Exploration Behavior and Morphology are Correlated in Captive Gray Mouse Lemurs (<Emphasis Type="Italic">Microcebus murinus</Emphasis>)

Behavior varies among individuals and is flexible within individuals. However, studies of behavioral syndromes and animal personality have demonstrated that animals can show consistency in their behavior and as such may be restricted in their behavioral responses. Like any other trait, including morphology, performance, or physiology, personality is now considered an important component of ecology and may have fitness consequences. Moreover, in some species personality correlates with other traits, as predicted in the context of a recent theoretical framework postulating that individual differences in growth and body size can affect behavior through effects on growth–mortality tradeoffs. This “pace of life” hypothesis predicts that animals that explore more should be larger and have higher growth rates than those that explore less. We tested for associations between morphology and a behavioral trait in a captive colony of gray mouse lemurs (Microcebus murinus). We used open-field tests to evaluate exploration behavior and measured a series of morphological traits in 72 individuals (32 males and 40 females). Our results show that the latency to start exploring correlates positively with adult body size and body weight at birth. These data provide evidence for a link between morphology and behavior in this species, thus supporting predictions of dispersal models but diverging from the predictions of the “pace of life” model.     

Female reproduction bears no survival cost in captivity for gray mouse lemurs

The survival cost of reproduction has been revealed in many free‐ranging vertebrates. However, recent studies on captive populations failed to detect this cost. Theoretically, this lack of survival/reproduction trade‐off is expected when resources are not limiting, but these studies may have failed to detect the cost, as they may not have fully accounted for potential confounding effects, in particular interindividual heterogeneity. Here, we investigated the effects of current and past reproductive effort on later survival in captive females of a small primate, the gray mouse lemur. Survival analyses showed no cost of reproduction in females; and the pattern was even in the opposite direction: the higher the reproductive effort, the higher the chances of survival until the next reproductive event. These conclusions hold even while accounting for interindividual heterogeneity. In agreement with aforementioned studies on captive vertebrates, these results remind us that reproduction is expected to be traded against body maintenance and the survival prospect only when resources are so limiting that they induce an allocation trade‐off. Thus, the cost of reproduction has a major extrinsic component driven by environmental conditions.     

Low Inbreeding and High Pollen Dispersal Distances in Populations of Two Amazonian Forest Tree Species

Recent studies suggest that tropical tree species exhibit low inbreeding and high gene dispersal levels despite the typically low density of conspecifics in tropical forests. To examine this, we undertook a study of pollen gene dispersal and mating system of two Amazonian tree species. We analyzed 341 seeds from 33 trees at four microsatellite loci in a Carapa guianensis population from Brazil, and 212 seeds from 22 trees at four microsatellite loci in a Sextonia rubra population from French Guiana. Differentiation of allele frequencies among the pollen pool of individual trees was Φ_FT= 0.053 (95% CI: 0.027–0.074) for C. guianensis and Φ_FT= 0.064 (95% CI: 0.017–0.088) for S. rubra. The mean pollen dispersal distances were estimated at 69–355 m for C. guianensis , and 86–303 m for S. rubra , depending on the pollen dispersal model and the estimate of reproductive tree density used. The multi-locus outcrossing rate was estimated at 0.918 and 0.945, and the correlation of paternity at 0.089 and 0.096, for C. guianensis and S. rubra , respectively, while no significant levels of biparental inbreeding were detected. Comparing trees with high and low local density of conspecifics, we found no evidence for differences in inbreeding levels. The results are discussed within the framework of the emerging picture of the reproductive biology of tropical forest trees.     

Proposed minimum reporting standards for chemical analysis

There is a general consensus that supports the need for standardized reporting of metadata or information describing large-scale metabolomics and other functional genomics data sets. Reporting of standard metadata provides a biological and empirical context for the data, facilitates experimental replication, and enables the re-interrogation and comparison of data by others. Accordingly, the Metabolomics Standards Initiative is building a general consensus concerning the minimum reporting standards for metabolomics experiments of which the Chemical Analysis Working Group (CAWG) is a member of this community effort. This article proposes the minimum reporting standards related to the chemical analysis aspects of metabolomics experiments including: sample preparation, experimental analysis, quality control, metabolite identification, and data pre-processing. These minimum standards currently focus mostly upon mass spectrometry and nuclear magnetic resonance spectroscopy due to the popularity of these techniques in metabolomics. However, additional input concerning other techniques is welcomed and can be provided via the CAWG on-line discussion forum at or . Further, community input related to this document can also be provided via this electronic forum. The contents of this paper do not necessarily reflect any position of the Government or the opinion of the Food and Drug Administration Sponsor: Metabolomics Society http://www.metabolomicssociety.org/ Reference: http://msi-workgroups.sourceforge.net/bio-metadata/reporting/pbc/ http://msi-workgroups.sourceforge.net/chemical-analysis/ Version: Revision: 5.1 Date: 09 January, 2007     

