Spatial scaling properties of coral reef benthic communities

The spatial structure of ecological communities on tropical coral reefs across seascapes and geographies have historically been poorly understood. Here we addressed this for the first time using spatially expansive and thematically resolved benthic community data collected around five uninhabited central Pacific oceanic islands, spanning 6° latitude and 17° longitude. Using towed-diver digital image surveys over ~140 linear km of shallow (8–20 m depth) tropical reef, we highlight the autocorrelated nature of coral reef seascapes. Benthic functional groups and hard coral morphologies displayed significant spatial clustering (positive autocorrelation) up to kilometre-scales around all islands, in some instances dominating entire sections of coastline. The scale and strength of these autocorrelation patterns showed differences across geographies, but patterns were more similar between islands in closer proximity and of a similar size. For example, crustose coralline algae (CCA) were clustered up to scales of 0.3 km at neighbouring Howland and Baker Islands and macroalgae were spatially clustered at scales up to ~3 km at both neighbouring Kingman Reef and Palmyra Atoll. Of all the functional groups, macroalgae had the highest levels of spatial clustering across geographies at the finest resolution of our data (100 m). There were several cases where the upper scale at which benthic community members showed evidence of spatial clustering correlated highly with the upper scales at which concurrent gradients in physical environmental drivers were spatially clustered. These correlations were stronger for surface wave energy than subsurface temperature (regardless of benthic group) and turf algae and CCA had the closest alignments in scale with wave energy across functional groups and geographies. Our findings suggest such physical drivers not only limit or promote the abundance of various benthic competitors on coral reefs, but also play a key role in governing their spatial scaling properties across seascapes

Benthic communities at two remote Pacific coral reefs: effects of reef habitat, depth, and wave energy gradients on spatial patterns

Kingman Reef and Palmyra Atoll in the central Pacific are among the most remote coral reefs on the planet. Here we describe spatial patterns in their benthic communities across reef habitats and depths, and consider these in the context of oceanographic gradients. Benthic communities at both locations were dominated by calcifying organisms (54–86% cover), namely hard corals (20–74%) and crustose coralline algae (CCA) (10–36%). While turf algae were relatively common at both locations (8–22%), larger fleshy macroalgae were virtually absent at Kingman (<1%) and rare at Palmyra (0.7–9.3%). Hard coral cover was higher, but with low diversity, in more sheltered habitats such as Palmyra’s backreef and Kingman’s patch reefs. Almost exclusive dominance by slow-growing Porites on Kingman’s patch reefs provides indirect evidence of competitive exclusion, probably late in a successional sequence. In contrast, the more exposed forereef habitats at both Kingman and Palmyra had higher coral diversity and were characterized by fast-growing corals (e.g., Acropora and Pocillopora), indicative of more dynamic environments. In general at both locations, soft coral cover increased with depth, likely reflecting increasingly efficient heterotrophic abilities. CCA and fleshy macroalgae cover decreased with depth, likely due to reduced light. Cover of other calcified macroalgae, predominantly Halimeda, increased with depth. This likely reflects the ability of many calcifying macroalgae to efficiently harvest light at deeper depths, in combination with an increased nutrient supply from upwelling promoting growth. At Palmyra, patterns of hard coral cover with depth were inconsistent, but cover peaked at mid-depths at Kingman. On Kingman’s forereef, benthic community composition was strongly related to wave energy, with hard coral cover decreasing and becoming more spatially clustered with increased wave energy, likely as a result of physical damage leading to patches of coral in localized shelter. In contrast, the cover of turf algae at Kingman was positively related to wave energy, reflecting their ability to rapidly colonize newly available space. No significant patterns with wave energy were observed on Palmyra’s forereef, suggesting that a more detailed model is required to study biophysical coupling there. Kingman, Palmyra, and other remote oceanic reefs provide interesting case studies to explore biophysical influences on benthic ecology and dynamics

Scale-dependent spatial patterns in benthic communities around a tropical island seascape

