Revealing the biodiversity of Chilean birds through the COI barcode approach.

The mitochondrial cytochrome c oxidase subunit I (COI) gene is an effective molecular tool for the estimation of genetic variation and the identification of bird species. This molecular marker is used to differentiate among Chilean bird species by analyzing barcodes for 76 species (197 individuals), comprising 28 species with no previous barcode data and 48 species with sequences retrieved from the BOLD and GenBank databases. The DNA barcodes correctly identified 94.7% of the species analyzed (72 of 76 species). Mean intraspecific K2P distance was 0.3% (range 0-8.7%). Within the intraspecific divergence range, three species, Phrygilus gayi, Sephanoides sephanoides and Curaeus curaeus, showed relatively high intraspecific divergence (1.5-8.7%), possibly due to the presence of a species complex or geographic isolation of sub-populations. Mean interspecific K2P distance was 24.7% (range 1.3-43.5%). Consequently, the intraspecific K2P distance showed limited overlap with interspecific K2P distance. The mean intraspecific divergence in our study was similar to that found in temperate regions of South America (0.24%). However, it was approximately one order of magnitude lower than values reported for bird species in tropical regions of northern South America (1.8-2.13%). This result suggests that bird species from Chile show low levels of genetic structure and divergence. The small overlap between intra- and inter-specific distances implies that COI barcodes could be used as an effective tool to identify nearly all the Chilean bird species analyzed.

Genetic divergence analysis of the Common Barn Owl Tyto alba (Scopoli, 1769) and the Short-eared Owl Asio flammeus (Pontoppidan, 1763) from southern Chile using COI sequence.

In this paper new mitochondrial COI sequences of Common Barn Owl Tyto alba (Scopoli, 1769) and Short-eared Owl Asio flammeus (Pontoppidan, 1763) from southern Chile are reported and compared with sequences from other parts of the World. The intraspecific genetic divergence (mean p-distance) was 4.6 to 5.5% for the Common Barn Owl in comparison with specimens from northern Europe and Australasia and 3.1% for the Short-eared Owl with respect to samples from north America, northern Europe and northern Asia. Phylogenetic analyses revealed three distinctive groups for the Common Barn Owl: (i) South America (Chile and Argentina) plus Central and North America, (ii) northern Europe and (iii) Australasia, and two distinctive groups for the Short-eared Owl: (i) South America (Chile and Argentina) and (ii) north America plus northern Europe and northern Asia. The level of genetic divergence observed in both species exceeds the upper limit of intraspecific comparisons reported previously for Strigiformes. Therefore, this suggests that further research is needed to assess the taxonomic status, particularly for the Chilean populations that, to date, have been identified as belonging to these species through traditional taxonomy.

Effects of sampling regime on the mean and variance of home range size estimates.

1. Although the home range is a fundamental ecological concept, there is considerable debate over how it is best measured. There is a substantial literature concerning the precision and accuracy of all commonly used home range estimation methods; however, there has been considerably less work concerning how estimates vary with sampling regime, and how this affects statistical inferences. 2. We propose a new procedure, based on a variance components analysis using generalized mixed effects models to examine how estimates vary with sampling regime. 3. To demonstrate the method we analyse data from one study of 32 individually marked roe deer and another study of 21 individually marked kestrels. We subsampled these data to simulate increasingly less intense sampling regimes, and compared the performance of two kernel density estimation (KDE) methods, of the minimum convex polygon (MCP) and of the bivariate ellipse methods. 4. Variation between individuals and study areas contributed most to the total variance in home range size. Contrary to recent concerns over reliability, both KDE methods were remarkably efficient, robust and unbiased: 10 fixes per month, if collected over a standardized number of days, were sufficient for accurate estimates of home range size. However, the commonly used 95% isopleth should be avoided; we recommend using isopleths between 90 and 50%. 5. Using the same number of fixes does not guarantee unbiased home range estimates: statistical inferences differ with the number of days sampled, even if using KDE methods. 6. The MCP method was highly inefficient and results were subject to considerable and unpredictable biases. The bivariate ellipse was not the most reliable method at low sample sizes. 7. We conclude that effort should be directed at marking more individuals monitored over long periods at the expense of the sampling rate per individual. Statistical results are reliable only if the whole sampling regime is standardized. We derive practical guidelines for field studies and data analysis.

An integrated approach to identify spatiotemporal and individual-level determinants of animal home range size.

Animal home range use is a central focus of ecological research. However, how and why home range size varies between individuals is not well studied or understood for most species. We develop a hierarchical analytical approach--using generalized linear mixed-effects modeling of time series of home range sizes--that allows variance in home range size to be decomposed into components due to variation in temporal, spatial, and individual-level processes, also facilitating intra- and interspecific comparative analyses. We applied the approach to data from a roe deer population radiotracked in central Italy. Over multiple timescales, temporal variation is explained by photoperiod and climate and spatial variation by the distribution of habitat types and spatial variance in radiotracking error. Differences between individuals explained a substantial amount of variance in home range size, but only a relatively minor part was explained by the individual attributes of sex and age. We conclude that the choice of temporal scale at which data are collected and the definition of home range can significantly influence biological inference. We suggest that the appropriate choice of scale and definition requires a good understanding of the ecology and life history of the study species. Our findings contrast with several common assumptions about roe deer behavior.