The aim of this research was to assess three hierarchical aspects of alga-grazer interactions in intertidal communities on a small scale: spatial heterogeneity, grazing effects and spatial stability in grazing effects. First, using semivariograms and cross-semivariograms I observed hierarchical spatial patterns in most algal groups and in grazers. However, these patterns varied with the level on the shore and between shores, suggesting that either human exploitation or wave exposure can be a source of variability. Second, grazing effects were studied using manipulative experiments at different levels on the shore. These revealed significant effects of grazing on the low shore and in tidal pools. Additionally, using a transect of grazer exclusions across the shore, I observed unexpected hierarchical patchiness in the strength of grazing, rather than zonation in its effects. This patchiness varied in time due to different biotic and abiotic factors. In a separate experiment, the effect of mesograzers effects were studied in the upper eulittoral zone under four conditions: burnt open rock (BOR), burnt pools (Bpool), non-burnt open rock (NBOR) and non-burnt pools (NBpool). Additionally, I tested spatial stability in the effects of grazing in consecutive years, using the same plots. I observed great spatial variability in the effects of grazing, but this variability was spatially stable in Bpools and NBOR, meaning deterministic and significant grazing effects in consecutive years on the same plots. Both the significance in grazing effects and spatial stability depended on the level of resolution (species, functional, biomass) at which the algal assemblage was evaluated, suggesting hierarchical variability. In order to be able to predict spatial variability in the effects of grazers in the upper eulittoral zone using biotic and abiotic micro- and macrofactors, a conceptual model was proposed, based on data from several multiple-regressions. This linked the interactions among three elements: idiosyncratic heterogeneity, micro and macrofactors. This suggests that spatial variability can be a product of these factors, while spatial stability can be caused by the same or different combinations of factors. In conclusion, grazing and other ecological phenomena must be studied hierarchically, not only through spatiotemporal scales, but also at different levels of resolution, as these also influence our perception of patterns.

An ecosytem-based spatial conservation plan for the South African sandy beaches. Sandy beaches are valuable ecosystems. They support a collection of species that is unique, comprising many endemic species, and provide a number of key ecosystem goods and services, including scenic vistas for human recreation, nesting sites for turtles and birds, and important areas for biogeochemical recycling, water filtration and purification. However, sandy beaches have not been well understood or appreciated as ecosystems, and consequently have a legacy of poor coastal management. In many instances this has lead to a "tyranny of small decisions", where multiple, seemingly insignificant management decisions and actions have resulted in complete transformation and degradation of the shoreline in several places. In addition to inappropriate management strategies, beaches are also poorly represented in conservation areas. Further, where they are recognised as being "conserved" in marine protected areas, this often is a false sense of protection because the far more sensitive dune portion of the littoral active zone is invariably not included in the reserve. In short, there is a need for a new way to approach sandy beach conservation and management that includes the system (dunes, intertidal beaches and surf zones) as a whole. On one hand, the approach should make provision for use of the abundant natural resources and opportunities associated with sandy shores in ways that are sustainable and contribute to biodiversity stewardship - through ecosystem-based management and marine spatial planning. But, on the other hand, it must simultaneously contribute to securing a sufficient amount of the key ecological attributes of beaches (habitats, biodiversity and processes) in a network of reserves, to ensure that the ecosystem, natural resources, and services all persist in perpetuity - through systematic conservation planning. The aim of this Thesis is to integrate these into a single approach, which I call ecosystem-based spatial conservation planning for sandy beaches, using the South African sandy shores as a case study. To achieve this broad aim, the Thesis is divided into three parts. Part 1 deals with establishing baseline information by quantifying spatial patterns in sandy beach habitats (Chapter 1), biodiversity, key assemblages and processes, and outstanding physical features (Chapter 2). First, mapping sandy beach habitats is a challenge given the vast, linear extent of shorelines and significant resources required to complete the project. Therefore, a novel approach was derived using statistical techniques (conditional inference trees) to identify physical features of beaches that can be observed on Google Earth (or similar) imagery, and that can provide good predictions of beach morphodynamic (habitat) types. Based on the results of this analysis, sandy beaches (and all other coastal habitat types) were mapped digitally in ArcGIS. Second, spatial patterns in sandy beach biodiversity (vertebrates, macrofauna, microflora and foredune plants) were mapped by compiling existing data on the distributions of key species that have been well studied or mapped previously (vertebrates and foredune plants), and by niche modelling (macrofauna and microflora). For the latter, data from all previous sandy-beach sampling events in South Africa were compiled from published and unpublished sources, and supplemented with additional sampling of 23 beaches along the national shoreline, targeting macrofauna and phytoplankton. Altogether, the macrofauna database comprised data from 135 sites and 186 sampling events, and the microflora (phytoplankton and microphytobenthos) database comprised data from 73 sites and 510 samples. The probabilistic distribution of each "resident" species (present at 10 or more sites) was modelled in MaxEnt version 3.3.3k, probability thresholds were determined statistically (to convert the data into predicted presence-absence), and displayed as a digital map. A composite biodiversity map was compiled, and key trends in species richness and endemism along the national shoreline were quantified. To supplement biodiversity proper, additional valued-features of sandy beaches were mapped, including: important assemblages; unique habitat features; and sites associated with key ecological processes. Part 2 considers threats to sandy beaches in the context of deriving an appropriate management strategy that seeks to provide for use of the coast, but in a way that has least overall impact to the ecosystem. A method for assessing cumulative threats to sandy beaches is adapted from an existing framework (Chapter 4). This entailed compiling a list of threats to beaches, and scoring these (out of 10) in terms of the severity of their respective impacts to beaches, and how long it would take the ecosystem to recover should the threat be removed. The scoring was based on the collective expert opinion of the scientific community working on sandy beaches, at a workshop during the VIth International Sandy Beach Symposium 2012. To standardize the scores and ensure broad applicability, a base case scenario of a pristine beach was established, and maximum theoretical scores were provided for this context. The method for integrating these scores into a spatial, cumulative threat assessment was then determined. In Chapter 5, the maximum theoretical scores (from Chapter 4) were down-scaled to suit the current threat regime to the South African sandy beaches, and the cumulative threat assessment methodology was applied. From this analysis, the most threatened beaches in South Africa, and the most important threats were highlighted. A decision-support tool for managers was derived from the site-specific cumulative threat-impact scores, based first on the degree of permanent habitat transformation, and second on the cumulative impact of other stressors where the impacts these stressors have could potentially be mitigated or ameliorated. Part 3 concerns conservation of beaches explicitly. It addresses how much of which valued features of beaches is required to ensure their long-term persistence, and the design of a network of beaches in South Africa that are of ecological importance and should be set aside as reserves. Conservation targets are set in Chapter 6, using species-area curves to determine a baseline percentage-area required to protect sandy beach habitats, which is modified using heuristic principles based on habitat rarity and threat status (from a recent national assessment). A fixed target was applied to all species, also modified by heuristic principles, and another fixed target was applied to key assemblages and processes.