Demersal fish biomass declines with temperature across productive shelf seas

Aim: Theory predicts fish community biomass to decline with increasing temperature due to higher metabolic losses resulting in less efficient energy transfer in warm-water food webs. However, whether these metabolic predictions explain observed macroecological patterns in fish community biomass is virtually unknown. Here, we test these predictions by examining the variation in demersal fish biomass across productive shelf regions. Location: Twenty one continental shelf regions in the North Atlantic and Northeast Pacific. Time Period: 1980-2015. Methods: We compiled high-resolution bottom trawl survey data of fish biomass containing 166,000 unique tows and corrected biomass for differences in sampling area and trawl gear catchability. We examined whether relationships between net primary production and demersal fish community biomass are mediated by temperature, food-web structure and the level of fishing exploitation, as well as the choice of spatial scale of the analysis. Subsequently, we examined if temperature explains regional changes in fish biomass over time under recent warming. Results: We find that biomass per km2 varies 40-fold across regions and is highest in cold waters and areas with low fishing exploitation. We find no evidence that temperature change has impacted biomass within marine regions over the time period considered. The biomass variation is best explained by an elementary trophodynamic model that accounts for temperature-dependent trophic efficiency. Main Conclusions: Our study supports the hypothesis that temperature is a main driver of large-scale cross-regional variation in fish community biomass. The cross-regional pattern suggests that long-term impacts of warming will be negative on biomass. These results provide an empirical basis for predicting future changes in fish community biomass and its associated services for human wellbeing that is food provisioning, under global climate change

Programmable Ligand Detection System in Plants through a Synthetic Signal Transduction Pathway

There is an unmet need to monitor human and natural environments for substances that are intentionally or unintentionally introduced. A long-sought goal is to adapt plants to sense and respond to specific substances for use as environmental monitors. Computationally re-designed periplasmic binding proteins (PBPs) provide a means to design highly sensitive and specific ligand sensing capabilities in receptors. Input from these proteins can be linked to gene expression through histidine kinase (HK) mediated signaling. Components of HK signaling systems are evolutionarily conserved between bacteria and plants. We previously reported that in response to cytokinin-mediated HK activation in plants, the bacterial response regulator PhoB translocates to the nucleus and activates transcription. Also, we previously described a plant visual response system, the de-greening circuit, a threshold sensitive reporter system that produces a visual response which is remotely detectable and quantifiable.We describe assembly and function of a complete synthetic signal transduction pathway in plants that links input from computationally re-designed PBPs to a visual response. To sense extracellular ligands, we targeted the computational re-designed PBPs to the apoplast. PBPs bind the ligand and develop affinity for the extracellular domain of a chemotactic protein, Trg. We experimentally developed Trg fusions proteins, which bind the ligand-PBP complex, and activate intracellular PhoR, the HK cognate of PhoB. We then adapted Trg-PhoR fusions for function in plants showing that in the presence of an external ligand PhoB translocates to the nucleus and activates transcription. We linked this input to the de-greening circuit creating a detector plant.Our system is modular and PBPs can theoretically be designed to bind most small molecules. Hence our system, with improvements, may allow plants to serve as a simple and inexpensive means to monitor human surroundings for substances such as pollutants, explosives, or chemical agents

Scenario set-up and forcing data for impact model evaluation and impact attribution within the third round of the Inter-Sectoral Model Intercomparison Project (ISIMIP3a)

This paper describes the rationale and the protocol of the first component of the third simulation round of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a, www.isimip.org) and the associated set of climate-related and direct human forcing data (CRF and DHF, respectively). The observation-based climate-related forcings for the first time include high-resolution observational climate forcings derived by orographic downscaling, monthly to hourly coastal water levels, and wind fields associated with historical tropical cyclones. The DHFs include land use patterns, population densities, information about water and agricultural management, and fishing intensities. The ISIMIP3a impact model simulations driven by these observation-based climate-related and direct human forcings are designed to test to what degree the impact models can explain observed changes in natural and human systems. In a second set of ISIMIP3a experiments the participating impact models are forced by the same DHFs but a counterfactual set of atmospheric forcings and coastal water levels where observed trends have been removed. These experiments are designed to allow for the attribution of observed changes in natural, human and managed systems to climate change, rising CH4 and CO2 concentrations, and sea level rise according to the definition of the Working Group II contribution to the IPCC AR6

Bottom-up drivers of global patterns of demersal, forage, and pelagic fishes

Large-scale spatial heterogeneity in fisheries production is predominantly controlled by the availability of zooplankton and benthic organisms, which have a complex relationship with primary production. To investigate how cross-ecosystem differences in these drivers determine fish assemblages and productivity, we constructed a spatially explicit mechanistic model of three fish functional types: forage, large pelagic, and demersal fishes. The model is based on allometric scaling principles, includes basic life cycle transitions, and has trophic interactions between the fishes and with their pelagic and benthic food resources. The model was applied to the global ocean, with plankton food web estimates and ocean conditions from a high-resolution earth system model. Further, a simple representation of fishing was included, and led to moderate matches with total, large pelagic, and demersal catches, including re-creation of observed variations in fish catch spanning two orders of magnitude. Our results highlight several ecologically meaningful model sensitivities. First, coexistence between forage and large pelagic fish in productive regions occurred when forage fish survival is promoted via both favorable metabolic allometry and enhanced predator avoidance in adult forage fish. Second, the prominence of demersal fish is highly sensitive to the efficiency of energy transfer to benthic invertebrates. Third, the latitudinal distribution of the total catch is modulated by the temperature dependence of metabolic rates, with increased sensitivity pushing fish biomass toward the poles. Fourth, forage fish biomass is suppressed by strong top-down controls on temperate and subpolar shelves, where mixed assemblages of large pelagic and demersal fishes exerted high predation rates. Last, spatial differences in the dominance of large pelagics vs. demersals is strongly related to the ratio of pelagic zooplankton production to benthic production. We discuss the potential linkages between model misfits and unresolved processes including movement, spawning phenology, seabird and marine mammal predators, and socioeconomically driven fishing pressure, which are identified as priorities for future model development. Ultimately, the model and analyses herein are intended as a baseline for a robust, mechanistic tool to understand, quantify, and predict global fish biomass and yield, now and in a future dominated by climate change and improved fishing technology

Skillful multiyear prediction of marine habitat shifts jointly constrained by ocean temperature and dissolved oxygen

Abstract The ability to anticipate marine habitat shifts responding to climate variability has high scientific and socioeconomic value. Here we quantify interannual-to-decadal predictability of habitat shifts by combining trait-based aerobic habitat constraints with a suite of initialized retrospective Earth System Model forecasts, for diverse marine ecotypes in the North American Large Marine Ecosystems. We find that aerobic habitat viability, defined by joint constraints of temperature and oxygen on organismal energy balance, is potentially predictable in the upper-600 m ocean, showing a substantial improvement over a simple persistence forecast. The skillful multiyear predictability is dominated by the oxygen component in most ecosystems, yielding higher predictability than previously estimated based on temperature alone. Notable predictability differences exist among ecotypes differing in temperature sensitivity of hypoxia vulnerability, especially along the northeast coast with predictability timescale ranging from 2 to 10 years. This tool will be critical in predicting marine habitat shifts in face of a changing climate