Recent pace of change in human impact on the world's ocean.

Humans interact with the oceans in diverse and profound ways. The scope, magnitude, footprint and ultimate cumulative impacts of human activities can threaten ocean ecosystems and have changed over time, resulting in new challenges and threats to marine ecosystems. A fundamental gap in understanding how humanity is affecting the oceans is our limited knowledge about the pace of change in cumulative impact on ocean ecosystems from expanding human activities - and the patterns, locations and drivers of most significant change. To help address this, we combined high resolution, annual data on the intensity of 14 human stressors and their impact on 21 marine ecosystems over 11 years (2003-2013) to assess pace of change in cumulative impacts on global oceans, where and how much that pace differs across the ocean, and which stressors and their impacts contribute most to those changes. We found that most of the ocean (59%) is experiencing significantly increasing cumulative impact, in particular due to climate change but also from fishing, land-based pollution and shipping. Nearly all countries saw increases in cumulative impacts in their coastal waters, as did all ecosystems, with coral reefs, seagrasses and mangroves at most risk. Mitigation of stressors most contributing to increases in overall cumulative impacts is urgently needed to sustain healthy oceans

Improving estimates of population status and trend with superensemble models

Fishery managers must often reconcile conflicting estimates of population status and trend. Superensemble models, commonly used in climate and weather forecasting, may provide an effective solution. This approach uses predictions from multiple models as covariates in an additional "superensemble" model fitted to known data. We evaluated the potential for ensemble averages and superensemble models (ensemble methods) to improve estimates of population status and trend for fisheries. We fit four widely applicable data-limited models that estimate stock biomass relative to equilibrium biomass at maximum sustainable yield (B/BMSY). We combined these estimates of recent fishery status and trends in B/BMSY with four ensemble methods: an ensemble average and three superensembles (a linear model, a random forest and a boosted regression tree). We trained our superensembles on 5,760 simulated stocks and tested them with cross-validation and against a global database of 249 stock assessments. Ensemble methods substantially improved estimates of population status and trend. Random forest and boosted regression trees performed the best at estimating population status: inaccuracy (median absolute proportional error) decreased from 0.42 -0.56 to 0.32 -0.33, rank-order correlation between predicted and true status improved from 0.02 - 0.32 to 0.44 - 0.48 and bias (median proportional error) declined from - 0.22 - 0.31 to - 0.12 - 0.03. We found similar improvements when predicting trend and when applying the simulation-trained superensembles to catch data for global fish stocks. Superensembles can optimally leverage multiple model predictions; however, they must be tested, formed from a diverse set of accurate models and built on a data set representative of the populations to which they are applied

Environmental determinants of motile cryptofauna on an eastern Pacific coral reef

Coral reef cryptofauna, which live hidden within reef framework structures, are considered to be the most diverse group of coral reef metazoans. They likely comprise more biomass than all surface fauna, providing food sources for fishes and playing important roles as predators, herbivores, detritivores, filter feeders, and scavengers. In an era of global change, it is necessary to determine how these communities are structured across reef habitats as well as to understand how reef framework degradation will impact the cryptofauna and, by extension, ecosystem function. Artificial reef framework units were constructed from coral rubble to approxi-mate framework substrates. Forty replicates were subjected to treatments of differing porosity, flow, and coral cover in a fully crossed ANOVA design. After 2 mo in situ, all motile cryptofauna (2 mm) were counted, weighed, and identified to the lowest possible level. A total of 11309 specimens were collected, comprising 121 species from 6 separate phyla. Cryptofaunal abundances and biomass were higher in low-porosity crypts and biomass was greater in slow-flow environments, highlighting the importance of sheltered low-porosity habitats, such as back-reef rubble plains. The presence of live coral was not found to have a significant effect on the motile cryptofauna occupying the dead coral framework below it, suggesting a high degree of resilience in how framework-dwelling fauna respond to coral mortality. These data support the assertion that artificial reefs are capable of facilitating the accumulation of a diverse cryptic community, independent of live coral, provided they contain suitably porous crypts

Cumulative human impacts in the Bering Strait Region

<p><b>Introduction:</b>Human impacts on Arctic marine ecosystems are increasing in extent and intensity as sea ice shrinks and utilization of marine resources expands. The effects of climate change are being felt across the arctic while stressors such as commercial fishing and shipping continue to grow as the Arctic becomes more accessible. Given these emerging changes, there is need for an assessment of the current cumulative impact of human activities to better anticipate and manage for a changing Arctic. Cumulative human impacts (CHI) assessments have been widely applied around the world in a variety of ecosystem types but have yet to incorporate temporal dynamics of individual stressors. Such dynamics are fundamental to Arctic ecosystems.</p> <p><b>Outcomes:</b>Here, we present the first CHI assessment of an Arctic ecosystem to incorporate sea ice as a habitat and assess impact seasonality, using the Bering Strait Region (BSR) as a case study. We find that cumulative impacts differ seasonally, with lower impacts in winter and higher impacts in summer months. Large portions of the BSR have significantly different impacts within each season when compared to a mean annual cumulative impact map. Cumulative impacts also have great spatial variability, with Russian waters between 2.38 and 3.63 times as impacted as US waters.</p> <p><b>Conclusion:</b>This assessment of seasonal and spatial cumulative impacts provides an understanding of the current reality in the BSR and can be used to support development and evaluation of future management scenarios that address expected impacts from climate change and increasing interest in the Arctic.</p

A global survey of “TURF-reserves”, Territorial Use Rights for Fisheries coupled with marine reserves

