Reproductive success of monogamous and polygynous pied flycatchers (Ficedula hypoleuca)

One of the most interesting aspects of the mating system of pied flycatchers is the regular occurrence of polygyny. Here we present data on the reproductive success of polygynously paired pied flycatcher males compared to monogamous males based on paternity analyses through DNA fingerprinting. Males paired with two females suffered a higher loss in reproductive output per female compared to monogamous males due to (1) a greater proportion of unhatched eggs in their broods, (2) greater nestling mortality and (3) a greater probability of being cuckolded. Nevertheless, the number of fledglings was significantly greater for polygynous males. Based on the number of nestlings that returned for subsequent breeding seasons, however, the reproductive success of monogamous and polygynous males did not differ significantly. These data raise the question as to why males attempt polygyny. Received: 16 August 1999 / Received in revised form: 15 March 2000 / Accepted: 18 March 2000     

Long-term effects of clear-cutting and selective cutting on soil methane fluxes in a temperate spruce forest in southern Germany

Based on multi-year measurements of CH₄ exchange in sub-daily resolution we show that clear-cutting of a forest in Southern Germany increased soil temperature and moisture and decreased CH₄ uptake. CH₄ uptake in the first year after clear-cutting (−4.5 ± 0.2 μg C m⁻² h⁻¹) was three times lower than during the pre-harvest period (−14.2 ± 1.3 μg C m⁻² h⁻¹). In contrast, selective cutting did not significantly reduce CH₄ uptake. Annual mean uptake rates were −1.18 kg C ha⁻¹ yr⁻¹ (spruce control), −1.16 kg C ha⁻¹ yr⁻¹ (selective cut site) and −0.44 kg C ha⁻¹ yr⁻¹ (clear-cut site), respectively. Substantial seasonal and inter-annual variations in CH₄ fluxes were observed as a result of significant variability of weather conditions, demonstrating the need for long-term measurements. Our findings imply that a stepwise selective cutting instead of clear-cutting may contribute to mitigating global warming by maintaining a high CH₄ uptake capacity of the soil.     

Convergence in carbon dioxide emissions and the role of growth and institutions: a parametric and non-parametric analysis

Environmental Economics and Policy Studies - This paper examines convergence of per capita carbon dioxide (CO2) emission for a panel of 124 countries taking into account the impact of economic...     

Ecological scenarios analyzed and evaluated by a shallow lake model

We applied the complex ecosystem model EMMO, which was adopted to the shallow lake Müggelsee (Germany), in order to evaluate a large set of ecological scenarios. By means of EMMO, 33 scenarios and 17 indicators were defined to characterize their effects on the lake ecosystem. The indicators were based on model outputs of EMMO and can be separated into biological indicators, such as chlorophyll-a and cyanobacteria, and hydro-chemical indicators, such as phosphorus. The question to be solved was, what is the ranking of the scenarios based on their characterization by these 17 indicators? And how can we handle high quantities of complex data within evaluation procedures? The scenario evaluation was performed by partial order theory which, however, did not provide a clear result. By subsequently applying the hierarchical cluster analysis (complete linkage) it was possible to reduce the data matrix to indicator and scenario representatives. Even though this step implies losses of information, it simplifies the application of partial order theory and the post processing by METEOR. METEOR is derived from partial order theory and allows the stepwise aggregation of indicators, which subsequently leads to a distinct and clear decision. In the final evaluation result the best scenario was the one which defines a minimum nutrient input and no phosphorus release from the sediment while the worst scenario is characterized by a maximum nutrient input and extensive phosphorus release from the sediment. The reasonable and comprehensive results show that the combination of partial order, cluster analysis and METEOR can handle big amounts of data in a very clear and transparent way, and therefore is ideal in the context of complex ecosystem models, like that we applied.