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Nosema ceranae is a highly prevalent intracellular parasite of honey bees’ midgut worldwide. This Microsporidium was monitored during a long-term study to evaluate the infection at apiary and intra-colony levels in six apiaries in four Mediterranean countries (France, Israel, Portugal, and Spain). Parameters on colony strength, honey production, beekeeping management, and climate were also recorded. Except for São Miguel (Azores, Portugal), all apiaries were positive for N. ceranae, with the lowest prevalence in mainland France and the highest intra-colony infection in Israel. A negative correlation between intra-colony infection and colony strength was observed in Spain and mainland Portugal. In these two apiaries, the queen replacement also influenced the infection levels. The highest colony losses occurred in mainland France and Spain, although they did not correlate with the Nosema infection levels, as parasitism was low in France and high in Spain. These results suggest that both the effects and the level of N. ceranae infection depends on location and beekeeping conditions. Further studies on host-parasite coevolution, and perhaps the interactions with other pathogens and the role of honey bee genetics, could assist in understanding the difference between nosemosis disease and infection, to develop appropriate strategies for its control., ARIMNet2 2016 Call, Ministerio de Asuntos Económicos y Transformación Digital, FCT, Depto. de Sanidad Animal, Fac. de Veterinaria, TRUE, pub

Forest wildfires typically increase runoff and associated soil and organic matter losses. Both ploughing and mulching with forest residues have been applied in recently burnt areas in Portugal to mitigate these effects in soil erosion, but their effectiveness has never been compared directly. To this end, soil and organic matter losses by water after a wildfire were studied in two eucalypt plantations in central Portugal that had been affected by the same wildfire (August 2015). One of the sites was instrumented with six erosion plots (2 m by 8 m), divided over two blocks with one treatment per block: control (doing nothing) and ploughing to 0.2 m depth with a tracked excavator. The other site was instrumented with nine erosion plots, divided over three blocks with three treatments in each block: control (doing nothing) and mulching with forest logging residues at reduced (2.6 Mg ha-1) and standard application rates (8 Mg ha-1). Mulching was performed one month after the wildfire, whereas ploughing took place one year after the wildfire. For this study, soil and organic matter losses were monitored at 12 occasions from July 2016 to May 2017, roughly coinciding with the second post-fire year. Over this relatively dry period sediment losses at the control plots of both ploughed and mulched sites averaged 1.6 and 0.6 Mg ha-1 respectively. The corresponding losses of the ploughed plots were 19% lower, whereas those of the mulched plots were 67 and 93% lower at the reduced and standard mulch rates, respectively. The organic matter content of the eroded sediments was 22% in the unploughed plots, and ploughing reduced this figure in half, which could be explained by the inversion of the topsoil horizons by the excavator. Mulching at the standard application rate seemed to produce a clear enrichment in organic matter content compared to mulching at the reduced rate as well as doing nothing (25 vs. 16 and 14%). The two main findings of this research were that i) erosion rate, Los incendios forestales suelen incrementar la escorrentía superficial, la erosión del suelo y de la materia orgánica asociada. Técnicas como el labrado o el acolchado de restos forestales han sido realizadas en Portugal para mitigar estos efectos, pero sus efectividades no han sido nunca comparadas directamente. En este estudio se analiza la efectividad de estas técnicas en el control de la erosión hídrica y de las pérdidas de materia orgánica en dos plantaciones de eucalipto quemadas por el mismo incendio en Agosto de 2015 en el Centro de Portugal. En una ladera se instalaron seis parcelas de 2 m x 8 m, divididas en dos bloques con un tratamiento por bloque: control (sin intervención) y labrado del suelo a 20 cm de profundidad con una retroexcavadora. En la otra ladera se instalaron nueve parcelas en tres bloques, con tres tratamientos por bloque: control (sin intervención), acolchado (mulching) con restos forestales triturados aplicados a una tasa reducida (2.6 Mg ha-1) y otra estándar (8.0 Mg ha-1). El acolchado fue aplicado un mes después del incendio, mientras que el labrado ocurrió once meses después del incendio. La erosión del suelo fue monitorizada entre Julio 2016 y Mayo 2017, coincidiendo con el segundo año post-incendio. La erosión del suelo para este periodo relativamente seco fue de 1.6 y 0.6 Mg ha-1, respectivamente para las parcelas control de las laderas labrada y acolchada. La erosión de suelo en las parcelas labradas fue un 19% menor que la erosión en las parcelas sin labrar, mientras que la erosión en las parcelas con acolchado a tasas reducida y estándar fue, respectivamente, un 67 y 93% menor que la erosión medida en las parcelas sin acolchado. El contenido de materia orgánica en los sedimentos fue de un 22% en el caso de las parcelas sin labrar. En el caso de las parcelas labradas esta cantidad se redujo a la mitad, lo que puede ser atribuido a la inversión de los horizontes edáficos por acción del labrado. El acolchado con tasa de aplicación

Microorganisms are vital in mediating the earth's biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: 'When do we need to understand microbial community structure to accurately predict function?' We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of process rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology.

Microorganisms are vital in mediating the earth's biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: 'When do we need to understand microbial community structure to accurately predict function?' We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of process rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology.