State factor network analysis of ecosystem response to climate change

Abstract

Case studies of ecosystem responses to changing climates are necessary in understanding and adapting to these changes. However, more general conceptual frameworks are also needed to contextualize and synthesize case studies, and to provide guidelines for assessment and prediction. This study analyzes a network model of ecological and soil state factor interrelationships to address issues such as sensitivity, resilience, and complexity of climate-driven terrestrial ecosystem changes. A factorial ecosystem model is analyzed using techniques from algebraic graph theory. Results show high values for spectral radius, graph energy, and algebraic connectivity. These indicate complexity, dynamical instability, active reverberating feedbacks, and high synchronization. Implications are that climate effects on ecosystems will be complicated, complex, and difficult to predict. We should be prepared for surprises in the form of unanticipated pathways and outcomes. The inherent nature of ecosystem interconnectivity indicated by the state factor model also suggests that when simulation models and change assessments do turn out to be wrong, it does not necessarily mean the underlying scientific understandings, data, or assumptions are wrong, as sensitivity to relatively minor variations and disturbances is high, and complexity and low predictability are inherent. Ecosystem reactions to climate (and other, often contemporaneous) changes will reverberate through the ecosystem. Both filtering and amplification may occur, but net amplification is indicated by the graph analysis. Ecosystem responses are integrated system responses–state factors will respond as a single integrated unit, not as a collection or sequence of individual responses.