Overfishing and degradation of the marine environment continue to plague coastal communities worldwide, with multiple diverse solutions being proposed. Territorial Use Rights for Fisheries (TURFs) is a fishery management approach that aligns fishers’ incentives with sustainability, while marine reserves have proven effective for ecosystem protection, and in some cases for fishery enhancement. These two management approaches are often used in isolation, leaving the potential utility of integrating them poorly understood. We examine cases where TURFs and marine reserves have been implemented together to create “TURF-reserves”. We compiled a database of 27 TURF-reserves and collected information on the governance, management, enforcement, fishing practices, fishing rights, regulations, and design attributes for each site. We address several research questions including: what species are managed with TURF-reserves, how are TURF-reserves created and who is involved in the process? Our findings show that the majority of surveyed TURF-reserves arose from previously established TURF systems that target a range of fisheries, and multiple entities play a role in TURF-reserve development and management. We also examine the differences between two TURF-reserve archetypes and find that those developed with a strong history of customary tenure share distinct qualities from those created in a more recently established, government-mandated system. Keywords: TURF, Marine reserve, TURF-reserve, Fisheries, Rights-based managemen

Aligning marine species range data to better serve science and conservation

<div><p>Species distribution data provide the foundation for a wide range of ecological research studies and conservation management decisions. Two major efforts to provide marine species distributions at a global scale are the International Union for Conservation of Nature (IUCN), which provides expert-generated range maps that outline the complete extent of a species' distribution; and AquaMaps, which provides model-generated species distribution maps that predict areas occupied by the species. Together these databases represent 24,586 species (93.1% within AquaMaps, 16.4% within IUCN), with only 2,330 shared species. Differences in intent and methodology can result in very different predictions of species distributions, which bear important implications for scientists and decision makers who rely upon these datasets when conducting research or informing conservation policy and management actions. Comparing distributions for the small subset of species with maps in both datasets, we found that AquaMaps and IUCN range maps show strong agreement for many well-studied species, but our analysis highlights several key examples in which introduced errors drive differences in predicted species ranges. In particular, we find that IUCN maps greatly overpredict coral presence into unsuitably deep waters, and we show that some AquaMaps computer-generated default maps (only 5.7% of which have been reviewed by experts) can produce odd discontinuities at the extremes of a species’ predicted range. We illustrate the scientific and management implications of these tradeoffs by repeating a global analysis of gaps in coverage of marine protected areas, and find significantly different results depending on how the two datasets are used. By highlighting tradeoffs between the two datasets, we hope to encourage increased collaboration between taxa experts and large scale species distribution modeling efforts to further improve these foundational datasets, helping to better inform science and policy recommendations around understanding, managing, and protecting marine biodiversity.</p></div

Recent pace of change in human impact on the world's ocean.

Humans interact with the oceans in diverse and profound ways. The scope, magnitude, footprint and ultimate cumulative impacts of human activities can threaten ocean ecosystems and have changed over time, resulting in new challenges and threats to marine ecosystems. A fundamental gap in understanding how humanity is affecting the oceans is our limited knowledge about the pace of change in cumulative impact on ocean ecosystems from expanding human activities - and the patterns, locations and drivers of most significant change. To help address this, we combined high resolution, annual data on the intensity of 14 human stressors and their impact on 21 marine ecosystems over 11 years (2003-2013) to assess pace of change in cumulative impacts on global oceans, where and how much that pace differs across the ocean, and which stressors and their impacts contribute most to those changes. We found that most of the ocean (59%) is experiencing significantly increasing cumulative impact, in particular due to climate change but also from fishing, land-based pollution and shipping. Nearly all countries saw increases in cumulative impacts in their coastal waters, as did all ecosystems, with coral reefs, seagrasses and mangroves at most risk. Mitigation of stressors most contributing to increases in overall cumulative impacts is urgently needed to sustain healthy oceans

MPA gap analysis results based upon alternate choices of datasets.

<p>Percent of species range covered by MPAs based upon methods in Klein et al. (2015). Scenario 1 replicates the original results, measuring protected range of species in AquaMaps version 08/2013 dataset, with a 50% presence threshold, against the 2014 World Database of Protected Areas, filtered for IUCN categories I-IV that overlap marine areas. Scenario 2 updates the results using AquaMaps version 08/2015, showing very small changes despite the inclusion of an additional 5,545 species. Scenario 3, still using 2015 AquaMaps data, drops the presence threshold to zero, showing an expected decrease in gap species, but also a decrease in species with 5% or greater protected range. Scenario 4 examines species MPA coverage using only the IUCN dataset.</p

Effect of FAO Major Fishing Area constraints on AquaMaps distributions.

<p>(A) AquaMaps species distribution of <i>Hoplichthys regani</i>, the ghost flathead, with known occurrence records. (B) Aggregated AquaMaps predicted ranges for 3,208 species whose equatorial distribution encounters an eastern discontinuity exactly at 175° W, the boundary between FAO Major Fishing Areas 71 and 77 (shown in blue). Other FAO area boundaries create additional clear discontinuities.</p

Comparison of alignment between AquaMaps and IUCN range data.

<p>(A) Distribution alignment (overlap of smaller range within larger) versus area ratio (the ratio of smaller range area to the larger range area) for 2,330 species included in both IUCN and AquaMaps datasets. The upper right quadrant comprises species whose maps largely agree in both spatial distribution and the extent of described ranges (n = 522; 22.4% of paired map species). The upper left quadrant comprises species whose maps agree well in distribution, but disagree in area (n = 715; 30.7%). The lower right quadrant includes species for which the paired maps generally agree in range area, but disagree on where those ranges occur (n = 649; 27.9%). The lower left quadrant indicates species for which the map pairs agree poorly in both area and distribution (n = 444; 19.1%). (B) Alignment quadrant breakdown of species by taxonomic group.</p