Tropical deforestation in a future international climate policy regime—lessons from the Brazilian Amazon

The possibility of adopting national targets for carbon dioxide (CO₂) emissions from tropical deforestation in a future international climate treaty has received increasing attention recently. This attention has been prompted by proposals to this end and more intensified talks on possible commitments for developing countries beyond the United Nations Framework Convention on Climate Change Kyoto Protocol. We analyze four main scientific and political challenges associated with national targets for emissions from tropical deforestation: (1) reducing the uncertainties in emission inventories, (2) preserving the environmental integrity of the treaty, (3) promoting political acceptance and participation in the regime, and (4) providing economic incentives for reduced deforestation. We draw the following conclusions. (1) Although there are large uncertainties in carbon flux from deforestation, these are in the same range as for other emissions included in the current Kyoto protocol (i.e., non-CO₂ GHGs), and they can be reduced. However, for forest degradation processes the uncertainties are larger. A large challenge lies in building competence and institutions for monitoring the full spectrum of land use changes in developing countries. (2 and 3) Setting targets for deforestation is difficult, and uncertainties in future emissions imply a risk of creating ‘tropical hot air’. However, there are proposals that may sufficiently deal with this, and these proposals may also have the advantage of making the targets more attractive, politically speaking. Moreover, we conclude that while a full carbon accounting system will likely be politically unacceptable for tropical countries, the current carbon accounting system should be broadened to include forest degradation in order to safeguard environmental integrity. (4) Doubts can be cast over the possible effect a climate regime alone will have on deforestation rates, though little thorough analysis of this issue has been made.

Recruits of the stingless bee Scaptotrigona pectoralis learn food odors from the nest atmosphere

The ability to learn food odors inside the nest and to associate them with food sources in the field is of essential importance for the recruitment of nestmates in social bees. We investigated odor learning by workers within the hive and the influence of these odors on their food choice in the field in the stingless bee Scaptotrigona pectoralis. During the experiments, recruited bees had to choose between two feeders, one with an odor that was present inside the nest during the recruitment process, and one with an unknown odor. In all experiments with different odor combinations (linalool/phenylacetaldehyde, geraniol/eugenol) a significant majority of bees visited the feeder with the odor they had experienced in their nest (χ ²-tests; p?<?0.05). By contrast, the bees showed no preference for one of two feeders when they were either baited with the same odor (linalool) or contained no odor. Our results clearly show that naïve workers of S. pectoralis can learn the odor of a food source during the recruitment process from the nest atmosphere and that their subsequent food search in the field is influenced by the learned odor.     

Using multivariate regression modeling for sampling and predicting chemical characteristics of mixed waste in old landfills

Municipal solid waste landfills pose a threat on environment and human health, especially old landfills which lack facilities for collection and treatment of landfill gas and leachate. Consequently, missing information about emission flows prevent site-specific environmental risk assessments. To overcome this gap, the combination of waste sampling and analysis with statistical modeling is one option for estimating present and future emission potentials. Optimizing the tradeoff between investigation costs and reliable results requires knowledge about both: the number of samples to be taken and variables to be analyzed.This article aims to identify the optimized number of waste samples and variables in order to predict a larger set of variables. Therefore, we introduce a multivariate linear regression model and tested the applicability by usage of two case studies. Landfill A was used to set up and calibrate the model based on 50 waste samples and twelve variables. The calibrated model was applied to Landfill B including 36 waste samples and twelve variables with four predictor variables.The case study results are twofold: first, the reliable and accurate prediction of the twelve variables can be achieved with the knowledge of four predictor variables (Loi, EC, pH and Cl). For the second Landfill B, only ten full measurements would be needed for a reliable prediction of most response variables. The four predictor variables would exhibit comparably low analytical costs in comparison to the full set of measurements. This cost reduction could be used to increase the number of samples yielding an improved understanding of the spatial waste heterogeneity in landfills.Concluding, the future application of the developed model potentially improves the reliability of predicted emission potentials. The model could become a standard screening tool for old landfills if its applicability and reliability would be tested in additional case studies.     

Asymmetries in commitment in an avian communication network

Mobbing of predators occurs within a conspecific and heterospecific context but has not been quantified within the framework of a communication network and analysed with respect to heterospecific reciprocity. Here, we used playbacks of mobbing calls to show that mobbing is unequally distributed within a community of deciduous forest birds. Five species (great tit Parus major, blue tit Cyanistes caeruleus, marsh tit Poecile palustris, nuthatch Sitta europaea and chaffinch Fringilla coelebs) responded to each other’s playbacks of mobbing calls. Commitment to mob was measured by minimum distance, response latency and uttering of calls. Commitment was higher when conspecific calls were broadcast. Yet, responses to heterospecific calls were significantly different between the five species. Chaffinches had the lowest commitment, and blue tits tended to have the highest. The communication network is asymmetric. Some species invest more than they receive from other species. As mobbing might incur costs, these are unequally distributed across the community.