C. Roland Pitcher

Adaptive management of the Great Barrier Reef: A globally significant demonstration of the benefits of networks of marine reserves

The Great Barrier Reef (GBR) provides a globally significant demonstration of the effectiveness of large-scale networks of marine reserves in contributing to integrated, adaptive management. Comprehensive review of available evidence shows major, rapid benefits of no-take areas for targeted fish and sharks, in both reef and nonreef habitats, with potential benefits for fisheries as well as biodiversity conservation. Large, mobile species like sharks benefit less than smaller, site-attached fish. Critically, reserves also appear to benefit overall ecosystem health and resilience: outbreaks of coral-eating, crown-of-thorns starfish appear less frequent on no-take reefs, which consequently have higher abundance of coral, the very foundation of reef ecosystems. Effective marine reserves require regular review of compliance: fish abundances in no-entry zones suggest that even no-take zones may be significantly depleted due to poaching. Spatial analyses comparing zoning with seabed biodiversity or dugong distributions illustrate significant benefits from application of best-practice conservation principles in data-poor situations. Increases in the marine reserve network in 2004 affected fishers, but preliminary economic analysis suggests considerable net benefits, in terms of protecting environmental and tourism values. Relative to the revenue generated by reef tourism, current expenditure on protection is minor. Recent implementation of an Outlook Report provides regular, formal review of environmental condition and management and links to policy responses, key aspects of adaptive management. Given the major threat posed by climate change, the expanded network of marine reserves provides a critical and cost-effective contribution to enhancing the resilience of the Great Barrier Reef.

Global Patterns and Predictions of Seafloor Biomass Using Random Forests

A comprehensive seafloor biomass and abundance database has been constructed from 24 oceanographic institutions worldwide within the Census of Marine Life (CoML) field projects. The machine-learning algorithm, Random Forests, was employed to model and predict seafloor standing stocks from surface primary production, water-column integrated and export particulate organic matter (POM), seafloor relief, and bottom water properties. The predictive models explain 63% to 88% of stock variance among the major size groups. Individual and composite maps of predicted global seafloor biomass and abundance are generated for bacteria, meiofauna, macrofauna, and megafauna (invertebrates and fishes). Patterns of benthic standing stocks were positive functions of surface primary production and delivery of the particulate organic carbon (POC) flux to the seafloor. At a regional scale, the census maps illustrate that integrated biomass is highest at the poles, on continental margins associated with coastal upwelling and with broad zones associated with equatorial divergence. Lowest values are consistently encountered on the central abyssal plains of major ocean basins The shift of biomass dominance groups with depth is shown to be affected by the decrease in average body size rather than abundance, presumably due to decrease in quantity and quality of food supply. This biomass census and associated maps are vital components of mechanistic deep-sea food web models and global carbon cycling, and as such provide fundamental information that can be incorporated into evidence-based management.

Exploring the role of environmental variables in shaping patterns of seabed biodiversity composition in regional‐scale ecosystems

Summary 1. Environmental variables are often used as indirect surrogates for mapping biodiversity because species survey data are scant at regional scales, especially in the marine realm. However, environmental variables are measured on arbitrary scales unlikely to have simple, direct relationships with biological patterns. Instead, biodiversity may respond nonlinearly and to interactions between environmental variables. 2. To investigate the role of the environment in driving patterns of biodiversity composition in large marine regions, we collated multiple biological survey and environmental data sets from tropical NE Australia, the deep Gulf of Mexico and the temperate Gulf of Maine. We then quantified the shape and magnitude of multispecies responses along >30 environmental gradients and the extent to which these variables predicted regional distributions. To do this, we applied a new statistical approach, Gradient Forest, an extension of Random Forest, capable of modelling nonlinear and threshold responses. 3. The regional‐scale environmental variables predicted an average of 13–35% (up to 50–85% for individual species) of the variation in species abundance distributions. Important predictors differed among regions and biota and included depth, salinity, temperature, sediment composition and current stress. The shapes of responses along gradients also differed and were nonlinear, often with thresholds indicative of step changes in composition. These differing regional responses were partly due to differing environmental indicators of bioregional boundaries and, given the results to date, may indicate limited scope for extrapolating bio‐physical relationships beyond the region of source data sets. 4.  Synthesis and applications. Gradient Forest offers a new capability for exploring relationships between biodiversity and environmental gradients, generating new information on multispecies responses at a detail not available previously. Importantly, given the scarcity of data, Gradient Forest enables the combined use of information from disparate data sets. The gradient response curves provide biologically informed transformations of environmental layers to predict and map expected patterns of biodiversity composition that represent sampled composition better than uninformed variables. The approach can be applied to support marine spatial planning and management and has similar applicability in terrestrial realms.

