Mist nets are one of the most widely used techniques in the study of birds and bats worldwide. However, a number of risks are involved, including opportunistic predation. Given this potential cost, here we: (1) review the global literature to understand the factors that might contribute to predation risk for birds and bats captured in mist nets; (2) review existing guidelines for best practice use of mist nets; and (3) based on our reviews, recommend new guidelines for the use of mist nets to minimize the risk of opportunistic predation. Based on keyword in English, Spanish, Portuguese, and French, and using Google Scholar, Scopus, SciElo, and Web of Science, we found 48 articles reporting opportunistic predation. In the included articles, 178 predation events, involving 52 predator and 84 prey species, were reported. In most of the reports, the mist nets were placed at ground level, the bats and birds were preyed on from the shelf closest to the ground, the mist-net checks occurred at intervals of 1 h or 30 min and the most common predators were arboreal and scansorial species (primates and marsupials). Despite the occurrences of predation in 13 countries, guidelines for best practice mist-net use were found in only three, despite extensive searches and contact with key people in each country. Based on the existing guidelines and our results, we recommend that mist nets be fixed with the lowest shelf at least 50 cm above ground level and be checked at 15-min intervals; when predators are observed near mist nets, the nets either be constantly observed, closed, or relocated; suppressed the vegetation around the mist nets; captured animals be removed from the mist nets as soon as possible, and more than one researcher/technician should be in the field at all times.

Mitogenomic data are increasingly used in evolutionary biology and ecology, stressing the importance for double checking the authenticity of DNA sequences. For example, Szcześniak et al. (2013) recently published the mitochondrial genome of a bat, the Leschenault\'s rousette (Rousettus leschenaultii). Here we show using straightforward phylogenetic analyses of available chiropteran sequence data that the taxonomic attribution of the reported mitogenome is erroneous. The purportedly-new complete mitochondrial genome likely belongs to the Egyptian fruit bat (R. aegyptiacus) for which a reference sequence already exists. We propose that future articles reporting complete mitochondrial genome sequences should mandatorily include maximum likelihood trees inferred from (i) the standard barcoding marker for the taxon under focus, which would benefit from the massive data available in public databases, and (ii) the available mitogenomes of closely related species. We also strongly advise these trees be presented as phylograms so that all pertinent phylogenetic information is displayed in the form of a topology and its associated branch lengths. Along with compulsory information on the geographical location and origin of the specimen, these new standards should help avoiding the publication of taxonomically misidentified mitogenomes that might end up as reference sequences in public databases and re-used in subsequent meta-analyses.

Infectious disease ecology has recently raised its public profile beyond the scientific community due to the major threats that wildlife infections pose to biological conservation, animal welfare, human health and food security. As we start unravelling the full extent of emerging infectious diseases, there is an urgent need to facilitate multidisciplinary research in this area. Even though research in ecology has always had a strong theoretical component, cultural and technical hurdles often hamper direct collaboration between theoreticians and empiricists. Building upon our collective experience of multidisciplinary research and teaching in this area, we propose practical guidelines to help with effective integration among mathematical modelling, fieldwork and laboratory work. Modelling tools can be used at all steps of a field-based research programme, from the formulation of working hypotheses to field study design and data analysis. We illustrate our model-guided fieldwork framework with two case studies we have been conducting on wildlife infectious diseases: plague transmission in prairie dogs and lyssavirus dynamics in American and African bats. These demonstrate that mechanistic models, if properly integrated in research programmes, can provide a framework for holistic approaches to complex biological systems.

Resolution of the total evidence (i.e., character congruence) versus consensus (i.e., taxonomic congruence) debate has been impeded by (1) a failure to employ validation methods consistently across both tree-building and consensus analyses, (2) the incomparability of methods for constructing as opposed to those for combining trees, and (3) indifference to aspects of trees other than their topologies. We demonstrate a uniform, distance-based approach which allows for comparability among the results of character- and taxonomic-congruence studies, whether or not an identical suite of taxa has been included in all contributing data sets. Our results indicate that total-evidence and consensus trees differ little in topology if branch lengths are taken into account when combining two or more trees. In addition, when character-state data are converted to distances, our method permits their combination with information produced by techniques which generate distances directly. Moreover, treating all data sets or trees as distance matrices avoids the problem that different numbers of characters in contributing studies may confound the conclusions of a total-evidence or consensus analysis. Our protocol is illustrated with an example involving bats, in which the three component studies based on serology, DNA hybridization, and anatomy imply distinct phylogenies. However, the total-evidence and consensus trees support a fourth, somewhat different, topology resolved at all but one node and which conforms closely to the currently accepted higher category classification of Chiroptera.

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