Integrated assessment of the spatial distribution and structural dynamics of deep benthic marine communities.

Characterizing the spatial distribution and variation of species communities and validating these characteristics with data from the field are key elements for an ecosystem-based approach to management. However, models of species distributions that yield community structure are usually not linked to models of community dynamics, constraining understanding and management of the ecosystem, particularly in data-poor regions. Here we use a qualitative network model to predict changes in Antarctic benthic community structure between major marine habitats characterized largely by seafloor depth and slope, and use multivariate mixture models of species distributions to validate the community dynamics. We then assess how future increases in primary production associated with anticipated loss of sea-ice may affect the ecosystem. Our study shows how both spatial and structural features of ecosystems in data-poor regions can be analyzed and possible futures assessed, with direct relevance for ecosystem-based management.

Global patterns of change and variation in sea surface temperature and chlorophyll a.

Changes over the scale of decades in oceanic environments present a range of challenges for management and utilisation of ocean resources. Here we investigate sources of global temporal variation in Sea Surface Temperature (SST) and Ocean Colour (Chl-a) and their co-variation, over a 14 year period using statistical methodologies that partition sources of variation into inter-annual and annual components and explicitly account for daily auto-correlation. The variation in SST shows bands of increasing variability with increasing latitude, while the analysis of annual variability in Chl-a shows mostly mid-latitude high variability bands. Covariation patterns of SST and Chl-a suggests several different mechanisms impacting Chl-a change and variance. Our high spatial resolution analysis indicates these are likely to be operating at relatively small spatial scales. There are large regions showing warming and rising of Chl-a, contrasting with regions that show warming and decreasing Chl-a. The covariation pattern in annual variation in SST and Chl-a reveals broad latitudinal bands. On smaller scales there are significant regional anomalies where upwellings are known to occur. Over decadal time scales both trend and variation in SST, Chl-a and their covariance is highly spatially heterogeneous, indicating that monitoring and resource management must be regionally appropriate.

Abundance and richness of key Antarctic seafloor fauna correlates with modelled food availability.

Most seafloor communities at depths below the photosynthesis zone rely on food that sinks through the water column. However, the nature and strength of this pelagic-benthic coupling and its influence on the structure and diversity of seafloor communities is unclear, especially around Antarctica where ecological data are sparse. Here we show that the strength of pelagic-benthic coupling along the East Antarctic shelf depends on both physical processes and the types of benthic organisms considered. In an approach based on modelling food availability, we combine remotely sensed sea-surface chlorophyll-a, a regional ocean model and diatom abundances from sediment grabs with particle tracking and show that fluctuating seabed currents are crucial in the redistribution of surface productivity at the seafloor. The estimated availability of suspended food near the seafloor correlates strongly with the abundance of benthic suspension feeders, while the deposition of food particles correlates with decreasing suspension feeder richness and more abundant deposit feeders. The modelling framework, which can be modified for other regions, has broad applications in conservation and management, as it enables spatial predictions of key components of seafloor biodiversity over vast regions around Antarctica.

Deep-sea diversity patterns are shaped by energy availability.

The deep ocean is the largest and least-explored ecosystem on Earth, and a uniquely energy-poor environment. The distribution, drivers and origins of deep-sea biodiversity remain unknown at global scales. Here we analyse a database of more than 165,000 distribution records of Ophiuroidea (brittle stars), a dominant component of sea-floor fauna, and find patterns of biodiversity unlike known terrestrial or coastal marine realms. Both patterns and environmental predictors of deep-sea (2,000-6,500 m) species richness fundamentally differ from those found in coastal (0-20 m), continental shelf (20-200 m), and upper-slope (200-2,000 m) waters. Continental shelf to upper-slope richness consistently peaks in tropical Indo-west Pacific and Caribbean (0-30°) latitudes, and is well explained by variations in water temperature. In contrast, deep-sea species show maximum richness at higher latitudes (30-50°), concentrated in areas of high carbon export flux and regions close to continental margins. We reconcile this structuring of oceanic biodiversity using a species-energy framework, with kinetic energy predicting shallow-water richness, while chemical energy (export productivity) and proximity to slope habitats drive deep-sea diversity. Our findings provide a global baseline for conservation efforts across the sea floor, and demonstrate that deep-sea ecosystems show a biodiversity pattern consistent with ecological theory, despite being different from other planetary-scale habitats.

