Description: Field studies are essential to reliably quantify ecological responses to global change because they are exposed to realistic climate manipulations. Yet such studies are limited in replicates, resulting in less power and, therefore, potentially unreliable effect estimates. Furthermore, while manipulative field experiments are assumed to be more powerful than non-manipulative observations, it has rarely been scrutinized using extensive data. Here, using 3847 field experiments that were designed to estimate the effect of environmental stressors on ecosystems, we systematically quantified their statistical power and magnitude (Type M) and sign (Type S) errors. Our investigations focused upon the reliability of field experiments to assess the effect of stressors on both ecosystem's response magnitude and variability. When controlling for publication bias, single experiments were underpowered to detect response magnitude (median power: 18%–38% depending on effect sizes). Single experiments also had much lower power to detect response variability (6%–12% depending on effect sizes) than response magnitude. Such underpowered studies could exaggerate estimates of response magnitude by 2–3 times (Type M errors) and variability by 4–10 times. Type S errors were comparatively rare. These observations indicate that low power, coupled with publication bias, inflates the estimates of anthropogenic impacts. Importantly, we found that meta-analyses largely mitigated the issues of low power and exaggerated effect size estimates. Rather surprisingly, manipulative experiments and non-manipulative observations had very similar results in terms of their power, Type M and S errors. Therefore, the previous assumption about the superiority of manipulative experiments in terms of power is overstated. These results call for highly powered field studies to reliably inform theory building and policymaking, via more collaboration and team science, and large-scale ecosystem facilities. Future studies also require transparent reporting and open science practices to approach reproducible and reliable empirical work and evidence synthesis.

Description: The ongoing development of the Global Carbon Project (GCP) global methane (CH4) budget shows a continuation of increasing CH4 emissions and CH4 accumulation in the atmosphere during 2000–2017. Here, we decompose the global budget into 19 regions (18 land and 1 oceanic) and five key source sectors to spatially attribute the observed global trends. A comparison of top-down (TD) (atmospheric and transport model-based) and bottom-up (BU) (inventory- and process model-based) CH4 emission estimates demonstrates robust temporal trends with CH4 emissions increasing in 16 of the 19 regions. Five regions—China, Southeast Asia, USA, South Asia, and Brazil—account for 〉40% of the global total emissions (their anthropogenic and natural sources together totaling 〉270 Tg CH4 yr−1 in 2008–2017). Two of these regions, China and South Asia, emit predominantly anthropogenic emissions (〉75%) and together emit more than 25% of global anthropogenic emissions. China and the Middle East show the largest increases in total emission rates over the 2000 to 2017 period with regional emissions increasing by 〉20%. In contrast, Europe and Korea and Japan show a steady decline in CH4 emission rates, with total emissions decreasing by ~10% between 2000 and 2017. Coal mining, waste (predominantly solid waste disposal) and livestock (especially enteric fermentation) are dominant drivers of observed emissions increases while declines appear driven by a combination of waste and fossil emission reductions. As such, together these sectors present the greatest risks of further increasing the atmospheric CH4 burden and the greatest opportunities for greenhouse gas abatement.

Description: Ocean warming and species exploitation have already caused large‐scale reorganization of biological communities across the world. Accurate projections of future biodiversity change require a comprehensive understanding of how entire communities respond to global change. We combined a time‐dynamic integrated food web modeling approach (Ecosim) with previous data from community‐level mesocosm experiments to determine the independent and combined effects of ocean warming, ocean acidification and fisheries exploitation on a well‐managed temperate coastal ecosystem. The mesocosm parameters enabled important physiological and behavioral responses to climate stressors to be projected for trophic levels ranging from primary producers to top predators, including sharks. Through model simulations, we show that under sustainable rates of fisheries exploitation, near‐future warming or ocean acidification in isolation could benefit species biomass at higher trophic levels (e.g., mammals, birds, and demersal finfish) in their current climate ranges, with the exception of small pelagic fishes. However, under warming and acidification combined, biomass increases at higher trophic levels will be lower or absent, while in the longer term reduced productivity of prey species is unlikely to support the increased biomass at the top of the food web. We also show that increases in exploitation will suppress any positive effects of human‐driven climate change, causing individual species biomass to decrease at higher trophic levels. Nevertheless, total future potential biomass of some fisheries species in temperate areas might remain high, particularly under acidification, because unharvested opportunistic species will likely benefit from decreased competition and show an increase in biomass. Ecological indicators of species composition such as the Shannon diversity index decline under all climate change scenarios, suggesting a trade‐off between biomass gain and functional diversity. By coupling parameters from multilevel mesocosm food web experiments with dynamic food web models, we were able to simulate the generative mechanisms that drive complex responses of temperate marine ecosystems to global change. This approach, which blends theory with experimental data, provides new prospects for forecasting climate‐driven biodiversity change and its effects on ecosystem processes.

Description: 〈jats:p〉Anthropogenic climate change is altering global biogeographical patterns. However, it remains difficult to quantify how bioregions are changing because pre‐industrial records of species distributions are rare. Marine microfossils, such as planktonic foraminifera, are preserved in seafloor sediments and allow the quantification of bioregions in the past. Using a recently compiled data set of pre‐industrial species composition of planktonic foraminifera in 3802 worldwide seafloor sediments, we employed multivariate and statistical model‐based approaches to study spatial turnover in order to 1) quantify planktonic foraminifera bioregions and 2) understand the environmental drivers of species turnover. Four latitudinally banded bioregions emerge from the global assemblage data. The polar and temperate bioregions are bi‐hemispheric, supporting the idea that planktonic foraminifera species are not limited by dispersal. The equatorial bioregion shows complex longitudinal patterns and overlaps in sea surface temperature (SST) range with the tropical bioregion. Compositional‐turnover models (Bayesian bootstrap generalised dissimilarity models) identify SST as the strongest driver of species turnover. The turnover rate is constant across most of the SST gradient, showing no SST threshold values with rapid shifts in species composition, but decelerates above 25°C, suggesting SST is less predictive of species composition in warmer waters. Other environmental predictors affect species turnover non‐linearly, and their importance differs across regions. In the Pacific ocean, net primary productivity below 500 mgC m〈jats:sup〉−2〈/jats:sup〉 day〈jats:sup〉−1〈/jats:sup〉 drives fast compositional change. Water depth values below 3000 m (which affect calcareous microfossil preservation) increasingly drive changes in species composition among death assemblages in the Pacific and Indian oceans. Together, our results suggest that the dynamics of planktonic foraminifera bioregions are expected to be highly responsive to climate change; however, at lower latitudes, environmental drivers other than SST may affect these dynamics.〈/jats:p〉

Description: Aim: The distribution of mesoplankton communities has been poorly studied at global scale, especially from in situ instruments. This study aims to (1) describe the global distribution of mesoplankton communities in relation to their environment and (2) as-sess the ability of various environmental- based ocean regionalizations to explain the distribution of these communities. Location: Global ocean, 0–500 m depth. Time Period: 2008–2019. Major Taxa Studied: Twenty-eight groups of large mesoplanktonic and macroplank-tonic organisms, covering Metazoa, Rhizaria and Cyanobacteria. Methods: From a global data set of 2500 vertical profiles making use of the Underwater Vision Profiler 5 (UVP5), an in situ imaging instrument, we studied the global distribu-tion of large (〉600 μm) mesoplanktonic organisms. Among the 6.8 million imaged ob-jects, 330,000 were large zooplanktonic organisms and phytoplankton colonies, the rest consisting of marine snow particles. Multivariate ordination (PCA) and clustering were used to describe patterns in community composition, while comparison with existing regionalizations was performed with regression methods (RDA). Results: Within the observed size range, epipelagic plankton communities were Trichodesmium- enriched in the intertropical Atlantic, Copepoda- enriched at high latitudes and in upwelling areas, and Rhizaria-enriched in oligotrophic areas. In the mesopelagic layer, Copepoda-enriched communities were also found at high lati-tudes and in the Atlantic Ocean, while Rhizaria-enriched communities prevailed in the Peruvian upwelling system and a few mixed communities were found elsewhere. The comparison between the distribution of these communities and a set of existing regionalizations of the ocean suggested that the structure of plankton communities described above is mostly driven by basin- level environmental conditions. Main Conclusions: In both layers, three types of plankton communities emerged and seemed to be mostly driven by regional environmental conditions. This work sheds light on the role not only of metazoans, but also of unexpected large protists and cy-anobacteria in structuring large mesoplankton communities.

Description: Marine life is controlled by multiple physical and chemical drivers and by diverse ecological processes. Many of these oceanic properties are being altered by climate change and other anthropogenic pressures. Hence, identifying the influences of multifaceted ocean change, from local to global scales, is a complex task. To guide policy-making and make projections of the future of the marine biosphere, it is essential to understand biological responses at physiological, evolutionary and ecological levels. Here, we contrast and compare different approaches to multiple driver experiments that aim to elucidate biological responses to a complex matrix of ocean global change. We present the benefits and the challenges of each approach with a focus on marine research, and guidelines to navigate through these different categories to help identify strategies that might best address research questions in fundamental physiology, experimental evolutionary biology and community ecology. Our review reveals that the field of multiple driver research is being pulled in complementary directions: the need for reductionist approaches to obtain process-oriented, mechanistic understanding and a requirement to quantify responses to projected future scenarios of ocean change. We conclude the review with recommendations on how best to align different experimental approaches to contribute fundamental information needed for science-based policy formulation.

