Effects of changes in climate on landscape and regional processes, and feedbacks to the climate system

Biological and physical processes in the Arctic system operate at various temporal and spatial scales to impact large-scale feedbacks and interactions with the earth system. There are four main potential feedback mechanisms between the impacts of climate change on the Arctic and the global climate system: albedo, greenhouse gas emissions or uptake by ecosystems, greenhouse gas emissions from methane hydrates, and increased freshwater fluxes that could affect the thermohaline circulation. All these feedbacks are controlled to some extent by changes in ecosystem distribution and character and particularly by large-scale movement of vegetation zones. Indications from a few, full annual measurements of CO2 fluxes are that currently the source areas exceed sink areas in geographical distribution. The little available information on CH4 sources indicates that emissions at the landscape level are of great importance for the total greenhouse balance of the circumpolar North. Energy and water balances of Arctic landscapes are also important feedback mechanisms in a changing climate. Increasing density and spatial expansion of vegetation will cause a lowering of the albedo and more energy to be absorbed on the ground. This effect is likely to exceed the negative feedback of increased C sequestration in greater primary productivity resulting from the displacements of areas of polar desert by tundra, and areas of tundra by forest. The degradation of permafrost has complex consequences for trace gas dynamics. In areas of discontinuous permafrost, warming, will lead to a complete loss of the permafrost. Depending on local hydrological conditions this may in turn lead to a wetting or drying of the environment with subsequent implications for greenhouse gas fluxes. Overall, the complex interactions between processes contributing to feedbacks, variability over time and space in these processes, and insufficient data have generated considerable uncertainties in estimating the net effects of climate change on terrestrial feedbacks to the climate system. This uncertainty applies to magnitude, and even direction of some of the feedbacks.     

A comparison of relative abundance versus class data in diatom-based quantitative reconstructions

Relative species abundances are the most frequently applied data type used for modern or paleolimnological diatom studies. In contrast, plant ecologists save time by commonly using ordinal scale data (class data), where the abundance of a species is estimated using dominance classes, instead of relative abundance data. This study compares the performance of models based on ordinal diatom species class data (class 1: sporadic (<0–1%) up to class 6: dominant (>60%)) with similar model types based on relative abundance data for different regional training sets and sediment cores. First, relative diatom abundances were converted into ordinal classes. Species response to total phosphorous (TP) was modelled using both types of data - relative abundance and ordinal class data. Secondly, TP was reconstructed for six sediment cores from North-East Germany, Switzerland, and Denmark using WA and WA-PLS based on both types of data. Thirdly, 20 lake sediment surface samples with known relative diatom abundances and known water TP concentrations were recounted using an ordinal data scale to create an independent test set. No significant differences were found between relative abundance and class data for (1) explained species variance, (2) reconstructed TP values, and (3) inferred TP values of the 20 recounted samples. This approach demonstrates that past TP concentrations may also be reliably reconstructed using class data instead of relative diatom abundances. Thus, by using class data lake managers may not only obtain more long-term records past water quality, but this approach is also quicker and therefore more cost effective. Moreover, the findings of this study may also advance the use of automatic diatom identification with digital image recognition, as we demonstrate that not every damaged diatom valve needs to be identified.     

Crop Biotechnology for the Environment?

In public debates, agricultural biotechnology is almost invariably discussed as a potential threat to the environment and to human health. Without downplaying the risks associated with this technology we emphasize that if properly regulated, it can be a forceful tool to solve environmental problems and promote human health. Agricultural biotechnology can reduce environmental problems in at least three ways: it can diminish the need for environmentally damaging agricultural practices such as pesticides, fertilizers, tillage, and irrigation. It can reduce the land area needed for agriculture, thus reducing the CO₂ effect of agriculture and improving biodiversity. It can produce energy in a CO₂-neutral way (especially if new technologies involving the cultivation of microalgae become successful). Furthermore, agricultural biotechnology can have positive effects on human health by decreasing occupational and dietary exposure to pesticides, improving the nutritional value of food, and producing pharmaceuticals more efficiently. We argue that those who wish to give high priority to environmental goals cannot afford any longer to be mere onlookers while others decide the future directions of agricultural biotechnology.     

Carbon turnover and ammonia emissions during composting of biowaste at different temperatures

The effects of different process temperatures (40, 55, and 67 degrees C) during composting of source-separated household waste were studied in a 200 L compost reactor at an oxygen concentration of 16%. The overall decomposition measured as carbon mineralization, decomposition of different carbon constituents, and the dynamics of nitrogen mineralization and the microbial community, are reported. Ammonia emissions at 67 degrees C were more than double those at lower temperatures, and they were lowest at 40 degrees C. The decomposition rate, measured as CO2 emission, was highest at 55 degrees C. Decomposition of crude fat was slower at 40 degrees C than at 55 and 67 degrees C. The peak in microbial biomass was largest in the run at 40 degrees C, where substantial differences were seen in the microbial community structure and succession compared to thermophilic temperatures. Biowaste composting can be optimized to obtain both a high decomposition rate and low ammonia emissions by controlling the process at about 55 degrees C in the initial, high-rate stage. To reduce ammonia emissions it seems worthwhile to reduce the temperature after an initial high-temperature stage.     

State-of-the-art of ecological modelling with emphasis on development of structural dynamic models

The paper deals with two major problems in ecological modelling today, namely how to get reliable parameters? and how to build ecosystem properties into our models? The use of new mathematical tools to answer these questions is mentioned briefly, but the main focus of the paper is on development of structural dynamic models which are models using goal functions to reflect a current change of the properties of the biological components in the models. These changes of the properties are due to the enormous adaptability of the biological components to the prevailing conditions. All species in an ecosystem attempt to obtain most biomass, i.e. to move as far away as possible from thermodynamic equilibrium which can be measured by the thermodynamic concept exergy. Consequently, exergy has been proposed as a goal function in ecological models with dynamic structure, meaning currently changed properties of the biological components and in model language currently changed parameters. An equation to compute an exergy index of a model is presented. The theoretical considerations leading to this equation are not presented here but references to literature where the basis theory can be found are given. Two case studies of structural dynamic modelling are presented: a shallow lake where the structural dynamic changes have been determined before the model was developed, and the application of biomanipulation in lake management, where the structural dynamic changes are generally known. Moreover. it is also discussed how the same idea of using exergy as a goal function in ecological modelling may be applied to facilitate the estimation of parameters.     

Dynamic model of Lake Chozas (León, NW Spain)—Decrease in eco-exergy from clear to turbid phase due to introduction of exotic crayfish

We developed a dynamic model of the phosphorus cycle in Lake Chozas, a small shallow water body in León (NW Spain). The calibrated model simulated seasonal dynamics of phosphorus concentrations in major components of the lake's ecological network before and after 1997, the year when an invasive allochthonous crustacean, the Louisiana red swamp crayfish (Procambarus clarkii), was introduced into the lake. The shift from clean to turbid phase, due to grazing by crayfish on submerged vegetation, caused a gradual decrease in eco-exergy, reflecting an increase in entropy, related to breakdown of ecosystem internal equilibria. This case study verifies the hypothesis of Marchi et al. (2010) that, after an initial relatively stable state, the allochthonous species may cause an increase in entropy indicating perturbation of the ecosystem.