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Solanum subg. Leptostemonum contains approximately 350-450 species, including the cultivated eggplant, S. melongena. Most species placed in this subgenus form a monophyletic group, the Leptostemonum clade, characterized by the presence of stellate hairs and prickles, leading to the common name of \"spiny solanums\". Here we present a phylogenetic analysis that circumscribes the major clades within the spiny solanums and examines the relationships among them, with an emphasis on New World species. Of particular interest is the clarification of the clade limits and species composition of groups that have not been well-sampled. We also increase sampling of taxa that have been previously analyzed in molecular studies, namely those in the Torva, Micracantha, and Erythrotrichum clades. These groups have convergent morphological characteristics that have challenged taxonomists, making classification difficult. Results from our study delimit 14 clades within the spiny solanums, including the newly designated Asterophorum, Gardneri, Sisymbriifolium, and Thomasiifolium clades. We also establish the placement of species not previously sampled, especially those endemic to Brazil. These results give an increased understanding of the evolution of the Leptostemonum clade by defining monophyletic groups within it and identify areas of the phylogenetic tree that remain unresolved and require further taxon sampling.

AIM: Models of species niches and distributions have become invaluable to biogeographers over the past decade, yet several outstanding methodological issues remain. Here we address three critical ones: selecting appropriate evaluation data, detecting overfitting, and tuning program settings to approximate optimal model complexity. We integrate solutions to these issues for Maxent models, using the Caribbean spiny pocket mouse, Heteromys anomalus, as an example. LOCATION: North‐western South America. METHODS: We partitioned data into calibration and evaluation datasets via three variations of k‐fold cross‐validation: randomly partitioned, geographically structured and masked geographically structured (which restricts background data to regions corresponding to calibration localities). Then, we carried out tuning experiments by varying the level of regularization, which controls model complexity. Finally, we gauged performance by quantifying discriminatory ability and overfitting, as well as via visual inspections of maps of the predictions in geography. RESULTS: Performance varied among data‐partitioning approaches and among regularization multipliers. The randomly partitioned approach inflated estimates of model performance and the geographically structured approach showed high overfitting. In contrast, the masked geographically structured approach allowed selection of high‐performing models based on all criteria. Discriminatory ability showed a slight peak in performance around the default regularization multiplier. However, regularization levels two to four times higher than the default yielded substantially lower overfitting. Visual inspection of maps of model predictions coincided with the quantitative evaluations. MAIN CONCLUSIONS: Species‐specific tuning of model parameters can improve the performance of Maxent models. Further, accurate estimates of model performance and overfitting depend on using independent evaluation data. These strategies for model evaluation may be useful for other modelling methods as well.

The risk of predation strongly affects mammalian population dynamics and community interactions. Bright moonlight is widely believed to increase predation risk for nocturnal mammals by increasing the ability of predators to detect prey, but the potential for moonlight to increase detection of predators and the foraging efficiency of prey has largely been ignored. Studies have reported highly variable responses to moonlight among species, calling into question the assumption that moonlight increases risk. Here, we conducted a quantitative meta‐analysis examining the effects of moonlight on the activity of 59 nocturnal mammal species to test the assumption that moonlight increases predation risk. We examined patterns of lunarphilia and lunarphobia across species in relation to factors such as trophic level, habitat cover preference and visual acuity. Across all species included in the meta‐analysis, moonlight suppressed activity. The magnitude of suppression was similar to the presence of a predator in experimental studies of foraging rodents (13·6% and 18·7% suppression, respectively). Contrary to the expectation that moonlight increases predation risk for all prey species, however, moonlight effects were not clearly related to trophic level and were better explained by phylogenetic relatedness, visual acuity and habitat cover. Moonlight increased the activity of prey species that use vision as their primary sensory system and suppressed the activity of species that primarily use other senses (e.g. olfaction, echolocation), and suppression was strongest in open habitat types. Strong taxonomic patterns underlay these relationships: moonlight tended to increase primate activity, whereas it tended to suppress the activity of rodents, lagomorphs, bats and carnivores. These results indicate that visual acuity and habitat cover jointly moderate the effect of moonlight on predation risk, whereas trophic position has little effect. While the net effect of moonlight appears to increase predation risk for most nocturnal mammals, our results highlight the importance of sensory systems and phylogenetic history in determining the level of risk.

