationships across scales. The influence of forest structure increased with distance and became particularly important, when including a neighbourhood of at least 750 m around observation points; for fruit availability and THV, predictor influence decreased with increasing distance and was mainly influential below 600 and 300 m, respectively. There was almost no difference in model fit, when weighing predictor values within the extraction neighbourhood by distance compared to simply taking the arithmetic mean of predictor values. The spatial scale models provide information on bonobo nesting preferences and are useful for the understanding of bonobo ecology and conservation, such as in the context of mitigating the impact of logging. The proposed approach is flexible and easily applicable to a wide range of species, response and predictor variables and over diverse spatial scales and ecological settings. © 2016 Wiley Periodicals, Inc.
Disciplines :
Environmental sciences & ecology
Author, co-author :
Serckx, Adeline ;  Université de Liège - ULiège > Département de Biologie, Ecologie et Evolution > Biologie du comportement - Ethologie et psychologie animale
Huynen, Marie-Claude ;  Université de Liège - ULiège > Département de Biologie, Ecologie et Evolution > Biologie du comportement - Ethologie et psychologie animale
Beudels-Jamar, R. C.;  Conservation Biology Unit, Royal Belgian Institute of Natural Sciences, Brussels, Belgium
Vimond, M.;  Primatology Research Group, Behavioral Biology Unit, University of Liege, Liege, Belgium
Bogaert, Jan  ;  Université de Liège - ULiège > Ingénierie des biosystèmes (Biose) > Biodiversité et Paysage
Kühl, H. S.;  Department of Primatology, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany, German Center for Integrative Biodiversity Research (iDiv), Leipzig, Germany
Language :
English
Title :
Bonobo nest site selection and the importance of predictor scales in primate ecology
Publication date :
2016
Journal title :
American Journal of Primatology
ISSN :
0275-2565
eISSN :
1098-2345
Publisher :
John Wiley and Sons Inc.
Volume :
78
Issue :
12
Pages :
1326-1343
Peer reviewed :
Peer Reviewed verified by ORBi
Available on ORBi :
since 05 October 2018

Statistics


Number of views
69 (6 by ULiège)
Number of downloads
216 (3 by ULiège)

Scopus citations®
 
13
Scopus citations®
without self-citations
12
OpenCitations
 
9

Bibliography


Similar publications



Contact ORBi