Planet of the apes

What makes us humans so special? Our language, our genes, our culture, our cognitive skills? At the Max-Planck-Institute for Evolutionary Anthropology in Leipzig, psychologists, linguists and biologists tackle this old question in a truly multidisciplinary way. Their results have implications not just for our understanding of human evolution – they also touch directly on many social and environmental issues. Florian Maderspacher reports.     

Our Planet,Our Health

Readers' corner

Our Planet, Our Health Report of the who commission on health and environment     

Marine Ecosystem Science on an Intertwined Planet

Ecosystems - Marine ecosystem science has developed since the 1940s, when humans obtained the ability to spend substantial time underneath the surface of the ocean. Since then, and drawing on...     

Balancing on a Planet: Toward an Agricultural Anthropology for the Twenty-First Century

Robert Netting had a central role in establishing agricultural anthropology. Many people rightly remember him as an astute ethnographer of farming communities, focused on analyzing the empirical details of changing patterns of household composition, land holding size and labor use. Yet, during his career he was increasingly concerned about the sustainability of smallholder vs. conventional industrial agriculture models on a global scale. Thus, Netting also had an important role in laying the foundation for the development of an agricultural anthropology for the twenty-first century, an anthropology that shows how smallholders balancing on an Alp can help us to understand how we might balance on this planet. This paper analyzes Netting's contribution to the future of agricultural anthropology in three key areas: the environment, population, and agriculture relationship; farmer knowledge and epistemology; and models for global sustainability.     

A Scientometric Prediction of the Discovery of the First Potentially Habitable Planet with a Mass Similar to Earth

Background

The search for a habitable extrasolar planet has long interested scientists, but only recently have the tools become available to search for such planets. In the past decades, the number of known extrasolar planets has ballooned into the hundreds, and with it, the expectation that the discovery of the first Earth-like extrasolar planet is not far off.

Methodology/Principal Findings

Here, we develop a novel metric of habitability for discovered planets and use this to arrive at a prediction for when the first habitable planet will be discovered. Using a bootstrap analysis of currently discovered exoplanets, we predict the discovery of the first Earth-like planet to be announced in the first half of 2011, with the likeliest date being early May 2011.

Conclusions/Significance

Our predictions, using only the properties of previously discovered exoplanets, accord well with external estimates for the discovery of the first potentially habitable extrasolar planet and highlight the the usefulness of predictive scientometric techniques to understand the pace of scientific discovery in many fields.     

Circular Polarization of Light by Planet Mercury and Enantiomorphism of its Surface Minerals

Different mechanisms for the generation of circular polarization by the surface of planets and satellites are described. The observed values for Venus, the Moon, Mars, and Jupiter obtained by photo-polarimetric measurements with Earth based telescopes, showed accordance with theory. However, for planet Mercury asymmetric parameters in the circular polarization were measured that do not fit with calculations. For BepiColombo, the ESA cornerstone mission 5 to Mercury, we propose to investigate this phenomenon using a concept which includes two instruments. The first instrument is a high-resolution optical polarimeter, capable to determine and map the circular polarization by remote scanning of Mercury's surface from the Mercury Planetary Orbiter MPO. The second instrument is an in situ sensor for the detection of the enantiomorphism of surface crystals and minerals, proposed to be included in the Mercury Lander MSE.     

Quantifying reliability and data deficiency in global vertebrate population trends using the Living Planet Index

Global biodiversity is facing a crisis, which must be solved through effective policies and on-the-ground conservation. But governments, NGOs, and scientists need reliable indicators to guide research, conservation actions, and policy decisions. Developing reliable indicators is challenging because the data underlying those tools is incomplete and biased. For example, the Living Planet Index tracks the changing status of global vertebrate biodiversity, but taxonomic, geographic and temporal gaps and biases are present in the aggregated data used to calculate trends. However, without a basis for real-world comparison, there is no way to directly assess an indicator's accuracy or reliability. Instead, a modelling approach can be used. We developed a model of trend reliability, using simulated datasets as stand-ins for the “real world”, degraded samples as stand-ins for indicator datasets (e.g., the Living Planet Database), and a distance measure to quantify reliability by comparing partially sampled to fully sampled trends. The model revealed that the proportion of species represented in the database is not always indicative of trend reliability. Important factors are the number and length of time series, as well as their mean growth rates and variance in their growth rates, both within and between time series. We found that many trends in the Living Planet Index need more data to be considered reliable, particularly trends across the global south. In general, bird trends are the most reliable, while reptile and amphibian trends are most in need of additional data. We simulated three different solutions for reducing data deficiency, and found that collating existing data (where available) is the most efficient way to improve trend reliability, whereas revisiting previously studied populations is a quick and efficient way to improve trend reliability until new long-term studies can be completed and made available.