Global analysis of depletion and recovery of seabed biota after bottom trawling disturbance

Significance Bottom trawling is the most widespread source of physical disturbance to the world’s seabed. Predictions of trawling impacts are needed to underpin risk assessment, and they are relevant for the fishing industry, conservation, management, and certification bodies. We estimate depletion and recovery of seabed biota after trawling by fitting models to data from a global data compilation. Trawl gears removed 6–41% of faunal biomass per pass, and recovery times posttrawling were 1.9–6.4 y depending on fisheries and environmental context. These results allow the estimation of trawling impacts on unprecedented spatial scales and for data poor fisheries and enable an objective analysis of tradeoffs between harvesting fish and the wider ecosystem effects of such activities. Bottom trawling is the most widespread human activity affecting seabed habitats. Here, we collate all available data for experimental and comparative studies of trawling impacts on whole communities of seabed macroinvertebrates on sedimentary habitats and develop widely applicable methods to estimate depletion and recovery rates of biota after trawling. Depletion of biota and trawl penetration into the seabed are highly correlated. Otter trawls caused the least depletion, removing 6% of biota per pass and penetrating the seabed on average down to 2.4 cm, whereas hydraulic dredges caused the most depletion, removing 41% of biota and penetrating the seabed on average 16.1 cm. Median recovery times posttrawling (from 50 to 95% of unimpacted biomass) ranged between 1.9 and 6.4 y. By accounting for the effects of penetration depth, environmental variation, and uncertainty, the models explained much of the variability of depletion and recovery estimates from single studies. Coupled with large-scale, high-resolution maps of trawling frequency and habitat, our estimates of depletion and recovery rates enable the assessment of trawling impacts on unprecedented spatial scales.

Estimating the sustainability of towed fishing‐gear impacts on seabed habitats: a simple quantitative risk assessment method applicable to data‐limited fisheries

1. Impacts of bottom fishing, particularly trawling and dredging, on seabed (benthic) habitats are commonly perceived to pose serious environmental risks. Quantitative ecological risk assessment can be used to evaluate actual risks and to help guide the choice of management measures needed to meet sustainability objectives. 2. We develop and apply a quantitative method for assessing the risks to benthic habitats by towed bottom-fishing gears. The method is based on a simple equation for relative benthic status (RBS), derived by solving the logistic population growth equation for the equilibrium state. Estimating RBS requires only maps of fishing intensity and habitat type — and parameters for impact and recovery rates, which may be taken from meta-analyses of multiple experimental studies of towed-gear impacts. The aggregate status of habitats in an assessed region is indicated by the distribution of RBS values for the region. The application of RBS is illustrated for a tropical shrimp-trawl fishery. 3. The status of trawled habitats and their RBS value depend on impact rate (depletion per trawl), recovery rate and exposure to trawling. In the shrimp-trawl fishery region, gravel habitat was most sensitive, and though less exposed than sand or muddy-sand, was most affected overall (regional RBS=91% relative to un-trawled RBS=100%). Muddy-sand was less sensitive, and though relatively most exposed, was less affected overall (RBS=95%). Sand was most heavily trawled but least sensitive and least affected overall (RBS=98%). Region-wide, >94% of habitat area had >80% RBS because most trawling and impacts were confined to small areas. RBS was also applied to the regions benthic invertebrate communities with similar results. 4. Conclusions. Unlike qualitative or categorical trait-based risk assessments, the RBS method provides a quantitative estimate of status relative to an unimpacted baseline, with minimal requirements for input data. It could be applied to bottom-contact fisheries worldwide, including situations where detailed data on characteristics of seabed habitats, or the abundance of seabed fauna are not available. The approach supports assessment against sustainability criteria and evaluation of alternative management strategies (e.g. closed areas, effort management, gear modifications).

Congruence in demersal fish, macroinvertebrate, and macroalgal community turnover on shallow temperate reefs.

