Mass effects mediate coexistence in competing shrews.

Recent developments in metacommunity theory have raised awareness that processes occurring at regional scales might interfere with local dynamics and affect conditions for the local coexistence of competing species. Four main paradigms are recognized in this context (namely, neutral, patch-dynamics, species-sorting, and mass-effect), which differ according to the role assigned to ecological or life-history differences among competing species, as well as to the relative time scale of regional vs. local dynamics. We investigated the patterns of regional and local coexistence of two species of shrews (Crocidura russula and Sorex coronatus) sharing a similar diet (generalist insectivores) over four generations, in a spatially structured habitat at the altitudinal limit of their distributions. Local populations were small, and regional dynamics were strong, with high rates of extinction and recolonization. Niche analysis revealed significant habitat differentiation on a few important variables, including temperature and availability of winter resting sites. In sites suitable for both species, we found instances of local coexistence with no evidence of competitive exclusion. Patterns of temporal succession did not differ from random, with no suggestion of a colonization-competition trade-off. Altogether, our data provide support for the mass-effect paradigm, where regional coexistence is mediated by specialization on different habitat types, and local coexistence by rescue effects from source sites. The strong regional dynamics and demographic stochasticity, together with high dispersal rates, presumably contributed to mass effects by overriding local differences in specific competitive abilities.

Structured RNAs in the ENCODE selected regions of the human genome.

Functional RNA structures play an important role both in the context of noncoding RNA transcripts as well as regulatory elements in mRNAs. Here we present a computational study to detect functional RNA structures within the ENCODE regions of the human genome. Since structural RNAs in general lack characteristic signals in primary sequence, comparative approaches evaluating evolutionary conservation of structures are most promising. We have used three recently introduced programs based on either phylogenetic-stochastic context-free grammar (EvoFold) or energy directed folding (RNAz and AlifoldZ), yielding several thousand candidate structures (corresponding to approximately 2.7% of the ENCODE regions). EvoFold has its highest sensitivity in highly conserved and relatively AU-rich regions, while RNAz favors slightly GC-rich regions, resulting in a relatively small overlap between methods. Comparison with the GENCODE annotation points to functional RNAs in all genomic contexts, with a slightly increased density in 3'-UTRs. While we estimate a significant false discovery rate of approximately 50%-70% many of the predictions can be further substantiated by additional criteria: 248 loci are predicted by both RNAz and EvoFold, and an additional 239 RNAz or EvoFold predictions are supported by the (more stringent) AlifoldZ algorithm. Five hundred seventy RNAz structure predictions fall into regions that show signs of selection pressure also on the sequence level (i.e., conserved elements). More than 700 predictions overlap with noncoding transcripts detected by oligonucleotide tiling arrays. One hundred seventy-five selected candidates were tested by RT-PCR in six tissues, and expression could be verified in 43 cases (24.6%).

Local adaptation and matching habitat choice in female barn owls with respect to melanic coloration.

Local adaptation is a major mechanism underlying the maintenance of phenotypic variation in spatially heterogeneous environments. In the barn owl (Tyto alba), dark and pale reddish-pheomelanic individuals are adapted to conditions prevailing in northern and southern Europe, respectively. Using a long-term dataset from Central Europe, we report results consistent with the hypothesis that the different pheomelanic phenotypes are adapted to specific local conditions in females, but not in males. Compared to whitish females, reddish females bred in sites surrounded by more arable fields and less forests. Colour-dependent habitat choice was apparently beneficial. First, whitish females produced more fledglings when breeding in wooded areas, whereas reddish females when breeding in sites with more arable fields. Second, cross-fostering experiments showed that female nestlings grew wings more rapidly when both their foster and biological mothers were of similar colour. The latter result suggests that mothers should particularly produce daughters in environments that best match their own coloration. Accordingly, whiter females produced fewer daughters in territories with more arable fields. In conclusion, females displaying alternative melanic phenotypes bred in habitats providing them with the highest fitness benefits. Although small in magnitude, matching habitat selection and local adaptation may help maintain variation in pheomelanin coloration in the barn owl.

Variation in habitat suitability does not always relate to variation in species' plant functional traits.

Habitat suitability models, which relate species occurrences to environmental variables, are assumed to predict suitable conditions for a given species. If these models are reliable, they should relate to change in plant growth and function. In this paper, we ask the question whether habitat suitability models are able to predict variation in plant functional traits, often assumed to be a good surrogate for a species' overall health and vigour. Using a thorough sampling design, we show a tight link between variation in plant functional traits and habitat suitability for some species, but not for others. Our contrasting results pave the way towards a better understanding of how species cope with varying habitat conditions and demonstrate that habitat suitability models can provide meaningful descriptions of the functional niche in some cases, but not in others.

IQRray, a new method for Affymetrix microarray quality control, and the homologous organ conservation score, a new benchmark method for quality control metrics.