Results of efforts by the Convention on Biological Diversity to describe ecologically or biologically significant marine areas.

In 2004, Parties to the Convention on Biological Diversity (CBD) addressed a United Nations (UN) call for area-based planning, including for marine-protected areas that resulted in a global effort to describe ecologically or biologically significant marine areas (EBSAs). We summarized the results, assessed their consistency, and evaluated the process developed by the Secretariat of the CBD to engage countries and experts in 9 regional workshops held from 2011 to 2014. Experts from 92 countries and 79 regional or international bodies participated. They considered 250 million km(2) of the world's ocean area (two-thirds of the total). The 204 areas they examined in detail differed widely in area (from 5.5 km(2) to 11.1 million km(2) ). Despite the initial focus of the CBD process on areas outside national jurisdiction, only 31 of the areas examined were solely outside national jurisdiction. Thirty-five extended into national jurisdictions, 137 were solely within national jurisdictions, and 28 included the jurisdictions of more than 1 country (1 area lacked precise boundaries). Data were sufficient to rank 88-99% of the areas relative to each of the 7 criteria for EBSAs agreed to previously by Parties to the CBD. The naturalness criterion ranked high for a smaller percentage of the EBSAs (31%) than other criteria (51-70%), indicating the difficulty in finding relatively undisturbed areas in the ocean. The highly participatory nature of the workshops, including easy and consistent access to the relevant information facilitated by 2 technical teams, contributed to the workshop participants success in identifying areas that could be ranked relative to most criteria and areas that extend across jurisdictional boundaries. The formal recognition of workshop results by the Conference of Parties to the CBD resulted in these 204 areas being identified as EBSAs by the 196 Parties. They represent the only suite of marine areas recognized by the international community for their greater importance for biodiversity it is their importance for biodiversity itself not conservation as process explicitly excluded management issues than their surroundings. This comes at a critical juncture in negotiations at the UN that will consider developing a new implementation agreement under UN Convention of the Law of the Sea to support the conservation and sustainable use of marine biological diversity beyond areas of national jurisdiction. The EBSA description process is a good example of how to bring the international community together to build a shared understanding of which ocean areas are particularly valuable to biodiversity.

Modelling marine protected areas: insights and hurdles.

Models provide useful insights into conservation and resource management issues and solutions. Their use to date has highlighted conditions under which no-take marine protected areas (MPAs) may help us to achieve the goals of ecosystem-based management by reducing pressures, and where they might fail to achieve desired goals. For example, static reserve designs are unlikely to achieve desired objectives when applied to mobile species or when compromised by climate-related ecosystem restructuring and range shifts. Modelling tools allow planners to explore a range of options, such as basing MPAs on the presence of dynamic oceanic features, and to evaluate the potential future impacts of alternative interventions compared with 'no-action' counterfactuals, under a range of environmental and development scenarios. The modelling environment allows the analyst to test if indicators and management strategies are robust to uncertainties in how the ecosystem (and the broader human-ecosystem combination) operates, including the direct and indirect ecological effects of protection. Moreover, modelling results can be presented at multiple spatial and temporal scales, and relative to ecological, economic and social objectives. This helps to reveal potential 'surprises', such as regime shifts, trophic cascades and bottlenecks in human responses. Using illustrative examples, this paper briefly covers the history of the use of simulation models for evaluating MPA options, and discusses their utility and limitations for informing protected area management in the marine realm.

Do communities exist? Complex patterns of overlapping marine species distributions.