To support coastal planning through improved understanding of patterns of biotic and abiotic surrogacy at broad scales, we used gradient forest modeling (GFM) to analyze and predict spatial patterns of compositional turnover of demersal fishes, macroinvertebrates, and macroalgae on shallow, temperate Australian reefs. Predictive models were first developed using environmental surrogates with estimates of prediction uncertainty, and then the efficacy of the three assemblages as biosurrogates for each other was assessed. Data from underwater visual surveys of subtidal rocky reefs were collected from the southeastern coastline of continental Australia (including South Australia and Victoria) and the northern coastline of Tasmania. These data were combined with 0.01 degree-resolution gridded environmental variables to develop statistical models of compositional turnover (beta diversity) using GFM. GFM extends the machine learning, ensemble tree-based method of random forests (RF), to allow the simultaneous modeling of multiple taxa. The models were used to generate predictions of compositional turnover for each of the three assemblages within unsurveyed areas across the 6600 km of coastline in the region of interest. The most important predictor for all three assemblages was variability in sea surface temperature (measured as standard deviation from measures taken interannually). Spatial predictions of compositional turnover within unsurveyed areas across the region of interest were remarkably congruent across the three taxa. However, the greatest uncertainty in these predictions varied in location among the different assemblages. Pairwise congruency comparisons of observed and predicted turnover among the three assemblages showed that invertebrate and macroalgal biodiversity were most similar, followed by fishes and macroalgae, and lastly fishes and invertebrate biodiversity, suggesting that of the three assemblages, macroalgae would make the best biosurrogate for both invertebrate and fish compositional turnover.

Bottom trawl fishing footprints on the world’s continental shelves

Significance We conducted a systematic, high-resolution analysis of bottom trawl fishing footprints for 24 regions on continental shelves and slopes of five continents and New Zealand. The proportion of seabed trawled varied >200-fold among regions (from 0.4 to 80.7% of area to a depth of 1,000 m). Within 18 regions, more than two-thirds of seabed area remained untrawled during study periods of 2–6 years. Relationships between metrics of total trawling activity and footprint were strong and positive, providing a method to estimate trawling footprints for regions where high-resolution data are not available. Trawling footprints were generally smaller in regions where fisheries met targets for exploitation rates, implying collateral environmental benefits of effective fisheries management. Bottom trawlers land around 19 million tons of fish and invertebrates annually, almost one-quarter of wild marine landings. The extent of bottom trawling footprint (seabed area trawled at least once in a specified region and time period) is often contested but poorly described. We quantify footprints using high-resolution satellite vessel monitoring system (VMS) and logbook data on 24 continental shelves and slopes to 1,000-m depth over at least 2 years. Trawling footprint varied markedly among regions: from <10% of seabed area in Australian and New Zealand waters, the Aleutian Islands, East Bering Sea, South Chile, and Gulf of Alaska to >50% in some European seas. Overall, 14% of the 7.8 million-km2 study area was trawled, and 86% was not trawled. Trawling activity was aggregated; the most intensively trawled areas accounting for 90% of activity comprised 77% of footprint on average. Regional swept area ratio (SAR; ratio of total swept area trawled annually to total area of region, a metric of trawling intensity) and footprint area were related, providing an approach to estimate regional trawling footprints when high-resolution spatial data are unavailable. If SAR was ≤0.1, as in 8 of 24 regions, there was >95% probability that >90% of seabed was not trawled. If SAR was 7.9, equal to the highest SAR recorded, there was >95% probability that >70% of seabed was trawled. Footprints were smaller and SAR was ≤0.25 in regions where fishing rates consistently met international sustainability benchmarks for fish stocks, implying collateral environmental benefits from sustainable fishing.

Monitoring demersal scalefish populations in the Browse Basin region: accounting for spatial variability and detecting change in key fish populations

One of the objectives of the Applied Research Program (ARP), funded by Shell and the INPEX-operated Ichthys LNG Project, was to establish the basis for evaluating the effects of any potential oil spill from the Prelude or Ichthys fields on populations of commercially important demersal fishes in the Northern Demersal Scalefish Managed Fishery. The ARP has delivered improved baseline understanding of the status and spatial variability in populations of commercially and ecologically important finfish of the Browse Basin region, in the vicinity of the Prelude and Ichthys fields, using both commercial-style fish traps and baited remote underwater videos (BRUVs) as sampling methods. We used available environmental-data layers and fish-distribution data, in combination with modelled plume projections, to design a study such that sites were balanced with respect to fish habitat and likely affected and unaffected zones. The sampling-design employed was statistically effective with power to show changes in fish assemblages, and relative abundance of as little as 30% could be detected with 80% certainty in the main commercial species, goldband snapper (Pristipomoides multidens), using BRUVs. For the second-most important species, red emperor (Lutjanus sebae), a larger decline of 50% would have to occur for this change to be determined with the same level of confidence. Traps were a more powerful tool for sampling L. sebae, allowing a 40% change to be detected; however, for all other species BRUVs were more powerful. Sampling of the demersal-fish assemblages surrounding the Prelude and Ichthys fields by using both fish traps and BRUVs demonstrated the feasibility of detecting change in the relative abundance of the fish assemblage as well as in the key commercial species.