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Identifying environmental versus phylogenetic correlates of behavioural ecology in gibbons: implications for conservation management of the world's rarest ape.

Bryant JV, Olson VA, Chatterjee HJ, Turvey ST - BMC Evol. Biol. (2015)

Bottom Line: For conservation of highly threatened species to be effective, it is crucial to differentiate natural population parameters from atypical behavioural, ecological and demographic characteristics associated with human disturbance and habitat degradation, which can constrain population growth and recovery.Predictive models incorporating intraspecific trait variation but controlling for covariance between population samples due to phylogenetic relatedness reveal additional environmental and biological determinants of variation in gibbon ranging requirements and social structure, but not those immediately associated with recent habitat degradation.This approach reveals key insights with a direct impact on future Hainan gibbon conservation planning, and demonstrates the usefulness of the comparative approach for informing management of species of conservation concern.

View Article: PubMed Central - PubMed

Affiliation: Institute of Zoology, Zoological Society of London, Regent's Park, London, NW1 4RY, UK. jessica.bryant@ioz.ac.uk.

ABSTRACT

Background: For conservation of highly threatened species to be effective, it is crucial to differentiate natural population parameters from atypical behavioural, ecological and demographic characteristics associated with human disturbance and habitat degradation, which can constrain population growth and recovery. Unfortunately, these parameters can be very hard to determine for species of extreme rarity. The Hainan gibbon (Nomascus hainanus), the world's rarest ape, consists of a single population of c.25 individuals, but intensive management is constrained by a limited understanding of the species' expected population characteristics and environmental requirements. In order to generate a more robust evidence-base for Hainan gibbon conservation, we employed a comparative approach to identify intrinsic and extrinsic drivers of variation in key ecological and behavioural traits (home range size, social group size, mating system) across the Hylobatidae while controlling for phylogenetic non-independence.

Results: All three studied traits show strong phylogenetic signals across the Hylobatidae. Although the Hainan gibbon and some closely related species have large reported group sizes, no observed gibbon group size is significantly different from the values expected on the basis of phylogenetic relationship alone. However, the Hainan gibbon and two other Nomascus species (N. concolor, N. nasutus) show home range values that are higher than expected relative to all other gibbon species. Predictive models incorporating intraspecific trait variation but controlling for covariance between population samples due to phylogenetic relatedness reveal additional environmental and biological determinants of variation in gibbon ranging requirements and social structure, but not those immediately associated with recent habitat degradation.

Conclusions: Our study represents the first systematic assessment of behavioural and ecological trait patterns across the Hylobatidae using recent approaches in comparative analysis. By formally contextualising the Hainan gibbon's observed behavioural and ecological characteristics within family-wide variation in gibbons, we are able to determine natural population parameters expected for this Critically Endangered species, as well as wider correlates of variation for key population characteristics across the Hylobatidae. This approach reveals key insights with a direct impact on future Hainan gibbon conservation planning, and demonstrates the usefulness of the comparative approach for informing management of species of conservation concern.

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Assessment of model fit for best-approximating home range and group size predictive models: scatterplots of model fit: (a) observed HR values (log-transformed) versus values predicted under best-approximating linear mixed-effects kinship model for HR (log values); (b) observed GS values (log-transformed) versus values predicted under best-approximating linear mixed-effects kinship model for GS (log values); (c) HR values predicted under best-approximating linear mixed-effects kinship model for HR (log values) versus model residuals; (d) GS values predicted under best-approximating linear mixed-effects kinship model for GS (log values) versus model residuals
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Fig2: Assessment of model fit for best-approximating home range and group size predictive models: scatterplots of model fit: (a) observed HR values (log-transformed) versus values predicted under best-approximating linear mixed-effects kinship model for HR (log values); (b) observed GS values (log-transformed) versus values predicted under best-approximating linear mixed-effects kinship model for GS (log values); (c) HR values predicted under best-approximating linear mixed-effects kinship model for HR (log values) versus model residuals; (d) GS values predicted under best-approximating linear mixed-effects kinship model for GS (log values) versus model residuals

Mentions: Assessment of model fit supports the validity of the best-approximating HR and GS models. Observed HR and GS values display linear trends when compared to values predicted by the top-ranking models (Fig. 2a–b), indicating that specification of main effects only did not result in poor fit due to omission of any major interaction terms. Plots of residuals versus predicted values from each model further confirms adequacy of both models, with points scattering around zero and no obvious linearity or curvature (Fig. 2c–d).Fig. 2


Identifying environmental versus phylogenetic correlates of behavioural ecology in gibbons: implications for conservation management of the world's rarest ape.