Description: Aim: The distribution of mesoplankton communities has been poorly studied at global scale, especially from in situ instruments. This study aims to (1) describe the global distribution of mesoplankton communities in relation to their environment and (2) assess the ability of various environmental-based ocean regionalizations to explain the distribution of these communities. Location: Global ocean, 0–500 m depth. Time Period: 2008–2019. Major Taxa Studied: Twenty-eight groups of large mesoplanktonic and macroplanktonic organisms, covering Metazoa, Rhizaria and Cyanobacteria. Methods: From a global data set of 2500 vertical profiles making use of the Underwater Vision Profiler 5 (UVP5), an in situ imaging instrument, we studied the global distribution of large (〉600 μm) mesoplanktonic organisms. Among the 6.8 million imaged objects, 330,000 were large zooplanktonic organisms and phytoplankton colonies, the rest consisting of marine snow particles. Multivariate ordination (PCA) and clustering were used to describe patterns in community composition, while comparison with existing regionalizations was performed with regression methods (RDA). Results: Within the observed size range, epipelagic plankton communities were Trichodesmium-enriched in the intertropical Atlantic, Copepoda-enriched at high latitudes and in upwelling areas, and Rhizaria-enriched in oligotrophic areas. In the mesopelagic layer, Copepoda-enriched communities were also found at high latitudes and in the Atlantic Ocean, while Rhizaria-enriched communities prevailed in the Peruvian upwelling system and a few mixed communities were found elsewhere. The comparison between the distribution of these communities and a set of existing regionalizations of the ocean suggested that the structure of plankton communities described above is mostly driven by basin-level environmental conditions. Main Conclusions: In both layers, three types of plankton communities emerged and seemed to be mostly driven by regional environmental conditions. This work sheds light on the role not only of metazoans, but also of unexpected large protists and cyanobacteria in structuring large mesoplankton communities.

Description: This article presents risk factors that are associated with the handling of unexploded ordnance (UXO) during explosive ordnance disposal (EOD) operations in German waters. The construction of offshore wind parks and the German immediate action program are expected to increase the number of EOD operations. Existing literature and guidelines do not offer a structured and reproducible framework for assessing EOD risk. To fill this gap, a network of EOD risk factors was developed by means of a literature review and validation via expert consultation. The study was scoped to “personnel and equipment at the EOD location” as the risk receptor and “undesired detonation” as the undesired event under investigation. Factors are subdivided into UXO factors that depend on the object that should be handled and factors that describe the object's surrounding environment. While the former can be researched by an EOD expert, the latter must be measured on site or acquired from a model. Each of these factors contributes to risk, some directly and others indirectly via other factors. The complexity of the resulting network, with its 33 factors, demonstrates the need for a reliable and reproducible model to quantify EOD risk. Its purpose is not to replace EOD experts but to aid them in their decision‐making process. Such a tool can provide valuable support for the high‐cost and high‐risk EOD operations.

Description: The deep-sea is vast, remote, and largely underexplored. However, methodological advances in environmental DNA (eDNA) surveys could aid in the exploration efforts, such as using sponges as natural eDNA filters for studying fish biodiversity. In this study, we analyzed the eDNA from 116 sponge tissue samples and compared these to 18 water eDNA samples and visual surveys obtained on an Arctic seamount. Across survey methods, we revealed approximately 30% of the species presumed to inhabit this area and 11 fish species were detected via sponge derived eDNA alone. These included commercially important fish such as the Greenland halibut and Atlantic mackerel. Fish eDNA detection was highly variable across sponge samples. Highest detection rates were found in sponges with low microbial activity such as those from the class Hexactinellida. The different survey methods also detected alternate fish communities, highlighted by only one species overlap between the visual surveys and the sponge eDNA samples. Therefore, we conclude that sponge eDNA can be a useful tool for surveying deep-sea demersal fish communities and it synergises with visual surveys improving overall biodiversity assessments. Datasets such as this can form comprehensive baselines on fish biodiversity across seamounts, which in turn can inform marine management and conservation practices in the regions where such surveys are undertaken.