The structure of stereotyped calls reflects kinship and social affiliation in resident killer whales (Orcinus orca)

A few species of mammals produce group-specific vocalisations that are passed on by learning, but the function of learned vocal variation remains poorly understood. Resident killer whales live in stable matrilineal groups with repertoires of seven to 17 stereotyped call types. Some types are shared among matrilines, but their structure typically shows matriline-specific differences. Our objective was to analyse calls of nine killer whale matrilines in British Columbia to test whether call similarity primarily reflects social or genetic relationships. Recordings were made in 1985–1995 in the presence of focal matrilines that were either alone or with groups with non-overlapping repertoires. We used neural network discrimination performance to measure the similarity of call types produced by different matrilines and determined matriline association rates from 757 encounters with one or more focal matrilines. Relatedness was measured by comparing variation at 11 microsatellite loci for the oldest female in each group. Call similarity was positively correlated with association rates for two of the three call types analysed. Similarity of the N4 call type was also correlated with matriarch relatedness. No relationship between relatedness and association frequency was detected. These results show that call structure reflects relatedness and social affiliation, but not because related groups spend more time together. Instead, call structure appears to play a role in kin recognition and shapes the association behaviour of killer whale groups. Our results therefore support the hypothesis that increasing social complexity plays a role in the evolution of learned vocalisations in some mammalian species.     

The effect of protected areas on forest disturbance in the Carpathian Mountains 1985–2010

Protected areas are a cornerstone for forest protection, but they are not always effective during times of socioeconomic and institutional crises. The Carpathian Mountains in Eastern Europe are an ecologically outstanding region, with widespread seminatural and old‐growth forest. Since 1990, Carpathian countries (Czech Republic, Hungary, Poland, Romania, Slovakia, and Ukraine) have experienced economic hardship and institutional changes, including the breakdown of socialism, European Union accession, and a rapid expansion of protected areas. The question is how protected‐area effectiveness has varied during these times across the Carpathians given these changes. We analyzed a satellite‐based data set of forest disturbance (i.e., forest loss due to harvesting or natural disturbances) from 1985 to 2010 and used matching statistics and a fixed‐effects estimator to quantify the effect of protection on forest disturbance. Protected areas in the Czech Republic, Slovakia, and the Ukraine had significantly less deforestation inside protected areas than outside in some periods; the likelihood of disturbance was reduced by 1–5%. The effectiveness of protection increased over time in these countries, whereas the opposite was true in Romania. Older protected areas were most effective in Romania and Hungary, but newer protected areas were more effective in Czech Republic, and Poland. Strict protection (International Union for Conservation of Nature [IUCN] protection category Ia‐II) was not more effective than landscape‐level protection (IUCN III‐VI). We suggest that the strength of institutions, the differences in forest privatization, forest management, prior distribution of protected areas, and when countries joined the European Union may provide explanations for the strikingly heterogeneous effectiveness patterns among countries. Our results highlight how different the effects of protected areas can be at broad scales, indicating that the effectiveness of protected areas is transitory over time and space and suggesting that generalizations about the effectiveness of protected areas can be misleading.     

Metabolomic analysis of the selection response of Drosophila melanogaster to environmental stress: are there links to gene expression and phenotypic traits?

We investigated the global metabolite response to artificial selection for tolerance to stressful conditions such as cold, heat, starvation, and desiccation, and for longevity in Drosophila melanogaster. Our findings were compared to data from other levels of biological organization, including gene expression, physiological traits, and organismal stress tolerance phenotype. Overall, we found that selection for environmental stress tolerance changes the metabolomic ¹H NMR fingerprint largely in a similar manner independent of the trait selected for, indicating that experimental evolution led to a general stress selection response at the metabolomic level. Integrative analyses across data sets showed little similarity when general correlations between selection effects at the level of the metabolome and gene expression were compared. This is likely due to the fact that the changes caused by these selection regimes were rather mild and/or that the dominating determinants for gene expression and metabolite levels were different. However, expression of a number of genes was correlated with the metabolite data. Many of the identified genes were general stress response genes that are down-regulated in response to selection for some of the stresses in this study. Overall, the results illustrate that selection markedly alters the metabolite profile and that the coupling between different levels of biological organization indeed is present though not very strong for stress selection at this level. The results highlight the extreme complexity of environmental stress adaptation and the difficulty of extrapolating and interpreting responses across levels of biological organization.     

Ten ways remote sensing can contribute to conservation

In an effort to increase conservation effectiveness through the use of Earth observation technologies, a group of remote sensing scientists affiliated with government and academic institutions and conservation organizations identified 10 questions in conservation for which the potential to be answered would be greatly increased by use of remotely sensed data and analyses of those data. Our goals were to increase conservation practitioners’ use of remote sensing to support their work, increase collaboration between the conservation science and remote sensing communities, identify and develop new and innovative uses of remote sensing for advancing conservation science, provide guidance to space agencies on how future satellite missions can support conservation science, and generate support from the public and private sector in the use of remote sensing data to address the 10 conservation questions. We identified a broad initial list of questions on the basis of an email chain‐referral survey. We then used a workshop‐based iterative and collaborative approach to whittle the list down to these final questions (which represent 10 major themes in conservation): How can global Earth observation data be used to model species distributions and abundances? How can remote sensing improve the understanding of animal movements? How can remotely sensed ecosystem variables be used to understand, monitor, and predict ecosystem response and resilience to multiple stressors? How can remote sensing be used to monitor the effects of climate on ecosystems? How can near real‐time ecosystem monitoring catalyze threat reduction, governance and regulation compliance, and resource management decisions? How can remote sensing inform configuration of protected area networks at spatial extents relevant to populations of target species and ecosystem services? How can remote sensing‐derived products be used to value and monitor changes in ecosystem services? How can remote sensing be used to monitor and evaluate the effectiveness of conservation efforts? How does the expansion and intensification of agriculture and aquaculture alter ecosystems and the services they provide? How can remote sensing be used to determine the degree to which ecosystems are being disturbed or degraded and the effects of these changes on species and ecosystem functions?     

Characterization of Particulates from Power Plants

The emphasis on participate control from industrial processes has been shifted recently towards fine particulates, having diameters less than 3 microns. There exists an urgent need for more scientific information of fine particle characterization.^1,2 Coal and oil fired power plants are among the largest anthropogenic point sources of particulate matter.³ Limited knowledge is available on particle size distribution and trace metal composition in power plant emissions.^4-7 The morphological properties of particle emissions have been largely neglected. In this report we present some information on particle characteristics for an oil-fired and coal-fired power plant.     

The contribution of ship emissions to air pollution in the North Sea regions

As a consequence of the global distribution of manufacturing sites and the increasing international division of labour, ship traffic is steadily increasing and is becoming more and more important as an origin of air pollution.This study investigates the impact of ship emissions in coastal areas of the North Sea under conditions of the year 2000 by means of a regional chemistry transport model which runs on a sufficiently high resolution to study air pollution in coastal regions. It was found that northern Germany and Denmark in summer suffer from more than 50% higher sulphate, nitrate and ammonium aerosol concentrations due to contributions from ships. The implementation of a sulphur emission control area (SECA) in the North Sea, as it was implemented at the end of 2007, directly results in reduced sulphur dioxide and sulphate aerosol concentrations while nitrate aerosol concentrations are slightly increased.