Understanding the way in which species are associated in communities is a fundamental question in ecology. Yet there remains a tension between communities as highly structured units or as coincidental collections of individualistic species. We explored these ideas using a new statistical approach that clusters species based on their environmental response: a species archetype, rather than clustering sites based on their species composition. We found groups of species that are consistently highly correlated, but that these groups are not unique to any set of locations and overlap spatially. The species present at a single site are a realization of species from the (multiple) archetype groups that are likely to be present at that location based on their response to the environment.

Twenty years of high-resolution sea surface temperature imagery around Australia: inter-annual and annual variability.

The physical climate defines a significant portion of the habitats in which biological communities and species reside. It is important to quantify these environmental conditions, and how they have changed, as this will inform future efforts to study many natural systems. In this article, we present the results of a statistical summary of the variability in sea surface temperature (SST) time-series data for the waters surrounding Australia, from 1993 to 2013. We partition variation in the SST series into annual trends, inter-annual trends, and a number of components of random variation. We utilise satellite data and validate the statistical summary from these data to summaries of data from long-term monitoring stations and from the global drifter program. The spatially dense results, available as maps from the Australian Oceanographic Data Network's data portal (http://www.cmar.csiro.au/geonetwork/srv/en/metadata.show?id=51805), show clear trends that associate with oceanographic features. Noteworthy oceanographic features include: average warming was greatest off southern West Australia and off eastern Tasmania, where the warming was around 0.6°C per decade for a twenty year study period, and insubstantial warming in areas dominated by the East Australian Current, but this area did exhibit high levels of inter-annual variability (long-term trend increases and decreases but does not increase on average). The results of the analyses can be directly incorporated into (biogeographic) models that explain variation in biological data where both biological and environmental data are on a fine scale.

The coral sea: physical environment, ecosystem status and biodiversity assets.

The Coral Sea, located at the southwestern rim of the Pacific Ocean, is the only tropical marginal sea where human impacts remain relatively minor. Patterns and processes identified within the region have global relevance as a baseline for understanding impacts in more disturbed tropical locations. Despite 70 years of documented research, the Coral Sea has been relatively neglected, with a slower rate of increase in publications over the past 20 years than total marine research globally. We review current knowledge of the Coral Sea to provide an overview of regional geology, oceanography, ecology and fisheries. Interactions between physical features and biological assemblages influence ecological processes and the direction and strength of connectivity among Coral Sea ecosystems. To inform management effectively, we will need to fill some major knowledge gaps, including geographic gaps in sampling and a lack of integration of research themes, which hinder the understanding of most ecosystem processes.

To mix or not to mix: comparing the predictive performance of mixture models vs. separate species distribution models.

Species distribution models (SDMs) are an important tool for studying the patterns of species across environmental and geographic space. For community data, a common approach involves fitting an SDM to each species separately, although the large number of models makes interpretation difficult and fails to exploit any similarities between individual species responses. A recently proposed alternative that can potentially overcome these difficulties is species archetype models (SAMs), a model-based approach that clusters species based on their environmental response. In this paper, we compare the predictive performance of SAMs against separate SDMs using a number of multi-species data sets. Results show that SAMs improve model accuracy and discriminatory capacity compared to separate SDMs. This is achieved by borrowing strength from common species having higher information content. Moreover, the improvement increases as the species become rarer.

Characterising and predicting benthic biodiversity for conservation planning in deepwater environments.

