| Summary: | Variation in environmental conditions is a pervasive feature of natural systems that has profound consequences for the structure of ecological communities. As a result of altered local conditions produced by human urbanisation, shifts in marine habitats from kelp forests to mats of turfing algae are increasingly common. Forecasting whether such ecological change will be accelerated or reversed as a function of modified global conditions is a new form of ecological enquiry. Throughout this thesis, I assessed the conceptual model that while cross-scale abiotic stressors can combine to have interactive effects, management of local conditions can counter-balance this change. My experimental manipulations were intended to test the hypotheses that; 1) cross-scale factors (i.e. local and global) will have interactive effects that increase the probability of expansion of turfs but not kelp, and, 2) management of local conditions (e.g. presence of biota, nutrient enrichment) will dampen the effects of global change on turfs (e.g. forecasted CO₂). Change in ecological communities is anticipated where altered environmental conditions have contrasting effects on interacting taxa that determine their composition and relative abundances. Experimental enrichment of CO₂ and nutrients influenced biomass accumulation of turf and kelp differently, with turf responding positively to enrichment of both resources while kelp responded to enrichment of nutrients but not CO₂. These responses likely reflect resource limitations experienced by the algae, as stoichiometry indicated turf was co-limited by CO₂ and nutrients while kelp appeared to be limited by nutrients but not CO₂. Simultaneous enrichment of these factors would, consequently, be anticipated to facilitate the expansion of turf algae at the expense of established kelp canopies. Considerable attention has focused on the influence of altered conditions on single taxa in isolation, yet such approaches only elucidate direct response(s). In natural systems, these responses may be ...
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