Understanding and predicting patterns of spatial organization across ecological communities is central to the field of landscape ecology, and a similar line of inquiry has begun to evolve sub-tidally among seascape ecologists. Much of our current understanding of the processes driving marine community patterns, particularly in the tropics, has come from small-scale, spatially-discrete data that are often not representative of the broader seascape. Here we expand the spatial extent of seascape ecology studies and combine spatially-expansive in situ digital imagery, oceanographic measurements, spatial statistics, and predictive modeling to test whether predictable patterns emerge between coral reef benthic competitors across scales in response to intra-island gradients in physical drivers. We do this around the entire circumference of a remote, uninhabited island in the central Pacific (Jarvis Island) that lacks the confounding effects of direct human impacts. We show, for the first time, that competing benthic groups demonstrate predictable scaling patterns of organization, with positive autocorrelation in the cover of each group at scales \u3c ~1 km. Moreover, we show how gradients in subsurface temperature and surface wave power drive spatially-abrupt transition points in group dominance, explaining 48–84% of the overall variation in benthic cover around the island. Along the western coast, we documented ten times more sub-surface cooling-hours than any other part of the coastline, with events typically resulting in a drop of 1–4°C over a period of \u3c 5 h. These high frequency temperature fluctuations are indicative of upwelling induced by internal waves and here result in localized nitrogen enrichment (NO 2 + NO 3 ) that promotes hard coral dominance around 44% of the island\u27s perimeter. Our findings show that, in the absence of confounding direct human impacts, the spatial organization of coral reef benthic competitors are predictable and somewhat bounded across the seascape by concurrent gradients in physical drivers

Near-island biological hotspots in barren ocean basins

Phytoplankton production drives marine ecosystem trophic-structure and global fisheries yields. Phytoplankton biomass is particularly influential near coral reef islands and atolls that span the oligotrophic tropical oceans. The paradoxical enhancement in phytoplankton near an island-reef ecosystem—Island Mass Effect (IME)—was first documented 60 years ago, yet much remains unknown about the prevalence and drivers of this ecologically important phenomenon. Here we provide the first basin-scale investigation of IME. We show that IME is a near-ubiquitous feature among a majority (91%) of coral reef ecosystems surveyed, creating near-island ‘hotspots' of phytoplankton biomass throughout the upper water column. Variations in IME strength are governed by geomorphic type (atoll vs island), bathymetric slope, reef area and local human impacts (for example, human-derived nutrient input). These ocean oases increase nearshore phytoplankton biomass by up to 86% over oceanic conditions, providing basal energetic resources to higher trophic levels that support subsistence-based human populations

Advancing the integration of spatial data to map human and natural drivers on coral reefs

<div><p>A major challenge for coral reef conservation and management is understanding how a wide range of interacting human and natural drivers cumulatively impact and shape these ecosystems. Despite the importance of understanding these interactions, a methodological framework to synthesize spatially explicit data of such drivers is lacking. To fill this gap, we established a transferable data synthesis methodology to integrate spatial data on environmental and anthropogenic drivers of coral reefs, and applied this methodology to a case study location–the Main Hawaiian Islands (MHI). Environmental drivers were derived from time series (2002–2013) of climatological ranges and anomalies of remotely sensed sea surface temperature, chlorophyll-<i>a</i>, irradiance, and wave power. Anthropogenic drivers were characterized using empirically derived and modeled datasets of spatial fisheries catch, sedimentation, nutrient input, new development, habitat modification, and invasive species. Within our case study system, resulting driver maps showed high spatial heterogeneity across the MHI, with anthropogenic drivers generally greatest and most widespread on O‘ahu, where 70% of the state’s population resides, while sedimentation and nutrients were dominant in less populated islands. Together, the spatial integration of environmental and anthropogenic driver data described here provides a first-ever synthetic approach to visualize how the drivers of coral reef state vary in space and demonstrates a methodological framework for implementation of this approach in other regions of the world. By quantifying and synthesizing spatial drivers of change on coral reefs, we provide an avenue for further research to understand how drivers determine reef diversity and resilience, which can ultimately inform policies to protect coral reefs.</p></div

Parsing human and biophysical drivers of coral reef regimes

Coral reefs worldwide face unprecedented cumulative anthropogenic effects of interacting local human pressures, global climate change and distal social processes. Reefs are also bound by the natural biophysical environment within which they exist. In this context, a key challenge for effective management is understanding how anthropogenic and biophysical conditions interact to drive distinct coral reef configurations. Here, we use machine learning to conduct explanatory predictions on reef ecosystems defined by both fish and benthic communities. Drawing on the most spatially extensive dataset available across the Hawaiian archipelago-20 anthropogenic and biophysical predictors over 620 survey sites-we model the occurrence of four distinct reef regimes and provide a novel approach to quantify the relative influence of human and environmental variables in shaping reef ecosystems. Our findings highlight the nuances of what underpins different coral reef regimes, the overwhelming importance of biophysical predictors and how a reef's natural setting may either expand or narrow the opportunity space for management interventions. The methods developed through this study can help inform reef practitioners and hold promises for replication across a broad range of ecosystems. © 2019 The Author(s