I look at you to learn: Effects of the owner's sex on social learning in domestic dogs

Dogs have been shown to be able to learn from a human demonstrator. However, to date, there have been no studies investigating the effect of the demonstrator?s sex on such learning. The aim of our study was to evaluate this effect by comparing an experimental condition in which dogs received a demonstration from their owner on how to manipulate one of two possible containers to obtain food and a control condition without any human demonstration. Each of these conditions was divided into two groups: male-owned and female-owned dogs.Overall, the dogs performed better in the experimental condition compared to the control condition. This was evidentbased ona higher frequency of correct choices and opening the correct container, as well as a higher frequency of contact and gaze towards the demonstration. The female-owned group benefited from the demonstration by choosing the correct container more frequentlyin the experimental condition compared to the control. Conversely, male-owned dogs chose the correct container more often and looked more frequently at the demonstration than female-owned dogs, without differences between conditions. This could indicate a higher capacity for problem-solvingin this group of dogs beyond the human demonstration, and therefore would not reflect a modulatory effect of the owner?s sex over social learning in particular. In conclusion, the sex of the demonstrator seems to have an effect on social learning in dogs when the demonstrator is a female owner. This might have an impact on several applied settings as well as sampling criteria in canine social cognition research.Fil: Dzik, Marina Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Médicas. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Médicas; ArgentinaFil: Gutierrez Torres, J. S.. Universidad Central; ColombiaFil: Berdugo Lattke, M. L.. Universidad Central; ColombiaFil: Bentosela, Mariana. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Médicas. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Médicas; Argentin

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Lista de gêneros de Hymenoptera (Insecta) do Espírito Santo, Brasil

The first checklist of genera of Hymenoptera from Espírito Santo state, Brazil is presented. A total of 973 genera of Hymenoptera is listed, of which 555 (57%) are recorded for the first time from this state. Ichneumonoidea and Chalcidoidea are the two superfamilies with the most genera, 241 and 203 respectively. Braconidae, with 141 genera, are the richest family.The first checklist of genera of Hymenoptera from Espírito Santo state, Brazil is presented. A total of 973 genera of Hymenoptera is listed, of which 555 (57%) are recorded for the first time from this state. Ichneumonoidea and Chalcidoidea are the two superfamilies with the most genera, 241 and 203 respectively. Braconidae, with 141 genera, are the richest family.Fil: Azevedo, Celso O.. Universidade Federal do Espírito Santo; BrasilFil: Molin, Ana Dal. Texas A&M University; Estados UnidosFil: Penteado-Dias, Angelica. Universidade Federal do São Carlos; BrasilFil: Macedo, Antonio C. C.. Secretaria do Meio Ambiente do Estado de São Paulo; BrasilFil: Rodriguez-V, Beatriz. Universidad Nacional Autónoma de México; MéxicoFil: Dias, Bianca Z. K.. Universidade Federal do Espírito Santo; BrasilFil: Waichert, Cecilia. State University of Utah; Estados UnidosFil: Aquino, Daniel Alejandro. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. División Entomología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Smith, David. Smithsonian Institution; Estados UnidosFil: Shimbori, Eduardo M.. Universidade Federal do São Carlos; BrasilFil: Noll, Fernando B.. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Gibson, Gary. Agriculture and Agri-Food Canada; CanadáFil: Onody, Helena. Universidade Federal do São Carlos; BrasilFil: Carpenter, James M.. American Museum of Natural History; Estados UnidosFil: Lattke, John. Universidad Nacional de Loja; EcuadorFil: Ramos, Kelli dos S.. Universidade de Sao Paulo; BrasilFil: Williams, Kevin. Florida State Collection of Arthropods; Estados UnidosFil: Masner, Lubomir. Agriculture and Agri-Food Canada; CanadáFil: Kimsey, Lynn. University of California; Estados UnidosFil: Tavares, Marcelo T.. Universidade Federal do Espírito Santo; BrasilFil: Olmi, Massimo. Università degli Studi della Tuscia; ItaliaFil: Buffington, Matthew L.. United States Department of Agriculture; Estados UnidosFil: Ohl, Michael. Staatliches Museum fur Naturkunde Stuttgart; AlemaniaFil: Sharkey, Michael. University of Kentucky; Estados UnidosFil: Johnson, Norman F.. Ohio State University; Estados UnidosFil: Kawada, Ricardo. Universidade Federal do Espírito Santo; BrasilFil: Gonçalves, Rodrigo B.. Universidade Federal do Paraná; BrasilFil: Feitosa, Rodrigo. Universidade Federal do Paraná; BrasilFil: Heydon, Steven. University of California; Estados UnidosFil: Guerra, Tânia M.. Universidade Federal do Espírito Santo; BrasilFil: da Silva, Thiago S. R.. Universidade Federal do Espírito Santo; BrasilFil: Costa, Valmir. Instituto Biológico; Brasi

Timeless standards for species delimitation

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