Understanding patterns of biodiversity in deep sea systems is increasingly important because human activities are extending further into these areas. However, obtaining data is difficult, limiting the ability of science to inform management decisions. We have used three different methods of quantifying biodiversity to describe patterns of biodiversity in an area that includes two marine reserves in deep water off southern Australia. We used biological data collected during a recent survey, combined with extensive physical data to model, predict and map three different attributes of biodiversity: distributions of common species, beta diversity and rank abundance distributions (RAD). The distribution of each of eight common species was unique, although all the species respond to a depth-correlated physical gradient. Changes in composition (beta diversity) were large, even between sites with very similar environmental conditions. Composition at any one site was highly uncertain, and the suite of species changed dramatically both across and down slope. In contrast, the distributions of the RAD components of biodiversity (community abundance, richness, and evenness) were relatively smooth across the study area, suggesting that assemblage structure (i.e. the distribution of abundances of species) is limited, irrespective of species composition. Seamounts had similar biodiversity based on metrics of species presence, beta diversity, total abundance, richness and evenness to the adjacent continental slope in the same depth ranges. These analyses suggest that conservation objectives need to clearly identify which aspects of biodiversity are valued, and employ an appropriate suite of methods to address these aspects, to ensure that conservation goals are met.

The analysis of biodiversity using rank abundance distributions.

Biodiversity is an important topic of ecological research. A common form of data collected to investigate patterns of biodiversity is the number of individuals of each species at a series of locations. These data contain information on the number of individuals (abundance), the number of species (richness), and the relative proportion of each species within the sampled assemblage (evenness). If there are enough sampled locations across an environmental gradient then the data should contain information on how these three attributes of biodiversity change over gradients. We show that the rank abundance distribution (RAD) representation of the data provides a convenient method for quantifying these three attributes constituting biodiversity. We present a statistical framework for modeling RADs and allow their multivariate distribution to vary according to environmental gradients. The method relies on three models: a negative binomial model, a truncated negative binomial model, and a novel model based on a modified Dirichlet-multinomial that allows for a particular type of heterogeneity observed in RAD data. The method is motivated by, and applied to, a large-scale marine survey off the coast of Western Australia, Australia. It provides a rich description of biodiversity and how it changes with environmental conditions.

Linking richness, community variability, and invasion resistance with patch size.

The influence of community dynamics on the success or failure of an invasion is of considerable interest. What has not been explored is the influence of patch size on the outcomes of invasions for communities with the same species pool. Here we use an empirically validated spatial model of a marine epibenthic community to examine the effects of patch size on community variability, species richness, invasion, and the relationships between these variables. We found that the qualitative form of the relationship between community variability and species richness is determined by the size of the model patch. In small patches, variability decreases with species richness, but beyond a critical patch size, variability increases with increasing richness. This occurs because in large patches large, long-lived colonies attain sufficient size to minimize mortality and dominate the community, leading to decreased species richness and community variability. This mechanism cannot operate on smaller patches where the size of colonies is limited by the patch size and mortality is high irrespective of species identity. Further, invasion resistance is strongly correlated with community variability. Thus, the relationship between species richness and invasion resistance is also determined by patch size. These patterns are generated largely by an inverse relationship between colony size and mortality, and they depend on the spatial nature and patch size of the community. Our results suggest that a continuum of possible relationships can exist between species richness, community variability, invasion resistance, and area. These relationships are emergent behaviors generated by the individual properties of the particular component species of a community.

Invasion rates increase with species richness in a marine epibenthic community by two mechanisms.

It is widely believed that, when extrinsic conditions are similar, the likelihood of species invading established assemblages decreases with increasing species richness of the recipient community. Here we show that, for a sessile marine invertebrate community, invasion of patches increases with richness of the patch. We show that invasions can increase with local species richness by two distinct mechanisms. In the first, opportunistic colonisers with traits typical of invasive species colonise species-rich patches at higher rates because speciose patches are dominated by small colonies and mortality rates of small colonies are greater than that of large ones. Thus, mortality provides bare space for opportunists to colonise more frequently in species-rich patches. In the second, some species avoid colonising open areas of free space but preferentially associate with established colonies of particular other species, and a given preferred associate is more likely to occur in species-rich than in species-poor patches. These patterns are the result of particular properties of individual species and local species dynamics, and show that reduced risk of invasion is not necessarily an intrinsic property of species-rich communities. We conclude that resistance to invasion will be determined by the properties of the particular component species and emergent dynamics of the recipient community, and not by an aggregate community property such as richness.