AIM: One of the main gaps in the assessment of biodiversity is the lack of a unified framework for measuring its taxonomic and functional facets and for unveiling the underlying patterns. LOCATION: Europe, 25 large river basins. METHODS: Here, we develop a decomposition of functional β‐diversity, i.e. the dissimilarity in functional composition between communities, into a functional turnover and a functional nestedness‐resultant component. RESULTS: We found that functional β‐diversity was lower than taxonomic β‐diversity. This difference was driven by a lower functional turnover compared with taxonomic turnover while the nestedness‐resultant component was similar for taxonomic and functional β‐diversity. MAIN CONCLUSIONS: Fish faunas with different species tend to share the same functional attributes. The framework presented in this paper will help to analyse biogeographical patterns as well as to measure the impact of human activities on the functional facets of biodiversity.

AIM: To propose a unified framework for quantifying taxon (Tβ), phylogenetic (Pβ) and functional (Fβ) beta diversity via pairwise comparisons of communities, which allows these types of beta diversity to be partitioned into ecologically meaningful additive components. LOCATION: Global, with case studies in Europe and the Azores archipelago. METHODS: Using trees as a common representation for taxon, phylogenetic and functional diversity, we partition total beta diversity (βₜₒₜₐₗ) into its replacement (turnover, βᵣₑₚₗ) and richness difference (βᵣᵢcₕ) components according to which part of a global tree was shared by or unique to communities that were being compared. We demonstrate the application of this framework using artificial and empirical examples (mammals in Europe and epigean arthropods in the Azores). RESULTS: Our empirical examples show that comparing Pβ and Fβ with the most commonly used Tβ revealed previously hidden patterns of beta diversity. More importantly, we demonstrate that partitioning Pβₜₒₜₐₗ and Fβₜₒₜₐₗ into their respective βᵣₑₚₗ and βᵣᵢcₕ components facilitates the detection of more complex patterns than using the overall coefficients alone, further elucidating the different forces operating in community assembly. MAIN CONCLUSIONS: The methods presented here allow the integration and full comparison of Tβ, Pβ and Fβ. They provide a tool for effectively disentangling the replacement (turnover) and richness difference components of the different biodiversity facets within the same methodological framework.

Guidelines for use of wild mammal species are updated from the American Society of Mammalogists (ASM) 2007 publication. These revised guidelines cover current professional techniques and regulations involving mammals used in research and teaching. They incorporate additional resources, summaries of procedures, and reporting requirements not contained in earlier publications. Included are details on marking, housing, trapping, and collecting mammals. It is recommended that institutional animal care and use committees (IACUCs), regulatory agencies, and investigators use these guidelines as a resource for protocols involving wild mammals. These guidelines were prepared and approved by the ASM, working with experienced professional veterinarians and IACUCs, whose collective expertise provides a broad and comprehensive understanding of the biology of nondomesticated mammals in their natural environments. The most current version of these guidelines and any subsequent modifications are available at the ASM Animal Care and Use Committee page of the ASM Web site (http://mammalsociety.org/committees/index.asp).

The strength of phylogenetic signal in extinction risk can give insight into the mechanisms behind species' declines. Nevertheless, no existing measure of phylogenetic pattern in a binary trait, such as extinction-risk status, measures signal strength in a way that can be compared among data sets. We developed a new measure for phylogenetic signal of binary traits, D, which simulations show gives robust results with data sets of more than 50 species, even when the proportion of threatened species is low. We applied D to the red-list status of British birds and the world's mammals and found that the threat status for both groups exhibited moderately strong phylogenetic clumping. We also tested the hypothesis that the phylogenetic pattern of species threatened by harvesting will be more strongly clumped than for those species threatened by either habitat loss or invasive species because the life-history traits mediating the effects of harvesting show strong evolutionary pattern. For mammals, our results supported our hypothesis; there was significant but weaker phylogenetic signal in the risk caused by the other two drivers (habitat loss and invasive species). We conclude that D is likely to be a useful measure of the strength of phylogenetic pattern in many binary traits.

