Habitat structural complexity of Caribbean coral reefs and its relationships with fish community structure

PhD ThesisHabitat structural complexity (HSC) is a key component of natural ecosystems. It helps to describe the morphological characteristics of the three-dimensional space that floral and faunal communities exist within. The physical structure can have a profound influence on the associated diversity and functioning of the ecosystem. This thesis is a macroecological study of Caribbean coral reef HSC and how changes in it might influence associated fish communities. An assessment of contemporary reef HSC in 15 countries and its relationship with spatial, environmental and anthropogenic variables, identified the degree and frequency of physical disturbance as significant drivers. There was also a strong link between live coral and HSC indicating that, despite region-wide declines in coral cover, there has not been a decoupling of complexity and coral, and that healthy coral populations facilitate the persistence of structurally complex coral habitats. To examine the relationships between different measures of HSC and their relevance to the fish community, a multidimensional model of HSC was developed. Through this approach it was possible to combine a number of variables which individually indicate different components of reef HSC, and derive compound ‘refuge’ and ‘complexity’ variables which are expected to be of greater relevance to the fish community, and potentially of greater use to understanding macroecological relationships on coral reefs. This approach was used to identify relationships between the Caribbean reef fish functional community structure and the derived refuge variable. Sites with low refuge levels were dominated by generalist fish species and had low levels of functional diversity. Additionally, the biomass of a number of fish functional groups and the size ii structure of groups was found to be related to the refuge characteristics of coral reefs. The examination of fish communities at night revealed a continued relationship with HSC over the entire diel cycle for some functional groups while others varied in their association with reef structure. Nocturnally active groups decoupled from HSC as they moved over flatter areas of reef to feed, while diurnally active groups moved into the reef to shelter. Observations of behaviour and feature preferences identified potential drivers behind the numerical relationships between the fish community and HSC. Some species have strong behavioural associations with HSC or features of reef structure and may suffer as result of habitat complexity declines. However, small non-fisheries target species such as wrasse and damsels, with less direct physical ties to the habitat structure are those most likely to persist after habitat degradation. The thesis highlights the state of and threats to Caribbean HSC and the pivotal role it plays in determining fish community structure.Fisheries Society of the British Isles PhD Studentship. Further funding for fieldwork was provided by European Union 7th Framework program through the Future of Reefs in a Changing Environment and the Department for Environment, Food and Rural Affairs

Data from: Reef flattening effects on total richness and species responses in the Caribbean

1. There has been ongoing flattening of Caribbean coral reefs with the loss of habitat having severe implications for these systems. Complexity and its structural components are important to fish species richness and community composition, but little is known about its role for other taxa or species-specific responses. 2. This study reveals the importance of reef habitat complexity and structural components to different taxa of macrofauna, total species richness, and individual coral and fish species in the Caribbean. 3. Species presence and richness of different taxa were visually quantified in one hundred 25-m2 plots in three marine reserves in the Caribbean. Sampling was evenly distributed across five levels of visually estimated reef complexity, with five structural components also recorded: the number of corals, number of large corals, slope angle, maximum sponge and maximum octocoral height. Taking advantage of natural heterogeneity in structural complexity within a particular coral reef habitat (Orbicella reefs) and discrete environmental envelope, thus minimizing other sources of variability, the relative importance of reef complexity and structural components was quantified for different taxa and individual fish and coral species on Caribbean coral reefs using boosted regression trees (BRTs). 4. Boosted regression tree models performed very well when explaining variability in total (82·3%), coral (80·6%) and fish species richness (77·3%), for which the greatest declines in richness occurred below intermediate reef complexity levels. Complexity accounted for very little of the variability in octocorals, sponges, arthropods, annelids or anemones. BRTs revealed species-specific variability and importance for reef complexity and structural components. Coral and fish species occupancy generally declined at low complexity levels, with the exception of two coral species (Pseudodiploria strigosa and Porites divaricata) and four fish species (Halichoeres bivittatus, H. maculipinna, Malacoctenus triangulatus and Stegastes partitus) more common at lower reef complexity levels. A significant interaction between country and reef complexity revealed a non-additive decline in species richness in areas of low complexity and the reserve in Puerto Rico. 5. Flattening of Caribbean coral reefs will result in substantial species losses, with few winners. Individual structural components have considerable value to different species, and their loss may have profound impacts on population responses of coral and fish due to identity effects of key species, which underpin population richness and resilience and may affect essential ecosystem processes and services

Data Newman et al

Sheet 1: Taxa Richness: species richness of each taxa in each plot (row), with 7 predictor variables. Sheet 2: Coral Species: 6 predictor variables, with presence (1) absence (0) of each coral species modelled. Sheet 3: Fish Species: 7 predictor variables, with presence/absence of each fish species modelled