MOTIVATION: Microarray results accumulated in public repositories are widely reused in meta-analytical studies and secondary databases. The quality of the data obtained with this technology varies from experiment to experiment, and an efficient method for quality assessment is necessary to ensure their reliability. RESULTS: The lack of a good benchmark has hampered evaluation of existing methods for quality control. In this study, we propose a new independent quality metric that is based on evolutionary conservation of expression profiles. We show, using 11 large organ-specific datasets, that IQRray, a new quality metrics developed by us, exhibits the highest correlation with this reference metric, among 14 metrics tested. IQRray outperforms other methods in identification of poor quality arrays in datasets composed of arrays from many independent experiments. In contrast, the performance of methods designed for detecting outliers in a single experiment like Normalized Unscaled Standard Error and Relative Log Expression was low because of the inability of these methods to detect datasets containing only low-quality arrays and because the scores cannot be directly compared between experiments. AVAILABILITY AND IMPLEMENTATION: The R implementation of IQRray is available at: ftp://lausanne.isb-sib.ch/pub/databases/Bgee/general/IQRray.R. CONTACT: Marta.Rosikiewicz@unil.ch SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Stochastic demography and the neutral substitution rate in class-structured populations.

The neutral rate of allelic substitution is analyzed for a class-structured population subject to a stationary stochastic demographic process. The substitution rate is shown to be generally equal to the effective mutation rate, and under overlapping generations it can be expressed as the effective mutation rate in newborns when measured in units of average generation time. With uniform mutation rate across classes the substitution rate reduces to the mutation rate.

Early-onset Crohn's disease is a risk factor for smaller final height.

OBJECTIVES: Growth retardation is a frequent complication of paediatric inflammatory bowel disease (IBD). Only a few studies report the final height of these patients, with controversial results. We compared adult height of patients with paediatric IBD with that of patients with adult-onset disease. METHODS: Height data of 675 women 19-44 years of age and 454 men 23-44 years of age obtained at inclusion in the Swiss IBD cohort study registry were grouped according to the age at diagnosis: (a) prepubertal (men≤13, women≤11 years), (b) pubertal (men 13-22, women 11-18 years) and (c) adult (men>22, women>18 years of age), and compared with each other and with healthy controls. RESULTS: Male patients with prepubertal onset of Crohn's disease (CD) had significantly lower final height (mean 172±6 cm, range 161-182) compared with men with pubertal (179±6 cm, 161-192) or adult (178±7 cm, 162-200) age at onset and the general population (178±7 cm, 142-204). Height z-scores standardized against heights of the normal population were significantly lower in all patients with a prepubertal diagnosis of CD (-0.8±0.9) compared with the other patient groups (-0.1±0.8, P<0.001). Prepubertal onset of CD emerged as a risk factor for reduced final height in patients with prepubertal CD. No difference for final height was found between patients with ulcerative or unclassified IBD diagnosed at prepubertal, pubertal or adult age. CONCLUSION: Prepubertal onset of CD is a risk for lower final height, independent of the initial disease location and the necessity for surgical interventions.

Habitat, breeding performance, diet and individual age in Swiss barn owls (Tyto alba)

Intensification of farming over the past 50 years has homogenised the landscape structure and contributed to the decline of bird populations in Europe. To better target the conservation of the Barn Owl Tyto alba, we assessed the influence of the landscape structure on breeding performance in western Switzerland. The analyses considered a 23-year data set of breeding parameters collected in an area dominated by intensive agriculture. Using a Geographic Information System approach, landscape characteristics were described around 194 nest sites. Our analyses showed that nest-box occupancy, laying date, clutch and brood size, egg volume and probability of producing a second annual clutch were not significantly associated with any of the eight principal landscape variables (agricultural land, woodland, urban area, hedgerows, cereals, sugar beet, maize and meadow). Nevertheless, the probability that a breeding pair occupied a nest-box decreased the more roads there were surrounding the nest-box. The absence of strong associations between habitat features and breeding parameters suggests that prey availability may be relatively similar between the different breeding sites. In our study area Barn Owls can always find suitable foraging habitats around most nest-boxes.

Structured output SVM for remote sensing image classification

In the recent years, kernel methods have revealed very powerful tools in many application domains in general and in remote sensing image classification in particular. The special characteristics of remote sensing images (high dimension, few labeled samples and different noise sources) are efficiently dealt with kernel machines. In this paper, we propose the use of structured output learning to improve remote sensing image classification based on kernels. Structured output learning is concerned with the design of machine learning algorithms that not only implement input-output mapping, but also take into account the relations between output labels, thus generalizing unstructured kernel methods. We analyze the framework and introduce it to the remote sensing community. Output similarity is here encoded into SVM classifiers by modifying the model loss function and the kernel function either independently or jointly. Experiments on a very high resolution (VHR) image classification problem shows promising results and opens a wide field of research with structured output kernel methods.