The importance of structural complexity in coral reefs has come to the fore with the global degradation of reef condition; however, the limited scale and replication of many studies have restricted our understanding of the role of complexity in the ecosystem. We qualitatively and quantitatively (where sufficient standardised data were available) assess the literature regarding the role of structural complexity in coral reef ecosystems. A rapidly increasing number of publications have studied the role of complexity in reef ecosystems over the past four decades, with a concomitant increase in the diversity of methods used to quantify structure. Quantitative analyses of existing data indicate a strong negative relationship between structural complexity and algal cover, which may reflect the important role complexity plays in enhancing herbivory by reef fishes. The cover of total live coral and branching coral was positively correlated with structural complexity. These habitat attributes may be creating much of the structure, resulting in a collinear relationship; however, there is also evidence of enhanced coral recovery from disturbances where structural complexity is high. Urchin densities were negatively correlated with structural complexity; a relationship that may be driven by urchins eroding reef structure or by their gregarious behaviour when in open space. There was a strong positive relationship between structural complexity and fish density and biomass, likely mediated through density-dependent competition and refuge from predation. More variable responses were found when assessing individual fish families, with all families examined displaying a positive relationship to structural complexity, but only half of these relationships were significant. Although only corroborated with qualitative data, structural complexity also seems to have a positive effect on two ecosystem services: tourism and shoreline protection. Clearly, structural complexity is an integral component of coral reef ecosystems, and it should be incorporated into monitoring programs and management objectives.

AIM: Advancement in ecological methods predicting species distributions is a crucial precondition for deriving sound management actions. Maximum entropy (MaxEnt) models are a popular tool to predict species distributions, as they are considered able to cope well with sparse, irregularly sampled data and minor location errors. Although a fundamental assumption of MaxEnt is that the entire area of interest has been systematically sampled, in practice, MaxEnt models are usually built from occurrence records that are spatially biased towards better‐surveyed areas. Two common, yet not compared, strategies to cope with uneven sampling effort are spatial filtering of occurrence data and background manipulation using environmental data with the same spatial bias as occurrence data. We tested these strategies using simulated data and a recently collated dataset on Malay civet Viverra tangalunga in Borneo. LOCATION: Borneo, Southeast Asia. METHODS: We collated 504 occurrence records of Malay civets from Borneo of which 291 records were from 2001 to 2011 and used them in the MaxEnt analysis (baseline scenario) together with 25 environmental input variables. We simulated datasets for two virtual species (similar to a range‐restricted highland and a lowland species) using the same number of records for model building. As occurrence records were biased towards north‐eastern Borneo, we investigated the efficacy of spatial filtering versus background manipulation to reduce overprediction or underprediction in specific areas. RESULTS: Spatial filtering minimized omission errors (false negatives) and commission errors (false positives). We recommend that when sample size is insufficient to allow spatial filtering, manipulation of the background dataset is preferable to not correcting for sampling bias, although predictions were comparatively weak and commission errors increased. MAIN CONCLUSIONS: We conclude that a substantial improvement in the quality of model predictions can be achieved if uneven sampling effort is taken into account, thereby improving the efficacy of species conservation planning.

Mammals are metagenomic in that they are composed of not only their own gene complements but also those of all of their associated microbes. To understand the coevolution of the mammals and their indigenous microbial communities, we conducted a network-based analysis of bacterial 16S ribosomal RNA gene sequences from the fecal microbiota of humans and 59 other mammalian species living in two zoos and in the wild. The results indicate that host diet and phylogeny both influence bacterial diversity, which increases from carnivory to omnivory to herbivory; that bacterial communities codiversified with their hosts; and that the gut microbiota of humans living a modern life-style is typical of omnivorous primates.