Proposed reporting requirements for the description of NMR-based metabolomics experiments

The amount of data generated by NMR-based metabolomic experiments is increasing rapidly. Furthermore, diverse techniques increase the need for informative and comprehensive meta-data. These factors present a challenge in the dissemination, interpretation, reviewing and comparison of experimental results using this technology. Thus, there is a strong case for unification and standardisation of the data representation for both academia and industry. Here, a systems analysis of an NMR-based metabolomics experiment is presented in order to reveal the reporting requirements. An in-depth analysis of the NMR component of a metabolomics experiment has been produced, and a first round of data standard development completed. This has focussed on both one- and two-dimensional ¹H NMR experiments, but is also applicable to higher dimensions and other nuclei. We also report the modelling of this schema using Unified Modelling Language (UML), and have extended this to a proof-of-concept implementation of the standard as an XML schema.     

A metal-coded affinity tag approach to quantitative proteomics

The quantitative analysis of protein mixtures is pivotal for the understanding of variations in the proteome of living systems. Therefore, approaches have been recently devised that generally allow the relative quantitative analysis of peptides and proteins. Here we present proof of concept of the new metal-coded affinity tag (MeCAT) technique, which allowed the quantitative determination of peptides and proteins. A macrocyclic metal chelate complex (1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA)) loaded with different lanthanides (metal(III) ions) was the essential part of the tag. The combination of DOTA with an affinity anchor for purification and a reactive group for reaction with amino acids constituted a reagent that allowed quantification of peptides and proteins in an absolute fashion. For the quantitative determination, the tagged peptides and proteins were analyzed using flow injection inductively coupled plasma MS, a technique that allowed detection of metals with high precision and low detection limits. The metal chelate complexes were attached to the cysteine residues, and the course of the labeling reaction was followed using SDS-PAGE and MALDI-TOF MS, ESI MS, and inductively coupled plasma MS. To limit the width in isotopic signal spread and to increase the sensitivity for ESI analysis, we used the monoisotopic lanthanide macrocycle complexes. Peptides tagged with the reagent loaded with different metals coelute in liquid chromatography. In first applications with proteins, the calculated detection limit for bovine serum albumin for example was 110 amol, and we have used MeCAT to analyze proteins of the Sus scrofa eye lens as a model system. These data showed that MeCAT allowed quantification not only of peptides but also of proteins in an absolute fashion at low concentrations and in complex mixtures.     

Testing and interpreting the shared space‐environment fraction in variation partitioning analyses of ecological data

Variation partitioning analyses combined with spatial predictors (Moran's eigenvector maps, MEM) are commonly used in ecology to test the fractions of species abundance variation purely explained by environment and space. However, while these pure fractions can be tested using a classical residuals permutation procedure, no specific method has been developed to test the shared space‐environment fraction (SSEF). Yet, the SSEF is expected to encompass a major driver of community assembly, that is, an induced spatial dependence effect (ISD; i.e. the reflection of a spatially structured habitat filter on a species distribution). A reliable test of this fraction is therefore crucial to properly test the presence of an ISD on ecological data. To bridge the gap, we propose to test the SSEF through spatially‐constrained null models: torus‐translations, and Moran spectral randomisations. We investigated the type I error rate and statistical power of our method based on two real environmental datasets and simulations of tree distributions. Ten types of tree distribution displaying contrasted aggregation properties were simulated, and their abundances were sampled in 153 regularly‐distributed 20 × 20 m quadrats. The SSEF was tested for 1000 simulated tree distributions either unrelated to the environment, or filtered by environmental variables displaying contrasting spatial structures. The method proposed provided a correct type I error rate (< 0.05). The statistical power was high (> 0.9) when abundances were filtered by an environmental variable structured at broad scale. However, the spatial resolution allowed by the sampling design limited the power of the method when using a fine‐scale filtering variable. This highlighted that an ISD can be properly detected providing that the spatial pattern of the filtering process is correctly captured by the sampling design of the study. An R function to apply the SSEF testing method is provided and detailed in a tutorial.