PhD Thesis

Springs as models to unveil ecological drivers and responses: Perspectives for ecosystem theory from neglected ecosystems

Andreas Schweiger (02/2013-02/2016)

Support: Carl Beierkuhnlein, Konrad Dettner, Gregor Aas

Springs are semi-aquatic ecosystems where micro-environmental conditions affecting the compositions of inhabiting plant species on local scale are strongly linked to the macro-environmental conditions of the surrounding landscape. This environmental and ecological coherence of springs provides experiment-like conditions to test fundamental ecological theories about the functioning of natural ecosystems. Despite their model character, springs are completely underrepresented in ecological research and empirical tests of general ecological theories are missing so far. This thesis, which includes six manuscripts, aims to contribute to an integrative understanding of complex ecosystem functioning by combining long-term empirical research conducted on springs with theoretical, community and system ecological considerations. By combining recent and past investigations on water characteristics and plant community composition of seepage springs in the lower mountain regions of Central Germany, the long-term dataset used in this thesis documents long-term ecological responses to historic and emerging anthropogenic stressors over the last 25 years. The theory of complex adaptive systems was used as a general theoretical framework for this thesis. This general theory defines ecosystems as a collectivity of biotic elements adaptively interacting with each other and the abiotic environment on varying spatial and temporal scales. Thus, five major principles qualify complex adaptive ecosystems: 1) diversity and organisation of system elements (i.e. species, communities), 2) flow, distribution and interaction of information, energy and matter in the ecosystem, 3) stability of ecological responses, 4) scale-dependence and cross-scale similarity of ecological processes and patterns and, 5) path-dependence and ecological memory of the ecological system. All five major principles were investigated empirically by at least one manuscript of this thesis. While studying the diversity and organisation of plant communities inhabiting the investigated springs, three hyper-dominant (oligarchic) species were detected, which reflect the acidity and water temperature regime of the springs as major abiotic drivers of plant community composition. Springs that were less affected by historic acidification during the 20th century were characterised by the herb Chrysosplenium oppositifolium whereas antropogenically acidified springs were characterised by Sphagnum moss species. The grass species Calamagrostis villosa was characteristic for the cooler springs in the higher elevations of the study region. Spring plant communities that were less affected by historic acidification showed significantly higher stability to the climatic extreme summer of 2003 than strongly acidified springs. This alternative state in the plant community composition of anthropogenically acidified springs turned out to be further stabilised by positive feedbacks between historic acidification and biogenic habitat modification caused by Sphagnum species, which significantly affected long-term trajectories of plant community composition. These positive feedbacks as well as the interactive effects of abiotic conditions, which turned out to influence spring plant communities on varying temporal scales, stress the importance of path-dependence, abiotic-biotic interactions and ecological memory in these ecosystems. Furthermore, high cross-scale similarity was observed for the realised temperature niches of plant species inhabiting these springs. As cross-scale similarity is just rarely reported in current literature, I argue, that low environmental noise at local scale and strong cross-scale links between micro- and macro-environmental conditions, both environmental characteristics of the studied springs, can explain this exceptional observation. Besides the empirical research presented here in the framework of a general ecological theory, methodical requirements to test and further develop ecological theories are discussed. Simulations based on artificial data show that the risk of statistical biases and, thus, misinterpretations of ecological patterns strongly varies with the amount and type of noise (random vs. systematic). This thesis provides one of the first rigorous tests of the complex adaptive systems theory for natural ecosystems and fills numerous knowledge gaps about the structure and functioning of springs. Several fascinating research questions emerged from this dissertation, including the role of contingency and cross-scale interactions in explaining ecological patterns and processes. In general, the theory of complex adaptive systems is a promising candidate for a general theory of ecology with the potential to increase our understanding about the functioning of complex natural ecosystems.