Bryant JV, Olson VA, Chatterjee HJ, Turvey ST - BMC Evol. Biol. (2015)

Assessment of model fit for best-approximating home range and group size predictive models: scatterplots of model fit: (a) observed HR values (log-transformed) versus values predicted under best-approximating linear mixed-effects kinship model for HR (log values); (b) observed GS values (log-transformed) versus values predicted under best-approximating linear mixed-effects kinship model for GS (log values); (c) HR values predicted under best-approximating linear mixed-effects kinship model for HR (log values) versus model residuals; (d) GS values predicted under best-approximating linear mixed-effects kinship model for GS (log values) versus model residuals
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4549120&req=5

Fig2: Assessment of model fit for best-approximating home range and group size predictive models: scatterplots of model fit: (a) observed HR values (log-transformed) versus values predicted under best-approximating linear mixed-effects kinship model for HR (log values); (b) observed GS values (log-transformed) versus values predicted under best-approximating linear mixed-effects kinship model for GS (log values); (c) HR values predicted under best-approximating linear mixed-effects kinship model for HR (log values) versus model residuals; (d) GS values predicted under best-approximating linear mixed-effects kinship model for GS (log values) versus model residuals
Mentions: Assessment of model fit supports the validity of the best-approximating HR and GS models. Observed HR and GS values display linear trends when compared to values predicted by the top-ranking models (Fig. 2a–b), indicating that specification of main effects only did not result in poor fit due to omission of any major interaction terms. Plots of residuals versus predicted values from each model further confirms adequacy of both models, with points scattering around zero and no obvious linearity or curvature (Fig. 2c–d).Fig. 2

Bottom Line: For conservation of highly threatened species to be effective, it is crucial to differentiate natural population parameters from atypical behavioural, ecological and demographic characteristics associated with human disturbance and habitat degradation, which can constrain population growth and recovery.Predictive models incorporating intraspecific trait variation but controlling for covariance between population samples due to phylogenetic relatedness reveal additional environmental and biological determinants of variation in gibbon ranging requirements and social structure, but not those immediately associated with recent habitat degradation.This approach reveals key insights with a direct impact on future Hainan gibbon conservation planning, and demonstrates the usefulness of the comparative approach for informing management of species of conservation concern.

View Article: PubMed Central - PubMed

Affiliation: Institute of Zoology, Zoological Society of London, Regent's Park, London, NW1 4RY, UK. jessica.bryant@ioz.ac.uk.

ABSTRACT

Background: For conservation of highly threatened species to be effective, it is crucial to differentiate natural population parameters from atypical behavioural, ecological and demographic characteristics associated with human disturbance and habitat degradation, which can constrain population growth and recovery. Unfortunately, these parameters can be very hard to determine for species of extreme rarity. The Hainan gibbon (Nomascus hainanus), the world's rarest ape, consists of a single population of c.25 individuals, but intensive management is constrained by a limited understanding of the species' expected population characteristics and environmental requirements. In order to generate a more robust evidence-base for Hainan gibbon conservation, we employed a comparative approach to identify intrinsic and extrinsic drivers of variation in key ecological and behavioural traits (home range size, social group size, mating system) across the Hylobatidae while controlling for phylogenetic non-independence.

Results: All three studied traits show strong phylogenetic signals across the Hylobatidae. Although the Hainan gibbon and some closely related species have large reported group sizes, no observed gibbon group size is significantly different from the values expected on the basis of phylogenetic relationship alone. However, the Hainan gibbon and two other Nomascus species (N. concolor, N. nasutus) show home range values that are higher than expected relative to all other gibbon species. Predictive models incorporating intraspecific trait variation but controlling for covariance between population samples due to phylogenetic relatedness reveal additional environmental and biological determinants of variation in gibbon ranging requirements and social structure, but not those immediately associated with recent habitat degradation.

Conclusions: Our study represents the first systematic assessment of behavioural and ecological trait patterns across the Hylobatidae using recent approaches in comparative analysis. By formally contextualising the Hainan gibbon's observed behavioural and ecological characteristics within family-wide variation in gibbons, we are able to determine natural population parameters expected for this Critically Endangered species, as well as wider correlates of variation for key population characteristics across the Hylobatidae. This approach reveals key insights with a direct impact on future Hainan gibbon conservation planning, and demonstrates the usefulness of the comparative approach for informing management of species of conservation concern.

Show MeSH